More Than 600 Illustrations of Critical
Thinking
How to Mislead With Statistics: Let
Me Illustrate the Ways
Bob Jensen
at Trinity University
Concept Knowledge and Critical Thinking Should Be a Major
Mission of Education ---
http://faculty.trinity.edu/rjensen/assess.htm#ConceptKnowledge
Bob Jensen's threads on Data Visualization ---
http://faculty.trinity.edu/rjensen/352wpvisual/000datavisualization.htm
Animated Visualization of the United States’ Exploding Population Growth
Over 200 Years (1790 – 2010) ---
A Visualization of the United States’ Exploding Population Growth Over 200 Years
(1790 – 2010)
USA Debt Clock
--- http://www.usdebtclock.org/ ubl
In September 2017 the USA National Debt exceeded $20 trillion for the first time
---
http://www.statedatalab.org/news/detail/national-debt-surpasses-20-trillion-for-the-first-time-in-us-history
Human Population Over Time on Earth ---
https://www.youtube.com/watch?v=PUwmA3Q0_OE
What are the most important statistical ideas of the past 50 years? ---
https://marginalrevolution.com/marginalrevolution/2021/02/what-are-the-most-important-statistical-ideas-of-the-past-50-years.html
Table of Contents (some modules are listed in more than one
category)
Statistical Fallacies
Big Deal Issues Important for Students to Debate
(including research replication and analysis bias)
Misleading Distortions (including cherry
picking and outliers and
denominator effects in proportions, intensity issues, misuse of the word
"proved," lack of robustness, and faked data)
Incomplete Analysis (including
failure to report variances and skewness (kutosis), black swans, and
unwarranted extrapolations)
Associating Cause With Correlation
Misleading Definitions and Assumptions
(including misleading survey questions and false assumptions of stationarity, robustness,
externalities, and misleading extrapolations)
Small, Large or Otherwise Misleading Samples
(including sampling bias, non-stationarity, misleading statistical inference
for large samples)
Missing Variables and Data
Misleading Rankings
Misleading With Wikipedia
**How to Mislead With Statistics
Statistical Fallacies ---
https://www.geckoboard.com/best-practice/statistical-fallacies/
**How to Mislead With Statistics
We think linearly, in terms of cause and effect, but the fact is that we live
in a complex system – a system with many interacting agents, whose collective
behaviour is usually hard to predict ---
https://aeon.co/essays/complex-systems-science-allows-us-to-see-new-paths-forward
How to Try Not to Mislead With Statistics
And The Award For Worst Career After An Oscar Win Goes To ---
http://fivethirtyeight.com/features/and-the-award-for-worst-career-after-an-oscar-win-goes-to/
Jensen Comment
This is an interesting article from the standpoint of going to considerable
lengths to avoid misleading statistics.
The Data Detective: Ten Easy Rules to Make Sense of Statistics ---
https://marginalrevolution.com/marginalrevolution/2021/01/the-data-detective-ten-easy-rules-to-make-sense-of-statistics.html
Also see
https://www.amazon.com/Data-Detective-Rules-Sense-Statistics/dp/0593084594/ref=sr_1_2?crid=28EG2H6C3ODWZ&dchild=1&keywords=tim+harford&qid=1610924306&s=books&sprefix=Tim+Har%2Caps%2C191&sr=1-2
**How to Mislead With Statistics
Paradoxes of Probability & Statistical Strangeness
https://scitechdaily.com/paradoxes-of-probability-statistical-strangeness/?fbclid=IwAR3JlsjucUeAQg8LeYTFvSoGJcFWpovSvr3gnB4CM99Ekihr-_FTuXlTQOo
Thank you Jagdish Gangolly for the heads up
Simpson's Paradox
Base Rate Fallacy
Will Rogers Paradox
Berkson's Paradox
Multiple Comparisons Fallacy
Which economic methods are
in practice statistically more honest than others?
https://marginalrevolution.com/marginalrevolution/2020/09/which-economic-methods-are-in-practice-statistically-more-honest-than-others.html
… our
results suggest that the [instrumental variables] and, to a lesser extent,
[difference-in-difference] research bodies have substantially more p-hacking
and/or selective publication than those based on [randomized controlled
trials] and [regression-discontinuity]…
How to Be a Statistical
Detective: You Do Not Have to Be a Statistics Expert ---
https://onlinelibrary.wiley.com/doi/abs/10.1002/pmrj.12305
Jensen Comment
Although you don't have to be a statistics expert, you do have to know something
about definitions and underlying assumptions. One of the most important thing to
be aware of is the concept of "robustness" ---
https://en.wikipedia.org/wiki/Robust_statistics
Robustness often deals with the relevance of a finding in terms of its
underlying assumptions. Robust findings usually allow for rather generous
violations of underlying assumptions. For example, capital markets studies in
finance often assume markets are efficient in terms of impounding events
instantly into price changes. Markets are almost never perfectly efficient, but
some capital markets studies are more robust than others in terms of how the
findings hold up in terms of market inefficiencies.
Another statistical assumption
that is often violated in randomness. For example, does every member of a
statistical population have an equal chance of being selected in a sample. The
classical example of violations of randomness is in opinion polling where
something prevents random selection. When teaching sampling a common example is
the political polling by by telephone in the days when a lot of voters did not
have telephones ---
https://en.wikipedia.org/wiki/Opinion_poll
Another thing to be keenly
aware of is how outliers might impact findings. For example outliers can impact
both reporting of means and medians, but medians are often less sensitive to a
small number of outliers. Modes are not sensitive to outliers, but they have
severe problems as measures of central tendency such as when distributions are
bimodal.
The main problem I find in
reporting statistical findings is failure to report distributional outcomes such
as when means are reported without graphical displays of the distributions of
outcomes. For example, when reporting average (mean or median) salaries of
college graduates the distributions are often very skewed by having a rather
large number of graduates who choose not earn any salary or a very low part-time
salary because of becoming new parents or choosing to take some time off from
working after graduation. Also some people fall into abnormally high salaries
after graduating such as graduates who become instant CEOs in a family business.
Over 500 Examples of Critical Thinking and Illustrations of How to Mislead
With Statistics ---
See below
Statistical Fallacies ---
https://www.geckoboard.com/best-practice/statistical-fallacies/
Tim Harford: How to Make the World Add Up
Ten Rules for Thinking Differently About Numbers
https://www.amazon.com/How-Make-World-Add-Up/dp/1408712237/ref=sr_1_1?dchild=1&keywords=how+to+make+the+world+add+up&qid=1600435042&sr=8-1/marginalrevol-20
The Argumentation Toolkit (evidence in science) ---
www.argumentationtoolkit.org
**How to Mislead Without Evidence
Michael Bloomberg's Claim About 'Children'
Killed by 'Gun Violence' Is Off by 73% ---
https://reason.com/2020/02/02/michael-bloombergs-claim-about-children-killed-by-gun-violence-is-off-by-73/
It appears that Bloomberg's claim is an outright lie.
**How to Mislead With Statistics:
'Big 4' salaries, revealed: How much Deloitte, KPMG, EY, and PwC
accountants and consultants make, from entry level to executive roles ---
https://www.businessinsider.com/salary-of-consultants-accountants-big-4-deloitte-kpmg-ey-pwc-2020-7?nr_email_referer=1&utm_source=Sailthru&utm_medium=email&utm_content=Business_Insider_select&pt=385758&ct=Sailthru_BI_Newsletters&mt=8&utm_campaign=Insider%20Select%202021-01-06&utm_term=INSIDER%20SELECT%20-%20ENGAGED%2C%20ACTIVE%2C%20PASSIVE%2C%20DISENGAGED%2C%20NEW
-
In 2019, the so called
"Big Four" accounting firms — PricewaterhouseCoopers (PwC), KPMG,
Ernst & Young (EY), and Deloitte — employed well
over a million people.
-
These firms are known
for paying employees six-figure salaries right out of business
school.
-
To figure out how much
accountants and consultants make at these firms, Business Insider
analyzed the US
Office of Foreign Labor Certification's 2020 disclosure data for
permanent and temporary foreign workers.
-
For example, some
analysts and auditors made more than $120,000 at Ernst & Young (EY),
principals were given up to $950,000 in compensation at KPMG, and
managers at PwC made $123,019 or more.
The so called "Big
Four" accounting firms — PricewaterhouseCoopers (PwC), KPMG, Ernst & Young (EY),
and Deloitte — are known for paying their staff high salaries.
In 2019, the four firms combined employed well
over a million people worldwide. New
hires typically earn six-figure salaries from the get-go. An entry-level
consultant who just graduated from business school can make more
than $200,000 a year at the four firms when
you include base salary, bonuses, and relocation expenses.
The Big Four firms are planning to hire in 2021. A
spokeswoman at PwC previously told Insider that the firm typically brings in
13,000 entry-level and experienced employees on a yearly basis, and its
hiring volume for interns and full-time workers will be similar this year.
Deloitte and EY are both planning to expand
their workforces in India.
Insider analyzed the US
Office of Foreign Labor Certification's 2020 disclosure data for
permanent and temporary foreign workers to find out what PwC, KPMG, EY, and
Deloitte paid employees for jobs ranging from entry-level to executive
roles. The salary data analyzed were based across the US.
We looked through entries specifically for
roles related to management consulting and accounting. Performance bonuses,
signing bonuses, and compensation other than base salaries are not reflected
in this data.
Here's how much PwC, KPMG, EY, and Deloitte
paid their hires last year.
Deloitte is organized
into three main service areas that offer
different salaries. These areas include the human capital division, the
strategy and operations division, and the technology division. Deloitte had
the greatest
number of employees, topping
312,028 in 2019, according
to research platform Statista.
It also applied for the greatest number of
visas compared to other leading consultancies. The company applied for 7,444
visas in the last half of 2019 and the first half of 2020. Deloitte did not
immediately respond to a request for comment on the salary data.
Deloitte delayed many of its full-time hires' start
dates, shortened internship programs for students, and laid off 5,000
US workers and 200
people in Canada in response to the
coronavirus pandemic.
Here are the salary ranges for consulting and
accounting roles:
-
Analyst: $58,261
to $116,500 (includes analysts specialized in business, human capital,
project delivery, and solutions)
-
Consultant:
$91,000 to $122,100
-
Senior consultant: $81,167
to $118,384
-
Manager: $107,640
to $160,480
-
Senior manager: $187,253
-
Consulting managing
director: $191,300
-
Audit and assurance
assistant: $58,822
-
Tax consultant: $47,570
to $55,195
-
Tax senior
manager: $124,909
Continued in article
Jensen Comment
Averages almost always are misleading without knowing standard deviations and
skewness. The most misleading part of this is differences in cost of
living. A $125,000 salary does not go far in San Francisco, London, or anywhere
in Switzerland. It goes quite a ways in Des Moines, San Antonio, and
Tallahassee.
My advice to my graduate students about to go to work full time was to almost
ignore starting salaries and look at the more important aspects of the first
job, including training, type of experiences, direct contact with clients, etc.
Especially important was and still is the type of training and experience. One
of my best graduating students in the specialty of accounting for financial
derivatives and hedging activities went with the Big Four that promised to let
him work mostly for a client in Houston having billions or dollars in derivative
contracts. In short time that student became a genuine expert on FAS 133 and
IFRS 39 to a point that in about six years he took on a new job as a financial
executive with Microsoft. Guess why Microsoft needed him?
One of my students who spoke Russian went with a firm that would send him to
Moscow. By doing so he was offered a partnership in a Big Four firm in what I
consider to almost be record time relative to his classmates that went with the
Big Four in the USA.
Sometimes my students complained that auditing and tax graduates are offered
less from the large accounting firms relative new graduates in engineering. I
consoled them by saying that accounting can often be a faster track to the
executive suite, especially the executive suite in finance and accounting.
Corporations often hire very few, if any, new (entry-level) graduates in
accounting. But they make very good deals with accountants who have become
specialized (think derivatives accounting, insurance accounting, lease
accounting, SEC accounting, etc.) after a few years of working for large
accounting firms.
There's also another aspect of high paying jobs to consider. Consultants in
the Big Four often start at higher salaries, but they are constantly living
under pressures to obtain new clients. Audit and tax clients, on the other hand,
tend to be the same clients year after year. For example, KPMG audited GE for
over 100 years before finally losing GE as an audit client. In comparison, KPMG
consultants had to keep competing for new consulting contracts year after year.
It can be very tedious writing consulting proposals year after year after year.
Another thing to contemplate when offered what seems like a huge starting
salary. The thing to ask is how much of that salary is based upon commissions
that create a lot of tensions on the job, especially when there is stiff
competition coming from other consulting firms writing proposals.
**Now to Mislead
With Statistics
Modeling Skewness Determinants in Accounting Research
SSRN
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3740197
60 Pages Posted:
6 Feb 2021
Temple University - Department of Accounting
Temple University - Fox School of Business and Management - Department of
Accounting
Date Written: November 30, 2020
Abstract
Skewness-based proxies are widely used in accounting and
finance research. To study how the skewness of a dependent variable Y varies
with conditioning variables X, researchers typically compute firm-specific
skewness measures over a short rolling window and regress them on X.
However, we show that this standard approach can cause severe biases and
produce false findings of both conditional skewness on average and
systematic variation in conditional skewness. These biases generalize beyond
rolling-window skewness. We develop alternative methods that address these
biases by directly modeling the conditional skewness of Y for each
observation as a function of X. Simulations confirm that our methods have
good type-I errors and test power even in scenarios in which the standard
method is severely biased. Our methods are transparent, robust, and can be
implemented in a few lines of code. Use of our methods changes a major prior
finding.
Keywords: Pearson’s
moment coefficient of skewness, quantile-based skewness, rolling window,
conditional distribution, generalized method of moments (GMM)
JEL Classification: M41,
C20, C25
Suggested Citation:
**How to Mislead With
Statistics
What Do Happiness Data Mean?
Theory and Survey Evidence—Dan Benjamin, Jakina Debnam Guzman, Marc Fleurbaey,
Ori Heffetz and Miles Kimball ---
https://blog.supplysideliberal.com/post/2021/2/11/what-do-happiness-data-mean-theory-and-survey-evidencedan-benjamin-jakina-debnam-guzman-ori-heffetz-marc-fleurbaey-and-miles-kimb
**How to Mislead With Statistics
Freedom from Fossil Fuels is Good for Your Health ---
https://www.nakedcapitalism.com/2020/02/freedom-from-fossil-fuels-is-good-for-your-health.html
Jensen Comment
This is a very superficial article that mentions many of the benefits of a world
without fossil fuels. It totally ignores the costs and risks. For example, is
starvation good for health? We don't really know how loss of fossil fuels (think
farm machinery) and petrochemicals will affect food production for over seven
billion people worldwide, but there are a huge degrees of agricultural
productivities and efficiencies that might be adversely affected by abrupt shut
down of fossil fuels. Then there's the global distribution of food that
currently relies upon fossil fuels from cargo ships to fleets of trucks between
farms and markets around the world.
Certainly there are positives about eliminating fossil fuels from heating our
homes, cooling our homes, and transporting us to jobs and other places we want
to travel. But are there no negatives in the alternatives to replacing fossil
fuels? For example, there are tremendous environmental problems with all the
battery production needed to accompany solar and wind electricity production.
Petrochemicals are now essential in the production of vital medicines.
Realistically, nuclear energy is about the only known solution to the massive
shortage of power lost with the elimination of fossil fuels. Nuclear energy is
getting safer and more economically feasible, but the cost for seven billion
people on earth will still be tremendous and require great economic sacrifices
on nations trying to do without fossil fuels.
Certainly one day in the future fossil fuels will no longer be necessary (or
even available) for any life that remains on earth. However, articles on ending
reliance upon fossil fuels must consider the advantages and disadvantages of
living without fossil fuels and why it will take so long to do so ---
https://www.bartleby.com/topics/Essay-on-Fossil-Fuels
Certainly our politicians are not doing us big favors by ignoring (think
Trump) the carbonization problem or by making decarbonization political
promises that are absurd.
MIT: Pete Buttigieg’s $2 trillion climate plan is
infeasible, but less so than most ---
https://www.technologyreview.com/s/615265/pete-buttigieg-2-trillion-climate-plan-is-infeasible-but-less-so-than-most/
MIT on Promises That are Literally Impossible to Keep: Elizabeth Warren
has a ($3 trillion) climate change plan ---
https://www.technologyreview.com/s/615212/climate-change-elizabeth-warren-has-a-3-trillion-plan-for-that/
Much depends upon future research discoveries that are hard to predict in terms
of types and timing (think flow batteries) ---
https://www.computerworld.com/article/2918235/can-elon-musks-battery-really-cut-your-power-lines.html
Petrochemicals ---
https://en.wikipedia.org/wiki/Petrochemical
Examples of Petrochemicals and Petroleum Products (think medicines and food)
---
https://www.thoughtco.com/petrochemicals-and-petroleum-products-603558
**How to Mislead With
Statistics
Research: Women Are Better
Leaders During a Crisis ---
https://hbr.org/2020/12/research-women-are-better-leaders-during-a-crisis?utm_medium=email&utm_source=newsletter_weekly&utm_campaign=weeklyhotlist_not_activesubs&deliveryName=DM113092
Jensen Comment
Firstly, I wonder if this study would have been published by Harvard if the data
revealed men are better leaders in a crisis. In this era I doubt it.
Irrespective of how the survey
data turned out, I don't like comparing opinion poll averages of gender
differences in leadership "during a crisis." Crises are highly specific events
in specific circumstances. They vary from such extremes as a local crisis (think
of someone passing out in a presidential cabinet meeting) to very global crisis
(think of missiles sinking of a USA aircraft carrier in the China Sea or Persian
Gulf). I think gender differences are negligible compared with a person's unique
history, training, experience, personality, data understanding, etc. in a
particular crisis at a particular time.
We're not dealing with fungible items in stationary processes with most types of
"crises."
The study is not restricted to
a particular types of crises such as when pilots experience engine failures in
fighter aircraft. The study refers to any type of crisis, and I think the survey
outcomes are garbage with respect to leadership in every type of crisis in every
type of circumstance. There are instances where a particular leader, man or
woman, can step up to the plate like a rather lousy leader in many respects
named Winston Churchill stepped forward marvelously when Hitler was on the verge
of taking over all of Europe.
Of course there are types of
crises were gender might be an important element of leadership, but there are
certainly many other types of crises where gender is probably irrelevant among
all the most important factors affecting great leadership at the moment.
**How to Mislead Without Statistics
With Centuries-Old Techniques, This Farm Is Preparing for the Future No
modern methods or machinery required — just crops cultivated by hand in
incredible, climate-proof quantities ---
https://reasonstobecheerful.world/permaculture-bec-hellouin-farm-france/
. . .
There is no tractor or plow in this place of constant
growth. The farmers do not use fossil fuels, nor artificial fertilizers and
pesticides. The manual work saves costs and reduces their carbon footprint.
But there is also another reason. A tractor designed for modern farming
could not plant more than three rows of carrots on the barely one-meter-wide
strips utilized by this farm. At Bec Hellouin, four times that density of
crops is grown in that amount of soil. “We cultivate radishes, carrots,
lettuce and cabbage in 12 rows on this space,” says Charles.
Continued in article
Jensen Comment
Much can be said for the above ventures into farming on land not amenable to
mechanized large-scale food production. But we should not extrapolate this
article to world production of grains (corn, soybean, and wheat)
production from giant farms in the USA's Midwest or the mechanized vegetable
production in California where my son is connected by marriage to a 5,000 acres
of rice and tomato farm using enormous Caterpillar tractors, giant combines,
etc. Yes you can now plant and harvest rice and tomatoes with robotic tractors,
combines, and trucks. The produce is untouched by human hands. The trucks taking
harvests to processing mills could even be driverless if the laws permitted such
deliveries without drivers.
The modern world with over seven billion hungry people cannot and will not
return to farming without machines --- big and better machines. What the above
article fails to compare is the productivity of our present mechanized farms
with productivity of what they would become today if we banned the machinery and
chemicals of farming. We can now longer
feed the world with hunting, gathering, and non-mechanized organic farms and
food factories.
I'm reminded of the following remarks of Milton Friedman about the lesson of
spoons.
Milton Friedman: The Lesson of the
Spoons ---
https://marginalrevolution.com/marginalrevolution/2019/08/spoons-are-in-aisle-9.html
Chopsticks would be even better than spoons in providing more and more workers
with tools to move the earth.
**How to Mislead With Quotations
College is "not for learning" and "basically
for fun."
Elon Musk
Elon Musk said a college degree isn't required for a job at Tesla —
and Apple, Google, and Netflix don't require employees to have 4-year degrees
either ---
https://www.businessinsider.com/top-companies-are-hiring-more-candidates-without-a-4-year-degree-2019-4?utm_source=Sailthru&utm_medium=email&utm_content=BIPrime_select&utm_campaign=BI%20Prime%202020-03-11&utm_term=BI%20Prime%20Select
Jensen Comment
But what proportion of
professional employees (computer scientists, engineers, accountants, lawyers,
nurses, financial analysts, etc.) have college degrees?
My guess is over
99%.
Some professionals must have college degrees (maybe even advanced
degrees just to be licensed). For example CPAs and lawyers cannot be licensed
without advanced degrees.
Prodigies hired without college degrees are few
and far between, although there are interesting stories about Harvey Firestone,
Bill Gates, and others who became wealthy CEOs without diplomas on the wall. You
don't have to have a diploma to lead a company, but that company is not going to
hire a notable proportion of professionals without college diplomas.
I hate it when Elon Musk encourages students to
party it up in college rather than make the primary goals learning and completion
of one or more degree programs.
**How to Mislead With Statistics (by avoiding key variables)
Are Home Prices in Black Neighborhoods Underpriced? ---
https://www.thestreet.com/mishtalk/economics/are-home-prices-in-black-neighborhoods-underpriced
Jensen Comment
Read the article for examples of how the statistics are misleading in this
study. However, the article misses several main points. Firstly, it does not
mention crime statistics for black neighborhoods. Secondly, it does not mention
that many black neighborhoods like those in Chicago are centers for dangerous
gangs and gang warfare. Thirdly, I don't know how an analyst makes adjustments
for public education troubles and "walkability" troubles for whites in most
black neighborhoods.
And there are some seemingly little things that are not so little in terms of
real estate value. Because many prosecutors are not discouraging shoplifting
crime in low income neighborhoods (think of Los Angeles that no longer
prosecutes teenage misdemeanors) retail businesses like supermarkets and big box
stores are avoiding low income neighborhoods. This in turn, affects real estate
values, since shopping is no longer convenient in those neighborhoods. There are
other inconveniences such as having worse taxi pickup services in high crime
neighborhoods.
From David Giles on Econometrics ---
https://davegiles.blogspot.com/2019/08/book-series-on-statistical-reasoning-in.html
David has retired from updating this wonderful blog
Book
Series on "Statistical Reasoning in Science & Society"
Back in
early 2016, the American
Statistical Association (ASA) made an announcement in
its newsletter, Amstat
News, about the introduction of an important new series of
books. In part, that announcement said:
"The
American Statistical Association recently partnered with Chapman
& Hall/CRC Press to launch a book series called the ASA-CRC Series
on Statistical Reasoning in Science and Society.
'The ASA
is very enthusiastic about this new series,' said 2015 ASA President David
Morganstein, under whose leadership the arrangement was made. 'Our strategic
plan includes increasing the visibility of our profession. One way to do
that is with books that are readable, exciting, and serve a broad audience
having a minimal background in mathematics or statistics.'
The
Chapman & Hall/CRC press release states the book series will do the
following:
·
Highlight the
important role of statistical and probabilistic reasoning in many areas
·
Require minimal
background in mathematics and statistics
·
Serve a broad
audience, including professionals across many fields, the general public,
and students in high schools and colleges
·
Cover statistics in
wide-ranging aspects of professional and everyday life, including the media,
science, health, society, politics, law, education, sports, finance,
climate, and national security
·
Feature short,
inexpensive books of 100–150 pages that can be written and read in a
reasonable amount of time."
Seven
titles have now been published in this series -
Measuring Society,
by Chaitra H. Nagaraja (2019)
Measuring Crime: Behind the Statistics, by Sharon L. Lohr (2019)
Statistics and Health Care Fraud: How to Save Billions, by Tahir Ekin
(2019)
Improving Your NCAA® Bracket with Statistics, by Tom Adams (2018)
Data Visualization: Charts, Maps, and Interactive Graphics, by Robert
Grant (2018)
Visualizing Baseball, by Jim Albert (2017)
Errors, Blunders, and Lies: How to Tell the Difference, by David S.
Salsburg (2017)
Readers
of this blog should be especially interested in Chaitra Nagaraja's recently
published additionto this series. Chaitra devotes
chapters in her book to the topics of Jobs, Inequality, Housing, Prices,
Poverty, and Deprivation. I particularly like the historical perspective
that Chaitra provides in this very readable contribution, and I recommend
her book to you (and your non-economist friends).
Type 1 (Alpha) and Type 2 (Beta) Errors in Statistical Inference ---
https://en.wikipedia.org/wiki/Type_I_and_type_II_errors#Type_II_error
Why is Type 2 error seldom computed in practice?
The probability of a Type II Error cannot generally be computed because it
depends on the population mean which is unknown. It can be computed at, however,
for given values of µ, 2 σ , and n .
https://www.ssc.wisc.edu/~gwallace/PA_818/Resources/Type%20II%20Error%20and%20Power%20Calculations.pdf
Engineers frequently are able to construct Operating Characteristic (C) curves
for routine tests in quality control ---
https://www.businessmanagementideas.com/production-management/operating-characteristic-o-c-curves/6960
Jensen Comment
I don't know of a single accounting research study or auditing firm that has
ever measured Type 2 error other than on hypothetical data. I also have never
heard of a study in economics and finance that measured Type 2 error.
However, when I took Engineering Statistics 100 years ago we derived OC curves
from real world quality control and vehicle traffic data using known means and
variances.
There are numerous tutorials on how to compute Type II error with known means
and variances. One of the more popular is provided by the Khan Academy ---
https://www.khanacademy.org/math/ap-statistics/tests-significance-ap/error-probabilities-power/v/introduction-to-type-i-and-type-ii-errors
**How to Mislead With
Statistics
New York algebra fact of the
day ---
https://marginalrevolution.com/marginalrevolution/2020/06/new-york-fact-of-the-day-2.html
Take
here in New York, where in 2016 the passing rate for the Regents Examination
in Algebra I test was 72 percent. Unfortunately, this (relatively) higher
rate of success does not indicate some sort of revolutionary pedagogy on the
part of New York state educators. As the New York Post complained in 2017,
passing rates were so high in large measure because the cutoff for passing
was absurdly low — so low that students needed only to answer 31.4 percent
of the questions correctly to pass the 2017 exam.
Walter A. Williams: The Nation's Report Card
How are K-12 schools doing under President Trump versus
President Obama?
https://townhall.com/columnists/walterewilliams/2020/05/06/the-nations-report-card-n2568167?utm_source=thdaily&utm_medium=email&utm_campaign=nl&newsletterad=05/06/2020&bcid=b16c6f948f297f77432f990d4411617f&recip=17935167
Jensen's Comment
Most K-12 schools were probably doing better when I was a child than they're
doing today. The downhill slide is greatest in the gang-ridden schools,
drug-infested urban schools like Chicago and New Orleans. Throwing money at such
schools is not the answer until life at home recovers. Finland
knows this, which is why Finland's dads spend more time with school children
than the moms or the teachers.
https://www.theguardian.com/lifeandstyle/2017/dec/04/finland-only-country-world-dad-more-time-kids-moms
The New Yorker: What Statistics Can't Tell Us About Ourselves ---
https://www.newyorker.com/magazine/2019/09/09/what-statistics-can-and-cant-tell-us-about-ourselves
Thank you Denny Beresford for the heads up!
If the end brings me out all right, what is said
against me won’t amount to anything. If the end brings me out wrong, ten angels
swearing I was right would make no difference.
Lincoln on How to Handle Criticism ---
https://www.brainpickings.org/2019/03/27/abraham-lincoln-criticism/?mc_cid=855d203b71&mc_eid=4d2bd13843
Skepticism 101 ---
http://www.skeptic.com/skepticism-101
**How to Mislead With Statistics (spurious
correlations) ---
https://reason.com/archives/2015/12/04/did-california-prop-47-cause-state-crime
Unprofessional
Journalism: The Mueller Report ---
https://twitter.com/moorehn/status/1154558852043591681
How to Mislead With Statistics
Anaesthetist John Carlisle has spotted problems in hundreds of research papers —
and spurred a leading medical journal to change its practice ---
https://www.nature.com/articles/d41586-019-02241-z
Poroi: Project on Rhetoric of Inquiry ---
https://ir.uiowa.edu/poroi/
Why History Gets Stuff Wrong All the Time ---
https://awealthofcommonsense.com/2019/07/why-history-get-stuff-wrong-all-the-time/
Stanford University: Civic Online Reasoning ---
https://irlpodcast.org/
The Truth About Teacher Pay ---
https://www.nationalaffairs.com/publications/detail/the-truth-about-teacher-pay
Stanford professor who changed America with just one study was also a liar
(cherry picking study outcomes) ---
https://nypost.com/2019/11/02/stanford-professor-who-changed-america-with-just-one-study-was-also-a-liar/?utm_source=pocket-newtab
Big
Data+Small Bias << Small Data+Zero Bias ---
https://marginalrevolution.com/marginalrevolution/2020/01/big-datasmall-bias.html
An Oversimplified, Misleading Argument about Inequality and
Taxes ---
https://www.nationalreview.com/2019/11/book-review-triumph-of-injustice-oversimplified-misleading-arguments-about-inequality-taxe
Chronicle of Higher Education: What College Activists Want?
https://www.chronicle.com/article/What-College-Activists-Want/249184?utm_source=at&utm_medium=en&utm_source=Iterable&utm_medium=email&utm_campaign=campaign_1363707&cid=at&source=ams&sourceId=296279
Defunded police.
Inclusive coursework.
Faculty members who look like them. (including
administrators and coaches.
Students are demanding radical change for racial justice,
and they’re not backing down.
The demand: Sever ties with the police
(except armed Antifa patrols)
The demand: Remove symbols of oppression (including the library's
politically incorrect materials)
The demand: Hire people of color (even if they are less qualified
than others)
The demand: Diversify the curriculum (No
Shakespeare/math/business and more Che Guevara)
Some of the unmentioned demands in the above article
Free tuition, room and board, pot, and booze
Free medical and dental care (including free abortions)
Open admission for for people of color
Only A grades (stop giving mostly A- and B grades)
No examinations, quizzes or grading of term papers
Excuse from class attendance in favor of protesting
Screening of all campus speakers for political correctness (pretty much like
it is now)
No suspensions or dismissals (except in the case of the first signs of
conservatism disease)
Reparations plus guaranteed annual income during and after graduation
Reply from Bob Jensen later in the day
I perhaps exaggerated too much on student demands and tried unsuccessfully
to be somewhat funny. However, I think if I dug deeper I would find where
student groups have made demands of all the the things I mentioned.
I note that the Daily Beast articles almost always promoted a leftist
agenda.
Here are some of the documented demands of students listed by the Daily
Beast (note the ones to get rid of grades, tests, and teachings of all
male poets (including Shakespeare). I also note that some colleges (think
Michigan State) removed mathematics from the core course and skills
requirements:
https://www.thedailybeast.com/the-craziest-demands-of-college-kids-in-2016
**How to Mislead
With Statistics
Stratified Sampling ---
https://en.wikipedia.org/wiki/Stratified_sampling
Mathematician Gary Cornell argues that current testing procedures won't
tell us much about vaccine efficacy for the elderly because sampling was not
stratified ---
https://garycornell.com/2020/10/22/we-are-unlikely-to-have-a-vaccine-that-is-proven-effective-for-seniors-for-a-long-time-unless-dramatic-action-is-taken-now/
**How to Mislead With Statistics
Statistical Anomalies in Biden Votes, Analyses Indicate ---
https://www.theepochtimes.com/statistical-anomalies-in-biden-votes-analyses-indicate_3570518.html?utm_source=newsnoe&utm_medium=email&utm_campaign=breaking-2020-11-08-5
Jensen Comment
Be aware that the above article is published by a conservative and highly biased
media outlet. In spite of this the article raises some interesting questions
such as Benford's Law commonly used by accountants (think IRS) in search
of fraud in financial data. Benford's Law is also a common component of forensic
accounting education ---
https://www.mentalfloss.com/article/63099/irss-favorite-mathematical-law
I want to claim that I do no support the long delay in the the GOP concession
that Trump lost to Biden. But it is interesting how data analysts are
identifying and analyzing statistical anomalies. Readers can be confused by
false claims of statistical anomalies and true anomalies that are not due to
fraud or error ---
https://www.kdnuggets.com/2020/09/diy-election-fraud-analysis-benfords-law.htm
Having said this I don't think there's probably sufficient evidence to
overthrow the 2020 election results. Investigations of fraud should proceed to
improve the integrity of future elections. But the Biden team should not be
delayed in their efforts to take over the leadership of the USA.
Election fraud analysis becomes increasingly important as the margins of
difference vote counts shrink like they did in the November 2020 election.
Some fraud controls in live voting are lost when votes are accepted by mail. For
example, it's much harder for the dead to show up at the voting centers.
How to Mislead With Statistics
Why Was The National Polling Environment So Off In 2020?
https://fivethirtyeight.com/features/why-was-the-national-polling-environment-so-off-in-2020/
The bottom line is that we really don't know. We have far more excuses than
reasons.
**How to Mislead
With Statistics
Epic miscalls
and landslides unforeseen: The exceptional catalog of polling failure ---
https://theconversation.com/epic-miscalls-and-landslides-unforeseen-the-exceptional-catalog-of-polling-failure-146959
**How to Mislead With Statistics: Failure to Recognize Externalities
Externality ---
https://en.wikipedia.org/wiki/Externality
Boston schools wanted to stagger start times to save on transportation
costs and improve student health. Here's why parents were against it — and what
it can teach us about pandemic planning ---
https://www.businessinsider.com/why-some-boston-parents-were-against-staggered-school-start-times-2020-10
Jensen Comment
The school districts primarily considered parties most directly involved in
start-time decisions --- students, teachers, and taxpayers who pay the
transportation costs. Parents are more indirectly and variably involved. For
example, stay-at-home parents and parents now working remotely in a majority of
homes may be less concerned than working parentshaving to physically commute to
work on tight schedules. Those parents with less scheduling flexibility
became powerful voices in this illustration.
**How to Mislead With Statistics
Paradoxes of Probability & Statistical Strangeness
https://scitechdaily.com/paradoxes-of-probability-statistical-strangeness/?fbclid=IwAR3JlsjucUeAQg8LeYTFvSoGJcFWpovSvr3gnB4CM99Ekihr-_FTuXlTQOo
Thank you Jagdish Gangolly for the heads up
Simpson's Paradox
Base Rate Fallacy
Will Rogers Paradox
Berkson's Paradox
Multiple Comparisons Fallacy
**How to Mislead With Statistics
Canadian researchers gave $7,500 to people without a home — and the results show
the power of universal basic income ---
https://www.businessinsider.com/canadian-basic-income-experiment-gives-homeless-people-cash-2020-10
. . .
The Foundation for Social Change, a Vancouver-based charity, partnered with
the University of British Columbia to identify 50 people between 19 and 64
years old who had recently become
homeless. The recipients were identified as not having significant
substance abuse or mental health issues.
Researchers studied
their spending habits over
12 months and compared their outcomes to a control group who did not receive
the cash payment.
Those who were
given the cash largely spent the money on food, rent, and transportation and
moved into stable housing faster over the course of the year, according to
the findings.
Spending on
"temptation goods," such as drugs, cigarettes, and alcohol declined by 39%,
on average. And recipients were able to keep an average of $1,000 in
savings, according to Canadian news outlet CBC.
The cash payment saved the shelter system $8,100 per person over the course
of the year, a total savings of $405,000.
Continued in article
Jensen Comment
In fairness the findings report of this study emphasizes that the stipends were
given to only people who recently became homeless (during the Covid-19
pandemic). Without saying so, I think that it's
implied that the findings do not extrapolate well the people who are chronically
homeless due to addictions, mental illness, depression, or lack of motivation to
better themselves.
A recent homeless person could be a hard worker (think a waiter or waitress)
unable to pay rent because of restaurant closures during the pandemic. People
motivated to work are more apt to use the money to find work compared to
hard-core alcoholics unable to think beyond where to get the next bottle of
booze.
The main point is that statistical findings are often difficult to extrapolate
to different people and different circumstance
**How to Mislead With Statistics
Capitalized Value ---
https://en.wikipedia.org/wiki/Market_capitalization
Zoom is Now Worth More Than
Exxon, I Have Ten Questions ---
https://www.thestreet.com/mishtalk/economics/zoom-is-now-worth-more-than-exxon-i-have-ten-questions
Jensen Comment
Capitalized value is a highly controversial way of valuing a company because
most of the shares outstanding are not traded on a daily basis such that prices
of the relatively few shares being traded are generally poor estimates of what
all outstanding shares would bring if they were suddenly made available. Share
trading prices are also subject to a lot market fluctuations that have little to
do with the company itself such as when a powerful world leader dies or is
overthrown.
Accountants argue that using
capitalized value to estimate the total value of a company is usually nonsense
since only equity is being valued rather than total asset value. Using share
prices puts the carts before the accounting horses. The purpose of financial
accounting is to help investors set their buy, sell, and hold decisions based
upon accounting measurements and accounting disclosures such as contingencies.
Would all the owners of Exxon
shares pool their holdings and trade them for all the shares of Zoom? I
seriously doubt it!
Zoom's value is based upon a speculative balloon in the sky, whereas a lot of
Exxon's value lies in hard and soft assets like real estate, oil leases,
tankers, trucks, oil rigs, refineries, etc. Most of those assets have
alternative uses with great value. Zoom's value can pop in an instant, whereas a
great many of Exxon's assets can be put into alternative valuable uses. Also the
hundreds of millions of home and vehicle owners who rely of some type of Exxon
fuel cannot easily change to alternative energies. For example, it will take
decades for hundreds of millions vehicles relying on carbon fuel to be replaced
by carbon-free alternatives.
Zoom's customers can switch on
short notice when some better technology emerges on the scene.
**How to Mislead With Statistics
Simple
Solution to California’s Anticipated $54 Billion Budget Deficit ---
https://www.counterpunch.org/2020/05/15/simple-solution-to-californias-anticipated-54-billion-budget-deficit/
. . .
A 50% tax on the
wealth of just Larry Ellison, Mark Zuckerberg and Elon Musk would solve the
deficit with tens of billions remaining. A quick google search puts their
wealth at:[1]
Zuckerberg $68.2 billion
Ellison $67.4 billion
Musk $36.8 billion
An emergency wealth
tax of 50% on these three individuals alone would come to $86.2 billion.[2] That
would leave over $30 billion more than the estimate of California’s
government deficit. That extra money could be used to house the homeless,
guarantee everyone food and access to medical care, finally provide a proper
level of funding for the state’s public colleges and schools, lift many, if
not all, of the state’s residents out of poverty, and have funds to help out
in case the state experiences another round of destructive fires and/or a
major earthquake.
This type of tax should
have no impact on the lifestyles of the super-wealthy. Recently, they
appeared to be able to get by on “far less.” Zuckerberg’s wealth was put at $46
billion at
the end of 2015 and “just” $4
billion in
2010, less than 6% of what it is today. In 2015, Musk’s wealth was estimated
at $13.2
billion,
not even half of what it is now. After the tax, the net worth of the
super-wealthy would still be excessive.
Continued in article
Jensen Common
An extreme
wealth tax such as that suggested above is not so simple as the article naively
makes it sound. California needs cash and none of the billionaires mentioned
above are sitting on tens of billions in cash or gold or any other investments
that are easily cashed in at market values. They're sitting mostly on common
stock in the companies they control (Facebook, Oracle, Tesla, Boring, and SpaceX,
etc.). Stock prices are set by supply and demand at relatively small amounts of
daily trading. Forcing these huge shareholders to quickly dump 50% of their
enormous holdings would send share values plunging to a point where these
billionaires and their companies no longer have the wealth envisioned in the
above article.
Secondly, the
author of the above article assumes that these billionaires will passively
accept a 50% tax on all their wealth. If such legislation in Sacramento
approaches reality those billionaires will be long gone from California and may
even move their companies out of state. The naive author of the above article
does not investigate why Sweden and France experimented with and then abandoned
much more modest wealth taxes on their most wealthy taxpayers as the wealth
taxes were discovered to be counterproductive on the economies.
Thirdly,
California would be sending a message that there is no longer a California dream
of becoming a billionaire with new ventures in the no-longer Golden State.
Instead the message would be to start new ventures iin more business-friendly
states that still offer an American Dream.
Sir Jim
Ratcliffe, Britain's wealthiest man and a key Brexit backer, has decided to
leave the UK and live in Monaco ---
https://www.independent.co.uk/news/uk/home-news/jim-ratcliffe-brexit-uk-richest-man-monaco-move-tax-haven-eu-leave-a8484211.html
Sir Jim Ratcliffe, Britain’s
wealthiest man and a key Brexit backer,
has decided to leave the UK and live in Monaco.
Despite his previous claims
that the UK would be “perfectly successful” outside of the European Union (EU),
the billionaire has chosen to leave the country of his birth and move to the
principality, whose residents do not pay income tax, on the Mediterranean
coast.
Sir Jim, founder and CEO of the
chemicals giant Ineos, was named as
the richest man in Britain in this year’s Sunday
Times rich
list, with an estimated fortune of Ł21bn.
Continued in
article
The Achilles
heel of the dual income tax : the Norwegian case ---
https://ssb.brage.unit.no/ssb-xmlui/handle/11250/180583
The dual income tax provides the
self-employed individual with large incentives to participate in tax
minimizing income shifting. The present paper analyses the income shifting
incentives under the Norwegian split model in the presence of technology
risk, and it concludes that the
widely held corporation serves as a tax shelter for high-income
self-employed individuals. In addition, real capital investments with
a low risk profile are means to shift income from the labor income tax base
to the capital income tax base for the high-income self-employed.
OECD:
Recommended Tax Reform in Norway --- Phase Out the Wealth Tax
https://www.oecd-ilibrary.org/content/paper/5k9bls0vpd5d-en?crawler=true
Tax Reform in Norway
A Focus on Capital Taxation
Norway’s dual income tax system achieves high levels of revenue collection
and income redistribution, without overly undermining economic performance
and while paying attention to environmental externalities. It treats capital
and labour income in different ways:
capital income is taxed at a single low rate, while labour income is taxed
at progressive rates.
However, effective tax rates on savings vary widely across asset classes.
The favourable treatment of owner-occupied housing relative to financial
savings should be reduced, preferably by taxing imputed rents at the
standard 28% statutory rate. The wealth tax implies very high effective tax
rates on savings, indicating that it either gives rise to tax avoidance or
significantly inhibits growth. The government should investigate the issue
and, if the growth-equity trade-off is too unfavourable to growth,
phase out or lower the wealth tax.
To restrain tax avoidance by the wealthy, the base of the gift and
inheritance tax should be broadened. Overall, the reform package recommended
in this paper would improve the allocation of capital and increase work and
investment incentives. It could be designed to be broadly neutral in regard
to income redistribution and public revenue.
American
Economic Review 2019: Tax Evasion and Inequality (Scandinavia) ---
https://www.aeaweb.org/articles?id=10.1257/aer.20172043
Drawing on a unique dataset of leaked
customer lists from offshore financial institutions matched to
administrative wealth records in Scandinavia, we show that offshore tax
evasion is highly concentrated among the rich. The skewed distribution of
offshore wealth implies high rates of tax evasion at the top:
we find that the 0.01 percent richest households evade about 25 percent of
their taxes. By contrast, tax evasion detected in stratified random
tax audits is less than 5 percent throughout the distribution. Top wealth
shares increase substantially when accounting for unreported assets,
highlighting the importance of factoring in tax evasion to properly measure
inequality.
Here's a humorous and serious TED talk that seriously argues why the world
needs billionaires---
https://www.ted.com/talks/harald_eia_where_in_the_world_is_it_easiest_to_get_ric
**How to Mislead With
Statistics
The COVID Panic Is a Lesson in Using Statistics to Get
Your Way in Politics ---
https://mises.org/wire/covid-panic-lesson-using-statistics-get-your-way-politics?utm_source=Mises+Institute+Subscriptions&utm_campaign=e9c5c5695a-EMAIL_CAMPAIGN_9_21_2018_9_59_COPY_01&utm_medium=email&utm_term=0_8b52b2e1c0-e9c5c5695a-228708937
Jensen Comment
One of my favorite examples is the media's use of Sweden's relatively high
Covid-19 death rate (that's lower than that of the Belgium, the UK, and various
other EU nations) as a glaring example of what happens when you don't have a
national lockdown. Evidence seems to be mounting that Sweden's high death rate
comes more from a glaring failure to protect its most vulnerable citizens,
especially the elderly. Had Sweden done this aggressively early on in March the
case the media might have had less of a case against the Swedish failure to lock
down. Of course we'll never know in hind sight since national death rates from
Corona-19 are so varied and complicated and the data are so inaccurate.
Please don't take this tidbit
as a suggestion that locking down is not important for most (all?) nations.
Heterogeneity ---
https://en.wikipedia.org/wiki/Homogeneity_(statistics)
Also see ---
https://en.wikipedia.org/wiki/Heterogeneity_in_economics
**How to Mislead With
Statistics
Pandemics and persistent
heterogeneity ---
https://www.medrxiv.org/content/10.1101/2020.07.26.20162420v1
It
has become increasingly clear that the COVID-19 epidemic is characterized by
overdispersion whereby the majority of the transmission is driven by a
minority of infected individuals. Such a strong departure from the
homogeneity assumptions of traditional well-mixed compartment model is
usually hypothesized to be the result of short-term super-spreader events,
such as individual's extreme rate of virus shedding at the peak of
infectivity while attending a large gathering without appropriate
mitigation. However, heterogeneity can also arise through long-term, or
persistent variations in individual susceptibility or infectivity. Here, we
show how to incorporate persistent heterogeneity into a wide class of
epidemiological models, and derive a non-linear dependence of the effective
reproduction number R_e on the susceptible population fraction S. Persistent
heterogeneity has three important consequences compared to the effects of
overdispersion: (1) It results in a major modification of the early epidemic
dynamics; (2) It significantly suppresses the herd immunity threshold; (3)
It significantly reduces the final size of the epidemic. We estimate social
and biological contributions to persistent heterogeneity using data on
real-life face-to-face contact networks and age variation of the incidence
rate during the COVID-19 epidemic, and show that empirical data from the
COVID-19 epidemic in New York City (NYC) and Chicago and all 50 US states
provide a consistent characterization of the level of persistent
heterogeneity. Our estimates suggest that the hardest-hit areas, such as
NYC, are close to the persistent heterogeneity herd immunity threshold
following the first wave of the epidemic, thereby limiting the spread of
infection to other regions during a potential second wave of the epidemic.
Our work implies that general considerations of persistent heterogeneity in
addition to overdispersion act to limit the scale of pandemics.
**How to Mislead With Statistics
Corona19 Death Rates ---
https://www.factcheck.org/2020/05/where-the-u-s-ranks-in-covid-19-deaths-per-capita/
President Trump claimed the USA had one of the lowest death rates.
Chris Wallace Claimed the USA has had the seventh highest death rate ---
https://townhall.com/tipsheet/guybenson/2020/07/20/fact-check-president-trump-vs-chris-wallace-on-coronavirus-death-rates-defunding-the-police-n2572736
Both are wrong. Out of 144 nations the USA comes in at Rank 32
with most European nations having higher
death rates. Austria and Norway had death rates lower than the USA.
Averages (for some nations are more misleading than others). For example, the
Netherlands has a relatively dense population across the entire country. Its
death rate has a low standard deviation relative to the USA. In comparison, the
USA has a relatively disperse nation with populations concentrated in some large
cities in in some states and other states that are relatively low in population.
Among other things population density contributes to higher death rates (but
there are exceptions for other interactive factors like age of the state
populations, number of people commuting by subways and trains, etc.).
Corona-19 Death Rates Per 10,000 Cases
Accumulated Data as of July 19, 2020

Since accuracy of reported data is
so suspect in the majority of nations, it's misleading to compare number of
cases and number of deaths by nation.
Having said this I will report the following in any case because it's
consistent with the Johns Hopkins Data
Coronavirus (COVID-19) death rate in countries with confirmed deaths and
over 1,000 reported cases as of July 17, 2020, by country ---
https://www.statista.com/statistics/1105914/coronavirus-death-rates-worldwide/
Yemen |
Confirmed
Cases
1,552 |
Number of
Deaths
438 |
Death
Rate %
28.22 |
Belgium |
63,238 |
9,795 |
15.49 |
United Kingdom |
292,552 |
45,119 |
15.42 |
France |
200,929 |
30,049 |
14.96 |
Italy |
243,736 |
35,017 |
14.37 |
Hungary |
4,279 |
595 |
13.91 |
Netherlands |
51,351 |
6,137 |
11.95 |
Mexico |
324,041 |
37,574 |
11.6 |
Spain |
258,855 |
28,416 |
10.98 |
Canada |
111,144 |
8,875 |
7.99 |
Ecuador |
71,365 |
5,207 |
7.30 |
Sweden |
76,877 |
5,593 |
7.28 |
Ireland |
25,698 |
1,749 |
6.81 |
|
Liberia |
1,070 |
68 |
6.36 |
Sudan |
10,527 |
668 |
6.35 |
Niger |
1,102 |
69 |
6.26 |
Switzerland |
33,290 |
1,969 |
5.91 |
Slovenia |
1,897 |
111 |
5.85 |
Romania |
35,003 |
1,971 |
5.63 |
China |
85,314 |
4,644 |
5.44 |
Burkina Faso |
1,038 |
53 |
5.11 |
Iran |
267,061 |
13,608 |
5.10 |
North Macedonia |
8,623 |
401 |
4.65 |
Denmark |
13,124 |
610 |
465 |
Germany |
201,450 |
9,087 |
4.50 |
Finland |
7,293 |
328 |
4.25 |
Guatemala |
32,939 |
1,404 |
4.26 |
Lithuania |
1,902 |
79 |
4.15 |
Japan |
23,833 |
985 |
4.13 |
Poland |
39,054 |
1,605 |
4.11 |
Iraq |
86,148 |
3,532 |
4.09 |
USA |
3,565,256 |
138,174 |
3.88 |
Sierra Leone |
1,678 |
64 |
3.81 |
Brazil |
2,012,151 |
76,688 |
3.81 |
Followed by 112 other nations |
|
|
|
Accuracy varies greatly |
**How to Mislead With Statistics
Surprising study: Urban density doesn’t cause more COVID-19 infections, even
promotes lower death rates ---
https://www.studyfinds.org/surprising-study-urban-density-doesnt-cause-more-covid-19-infections-even-promotes-lower-death-rates/
Crowded city streets, subways, and buses have been
considered the most likely places to become infected with COVID-19 over the
past few months. Surprisingly, however, a new study from the Johns Hopkins
Bloomberg School of Public Health concludes that densely populated spaces
aren’t actually linked to higher infection
rates.
Even more confounding, the study’s
analysis indicates that crowded, dense locations are associated with lower coronavirus death
rates.
In all, COVID-19 infection and death rates were
assessed across 913 U.S. metropolitan counties. After researchers accounted
for additional factors like race and education, the population density
within each county was not significantly linked to infection rates. As
mentioned, denser counties, as opposed to more rural, sprawling
areas with smaller populations, were associated with lower death rates. The
study’s authors speculate this is because denser, urban areas often offer
better healthcare services.
Instead, higher
coronavirus infection and death rates seem to be linked to a metropolitan
area’s size,
not its density. So, cities that are
very big and stretch across multiple counties that are “tightly linked
together through economic, social, and commuting relationships” appear to be most
at risk of
high coronavirus infection rates
Continued in Article
Jensen Comment
I think the populated density issues are more complicated than density per se
(think population per square mile). For example, the above study concludes that "densely
populated spaces aren’t actually linked to higher infection
rates". However,
I contend that the most dense populations vary greatly in terms of lifestyles.
Los Angeles differs greatly from New York City in many ways, including the LA's
relative lack of public transportation relative to NYC. Also in NCC it's
extremely common for workers to move out of NYC when they retire. And if they
retire in a another dense area like Miami or LA their lifestyles change because
they are no longer commuting daily over long distances by public transportation
to get to and from jobs. The public indoor places of Manhattan and San Francisco
are crowded many hours of each day relative to the public indoor places of
Miami, LA, and Houston.
My point here is that population density as a predictor of Covid-19 infections
and deaths confounds many other issues like demographic differences of
residents, lifestyle differences, etc. But
density should not be eliminated as a contributing factor to the multivariate
set of interactive causes.
Both the risks of infection from Covid-19 and the risk of dying when infected
are multivariate and interactive.
Except for age I don't think we can factor out any one variable (like population
per square mile) from all the other interactive causes.
And density is a continuum. Southern New Hampshire is much less densely
populated than Northern New Hampshire. And Southern New Hampshire is very much
less densely populated than New York City.
New York State has a population of 19.5 million out of which over 8.2 million
live in NYC. New Hampshire has a population of 1.4 million out of which 110,000
live in Manchester, NH.
As a retired total recluse living on food and drink ordered from Amazon, your
odds of testing positive for Covid-10 are probably about the same in NYC or New
Hampshire's Manchester or Littleton in the north. If
you're a patrol cop or hospital worker your probability of testing positive is
much higher in dense NYC or Manchester. However your probability is even lower
in Littleton relative to Manchester and points along I-93 leading toward
Massachusetts.
Now consider the following map of New Hampshire where the state's highest
population density is skewed toward the southern part of the state ---
https://www.nh.gov/covid19/
Note that "50+" in the color
coding includes such large numbers as 500 and 800.
In the middle of New Hampshire my guess is that nursing home residents
contributed to nearly all of the 6, 7, AND 16 numbers shown on the map below.
I contend that the Covid-19 infection rates along the southeastern boundary are
relatively high because this is where NH workers commuting to Massachusetts
(think Boston) are most likely to live in NH. These NH state line residents most
likely were infected due to working in Massachusetts (think NH medical
professionals who work in Massachusetts hospitals)
Contrary to the conclusion of
the above "Surprising Study," the one thing I'm certain of is that people who
move from New York City to northern New Hampshire at the present time ipso
facto have lower probabilities of becoming infected unless they live like a
recluses before and after the move.

**How to Mislead With Bad
Assumptions
Biden plan for free public
college tuition could doom most private colleges ---
https://www.foxnews.com/opinion/biden-free-college-justin-haskins-chris-talgo
Jensen Comment
I'm opposed to free public colleges except possibly the first two years in local
community colleges. My reason is the trillions of dollars it will cost to
otherwise provide free tuition and other aid to all public universities for
undergraduate and postgraduate education. It's unfair to give them free
undergraduate degrees and then tell them they have to pay to graduate schools
aimed at career education.
The conclusion that free public
education will doom most private colleges is misleading.
Some private colleges are on the brink of extinction and will fail with or
without free public college competition.
Free public college education
will overwhelm the best public colleges (think flagship universities) with
applicants. Either top public universities will limit the acceptance rates for
onsite campuses to what it is now, or they will ruin onsite education with
gigantic lecture classes, or they will limit the free tuition to inferior
distance education. By inferior I mean that online courses will be huge with
almost no interaction between students and their teachers and other students in
each course. The very best online courses are small with instant messaging
between faculty and students. These can
be even better than face-to-face tutorials.
The better private schools will
survive by offering what they offer now --- smaller classes, closer interactions
with faculty, and campus residency aimed at providing all the things they cannot
obtain in large public universities, small dormitories, participation in sports
without having to perform at a professional level, etc.
But the nation may not survive
as Biden's social program promises inch up toward $100 trillion per year for
universal health care for legal and illegal residents, minimum basic income,
green initiatives, reparations for all people of color, open borders, massive
housing subsidies, free college for all legal and illegal residents, enormous
increase in funding to K-12 schools, new roads/bridges,
bailout of states, etc.
The ploy of promising everything for
everybody is not new to political candidates.
History is replete with failed promises when economic realities set in for
elected officials. The worry today is that activists will no longer accept
excuses for failed promises and will elect zealots like AOC, Harris, or Bernie
Sanders instead of Joe Biden --- who, like Obama, I hope is more tuned into
economic realities even though Biden's now making unrealistic promises.
I hope Biden's VP choice is a
realist and not a zealot.
Here's One Economic Reality
That Activists Avoid Mentioning
Some argue that public colleges aren't all that radical, and some European
nations (think Finland and Germany) now offer free university education. But
they don't tell you how these nations face economic realities.
These nations painfully limit the number
of students getting free college education or free training to about the top 1/3
of Tier 2 graduates such that the other 2/3 either cannot get into college or
have to rely on private sector companies to train them with apprenticeships
---
http://faculty.trinity.edu/rjensen/HigherEdControversies.htm#Tertiary
**How to Mislead With Statistics
CDC: USA Media Over Reporting Coronavirus Deaths by 60%
https://www.blabber.buzz/conservative-news/867450-cdc-data-shows-coronavirus-deaths-actually-37308-nearly-half-what-media-is-reporting-special?utm_source=c-alrt&utm_medium=c-alrt-email&utm_term=c-alrt-GI&utm_content=9GHGkdpWhYe83EFyZJjkFO8_21LdfGwaVfyZOKuqu1nQ.A
As of May 1, the CDC website states that 37,308 people died
from the Wuhan coronavirus, which includes confirmed and presumed deaths
from the pathogen.
The data also
shows that the coronavirus pandemic peaked in the U.S. the week of April 11.
Additionally, the
number of coronavirus deaths have been decreasing since April 25, with about
93% of all coronavirus deaths happening to individuals over 55 years old.
As Newsmax
journalist John Cardillo noted, the data reported on by the media and
Worldometer is a “scam” for likely attributing other causes of death to
inflate coronavirus fatalities
Jensen Comment
I can think of trillions of reasons for overstating the deaths, although in
truth much of the problem may be due to careless reporting errors. The same
thing has happened for over 100 years with pneumonia. Pneumonia is known as the
old peoples' friend because when people suffering with cancer or other terminal
illnesses experience weakened immune systems the final cause of death is often
pneumonia. It would've been a total waste of money all those years to have
diverted 60% of the medical research money to preventing pneumonia when that
medical research money was better spent on cancer and other terminal illnesses
that led to the weakened immune systems.
Of course pneumonia among young and healthy people was a much bigger problem
before penicillin and other antibiotics.
There are many reasons (think stimulus money) for over reporting Covid-19
deaths, but the above article has huge statistical errors ---
https://www.snopes.com/fact-check/cdc-death-figures/
**How to Mislead With
Statistics
Have We Already Defunded the
Police?
https://marginalrevolution.com/marginalrevolution/2020/06/have-we-already-defunded-the-police.html
Jensen Comment
A well known problem in cost accounting comes in precisely defining costs to be
classified. The classic example is the definition of a $20 million building on a
balance sheet.
Firstly, that $20 million most likely includes the cost of the land under and
surrounding the building. Land costs are quite different than construction costs
of the building itself. For one thing land site lasts forever and is not subject
to depreciation like the construction costs of the building certain land
improvements.
Secondly, there's the classic problem in accountancy of costs that get
expensed (on the income statement) versus costs that get capitalized (on the
balance sheet) and the rates at which some of those capitalized costs become
expensed. For example, the costs of light bulbs in a $20 million building is a
significant cost. When the building was new, those light bulb costs were
probably included in the $20 million capitalized cost. However, every year
thereafter the replacement costs of those light bulbs are probably expensed each
year even when the light bulbs themselves are expected to last several years.
Now consider "Police and Corrections Expenditures" in the above article. I
suspect these numbers are taken from the annual expenditure budgets.
Governmental accounting is based more on fund accounting than accrual accounting
used by business firms. But fund accounting is troubled by some of the
definitional problems faced in accrual accounting. Does "Police Expenditure" in
the above article include the cost of operating police station buildings or is
it only based on the salaries and bonuses of police officers and administrators?
Does it include the related cost of vehicles, computers, etc.?
Then there's the gray zone of technology costs affecting policing. Does
"Police Expenditure" include the cost of creating and maintaining databases such
as fingerprint, DNA, and criminal records in national, state, and regional
databases?
Presumably, there are tradeoffs such as the more we spend on newer policing
technologies the less we have to spend on police labor that those technologies
replaced. Those technology costs may be included in budgetary funds other than
"Police Expenditures."
Then there's the problem of those multimillion dollar punitive damage awards
the courts pass against police departments. Are they "Police Expenditures?"
And then there's the enormous problem that the State of Illinois and the City
of Chicago know more about than anybody else. Does "Police Expenditure" include
the massive cost of pensions of police officers and administrators? If so
defunding of police is not such a simple matter since retirement obligations go
on and on even if you fire the entire police force.
My point here is that accountancy in the 21st Century accountancy is much
more complex that in the 1400s when Pacioli expressed double-entry bookkeeping
in simple algebraic equations.
The question of whether we are
already "defunding the police" is not so simple to answer as concluded in the
above article.
**How to Mislead With Statistics
California's Energy
Regulations Hurt the Poor, While 'Green' Subsidies Benefit the Rich ---
https://reason.com/2020/07/10/californias-energy-regulations-hurt-the-poor-while-subsidies-benefit-the-rich/
Jensen Comment
This is a classic problem of short-term versus long-term benefits.
The real issue is whether subsidies to wealthy corporations and wealthy
universities might greatly benefit all earthlings (rich and poor) in the
long-run. For example, R&D supplements to Big Oil may help those companies find
and develop low-carbon energy solutions that are much more important to the
planet than solar panels on housing for the rich and poor owners.
And it's not just R&D. Big Oil companies are already investing heavily in
alternative energies (think windmill farms) --- possibly more than the public
sector is investing in such alternatives. Subsidies to Big Oil might hasten
their replacement of carbon-based energies.
**How to Mislead With Statistics
New York Is Having a Violent Summer, But It's Not Because of Bail Reform ---
https://reason.com/2020/07/09/new-york-is-having-a-violent-summer-but-its-not-because-of-bail-reform/
Jensen Comment
This article is misleading because it fails to mention the effect of bail reform
on lesser crimes, particularly shoplifting. To the extent that bail reform
essentially legalizes shoplifting it can do great harm to areas where
shoplifting is heaviest. For example, in the poor parts of Los Angeles, Chicago,
St. Louis, and Baltimore having no punishments for shoplifters means that stores
in those poor parts will close up giving less shopping alternatives (think
grocery stores, pharmacies, Walmarts, Targets, etc.) to the poorest residents of
the cities.
If you want more stores in the ghettos
you have to prevent shoplifting in most every way possible, including punishing
the shoplifters.
**How to Mislead With
Statistics
From a Retraction Watch Newsletter on June 1, 2020
Especially note the study in Lancet that the liberal media jumped on as being
the most definitive study to date. The media loved it, but 180 scientists were
skeptical of parts of it.
Also note that there's a lot of completely phony research being circulated.
How many papers
about COVID-19 have been retracted? We’ve been keeping track, as part of our
database. Here’s
our frequently updated list.
Here’s what was
happening elsewhere:
·
A
large study in The Lancet of hydroxychloroquine for COVID-19 has earned a correction after more
than 180 scientists signed a letter criticizing it. More from Andrew
Gelman.
·
A
company allegedly “fabricated phony scientific studies…to
substantiate their false claims” about COVID-19.
·
The
US Food and Drug Administration (FDA) “has
warned a drug company for data falsification” and environmental
issues.
·
“Scientific misinformation persists when
retractions and corrections are not promptly issued, are not sufficiently
detailed, and fail to connect to the misinformation.”
·
“We
use network models to think about why
retractions often fail.”
·
“The
preliminary nature of what I’ve seen published in top journals is
eye-opening. It forces us to rethink what
peer review means, what rigor means, and what prestige means.”
·
“The
problem is that good science, which requires scrutiny and replication,
simply cannot
move at the speed of the rolling news cycle.”
·
“British psychologist Hans Eysenck has always been controversial for his
social views. His scientific
integrity is now also under attack – again.” More here.
·
“Disability rights activists are pressuring a law school journal to retract
a paper that they claim justifies ‘ableism and eugenics’ in
response to the COVID-19 pandemic.”
·
“Reasons to Worry Less
About the Explosion of Preprints.”
·
“[I]n
recent years,” says a report, “all the major publishers have made
their own investments in preprint platforms.”
·
A
look at open
peer review.
·
“Subsequently, on the same day, this paper was alerted to allegations —
first made public on social media — that parts
of the same piece by Ravi were similar to sections of a paper, ‘Roadmap to
Responsibly Reopen America’, published on April 23, by Paul Romer,
University Professor, New York University, and 2018 Nobel Laureate in
Economics.”
·
“Coronavirus studies appear at lightning speed. Too
soon maybe?”
·
“The
speed of coronavirus
science has consequences.”
·
“When
does fast science become problematic science? COVID-19
is testing us on that question and many more,” says the Los
Angeles Times.
·
“Post-Publication Peer Review for Real:” Researchers say the approach taken
by one neuroscience journal could
succeed where others have failed.
·
“We
also found a better affinity to Nature by
the general audience and a
better affinity to Science in
former USSR scholarly allies.”
·
A study
of retractions in the life sciences, using PubMed, which the
author says is, to the best of her knowledge, “the biggest dataset on
retractions in biomedical literature to be studied.” We’d humbly suggest
looking at our
database, which is far
more comprehensive, next time.
·
“A
Vigilante in Statistical Badlands:” How
a JAMA paper on dialysis came to be retracted.
·
“It
is also interesting to note that several preprints received negatively by
the scientific community are amongst the most tweeted.” A preprint
about preprints during COVID-19.
·
“Concerns have been raised about the treatment of Chinese academics deemed
to have strayed from official narratives about the Covid-19 pandemic.”
·
“An
academic who doesn’t
have the ability to challenge the research findings of their colleagues because
those questions threaten the university’s funding doesn’t have intellectual
freedom.”
·
“However, the results may have been influenced by the (re)search bubble
effect. In other words, using
the Google search engine may have influenced study results due to
underlying, highly personalized algorithms…”
Journal Retracts Study
Debunking Hydroxychloroquine ---
https://www.ozy.com/presidential-daily-brief/pdb-337486/?utm_term=OZY&utm_source=Sailthru&utm_medium=email&utm_campaign=PDB%20%282020-06-05%2010:34:26%29#article337492
Prognosis: Yikes. On May 22, British medical journal The Lancet published a
Harvard study that found not only does the malaria drug not help treat
COVID-19, it’s associated with higher mortality rates. Alarmed, the World
Health Organization paused trials of the drug. But now the journal has
retracted the study at the request of three of its authors, who expressed
concerns about the quality of the data — and Surgisphere, the company that
provided it, has refused to transfer the full dataset.
The retraction could fuel supporters
of hydroxychloroquine like President Trump and Brazilian President Jair
Bolsonaro.
Australian scientists have savaged the international mess over a Harvard
study of the drug hydroxychloroquine as a disastrous setback in the search for
COVID-19 treatments that will scare off patients and undermine trust in good
science ---
https://www.smh.com.au/national/this-is-not-how-science-works-major-setback-in-the-search-for-covid-19-treatment-20200605-p54zxi.html
Australian scientists have
savaged the international mess over a study of the drug hydroxychloroquine
as a disastrous setback in the search for COVID-19 treatments that will
scare off patients and undermine trust in good science.
On Friday, the
World Health
Organisation restarted its trial of
hydroxychloroquine after
The Lancet
medical journal spectacularly retracted
a
research paper that reported the drug was
associated with a
35 per cent increased risk of serious cardiac side effects.
The study’s authors said
they could no longer vouch for the veracity of its data, following repeated
concerns raised about the methods of the US data collection company
Surgisphere.
The Lancet editor, Dr Richard
Horton described the fiasco as "a shocking example of research misconduct in
the middle of a global health emergency” to
The Guardian.
Despite the retraction, British scientists on Friday halted their own
large-scale hydroxychloroquine trial after initial results showed no
evidence of benefit.
"We
reviewed the data and concluded there is no evidence of a beneficial effect
of hydroxychloroquine in patients hospitalised with COVID, and decided to
stop enrolling patients to the hydroxychloroquine arm with immediate
effect," said Martin Landray, an Oxford University professor who is
co-leading the so-called RECOVERY trial.
"This is not a treatment for COVID-19. It doesn't work. This result should
change medical practice worldwide. We can now stop using a drug that is
useless."
In Australia, Health
Minister Greg Hunt announced $170,000 to
fund hydroxychloroquine research at Queensland University of Technology,
the Doherty Institute has resumed recruiting COVID-19 patients for its
hydroxychloroquine ASCOT trial, and the Walter Eliza Hall Institute’s SHIELD
trial has continued to test the prophylactic effects of the drug in
healthcare workers.
Mr
Hunt said Australia is taking cautious steps to consider a range of
different therapies and treatments and "we'll continue with our programs".
But
the damage had been considerable, said SHIELD trial lead investigator
Professor Marc Pellegrini.
“We are diverting valuable resources to mitigate the
fall-out of this scandalous
Lancet
paper,” he said.
“This is incredibly damaging when we need to be moving very fast. The
greatest damage is to science itself.”
Dr
Gaetan Burgio, head of an infectious diseases lab at the Australian National
University, said it is “an absolute disaster” to be focused on an
observational trial of limited value that has distracted from the
gold-standard randomised controlled trials to find an effective treatment
for COVID-19.
“I
wouldn’t be surprised if [trial investigators] have a lot of trouble
recruiting patients as a result of this,” Dr Burgio said.
Continued in article
Bob Jensen's blog called Fraud
Updates ---
http://faculty.trinity.edu/rjensen/FraudUpdates.htm
How to
Mislead With Statistics
The Cost of
Living Adjustment (COLA) for Social Security is Not Based Upon What Senior
Citizens Buy
Social Security beneficiaries might not receive much of a cost-of-living
adjustment next year — and some say recipients might not get anything at
all.
COLA
is linked to the consumer-price index, which has suffered lately because of
low oil prices. Based on the CPI data between January and April of this
year, COLA for next year would be zero, according to Mary Johnson, a Social
Security policy analyst for The Senior Citizens League. There are still five
months until the administration announces the COLA for 2021, which occurs in
October. The adjustment in 2020 was considered minimal, at 1.6% this year,
down from 2.8% in 2019. COLAs have averaged 1.4% over the last decade, down
from the average 3% it was between 2000 and 2009.
. . .
The problem:
Social Security’s cost-of-living adjustment is linked to the consumer-price
index for urban workers. There’s another subset of CPI, known as
CPI-E,
which tracks
elderly spending. The difference is primarily in health care and housing.
Those expenses, including Medicare
premiums and homeowners’ insurance, grow rapidly year over year, but benefit
adjustments don’t reflect that growth.
The coronavirus
crisis could deepen the divide, especially as medical expenses drop in some
areas — such as elective surgeries — but increase in others, including care
for COVID-19 patients. “Older people are disproportionately affected by the
COVID-19 crisis, often due to underlying medical conditions,” Johnson said.
The Centers for Disease Control and Prevention, as well as other leading
figures, have urged older Americans to stay home and away from others as
they are typically at a
higher risk
of complications from contracting the virus.
Annual average out-of-pocket expenses for prescription drugs were $1,102 in
January 2000 and $3,875.76 in January 2020, according to the study — a 252%
increase. Medicare Part B premiums jumped 218% during the same time frame,
and home heating oil grew 172% during that period. Even the price of oranges
grew more than double, from $0.61 in 2000 to $1.34 in 2020, a 120% increase.
A retiree in 2000 with an average benefit of $816 a month would have
$1,246.20 in 2020, but would need $380 more a month just to maintain that
same level of buying power she had in 2000.
Continued in article
Jensen Comment
The 800-lb gorilla in all of this is what will happen to nursing home pricing
and other long-term care nursing prices not covered by Medicare? Nursing home
expenses are going through the roof as nursing homes adapt to the risks of the
pandemic and increased attention given to nursing homes by regulators. It's
pretty safe to predict that already very high nursing home prices in the USA are
going to take another leap upward. There will be increases in Medicare fraud as
heirs try to get loved ones onto Medicaid that covers nursing home care for
"poor people."
Increased costs of Medicaid coverage is
the most serious expense rise for our beleaguered state budgets.
Nursing home pricing trends
2004-2019 ---
https://www.genworth.com/aging-and-you/finances/cost-of-care/cost-of-care-trends-and-insights.html
**How to Mislead With
Statistics (What the attention/advertising seeking media usually ignores)
Coronavirus: Why are
international comparisons difficult?
https://www.bbc.com/news/52311014
Thank you Arnold Barkman for the heads up. b
Everyone wants to know how well their country is tackling coronavirus,
compared with others. But you have to make sure you're comparing the same
things.
The United States, for example, has far more Covid-19 deaths than any other
country - as of 20 April, a total of over 40,000 deaths.
But the US has a population of 330 million people.
If you take the five largest countries in Western Europe - the UK, Germany,
France, Italy and Spain - their combined population is roughly 320 million.
And the total number of registered coronavirus deaths from those five
countries, as of 20 April, was over 85,000 - more than twice that of the US.
So, individual statistics don't tell the full story.
For comparisons to be useful, says Rowland Kao, professor of data science at
the University of Edinburgh, there are two broad issues to consider.
"Does the underlying data mean the same thing? And does it make sense to
compare two sets of numbers if the epidemiology [all the other factors
surrounding the spread of the disease] is different?"
Counting deaths
Let's look at some of the numbers first. There are differences in how
countries record Covid-19 deaths.
France, for example, includes deaths in care homes in the headline numbers
it produces every day, but the daily headline figures for England only
include deaths in hospitals.
There's also no accepted international standard for how you measure deaths,
or their causes.
Does somebody need to have been tested for coronavirus to count towards the
statistics, or are the suspicions of a doctor enough? Does the virus need to
be the main cause of death, or does any mention on a death certificate
count?
Are you really comparing like with like?
Death rates
There is a lot of focus on death
rates, but
there are different ways of measuring them
too.
One
is the ratio of deaths to confirmed cases - of all the people who test
positive for coronavirus, how many go on to die?
But
different countries are testing in very different ways. The UK has mainly
tested people who are ill enough to be admitted to hospital. That can make
the death rate appear much higher than in a country which had a wider
testing programme.
The
more testing a country carries out, the more it will find people who have
coronavirus with only mild symptoms, or perhaps no symptoms at all.
Most cases are never counted at all!
Continued in article
Jensen Comment
There are of course giant nations more populated than the USA. China has 1.5
billion people, but it's suspected that China cheats with statistics when it
suits a purpose. India has almost as many people but is way down the list of
confirmed coronavirus cases and deaths ---
https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6
Reasons are not clear, but India and Africa are mysteriously immune to
coronavirus infections to date.
**How to Mislead With Statistics
Veterans Affairs Secretary Shares Some Key Details About that HCQ Study the
Media Is Obsessing Over
(like patients were so sick nothing could save them) ---
https://townhall.com/tipsheet/cortneyobrien/2020/04/22/veterans-affairs-secretary-shares-some-key-details-about-that-hcq-study-the-media-is-obsessing-over-n2567406?utm_source=thdailypm&utm_medium=email&utm_campaign=nl_pm&newsletterad=&bcid=b16c6f948f297f77432f990d4411617f&recip=17935167
People are dying from
coronavirus because clinical research is too slow (and I
think almost impossible given our changed way of life since March 2020)
https://marginalrevolution.com/marginalrevolution/2020/04/people-are-dying-from-coronavirus-because-research-is-too-slow.html
Jensen Comment
One of the main reasons for general clinical research delay (maybe forever) is
that developers fear massive class action lawsuits. This is why, in most
instances, Big Pharma outsources clinical trials to medical schools. However, in
some instances the costs of this outsourcing combined with fear of lawsuits
leads to failure to test at all (particularly in heart medications and devices
mentioned in the above article). Added to the delay is that for successful
research outcomes there is the added delay of cranking up production and fear
that nations who cheat on patents will develop black market versions of the
medication or medical device. In the case of the coronavirus Bill Gates is
investing in early production of the seven leading prospects of vaccination to
avoid some of the production delays.
The big
problem is that there's such a long delay imposed by nature itself. How
often have we heard that a super flu vaccination is in production only to
discover at the end of the season that it's been a flakey flu vaccination.
Viruses mutate so quickly and unpredictably. More accurate testing of a
vaccination alternative takes years and years --- as in the case of the
successful smallpox vaccination.
Then there's the issue of ethics. Suppose
coronavirus Alternative X is being tested among 500 people chosen at random to
receive Alternative X versus 500 who will receive a placebo.
Do you want to be one of those test
subjects put in a chamber that exposes each of these people to very high risk of
infection? Instead we must let those people be exposed in "normal life,"
and in normal life most people aren't being exposed to the coronavirus,
especially during and after the lockdowns. In the olden days we might go to an
third-world country and pay poor people whatever it takes to be put into a high
risk infection chamber. This is now rightly considered a violation of human
rights to even let poor people have such a choice.
Clinical studies of coronavirus vaccinations will
have a high risk of false negatives
for people in both test groups simply because they were not exposed in a
high risk way to the virus. This is particularly a problem for test subjects in
nursing homes who are now being more carefully shielded from exposure.
It would be monumentally difficult to run clinical
trials in New Zealand or Mongolia or Siberia where so many people are
geographically separated due to huge distances between very small towns and
farms.
Added to this is the issue is a great mystery of
the coronavirus immunities.
Covid-19: South Africa versus Louisiana
As of April 17 South Africa reports
2,605 Covid-19 cases to date and
48 deaths
https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6
South Africa has almost 60 million people with over 80% being Black African
As of April 8 Louisiana reports
17,030 Covid-19 cases with 652
deaths (with an abnormally high proportion being African American)
https://gov.louisiana.gov/index.cfm/communication/viewcampaign/2605?&uid=h5d%2Afvl6n%5B&nowrap=1
Louisiana has 4.6 million people with over 32% being African American
Even with reporting discrepancies there should be an investigation of why
African Americans are so much more prone to die from Covid-19 than Black
Africans. There are many possible reasons even after doubting the degree of
testing and poor record keeping in South Africa ---
https://wgno.com/news/health/coronavirus/louisiana-covid-19-cases-reach-12496-with-409-deaths/
International comparisons of most anything are complicated. This is especially
so in the case of the great 2020 pandemic!
**How to Mislead With Statistics
How Germany is managing its coronavirus epidemic, and reacting with
disdain to Trump’s policies ---
https://theconversation.com/how-germany-is-managing-its-coronavirus-epidemic-and-reacting-with-disdain-to-trumps-policies-134758
The solid and publicly funded German health system
is also credited for Germany’s relatively low death rate. There are over
28,000 intensive care beds with sufficient respirators available at German
hospitals, more than in most other parts of the world.
Jensen Comment
The author of the above article makes no note that its almost impossible to
compare Germany (with 83 million people crowded into a land mass less than half
the size of Texas)
with the USA (with over 350 million residents spread over vast square miles of
sparsely populated land as well as being concentrated in some cities). The
author of the above article would not dare mention that the USA has over 34.7
critical care beds
per 100,000 capita
compared with Germany's 29.2 critical care beds. That author would not dare
mention that the USA has more new drug patents than the rest of the world each
year ---
https://sccm.org/Blog/March-2020/United-States-Resource-Availability-for-COVID-19
The world is more eagerly awaiting a new vaccine from the USA than it is waiting
for one from Germany.
The huge problem with comparing the USA health care with that of Germany is
that the patients in the USA are spread over such a vast territory compared to
Germany. The Coronavirus case has hit some parts of the USA (think the areas
around NYC and Seattle) very hard relative to vast system of thousands rural
communities that have zero or less than a handful of Coronavirus cases. There
are a lot of supplies (think masks, gowns, and ventilators) in the USA stored
unused in USA hospitals that have never seen a Coronavirus case (we have a son
who works in one of these hospitals in Maine). But it would be unwise for these
rural hospitals to strip their supplies when there are risks of sudden outbreaks
anywhere in the USA.
Since Germany has a national health care plan progressives
think think that these "free" health care services must be vastly superior to
the USA's health care coverage. The fact of the matter is that Germany's free
plan is quite basic and relatively inferior to the free plans in other parts of
Europe. The Germans that can afford it pay for private medical insurance to get
better health care coverage.
Health Insurance in Germany --- http://www.toytowngermany.com/wiki/Health_insurance
I think the USA should consider the German insurance plan.
Germany does have some economic advantages over the USA. Since it has much
less National Debt/GDP relative to the USA it's much
easier for the Germans to borrow in order to finance a huge economic stimulus
package relative the USA that will probably have to rely on printing money for
the first stage of a stimulus package ---
https://worldpopulationreview.com/countries/countries-by-national-debt/
A problem for the EU right now is that this pandemic further threatens to
break up the EU since the more prosperous European nations are weary of
supporting their poor neighbors.
**How to Mislead With
Statistics by Assuming a Stationary Process That is Not Stationary
What should we believe and
not believe about R?
https://marginalrevolution.com/marginalrevolution/2020/04/our-best-people-are-working-on-this-problem.html
. . .
Ultimately, the models and
statistics in the field aren’t designed to handle rapidly changing R,
and everything is made much worse by the massive inconsistencies in the
observed data. R itself is a surprisingly subtle concept (especially in
changing systems): for instance, rt.live uses a simple relationship between
R and the observed rate of growth, but their claimed relationship only holds
for the simplest SIR model (not epidemiologically plausible at all for
COVID-19), and it has as an input the median serial interval, which is also
substantially uncertain for COVID-19 (they treat it as a known constant).
These things make it easy to badly missestimate R. Usually these errors pull
or push R away from 1 — rt.live would at least get sign(R – 1) right if
their data weren’t garbage and they fixed other statistical problems — but
of course getting sign(R – 1) right is a low bar, it’s just figuring out
whether what you’re observing is growing or shrinking. Many folks would
actually be better off not trying to forecast R and just looking carefully
at whether they believe the thing they’re observing is growing or shrinking
and how quickly.
All that
said, the growing (not total, but mostly shared) consensus among both folks
I’ve talked to inside Google and with academic epidemiologists who are
thinking hard about this is:
-
Lockdowns, including Western-style lockdowns, very
likely drive R substantially below 1 (say .7 or lower), even without
perfect compliance. Best evidence is the daily death graphs from Italy,
Spain, and probably France (their data’s a mess): those were some
non-perfect lockdowns (compared to China), and you see a clear peak
followed by a clear decline after basically one time constant (people
who died at peak were getting infected right around the lockdown). If R
was > 1 you’d see exponential growth up to herd immunity, if R was 0.9
you’d see a much bigger and later peak (there’s a lot of momentum in
these systems). This is good news if true (and we think it’s probably
true), since it means there’s at least some room to relax policy while
keeping things under control. Another implication is the “first wave” is
going to end over the next month-ish, as IHME and
UTexas (my
preferred public deaths forecaster; they don’t do R) predict.
-
Cases are of course
massively undercounted, but the weight of evidence is that they’re
*probably* not *so* massively undercounted that we’re anywhere near herd
immunity (though this would of course be great news). Looking at
Iceland, Diamond Princess, the other studies, the flaws in the Stanford
study, we’re very likely still at < ~2-3% infected in the US. (25% in
large parts of NYC wouldn’t be a shock though).
Anyways,
I guess my single biggest point is that if you see a result that says
something about R, there’s a very good chance it’s just mathematically
broken or observationally broken and isn’t actually saying that thing at
all.”
That is
all from Rif A. Saurous, Research Director at Google, currently working on
COVID-19 modeling.
Currently it seems to me that those are the smartest and best informed views
“out there,” so at least for now they are my views too.
Jensen Comment
Misleading statistics aren't all bad as long as they get you tenure, promotions,
and pay raises.
**How to Mislead With Speculative Assumptions
Capitalism Has Failed in Fighting Coronavirus ---
https://www.nakedcapitalism.com/2020/04/capitalism-has-failed-in-fighting-coronavirus.html
Jensen Comment
Socialists are embarrassed by not being able to point to a single socialist
takeover in the real world that succeeded. But they are great at making
speculative assumptions without the least bit of evidence.
For example, the above article assumes that socialist regimes would've
stockpiled the needed supplies for all possible pandemics. This is garbage. Was
Mao stockpiling pandemic supplies for his starving peasants? Firstly there are
too many kinds of possible pandemics and other looming disasters to stockpile
for every contingency. Secondly, socialist regimes have repeatedly demonstrated
an inability to feed the people now, let alone spend trillions on stockpiling
supplies to save their lives if future pandemics hit.
I cringe when reading the following written by an academic:
A worker-coop based economy—where workers
democratically run enterprises, deciding what, how and where to produce, and
what to do with any profits—could, and likely would, put social needs and
goals (like proper preparation for pandemics) ahead of profits.
There's no evidence that worker-coop economies will make enormous sacrifices
needed for social goals. If fact there's no evidence of a single worker-coop
economy that sustained itself in the real world.
There is evidence in capitalist economies
(like the Nordic nations) are willing to tax profits for social goals, but then
so is the USA willing to do so or we would not have Social Security, Medicare,
Medicaid, and one of the more generous welfare systems in the world (think of
the tens of millions of people from all over the world trying to emigrate to the
USA). There aren't many nations giving nearly all its children two meals a day
in or out of school. I followed a school bus yesterday that stopped at nearly
every house on the road to hand out a large bag of food to each child.
I hate to say it but the above article is an example of misleading speculative
assumptions.
**How to Mislead With Statistics
Sr. Fauci: ‘You Can’t Rely On The Models,’ Too Many Variables ---
https://www.dailywire.com/news/fauci-you-cant-rely-on-the-models-too-many-variables
Jensen Comment
Missing variables are often overlooked problems by social science, finance, and
accounting researchers. Not only are there too many missing variables, but some
of those variables are ignored because they can't be reliably quantified and/or
are not in purchased databases that "lazy" researchers prefer to use rather than
gather their own data. Models don't deal well with qualitative variables. In
accountancy these variables are called intangibles and are often ignored by
model builders.
An even bigger problem is the assumption of stationary that does not apply to
a non-stationary world. This is especially a problem in a pandemic.
Academic researchers keep using defective models if they can get them tenure
and promotions with the help of journal referees who belong to the same clubs.
**How to Mislead With
Statistics
Critics Say a Pair of
California Antibody Studies Contain Critical Statistical Errors That Produced
Implausible Results ---
https://reason.com/2020/04/22/critics-say-a-pair-of-california-antibody-studies-contain-critical-statistical-errors-that-produced-implausible-results/
Too many false positives, nonrandom study
population, and infection fatality rates out of whack with other data,
critics claim.
Two
studies by researchers associated with Stanford University and the
University of Southern California using antibody blood tests have estimated
that many more people have been infected with the novel coronavirus that
causes COVID-19 than confirmed diagnoses would indicate. How many more
people? In the Santa Clara (Silicon Valley) study, the researchers estimated
that coronavirus infections at the beginning of April were 50- to 85-fold
more than the number of confirmed cases at that time. In the Los Angeles
County study, they estimated the infection rate at 28 to 55 times higher
than confirmed cases in that jurisdiction.
If true, these findings
of vastly more widespread rates of infection would suggest that the disease
is much less lethal than the crude case fatality rates suggest. (A point
noted by
me
and other Reason
colleagues
in reporting on these studies.) Not surprisingly, these findings have proved
quite controversial,
particularly drawing the
critical attention
of
statisticians
from other institutions.
Since the
Los Angeles County study
has apparently not yet been published online, let's focus on the chief
objections to the Santa Clara study. Those include arguments that (1) the
prevalence rates among people tested for antibodies to coronavirus published
in the study are mostly, or even entirely, very likely due to false
positives; (2) the results are skewed because it was enriched with
participants who were more likely to have been exposed to the virus than the
general population of the county; and (3) that COVID-19 infections must be
very widespread to produce the excess mortality seen in places like New York
City, e.g, essentially most New Yorkers must already have been infected,
suggesting an unprecedented level of contagiousness.
First,
let's look at the problem of false positives. The researchers' blood test
survey in Santa Clara County found that 1.5 percent (50 out of 3,330 people
tested) were positive for the presence of antibodies to the coronavirus. So
the question is, how many of the 50 positives they found might be false
positives?
Continued in article
A Wealth Tax is the Way to Fund the Pandemic ---
https://www.nytimes.com/2020/04/21/opinion/coronavirus-wealth-tax.html
A Wealth Tax is Not the Way to Fund a Pandemic ---
https://www.bloomberg.com/opinion/articles/2020-04-21/coronavirus-a-wealth-tax-isn-t-the-right-way-to-pay-for-pandemic?sref=y8VYjYe4
Jensen Comment
Note that a wealth tax is more symbolic than a viable way to raise the trillions
of dollars being spent on the pandemic to date unless you impose an enormous
wealth tax.
Firstly, if you want to eliminate billionaires you can send them all to tax
havens like Monaco before you get the legislation passed.
Secondly, taxes are collected in cash whereas billionaire wealth is invested
in things other than cash (think stocks, bonds, patents, and real estate),
Forcing billionaires to spend trillions in assets to raise cash to pay taxes
could collapse the stock markets, bond markets, real estate markets, and pension
funds at a time when the USA is struggling to keep those markets from collapsing
entirely.
Thirdly, billionaires are not stupid. Thev've seen fit to protect themselves
in constitutional law and obedient bipartisan legislators making passage of a
serious wealth tax almost impossible.
Nations like Sweden, France, and others that passed wealth taxes found wealth
taxes to be a disaster and later rescinded most the wealth taxes and even high
marginal income taxes ---
https://en.wikipedia.org/wiki/Wealth_tax#Criticisms
Adding an enormous wealth tax on top of all the other economic disasters of
the 2020 pandemic will become another nail in the coffin of the USA economy
relative to the world economy that now knows better than to impose serious
wealth taxes.
Here's a humorous and serious TED talk that seriously argues why the world
needs billionaires
https://www.ted.com/talks/harald_eia_where_in_the_world_is_it_easiest_to_get_rich
The Singapore Dream: How Singapore's richest man went
from welding in a factory for $14 per hour to owning a $17 billion hotpot
restaurant chain ---
https://www.businessinsider.com/life-of-singapore-richest-man-from-welder-to-hotpot-billionaire-2020-1
While a
move is underway to destroy the American Dream of rags to riches (by taxing away
the riches) the Chinese dream is on the rise.
The Chinese Dream
How a Chinese billionaire went from making $16 a month in a factory to being one
of the world's richest self-made women with an $8.3 billion real-estate empire
---
https://www.businessinsider.com/worlds-richest-self-made-woman-wu-yajun-net-worth-2019-2
Top 50 Billionaires in China ---
https://en.wikipedia.org/wiki/List_of_Chinese_by_net_worth
Jensen
Comment
The question for students to debate is why a supposed
communist country allows so many billionaires to rise up from poverty.
That's supposed to happen in the USA where a child growing up in deep
poverty (think Oprah Winfrey or Howard Shultz) became a multi-billionaires.
But is it also supposed to happen under communism? If
so, why?
One reason is that many billionaires can afford to pour lots
of money into high risk ventures. When's the last time you heard about a high
risk (think Silicon Valley).
I don't think China is giving any thought to a wealth tax as the result of
the 2020 pandemic. China understands
economics these days better than most USA voters
**How to Mislead With Statistics
The best students in the world, charted ---
https://qz.com/1759506/pisa-2018-results-the-best-and-worst-students-in-the-world/
Once again, Asian countries came out on top. In the
latest test, China and Singapore ranked first and second, respectively, in
math, science, and reading. Elsewhere, Estonia is noteworthy for its
performance, ranking highly in all three subjects.
In the world’s biggest education test, one small country has raced past
all the others ---
https://qz.com/853656/massachusetts-ranks-nears-singapore-the-education-powerhouse-in-global-assessment-of-15-year-olds-who-are-the-best-students-in-the-world-according-to-pisa-2015/
The United States fared poorly, as usual: with a
math score of 470, it performed well below the OECD average, and it is among
the lowest-performing countries in the subject. Results in science declined
from 2012, coming in at 496, slightly above the OECD average. In reading, it
also performed slightly better than the OECD average (493) at 497.
Disadvantaged Schools Don't Need Smaller Classes --- They Need Better
Teachers ---
https://qz.com/1759506/pisa-2018-results-the-best-and-worst-students-in-the-world/
Jensen Comment
Who can argue against wanting and needing better teachers?
But I've long contended that two-parent homes (like
you find in Finland, China, Estonia, and other top-ranking nations) are the
single most important factor in education. It isn't just the
helping of kids do homework. What's more important are the externalities of
two-parent homes in terms of discipline, teamwork, role modeling,
motivation, and (gasp) happy homes.
The problem is that you can't just legislate two-parent homes like you
can legislated increased school budgets.
Jensen Comment
I'm bound to be lambasted for a closing observation on this topic of "best
students." I begin by noting that these are averages, and averages are distorted
by outliers and skewed distributions. Now the controversial observation:
The highest ranking nations in terms of education are really not very diverse
and generally are highly restrictive regarding immigration.
But before we conclude that diversity may draw testing performance down, we
need to observe that there are many confounding factors
when it comes to measuring what we really want from education in terms of
economic performance, innovation, etc. For example, the USA is overwhelmingly
successful in terms of development of new medications and technologies in spite
of the relatively poor performance of the USA relative to top performing OECD
nations on the PISA tests ---
https://en.wikipedia.org/wiki/Programme_for_International_Student_Assessment
The above articles contain some legitimate complaints about PISA testing as a
measure of education performance.
I'm a strong believer is diversity and rather generous limits on diverse
legal immigration. But open borders can destroy the USA or any other advanced
economy irreparably.
Statistically Controlling for Confounding Constructs is Harder than You
Think—Jacob Westfall and Tal Yarkoni ---
https://blog.supplysideliberal.com/post/2019/10/17/jacob-westfall-and-tal-yarkoni-statistically-controlling-for-confounding-constructs-is-harder-than-you-think
Bob Jensen's Threads on P-Values and What Went Wrong ---
http://faculty.trinity.edu/rjensen/theory01.htm#WhatWentWrong
**How to Mislead With False Promises
The Atlantic: We Need to Start Tossing
Money Out of Helicopters It’s the best option in such extreme circumstances ---
https://www.theatlantic.com/ideas/archive/2020/03/we-need-start-tossing-money-out-helicopters/608968/?utm_source=newsletter&utm_medium=email&utm_campaign=politics-daily-newsletter&utm_content=20200331&silverid-ref=NTk4MzY1OTg0MzY5S0
Jensen Comment
I agree to a controlled amount strategically placed, but not when it comes to
raining down trillions of dollars in printed currency. Raining down trillions of
dollars from helicopters would be a disaster. Need I remind you that in Zimbabwe
eventually one egg cost 100 billion Zimbabwe dollars ---
http://robinwestenra.blogspot.com/2019/10/a-crippling-drought-in-zimbabwe.html
By July 2019, the basic food basket was BsF.
2,600,000 in Caracas, according to the Venezuelan Federation of Teachers Center
of Documentation and Analysis, which makes monthly surveys about the price of
products. The Commerce Chamber, however, has a different figure: BsF. 3,700,000
---
https://www.theatlantic.com/ideas/archive/2020/03/we-need-start-tossing-money-out-helicopters/608968/?utm_source=newsletter&utm_medium=email&utm_campaign=politics-daily-newsletter&utm_content=20200331&silverid-ref=NTk4MzY1OTg0MzY5S0
A better alternative to helicopter raining is for the government to
temporarily buy (maybe with printed money) equity positions into newly issued
shares in many failing businesses --- to put them back on their feet until the
economy is turned around. Then government should sell those shares like it did
in a turned-around Chrysler Corporation following the 2008 recession. Multiplier
effects will create new businesses and new jobs ---
https://en.wikipedia.org/wiki/Fiscal_multiplier
Venezuelans would rather have jobs than billions of useless printed money.
The good news in this pandemic is that it may have dashed the false
promises of Warren and Sanders that the USA economy would be a better place with
$100 trillion spent on new social programs ---
Brian Riedl computed the added $100 trillion cost
of Bernie's initiatives (not counting his free pre-schooling for every child,
the collapse of the capital markets, the loss of most USA pensions, and tides
through open borders ) ---
https://www.city-journal.org/bernie-sanders-expensive-spending-proposals
That helicopter spending (think free college for everybody, guaranteed minimum
wage for everybody, free health care and medicines and nursing care for a great
tide of illegal immigrants from all over the world, etc.) would become an
economic disaster
**How to Mislead With Nothing
The Wall Street Journal published such a scathing story about Google's
search engine when they had absolutely nothing to back it up ---
https://searchengineland.com/misquoted-and-misunderstood-why-we-the-search-community-dont-believe-the-wsj-about-google-search-325241
Jensen Comment
I use DuckDuckGo whenever
I'm looking for a company's home page such as when I'm looking for the home page
of a restaurant ---
https://duckduckgo.com/
Often Google searches lead off with a list of reservation booking agents (not
the home site) that must pay Google to have their sites listed first. But that's
only my anecdotal experience.
I use DuckDuckGo increasingly when looking for a lot of things!
One thing I suspect some professors and students do is forget to use the
Google Scholar search engine ---
https://scholar.google.com/
Put your search phrase into quotation marks and find some of the most scholarly
publications about that phrase.
Bob Jensen's Search Helpers: You can do a lot more than just going
to Google or DuckDuckGo ---
http://faculty.trinity.edu/rjensen/Searchh.htm
The article below may be out of date
"I'm Being Followed: How Google—and 104 Other Companies—Are Tracking Me on
the Web," by Alexis Madrigal, The Atlantic, February 29, 2012 ---
http://www.theatlantic.com/technology/archive/12/02/im-being-followed-how-google-and-104-other-companies-are-tracking-me-on-the-web/253758/
This morning, if you opened your browser and went
to NYTimes.com, an amazing thing happened in the milliseconds between your
click and when the news about North Korea and James Murdoch appeared on your
screen. Data from this single visit was sent to 10 different companies,
including Microsoft and Google subsidiaries, a gaggle of traffic-logging
sites, and other, smaller ad firms. Nearly instantaneously, these companies
can log your visit, place ads tailored for your eyes specifically, and add
to the ever-growing online file about you.
There's nothing necessarily sinister about this
subterranean data exchange: this is, after all, the advertising ecosystem
that supports free online content. All the data lets advertisers tune their
ads, and the rest of the information logging lets them measure how well
things are actually working. And I do not mean to pick on The New York
Times. While visiting the Huffington Post or The Atlantic or Business
Insider, the same process happens to a greater or lesser degree. Every move
you make on the Internet is worth some tiny amount to someone, and a panoply
of companies want to make sure that no step along your Internet journey goes
unmonetized.
Even if you're generally familiar with the idea of
data collection for targeted advertising, the number and variety of these
data collectors will probably astonish you. Allow me to introduce the list
of companies that tracked my movements on the Internet in one recent 36-hour
period of standard web surfing: Acerno. Adara Media. Adblade. Adbrite. ADC
Onion. Adchemy. ADiFY. AdMeld. Adtech. Aggregate Knowledge. AlmondNet.
Aperture. AppNexus. Atlas. Audience Science.
And that's just the As. My complete list includes
105 companies, and there are dozens more than that in existence. You, too,
could compile your own list using Mozilla's tool, Collusion, which records
the companies that are capturing data about you, or more precisely, your
digital self.
While the big names -- Google, Microsoft, Facebook,
Yahoo, etc. -- show up in this catalog, the bulk of it is composed of
smaller data and advertising businesses that form a shadow web of companies
that want to help show you advertising that you're more likely to click on
and products that you're more likely to purchase.
To be clear, these companies gather data without
attaching it to your name; they use that data to show you ads you're
statistically more likely to click. That's the game, and there is
substantial money in it.
As users, we move through our Internet experiences
unaware of the churning subterranean machines powering our web pages with
their cookies and pixels trackers, their tracking code and databases. We
shop for wedding caterers and suddenly see ring ads appear on random web
pages we're visiting. We sometimes think the ads following us around the
Internet are "creepy." We sometimes feel watched. Does it matter? We don't
really know what to think.
The issues the industry raises did not exist when
Ronald Reagan was president and were only in nascent form when the Twin
Towers fell. These are phenomena of our time and while there are many
antecedent forms of advertising, never before in the history of human
existence has so much data been gathered about so many people for the sole
purpose of selling them ads.
"The best minds of my generation are thinking about
how to make people click ads," my old friend and early Facebook employee
Jeff Hammerbacher once said. "That sucks," he added. But increasingly I
think these issues -- how we move "freely" online, or more properly, how we
pay one way or another -- are actually the leading edge of a much bigger
discussion about the relationship between our digital and physical selves. I
don't mean theoretically or psychologically. I mean that the norms
established to improve how often people click ads may end up determining who
you are when viewed by a bank or a romantic partner or a retailer who sells
shoes.
Already, the web sites you visit reshape themselves
before you like a carnivorous school of fish, and this is only the
beginning. Right now, a huge chunk of what you've ever looked at on the
Internet is sitting in databases all across the world. The line separating
all that it might say about you, good or bad, is as thin as the letters of
your name. If and when that wall breaks down, the numbers may overwhelm the
name. The unconsciously created profile may mean more than the examined self
I've sought to build.
Most privacy debates have been couched in
technical. We read about how Google bypassed Safari's privacy settings,
whatever those were. Or we read the details about how Facebook tracks you
with those friendly Like buttons. Behind the details, however, are a tangle
of philosophical issues that are at the heart of the struggle between
privacy advocates and online advertising companies: What is anonymity? What
is identity? How similar are humans and machines? This essay is an attempt
to think through those questions.
The bad news is that people haven't taken control
of the data that's being collected and traded about them. The good news is
that -- in a quite literal sense -- simply thinking differently about this
advertising business can change the way that it works. After all, if you
take these companies at their word, they exist to serve users as much as to
serve their clients.
Continued in article
Intelligence and educational achievement ---
https://www.sciencedirect.com/science/article/abs/pii/S0160289606000171
This 5-year prospective longitudinal study of
70,000 + English children examined the association between psychometric
intelligence at age 11 years and educational achievement in national
examinations in 25 academic subjects at age 16. The correlation between a
latent intelligence trait (Spearman's g froK=12m CAT2E) and a latent trait
of educational achievement (GCSE scores) was 0.81. General intelligence
contributed to success on all 25 subjects. Variance accounted for ranged
from 58.6% in Mathematics and 48% in English to 18.1% in Art and Design.
Girls showed no advantage in g, but performed significantly better on all
subjects except Physics. This was not due to their better verbal ability. At
age 16, obtaining five or more GCSEs at grades A⁎–C is an important
criterion. 61% of girls and 50% of boys achieved this. For those at the mean
level of g at age 11, 58% achieved this; a standard deviation increase or
decrease in g altered the values to 91% and 16%, respectively.
Jensen Comment
There was a time when grades might have been competitive predictors of
educational achievement in the USA but then grade
inflation ruined both the predictors and the criterion of educational
achievement ---
Grade Inflation in High Schools 2005-2018 ---
https://fordhaminstitute.org/sites/default/files/20180919-grade-inflation-high-schools-2005-2016_0.pdf
Also see
https://www.k12academics.com/education-issues/grade-inflation
Grade inflation is the
increase in the number of high grades over time. Grade inflation is often
conflated with lax academic standards. For example, the following quote
about lax standards from a Harvard University report in 1894 has been used
to claim that grade inflation has been a longstanding issue: "Grades A and B
are sometimes given too readily ... insincere students gain passable grades
by sham work." Issues of standards in American education have been
longstanding. However, rising grades did not become a major issue in
American education until the 1960s.
The evidence for grade
inflation in the US was sparse, largely anecdotal and sometimes
contradictory until recently. Hard data were not abundant. A Stanford
University report in the 1990s showed that grades had been rising since the
1960s; in an effort to stem grade inflation, Stanford changed its grading
practices slightly. National surveys in the 1990s generally showed rising
grades at American colleges and universities, but a survey of college
transcripts by a senior research analyst in the US Department of Education
found that grades declined slightly in the 1970s and 1980s. Data for
American high schools were lacking.
However, recent data leave little doubt that grades are rising at American
colleges, universities and high schools.
Leaders from number of institutions, including Harvard University and
Princeton University, have publicly stated that grades have been rising and
have made efforts to change grading practices. An evaluation of grading
practices in US colleges and universities written in 2003, shows that since
the 1960s, grades in the US have risen at a rate of 0.15 per decade on a 4.0
scale. The study included over 80 institutions with a combined enrollment of
over 1,000,000 students. An annual national survey of college freshmen
indicates that students are studying less in high school, yet an increasing
number report high school grades of A- or better.
The debate on grade
inflation has moved from assessment to causes. Are grades rising because
standards are being lowered or because students are producing better work?
Grade inflation is highly correlated the timing when student evaluations of
teachers commenced to seriously impact tenure, promotion, and pay of teachers.
Efforts to limit granting of A grades at places like Cornell and Princeton
were deemed failures.
http://faculty.trinity.edu/rjensen/assess.htm#RateMyProfessor
It didn't help when RateMyProfessors.com commenced to post millions of student
evaluations of named teachers online for the world to see
https://www.ratemyprofessors.com/
The top college teachers at the above site tend to be rated as "easy graders."
Statement Against Student Evaluations for Promotion and Tenure Decisions
(American Sociological Association) ---
https://www.asanet.org/sites/default/files/asa_statement_on_student_evaluations_of_teaching_sept52019.pdf
Jensen Comment
They fail to mention my main objection student evaluations --- the disgrace of
grade inflation bringing the median grades up to A- across the USA ---
http://faculty.trinity.edu/rjensen/assess.htm#RateMyProfessor
The Atlantic: Has College Gotten Too Easy? Time spent studying is
down, but GPAs are up --
-
https://www.theatlantic.com/education/archive/2019/07/has-college-gotten-easier/594550/
Jensen Comment
In eight decades the median grade across the USA went from C+ to A- (with
variations of course) and efforts in such places as Princeton and Cornell to
limit the proportion of A grades were ended and deemed as failures.
http://faculty.trinity.edu/rjensen/assess.htm#RateMyProfessor
Now we ask: Has college gotten to easy. I guess you know what I think.
Higher education has become Lake Wobegon where (almost) all students are
above average in terms of what used to be average.
Especially note the grade inflation
graphs at
www.Gradeinflation.com
**How to Mislead With Statistics
MSNBC Contributor: 'The Iowa Caucus Is Essentially the Perfect Example of
Systemic Racism'
https://townhall.com/tipsheet/juliorosas/2020/02/04/msnbc-contributor-the-iowa-caucus-is-essentially-the-perfect-example-of-systemic-racism-n2560703?utm_source=thdailypm&utm_medium=email&utm_campaign=nl_pm&newsletterad=&bcid=b16c6f948f297f77432f990d4411617f&recip=17935167
"Yes, but I think for a different reason than a lot
of folks probably will think. Maybe I’ll be the only person to say this
today. The Iowa caucus is essentially the perfect example of systemic
racism. 91% of the voters in Iowa are white," Maxwell said.
Jensen Comment
That (91%) is about right without any racism since the population of Iowa is
90.7% with a "Black or African American" population of 4.0% ---
https://www.census.gov/quickfacts/fact/table/IA/PST045218
Doesn't 90.7% round to 91%?
This article is essentially the perfect example of crying racism ad
nauseam on MSNBC.
**How to Mislead With Statistics
The mother of all cognitive illusions: The belief
that having to pay higher taxes would make it more difficult to buy what you
want
https://behavioralscientist.org/behavioral-economics-robert-frank-taxes-mother-of-all-cognitive-illusions/
Jensen Comment
What a terrible article. The title of the above
paper should read "The mother of all academic illusions."
The above article is a combination of lousy research and slight of hand. An
example of slight of hand is the comparison of 1940s highest marginal tax rates
with those of the 1980s. Consider the quotation:
In World War II, the top
marginal tax rate in the United States was 92 percent. By 1966 it had fallen
to 70 percent. In 1982 it was 50 percent, and it is now just 37 percent.
This is a slight of hand because the author knows
(but does not tell us) that the USA marginal top tax rates of the 1940s are not
directly comparable with the marginal rates of the 1980s. No high income
taxpayers in the 1940s were paying 92% of their incomes in taxes. For example,
very favorable tax rates on capital gains were exploited by wealthy people to
greatly reduce taxes owed from since 1921 ---
https://en.wikipedia.org/wiki/Capital_gains_tax_in_the_United_States#History
Beginning in 1942, taxpayers
could exclude 50% of capital gains on assets held at least six months or
elect a 25% alternative tax rate if their ordinary tax rate exceeded
50%.[11] From 1954 to 1967, the maximum capital gains tax rate was 25%
Secondly taxpayers during World War II had
various alternatives to earn income tax free such as Series E, F and G U.S.
Treasury Bonds ---
https://en.wikipedia.org/wiki/War_bond#United_States_2
There were and still are various other ways to exempt or
reduce ncome from taxation ---
https://en.wikipedia.org/wiki/Tax_exemption#exempt_income
Probably the worst thing about "The Mother of All
Cognitive Illusions" is the total ignoring of why virtually all advanced nations
(and most others) greatly reduced highest marginal tax rates between 1979 and
2002, because high marginal top tax rates were counter
productive to economic growth and prosperity.
http://www.econlib.org/library/Enc/MarginalTaxRates.html
Those nations like Sweden that did not offer lower capital gains rates and other
tax avoidance alternatives took terrible hits by confiscating high incomes
essential to their economies. When they at last discovered how counter
productive these high tax rates were to their economies they quickly reduced the
top marginal rates. Also remember that some nations like Denmark that still have
relatively high marginal rates are including more services in with their tax
dollars like free medical care and free college and job training (for the top
35% of the students).
Table 1 Maximum
Marginal Tax Rates on Individual Income |
*. Hong
Kong�s
maximum tax (the
�standard
rate�)
has normally been 15 percent, effectively capping the marginal rate
at high income levels (in exchange for no personal exemptions). |
**. The
highest U.S. tax rate of 39.6 percent after 1993 was reduced to 38.6
percent in 2002 and to 35 percent in 2003. |
|
|
1979 |
1990 |
2002 |
Argentina |
45 |
30 |
35 |
Australia |
62 |
48 |
47 |
Austria |
62 |
50 |
50 |
Belgium |
76 |
55 |
52 |
Bolivia |
48 |
10 |
13 |
Botswana |
75 |
50 |
25 |
Brazil |
55 |
25 |
28 |
Canada (Ontario) |
58 |
47 |
46 |
Chile |
60 |
50 |
43 |
Colombia |
56 |
30 |
35 |
Denmark |
73 |
68 |
59 |
Egypt |
80 |
65 |
40 |
Finland |
71 |
43 |
37 |
France |
60 |
52 |
50 |
Germany |
56 |
53 |
49 |
Greece |
60 |
50 |
40 |
Guatemala |
40 |
34 |
31 |
Hong Kong |
25* |
25 |
16 |
Hungary |
60 |
50 |
40 |
India |
60 |
50 |
30 |
Indonesia |
50 |
35 |
35 |
Iran |
90 |
75 |
35 |
Ireland |
65 |
56 |
42 |
Israel |
66 |
48 |
50 |
Italy |
72 |
50 |
52 |
Jamaica |
58 |
33 |
25 |
Japan |
75 |
50 |
50 |
South Korea |
89 |
50 |
36 |
Malaysia |
60 |
45 |
28 |
Mauritius |
50 |
35 |
25 |
Mexico |
55 |
35 |
40 |
Netherlands |
72 |
60 |
52 |
New Zealand |
60 |
33 |
39 |
Norway |
75 |
54 |
48 |
Pakistan |
55 |
45 |
35 |
Philippines |
70 |
35 |
32 |
Portugal |
84 |
40 |
40 |
Puerto Rico |
79 |
43 |
33 |
Russia |
NA |
60 |
13 |
Singapore |
55 |
33 |
26 |
Spain |
66 |
56 |
48 |
Sweden |
87 |
65 |
56 |
Thailand |
60 |
55 |
37 |
Trinidad and Tobago |
70 |
35 |
35 |
Turkey |
75 |
50 |
45 |
United Kingdom |
83 |
40 |
40 |
United States |
70 |
33 |
39** |
|
Source: PricewaterhouseCoopers;
International Bureau of Fiscal Documentation. |
**How to
Mislead With Statistics
Market
Capitalization ---
https://en.wikipedia.org/wiki/Market_capitalization
Market cap is given by the formula MC = N × P where MC is the market
capitalization, N is the number of shares outstanding, and P is the closing
price per share.
Jensen
Comment
Although the above article contends MC is the "equity value of a company", I
flatly deny that a market capitalization value is "the" equity value of the
company unless all or most of the shares are traded such as in a cash
acquisition of all the shares. The closing price (Marginal P) may only be 100 or
less shares, and their price per share will be vastly different than the
(usually unknown) closing value of all shares divided by all outstanding shares.
No analyst in the world contends that the closing (marginal) price of a
company's shares is indicative of the total equity value of a corporation.
First and
foremost the closing (marginal) price based in a small trade of only a few
shares does not reflect control of the company. The element of control (which
may entail less than 50% of the shares) is of enormous value (and risk) that is
not reflected in a small marginal trade (e.g., 100 shares) at the end of a
trading day.
Secondly and
importantly the closing (marginal) price of a few shares reflects total market
ups and downs that often have little to do with the underlying long-term equity
value of a given company such as the downslide of market closing prices of Ford
and Tesla following a missile attack on a couple of
fuel tanks in Saudi Arabia. Tesla stock prices may actually decline as part of a
general market price slide even though Tesla cars do not consume gasoline. I
don't think Iran's recent missile attack on a Sauidi oil field had any impact on
the long-term value of Ford and Tesla.
Thirdly,
daily closing prices of small trades are impacted by short-term trading
strategies and liquidity preferences of investors who only trade relatively
small numbers of shares relative to total outstanding shares. Total (unknown)
equity values of Ford and Tesla change very little day-to-day as a rule whereas
the short-term trader profits and losses my change enormously. Small trades take
place most of the time even when total equity value is unchanged.
Baloney Stat BS: Tesla
is now the highest-valued automaker in US history
Tesla is now the highest-valued automaker in US history ---
https://markets.businessinsider.com/news/stocks/tesla-stock-price-rally-most-valuable-us-car-maker-history-2020-1-1028804022
This kind of headline should not be allowed
Tesla’s
market cap is now double Ford’s ---
https://qz.com/1779609/teslas-market-cap-is-now-more-than-double-fords/
Jensen
Comment
So now let's compare what factors (aside from small trader speculations) are
extremely important to the total equity value of Tesla versus Ford.
Tesla Inc.
Ford Motor Company ---
https://en.wikipedia.org/wiki/Ford_Motor_Company
Even though
GAAP accounting statements are not based upon current values of all assets and
liabilities GAAP accounting suggests Tesla
has a lot less total equity value than Ford? Anybody who invests
entirely on Tesla instead of Ford in pension savings is gambling big time. The
risk of gambling a small proportion of savings in Tesla can be diversified, but
the risk of gambling everything on Tesla is far greater than investing
everything in Ford.
The reason GAAP accounting does not report current value of a company's total
equity is that nobody in the world knows how to compute total equity value
unless future streams of the company's net cash flows are
known to infinity.
What accountants call current "exit
values" of most assets and liabilities are prohibitively costly to estimate with
reliability and the sums of asset and liability exit values are misleading as
estimates of total equity value because exit values of individual items do not
reflect interactive higher order interaction covariances ("value
in use") that are usually impossible to estimate along with the values of
intangibles that nobody knows how to estimate such as the current value of the
labor forces of Apple, Microsoft, Tesla, and Ford. The value of an intangible
employee (think Elon Musk) is fundamentally different than the tangible value of
a building or machine (think robot), because management cannot control the use
of an employee in the same manner as a building or machine. A machine cannot by
itself decide to change companies or retire from the company. But an employee
can simply decide to no longer work for a company. Slavery
was prohibited long ago.
Two reasons Ford is fundamentally more
valuable than Tesla are financial scale and diversification. Ford owns a lot
more tangible assets than Tesla that will be valuable if both Ford and Tesla
fail. Ford has a lot more borrowing capacity since Tesla is so deep in debt
relative to assets. Ford is much more likely to be bailed out by the USA
government in times of financial emergency due to the bargaining power of four
times as many employees and the dependency of local communities across the USA
on tax revenues from Ford assets and employees.
Baloney Stat BS: Tesla
is now the highest-valued automaker in US history
Tesla is now the highest-valued automaker in US history ---
https://markets.businessinsider.com/news/stocks/tesla-stock-price-rally-most-valuable-us-car-maker-history-2020-1-1028804022
This kind of headline should not be allowed
Why Hydrogen Fuel Cell Cars are Tesla's Biggest Threat
https://www.businessinsider.com/hydrogen-fuel-cell-cars-teslas-biggest-threat-2019-12
Two reasons Ford and the other larger
vehicle manufacturers are fundamentally more
valuable than Tesla are financial scale and diversification. Ford owns a lot
more tangible assets than Tesla that will be valuable if both Ford and Tesla
fail. Ford has a lot more borrowing capacity since Tesla is so deep in debt
relative to assets. Ford is much more likely to be bailed out by the USA
government in times of financial emergency due to the bargaining power of four
times as many employees and the dependency of local communities across the USA
on tax revenues from Ford assets and employees.
Suppose that new technology such as
cheap hydrogen fuel cells make both lithium battery and gasoline powered cars
obsolete. Ford has more cash, more factories, more employees, and more borrowing
power (credit) to quickly shift to manufacture of hydrogen-powered vehicles..
Tesla is stuck with one car ,manufacturing factory (using tents) in the USA.
lousy credit, and many fewer employees to quickly compete in the USA's hydrogen
vehicle market.
Tesla is a Ponzi fraud!
**How to Mislead
With Statistics
Market
Capitalization ---
https://en.wikipedia.org/wiki/Market_capitalization
Market cap is given by the formula MC = N × P where MC is the market
capitalization, N is the number of shares outstanding, and P is the closing
price per share.
Jensen Comment
Although the above article contends MC is the "equity value of a company", I
flatly deny that a market capitalization value is "the" equity value of the
company unless all or most of the shares are traded such as in a cash
acquisition of all the shares. The closing price (Marginal P) may only be 100 or
less shares, and their price per share will be vastly different than the
(usually unknown) closing value of all shares divided by all outstanding shares.
No analyst in the world contends that the closing (marginal) price of a
company's shares is indicative of the total equity value of a corporation.
First and
foremost the closing (marginal) price based in a small trade of only a few
shares does not reflect control of the company. The element of control (which
may entail less than 50% of the shares) is of enormous value (and risk) that is
not reflected in a small marginal trade (e.g., 100 shares) at the end of a
trading day.
Secondly and
importantly the closing (marginal) price of a few shares reflects total market
ups and downs that often have little to do with the underlying long-term equity
value of a given company such as the downslide of market closing prices of Ford
and Tesla following a missile attack on a couple of
fuel tanks in Saudi Arabia. Tesla stock prices may actually decline as part of a
general market price slide even though Tesla cars do not consume gasoline. I
don't think Iran's recent missile attack on a Sauidi oil field had any impact on
the long-term value of Ford and Tesla.
Thirdly, daily
closing prices of small trades are impacted by short-term trading strategies and
liquidity preferences of investors who only trade relatively small numbers of
shares relative to total outstanding shares. Total (unknown) equity values of
Ford and Tesla change very little day-to-day as a rule whereas the short-term
trader profits and losses my change enormously. Small trades take place most of
the time even when total equity value is unchanged.
Tesla’s
market cap is now double Ford’s ---
https://qz.com/1779609/teslas-market-cap-is-now-more-than-double-fords/
Jensen Comment
So now let's compare what factors (aside from small trader speculations) are
extremely important to the total equity value of Tesla versus Ford.
Tesla Inc.
Ford Motor Company ---
https://en.wikipedia.org/wiki/Ford_Motor_Company
Even
though GAAP accounting statements are not based upon current values of all
assets and liabilities GAAP
accounting suggests Tesla has a lot less total equity value than Ford?
Anybody who invests entirely on Tesla instead of Ford in
pension savings is gambling big time. The risk of gambling a small proportion of
savings in Tesla can be diversified, but the risk of gambling everything on
Tesla is far greater than investing everything in Ford.
https://www.investopedia.com/ask/answers/122314/what-difference-between-market-capitalization-and-market-value.asp
The reason GAAP accounting does not report current value of a company's total
equity is that nobody in the world knows how to compute total equity value
unless future streams of the company's net cash flows are
known to infinity.
What accountants call current "exit values"
of most assets and liabilities are prohibitively costly to estimate with
reliability and the sums of asset and liability exit values are misleading as
estimates of total equity value because exit values of individual items do not
reflect interactive higher order interaction covariances that are usually
impossible to estimate along with the values of intangibles that nobody knows
how to estimate such as the current value of the labor forces of Apple,
Microsoft, Tesla, and Ford. The value of an intangible employee (think Elon
Musk) is fundamentally different than the tangible value of a building or
machine (think robot), because management cannot control the use of an employee
in the same manner as a building or machine. A machine cannot by itself decide
to change companies or retire from the company. But an employee can simply
decide to no longer work for a company.
Slavery was prohibited long ago.
**How
to Mislead With Charts
MIT: Our pathetically slow shift to clean energy, in five
charts ---
https://www.technologyreview.com/s/614917/our-pathetically-slow-shift-to-clean-energy-in-five-charts/
Jensen Comment: Some of the charts are misleading. All "renewables" are
not carbon free. Up here amidst a national forest "renewable" biomass electric
generating plants burn wood chips with smoke pouring out of tall chimneys like
they are coal plants. People are also burning a lot of "renewable" split logs in
wood stoves that send carbon into the atmosphere far worse than my propane
stoves.
**How to
Mislead With Statistics (Note the bias ratings)
Which Pollsters To Trust In 2018 By Nate Silver
Filed under 2018 Election
https://fivethirtyeight.com/features/which-pollsters-to-trust-in-2018/
Climate Alarmists (think NASA) Caught Manipulating Temperature
Data Yet Again ---
https://www.blabber.buzz/conservative-news/603035-climate-alarmists-caught-manipulating-temperature-data-yet-again-special?utm_source=c-pm&utm_medium=c-pm-email&utm_term=c-pm-GI
**How to Mislead With Statistics: What can possibly go wrong when
comparing first-year incomes of history versus computer science graduates?
The U.S. Department of Education on Wednesday released data on first-year
earnings of college graduates, for the first time broken down by program level
---
https://www.insidehighered.com/news/2019/11/21/federal-government-releases-earnings-data-thousands-college-programs?utm_source=Inside+Higher+Ed&utm_campaign=6ed01ffd23-DNU_2019_COPY_02&utm_medium=email&utm_term=0_1fcbc04421-6ed01ffd23-197565045&mc_cid=6ed01ffd23&mc_eid=1e78f7c952
Jensen Comment
Firstly, earnings in the first year of a job may be of lesser importance than
other things. For example, it's well known that accounting graduates after
five-years of study and a masters degree earn less on average than computer
science and engineering graduates with four-year degrees. But accounting
graduates know that jobs are plentiful and the most desired starting jobs with
the largest multinational auditing, consulting, and tax firms are more important
than starting jobs at possibly higher salaries with other companies. The reasons
are many, the most important being the investment in training and experience
given by the largest multinational accounting firms.
Unlike physicians and engineers accounting graduates are not specialists when
they graduate. They rely upon the training and experience that their
first employers provide to them to become specialists. In fact more often than
not they don't even intend to stay with their first employers after they get
that training and experience.
What is known is that training and exposure to high paying auditing and tax
clients can lead to fast tracks to high-paying executive opportunities as well
as exciting challenges like getting into the FBI and other law enforcement
agencies. Some accountants hope to start out in the IRS that spends a lot on
training and offers opportunities later on to get a high paying tax accounting
job with business firms. Some accounting graduates intend to get all that
training and experience so they can start up their own firms.
Secondly, large accounting firms are now also providing non-salary benefits
including financial assistance for passing the CPA examination and help in
paying off student loans and family-friendly job assignments that allow young
parents to work out of their homes much of the time. And there are other
disciplines where non-salary benefits include time off. Many college
graduates become school teachers who want summers free to be with their young
children full time when those children are not in school.
Thirdly, in many fields those first-year incomes are not full salaries.
Especially in marketing and finance (think stock brokers) those incomes have a
low base salary plus commissions. Commissions are great if you bust your butt 80
hours a week, including becoming super active in your church and in your
community to make sales contacts and/or spend some of your earnings on travel
expenses and entertainment expenses that are not fully paid by your employer.
Some graduates don't want to bust their butts 80 hours per week drumming up
sales commissions.
Fourthly, reported first year salaries are often biased samples. Think of
where humanities graduates go after graduation. A goodly number have no
first-year incomes because they go on to graduate schools (think further study
in law schools and MBA programs). The ones that do not go on for graduate
studies may well be comprised of many graduates who had low GRE or GMAT scores
and could not get into top graduate programs. They're more likely to become
those over-qualified McJobs workers we hear so much about.
Fifthly, think of the poor slobs who graduate from college and join the
military --- Yeah those poorly-paid slobs who rise to the ranks of among
officers to retire in their early 40s with great lifetime pensions and
medical benefits and go on to double dip in life with new careers on top of
their retirement benefits. Their so-called "first-year earnings" in the military
are highly misleading when you forget to add in the retirement benefits.
Sixtly, some (most?) high-paying jobs are less secure. Yeah, school teachers
may have low-starting salaries but they're usually on a tenure track for job
security. Civil servants have lower incomes but they cannot be fired as long as
they're not sent to prison.
I could go on and on, but I think you get the point that studies like the one
above that compare first-year earnings can lead college students into making
lousy career choices.
**How to Mislead With
Statistics
Here's the salary breakdown for Yale's MBA class of 2019,
including the industries that are paying its grads the most ---
https://www.businessinsider.com/the-starting-salaries-for-yales-2019-mba-graduates-2019-12#1-law-8
Jensen Comment
One thing that's misleading is the category "Accounting and Finance." This is
more finance than accounting since most MBA programs, including that of Yale, do
not provide nearly enough accounting to sit for the CPA examination or get a job
in auditing or tax accounting. Any accountants graduating from from most MBA
programs took their accounting, auditing, and tax as undergraduates.
Secondly, those $125,000 annual starting salaries are averages,
and averages are distorted by distribution variations, skewness, and outliers.
More importantly, most of those high-paying starting salaries are
in urban centers like Boston, NYC, Chicago, San Francisco, Washington DC, and
Los Angeles. A starting salary of $125,000 in those cities won't go as far as a
$70,000 salary in Des Moines, Topeka, Oklahoma City, and San Antonio. In San
Francisco you may have to live in your van on only $125,000 per year.
This of course does not mean that some of those high-paying
starting salaries do not open the gates to much higher compensation a few years
down the road. But the best opportunities often depend upon the undergraduate
majors. A computer science, Chinese language, or engineering undergraduate
usually faces more opportunities with a Yale MBA diploma than an undergraduate
in art, music, or history having the same Yale MBA diploma.
And we have to ask why Ivy League MBA diplomas are usually worth
more than an MBA diploma from Cactus Gulch State University?
My answer is that it's mostly the high admission standards of the Ivy League,
University of Chicago, Stanford, and other prestigious university MBA programs.
It's the high standards of admission that count more than the top A
grades that most every graduate gets in the prestigious MBA programs.
My main point is that any measure of
central tendency cannot represent the total distribution without being
potentially misleading. It takes a graphic or some table of outcomes showing the
entire distribution.
One of the main distortions is to not
give special consideration to those who remain unemployed after graduation such
as an MBA graduate who elects for a time to be a parent at home with zero salary
or a relatively low salary from part-time employment. People get college degrees
with the long-run in mind, and doing an analysis at a point in time can be
misleading.
I would also like to see a factoring
out of some outliers. Two of my close friends at Stanford University decades ago
were an MBA student and his wife who lived in an apartment next door for a time.
Jerry graduated with an MBA and went to work an enormous salary where he would
have worked had he never gone to college. His father owned what was possibly the
largest car dealership in the State of Minnesota. Jerry started out the day
after graduation as the CEO.
Jerry was an outlier, but there are
likely to be several such outliers each year where graduates go to work at high
salaries in family businesses. Another example of an MBA friend at the time is a
graduate whose father owned the largest department store in Sydney, Australia.
Another example, is one of my former students who today is a billionaire (at
least on paper). He was a CEO of his own company when he commenced at Trinity
University as a freshman at age 18.
And there are bound to be some outliers
of unemployed graduates, including those that are unemployed for reasons other
than parenthood. MBA graduates are commonly not earning much to begin with
because they're commencing their own startups. I recall one Stanford MBA
graduate who partnered with his sister to form an ultimately successful chain of
cookie stores that financed his failed attempt to become a world-famous author.
In the first year of graduation his income was negative.
And there's the issue of salary before
and after getting a degree of any kind. I don't think Jack Palance's Hollywood
income changed because he got a degree from Stanford after he was already a
famous actor.
These are the types of distortions that
I have in mind when I talk about outliers and other aberrations in
distributions.
The Atlantic: Unhappy Socialists of South America ---
https://www.theatlantic.com/ideas/archive/2019/11/evo-morales-finally-went-too-far-bolivia/601741/?utm_source=newsletter&utm_medium=email&utm_campaign=atlantic-daily-newsletter&utm_content=20191111&silverid-ref=NTk4MzY1OTg0MzY5S0
When an independent observer mission from the Organization of American
States published its audit of Bolivia's election yesterday, the game was
finally up. After the OAS announced that there had been “clear
manipulations” of the vote in a scathing report, Morales agreed to new
elections. A few hours later, as scores of his own allies started to abandon
the sinking ship, he resigned from office. Though the future of Bolivian
democracy still remains radically uncertain, this is a momentous turning
point: one of the first times in recent memory that an authoritarian
populist has been forced to vacate his office, because his own compatriots
would not stand for his abuses.
Morales’s departure from office marks both a sea change in Latin American
politics and a stinging rebuke to the naďveté of parts of the Western left.
Even though there had always been strong evidence of their anti-democratic
leanings, new socialist leaders such as Hugo Chávez in Venezuela and Morales
in Bolivia were widely celebrated throughout the first decade of the 21st
century as the future face of Latin America.
Now virtually nothing remains of their erstwhile (socialist) appeal. Chávez
and his successor, Nicolás Maduro, have made Venezuela deeply authoritarian
and shockingly poor. Meanwhile, the Bolivian people have come out in great
numbers to stop Morales from violently crushing their protests. As one of
the most famous slogans of the Latin American left holds, El pueblo unido
jamás será vencido: The people united will never be defeated.
From east to west, and south to north, the dream of Latin America’s
so-called pink wave has turned into a nightmare. And the many scholars,
writers, and politicians who have for years sung the praises of aspiring
dictators like Maduro and Morales should not be easily forgiven for
sacrificing the rights of distant people on the altar of their rigid
ideology.
Continued in article
Jensen Comment
The so-called pink wave moved north among the faculties and
students of universities in the USA who applaud tens of trillions of dollars
in annual spending proposals for green initiatives, free medical
services, free medications, free nursing homes, free college, free
preschool, free housing, free food, guaranteed annual income, reparations,
open borders, legalized prostitution, etc. to the tune of over $10+ trillion
per year --- spending proposals that threaten
whatever's left of capitalism in the Western hemisphere.
Meanwhile capitalism thrives on the other side of the globe
in parts of Europe and in Asia.
Bernie Leads His Party to Open Borders
---
https://townhall.com/columnists/patbuchanan/2019/11/12/bernie-leads-his-party-to-open-borders-n2556311?utm_source=thdaily&utm_medium=email&utm_campaign=nl&newsletterad=11/12/2019&bcid=b16c6f948f297f77432f990d4411617f&recip=17935167
While a
move is underway to destroy the American Dream of rags to riches (by taxing away
the riches) the Chinese dream is on the rise.
The Chinese Dream
How a Chinese billionaire went from making $16 a month in a factory to being one
of the world's richest self-made women with an $8.3 billion real-estate empire
---
https://www.businessinsider.com/worlds-richest-self-made-woman-wu-yajun-net-worth-2019-2
Top 50 Billionaires in China ---
https://en.wikipedia.org/wiki/List_of_Chinese_by_net_worth
Jensen
Comment
The question for students to debate is why a supposed
communist country allows so many billionaires to rise up from poverty.
That's supposed to happen in the USA where a child growing up in deep
poverty (think Oprah Winfrey or Howard Shultz) became a multi-billionaires.
But is it also supposed to happen under communism? If
so, why?
One reason is that many billionaires can afford to pour lots
of money into high risk ventures. When's the last time you heard about a high
risk (think Silicon Valley) venture in Europe?
NYT: The Happy, Healthy Capitalists of Switzerland
---
https://www.nytimes.com/2019/11/02/opinion/sunday/switzerland-capitalism-wealth.html
Like many progressive intellectuals, Bernie
Sanders traces his vision of economic paradise not to socialist
dictatorships like Venezuela but to their distant cousins in Scandinavia,
which are just as wealthy and democratic as the United States but have more
equitable distributions of wealth, as well as affordable health care and
free college for all.
There is, however, a country far richer and
just as fair as any in the Scandinavian trio of Sweden, Denmark and Norway.
But no one talks about it.
This $700 billion European economy is among the
world’s 20 largest, significantly bigger than any in Scandinavia. It
delivers welfare benefits as comprehensive as Scandinavia’s but with lighter
taxes, smaller government, and a more open and stable economy. Steady growth
recently made it the second richest nation in the world, after Luxembourg,
with an average income of $84,000,
or $20,000 more than the Scandinavian average. Money is not the final
measure of success, but surveys also rank this nation as one of the world’s
10 happiest.
This less socialist but more successful utopia
is Switzerland.
While widening its income lead over Scandinavia
in recent decades, Switzerland has been catching up on measures of equality.
Wealth and income are distributed across the populace almost as equally as
in Scandinavia, with the middle class holding about 70 percent of the
nation’s assets. The big difference: The typical Swiss family has a net
worth around $540,000, twice its Scandinavian peer.
Switzerland did draw 15 minutes of media attention
around 2010, when Obamacare was still new — but only for its
health care system, which requires
all residents to buy insurance from private providers and subsidizes those
who can least afford it. Admirers said Swiss health care had something for
everyone: universal coverage for liberals, private providers and consumer
choice for conservatives.
But for the most part, intellectuals ignore
Switzerland as a model, perhaps put off by its exaggerated reputation as a
shady little tax haven, where Nazi gold and other illicit fortunes hide
behind strict bank secrecy laws. In 2015,
Switzerland agreed under pressure to share bank records
with foreign tax authorities, but that has not slowed the economy at all.
Switzerland always was more than secretive banks.
Capitalist to its core, Switzerland imposes
lighter taxes on individuals, consumers and corporations than the
Scandinavian countries do. In 2018 its top income tax rate was the lowest in
Western Europe at 36 percent, well below the Scandinavian average of 52
percent. Government spending amounts to a third of gross domestic product,
compared with half in Scandinavia. And Switzerland is more open to trade,
with a share of global exports around double that of any Scandinavian
economy.
Streamlined government and open borders have helped
make this landlocked, mountainous country an unlikely incubator of globally
competitive companies. To build wealth, a country needs to make rich things,
and an M.I.T. ranking of nations by the complexity of the products they
export
places Switzerland second behind Japan,
well ahead of the Scandinavian countries, whose average rank is 15.
The Swiss excel in just about every major
industry other than oil, often by targeting specialized niches, such as
biotech and engineering. The country is home to 13 of the top 100 European
companies, more than twice as many as in the three Scandinavian nations
combined. And most top Swiss firms dwarf Scandinavian peers. Nestlé, with a
stock market value of $320 billion, is 15 times larger than its closest
Scandinavian rival.
Though major multinationals are concentrated in
big cities, the Swiss economy is as decentralized as its political system.
Traveling southwest from Zurich to Geneva recently, I was struck by how many
iconic Swiss exports also originate in its provinces — Swiss Army knives
from Schwyz, watches from Bern, St. Bernard puppies from a mountain pass in
Valais, cheese and chocolates from Fribourg. Small companies anchor the
economy, accounting for two of every three jobs. Only one in seven Swiss
work for the government, about half the Scandinavian average.
No other nation’s currency has been rising
faster against its trading partners, and normally a rising franc should
erode Swiss exports by making them more expensive. Instead, while most rich
countries (including Scandinavia’s) saw their share of global exports fall
over the past decade, Switzerland’s continued to rise. Such is the
reputation of its engineers and chocolatiers that customers readily pay more
for Swiss goods.
The premium the world is willing to pay for
Swiss goods and services helps deter capital flight and stabilize the
economy. Switzerland has not been hit by a domestic financial crisis since
the 1970s; the Scandinavian countries were wracked by crises in the 1990s
and suffered sharper downturns than Switzerland did following the global
crisis of 2008.
If there is any fault line, it is that in
trying to slow the rise of the franc, Switzerland cut interest rates to
record lows ahead of its European peers, triggering a lending boom that has
driven private corporate and household debt up to 250 percent of G.D.P., a
risky height. No paradise is perfect.
For all its local charms, Switzerland is
worldly in the extreme. The Swiss are a polyglot mix of German, French and
Italian speakers, many intimidatingly fluent in multiple languages. The
foreign-born population has been increasing for more than a century and
accounts for a quarter of the whole, 40 percent non-European Union.
True, the rise of anti-immigrant parties across
Europe has an offshoot in Switzerland. The country has always been choosy,
accepting new arrivals based on their professional résumé more than family
ties or humanitarian need. But Australia and Canada also filter immigrants
to fill jobs and are widely studied models of how rich economies can survive
the aging of their domestic work forces.
Switzerland has been welcoming more immigrants
than any Scandinavian country since the 1950s. It is on track to accept more
than 250,000 immigrants between 2015 and 2020, expanding its population by 3
percent. That immigration rate is nearly double the Scandinavian average,
and one of the highest among large, developed countries. Immigrants are also
significantly more likely to hold jobs in Switzerland, in part because most
are required to land one before they arrive.
Continued in article
Jensen Comment
Comparisons of Switzerland with the USA is difficult because of the population
differences (less than 9 million residents versus over 350 million residents),
land mass differences, natural resource differences, ethnicity differences, and
the total lack of Swiss aspirations to get involved in foreign strife and wars.
The Swiss are very controlling about immigration whereas in the USA illegal
immigration is rampant. With controlled immigration Switzerland expands its
population by roughly 3% annually. In the USA legal (controlled) immigration is
nearly 5% whereas the undocumented immigrants in the USA comprise more than the
entire population of Switzerland. It's virtually impossible to determine the
exact number, but it's well in excess of 12 million.
Whereas Switzerland loves its brand of capitalism, a rising
population in the USA is clamoring for big government socialism and open
borders, especially among youth and universities. Not so in Switzerland. How
foolish!
Open immigration can’t exist with a strong social
safety net; if you’re going to assure healthcare and a decent income to
everyone, you can’t make that offer global ---
Paul Krugman
https://www.goodreads.com/quotes/724654-open-immigration-can-t-exist-with-a-strong-social-safety-ne
**
How to Mislead With Bad Analogies
"Under this plan, 45 percent (tantamount to
complete control) of the board of directors in any large corporation with
at least $100 million in annual revenue, corporations with at least $100 million
in balance sheet total, and all publicly traded companies will be directly
elected by the firm’s workers – similar to what happens under “employee
co-determination” in Germany, which long has had one of the most productive and
successful economies in the world."
Bernie Sanders
https://berniesanders.com/issues/corporate-accountability-and-democracy
Jensen Comment
Paul Krugman recently
wrote a piece defending Bernie Sanders' economics and plans for worker
control of corporations. Bernie Sanders skates on thin ice when comparing USA
corporations with German corporations. A most important difference in these two
nations is how capital investment is raised, especially high-risk financial
investment.. Germany traditionally never has had a lot
of success raising equity capital --- largely because of the lack of
control equity (capital stock) investors have on German corporations.
Historically up to and including today, German business
firms raise most of their capital from private sector banks that
limit the power that employees have on spending by corporations in Germany. In
the USA a much greatr share of corporate funding is raised from private sector
investors who have much more control of corporations and can greatly restrict
the power of workers to control how corporations spend their resources. Elon
Musk, for example, inhibits all efforts of Tesla employees to form unions.
Bernie Sanders wants to give workers and their unions complete
control of how large corporations in the USA spend their resources. Doing so
will among other things destroy the stock markets and accordingly all pension
funds now dependent upon stock prices. In a large corporation any shareholder
bloc that controls 45% of the shareholder vote essentially controls the company
(Elon Musk controls Tesla with a mere 22% oif Tesla's shares.)
What Bernie Sanders does not tell you is that he cannot have the
corporate democracy that he promises by giving workers control of large
companies in the USA. The reason is that those workers will not supply the
capital investments needed to create and sustain those companies. Therefore,
workers will have to bargain with the private sector to provide capital, and the
private sector will demand after-tax returns on their investments just like
German banks require after-tax returns on their investments in German
corporations.
And the German banks require thresholds of
after-tax returns which greatly limits the power of the German government
to tax those banks.
German corporations are not the worker honey pots that Sanders
wants for USA workers.
And for those who still argue in favor of the German way to raise
capital from the private sector, I remind you that Germany has no Silicon Valley
and has a poor track record for developing risky technology companies, new
patents for drugs (where over half come from the USA), If you want innovation
you have to somehow provide incentives to invest in high risk ventures.
German banks are not known for taking on great financial
risks.
New startup ventures are not flocking to Germany or trying to
sell their shares to German equity investors or German banks.
Chronicle of Higher Education: Free College Fantasy
https://reason.com/2019/12/09/ig-report-fbi-fisa-carter-page-trump-media/
The proposals floated by
presidential candidates are nonsensical. There’s a better way.
This
spring, Sen. Elizabeth Warren unveiled an
ambitious policy proposal:
a
$1.25-trillion plan to make college more affordable. It includes canceling
up to $50,000 in student-loan debt for 95 percent of borrowers, and putting
billions of dollars into historically black colleges and $100 billion in new
money toward the federal Pell Grant program.
Almost as
an afterthought, the plan also includes a proposal to make tuition free at
every public college and university in America. While light on details,
Warren’s version of free college seems to be
modeled after
Sen. Bernie Sanders’s. Sanders, of course, built his improbable 2016 primary
campaign in part by igniting millennial student debtors who were outraged by
the broken promise of affordable higher education. Now every serious
Democratic contender has had to propose some version of free college — or,
as Sen. Amy Klobuchar and Mayor Pete Buttigieg have done,
explain why not.
The broad
case for free college is strong. Many states have slashed public funding for
higher learning, shifting the burden to students and parents. Private
colleges, in pursuit of status and fame, have hiked prices into the
stratosphere. As real tuition at public universities
has tripled
over the
past three decades while middle-income wages have stagnated, the federal
government’s main response was to lend students ever-larger sums of money to
make up the difference, with no control over how much colleges charged or
whether the degrees were any good. It was a policy mistake of epic
proportions, leaving the path to economic mobility badly narrowed and a
generation of collegians saddled with unaffordable loans.
Continued in article
With new government programs will come price
controls. Medicare-for-All severely constrains what physicians, hospitals, and
other medical providers earn while at the same time setting new rules on work
loads. Free=College-for-All will greatly constrain what colleges and faculty
earn and add workload restrictions such as required teaching loads of four or
more courses per term. Leaves will be curtailed as well as research support.
In some European nations and elsewhere college and
trade skill training is free, but admission is restricted to the top third of
high school graduates ---
http://faculty.trinity.edu/rjensen/HigherEdControversies.htm#Tertiary
Restricting college and trade school admissions to the top third of high school
classes will never fly in the USA.
Furthermore the wages of teachers is severely limited in European nations and
class sizes are enormous.
For Democratic 2020 Presidential candidates the
media never reports the aggregated cost of promised for green
initiatives, free medical services, free medications, free nursing homes, free
college, free preschool, free housing, free food, guaranteed annual income,
reparations, open borders, legalized prostitution, etc. to the tune of over $10+
trillion per year. My guess is that
the total annual added aggregate cost for these promised programs is over $20
trillion per year.
Many voters for Trump would like to not vote for him
in 2020, but they may have to if the chosen Democratic Party contender intends
to ruin the USA economy.
Joe Biden Proposes $1 Trillion in New Corporate
Taxes ---
https://www.wsj.com/articles/joe-biden-proposes-1-trillion-in-new-corporate-taxes-11575492332?mod=djemCFO
Democratic presidential candidate Joe Biden proposed nearly $1 trillion in
new corporate taxes on Wednesday as he sought to generate more revenue to
pay for his policy plans on health care, climate, infrastructure and
education.
One of his new
taxes
would go after companies
such as
Amazon.com Inc. that
have years when they report profits to investors but show little or no U.S.
tax costs. A second would double the minimum tax rate on overseas income of
U.S.-based multinationals.
Until now, Mr. Biden has largely confined his ideas to rolling back parts of
the 2017 Republican tax cut and pursuing policies that the Democratic Obama
administration, in which he served as vice president, couldn’t get through
Congress.
The new proposals come atop Mr. Biden’s previous calls for tax increases,
which would push the corporate tax rate to 28% from 21%, tax unrealized
capital gains at death and push the top rate on individuals to 39.6% from
37%.
Mr. Biden’s proposed tax increases now total $3.2 trillion over a decade,
though his campaign confirmed on Wednesday that he also supports repealing
the $10,000 cap on the state and local tax deduction, a tax cut that would
disproportionately benefit some of the high-income households who would be
hit by his tax increases.
Still, Mr.
Biden’s tax plans are more modest than those of his main rivals for the
Democratic presidential nomination. Sens. Elizabeth Warren (D., Mass.) and
Bernie Sanders (I., Vt.)
have proposed wealth taxes on the super-rich.
Both of them, along with Mayor Pete Buttigieg, have called for returning the
corporate tax rate to 35%.
Jensen Comment
Continued in article
Jensen Comment
Bernie Sanders finally convinced Joe Biden as well as Elizabeth Warren that
voters are too stupid to understand how $1 trillion (or much more in the case of
Sanders and Warren) in new taxes is really a tax increase on the lower income
and middle income taxpayers. Biden at last believes that voters are too dumb to
understand that business firms don't pay taxes. Biden,
Sanders, and Warren think voters are just
too uneducated to understand that business firms don't pay taxes.
Instead business firms collect taxes from their customers. Nearly all companies
contributing to Biden's $1 trillion in new corporate taxes will raise prices to
(gasp) customers of Amazon, Walmart, etc. who mostly are lower and middle income
customers.
And tariffs will have to be increased on imported goods (think
sugar, TV sets, mobile phones and computers) to make it possible for USA
corporations to raise prices enough to collect the added trillion (or trillions)
in new business taxes.
In their zeal to attract ignorant voters, I don't think Biden,
Sanders, and Warren want to let on that taxing trillions from business firms and
investors will kill the stock markets. These politicians hope voters are too
stupid to realize how much their own futures depend on viable stock markets and
other capital markets. The vast pension funds of workers will get wiped out if
those capital markets get wiped out.
Biden,.Sanders, and Warren think voters are too stupid to realize
the mammoth size of the number $1 trillion or more in taxes. The CBO's estimated
total Federal revenue from all sources for 2019 is
$3.490 trillion ---
https://en.wikipedia.org/wiki/United_States_federal_budget
What's another trillion or more in new taxes?
As the saying goes: "The Road to Hell is Paved With Good Intentions."
Exhibit A is Venezuela.
Why is Capitalist Finland so Rich?
https://marginalrevolution.com/marginalrevolution/2011/03/why-is-finland-so-rich.html
Read the comments --- Finland encourages wealth incentives
Education in Finland, recipe for success?
https://marginalrevolution.com/marginalrevolution/2004/04/education_in_fi.html
Jensen Comment
One of the key differences between Finland and the USA, in my opinion, is that
Finland has a greater proportion of two-parent homes --- sounds so old fashioned
Honest Finland ---
https://en.wikipedia.org/wiki/Corruption_Perceptions_Index
The USA is dragged down by so much corruption in city, state, and federal
government, although business firms are often partners in this corruption
Demographics in Finland ---
https://en.wikipedia.org/wiki/Demographics_of_Finland
Low on racial diversity and immigration
Healthcare in Finland ---
https://en.wikipedia.org/wiki/Healthcare_in_Finland
The Dark Side (funding and sustainability) ---
https://www.cnn.com/2019/08/15/world/finland-health-care-intl/index.html
Religion in Finland ---
https://en.wikipedia.org/wiki/Religion_in_Finland#targetText=Finland is a
predominantly Christian,, Judaism, folk religion etc.
On the decline following a general trend in Europe
Sex in Finland ---
https://yle.fi/uutiset/osasto/news/study_more_finns_opting_for_solo_sexual_satisfaction/9090220
Is this a trend among all developed nations?
Bloomberg's Rankings of the Top 100 Business Schools ---
https://www.bloomberg.com/business-schools/regions/us
Jensen Comment
Whereas US News has multiple rankings for business studies specialties,
Bloomberg ignores specialties. Bloomberg also indicates scores on several
factors like entrepreneurship and compensation. The Bloomberg ranking
integrates graduate and undergraduate business schools which in some ways is
misleading. Note that the Bloomberg ranking ignores that some top schools do not
even have specialties such as tracks to take the CPA examination or forensic
accounting tracks. For example, students aspiring to for careers as CPAs will be
disappointed in top schools like Stanford, Dartmouth, and Harvard but not
Pennsylvania Wharton and UC Berkeley.
US News is a better source of multiple rankings and provides a "College
Compass" for finding fits for students with particular interests ---
https://www.usnews.com/usnews/store/college_compass.htm?src=web%3Acol_compass%3Ana%3Aalertbar%3A20180131
For employers, admission standards are the unmentioned criteria of great
importance. It's difficult to measure admission standards. For example,
rejection percentages are highly misleading since most students don't even
bother spend the time and and money applying to schools like Stanford and
Harvard. The upper-level GMAT students, on the other hand, often do not apply to
schools in the bottom half of the Bloomberg rankings unless there is some unique
geographic preference.
When asked to rank business schools employers may introduce subjective "best
buy" criteria. For example, some recruiters in the Boston area may consider
Bentley graduates to be a better buy than highly paid Harvard Business School
graduates.
The very top schools who get so many applicants with both stellar GMAT scores
and high undergraduate grades use added admissions criteria that are difficult
to quantify like undergraduate major (preferring engineers to elementary
education majors) and public service records (e.g., giving admission preference
to an applicant who taught computer programming in Tanzania as a volunteer?)
Why is Capitalist Finland so Rich?
https://marginalrevolution.com/marginalrevolution/2011/03/why-is-finland-so-rich.html
Read the comments --- Finland encourages wealth incentives
Education in Finland, recipe for success?
https://marginalrevolution.com/marginalrevolution/2004/04/education_in_fi.html
Jensen Comment
One of the key differences between Finland and the USA, in my opinion, is that
Finland has a greater proportion of two-parent homes --- sounds so old fashioned
Honest Finland ---
https://en.wikipedia.org/wiki/Corruption_Perceptions_Index
The USA is dragged down by so much corruption in city, state, and federal
government, although business firms are often partners in this corruption
Demographics in Finland ---
https://en.wikipedia.org/wiki/Demographics_of_Finland
Low on racial diversity and immigration
Healthcare in Finland ---
https://en.wikipedia.org/wiki/Healthcare_in_Finland
The Dark Side (funding and sustainability) ---
https://www.cnn.com/2019/08/15/world/finland-health-care-intl/index.html
Religion in Finland ---
https://en.wikipedia.org/wiki/Religion_in_Finland#targetText=Finland is a
predominantly Christian,, Judaism, folk religion etc.
On the decline following a general trend in Europe
Sex in Finland ---
https://yle.fi/uutiset/osasto/news/study_more_finns_opting_for_solo_sexual_satisfaction/9090220
Is this a trend among all developed nations?
**How to Mislead With Statistics
How Higher Education’s Data Obsession Leads Us Astray ---
https://www.chronicle.com/article/How-Higher-Education-s-Data/247409?utm_source=cr&utm_medium=en&cid=cr&source=ams&sourceId=296279
Has
there ever been an enterprise that produced so much data to so little effect
as higher education? We are drowning in data, awash in analytics. Yet,
critics demand even more data, contending that higher education remains
persistently opaque and lacking true accountability.
Here’s a heretical thought: Perhaps the problem
is not a lack of data, but rather, that metrics alone are a poor measure of
accountability. Our critics prefer lists over paragraphs, but sometimes
words are important to interpret statistics.
The data industry is huge, including magazine
rankings and credit-rating agencies; accreditors; and the mother of all data
collections, housed at the U.S. Department of Education: Ipeds, the
Integrated Postsecondary Education Data System. Easy access to voluminous
data allows just about anyone to extract random factoids as evidence to
assail or affirm collegiate value. Politicians assail high-tuition rates as
bad for consumers, but Moody’s rewards them for generating ever-higher
net-tuition revenues. Critics pummel elite universities for failing to
enroll enough low-income students, while berating colleges that enroll
majorities of Pell grantees for low graduation rates. More nuanced analyses
of the relationships among high-net tuition, volume of Pell grantees, and
graduation rates rarely make it into a public discussion that fixates on the
numbers, not the narrative.
Big data is helpful to understand megatrends like the
impact of student-debt burdens by race and ethnicity, the alarming growth in
discount rates, or changes in demand for majors. But statistics are no
substitute for professional judgment about the meaning of data for a
specific institution. Unfortunately, magazine rankings and the federal
College Scorecard choose to present
isolated data points as institutional quality measures without
interpretation.
Qualitative measures are also important for
accountability analysis. Rankings are silent on the ways in which the
first-year faculty members help students discover that they really can learn
statistics, write laboratory reports, analyze complex texts, conduct
research, or engage in professional work through internships. The College
Scorecard does not provide data on the campus climate for women or students
of color, or the scope of services for students with disabilities, or food
pantries and support for students who are also parents.
Accreditation has always been the place where
both quantitative and qualitative evidence is presented within the larger
institutional context; interpretation of performance data through the lens
of mission and student-body characteristics is essential to level-set the
basis for continuous quality improvement. Even more important are the
collegial conversations among visiting teams, institutional leaders, and
faculty to focus on challenges needing serious repair and opportunities to
move forward constructively. Those conversations, summarized in team
reports, often remain private, a fact that frustrates critics craving public
shaming of institutions that fall outside of traditional benchmarks.
In recent years, pushed by the critics who push
Congress and the U.S. Department of Education, accreditation has inexorably
moved toward even more data-driven assessment processes in both regional and
specialized accreditation. Whether this migration has produced more
accountability is unclear. While the idea of self-study and collegial peer
review continues, the hegemony of data analytics threatens to diminish the
most useful parts of the accreditation process in the collegial discussions
that honor mission and institutional context while also challenging
institutions to improve.
Some elite universities lobbied for this change on theory that if they surpass some normative benchmarks, they should not have
to bear the burden of the more onerous hands-on accreditation processes
beyond, perhaps, cursory reviews. Aside from the arrogance of insisting that
some universities are above collegial scrutiny (the climate that fostered
the Varsity Blues scandal notwithstanding), the use of data to exonerate
wealthy elite schools also perpetuates higher education’s caste system.
Institutions serving large numbers of at-risk students will probably not
qualify for lesser scrutiny since their
students move through college at variance from traditional norms; the more
variance, the deeper the scrutiny.
Continued in article
Jensen Comment
There's a difference between having too much data versus conducting studies that
mislead with that data. The main argument about having too much data is that too
much is being spent (in time and money) collecting it. The main argument about
misleading data can be found in the many examples of how it is misleading us ---
http://faculty.trinity.edu/rjensen/MisleadWithStatistics.htm
**How
to Mislead With Statistics
The Guardian: The 20 firms behind a third of all carbon
emissions
https://www.theguardian.com/environment/2019/oct/09/revealed-20-firms-third-carbon-emissions
Jensen
Comment
The article is misleading in a number of ways, firstly by failing to stress that
most of the increased carbon emissions are natural phenomena that are not caused
by mankind ---
https://en.wikipedia.org/wiki/Greenhouse_gas#Natural_and_anthropogenic_sources
The
second way the article is misleading is that it seems to imply that if we simply
banned those 20 companies from existence the carbon emissions on earth would
decline by a third. The fact of the matter is that people would simply grasp at
whatever other means are possible to heat their dwellings, power their
electricity, be transported from place to place, etc. Up here in New England we
would heat our homes and generate our electricity by decimating our forests ---
which is counter productive since all the carbon absorbing trees would be taken
from the earth. People in the southern USA sweltering in heat would find ways to
cool off by consuming vastly more water --- not exactly what environmentalists
hope for given the increasing scarcity of water.
Add to
this the impact of famine, job losses, and destruction of entire economies if we
tried to abruptly terminate the oil and gas infrastructure. Mad Max would become
an overnight reality ---
https://en.wikipedia.org/wiki/Mad_Max
Having
said this does not the world is simply ignoring the problem. Even the 20 firms
featured in this article are diversifying into energy alternatives that emit
less carbon --- including solar, wind power, and hydrogen initiatives.
And
there's the possibility that fanatics will impose drastic solutions that are
hopeless from the start ---
The New Yorker: The climate apocalypse is
coming. To prepare for it, we need to admit that we can’t prevent it ---
https://www.newyorker.com/culture/cultural-comment/what-if-we-stopped-pretending
**How
to Mislead With Statistics
Walter E. Williams: Idiotic Environmental Predictions ---
https://townhall.com/columnists/walterewilliams/2019/10/09/idiotic-environmental-predictions-n2554294?utm_source=thdaily&utm_medium=email&utm_campaign=nl&newsletterad=10/09/2019&bcid=b16c6f948f297f77432f990d4411617f&recip=17935167
The Competitive Enterprise Institute has published a new
paper, "Wrong Again: 50 Years of Failed Eco-pocalyptic Predictions." Keep in
mind that many of the grossly wrong environmentalist predictions were made
by respected scientists and government officials. My question for you is: If
you were around at the time, how many government restrictions and taxes
would you have urged to avoid the predicted calamity?
As reported in The New York Times (Aug. 1969) Stanford
University biologist Dr. Paul Erhlich warned: "The trouble with almost all
environmental problems is that by the time we have enough evidence to
convince people, you're dead. We must realize that unless we're extremely
lucky, everybody will disappear in a cloud of blue steam in 20 years."
In 2000, Dr. David Viner, a senior research scientist at
University of East Anglia's climate research unit, predicted that in a few
years winter snowfall would become "a very rare and exciting event. Children
just aren't going to know what snow is." In 2004, the U.S. Pentagon warned
President George W. Bush that major European cities would be beneath rising
seas. Britain will be plunged into a Siberian climate by 2020. In 2008, Al
Gore predicted that the polar ice cap would be gone in a mere 10 years. A
U.S. Department of Energy study led by the U.S. Navy predicted the Arctic
Ocean would experience an ice-free summer by 2016.
In May 2014, French Foreign Minister Laurent Fabius declared
during a joint appearance with Secretary of State John Kerry that "we have
500 days to avoid climate chaos."
Peter Gunter, professor at North Texas State University,
predicted in the spring 1970 issue of The Living Wilderness: "Demographers
agree almost unanimously on the following grim timetable: by 1975 widespread
famines will begin in India; these will spread by 1990 to include all of
India, Pakistan, China and the Near East, Africa. By the year 2000, or
conceivably sooner, South and Central America will exist under famine
conditions. ... By the year 2000, thirty years from now, the entire world,
with the exception of Western Europe, North America, and Australia, will be
in famine."
Ecologist
Kenneth Watt's 1970 prediction was, "If present trends continue, the world
will be about four degrees colder for the global mean temperature in 1990,
but eleven degrees colder in the year 2000." He added, "This is about twice
what it would take to put us into an ice age."
Mark J. Perry, scholar at
the American Enterprise Institute and professor of economics and finance at
the University of Michigan's Flint campus, cites 18 spectacularly wrong
predictions made around the time of first Earth Day in 1970. This time it's
not about weather. Harrison Brown, a scientist at the National Academy of
Sciences, published a chart in Scientific American that looked at metal
reserves and estimated that humanity would run out of copper shortly after
2000. Lead, zinc, tin, gold and silver would be gone before 1990. Kenneth
Watt said, "By the year 2000, if present trends continue, we will be using
up crude oil at such a rate ... that there won't be any more
crude oil."
Continued in article
The New Yorker: The climate apocalypse is
coming. To prepare for it, we need to admit that we can’t prevent it ---
https://www.newyorker.com/culture/cultural-comment/what-if-we-stopped-pretending
Jensen Comment
The problem with prior idiotic predictions is that they are like the boy who
cried wolf repeatedly ---
https://en.wikipedia.org/wiki/The_Boy_Who_Cried_Wolf
When the real wolf is lurking many people ignore the warnings.
How Fact Checkers Mislead With Statistics
Ilhan Omar Defended by Media and Fact Checkers ---
https://townhall.com/columnists/johnrlottjr/2019/07/31/ilhan-omar-defended-by-media-and-fact-checkers-n2550908?utm_source=thdaily&utm_medium=email&utm_campaign=nl&newsletterad=07/31/2019&bcid=b16c6f948f297f77432f990d4411617f&recip=17935167
Jensen Comment
The way fact checkers mislead with statistics is in selectivity bias by not fact
checking claims they agree with politically.
**How
to Mislead With Statistics
NYT:
The Rich Really Do Pay Lower Taxes Than You ---
https://www.nytimes.com/interactive/2019/10/06/opinion/income-tax-rate-wealthy.html
Jensen
Comment
The article is misleading in two major respects. Firstly, the title implies that
the rich pay less taxes than you. How can that be true
since nearly half the USA "taxpayers" who file tax returns pay zero income taxes
---
Washington Post:
https://www.washingtonpost.com/blogs/fact-checker/post/a-fierce-tax-debate-without-much-light/2012/06/18/gJQAijuEmV_blog.html
Add to that the number, millions *rich and poor) in the underground
economy, who don't even file tax returns.
Add to that the fact that the rich pay more in other taxes, especially property
taxes that largely fund USA K-12 schools.
This
does not mean that the rich are paying as much as they should be paying, and the
rich have tax havens and other tax avoidance/deferral strategies (legal
andillegal) to reduce their income taxes. But it is false to write that "The
Rich Really Do Pay Lower Taxes That You." The rich in general pay more taxes
than you. They just don't usually pay as much as they should be paying. But
that's a different statement.
U.S. Taxes are Progressive: Comment on “Progressive Wealth
Taxation” ---
http://www.davidsplinter.com/Splinter-TaxesAreProgressive.pdf
U.S. federal taxes are
progressive, as shown by Congressional Budget Office and Tax Policy Center
estimates, with average tax rates increasing with income. In fact, the OECD
(2011) estimated that the U.S. has the most progressive household taxes
among developed countries. Moreover, the 2017 tax reform is expected to have
little effect on overall tax progressivity (Tax Policy Center, 2017; Joint
Committee on Taxation, 2019). But Saez and Zucman (2019) argue that average
tax rates are nearly equal over the income distribution. To examine this
claim, this paper compares other estimates of average tax rates by income
group, all of which suggest a high degree of progressivity. Three issues are
found to bias the average tax rates presented in Saez and Zucman (2019).
After correcting for these issues, their estimates align more closely with
other estimates that show U.S. taxes are progressive.
I. Comparing Estimates
of Average Tax Rates There are two types of average tax rate estimates in
the literature, one based on federal taxes and another on taxes from all
sources. Figure 1 considers average federal tax rates over the income
distribution, showing estimates from Piketty and Saez (2007), Tax Policy
Center (2018, hereafter TPC), Congressional Budget Office (2019, hereafter
CBO), and Auten and Splinter (2019, hereafter AS). The left side presents
tax rates excluding payroll taxes.2 For 2004, Piketty and Saez (2007)
estimated a second quintile average tax rate of –1%, with the negative rate
resulting from refundable credits, while the top 0.01 percent tax rate was
33%. The other three estimates are for 2014, with CBO and TPC estimating
bottom quintile tax rates of –8% and –4% and top 1 percent rates of 32% and
31%. AS estimated a bottom 50 percent tax rate of 2% and a top 1 percent
rate of 29%. These average tax rates increase with income, suggesting
significant progressivity.
Figure 1, right side,
includes payroll taxes. This generally increases federal tax rates by about
10 percentage points for the bottom 99 percent of the income distribution
and 2 percentage points for the top 1 percent—a result of the Social
Security contribution taxable maximum.3 Average tax rates taxes are very
similar among these four estimates and imply a highly progressive federal
tax system.4 The Joint Committee Taxation (2019) also estimated average
federal tax rates. For 2019, before accounting for the effects of the 2017
tax reform, these tax rates almost exactly match those of Piketty-Saez. For
2015, U.S. Treasury (2015) data indicate that average federal tax rates were
more progressive than those presented in Figure 1: rangin
from –5% for the bottom
quintile to 39% for the top 0.1 percent.5 Note that Figure 1 exaggerates the
share of the population at the top. While this emphasizes differences in top
tax rates, Figure 2 instead uses an equal-spacing approach that shows how
average tax rates truly spike for a small share at the top of the
distribution.
. . .
Saez and Zucman (2019)
argue that the U.S. has a relatively proportional tax system across all
income levels. However, federal taxes are progressive, as shown by Piketty
and Saez (2007), Auten and Splinter (2019), The Urban-Brookings Tax Policy
Center, the Joint Committee on Taxation, the U.S. Treasury, and the
Congressional Budget Office. Three issues with the Saez and Zucman (2019)
methodology for calculating tax rates are shown to explain much of their
deviation from other measures.
The
second thing that is misleading is that the article implies that back in the
1950s when the tax rates on high income people were much higher (think 70%) that
the rich really paid those high rates. Multimillionaire Bing Crosby was
not paying 70% in 1950. The rich took advantage of tax loopholes as much
or more in the 1950s as they do in the 21st Century. And the levies for state
income taxes and property taxes were much, much lower.
NY Times:
Warren Wealth Tax Would Slow Economic Growth By 13% According To Penn Wharton
Budget Model ---
https://www.nytimes.com/2019/11/14/business/warren-wealth-tax-economy.html
Larry Summers ---
https://en.wikipedia.org/wiki/Lawrence_Summers
Summers on the Wealth Tax ---
https://marginalrevolution.com/marginalrevolution/2019/10/summers-on-the-wealth-tax.html
Larry Summers is my favorite liberal economist
because even while maintaining his liberal values he never stops thinking
like an economist. That makes him suspect among the left but it means that
he is always worth listening to. The video below with Saez, Summers and
Mankiw (with Rampell moderating) is excellent throughout. I cribbed a number
of points from Summers:
“I have studied last week’s
twitter war very carefully and I have to say that I am 98.5% convinced by
the critics that the Zucman-Saez data are substantially inaccurate and
misleading.”
The arguments around political
power are not persuasive. Most of what is wrong with politics is because
that is what the people want (I’m filling in a bit here from comments
throughout). A wealth tax does nothing about corporate lobbying and would
increase the incentive to give to
political organizations. If you cut wealth at the top by 30% that wouldn’t
change relative political power in the slightest.
Wealth is up in large part
because interest rates are down which means that permanent income hasn’t
increased.
Forced savings programs like
social security and unemployment insurance mean that people at the bottom
need to save less and thus their wealth falls even as their welfare
increases.
A wealth tax increases the
incentive to consume instead of save and invest.
On employee stock ownership
plans: “When you put workers in control of firms and you give them
substantial control–see Israeli kibbutz’s, see Yugoslav cooperatives, see
universities where faculties have a powerful voice–the one thing you do
not get is expansion. You get more
for the people who are already there. That does not seem to be an attractive
position for progressives.”
In the Q&A Summers just goes to
town on Saez when Saez claims 90% tax rates are a great American invention.
“The people who were around in the Kennedy administration who were at least
as progressive as you are were united in the belief that 90% tax rates were
a bad idea….The number of people who paid those 90% tax rates was trivial
and it wasn’t because there weren’t a lot of rich people.” Greg Mankiw, who
gives a nice parable in his remarks, has to stifle a laugh as Summers lets
rip.
Jensen
Comment
I've no objection to a modest wealth tax that does not badly destroy the wealth
tax. But to raise $20+ trillion annually needed to fund Democratic Party
spending proposals (Green Initiative, free medical care, free medicines, free
college, guaranteed annual income for 350+ million USA residents, reparations,
open borders, etc.) would wipe out the stock markets. That, in turn, would wipe
out most pension funds in the USA and make it impossible for business firms to
raise capital. In short it means the destruction of capitalism where
business firms raise capital from the private sector.
**How
to Mislead With Statistics
The Wealth Tax Runs Counter to the Objectives of Its Advocates
Comment on “Progressive Wealth Taxation” by Saez and Zucman prepared for the
Fall 2019 issue of Brookings Papers on Economic Activity ----
http://www.columbia.edu/~wk2110/bin/BPEASaezZucman.pdf
Emmanuel Saez and Gabriel Zucman offer a
discussion of rationale for, implementation and implications of introducing
wealth taxation in the United States. In my comments, I will primarily focus
on three topics: economic arguments for having this form of taxation,
practical issues in implementing it, and a few aspects of underlying data
and assumptions that authors rely on in evaluating the impact of this
proposal.
A general wealth tax does not exist in the
United States. However, the U.S. has a highly progressive estate tax and it
taxes capital income through a mix of (1) personal income taxes on
dividends, interest, capital gains, royalties and business incomes, and (2)
corporate taxation. Bases of all these taxes overlap with the base for
wealth taxation, although they are not economically or administratively
identical. Thus, the right question in my mind is whether a wealth tax is
desirable given existence of these other instruments. In my view, as
elaborated below, the case for wealth taxation over capital income taxation
in general is quite weak and rests on either desirability of one time
,ideally unexpected, taxation or on the presence of externalities from
wealth concentration (that ideally should be treated using instruments
tailored to specific problems). From the administrative point of view, even
then the challenging and ambitious solutions that could make wealth tax
feasible apply equally well to (otherwise preferred) capital income
taxation.
The case that authors make is not helped by
optimistic empirical assumptions that do not highlight uncertainty, which is
likely to run mostly in one direction; that may be a plus for public
presentation of the plan, but not for an economist. I discuss these issues
at the end of the comment.
Continued in article
Jensen
Comment
Along with destruction of pension fund investments in failed stock markets.
Taxing The “Rich” Won’t Pay For Politicians’ Promises ---
https://taxprof.typepad.com/taxprof_blog/2019/10/taxing-the-rich-wont-pay-for-politicians-promises.html
Hillary Clinton Is Not a Fan of Bernie’s or Warren’s Wealth Taxes
---
Click Here
She thinks they’re “unworkable” and would be “incredibly disruptive.”
Chronicle of Higher Education: Free College Fantasy
https://reason.com/2019/12/09/ig-report-fbi-fisa-carter-page-trump-media/
The proposals floated by
presidential candidates are nonsensical. There’s a better way.
This
spring, Sen. Elizabeth Warren unveiled an
ambitious policy proposal:
a
$1.25-trillion plan to make college more affordable. It includes canceling
up to $50,000 in student-loan debt for 95 percent of borrowers, and putting
billions of dollars into historically black colleges and $100 billion in new
money toward the federal Pell Grant program.
Almost as
an afterthought, the plan also includes a proposal to make tuition free at
every public college and university in America. While light on details,
Warren’s version of free college seems to be
modeled after
Sen. Bernie Sanders’s. Sanders, of course, built his improbable 2016 primary
campaign in part by igniting millennial student debtors who were outraged by
the broken promise of affordable higher education. Now every serious
Democratic contender has had to propose some version of free college — or,
as Sen. Amy Klobuchar and Mayor Pete Buttigieg have done,
explain why not.
The broad
case for free college is strong. Many states have slashed public funding for
higher learning, shifting the burden to students and parents. Private
colleges, in pursuit of status and fame, have hiked prices into the
stratosphere. As real tuition at public universities
has tripled
over the
past three decades while middle-income wages have stagnated, the federal
government’s main response was to lend students ever-larger sums of money to
make up the difference, with no control over how much colleges charged or
whether the degrees were any good. It was a policy mistake of epic
proportions, leaving the path to economic mobility badly narrowed and a
generation of collegians saddled with unaffordable loans.
Continued in article
With new government programs will come price
controls. Medicare-for-All severely constrains what physicians, hospitals, and
other medical providers earn while at the same time setting new rules on work
loads. Free=College-for-All will greatly constrain what colleges and faculty
earn and add workload restrictions such as required teaching loads of four or
more courses per term. Leaves will be curtailed as well as research support.
In some European nations and elsewhere college and
trade skill training is free, but admission is restricted to the top third of
high school graduates ---
http://faculty.trinity.edu/rjensen/HigherEdControversies.htm#Tertiary
Restricting college and trade school admissions to the top third of high school
classes will never fly in the USA.
Furthermore the wages of teachers is severely limited in European nations and
class sizes are enormous.
For Democratic 2020 Presidential candidates the
media never reports the aggregated cost of promised for green
initiatives, free medical services, free medications, free nursing homes, free
college, free preschool, free housing, free food, guaranteed annual income,
reparations, open borders, legalized prostitution, etc. to the tune of over $10+
trillion per year. etc. My guess is that
the total annual added aggregate cost for these promised programs is over $20
trillion per year --- well over four times what the government now spends for
everything in the Federal budget.
Many voters for Trump would like to not vote for him
in 2020, but they may have to if the chosen Democratic Party contender intends
to ruin the USA economy.
Joe Biden Proposes $1 Trillion in New Corporate
Taxes ---
https://www.wsj.com/articles/joe-biden-proposes-1-trillion-in-new-corporate-taxes-11575492332?mod=djemCFO
Democratic presidential candidate Joe Biden proposed nearly $1 trillion in
new corporate taxes on Wednesday as he sought to generate more revenue to
pay for his policy plans on health care, climate, infrastructure and
education.
One of his new
taxes
would go after companies
such as
Amazon.com Inc. that
have years when they report profits to investors but show little or no U.S.
tax costs. A second would double the minimum tax rate on overseas income of
U.S.-based multinationals.
Until now, Mr. Biden has largely confined his ideas to rolling back parts of
the 2017 Republican tax cut and pursuing policies that the Democratic Obama
administration, in which he served as vice president, couldn’t get through
Congress.
The new proposals come atop Mr. Biden’s previous calls for tax increases,
which would push the corporate tax rate to 28% from 21%, tax unrealized
capital gains at death and push the top rate on individuals to 39.6% from
37%.
Mr. Biden’s proposed tax increases now total $3.2 trillion over a decade,
though his campaign confirmed on Wednesday that he also supports repealing
the $10,000 cap on the state and local tax deduction, a tax cut that would
disproportionately benefit some of the high-income households who would be
hit by his tax increases.
Still, Mr.
Biden’s tax plans are more modest than those of his main rivals for the
Democratic presidential nomination. Sens. Elizabeth Warren (D., Mass.) and
Bernie Sanders (I., Vt.)
have proposed wealth taxes on the super-rich.
Both of them, along with Mayor Pete Buttigieg, have called for returning the
corporate tax rate to 35%.
Jensen Comment
Continued in article
Jensen Comment
Bernie Sanders finally convinced Joe Biden as well as Elizabeth Warren that
voters are too stupid to understand how $1 trillion (or much more in the case of
Sanders and Warren) in new taxes is really a tax increase on the lower income
and middle income taxpayers. Biden at last believes that voters are too dumb to
understand that business firms don't pay taxes. Biden,
Sanders, and Warren think voters are just
too uneducated to understand that business firms don't pay taxes.
Instead business firms collect taxes from their customers. Nearly all companies
contributing to Biden's $1 trillion in new corporate taxes will raise prices to
(gasp) customers of Amazon, Walmart, etc. who mostly are lower and middle income
customers.
And tariffs will have to be increased on imported goods (think
sugar, TV sets, mobile phones and computers) to make it possible for USA
corporations to raise prices enough to collect the added trillion (or trillions)
in new business taxes.
In their zeal to attract ignorant voters, I don't think Biden,
Sanders, and Warren want to let on that taxing trillions from business firms and
investors will kill the stock markets. These politicians hope voters are too
stupid to realize how much their own futures depend on viable stock markets and
other capital markets. The vast pension funds of workers will get wiped out if
those capital markets get wiped out.
Biden,.Sanders, and Warren think voters are too stupid to realize
the mammoth size of the number $1 trillion or more in taxes. The CBO's estimated
total Federal revenue from all sources for 2019 is
$3.490 trillion ---
https://en.wikipedia.org/wiki/United_States_federal_budget
What's another trillion or more in new taxes?
As the saying goes: "The Road to Hell is Paved With Good Intentions."
Exhibit A is Venezuela.
NY Times: Democratic Presidential Tax Plans Would Hit Blue States The
Hardest ---
https://taxprof.typepad.com/taxprof_blog/2019/11/ny-times-democratic-presidential-tax-plans-would-hit-blue-states-the-hardest.html
New York Times, How
Democrats Would Tax High-Income Professionals (Not Just the Mega-Rich):
Moody’s data shows that
higher taxes would be paid disproportionately in Democratic-leaning states.
Much of the Democratic
primary race has focused on taxes aimed at the billionaire class — policies
devised to reduce inequality and fund progressive goals on health care and
education.
But there’s also a less
discussed tax increase in leading Democratic policy proposals that would
affect not just a tiny sliver of the ultra-wealthy, but also millions of
high-income workers. For these people, many of them affluent professionals
in Democratic strongholds, it would be the biggest tax increase in recent
memory.
This year, American workers
and their employers owe a combined 12.4 percent on Social Security payroll
taxes for income up to $132,900 (rising to $137,700 in 2020). They owe
nothing on earnings above that level.
Some Democrats in the thick
of the presidential race and on Capitol Hill now seek to change or eliminate
that cap — potentially placing a new double-digit tax on high earners, with
several plans focusing on earnings above $250,000. ...
Moody’s data also shows
that the higher taxes would be paid disproportionately in Democratic-leaning
states. The 12 states with the highest share of earners who would owe higher
taxes all voted for Hillary Clinton in the 2016 election, led by New Jersey,
Connecticut and Massachusetts.
Jensen Comment
The most liberal candidates spending plans for green initiatives, free medical
services, free medications, free nursing homes, free college, free preschool,
free housing, free food, guaranteed annual income, reparations, open borders,
legalized prostitution, etc. to the tune of over $10+ trillion per year.
How to Mislead With Statistics
To combat the COVID-19
economic downturn, New Jersey Governor Phil Murphy passed a millionaire's tax.
Here's why he says that's good for everyone ---
https://www.businessinsider.com/nj-gov-phil-murphy-millionaires-tax-will-help-middle-class-2020-11
This year, New Jersey Governor Phil Murphy and the state legislature agreed
on a deal to raise the income tax by 2% on incomes over $1 million per year
to address the budget crisis brought on by the pandemic. Not only will this
tax help administer coronavirus relief to the communities and small
businesses that need it most, but it will also help rebalance a regressive
state tax code which puts a bigger tax burden on poorer households.
In this week's episode of Pitchfork
Economics,
David Goldstein and Nick Hanauer interview Governor Murphy about his
decision to tax the rich.
Murphy, a
millionaire former Goldman Sachs executive, wants to be very clear that he's
not fomenting class warfare.
"We don't begrudge people's
success," Murphy began. "Whether you're a wealthy individual or a large
corporation — we want more of each in New Jersey."
But Murphy says he raised
the tax because "I got elected to stand for a stronger, fairer New Jersey
that works for not just some, but for everybody." That meant asking the
wealthiest New Jerseyans to "help us rebuild our middle class."
From the beginning, Murphy
laid out the conditions for the tax very clearly: "Anyone earning a million
dollars and up, we're asking you to pay a few pennies more, and we'll put
every dime of that into the middle class."
Continued in article
Taxes are about to rise for
New Jersey millionaires. There aren’t many ways to duck the levies ---
https://www.cnbc.com/2020/09/24/taxes-are-about-to-rise-for-new-jersey-millionaires.html
. . .
“New Jersey is one of the more painful
states to really tax plan for,” said Albert J. Campo, CPA and managing
partner at AJC Accounting Services in Manalapan, New Jersey.
“Anyone who’s $1 million and up is
getting substantial benefits (tax breaks) at the federal level, but they’re
somewhat limited at the state level.”
The Garden State is known as a “gross
income” state, and that means certain exclusions and deductions are off the
table on state tax returns.
For instance, contributions you make
to a workplace retirement plan reduce your taxable income on your federal
return.
In New Jersey, only contributions to
401(k) plans are excludible from wages. Amounts you divert to a deferred
compensation plan or any other retirement plan – including 403(b) or 457
plans -- are not excludible from your pay.
Another quirk: People who itemize on
their federal income tax return can claim a write-off for charitable giving.
New Jerseyans, however, can’t do this on their state return.
Earlier this year, Garden State legislators
put forth a proposal to allow a gross
income tax deduction for
contributions made to certain New Jersey-based charitable organizations
during the pandemic. That measure is pending.
See here for
a list of items that can’t be excluded from wages in New Jersey.
There are a few moves
high-income households can take to lower their income if they’re close to
the margins and a couple of thousand dollars away from the steeper tax rate,
according to Alan Sobel, CPA at Sobel & Co. in Livingston, New Jersey, and
president of the New Jersey Society of CPAs:
-
Increase your 401(k) plan contributions: It’s
the one retirement plan contribution that can let you lower wages on
your New Jersey tax return.
-
Drawing down portfolio income? Consider tax-exempt
bonds: Garden
State municipal bonds can create income that’s free from federal and
state income tax.
-
Gift assets to family members in lower tax brackets: “This
way, the income is going to them and not you,” said Sobel. Be aware this
is a long-term play. You should coordinate with your accountant, estate
attorney and family members before making these gifts.
Continued in article
Jensen Comment
But in both the federal and state jurisdictions, millionaires often defer more
income tax than they report due to capital gains and losses, often value changes
that are highly volatile and highly subjective in measurement. For example,
owners of Tesla shares can see the values of their unsold shares bounce up and
down like a basketball.
Ten different real estate
appraisers may give you ten highly different value estimates of a 100 acre
parcel of land on the outskirts of Newark, the value of which may be highly
dependent upon where locations of future roads, road exits, train tracks, and
bridges are built. Ups and downs in values of such investments are unknown in
amount until sales transactions actually take place.
For the same reason, it's
virtually impossible to compare total wealth of most millionaires and
billionaires. The estimated wealth of such persons vary widely in the eyes of
different appraisers. In estate value disputes it's often the courts that have
to set values, and the courts do not have magical measurement wands any better
than the wands all disputing appraisers. The courts merely have the power to set values
when disputing value appraisers cannot agree.
My best example of
where the court resolved highly varying value estimates of finance
models is:
Questrom vs. Federated Department Stores, Inc.: A Question of Equity
Value," by University of Alabama faculty members by Gary
Taylor, William Sampson, and Benton Gup, May 2001 edition of Issues
in Accounting Education
---
http://faculty.trinity.edu/rjensen/roi.htm
One thing is certain is that
the federal government under Biden and Harris will soon impose heavy new taxes
on the same "millionaires" in New
Jersey and millionaires in all the other 49 states. This will soon become a taxing
time for high earners and wealthy people in the USA.
I think the Governor of New
Jersey overstates the case that his proposed "millionaires" tax will not lead to exodus of a significant
number of high earning citizens to move elsewhere or be a barrier to such
citizens that might move into New Jersey. New Jersey already has nearly the
highest state taxes for citizens at all levels of income. The problem with the causal
factors that inspire movements of households is that there are many such factors
that are highly interactive.
Consider me as an example,
although my income is way too low to qualify for the new millionaire tax in New
Jersey. When I retired in San Antonio, Texas my wife and I wanted to move out of
the heat, humidity, and congestion of a big city. We also wanted to be closer to
family. We have two children living in northern California, one living in
Wisconsin, and two in northern Maine. Almost like New Jersey, those three states
are among the highest taxing states in the USA. Having family within driving
distance was the primary consideration for where to move, but environmental
beauty and state taxation were interactive causal factors in choosing where to
retire. We thus narrowed our search down to northern Nevada next to California
or northern New Hampshire next to Maine. We found a mountain cottage in northern
New Hampshire that is within five hours of driving to where two of our children
live in Maine ---
http://faculty.trinity.edu/rjensen/Pictures.htm
State taxation was not the
primary causal factor for choosing to retire in New Hampshire, but the fact that
New Hampshire has no income tax and no sales tax was an interactive causal
factor that led us to choose New Hampshire over California, Wisconsin, and
Maine. If we had children in New Jersey we probably would've retired in a nearby
state with lower taxes. Never New Jersey!
My point here is some people
will avoid living in a state with very high taxes being the main reason. Others,
like my wife and I, left Texas primarily for reasons not affected by taxation.
But when choosing where to retire taxation became an interactive causal factor
--- along with other factors like not wanting to live in a city, having nice
surroundings like mountains, and having nearby family in an adjoining state.
New Jersey's
enormous state taxes have primarily or interactively been a factor in
keeping many people from wanting to live there. Adding more taxes to already
high taxes may be hurting more than helping revenue taxes in New Jersey,
the second highest taxing state in the USA.
People who can now work remotely are
leaving New York, New Jersey, and Silicon Valley in droves.
NYSE and Nasdaq threaten to
leave New Jersey if transaction tax goes ahead ---
https://www.datacenterdynamics.com/en/news/nyse-and-nasdaq-threaten-leave-new-jersey-if-transaction-tax-goes-ahead/
The New York Stock Exchange (NYSE) has threatened
New Jersey lawmakers it will move its data operations out of state if taxes
are imposed on electronic trades.
Nasdaq has also come out against the tax, saying it
is in talks with Texas as a future home.
New
Jersey is proposing a hundredth-a-cent tax on every financial transaction
processed in the state. The transaction tax won favor amongst politicians
and also of Governor Phil Murphy and Senate President Steve Sweeney back
when it was introduced
in July.
At the time it was set to charge a quarter-of-a-cent ($0.0025), but has been
scaled back due to the stock markets' resistance.
If implemented, New Jersey’s financial transaction tax would be a flat-rate
levy imposed per instrument, not per trade. Lawmakers believe it could
harvest about $500m each year or $1bn over the tax’s two year lifetime.
The securities industry in New Jersey employs about 38,000 people and pays
nearly $1.4bn in state and local taxes.
The
Assembly of Financial Institutions and Insurance Committee held a virtual
public hearing on Monday, as reported by NJ.com.
The tax would be paid by companies operating data centers specializing in
financial trades. Many such facilities are based out of New Jersey's
suburban districts like Mahwah, Secaucus, and Carteret.
In the past, proximity to Wall Street made it sensible for data centers to
be nearby for low latency trading, however, the market has now been testing
whether it can operate out-of-state.
Back in September and earlier this month, the NYSE simulated a trading day
using its backup data center in Chicago. This was a practice for any
possible relocation of the market to data centers out of New Jersey. The
co-head of government affairs for the NYSE, Hope Jarkowski, said: “From Sept
28 to Oct 2, we moved our production servers for our NYSE Chicago exchange
out of New Jersey to our secondary data center… Proximity to New York City
is no longer relevant in today’s trading environment."
She added: “We understand why a financial transaction tax, or FTT as it’s
commonly known, may be perceived as a silver bullet that can remedy or
offset financial hardship with little effect on the financial markets
themselves, impacting perhaps only big corporations or wealthy individuals.
In reality, this tax would be imposed on a processor of transactions but
would be passed along to a purchaser or seller.
"That said, these harms will never come to pass," she added, "because those
with obligations to their investor clients will simply move their business
out of New Jersey to avoid harm, leaving no transactions in New Jersey to
tax and undermining the revenue-generating aim of an FTT.”
Nasdaq also threatened to leave if any transaction tax was put in place and
said it is currently in talks with Texas Governor Greg Abbott about
relocating trading systems to the Dallas-Fort Worth area. Several other
unnamed states are also said to be talking to Nasdaq.
New Jersey Governor Phil Murphy revealed he has been in talks with market
representatives to get them on side. At a Covid-19 briefing on
Monday,
he said: “We’ve had - I thought - constructive discussions with Nasdaq and
the New York Stock Exchange. They’ve expressed their concerns. I can’t read
their minds. But the fact that we are in an hour of need, this is not a
'forever and always' consideration. I think our side of the argument is also
reasonable... we shall see. This is something we still are studying and we
still like what we see, but it’s complicated, there’s no question about it.”
Continued in article
**How to Mislead With Statistics
TripAdvisor, Hajj
Ratings or Ummah.com
:
Everything in Mecca gets 5 stars — and online reviews of other holy sites are
wildly inflated, too ---
https://theconversation.com/everything-in-mecca-gets-5-stars-and-online-reviews-of-other-holy-sites-are-wildly-inflated-too-119614
Jensen Comment
In Lake
Wobegon criticizing can get you killed.
Beto: Trump Is 'An Open, Avowed Racist' And That's
The Reason There's Violence In America ---
https://townhall.com/tipsheet/bethbaumann/2019/08/04/beto-trump-is-an-open-avowed-racist-and-thats-the-reason-theres-violence-in-n2551140
Jensen Comment
Yeah, Impeach Trump and make Beto President to eliminate all violence in the USA
Beto apparently did not conduct research on the reasons for violence in the USA
Mass Shootings in the USA ---
https://en.wikipedia.org/wiki/Mass_shootings_in_the_United_States#Differing_sources
Terrorism in the USA ---
https://en.wikipedia.org/wiki/Terrorism_in_the_United_States
Mass shootings aren’t growing more common – and evidence
contradicts common stereotypes about the killers ---
https://theconversation.com/mass-shootings-arent-growing-more-common-and-evidence-contradicts-common-stereotypes-about-the-killers-121471
The men behind the US's deadliest mass shootings have domestic
violence — not mental illness — in common ---
https://www.businessinsider.com/deadliest-mass-shootings-almost-all-have-domestic-violence-connection-2017-11
Jensen
Comment
I don't think dividing domestic violence from mental illness is that simple.
There's
a definitional problem with the phrase "deadliest mass shootings." Deadliest can
be defined in terms of the number killed and injured in one incident like the
Las Vegas shooting incident for which we probably will never know the cause.
And
there's the problem of limiting the definition of indiscriminate terror to
"shootings." What about the 9/11 terror that killed over 3,000 people?
Deadliest can defined it in terms of frequency of incidents with more than four
killed or injured --- in which case domestic violence is the cause in a majority
instances.
Racism
is scary because it seems to be on the rise among white supremacists, but the UN
tells us that with lots of money ISIS is patiently planting sleeper cells to
commit terror worldwide. They will probably inflict greater damage (think dirty
bombs). "Just you wait 'enry 'iggins just you wait!"
https://www.thebaghdadpost.com/en/Story/42360/Terrorist-sleeper-cells-ISIS-fighters-remain-in-Iraq
I've always been opposed to the entire idea of white supremacy. However, the
media is being entirely unfair and inconsistent when confounding desire to
destroy President Trump's election chances with desire to reduce mass shootings
and other terror. The media tries to mitigate Islamic terror reporting, because
we're increasingly dependent upon Islamic society to report terrorists before
they inflict damage, and we don't want to discourage our Islamic friends in this
regard (reporting terrorists). At the same time the media forgets that we are
increasingly dependent upon white supremacists to report racist killers before
they can inflict damage or in helping to find the racists who inflicted damage.
It's the white supremacist friends of extremists that we hope will report
lowlifes planning attacks (think school mates). Making people declare their
white supremacy before they can report the lowest of lowlifes is dysfunctional
in our media.
The media repeatedly hammers President Trump for once having said (the
Charlotte incident) that there are good people on both sides of a street
confrontation between white supremacists and Antifa, but the fact of the matter
is that we most certainly hope there are good guys on
both sides of the confrontation who will report acquaintances who are plotting
deadly terror.
**How to Mislead With Statistics (delay notification of data errors)
Elizabeth Warren and Bernie Sanders just slammed the Swiss drug giant
Novartis over a new controversy swirling around the world's most expensive drug
---
https://www.businessinsider.com/novartiss-zolgensma-data-manipulation-gets-scrutiny-from-us-senators-2019-8
**How to Mislead With Statistics
U.S. Crime 'Good Guys With Guns' Can Rarely Stop Mass Shootings, and Texas
and Ohio Show Why 'Good Guys With Guns' Can Rarely Stop Mass Shootings, and
Texas and Ohio Show Why ---
https://time.com/5644578/good-guys-with-guns-el-paso-dayton/?utm_source=newsletter&utm_medium=email&utm_campaign=the-brief&utm_content=20190807&xid=newsletter-brief
Jensen Comment
This is a classic biased article from a left wing rag.
In accountancy we hear over and over that financial audits are often failures
at detecting employee pilfering, and it's true that financial statement audits
are not designed to detect pilfering by employees in part because audits to
detect employee pilfering are prohibitively expensive unless there is prior
suspicion that narrows the search. Financial statement audits are designed
to test overall conformance of financial reports to reporting standards.
However, only naive analysts conclude that financial statement audits do not
prevent some employee pilfering.
The problem is that we can never conduct very useful research on the impact
of financial statement auditing on preventing
employee pilfering. How do you catch a moonbeam in
your hand? How many employees are discouraged from pilfering when they
know that internal and external auditors will be poking around their records?
The
Sandy Hook School Shooter knew that
there were no armed teachers, administrators, or police officers on duty at the
school the morning he shot up a bunch of little kids. Would he have been so
brazen if he knew there were armed officials all around the school. Would
he instead have picked a softer target like a restaurant or a park when the
school was no longer a marshmallow target?
We'll never know. How to you catch a moonbeam in
your statistical database?
There are no perfect employee pilfering prevention measures just like there
are no perfect mass shooting prevention measures. But it's a
politically-motivated conclusion that "guns rarely stop mass shootings."
Schools are softer targets than gun shows because there
are fewer guns on site.
How many mass shootings take place at gun shows?
**How to Mislead With Statistics
New York Times --- Why Can’t Everyone Get A’s?
https://taxprof.typepad.com/taxprof_blog/2019/06/why-cant-everyone-get-as.html
Framing excellence in these competitive terms
doesn’t lead to improvements in performance. Indeed, a consistent body of
social science research shows that competition tends to hold us back from
doing our best. It creates an adversarial mentality that makes productive
collaboration less likely, encourages gaming of the system and leads all
concerned to focus not on meaningful improvement but on trying to outdo (and
perhaps undermine) everyone else.
The article was written by
Alfie
Kohn (author, No
Grades + No Homework = Better Learning)
---
https://www.amazon.com/gp/product/B001T4Y1QA/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=lawproblo-20&creative=9325&linkCode=as2&creativeASIN=B001T4Y1QA&linkId=e245c2f94ba89c4b1fd7d0c7b9b7541c
Jensen Comment
This is a poorly researched article with citation bias that overlooks the
biggest disgrace in USA education over the past 50 years --- grade inflation in
K-12 and higher education where the median grade went from C+ to A-
http://faculty.trinity.edu/rjensen/assess.htm#RateMyProfessor
The author looks at the hypothetical case where the proportion of A grades
does not increase when courses get easier. He completely overlooks the reality
that the proportion of A grades actually increased to nearly 50% after teaching
evaluations commenced to affect tenure and pay raises of teachers ---
http://faculty.trinity.edu/rjensen/assess.htm#RateMyProfessor
Alfie Kohn completely ignores evidence that student put less effort into
courses taken on a pass/fail basis relative to when they take courses for letter
grades.
Academic Achievement Declines under Pass-Fail Grading ---
https://www.tandfonline.com/doi/abs/10.1080/00220973.1971.11011260
The author overlooks the case where over 60 students at Harvard were expelled
for cheating in a political science course where all students were assured of an
A grade if they turned in their homework (irrespective of the quality of their
answers). The students collaborated on cheating because without an incentive to
get a higher grade they did not want to waste their time on homework ---
http://faculty.trinity.edu/rjensen/Plagiarism.htm#UVA
"Cheating Scandal at Harvard," Inside Higher Ed, August 31,
2012 ---
http://www.insidehighered.com/quicktakes/2012/08/31/cheating-scandal-harvard
Harvard University is investigating about 125
students -- nearly 2 percent of all undergraduates -- who are suspected
of cheating on a take-home final during the spring semester, The
Boston Globe reported Thursday. The
students will appear before the college’s disciplinary board over the
coming weeks, seem to have copied each other’s work, the dean of
undergraduate education said. Those found guilty could face up to a
one-year suspension. The dean would not comment on whether students who
had already graduated would have their degrees revoked but he did tell
the Globe, “this is something we take really, really
seriously.” Harvard administrators said they are considering new ways to
educate students about cheating and academic ethics. While the
university has no honor code, the Globe noted, its official
handbook says students should “assume that collaboration in the
completion of assignments is prohibited unless explicitly permitted by
the instructor.”
"The Typo That Unfurled Harvard’s Cheating Scandal," Chronicle of
Higher Education, September 12, 2012 ---
http://chronicle.com/blogs/ticker/jp/the-typo-that-unfurled-harvards-cheating-scandal?cid=wc&utm_source=wc&utm_medium=en
How to Mislead With Charts
"How to Lie with Charts," Harvard Business Review, December 2014
---
https://hbr.org/2014/12/vision-statement-how-to-lie-with-charts
The above link is only a teaser. You have to pay to see the rest of the article.
"BP Misleads You With Charts," by Andrew Price, Good Blog, May
27, 2010 ---
Click Here
http://www.good.is/post/bp-misleads-you-with-charts/?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+good%2Flbvp+%28GOOD+Main+RSS+Feed%29
"Correlation or Causation? Need to prove something you already believe?
Statistics are easy: All you need are two graphs and a leading question," by
Vali Chandrasekaran, Business Week, December 1, 2011 ---
http://www.businessweek.com/magazine/correlation-or-causation-12012011-gfx.html
How to Mislead With Statistics
"Reminder: The FBI’s ‘Police Homicide’ Count Is Wrong," by Reuben
Fischer-Baum, Nate Silver's 5:38 Blog, November 12, 2014 ---
http://fivethirtyeight.com/datalab/reminder-the-fbis-police-homicide-count-is-wrong/
How to Mislead With Statistics
"Some Stats Are Just Nonsense," by Cullen Roche, Pragmatic Capitalism
via Business Insider, November 15, 2014 ---
http://www.businessinsider.com/historical-statistical-and-nonsensical-2014-11
How to Mislead With Statistics
Common Accountics Science and Econometric Science Statistical Mistakes ---
http://www.cs.trinity.edu/~rjensen/temp/AccounticsScienceStatisticalMistakes.htm
The Huffington Post‘s War on Medical Science: A Brief History ---
https://sciencebasedmedicine.org/the-huffington-posts-war-on-science-revisited/
Robustness Statistics ---
https://en.wikipedia.org/wiki/Robust_statistics
**How to Mislead With Statistics
Mass shootings aren’t growing more common – and evidence contradicts common
stereotypes about the killers
---
https://theconversation.com/mass-shootings-arent-growing-more-common-and-evidence-contradicts-common-stereotypes-about-the-killers-121471
State gun laws, gun ownership, and mass shootings in the US: cross
sectional time series ---
https://www.bmj.com/content/364/bmj.l542
Outcome variables
We used the Supplementary Homicide Reports from the Federal Bureau of
Investigation’s Uniform Crime Reporting System (1998-2015) to obtain counts
of mass shootings by state. We compiled these data in line with the most
commonly used definition of a mass shooting: one event in which
four or more individuals were killed by a perpetrator using a firearm and
the perpetrator themselves did not count toward the total number of victims.
These mass shooting events were analyzed in total and stratified as to
whether the mass shooting was domestic or non-domestic in nature. Domestic
mass shootings included instances where the perpetrator committed the act
against an immediate family member or partner. Non-domestic mass shootings
included all other types of relationships, such as acquaintances, employees,
employers, friends, neighbors, strangers, extended family members, and
others. Florida was excluded due to non-participation in the Uniform Crime
Reporting System program.
Jensen Comment
The above article is badly misleading in that its conclusions are based largely
on rounding error in computing averages and denominator effects that destroy
robustness. The study focuses on rare events, it's conclusions and displays are
unstable to slight sensitivity analysis.
I will focus my criticisms on Figure 2 where Rhode Island, Delaware, New
Hampshire, North Dakota, and Arkansas each have rounded averages of zero mass
shootings across 17 years. There were mass shootings in those five states, but
their averages round to zero. The worst state in Figure 2 is Vermont that
has the highest average of three mass shootings across those same 17 years. Thus
the lowest five states have zero mass shooting averages and the highest state
has an average of three mass shootings. The difference from lowest to highest
(in Figure 2) I suspect is heavily to heavily be rounding error and is not as
significant as it appears in Figure 2.
There also is what is known as a denominator effect that destroys robustness
in Figure 2 due to the low population of 600,000 people in Vermont. Such a low
population destroys much of the robustness in comparing the highest mass killing
state (Vermont) with more populated states like California, New York, Arkansas
and Delaware. The same applies to low population states of Wyoming, Montana,
North Dakota, New Hampshire, and Alaska.
The study concludes as follows:
Discussion
Our analyses show that US state gun laws have become more permissive in
recent decades, and that a growing divide in
rates of mass shootings appears to be emerging between restrictive and
permissive states. A 10 unit increase in the
permissiveness of state gun laws was associated with an approximately 9%
higher rate of mass shootings after adjusting for key factors. A 10%
increase in gun ownership was associated with an approximately 35% higher
rate of mass shootings after adjusting for key factors. On the absolute
scale, this means that a state like California, which has approximately two
mass shootings per year, will have an extra mass shooting for every 10 unit
increase in permissiveness over five years. It will also have three to five
more mass shootings per five years for every 10 unit increase in gun
ownership. These results were also consistent across multiple analyses and
when stratified as to whether or not mass shootings were committed by
someone in a close relationship with the victims.
I contend that the above conclusion is unstable (not robust) such as the
conclusion that a restrictive state like Rhode Island has a hugely greater
divide (an average of zero mass shootings per year) with a permissive state
Vermont (with an average of three average mass shootings) --- a conclusion
that does not, based upon this study, justify legislation for more restrictive
gun laws to reduce mass shootings. The authors of the above study are not
responsible in pointing out the lack of robustness in their displays and
discussion. For example the five states shown in Figure 2 to have zero average
mass shootings all had mass shootings that were so rare they rounded to zero.
The worst state (Vermont) had an average rounded up to three in Figure 2. But in
reality the difference between the worst state (Vermont) and the five best
states is not really 3-0 = 3. This difference is
somewhat due to rounding differences combined with denominator effects rather
than robust statistical outcomes.
The first rule of statistical analysis is discuss the robustness of the
outcomes. The above study lacks a robustness analysis.
**How
to Mislead With Smoke and Mirrors
Marketwatch: These 7 Social Security myths just aren’t true, no matter how
often you hear them ---
https://www.marketwatch.com/story/these-7-social-security-myths-just-arent-true-no-matter-how-often-you-hear-them-2019-08-27
Jensen
Comment
I agree with most of that most of the "myths" in this article are myths, but I
disagree with Myth 2.
Myth No. 2: The government raided the trust fund
Some people believe the Social Security system wouldn’t be facing insolvency
today if the government kept their gosh-darned theivin’ hands out of it.
Here’s the truth: There has never been any change in the way Social Security
payroll taxes are used by the federal government.
The Social Security trust fund has never been “put into the general fund of
the government.” It is a separate account, and always has been.
We
can find the origins of this myth in the change that happened back in 1969.
At that time, the government began listing the trust fund’s transactions in
a single budget along with all the other functions of the federal
government.
The transactions were shown alongside other functions, but the trust fund
remained a separate account. In 1990, the government began listing the
activities of the trust fund separately.
None of these movements had anything to do with the actual operations of the
trust fund; it was purely a change of accounting practices.
The government did not raid Social Security’s trust fund. But you might
still believe the myth that it did if you don’t understand where the money
went — because it is true that the system faces insolvency today.
Why isn’t there a trust fund sitting around with trillions of dollars from
all the money we working taxpayers put into the system? Because the Treasury
uses those dollars.
Before you say, “aha! This proves the point; the government did steal the
money!” …not so fast. The government always uses incoming revenue to meet
its current obligations before it borrows money. This includes funds coming
in and earmarked for the Social Security trust fund.
For every dollar that comes in from Social Security taxes, a special-issue
Treasury bond takes its place. These bonds earn interest — which is a good
thing.
In
fact, since these bonds were first introduced to the trust fund, they
generated $1.9 trillion in interest. For reference, the total trust fund
balance is only $2.9 trillion.
Had all those dollars been left in cash, the trust fund would be worth about
two-thirds less and would have run dry much earlier than currently
projected.
The bottom line is that there’s no difference between the way the federal
government runs the trust fund and the way your bank handles your cash
accounts.
Jensen
Added Comment
Who
pays the interest?
When a
lender lends cash to a borrower the borrower repays the
loan principal plus interest to the lender. The interest is called a
Return on Investment (ROI) to the lender.
But
borrowing from the Social Security Trust fund is all smoke and mirrors.
The current generation lends money to whom?
In effect they lend it to themselves. Presumably the money taken out each year
from the SS Trust Fund each year goes to first pay for current social security
benefits and any excess goes current government spending goes to current
government spending on other programs, thereby avoiding additional taxes that
the current generation should be funding this year with added taxes. Yes
Congress does promise to repay the money from the trust fund plus interest.
But the interest paid years down the road is paid by future generations of
unborn children that did not borrow the money. Those children will
eventually have to pay the added taxes the current generation should have
coughed up this year instead of raiding the SS Trust fund and forcing the future
generation repay the loan plus the interest. Those unborn children did not elect
to borrow the money and repay the principal plus interest. No the current
generation borrowed the money and forced the future generation to replay the
principal plus interest. It's all smoke and mirrors that the Marketwatch did not
own up to in the above article.
Sure it looks like the SS Trust funds earned interest
on the bonds it used to replace current cash collections. But in reality the
returns are paid eventually in taxes by our unborn children to pay for historic
government expenditures on other programs that otherwise would have required
increased taxes.
Something similar happens with Social Security benefits to disabled programs.
The government should help disabled people, but the disability benefits each
year should come from current tax money raised for by the current generation to
help disabled people. In effect the current generation avoided some disability
taxes this year for disabled people by borrowing from future generations of
unborn children to pay the current disability benefits.
In effect Congress is getting away with robbing our future generations of
unborn children by promising that they will eventually pay for disability
benefits doled out in the present years.
It's
all smoke and mirrors.
**How to Mislead With Statistics
New Study Defending NYC’s Minimum Wage Law is Fake News ---
https://mises.org/wire/new-study-defending-nyc’s-minimum-wage-law-fake-news?utm_source=Mises+Institute+Subscriptions&utm_campaign=a77e7113d9-EMAIL_CAMPAIGN_9_21_2018_9_59_COPY_01&utm_medium=email&utm_term=0_8b52b2e1c0-a77e7113d9-228708937
Jensen Comment
What liberals don't like to discuss is the impact of a state-wide $15 per hour
on small town small businesses.
From the CFO Journal's Morning Ledger on July 25, 2019
In
a small California city, America’s highest
minimum wage is
causing a debate over how to balance boosting wages for the lowest-paid
workers and ensuring small businesses can afford to keep employing them.
Jensen Comment
Showing once again that minimum wages are more of a problem for small businesses
than for Walmart and Amazon that are not located in small villages with less
than 1,000 people --- small town businesses that struggle to make any profits
and endure losses in some seasons (think a small New England inn in the winter
and spring). Actually I've recently discovered how the inn down the road from me
charging a $300 average (with tax) per night for a room is struggling with
competition from Airbnb renting scenic entire houses (think four bedrooms and a
garage) for $200 per night in very scenic locales.
The high-labor inn across from me is once again is
trying to lift itself out of bankruptcy while the Airbnbs are doing great ---
The Sunset Hill House --- https://www.thesunsethillhouse.com/
Prices
of course vary, but up here in small-village Sugar Hill (one store downtown) you
can rent a picture-perfect farm house for $200 per night, a ski chalet on Cannon
Mtn for $200 a night, and the historic dairy barn film Bette Davis hauled in
from Vermont and rebuilt into her main home (rent now for $300 per night) ---
ttps://hookedonhouses.net/2016/01/14/bette-davis-beloved-butternut-farm-new-hampshire/
Airbnbs can
also make labor-saving deals like bring your own sheets and towels and bring
your own breakfasts.
The bottom line is do you want to
pay $300 per night per room with a view versus $300 per night for four bedrooms
in wooded seclusion, a fully-equipped kitchen, a huge family room, and a deck
with a view --- all for $300 per night --- with much more privacy for your
family and friends?
New Hampshire has not yet doubled
the minimum wage to $15 per hour, but when it does hundreds of struggling inns
and other small businesses end up in bankruptcy court (yet again).
In small villages doubling the
minimum wage will wipe out jobs, once again driving people to the bigger cities.
**How to Mislead With Statistics
For years, the estimates of nonfatal gunshot injuries published by the
Centers for Disease Control and Prevention have grown increasingly unreliable
---
https://fivethirtyeight.com/features/how-one-hospital-skewed-the-cdcs-gun-injury-estimate/
Important Issues in Statistical Testing and Recommended Improvements in Research
April 27, 2019 Message from
Tom Dyckman, Emeritus Accounting Professor from Cornell University
Caught by accident a video
of the history of Persia on your blog. I think it was prepared by the
National Historical Association. I watched it for the hour and then another
on the a time-history of the world over the last 200,000 years. Both
fascinating and well done. I now put away an hour each day for education via
your blog. Thanks.
Enclosing my latest
manuscript just accepted for publication in Econometrics. It deals with
issues you have been interested in as well as I that address issues
in statistical testing and accounting.
Have a great day.
Tom
Econometrics Journal ---
https://academic.oup.com/ectj
Jensen Comment
Although the article has not yet been published, here's the introduction:
Important Issues in Statistical Testing and
Recommended Improvements in Accounting Research
Thomas R. Dyckman, Cornell University
Stephen A. Zeff, Rice University
Synopsis:
A great
deal of the accounting research published in recent years has involved
statistical tests. Our paper proposes improvements to both the quality and
execution of such research. We address the following limitations in current
research that appear to us to be ignored or used inappropriately: (1)
unaddressed situational effects resulting from model limitations and what
has been referred to as “data carpentry,” (2) limitations and alternatives
to winsorizing, (3) necessary improvements to relying on a study’s
calculated “p-values” instead of on the economic or behavioral importance of
the results, and (4) the information loss incurred by under-valuing what can
and cannot be learned from replications.
Keywords:
Model Specification, Model Testing, Reporting Results (p-values),
Replications.
Introduction
As
professors of accounting for nearly 60 years and past presidents of the
American Accounting Association, we are concerned about the quality of
statistical research in accounting. This article is a call to our accounting
colleagues, and perhaps also to those in other fields, to invest substantial
time and effort toward improving their requisite knowledge and skill when
conducting the appropriate statistical analysis. Involving expert
statisticians may be helpful, as we all need to recognize the limitations in
our own knowledge in order to tap into this expertise. Our heightened
interest in improvements to the quality of statistical analysis in
accounting research was in response to attending research presentations and
reading the current literature.
Several
years ago, we suggested several improvements to statistical testing and
reporting (Dyckman and Zeff 2014). In that paper, we reviewed the 66
articles involving statistical testing that accounted for 90 percent of the
research papers published between September 2012 and May 2013 in The
Accounting Review and the Journal of Accounting Research,
two leading journals in the field of accounting. Of these 66 papers, 90
percent relied on regression analysis. Our paper examined ways of improving
the statistical analysis and the need to report the economic importance of
the results.
An
extension of these concerns was included in a commissioned paper included in
the 50th anniversary of Abacus (Dyckman and Zeff 2015). We acknowledge
several accounting academics who are also concerned with these issues,
including Ohlson (2018), Kim, Ji and Ahmed (2018), and Stone (2018), whose
works we cite.
Concerns
about statistical testing led to exploring the advantages of a Bayesian
approach and abandoning null hypothesis tests (NHST) in favor of reporting
confidence intervals. We also suggested the advantages – and limitations –
of meta-analysis that would allow for the inclusion of replication studies
in the assessment of evidence. This approach would replace the typical NHST
process and its reliance on p-values (Dyckman 2016).
A fourth
article which reviewed the first 30 years’ history of the research journal,
Accounting Horizons, continued our concern with the current applications of
statistical testing to accounting research. An additional aspect of this
article was the attention we gave to accounting researchers’ seeming lack of
interest in communicating with an audience of professionals beyond other
like researchers, as if their only role as researchers was to enrich the
research literature and not to contribute to the stock of accounting
knowledge. We submit that accounting academics, because of the academic
reward structure in their universities, tend to write for their peers.
Accounting standard setters and accounting professionals, as well as those
who make business and policy decisions, are all too often relegated to the
sidelines. We argued that accounting research should, in the end, be
relevant to important issues faced by accounting professionals, regulators
and management, and that the research findings should be readable by
individuals in this broader user community (Zeff and Dyckman 2018).
In the
current paper, we expand on the statistical testing issues raised in our
earlier papers, and we identify limitations often overlooked or ignored. Our
experience suggests that many accounting professors, and perhaps those in
other fields, are not familiar with, or equipped to, address them. We take
up the following major topics: Model Specification and Data Carpentry,
Testing the Model, Reporting Results, and Replication Studies, followed by A
Critical Evaluation and A Way Forward.
Model
Specification and Data Carpentry
The
choice of a topic and related theory established the basis for the
hypotheses to be examined and the concepts that will constitute the
independent variables. Accounting investigations often rest only on a story
rather than on a theory. A major problem here is that a story, but not
theory, can be changed or modified, which encourages data mining (Black
1993, 73). Establishing the appropriate relationships require an
understanding of the actual decision-making environment. These ingredients,
along with the research team’s insights and abilities, are critical to
designing the research testing program and the data collection and analysis
process. Failure to take them into account in the data-selection decision
process and analysis was discussed in detail in a recent paper by Gow,
Larcker, and Reiss (2016). There, the authors provided a detailed example
(pp. 502-514) of how the decision environment can reflect its own
idiosyncratic differences that, in turn, influence the data. For example,
even if the business context is essentially the same across companies, data
limitations remain. First, the data will inevitably reflect different sets
of decision makers and different organizations, different time periods,
different information, and, at least, some differences in the definitions of
the variables deemed to be relevant. The interactions between these
variables, and with any relevant but excluded variables, will, as the
authors showed, lead to questionable results. How the selected variables
interact with each other – and with any excluded but relevant variables –
depends on the nature of the contextual environment in which the relation
arises. We note here that careful research designs up front can reduce
interactions among the independent variables. Authors can and should
describe the decision environment and differences, if any, that have a
potential impact upon the analysis and conclusions. A thorough analysis and
description of the decision environments is essential and endows additional
credibility on the research.
Continued in article
April 28, 2019 reply from Ed Scribner
Bob,
Maybe this paper by D&Z will
advance the cause of publishing replications.
Ed
April 28, 2019 reply from Bob Jensen
Hi Ed,
More importantly the
two major Dyckman and Zeff papers will (hopefully) advance academic research
into the various ways to mislead with statistics, albeit the "misleading" is
often done innocently (naively) rather than intentionally. Accountics
scientists over the years grew lazy by buying data (think Compustat, CRSP,
and AuditAnalytics) and feeding that data, sometimes unviewed, into
off-the-shelf statistical inference programs (like stirring the stew and
looking for lumps).
It's really naďve to
assume that replication is not needed when the data like Compustat data are
purchased and, therefore, cannot be "fabricated" by the researchers. Even if
we ignore errors in the purchased data, there are many other ways to lazily
mislead using purchased data --- ways summarized broadly in this Dyckman and
Zeff forthcoming 2019 econometrics paper.
Whenever I was asked to
referee papers using statistical inference my first suspicions were sample
size and non-stationarity. Oddly enough, samples are often too large for
statistical inference in accountics science. With very large samples,
differences are often statistically significant but not substantively
different. I recall pointing this out as an assigned discussant at a
conference before Deirdre McCloskey started writing about this problem ---
https://en.wikipedia.org/wiki/Deirdre_McCloskey
Also see
ttp://www.cs.trinity.edu/~rjensen/temp/DeirdreMcCloskey/StatisticalSignificance01.htm
At the conference the author of the paper did not appear to understand this
point that McCloskey latter became known for in economics.
An even bigger problem
is nonstationary populations from which data is sampled ---
https://en.wikipedia.org/wiki/Stationary_process
The classic example here is the major problem with election polling. The
famous statistician (at the time employed by the NYT) named Nate Silver
predicted the day before the 2010 election (for Ted Kennedy's Senate seat)
that Mass. Attorney General Martha Coakley would womp Republican Candidate
Scott Brown. After Scott Brown became Senator Brown Nate Silver discovered
belatedly that due to various reasons
a huge number of voters changed their minds on election day.
Economic/financial
data, like political poll data, are often sampled from non-stationary
processes where non-stationarity is overlooked by accountics scientists.
Dyckman and Zeff focused on this problem in their earlier (2014) paper.
I think it's important to study their 2014 paper before digging into this
subsequent 2019 paper.
Dyckman, T. R., and S. A.
Zeff. 2014. Some methodological deficiencies in empirical research articles
in accounting. Accounting Horizons 28 (3): 695-712.
Thanks,
Bob
April 28 reply from Paul Polinski
Bob: Here's a related column in the journal
Nature's online site ---
https://www.nature.com/articles/d41586-019-01307-2
Paul
April 28, 2019 reply from Bob Jensen
Hi Paul,
What a great citation.
As a doctoral student at Stanford I was one of the luckiest doctoral
students in the USA. The Graduate School of Business sent me to the School
of Engineering to learn statistical inference as taught to engineers.
Engineers are unique in that they are taught about "power" as the Type 2
error skipped over in nearly every discipline except engineering.
Engineering is unique in that quality control is one of the only sampling
population areas where "operating characteristic curves" can be generated
for Type 2 error measurement ---
https://en.wikipedia.org/wiki/Total_operating_characteristic
Is there any statistical inference study in accounting or social science
(including economics or finance) that measured Type 2 error? The proletariat
are destined to only study Type 1 error in statistical inference.
Thanks,
Bob
P-Value Nonsense
Statisticians clamor for retraction of paper by Harvard researchers they say
uses a “nonsense statistic” ---
https://retractionwatch.com/2019/06/19/statisticians-clamor-for-retraction-of-paper-by-harvard-researchers-they-say-uses-a-nonsense-statistic/#more-100498
Bob Jensen's threads on P-value nonsense
---
http://faculty.trinity.edu/rjensen/theory01.htm#WhatWentWrong
Which economic methods are
in practice statistically more honest than others?
https://marginalrevolution.com/marginalrevolution/2020/09/which-economic-methods-are-in-practice-statistically-more-honest-than-others.html
… our
results suggest that the [instrumental variables] and, to a lesser extent,
[difference-in-difference] research bodies have substantially more p-hacking
and/or selective publication than those based on [randomized controlled
trials] and [regression-discontinuity]…
Cornell University: To Your List of Biases in Meta-Analyses, Add
This One: Accumulation Bias ---
https://replicationnetwork.com/2019/07/05/to-your-list-of-biases-in-meta-analyses-add-this-one-accumulation-bias/
“Studies accumulate over
time and meta-analyses are mainly retrospective. These two characteristics
introduce dependencies between the analysis time, at which a series of
studies is up for meta-analysis, and results within the series.”
“Dependencies introduce
bias — Accumulation Bias — and invalidate the sampling distribution assumed
for p-value tests, thus inflating type-I errors.”
“…by using p-value
methods, conventional meta-analysis implicitly assumes that promising
initial results are just as likely to develop into (large) series of studies
as their disappointing counterparts. Conclusive studies should just as
likely trigger meta-analyses as inconclusive ones. And so the use of p-value
tests suggests that results of earlier studies should be unknown when
planning new studies as well as when planning meta-analyses.”
“Such assumptions are
unrealistic… ignoring these assumptions invalidates conventional p-value
tests and inflates type-I errors.”
“… we argue throughout the
paper that any efficient scientific process will introduce some form of
Accumulation Bias and that the exact process can never be fully known.”
“A likelihood ratio
approach to testing solves this problem … Firstly, it agrees with a form of
the stopping rule principle … Secondly, it agrees with the Prequential
principle … Thirdly, it allows for a betting interpretation …: reinvesting
profits from one study into the next and cashing out at any time.”
“This leads to two main
conclusions. First, Accumulation Bias is inevitable, and even if it can be
approximated and accounted for, no valid p-value tests can be constructed.
Second, tests based on likelihood ratios withstand Accumulation Bias: they
provide bounds on error probabilities that remain valid despite the bias.”
Probably the biggest deal in evaluating research is the importance of
replication by different researchers in both the same and varying circumstances.
**How to Mislead With Statistics
Battle for thermostat: Gender and the effect of temperature on cognitive
performance ---
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0216362
Jensen Comment
I don't know if this is a misleading conclusion or not, but I'm dubious for a
number of reasons.
Most importantly, psychology is under suspicion in research due to lack of
replication. First there are replications that are as exacting as possible in
terms of settings and tasks. For example, even for studies in the same location
(Berlin) there are differing circumstances regarding time of the year that can
affect how men and women dress, type of temperature control (e.g., forced air
heating versus baseboard heating), variations in heating over different parts of
large rooms, etc.
Second there are related studies under varying circumstances and tasks. For
example, are there studies regarding gender and job performance relative and
temperatures regarding other tasks such as job performances.
The bottom line is that the conclusions of this research are extremely
tenuous until there are more replications over wide-ranging conditions and other
researchers. And the conclusions are tenuous until medical science comes up with
theories to be tested on the physiological reasons for such gender differences
under varying temperatures.
Cognition is so dependent upon major factors such as motivation (some tests
are just more important than others), variations in factors affecting
preparation and alertness, variations in the tests themselves and how much they
rely on short-term versus long-term memory, etc. Somehow, I don't think
variations in test-taking temperature are as critical as a myriad of other
things affecting cognition.
Bob Jensen's threads on the absurd lack of replication in academic
accountancy research are at
http://faculty.trinity.edu/rjensen/TheoryTAR.htm
Positive Economics and the F-Twist ---
https://en.wikipedia.org/wiki/Essays_in_Positive_Economics
Economic Models vs. The Real World ---
https://mises.org/wire/economic-models-vs-real-world
. . .
The fact that people
consciously pursue purposeful actions provides us with definite knowledge,
which is always valid as far as human beings are concerned. This knowledge
sets the base for a coherent framework that permits meaningful assessments
of the state of an economy. In contrast, analysis that rely solely on
statistical correlations is likely to be problematic. So-called pure
statistical analysis can tell us very little about the essence of economic
activity.
Fanciful Assumptions
Similarly, we must reject
comments that are based on "purely" theoretical models, which derive their
foundation from economists' imaginations that are detached from the facts of
reality. A model, which is not derived from reality, cannot possibly explain
the real world.
For example, in order
to explain the economic crisis in Japan, the famous mainstream economist
Paul Krugman employed a model that assumes that people are identical and
live forever and that output is given.
Whilst admitting that these assumptions are not realistic, Krugman
nonetheless argued that somehow his model can be useful in offering
solutions to the economic crisis in Japan.
Conclusion
To be applicable, an
economic theory must emanate from the essence of what drives human conduct.
The key factor here is purposeful action, and the knowledge that people
pursue purposeful actions permits an analyst to make sense of economic data.
Jensen Comment
There's a huge difference between measurement errors versus missing variables.
When a variable is included in a prediction model, measurement error can be
judged according to
robustness of the prediction to measurement error on that variable. Missing
variables are usually much more troublesome because models cannot be improved by
developing more accurate measuring instruments. There are of course exceptions,
but these are few and far between for missing variables. Missing variables
are "missing" for many reasons such as being unknown or unmeasurable or
impractical to include in a model. For example, the many (infinite?) physical
and psychological factors that can affect performance of an athlete are often
unknown or unmeasureable or impractical to include in performance prediction
models. This is why athletic competitions are games of chance. Life is even more
complicated when it comes to predicting the stock market or GDP.
Between measurement error and missing variables we have the problem of
simplifying assumptions among included variables. For example, in multiple
regression it's common to assume independence among predictor variables when in
fact higher order interactions are usually present even if ignored due to
complications these interactions present. Another simplifying assumption is to
discard outliers among variables included in the model. Outliers are
complicating factors in the real world that distort modelling outcomes.
The biggest problem in statistical analysis is the sampling from
non-stationary processes that greatly complicate underlying statistical
assumptions of stationarity. Recovering addicts do well if the world around then
is a stationary process. However, unforeseeable events in the world around them
may present hurdles that some (not all) cannot overcome relative to people
without such addictions.
Bob Jensen's threads on the limits of analytical models built upon
unrealistic assumptions
Mathmatical Analysis in Plato's Cave ---
http://faculty.trinity.edu/rjensen/TheoryTAR.htm#Analytics
**How to mislead with statistics
There Are 79 Jobs With Six Figure Salaries ----
https://247wallst.com/special-report/2019/08/06/there-are-79-jobs-with-six-figure-salaries-2/9/
Jensen Comment
This is among the most misleading rankings I've ever seen.
Firstly, many of the professionals included in the rankings don't have "jobs"
that pay salaries. They are business owners who rely on profits rather than
salaries. Thinks of surgeons who have their own offices, nurses, physician
assistants, receptionists, accountants, etc. They have many expenses, especially
malpractice insurance policies and claims pay out.
Secondly, many have profit sharing and bonus plans that are almost impossible
to predict above and beyond salaries included in this study.
Thirdly, these are averages with enormous standard deviations and skewed
distributions. For example, college professor salaries and physician assistant
salaries are truncated much lower than salaries of lawyers and brain surgeons.
Fourthly, the jobs vary greatly in terms of benefits. College presidents for
example get free housing, huge expense allowances, cars, etc.
Fifthly, salaries are cover varying parts of the year. Professors, for
example, are included in this study at their nine-month base. Those same
professors get added salaries for summer teaching, research, book royalties,
consulting, patent royalties, etc.
Sixthly, some jobs are conducive to added compensation, particularly outside
consulting, book writing, speeches, musical performances, etc.
The bottom line is that these rankings are mostly garbage and very misleading
for career aspirants.
**How to Mislead With Statistics
The No. 1 job in America with the ‘best career opportunities’ pays
$112,000 a year — and it’s not in tech ---
https://www.marketwatch.com/story/the-no-1-job-in-america-with-the-best-career-opportunities-pays-112000-a-year-and-its-not-in-tech-2019-08-14?mod=article_inline
Jensen Comment
There's a lot that can be deceiving in this article. Firstly, being a tax
manager is not an entrylevel job. The left tail is probably truncated at at
least $100,000 which distorts the mean. More importantly, most tax managers make
a lot more than their base salaries with bonus plans and profit sharing that can
easily double or triple the base salary. Hence, there's a lot of missing data in
the study. It would not be uncommon for the base salary of the tax manager to be
less than that of some of the tech specialists who report to her or him. But
they most likely do not share as heavily in the bonuses and profit sharing
compensations.
The job is sometimes filled with IRS senior agents who are very experienced
with IRS tax accounting and tax planning.
The job is also a stepping stone to becoming a Chief Financial Officer or a
Chief Accounting Officer.
But I do not think that on "average" the compensation of a tax manager is
nearly as high as that of a top surgeon and some other types of physicians. But
surgeons most often are not employees. They are entrepreneurships or
partnerships and receive compensation in the form of business profits after
expenses. The biggest problem when comparing careers according to compensation
is that databases like those of the Department of Labor really don't have
provide data on every aspect of compensation.
**How to Mislead With Statistics
Here's the salary breakdown for Yale's MBA class of 2019,
including the industries that are paying its grads the most ---
https://www.businessinsider.com/the-starting-salaries-for-yales-2019-mba-graduates-2019-12#1-law-8
Jensen Comment
One thing that's misleading is the category "Accounting and Finance." This is
more finance than accounting since most MBA programs, including that of Yale, do
not provide nearly enough accounting to sit for the CPA examination or get a job
in auditing or tax accounting. Any accountants graduating from from most MBA
programs took their accounting, auditing, and tax as undergraduates.
Secondly, those $125,000 annual starting salaries are averages,
and averages are distorted by distribution variations, skewness, and outliers.
More importantly, most of those high-paying starting salaries are
in urban centers like Boston, NYC, Chicago, San Francisco, Washington DC, and
Los Angeles. A starting salary of $125,000 in those cities won't go as far as a
$70,000 salary in Des Moines, Topeka, Oklahoma City, and San Antonio. In San
Francisco you may have to live in your van on only $125,000 per year.
This of course does not mean that some of those high-paying
starting salaries do not open the gates to much higher compensation a few years
down the road. But the best opportunities often depend upon the undergraduate
majors. A computer science, Chinese language, or engineering undergraduate
usually faces more opportunities with a Yale MBA diploma than an undergraduate
in art, music, or history having the same Yale MBA diploma.
And we have to ask why Ivy League MBA diplomas are usually worth
more than an MBA diploma from Cactus Gulch State University?
My answer is that it's mostly the high admission standards of the Ivy League,
University of Chicago, Stanford, and other prestigious university MBA programs.
It's the high standards of admission that count more than the top A
grades that most every graduate gets in the prestigious MBA programs.
My main point is that any measure of
central tendency cannot represent the total distribution without being
potentially misleading. It takes a graphic or some table of outcomes showing the
entire distribution.
One of the main distortions is to not
give special consideration to those who remain unemployed after graduation such
as an MBA graduate who elects for a time to be a parent at home with zero salary
or a relatively low salary from part-time employment. People get college degrees
with the long-run in mind, and doing an analysis at a point in time can be
misleading.
I would also like to see a factoring
out of some outliers. Two of my close friends at Stanford University decades ago
were an MBA student and his wife who lived in an apartment next door for a time.
Jerry graduated with an MBA and went to work an enormous salary where he would
have worked had he never gone to college. His father owned what was possibly the
largest car dealership in the State of Minnesota. Jerry started out the day
after graduation as the CEO.
Jerry was an outlier, but there are
likely to be several such outliers each year where graduates go to work at high
salaries in family businesses. Another example of an MBA friend at the time is a
graduate whose father owned the largest department store in Sydney, Australia.
Another example, is one of my former students who today is a billionaire (at
least on paper). He was a CEO of his own company when he commenced at Trinity
University as a freshman at age 18.
And there are bound to be some outliers
of unemployed graduates, including those that are unemployed for reasons other
than parenthood. MBA graduates are commonly not earning much to begin with
because they're commencing their own startups. I recall one Stanford MBA
graduate who partnered with his sister to form an ultimately successful chain of
cookie stores that financed his failed attempt to become a world-famous author.
In the first year of graduation his income was negative.
And there's the issue of salary before
and after getting a degree of any kind. I don't think Jack Palance's Hollywood
income changed because he got a degree from Stanford after he was already a
famous actor.
These are the types of distortions that
I have in mind when I talk about outliers and other aberrations in
distributions.
**How to mislead with statistics
Schools ranked by student/faculty ratio ---
https://oedb.org/rankings/student-faculty-ratio/
This link also suggests why low ratios are expected to help learning.
The first thing to note is that very low student/faculty ratios often are
associated with specialty colleges like seminaries and other specialty college
that have increasingly hard times attracting students.
Secondly, the best (lowest) ratios are in heavily endowed universities (think
Ivy League). But this can be somewhat misleading in terms of exclusion of some
graduate programs from the calculations. For example, Harvard has a low 7/1
ratio overall but certainly not in the MBA or law school programs that are cash
cows with very large classes with high student/faculty ratios.
Thirdly, class sizes are sometimes skewed giving rise to misleading
student/faculty ratios. In flagship universities it's very common to have very,
very large classes for basic core courses in order to have much smaller classes
for majors in junior and senior years. Thus a flagship state university does not
necessarily have very large classes uniformly across the campus. It's extremely
common these days for colleges to have faculty shortages in majors that are the
most popular with students. For example, the many humanities departments may be
rich in faculty numbers relative to the number of majors in humanities such that
senior level seminars may only have three or four students.
But the business school having many more majors may end up
with senior-level courses with 100 or more students because of severe shortage
of faculty in the business school.
Fourthly, it's very difficult to conduct studies on the impact of
student/faculty ratios when comparing universities because there are so many
confounding factors such as admissions standards and grading rigor. Add to this
the impact of varying use of distance education. Distance education is unique in
that students online often have more intense learning relationships with both
teachers and other students. Student/faculty ratios may be less revealing in
online courses.
Fifthly, low student/faculty ratios say nothing about the quality and
dedication of the faculty to teaching. Some colleges and universities have 90%
or higher tenure rates giving rise to job securities that are more independent
of teaching performance than in schools having much lower tenure rates with
faculty being more intensely evaluated as to performance along various criteria,
including teaching.
Sixthly, universities with low student/faculty ratios may be smaller
universities that just do not have many faculty or students. For example, the
Computer Science Department at Cactus Gulch College may only have 12 majors and
two faculty members. Flagship State University may have 800 computer science
majors and 40 faculty in computer science. Where would you like your daughter to
major in computer science? Chances are Flagship State has many more curriculum
options and specialty courses in computer science leading to much better job
prospects relative to Cactus Gulch computer science graduates.
Lastly, low student/faculty ratios are not always best. The Harvard Business
School has very high student/faculty ratios, but most any Harvard MBA graduates
will tell you they learned more from other students than they did from faculty.
This, in part, is due to the Socratic pedagogy of the Harvard Business School
were most courses focus on cases where students rather than faculty solve the
cases in class or in teams of students outside the classroom. Socratic learning
is intended for students to learn more from each other than from faculty who do
not lecture under the Socratic pedagogy --- often faculty who do not even reveal
best answers. Often the cases are so complex there are no "best answers." My
point here is that having higher student/faculty ratios may be better under the
Socratic Pedagogy ---
https://en.wikipedia.org/wiki/Socratic_method
The bottom line here is that the "best" place to go to college is extremely
complicated and multivariate in terms of so many things that student/faculty
ratios can be meaningful in some contexts and extremely misleading in other
contexts. The Harvard Business School and the Wharton Business School
(Pennsylvania) have relatively high student/faculty ratios. But graduates of
those programs end up on uniquely fast tracks to Wall Street employment or
corporate employment that overwhelm almost any other criterion in terms of
students wanting to get on those same employment tracks. At the same time having
a 1/1 student faculty ratio in the classics might be very ideal at Oxford
University if you hope to teach classics at Cambridge University or Harvard
University.
And "size" does matter in many ways, including the non-academic aspect of
college life. The University of Texas at Austin affords many opportunities for
great learning, but when it comes to dormitory living Jester Hall is so enormous
it has two zip codes. Many young people leaving home for the first time do not
want that kind of "bigness." Cactus Gulch may not have all the computer science
opportunities of UT-Austin, but living and learning and extracurricular life at
Cactus Gulch may be better in combination for many students. You don't have to
be NFL material to participate in varsity football at Cactus Gulch. You may
become relatively close to every student living in your Cactus Gulch dorm.
And when you encounter a Cactus Gulch professor while walking on campus that
professor might actually know your name. Don't count on this at UT-Austin.
And you might enjoy the quiet of you Cactus Gulch dorm, a quiet that never
happens at Jester Hall 24/7 with its fast food joints and all the stereos
blaring and residents/non-residents who live by night rather than day amid the
police sirens.
**How to Mislead With Statistics
Double-Counting of Investment
by Robert J. Barro, NBER Working Paper No. 25826
Issued in May 2019, Revised in July 2019
https://www.nber.org/papers/w25826
The national-income accounts double-count investment, which enters once when it
occurs and again in present value as rental income on added capital. The
double-counting implies over-statement of levels of GDP and national income.
Across countries, those with higher propensities to invest artificially look
richer gauged by per capita GDP. There is also exaggeration of capital-income
shares. An alternative measure involves a form of full expensing of gross
investment. In the steady state, revised product and income correspond to
consumption. Outside of the steady state, the measure deviates from consumption
because full expensing applies to the long-run flow of gross investment.
You may purchase
this paper on-line in .pdf format from SSRN.com ($5) for electronic delivery
Also see
https://marginalrevolution.com/marginalrevolution/2019/07/robert-barro-says-we-double-count-investment.html
The Democratic Party will soon be writing a 2020 Election Platform. What I
fear is that this platform will overlook the following question:
What will the Democratic Party do for pension savings?
Like it or not pension savings are very fragile for the USA's hundreds of
millions of city workers, county workers, state workers, hotel workers, auto
workers, teachers, college employees, and nearly all other workers in the public
and private sectors.
The problem is that most every worker's pension savings
balance is dependent upon capital market values (e.g., stock prices, bond
prices, and real estate prices).
The 2020 Democratic Party Platform will likely propose new social spending
programs for green initiatives, free medical care, free medications, student
loan forgiveness followed by free college for everybody, guaranteed annual
income for 350+ USA residents, housing-for all, reparations for African and Native Americans, and
billions for new subsidized housing on top of existing safety nets such as food
stamps and welfare and housing.
Taxes will have to be increased annually by trillions of dollars to pay for
these new social programs.
Stock markets in the USA just reached all-time highs. The question is whether
those increased trillions in taxes will crash the capital markets
and, thereby, wipe out the pension savings of hundreds of
millions or workers.
To date the Democratic Party is vague about how it will fund the trillions of
dollars planned annually for new social programs.
How will pension savings be preserved when trillions in new taxes are
proposed?
What will keep stock markets from crashing?
For example, will free college for students wipe out the pension savings of
their parents in funds like CalPERS, CREF, Fidelity, Vanguard, e
In OECD nations (think Finland, Denmark, Germany, and Norway) that have free
college or free job training, well over half of the Tier 2 graduates are
not even allowed to go to college or receive free job
training paid for by their governments. This makes "free college" or
"free training" affordable by limiting it only to top graduates . . .
https://en.wikipedia.org/wiki/List_of_countries_by_tertiary_education_attainment
Bernie Sanders’s housing-for-all plan, explained
---
https://www.vox.com/2019/9/19/20873224/bernie-sanders-housing-for-all
The Atlantic: But the profits of health
insurers are not that exorbitant compared with other parts of the health-care
system. And in fact, many scholars suggest that American health care is so
dysfunctional because it simply costs too much. That’s the fault of doctors,
drugmakers, and hospitals, too, not just insurers ---
https://www.theatlantic.com/health/archive/2019/07/kamala-harris-blames-health-insurers-she-right/595252/?utm_source=newsletter&utm_medium=email&utm_campaign=politics-daily-newsletter&utm_content=20191101&silverid-ref=NTk4MzY1OTg0MzY5S0
Nancy Pelosi Is 'Not a Big Fan of Medicare For All’ ---
https://townhall.com/tipsheet/juliorosas/2019/11/01/nancy-pelosi-is-not-a-big-fan-of-medicare-for-all-n2555747?utm_source=thdaily&utm_medium=email&utm_campaign=nl&newsletterad=11/02/2019&bcid=b16c6f948f297f77432f990d4411617f&recip=17935167
**How to Mislead With Political False Promises
Updates on Medical Insurance
Leading Leftist Economists Split over Feasibility of
Medicare-for-All
Lawrence Summers ---
https://en.wikipedia.org/wiki/Lawrence_Summers
Paul Krugman ---
https://en.wikipedia.org/wiki/Paul_Krugman
Former Harvard University President and USA Treasury
Secretary under President Obama argues that Medicare-for-All replacement of
private sector coverage is not feasible
---
https://theintercept.com/2019/11/03/joe-biden-larry-summers-elizabeth-warren-medicare-for-all/
Especially look at
https://www.washingtonpost.com/opinions/2019/11/05/warrens-plan-finance-medicare-for-all-pushes-into-dangerous-uncharted-territory/
Also see his comments on a wealth tax intended to partially fund
Medicare-for-All
https://marginalrevolution.com/marginalrevolution/2019/10/summers-on-the-wealth-tax.html
Hillary Clinton Is Not a Fan of Bernie’s or Warren’s Wealth
Taxes ---
Click Here
She thinks they’re “unworkable” and would be “incredibly disruptive.”
Former Princeton Nobel Economist and New York
Times Columnist Paul Krugman argues that Medicare-for-All replacement of
private sector coverage is feasible
---
https://www.nytimes.com/2019/11/01/opinion/did-warren-pass-the-medicare-test-i-think-so.html
Jensen Comment
By the way, the radical Paul Krugman will no longer be subjected to the
editorial restraints of the New York Times--
https://krugman.blogs.nytimes.com/2017/12/06/the-blog-moves-on/?module=BlogPost-Title&version=Blog
Main&contentCollection=Opinion&action=Click&pgtype=Blogs®ion=Body
A message for regular readers of this blog: unless
something big breaks later today, this will be my last day blogging AT THIS
(NYT) SITE. The Times is consolidating the
process, so future blog-like entries will show up at my regular
columnist page. This should broaden the
audience, a bit, maybe, and certainly make it easier for the Times to
feature relevant posts.
It will also, for technical reasons, make my life
simpler — you’d be surprised how many hoops I
have to go through to get these (NYT) things
posted. But that’s not the reason.
Anyway, I expect to be
doing the same sort of thing, mixing regular columns with stuff, usually
wonkish, that doesn’t belong in the regular paper. Old blog posts will
remain available
Paul Krugman
Jensen Comment
One of the things I don't like about Paul Krugman is his
inconsistency in bending his economics to fit his
political agenda.
The "social safety net" includes such things as free medical
care, free education, food stamps, housing subsidies, and welfare.
Open immigration can’t exist with a strong
social safety net; if you’re going to assure healthcare and a decent income to
everyone, you can’t make that offer
global ---
Paul Krugman
https://www.goodreads.com/quotes/724654-open-immigration-can-t-exist-with-a-strong-social-safety-net
But now that Paul Krugman wants Elizabeth Warren or
Bernie Sanders to be President of the USA he changed his tune about a global
offer and promotes a honey pot of safety nets to
anybody who can sneak across the USA border, including
free medical care, free education, food stamps, housing subsidies, and
guaranteed annual income.
You can't have it both ways on global offers Paul.
Elizabeth Warren Finally Says How She'll Pay for Medicare for All
https://www.bloomberg.com/news/articles/2019-11-01/warren-pays-for-medicare-for-all-by-taxing-companies-wealthy?cmpid=BBD110119_BIZ&utm_medium=email&utm_source=newsletter&utm_term=191101&utm_campaign=bloombergdaily
Senator Elizabeth Warren said she would fund her
version of Medicare for All with taxes on large corporations and the
wealthy, a tax evasion crackdown, a reduction in defense spending and by
putting newly legalized immigrants on the tax rolls.
Her advisers also lowered the estimate of Medicare for
All’s price-tag to $20.5 trillion over 10 years from the $34 trillion the
Urban Institute predicted, by using the new Medicare-for-All negotiating
power to slash administrative spending, drug prices and provider payments.
Jensen
Comment
She
also promises that there will be zero taxes on the middle class to pay
for Medicare-for-All, Free College, Guaranteed Annual Income, Reparations, and
on and on and on.
The
promise of zero taxes on the middle class is misleading. Who does she think
ultimately pays for the taxes on large corporations? Large corporations don't
pay taxes. They collect taxes from their customers
which in most cases are the poor and the middle class customers.
And
what happens if you confiscate the wealth of Americans. They have to liquidate
their investments in stocks and real estate, thereby confiscating the pensions
and savings of the poor and middle class.
Notice
that she never says how she will keep pension funds viable when the stock
markets crash!
How to Mislead With Political False Promises
Elizabeth Warren Finally Says How She'll Pay for Medicare for All (Yeah Right!)
https://www.bloomberg.com/news/articles/2019-11-01/warren-pays-for-medicare-for-all-by-taxing-companies-wealthy?cmpid=BBD110119_BIZ&utm_medium=email&utm_source=newsletter&utm_term=191101&utm_campaign=bloombergdaily
Senator Elizabeth Warren said she would fund her
version of Medicare for All with taxes on large corporations and the
wealthy, a tax evasion crackdown, a reduction in defense spending and by
putting newly legalized immigrants on the tax rolls.
Her advisers also lowered the estimate of Medicare for
All’s price-tag to $20.5 trillion over 10 years from the $34 trillion the
Urban Institute predicted, by using the new Medicare-for-All negotiating
power to slash administrative spending, drug prices and provider payments.
Jensen
Comment
She
also promises that there will be zero taxes on the middle class to pay
for Medicare-for-All, Free. Plus she did not factor in the additional trillions
for Green Initiatives, Free College, Guaranteed Annual Income, Reparations, and
on and on and on.
Her
promise of zero taxes on the middle class is misleading. Who does she think
ultimately pays for the taxes on large corporations (think Walmart, Amazon, and
Exxon)? Large corporations don't pay taxes.
They collect taxes in prices to their customers which in
most cases are the poor and the middle class customers. Warren will
even collect from transactions that are exempt from sales tax such as when the
Pentagon pays billions to Boeing for aircraft and Microsoft for cloud services.
And
what happens if you confiscate the wealth of Americans. They have to liquidate
their investments in stocks and real estate, thereby confiscating the pensions
and savings of the poor and middle class.
“80%
of the assets of the rich are publicly traded stocks, bonds, real estate (upon
which most of the USA's pension and savings plans depend) ---
https://www.factcheck.org/2019/06/facts-on-warrens-wealth-tax-plan/
Notice that she never says how she will keep savings
investments pension pension incomes viable when the stock markets crash for
good!
Facts on Warren’s Wealth Tax Plan ---
https://www.factcheck.org/2019/06/facts-on-warrens-wealth-tax-plan/
. . .
How would the (wealth) tax revenues be spent?
Warren
is banking on a $2.75 trillion revenue projection from Zucman and Saez to
fund a host of her priorities. In speeches,
she has laid
out those beneficiaries:
-
Universal child care for every child age 0 to 5.
-
Universal pre-K for every 3- and 4-year old.
-
Raise wages for all child care workers and preschool teachers “to the
professional levels that they deserve.”
-
Free tuition and fees for all public technical schools, 2-year colleges
and 4-year colleges.
-
$50 billion for historically black colleges and universities.
-
Forgive student loan debt for 95% of those with such debt.
-
$100 billion over 10 years to combat the opioid
crisis.
-
“Down
payments” on a Green New Deal and
Medicare for All.
The Warren campaign estimates the first three programs — dealing with child
care and universal pre-K — would cost about $700 billion over 10 years. And
the next three — free public college tuition, money for historically black
colleges and canceling most student loan debt — would cost about $1.25
trillion over 10 years. That would leave more than about $750 billion for
the Green New Deal and Medicare for All, the campaign says. That’s not
enough to fully fund either one, but Warren says it is enough for a “down
payment” on each.
How reliable is Warren’s $2.75 trillion revenue forecast?
Whether Warren’s plan would actually raise $2.75 trillion is a matter of
debate among economists.
The $2.75
trillion forecast comes
from Zucman and Saez. To estimate how much revenue the tax would generate on
wealth over $50 million, the economists used data from the Survey
of Consumer Finances from the Federal Reserve Board and the Distributional National
Accounts recently created by economist Thomas
Piketty,
Saez and Zucman. To estimate the revenue from the tax on billionaires, the
economists used the Forbes 400 list of the richest 400 Americans in 2018.
Zucman and Saez estimated that people would reduce their reported wealth by
15% “through a combination of tax evasion and tax avoidance.” The authors
wrote that “recent research shows that the extent of wealth tax
evasion/avoidance depends crucially on loopholes and enforcement. The
proposed wealth tax has a comprehensive base with no loopholes and is well
enforced through a combination of systematic third party reporting and
audits. Therefore, the avoidance/evasion response is likely to be small.”
But some economists think that assumption is too rosy.
While neither the Tax Policy Center nor the Tax Foundation has yet released
a full analysis of Warren’s plan, economists at both said there is reason to
believe Warren’s revenue estimate is too high.
Kyle Pomerleau,
chief economist and vice president of economic analysis at the nonprofit,
pro-business Tax Foundation, said that the assumption of 15% tax
evasion/avoidance is “actually the average avoidance for the entire U.S. tax
system, which is primarily the income tax and payroll tax. These taxes are,
in principle, much harder to avoid than a wealth tax because the transaction
(income) is hard to game or hide from the tax authorities. There is a good
record of how much you are being paid by your employer.”
“A wealth tax, on the other hand, is much harder to enforce,” Pomerleau
said. “For one, much of the wealth tax base doesn’t have a market price. For
example, we don’t really know how much a particular privately-held business
is worth because equity (stocks) in that company are not regularly traded on
the open market.”
Pomerleau also warned that because the wealth tax is a significant tax on
savings, it will discourage people from holding on to assets. “This effect
will reduce the potential tax base,” Pomerleau said, a trend that was not
accounted for in Warren’s estimate.
Howard Gleckman,
a senior fellow at the nonpartisan Tax Policy Center, has similar concerns.
“First, while her plan anticipates some tax avoidance, it will be very
difficult for the IRS to keep up with the tax planning that highly-paid
lawyers and accountants can devise,” Gleckman told us via email. “With so
much money at risk, the wealthy will have powerful incentives to hire smart
advisers to help avoid, or at least reduce, their tax liability.
“Second, a large share of wealth held by the high net worth taxpayers is in
the form of privately held businesses,” he said. “And these are notoriously
difficult to value. In effect, the IRS would have to prove that a taxpayer’s
valuation is unreasonably low.”
“I suspect she would collect less revenue than she predicts, but I cannot
say how much less,” Gleckman told us.
In an op-ed published
in the Washington Post on April 4,
Lawrence Summers, a Harvard
University professor who was treasury secretary from 1999 to 2001 and an
economic adviser to President Barack Obama in 2009 and 2010, and Natasha
Sarin, an assistant professor of law at the University of Pennsylvania Law
School and an assistant professor of finance at the Wharton School, took
direct aim at the $2.75 trillion estimate.
“Common-sense revenue estimates by economists who are not very deeply
steeped in revenue estimation tend to be overly optimistic,” Summers and
Sarin wrote.
The two looked at the U.S. experience with estate tax data and concluded
Warren’s wealth tax would only raise about 40% of the amount estimated by
Saez and Zucman. And that’s being “maximally optimistic about the wealth
tax’s revenue potential,” Summers and Sarin wrote.
“We suspect that to a great extent it reflects the myriad ways wealthy
people avoid paying estate taxes that in some form will be applicable in any
actually legislated wealth tax,” Summers and Sarin wrote. “These include
questionable appraisals; valuation discounts for illiquidity and lack of
control; establishment of trusts that enable division of assets among family
members with substantial founder control; planning devices that give some
income to charity while keeping the remainder for the donor and her
beneficiaries; tax-advantaged lending schemes; and other complex devices
known only to sophisticated investors. Except for reducing a naive
calculation by 15 percent, Saez and Zucman do not seem to take account of
these devices.”
“If our suspicion is correct, such a wealth tax will not yield the revenue
that its proponents hope for, and that when actual scorekeepers score actual
proposals, their estimates will disappoint advocates,” they concluded.
“In our view, the $2.75T is not realistic,” Sarin wrote to us in an email.
“The closest we get based on extrapolation from the estate tax (which seems
relevant because it involves a very similar population and thus many of the
same evasion incentives and possibilities) is around 40% of this estimate.”
In an email response to FactCheck.org, Saez challenged the Summers and Sarin
use of the estate tax to estimate the effects of Warren’s wealth tax
proposal.
“It is well known that the estate tax is very poorly enforced and that the
rich manage to largely avoid/evade it by giving to heirs before death,
spouses, and charity, using lots of trick to discount assets,” Saez wrote.
“We
have assumed an evasion rate of 15% based on the best literature on the
question (as we discuss in our letter and in more detail here),”
Saez
added.
Saez said the Summers-Sarin estimate that the tax on those with assets worth
more than $50 million would bring in just $25 billion a year implicitly
assumes “that over 90% of the wealth will be hidden.” That’s not reasonable,
Saez said, because
“80% of the assets of the rich are publicly traded stocks, bonds, real
estate for which there are clear market values
Continued in article
Urban Institute: From Incremental to Comprehensive Health Reform: How Various
Reform Options Compare on Coverage and Costs ---
https://www.urban.org/research/publication/incremental-comprehensive-health-reform-how-various-reform-options-compare-coverage-and-costs
Report:
From Incremental to Comprehensive Health
Insurance Reform: How Various Reform Options Compare on Coverage and Costs
Brief:
Comparing Health Insurance Reform Options: From
“Building on the ACA” to Single Payer
Blog Post:
Don’t
Confuse Changes in Federal Health Spending with National Health Spending
Policymakers, including candidates in the 2020 presidential campaign and
members of Congress, have proposed a variety of options to address the
shortcomings of the current health care system. These range from
improvements to the Affordable Care Act to robust single-payer reform.
There are numerous challenging trade-offs when choosing an approach to
health care reform, including covering the uninsured, improving the
affordability of health care, and raising the government funding required to
implement them. The public and policymakers alike need more information
about the potential effects of various health reform proposals.
This study, funded by the Commonwealth Fund, analyzes eight health care
reforms and their potential effects on health insurance coverage and
spending. Each of the analyzed reform proposals makes health insurance
considerably more affordable by reducing people’s premiums and cost sharing.
Some reforms also reduce US health care costs, and all require additional
federal dollars.
Key findings:
·
Within the existing public-private health care system, near universal
coverage and improved affordability could be achieved with moderate
increases in national health spending. Under
one of the plans modeled in the report, which proposes a mix of private and
public health insurance, everyone in the US could be covered except for
undocumented immigrants. The plan would enable workers to opt for subsidized
nongroup coverage instead of their employer’s insurance plan. It would also
improve the ACA’s subsidies to help people afford coverage, cover people in
states that have not expanded Medicaid, require everyone to have insurance
with an auto-enrollment backup, offer a public insurance option, and cap
provider payment rates.
Coverage and costs:
This reform plan achieves universal coverage for people legally present in
the US, covering 25.6 million people who would otherwise be uninsured.
However, the plan leaves 6.6. million undocumented immigrants without
coverage. National spending on health care would decrease modestly, by $22.6
billion or 0.6 percent, compared with current law in 2020. Federal
government spending would increase by $122.1 billion in 2020, or $1.5
trillion over 10 years.
·
One single-payer approach would leave no one uninsured and largely eliminate
consumers’ out-of-pocket medical costs but would require much greater
federal spending to finance. The
modeled “enhanced” single-payer system would cover everyone, including
undocumented immigrants. The reform would include benefits more
comprehensive than Medicare’s—including adult dental, vision, hearing, and
long-term services and supports—with no premiums or cost sharing. All
current forms of insurance for acute care would be eliminated, including
private insurance, Medicaid, and Medicare, and everyone residing in the US
would be covered by a new public insurance program. Providers would be paid
rates closer to Medicare’s. Health spending by employers would be
eliminated, and household and state health spending would decline
considerably while federal spending would increase significantly.
Coverage and costs:
This reform option covers the entire US population. National spending on
health care would grow by about $720 billion in 2020. Federal government
spending would increase by $2.8 trillion in 2020, or $34.0 trillion over 10
years.
·
A second single-payer approach can be constructed with lower federal and
system-wide costs. In
addition to the enhanced single-payer plan above, researchers examined a
single-payer “lite” plan that is similar to the enhanced version but
includes cost sharing for out-of-pocket expenses based on income, adds fewer
new covered benefits, and only covers legally residing US residents.
Single-payer “lite” lowers total national health spending, decreasing health
spending by households, employers, and state governments and increasing
federal government spending by less than the enhanced single-payer reform.
Coverage and costs:
This reform plan achieves universal coverage for people legally present in
the US, covering 25.6 million people who were uninsured. However, the plan
leaves all 10.8 million undocumented immigrants without coverage (due to the
elimination of private insurance). National spending on health care would
decrease by $209.5 billion, or 6 percent, in 2020. Federal government
spending would increase by $1.5 trillion in 2020, or by $17.6 trillion over
10 years. The analysis demonstrates that there is more than one effective
approach to achieving universal health care coverage in the United States
and highlights the trade-offs of different reform strategies.
The analysis demonstrates that there is more than one effective approach to
achieving universal health care coverage in the United States and highlights
the trade-offs of different reform strategies.
Continued in article
Rob
Rrownstein: The Eye-Popping Cost of Medicare for All According to new
figures: more than the federal government will spend over the coming decade on
Social Security, Medicare, and Medicaid combined ---
https://www.theatlantic.com/politics/archive/2019/10/high-cost-warren-and-sanderss-single-payer-plan/600166/?utm_source=newsletter&utm_medium=email&utm_campaign=politics-daily-newsletter&utm_content=20191016&silverid-ref=NTk4MzY1OTg0MzY5S0
The Urban Institute estimates that a single-payer plan
would require $32 trillion in new tax revenue over the coming decade.
How big a lift is it to raise $32 trillion? It’s
almost 50 percent more than the total revenue the CBO projects Washington
will collect from the personal income tax over the next decade (about $23.3
trillion). It’s more than double the amount the CBO projects Washington will
collect over the next decade from the payroll tax that funds Social Security
and part of Medicare (about $15.4 trillion).
Jensen
Comment
And the Medicare for All Spending initiative is a relatively small part of what
most 2020 Presidential Candidates (except for Biden) want to spend on social
programs. To the average $3.2 trillion annual cost of Medicare for All the
annual cost of their Green Initiatives,
free medications, student loan forgiveness followed by free college for
everybody, guaranteed annual income for 350+ USA residents, housing-for all,
reparations for African and Native Americans, and billions for new subsidized
housing on top of existing safety nets such as food stamps and welfare and
housing.
Add to
this the free medical care, free college, housing, and food advertising for poor
people all over the world in cross-over-the-border invitations and you're easily
talking over $20 trillion per year. Whereas President Obama deported over a
million undocumented immigrants, the 2020 candidates are inviting people to
cross over the USA borders.
The
most misleading statement in the October 15, 2019 debates was Elizabeth Warren's
comment that she will not promote any "spending program that taxes the middle
class." But notice that she says nothing about destruction of the middle class
pensions dependent upon stock market prices (think CREF and CalPERS). She's
probably right about middle income retirees not paying more taxes. We won't have
any incomes left to tax if you destroy the stock markets.
And
when the stock markets are destroyed unemployment will soar because business
firms will lose the ability to raise capital necessary for operating businesses.
Businesses can turn to government for capital, but the cupboard will be bare due
to all the social programs draining $20 trillion from the economy.
Why did the number of working class college degrees increase when England
started charging tuition?
https://reason.com/2019/08/22/democrats-love-to-promise-free-college-but-why-did-u-k-recently-started-charging-tuition/
Jensen Comment
In the UK it became a choice of making free college available only to top
students (like in other EU nations) or to make it more widely available at
levels the UK taxpayers could not possibly provide without substantial
tuition supplements.
In OECD nations (think Finland, Denmark, Germany, and Norway) that have free
college or free job training, well over half of the Tier 2 graduates are not
even allowed to go to college or receive free job training paid for
by their governments. This makes "free college" or "free training" affordable by
limiting it only to top graduates . . .
https://en.wikipedia.org/wiki/List_of_countries_by_tertiary_education_attainment
The Democratic Party's 2020 Platform will assuredly not limit
the USA's free college to the very top high school graduates.
Current Democratic Party proposals for free college cannot possibly be sustained
at the number of students they hope to educate or train for free,
“You have to make decisions that you’re going
to reach certain goals, and some of our goals we
think are achievable”
Nancy Pelosi
In Europe and Elsewhere Free College Education Means College is Only for the
Intellectually Elite
Countries that provide more public funding for higher education tend to have
fewer graduates over all (restricting college education or free job training
to only the most intelligent 1/3 or Tier 2 graduates ---
https://www.insidehighered.com/news/2019/08/08/countries-often-sacrifice-postsecondary-attainment-when-they-expand-subsidies?utm_source=Inside+Higher+Ed&utm_campaign=5f76e299a1-DNU_2019_COPY_01&utm_medium=email&utm_term=0_1fcbc04421-5f76e299a1-197565045&mc_cid=5f76e299a1&mc_eid=1e78f7c952
Democratic politicians
-- many of them vying for their party's 2020 presidential nomination --
propose free college programs or other major investments in higher education
that reflect systems in countries like Finland and Sweden. But an American
Enterprise Institute report released
Thursday argues that when developed nations dedicate more public resources
to postsecondary education, they tend to produce fewer graduates.
The institute's customarily contrarian resident fellow, Jason Delisle, and
co-author Preston Cooper, an education research analyst at AEI, compared 35
high-income (gross domestic product per capita above $30,000) member
countries of the Organisation for Economic Co-operation and Development,
which produces statistics on countries’ total institutional spending,
college attainment rates among 25- to 34-year-olds, and government
subsidies. The OECD includes almost all large Western and Central European
countries, Australia, the Baltic states, Chile, Israel, Japan, New Zealand,
North America, Scandinavia, South Korea and Turkey.
Each country makes sacrifices when it prioritizes one aspect of higher
education -- attainment rates, institutional spending and government
subsidies -- over another, Delisle said, a reality he thinks is often
ignored during debates about free college. Politicians in the U.S. like to
suggest America can “learn from other countries and take the good parts” of
their education systems, without considering the impact subsidized education
has on the overall quality and accessibility of college, Delisle said.
“If you have a heavily subsidized system, that leads a country to ration
higher education, leading to a system that’s more selective,” Delisle said. “That’s
not an egalitarian higher education policy, which a lot of policy makers on
the left insist is the case.”
“If you want less college, one way to do that is to make it free,” he
said.
Delisle’s interest in researching international spending on higher education
was piqued during the 2016 presidential campaign, he said, when Senator
Bernie Sanders, the Vermont Independent, began promoting his plan to
eliminate the cost of attending public colleges and universities. More
recently, on June 24, Sanders announced his College
for All Act,
which if passed would eliminate tuition at public institutions and subsidize
learning with 100 percent government funding -- 67 percent from Washington
and 33 percent from individual states.
“[The legislation] makes certain that all Americans, regardless of income,
can get the college education or job training they need to secure
decent-paying jobs by making public colleges, universities and trade schools
tuition-free and debt-free,” Sanders said in a news
release.
However, college admissions would become much more competitive if the U.S.
could not rely on tuition to fund its institutions, Delisle said, though the
goal of free college policy suggestions is to increase the number of
students with degrees.
“The whole public university system in Finland has an admissions rate on par
with elite U.S. colleges,” Delisle said. “Not quite as selective as Harvard
or the [Ivy League colleges], but if you took a Berkeley, or a [University
of Virginia] -- imagine if the entire education system of the U.S. had to
meet UVA-level test scores.”
In the report, Delisle highlights Finland, which ranks first among the 35
countries in government subsidies provided for tertiary education
(international equivalent to an associate degree or higher in the U.S.).
Ninety-six percent of Finland’s higher education resources are public, but
its attainment rate -- the proportion of citizens ages 25 to 34 with a
degree beyond K-12 education -- is less than 45 percent, placing it 25th
among OECD countries. South Korea-based higher education, on the other hand,
gets about 36 percent of its funding from the government and achieves a
70 percent attainment rate, the highest among OECD countries, according to
the report.
The U.S. ranks 31st for subsidies and third when it comes to institutional
resources, which is measured as the amount of money -- a combination of
government funds and private dollars -- spent on each full-time-equivalent
student. These numbers are also adjusted for a country’s GDP per capita, so
as not to penalize countries with smaller economies for spending less.
The report praises more investment in higher education from government and
private sources as positive, suggesting that “generally, institutions with
greater resources have more latitude to offer a high-quality education.”
This could bring criticism from “our colleagues on the right” who prioritize
spending reductions, Delisle said.
“We gave [spending] a positive spin, and we also gave attainment a positive
spin,” Delisle said. “There are definitely people on the right who would
say, ‘We have too many people with college degrees and spend too much on
higher education.’”
The OECD includes subsidized student loan programs in its spending metrics,
so while governments in the U.S., U.K. and Australia are increasingly
providing loans and debt forgiveness, that’s not counted as public funding
in the report, Delisle said. Instead, student loans are considered
individual expenditures on tuition, though they could be paid off by these
governments in the future.
Loans should be kept in mind when reading the report, Delisle said, but they
don’t have enough impact in the U.S. to shift the country’s ranking, since
the government uses more of a “safety net” model for specific groups of
students in need. But forgiven loans make up a higher share of Australia’s
and the U.K.’s subsidies, which can’t be seen in the OECD data, he said.
There are other contextual differences between countries that are also
absent from data in the report, because these differences are vast and
difficult to measure, Delisle said. One variance -- countries’ typical age
range for college attainment -- could affect how the report is read, said
Alex Usher, president of Higher Education Strategy Associates.
While the AEI report analyzes 25- to 34-year-olds who may or may not have
degrees, students in Nordic countries tend to start college later and often
take breaks from their learning to participate in the labor market, Usher
said. Additionally, Nordic countries have a lower wage premium for
college-educated adults than the U.S., he said.
“Those countries tend to look fantastic when you look at adult education --
it’s actually adults who are going back and forth and taking breaks” from
higher ed, Usher said. “Here, it’s normal at age 25 to have a degree. There,
it’s not so normal.”
Continued in article
Sen. Bernie Sanders and Rep. Ilhan Omar on Monday proposed legislation to
cancel all federal and private student-loan debt, carried by about 45 million
Americans ---
https://www.chronicle.com/article/No-Exceptions-No-Questions/246553?utm_source=at&utm_medium=en&cid=at
Wall Street lashes out at Bernie Sanders' plan to pay off student debt
with a securities trading tax ---
https://www.investmentnews.com/article/20190624/FREE/190629961/wall-street-lashes-out-at-bernie-sanders-plan-to-pay-off-student
Jensen Comment
The problem is compounded by the fact that progressives want to spend tens of
trillions needed to fund debt forgiveness and free college in future years,
including spending programs for green initiatives, free medical care, free
medications, student loan forgiveness followed by free college for everybody,
guaranteed annual income for 350+ million USA residents, housing-for-all,
reparations for African and Native Americans, and billions housing-for-all on top of
existing safety nets such as food stamps and welfare and housing.
Bernie Sanders also wants to make you believe banks and brokerages will be
paying the $20 trillion annually. Absolute lie! Business firms don't pay taxes.
They collect taxes from customers. A tax imposed on brokerage transactions hits
pension funds for teachers, firefighters, professors, trash haulers, middle
class investors, and wealthy investors. Taking $100 trillion from brokerage
transactions (even if it were possible) would shut down stock markets and bond
markets and bankrupt pension funds.
The cost student debt forgiveness alone is nearly equal to all $1.7+ trillion
Federal income tax revenue currently used to fund existing government spending
---
https://www.usdebtclock.org/
Vague references are made to are made to taking the $1.6+ trillion
from rich investors, but no mention is made of how the aggregated cost of this
$1.6 trillion added to other new spending programs costing $100 trillion will
crash the stock, bond, and real estate markets.
When combined with free college education for anybody who wants it this will
make funding more difficult for $100 trillion in green initiatives,
Medicare-for-All, free medications for all, free nursing homes, guaranteed
annual income for 350+ million residents, reparations for black and native
Americans, and so on down the 2020 socialist democratic wish list.
My guess is that Sanders would not have backed this in current legislation if
it had a chance of getting the approval of the Senate and President Trump. If it
passed it would greatly complicate his other spending plans, especially
Medicare-for-All.
The ultimate cost of all this spending will be borne by USA pension fund
holders (think CREF and CalPERS) since pension funds depend mostly upon stock,
bond, and real estate markets that will crash if you take
$100+ trillion
from investors in any form whatsoever.
Progressive spenders never talk about how they will save USA's pension
funds for teachers, municipal workers, business workers, etc.
The bottom line is that for most student borrowers
the funding of the student-loan cancellation will wipe out the pension funds of
their parents.
Wall Street lashes out at Bernie Sanders' plan to pay off student debt
with a securities trading tax ---
https://www.investmentnews.com/article/20190624/FREE/190629961/wall-street-lashes-out-at-bernie-sanders-plan-to-pay-off-student
Jensen Comment
The problem is compounded by the fact that progressives want to spend tens of
trillions more on things other than student debt forgiveness and free college in
future years, including spending programs for green initiatives, free medical
care, free medications, student loan forgiveness followed by free college for
everybody, guaranteed annual income for 350+ USA residents, reparations for
African and Native Americans, and billions for new subsidized housing on top of
existing safety nets such as food stamps and welfare and housing.
Bernie Sanders also wants to make you believe banks and brokerages will be
paying the $100 trillion dollars. Absolute lie! Business firms don't pay taxes.
They collect taxes from customers. A tax imposed on brokerage transactions hits
pension funds for teachers, firefighters, professors, trash haulers, middle
class investors, and wealthy investors. Taking $100 trillion from brokerage
transactions (even if it were possible) would shut down stock markets and bond
markets and bankrupt pension funds.
The cost student debt forgiveness alone is nearly equal to all $1.7+ trillion
Federal income tax revenue currently used to fund existing government spending
---
https://www.usdebtclock.org/
Vague references references are made to are made to taking the $1.6+ trillion
from rich investors, but no mention is made of how the aggregated cost of this
$1.6 trillion added to other new spending programs costing $100 trillion will
crash the stock, bond, and real estate markets.
When combined with free college education for anybody who wants it this will
make funding more difficult for $100 trillion in green initiatives,
Medicare-for-All, free medications for all, free nursing homes, guaranteed
annual income for 350+ million residents, reparations for black and native
Americans, and so on down the 2020 socialist democratic wish list.
My guess is that Sanders would not have backed this in current legislation if
it had a chance of getting the approval of the Senate and President Trump. If it
passed it would greatly complicate his other spending plans, especially
Medicare-for-All.
The ultimate cost of all this spending will be borne by USA pension fund
holders (think CREF and CalPERS) since pension funds depend mostly upon stock,
bond, and real estate markets that will crash if you take
$100+ trillion
from investors in any form whatsoever.
Progressive spenders never talk about how they will save USA's pension
funds for teachers, municipal workers, business workers, etc.
The bottom line is that for most student borrowers
the funding of the student-loan cancellation will wipe out the pension funds of
their parents.
When England got rid of free college, enrollment
expanded, expenditure per student expanded, and inequality of access did NOT
increase ---
https://twitter.com/Noahpinion/status/1145783708802097152
Bernie Sanders’s housing-for-all plan,
explained ---
https://www.vox.com/2019/9/19/20873224/bernie-sanders-housing-for-all
How to Mislead With Statistics
Washington Post: Bernie Sanders and other Democrats are embracing free
college. Europe shows it can be done, but there’s a cost.
https://www.washingtonpost.com/world/europe/bernie-sanders-and-other-democrats-are-embracing-free-college-europe-shows-theres-a-cost/2019/06/25/2939047c-8bc4-11e9-b6f4-033356502dce_story.html?utm_term=.fcf29f7bfba6
Jensen Comment
I don't know how often I have to keep repeating something that the NYT,
Washington Post, Time Magazine, and other liberal media won't mention. These
news sources keep repeating the message that college education is free in
Europe. Yes it is free in most European nations, but these news outlets never
mention that it's only free for the intellectually elite. Unless you're in the
top third (or so) of your Tier 2 school (read that high school) you can't even
go to college let alone get a free college education. This is not at all what
Bernie Sanders and Elizabeth Warren have in mind for the USA which is providing
a free college education for any of the 350+ million residents of the USA who
want a college education.
In OECD nations (think Finland, Denmark, Germany, and Norway) that have free
college or free job training, well over half of the Tier 2 graduates are
not even allowed to go to college or receive free job
training paid for by their governments. This makes "free college" or
"free training" affordable by limiting it only to top graduates . . .
https://en.wikipedia.org/wiki/List_of_countries_by_tertiary_education_attainment
No --- Europe has not
shown that free college or free job training paid for by taxpayers can be done
for more than the top third of Tier 2 graduates. And yes this does hit minority
student hard since they are less likely to be in the top third.
And yes the top third of
USA's high school graduates and a nearly all of the USA's top minority students
get substantial financial aid for college. Most of the $1.6 trillion in student
debt is carried by students who were not so intellectually elite. These students
would not be eligible for a free college education or free job training if they
lived in Europe.
And by the way, most of
the job training costs in Europe are paid for by employers rather than
taxpayers.
Why did the number of working class college degrees increase when England
started charging tuition?
https://reason.com/2019/08/22/democrats-love-to-promise-free-college-but-why-did-u-k-recently-started-charging-tuition/
Jensen Comment
In the UK it became a choice of making free college available only to top
students (like in other EU nations) or to make it more widely available at
levels the UK taxpayers could not possibly provide without substantial
tuition supplements.
In OECD nations (think Finland, Denmark, Germany, and Norway) that have free
college or free job training, well over half of the Tier 2 graduates are not
even allowed to go to college or receive free job training paid for
by their governments. This makes "free college" or "free training" affordable by
limiting it only to top graduates . . .
https://en.wikipedia.org/wiki/List_of_countries_by_tertiary_education_attainment
The Democratic Party's 2020 Platform will assuredly not limit
the USA's free college to the very top high school graduates.
Current Democratic Party proposals for free college cannot possibly be sustained
at the number of students they hope to educate or train for free,
“You have to make decisions that you’re going
to reach certain goals, and some of our goals we
think are achievable”
Nancy Pelosi
In Europe and Elsewhere Free College Education Means College is Only for the
Intellectually Elite
Countries that provide more public funding for higher education tend to have
fewer graduates over all (restricting college education or free job training
to only the most intelligent 1/3 or Tier 2 graduates ---
https://www.insidehighered.com/news/2019/08/08/countries-often-sacrifice-postsecondary-attainment-when-they-expand-subsidies?utm_source=Inside+Higher+Ed&utm_campaign=5f76e299a1-DNU_2019_COPY_01&utm_medium=email&utm_term=0_1fcbc04421-5f76e299a1-197565045&mc_cid=5f76e299a1&mc_eid=1e78f7c952
Democratic politicians
-- many of them vying for their party's 2020 presidential nomination --
propose free college programs or other major investments in higher education
that reflect systems in countries like Finland and Sweden. But an American
Enterprise Institute report released
Thursday argues that when developed nations dedicate more public resources
to postsecondary education, they tend to produce fewer graduates.
The institute's customarily contrarian resident fellow, Jason Delisle, and
co-author Preston Cooper, an education research analyst at AEI, compared 35
high-income (gross domestic product per capita above $30,000) member
countries of the Organisation for Economic Co-operation and Development,
which produces statistics on countries’ total institutional spending,
college attainment rates among 25- to 34-year-olds, and government
subsidies. The OECD includes almost all large Western and Central European
countries, Australia, the Baltic states, Chile, Israel, Japan, New Zealand,
North America, Scandinavia, South Korea and Turkey.
Each country makes sacrifices when it prioritizes one aspect of higher
education -- attainment rates, institutional spending and government
subsidies -- over another, Delisle said, a reality he thinks is often
ignored during debates about free college. Politicians in the U.S. like to
suggest America can “learn from other countries and take the good parts” of
their education systems, without considering the impact subsidized education
has on the overall quality and accessibility of college, Delisle said.
“If you have a heavily subsidized system, that leads a country to ration
higher education, leading to a system that’s more selective,” Delisle said. “That’s
not an egalitarian higher education policy, which a lot of policy makers on
the left insist is the case.”
“If you want less college, one way to do that is to make it free,” he
said.
Delisle’s interest in researching international spending on higher education
was piqued during the 2016 presidential campaign, he said, when Senator
Bernie Sanders, the Vermont Independent, began promoting his plan to
eliminate the cost of attending public colleges and universities. More
recently, on June 24, Sanders announced his College
for All Act,
which if passed would eliminate tuition at public institutions and subsidize
learning with 100 percent government funding -- 67 percent from Washington
and 33 percent from individual states.
“[The legislation] makes certain that all Americans, regardless of income,
can get the college education or job training they need to secure
decent-paying jobs by making public colleges, universities and trade schools
tuition-free and debt-free,” Sanders said in a news
release.
However, college admissions would become much more competitive if the U.S.
could not rely on tuition to fund its institutions, Delisle said, though the
goal of free college policy suggestions is to increase the number of
students with degrees.
“The whole public university system in Finland has an admissions rate on par
with elite U.S. colleges,” Delisle said. “Not quite as selective as Harvard
or the [Ivy League colleges], but if you took a Berkeley, or a [University
of Virginia] -- imagine if the entire education system of the U.S. had to
meet UVA-level test scores.”
In the report, Delisle highlights Finland, which ranks first among the 35
countries in government subsidies provided for tertiary education
(international equivalent to an associate degree or higher in the U.S.).
Ninety-six percent of Finland’s higher education resources are public, but
its attainment rate -- the proportion of citizens ages 25 to 34 with a
degree beyond K-12 education -- is less than 45 percent, placing it 25th
among OECD countries. South Korea-based higher education, on the other hand,
gets about 36 percent of its funding from the government and achieves a
70 percent attainment rate, the highest among OECD countries, according to
the report.
The U.S. ranks 31st for subsidies and third when it comes to institutional
resources, which is measured as the amount of money -- a combination of
government funds and private dollars -- spent on each full-time-equivalent
student. These numbers are also adjusted for a country’s GDP per capita, so
as not to penalize countries with smaller economies for spending less.
The report praises more investment in higher education from government and
private sources as positive, suggesting that “generally, institutions with
greater resources have more latitude to offer a high-quality education.”
This could bring criticism from “our colleagues on the right” who prioritize
spending reductions, Delisle said.
“We gave [spending] a positive spin, and we also gave attainment a positive
spin,” Delisle said. “There are definitely people on the right who would
say, ‘We have too many people with college degrees and spend too much on
higher education.’”
The OECD includes subsidized student loan programs in its spending metrics,
so while governments in the U.S., U.K. and Australia are increasingly
providing loans and debt forgiveness, that’s not counted as public funding
in the report, Delisle said. Instead, student loans are considered
individual expenditures on tuition, though they could be paid off by these
governments in the future.
Loans should be kept in mind when reading the report, Delisle said, but they
don’t have enough impact in the U.S. to shift the country’s ranking, since
the government uses more of a “safety net” model for specific groups of
students in need. But forgiven loans make up a higher share of Australia’s
and the U.K.’s subsidies, which can’t be seen in the OECD data, he said.
There are other contextual differences between countries that are also
absent from data in the report, because these differences are vast and
difficult to measure, Delisle said. One variance -- countries’ typical age
range for college attainment -- could affect how the report is read, said
Alex Usher, president of Higher Education Strategy Associates.
While the AEI report analyzes 25- to 34-year-olds who may or may not have
degrees, students in Nordic countries tend to start college later and often
take breaks from their learning to participate in the labor market, Usher
said. Additionally, Nordic countries have a lower wage premium for
college-educated adults than the U.S., he said.
“Those countries tend to look fantastic when you look at adult education --
it’s actually adults who are going back and forth and taking breaks” from
higher ed, Usher said. “Here, it’s normal at age 25 to have a degree. There,
it’s not so normal.”
Continued in article
Alexandria Ocasio-Cortez says her Green New Deal climate plan would cost at
least $10 trillion ---
https://www.businessinsider.com/alexandria-ocasio-cortez-says-green-new-deal-cost-10-trillion-2019-6
Jensen Comment
She forgot to include a few costly items like the cost of networking the USA
with electric high-speed rail that replaces airplanes and airports. She also
fails to mention the cost of wiping out most employee pension funds due to
green-initiative plan costs combined with free medical insurance, free nursing
homes, free medications, free college, guaranteed annual income for 350+ million
residents of the USA, interest on $22+ trillion of national debt, combined with
existing free food stamps, free housing, Social Security benefits,
pensions, and other safety nets you're talking over $100 trillion per year.
Both
the Joe Biden and Elizabeth Warren green-initiative plans draw on the
progressive Green New Deal, prioritize environmental justice, and would be paid
for by closing corporate tax loopholes ---
https://psmag.com/news/green-jobs-and-new-technology-a-look-at-biden-and-warrens-latest-climate-plans?omhide
Jensen
Comment
If you start talking green-initiative plan costs combined with free medical
insurance, free nursing homes, free medications, free college, guaranteed annual
income for 350+ million residents of the USA, interest on $22+ trillion of
national debt, combined with existing free food stamps, housing subsidized,
Social Security benefits, pensions, and other safety nets you're talking over
$100 trillion per year. That cannot possibly be funded by closing corporate tax
loop holes, wealth taxes, or a 100% marginal income tax rate on high salaried
people --- and if you try to do so you will wipe out virtually all pension funds
of the USA.
It's
irresponsible for presidential candidates and their supporting media to promote
spending $100 trillion per year without also showing how this can be done
without destroying the stock markets, bond markets, and real estate markets
--- and the pension funds (think CREF and CalPERS) built almost entirely upon
those investor markets. My favorite example is how free college is
great for students but not if you zero out the pension funds of their parents.
Lets see the presidential candidates generate some
realistic numbers on how to support their new spending programs without
destroying pension savings in the USA.
Bernie Sanders’s housing-for-all plan,
explained ---
https://www.vox.com/2019/9/19/20873224/bernie-sanders-housing-for-all
**How to Mislead with Missing Variables
Young People Support Free College ---
https://www.insidehighered.com/news/2019/05/03/poll-support-free-college-among-young-people?utm_source=Inside+Higher+Ed&utm_campaign=f3e733cb11-DNU_2019_COPY_01&utm_medium=email&utm_term=0_1fcbc04421-f3e733cb11-197565045&mc_cid=f3e733cb11&mc_eid=1e78f7c952
Jensen Comment
This is a perfect example of what we call missing variables analysis. Free
college under Elizabeth Warren's plan will cost over a trillion dollars a year.
Add this to the yearly trillions her other proposed programs will cost.
The 2020 Democratic Party Platform will likely propose new social spending
programs for green initiatives, free medical care, free medications, student
loan forgiveness followed by free college for everybody, guaranteed annual
income for 350+ USA residents, reparations for African and Native Americans, and
billions for new housing-for-all, on top of existing safety nets such as food
stamps and welfare and housing.
The missing variable when young people "support free college" is the capital
market crash (think stock prices, bond prices, and real estate prices). New
annual spending for the above social programs will entail trillions in annual
taxation and most of those trillions will come out of the pockets of capital
markets investors and corporate profits. It's a virtual certainty that stock
markets will crash.
Now think of a young child of a university employee who's now enjoying
reports of record high pension savings in CREF. The USA stock markets are
currently at all-time highs. While that college employee's child is wishing for
free college that same child is not
considering what free college and the other spending programs mentioned will do
to capital markets --- spending that will almost certainly wipe out the value of
his or her parents' pension savings in TIAA/CREF.
Like it or not pension savings are very fragile for the USA's hundreds of
millions of city workers, county workers, state workers, hotel workers, auto
workers, teachers, college employees, and nearly all other workers in the public
and private sectors.
The problem is that most every worker's pension savings
balance is dependent upon capital market values (e.g., stock prices, bond
prices, and real estate prices).
How will pension savings be preserved when trillions in new taxes are
proposed?
What will keep stock markets from crashing at we tax capital market
investors and corporate profits for trillions of more dollars each year?
For example, will free college for all USA students wipe out the pension savings of
their parents in funds like CalPERS, CREF, Fidelity, Vanguard, etc.?
Progressives will counter that other nations manage to provide free college
and still have pension savings.
In OECD nations (think Finland, Denmark, Germany, and Norway) that have
free college or free job training, well over half of the Tier 2 graduates are not even allowed to go to college or receive free
job training paid for by their governments. This makes "free college"
or "free training" affordable by limiting it only to top graduates . . .
https://en.wikipedia.org/wiki/List_of_countries_by_tertiary_education_attainment
The Democratic Party's 2020 Platform will assuredly not
limit the USA's free
college to the very top high school graduates.
“You have to make decisions that you’re going to reach certain goals, and some
of our goals we think are
achievable”
Nancy Pelosi
"Plan for the best, but prepare for the worst"
Bob Jensen's fortune cookie on April 30, 2019 (my fortune cookie really did
say that).
Bernie Sanders’s housing-for-all plan,
explained ---
https://www.vox.com/2019/9/19/20873224/bernie-sanders-housing-for-all
Why did the number of working class college degrees increase when England
started charging tuition?
https://reason.com/2019/08/22/democrats-love-to-promise-free-college-but-why-did-u-k-recently-started-charging-tuition/
Jensen Comment
In the UK it became a choice of making free college available only to top
students (like in other EU nations) or to make it more widely available at
levels the UK taxpayers could not possibly provide without substantial
tuition supplements.
In OECD nations (think Finland, Denmark, Germany, and Norway) that have free
college or free job training, well over half of the Tier 2 graduates are not
even allowed to go to college or receive free job training paid for
by their governments. This makes "free college" or "free training" affordable by
limiting it only to top graduates . . .
https://en.wikipedia.org/wiki/List_of_countries_by_tertiary_education_attainment
The Democratic Party's 2020 Platform will assuredly not limit
the USA's free college to the very top high school graduates.
Current Democratic Party proposals for free college cannot possibly be sustained
at the number of students they hope to educate or train for free,
“You have to make decisions that you’re going
to reach certain goals, and some of our goals we
think are achievable”
Nancy Pelosi
In Europe and Elsewhere Free College Education Means College is Only for the
Intellectually Elite
Countries that provide more public funding for higher education tend to have
fewer graduates over all (restricting college education or free job training
to only the most intelligent 1/3 or Tier 2 graduates ---
https://www.insidehighered.com/news/2019/08/08/countries-often-sacrifice-postsecondary-attainment-when-they-expand-subsidies?utm_source=Inside+Higher+Ed&utm_campaign=5f76e299a1-DNU_2019_COPY_01&utm_medium=email&utm_term=0_1fcbc04421-5f76e299a1-197565045&mc_cid=5f76e299a1&mc_eid=1e78f7c952
Democratic politicians
-- many of them vying for their party's 2020 presidential nomination --
propose free college programs or other major investments in higher education
that reflect systems in countries like Finland and Sweden. But an American
Enterprise Institute report released
Thursday argues that when developed nations dedicate more public resources
to postsecondary education, they tend to produce fewer graduates.
The institute's customarily contrarian resident fellow, Jason Delisle, and
co-author Preston Cooper, an education research analyst at AEI, compared 35
high-income (gross domestic product per capita above $30,000) member
countries of the Organisation for Economic Co-operation and Development,
which produces statistics on countries’ total institutional spending,
college attainment rates among 25- to 34-year-olds, and government
subsidies. The OECD includes almost all large Western and Central European
countries, Australia, the Baltic states, Chile, Israel, Japan, New Zealand,
North America, Scandinavia, South Korea and Turkey.
Each country makes sacrifices when it prioritizes one aspect of higher
education -- attainment rates, institutional spending and government
subsidies -- over another, Delisle said, a reality he thinks is often
ignored during debates about free college. Politicians in the U.S. like to
suggest America can “learn from other countries and take the good parts” of
their education systems, without considering the impact subsidized education
has on the overall quality and accessibility of college, Delisle said.
“If you have a heavily subsidized system, that leads a country to ration
higher education, leading to a system that’s more selective,” Delisle said. “That’s
not an egalitarian higher education policy, which a lot of policy makers on
the left insist is the case.”
“If you want less college, one way to do that is to make it free,” he
said.
Delisle’s interest in researching international spending on higher education
was piqued during the 2016 presidential campaign, he said, when Senator
Bernie Sanders, the Vermont Independent, began promoting his plan to
eliminate the cost of attending public colleges and universities. More
recently, on June 24, Sanders announced his College
for All Act,
which if passed would eliminate tuition at public institutions and subsidize
learning with 100 percent government funding -- 67 percent from Washington
and 33 percent from individual states.
“[The legislation] makes certain that all Americans, regardless of income,
can get the college education or job training they need to secure
decent-paying jobs by making public colleges, universities and trade schools
tuition-free and debt-free,” Sanders said in a news
release.
However, college admissions would become much more competitive if the U.S.
could not rely on tuition to fund its institutions, Delisle said, though the
goal of free college policy suggestions is to increase the number of
students with degrees.
“The whole public university system in Finland has an admissions rate on par
with elite U.S. colleges,” Delisle said. “Not quite as selective as Harvard
or the [Ivy League colleges], but if you took a Berkeley, or a [University
of Virginia] -- imagine if the entire education system of the U.S. had to
meet UVA-level test scores.”
In the report, Delisle highlights Finland, which ranks first among the 35
countries in government subsidies provided for tertiary education
(international equivalent to an associate degree or higher in the U.S.).
Ninety-six percent of Finland’s higher education resources are public, but
its attainment rate -- the proportion of citizens ages 25 to 34 with a
degree beyond K-12 education -- is less than 45 percent, placing it 25th
among OECD countries. South Korea-based higher education, on the other hand,
gets about 36 percent of its funding from the government and achieves a
70 percent attainment rate, the highest among OECD countries, according to
the report.
The U.S. ranks 31st for subsidies and third when it comes to institutional
resources, which is measured as the amount of money -- a combination of
government funds and private dollars -- spent on each full-time-equivalent
student. These numbers are also adjusted for a country’s GDP per capita, so
as not to penalize countries with smaller economies for spending less.
The report praises more investment in higher education from government and
private sources as positive, suggesting that “generally, institutions with
greater resources have more latitude to offer a high-quality education.”
This could bring criticism from “our colleagues on the right” who prioritize
spending reductions, Delisle said.
“We gave [spending] a positive spin, and we also gave attainment a positive
spin,” Delisle said. “There are definitely people on the right who would
say, ‘We have too many people with college degrees and spend too much on
higher education.’”
The OECD includes subsidized student loan programs in its spending metrics,
so while governments in the U.S., U.K. and Australia are increasingly
providing loans and debt forgiveness, that’s not counted as public funding
in the report, Delisle said. Instead, student loans are considered
individual expenditures on tuition, though they could be paid off by these
governments in the future.
Loans should be kept in mind when reading the report, Delisle said, but they
don’t have enough impact in the U.S. to shift the country’s ranking, since
the government uses more of a “safety net” model for specific groups of
students in need. But forgiven loans make up a higher share of Australia’s
and the U.K.’s subsidies, which can’t be seen in the OECD data, he said.
There are other contextual differences between countries that are also
absent from data in the report, because these differences are vast and
difficult to measure, Delisle said. One variance -- countries’ typical age
range for college attainment -- could affect how the report is read, said
Alex Usher, president of Higher Education Strategy Associates.
While the AEI report analyzes 25- to 34-year-olds who may or may not have
degrees, students in Nordic countries tend to start college later and often
take breaks from their learning to participate in the labor market, Usher
said. Additionally, Nordic countries have a lower wage premium for
college-educated adults than the U.S., he said.
“Those countries tend to look fantastic when you look at adult education --
it’s actually adults who are going back and forth and taking breaks” from
higher ed, Usher said. “Here, it’s normal at age 25 to have a degree. There,
it’s not so normal.”
Continued in article
Trump’s Tariffs Only Work If Americans Pay Them
---
http://nymag.com/intelligencer/2019/05/trumps-china-tariffs-only-work-if-americans-pay-them.html
Jensen Comment
Actually Trump's tariffs work better at hurting the
Chinese economy if Americans don't pay them
just like Chinese tariffs (think soybeans) hurt American farmers when the
Chinese refuse to pay.
Demand Curve ---
https://en.wikipedia.org/wiki/Demand_curve
Example, tariffs hurt exporters if foreign customers learn to
live with less or find substitute suppliers. For example, China is learning how
to live with less soybeans. The USA is learning how to live with fewer imported
Chinese goods and in many cases shifting to other foreign suppliers like Chile,
South Korea, Indonesia, and Bangladesh.
American tariffs do work if Americans don't pay them. Chinese
tariffs work if the Chinese don't pay them. The problem is that both nations are
hurt badly with tariff walls. It hurts for Chinese to do with high quality
soybeans from the USA. It hurts to not have as much lithium coming from China
for use in batteries.
The problem is that economic issues in trade talks are turning
into face-saving politics where each nation is shooting itself in the foot with
pride and politics.
For academics, what matters more: journal prestige or readership?
https://www.sciencemag.org/careers/2019/07/academics-what-matters-more-journal-prestige-or-readership
Jensen Comment
The more interesting question is more complicated depending upon what one means
by "journal." It also varies with needs of the academic. Exhibit A is Paul
Krugman who has a Nobel Prize in Economics and a very popular blog in the New
York Times. It's misleading to compare whether a NYT Blog article or an article
in liberal media magazine called Slate or an article in the Journal of
Political Economy matters most to Paul.
Paul Krugman ---
https://en.wikipedia.org/wiki/Paul_Krugman
An occasional publication in a very prestigious and rigorously refereed
article such as the JPE matters a great deal to Paul
for maintaining respect as an economic theorists.
But the following article a choosy popular press magazine (Slate) gets
across an important and controversial message that he wants to be read
worldwide. For example, the following reference is very important to him
because, in defending multinational corporations, he riled the core audience of
the liberal Slate and even riled his core constituency in general.
Publishing this article in the WSJ or JPE would not have had the same emotional
worldwide impact.
"In
Praise of Cheap Labor," by Paul Krugman,
Slate, March 21, 1997 ---
https://slate.com/business/1997/03/in-praise-of-cheap-labor.html
In this article Paul demonstrates academic independence which I'm sure pleased
him even though his core constituency emotionally disagrees with his conclusions
in this article.
But it must please him even more when he stirs up his conservative critics
--- something he does regularly in his NYT blog. Yeah I know that in most blogs
and Websites the publications do not pass through a rigorous refereeing process
that chooses whether to publish or not publish an article. But once published or
cited in a popular blog the article may obtain hundreds or thousands of
commentaries.
Paul Krugman’s Most Evil Idea ---
https://marginalrevolution.com/marginalrevolution/2019/08/paul-krugmans-most-evil-idea.html
Especially note to number and range of commentaries --- including my own comment
published on August 2, 2019:
Never fear. Paul Krugman will swoop down from
Fantasy Heaven and show the USA how to raise $20+ trillion dollars to fund
the Democratic Party platform programs for Green Initiative costs combined
with free Medicare-for-All, free medications, free nursing homes, free
college, guaranteed annual income for 350+ million residents of the USA,
interest on eventual $200+ trillion of national debt, free food, free
housing, Social Security benefits, pensions, and other safety nets. Please
swoop down and save the USA pensions and the rest of the USA economy Paul.
Meanwhile the economy seems to be rolling along
with relatively low unemployment and record stock prices and record pension
fund levels. Those damn Republicans are really killing us Paul --- that is
before you swoop down to make big improvements in our economy and its
incoming hordes of undocumented immigrants.
It never dawned on me that you can raise $20+
trillion just by using the printing presses.
Added Jensen Comment
My added point this morning is that I don't think you can compare whether
journal prestige or readership matters most to an academic. Too much depends
upon circumstances. Whether you are an untenured assistant professor or a Nobel
Prize winner publishing in a prestigious journal that is rigorously refereed is
very important for for respect among your academic peers. Blogging controversial
articles that are widely read around the world is very important if you've
already earned a Nobel Prize. Doing so as an untenured assistant professor is
not at all advisable when the articles are controversial.
Also blogging popular articles daily probably takes too
much time for an untenured assistant professor.
My point is that the importance of journal prestige versus
readership varies considerably with stage of life and emotional attachment to
causes (think politics). I don't think we can really answer the question of
whether a publication in JPE matters more or less to Paul Krugman. relative to
publishing an article in Slate or the NYT. All are vitally important to
him for different reasons. An untenured assistant professor does not get such
luxury.
How to Mislead With Statistics
Do the Rich Get All the Gains from Economic Growth?
https://medium.com/@russroberts/do-the-rich-capture-all-the-gains-from-economic-growth-c96d93101f9c?sk=0e4f1f8aba0dcb0674bdf34af8b3ec08
Jensen Comment
This article pretty well explains how leading economists mislead for political
purposes. It seems so obvious that in the USA virtually everybody has benefited
from economic growth even if all have not shared anywhere near equally in the
bounty of growth. Cubans, on the other hand, would have
shared equally if there had been any significant economic growth.
Why did Cuba
abandon its socialist/communist dream of equality for everybody?
The Guardian: This was the
egalitarian dream of Cuba in the 1960s: For years in Cuba, jobs as varied as
farm workers and doctors only had a difference in their wages of the equivalent
of a few US dollars a month.
https://www.theguardian.com/world/2008/jun/12/cuba
Jensen Comment
Only now is Cuba backtracking from its egalitarian dream by uncapping wages and
legalizing profits while liberals in the USA want to return again to the 1960s
Cuban dream.
May 2019
**How to Mislead With Statistics
Polls Say Biden, Bernie Could Beat Trump. Should You Believe Them?
https://reason.com/2019/04/29/polls-say-biden-bernie-could-beat-trump-should-you-believe-them/
Jensen Comment
What is the most misleading about an traditional political poll?
Answer: It's reported accuracy. For example, the Emerson College Poll claims
93% accuracy on election day.
What this ignores how the poll is at times before election day, especially over
a year before election day.
Polls tend to converge with considerable accuracy
on election day, but they are often way off base long before elections.
Right up to the day of election, the
population from which polls are sampled is usually a non-stationary process
that, in many instances, changes dramatically week to week.
Also the polls can be highly inaccurate in very close races. The 2016
Presidential election is a dramatic illustration of polling errors since
virtually all polls predicted Clinton would beat Trump.
The article pretty well explains why polls are misleading, especially over a
year in advance. One problem is that polls often intentially bias predictions
because they themselves favor certain candidates. They may become less biased
closer to election day in an effort to appear to be more accurate on election
day.
One ranking of poll accuracy ---
https://projects.fivethirtyeight.com/pollster-ratings/
The American Dream: Kurdish Immigrant Becomes a
Billionaire ---
TED Talk: Hamdi Ulukaya: The anti-CEO playbook ---
https://www.ted.com/talks/hamdi_ulukaya_the_anti_ceo_playbook?utm_source=newsletter_weekly_2019-05-24&utm_campaign=newsletter_weekly&utm_medium=email&utm_content=talk_of_the_week_image
Jensen Comment
This video is not as anti-business as it sounds, and the fact that Ulukaya
became a billionaire as a CEO entrepreneur proves it. But he did in a socially
responsible way with hiring of refugees and local workers and the sharing of
corporate equity with employees.
Some things are overlooked in this otherwise inspiring video. Firstly, employees
that have their savings invested in their employer's company need, at some point
like retirement, to liquidate their holdings. In other words,
they need some kind of market for their shares that have
increased in value on paper but not necessarily in liquidity. One way
of achieving liquidity is the cursed IPO when private corporate shares are going
public to get into a cash market for those shares. Then
investors start asking questions like what are the profits and what is the
financial security of this investment?
The bottom line is that this is a pro-capitalism video, and seemingly
anti-socialist if you watch it closely. But it's socially responsible capitalism
to a point of where employees and Ulukay himself (a billionaire on paper) want
to cash in on their shares.
The other thing to note about Ulaukaya's yogurt business is that this is a
labor-intensive business relative to more capital-intensive businesses (think
electric cars and pharmaceuticals) that need to justify "profits" or
"anticipated profits" to get investors to put money into the business.
Hence it's a great video for a business case where there's a lot to debate like
keeping wages relatively low by paying in ownership shares.
How to Mislead With Statistics: Error leads to recall of paper
linking Jon Stewart and election results (the authors later apologized)
---
http://retractionwatch.com/2019/05/14/this-is-how-science-works-error-leads-to-recall-of-paper-linking-jon-stewart-and-election-results/#more-92576
Jensen Comment
The authors' apologies for careless work summarize what happened. Interestingly,
a number of readers got suspicious beforehand.
**How to Mislead With Statistics and Biased Media
Reporting (the externality of motivating the police to do less and less and
less)
Here are the stories about police misconduct uncovered so far by a new
media partnership ---
https://www.latimes.com/local/lanow/la-me-police-files-roundup-20190319-story.html
Jensen Comment
It would also be nice if the media partnership also reported good conduct deeds
by law enforcement.
The real problem about reporting police misconduct is that "no action" can
easily go undetected. For example, in Baltimore police are now suspected of
simply looking the other way in the presence of rising street crimes and traffic
crimes. Or the police might create long delays until a relatively formidable
armed squad can be assembled before entering dangerous public housing complexes
and domestic dispute residences.
And police departments can be simply overwhelmed (think Chicago and
Baltimore) by the number of murders and rapes such that "investigations" become
badly understaffed and underfunded.
Meanwhile minorities are the most impacted by reduced
police protections just like urban school children and their teachers are
subjected to more bullying and gang violence by paranoid school administrators
and security guards. Teachers in NYC now
complain that in some districts inmates have overtaken the asylum ---
https://www.manhattan-institute.org/html/school-discipline-reform-and-disorder-evidence-nyc-schools-10103.html
**How to Mislead With Statistics (missing variables)
American Economic Review: Who Pays for the
Minimum Wage? ---
https://www.aeaweb.org/articles?id=10.1257/aer.20171445&&from=f
Jensen
Comment
This is one of those studies with conclusions that are embedded in a whole lot
of unmentioned caveats. For example:
Does Hungary have anything close to the $2 trillion underground economy that
provides alternatives to the minimum wage for both employers and employees?
Are
there enormous differences between industries such as restaurant workers
versus landscape workers (in Texas there are probably more landscape workers
working in the underground economy than the
economy paying more and providing benefits)?
My own
opinion is that having an enormous underground economy changes everything about
minimum wage conclusions. Interestingly the underground economy may pay much
more than minimum wage, especially when there are skills (think auto mechanics)
or risks (think farm and yard chemicals) or enormous discomforts (think of
working on a metal roof under Arizona's sun). But even when there relatively
high wages there are seldom underground economy benefits like medical insurance
and unemployment compensation and pension contributions.
Bob
Jensen's threads on the underground economy ---
http://www.cs.trinity.edu/~rjensen/temp/TaxNoTax.htm#Poor
**How to Mislead With Statistics (non-stationary data)
Macroeconomics ---
https://en.wikipedia.org/wiki/Macroeconomics
There's only one reliable rule of thumb in macroeconomics (so typical of
economics)---
https://www.themoneyillusion.com/theres-only-one-reliable-rule-of-thumb-in-macro/
In the 1950s, rates began
rising and frequent mild recessions were the new norm.
In the 1960s, one long
“Phillips Curve” expansion was the new norm. We had it all figured out.
In the 1970s, the Phillips
Curve fell apart, and we just had to live with stagflation.
In the 1980s, we didn’t
have to live with stagflation, but big deficits were the new norm.
In the 1990s, we achieved
budget surpluses and a Great Moderation (noninflationary boom), something no
one expected.
In the 2000s, the Great
Moderation collapsed into a deep recession that few expected (certainly not
me or Robert Lucas.) Also, America’s first big housing boom and bust. Also,
bank runs that were supposedly ended by FDIC.
In the 2010s, we had
near-zero interest rates even as the economy recovered and unemployment fell
to moderate levels. Also unexpected.
Every decade produces a new
and unexpected macro situation and the 2020s will be no different. Rules of
thumb don’t hold up over time.
So don’t tell me, “When you
look at history, it’s clear that X will happen.”
Sorry, but there’s only one
reliable rule of thumb in macro:
Things change.
PS. I am reluctant to
hazard a guess as to what will make the 2020s special; perhaps it will
violate the rule of thumb that says, “American expansions never last more
than 10 years.”
PPS. I have a post on the
Steve Moore nomination at
Econlog.
PPPS. But don’t read the
Steve Moore post, read
this one.
Jensen Comment
It is so typical that accountics researchers devoted to multiple regression
ignore non-stationarities where things change.
From Two Former Presidents of the AAA
"Some Methodological Deficiencies in Empirical Research Articles in
Accounting." by Thomas R. Dyckman and Stephen A. Zeff , Accounting
Horizons: September 2014, Vol. 28, No. 3, pp. 695-712 ---
http://aaajournals.org/doi/full/10.2308/acch-50818 (not free)
This paper uses a sample of the regression and
behavioral papers published in The Accounting Review and the Journal of
Accounting Research from September 2012 through May 2013. We argue first
that the current research results reported in empirical regression papers
fail adequately to justify the time period adopted for the study.
Second, we maintain that the statistical analyses used in these papers as
well as in the behavioral papers have produced flawed results. We further
maintain that their tests of statistical significance are not appropriate
and, more importantly, that these studies do not�and cannot�properly address
the economic significance of the work. In other words, significance tests
are not tests of the economic meaningfulness of the results. We suggest ways
to avoid some but not all of these problems. We also argue that replication
studies, which have been essentially abandoned by accounting researchers,
can contribute to our search for truth, but few will be forthcoming unless
the academic reward system is modified.
The free SSRN version of this paper is at
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2324266
This Dyckman and Zeff paper is indirectly related to the following technical
econometrics research:
"The Econometrics of Temporal Aggregation - IV - Cointegration," by
David Giles, Econometrics Blog, September 13, 2014 ---
http://davegiles.blogspot.com/2014/09/the-econometrics-of-temporal.html
**How to Mislead With Statistics
PBS Nova: How did the polls get it so wrong?
http://www.pbs.org/wgbh/nova/next/body/why-did-the-polls-get-it-wrong/
Forbes: The Science Of Error: How Polling Botched The
2016 Election ---
https://www.forbes.com/sites/startswithabang/2016/11/09/the-science-of-error-how-polling-botched-the-2016-election/#6deb3b337959
Scientific American: Where Are the Real Errors in
Political Polls?
https://blogs.scientificamerican.com/guest-blog/where-are-the-real-errors-in-political-polls/
Examples of misleading statistics and polls ---
https://www.datapine.com/blog/misleading-statistics-and-data/
NYT: Affirmative Action Is an Example of How Polls Can
Mislead
https://www.nytimes.com/2017/08/04/upshot/affirmative-action-and-why-polls-on-issues-are-often-misleading.html
Misleading Charts
---
https://qz.com/580859/the-most-misleading-charts-of-2015-fixed/
The Top 10 Ways to Get Misleading Poll Results (many times these are
intentional mistakes for political purposes) ---
http://www.charneyresearch.com/resources/the-top-10-ways-to-get-misleading-poll-results/
Fake Polls are the Real Problem ---
https://fivethirtyeight.com/features/fake-polls-are-a-real-problem/
**How to Mislead With Statistics
Bogus Straw Stats Popped Up in October 7, 2018 Shark Tank ---
http://reason.com/blog/2018/10/08/bogus-straw-stats-pop-up-in-last-nights
P-Value Nonsense
Statisticians clamor for retraction of paper by Harvard researchers they say
uses a “nonsense statistic” ---
https://retractionwatch.com/2019/06/19/statisticians-clamor-for-retraction-of-paper-by-harvard-researchers-they-say-uses-a-nonsense-statistic/#more-100498
Bob Jensen's threads on P-value nonsense
---
http://faculty.trinity.edu/rjensen/theory01.htm#WhatWentWrong
**How to Mislead With P-Values and Statistical Inference
From David Giles on March 26, 2019
The American Statistical
Association has just published a special
supplementary issue of
The American Statistician,
titled Statistical
Inference in the 21st. Century: A World Beyond p < 0.05.
This
entire issue is
open-access.
In addition to an excellent editorial, Moving
to a World Beyond "p < 0.05" (by Ronald Wasserstein, Allen Schirm,
and Nicole Lazar) it comprises 43 articles with such titles as:
·
The p-Value Requires
Context, Not a Threshold (by Rebecca Betensky)
·
The False Positive Risk:
A Proposal Concerning What to do About p-Values (by David
Colquhoun)
·
What Have we (Not)
Learnt From Millions of Scientific Papers With P Values? (by John
Ioannidis)
·
Three Recommendations for Improving the Use of
p-Values (by Daniel Benjamin and James Berger)
I'm sure
that you get the idea of what this supplementary issue is largely about.
But look
back at its title - Statistical
Inference in the 21st. Century: A World Beyond p < 0.05. It's not
simply full of criticisms. There's a heap of excellent, positive, and
constructive material in there.
Highly
recommended reading!
How Many Ways Can You Misinterpret p-Values, Confidence Intervals,
Statistical Tests, and Power? 25
https://replicationnetwork.com/2019/02/09/how-many-ways-can-you-misinterpret-p-values-confidence-intervals-statistical-tests-and-power-25/
Time to say goodbye to “statistically significant” and embrace
uncertainty, say statisticians ---
https://retractionwatch.com/2019/03/21/time-to-say-goodbye-to-statistically-significant-and-embrace-uncertainty-say-statisticians/
Three years ago, the American Statistical Association (ASA) expressed hope
that the world would move to a “post-p-value
era.”
The statement in which they made that recommendation has been cited more
than 1,700 times, and apparently, the organization has decided that era’s
time has come. (At least one journal had already
banned p values by 2016.)
In an
editorial
in a
special issue
of The American Statistician out today, “Statistical Inference in the 21st
Century: A World Beyond P<0.05,” the executive director of the ASA, Ron
Wasserstein, along with two co-authors, recommends that when it comes to the
term “statistically significant,” “don’t say it and don’t use it.” (More
than 800 researchers signed onto a
piece published in Nature yesterday
calling for the same thing.) We asked Wasserstein’s co-author,
Nicole Lazar of the University of Georgia,
to answer a few questions about the move.
So the ASA wants to say goodbye to “statistically significant.” Why, and why
now?
In the past few years there has been a growing recognition in the scientific
and statistical communities that the standard ways of performing inference
are not serving us well. This manifests itself in, for instance, the
perceived crisis in science (of reproducibility, of credibility); increased
publicity surrounding bad practices such as p-hacking (manipulating the data
until statistical significance can be achieved); and perverse incentives
especially in the academy that encourage “sexy” headline-grabbing results
that may not have much substance in the long run. None of this is
necessarily new, and indeed there are conversations in the statistics (and
other) literature going back decades calling to abandon the language of
statistical significance. The tone now is different, perhaps because of the
more pervasive sense that what we’ve always done isn’t working, and so the
time seemed opportune to renew the call.
Much of the editorial is an impassioned plea to embrace uncertainty. Can you
explain?
The world is inherently an uncertain place. Our models of how it works —
whether formal or informal, explicit or implicit — are often only crude
approximations of reality. Likewise, our data about the world are subject to
both random and systematic errors, even when collected with great care. So,
our estimates are often highly uncertain; indeed, the p-value itself is
uncertain. The bright-line thinking that is emblematic of declaring some
results “statistically significant” (p<0.05) and others “not statistically
significant” (p>0.05) obscures that uncertainty, and leads us to believe
that our findings are on more solid ground than they actually are. We think
that the time has come to fully acknowledge these facts and to adjust our
statistical thinking accordingly.
Continued in article
Bob Jensen's threads on the decline of p-values from favor in statistical
analysis ---
http://faculty.trinity.edu/rjensen/theory01.htm#WhatWentWrong
To p-Value or Not to p-Value? An Answer From Signal Detection Theory ---
https://open.lnu.se/index.php/metapsychology/article/view/871
“In
statistics, Type I errors (false alarms) and Type II errors (misses) are
sometimes considered separately, with Type I errors being a function of
the alpha level and Type II errors being a function of power. An
advantage of signal detection theory is that it combines Type I and Type
II errors into a single analysis of discriminability…”
“…p values
were effective, though not perfect, at discriminating between real and
null effects.”
“Bayes factor
incurs no advantage over p values at detecting a real effect versus a
null effect … This is because Bayes factors are redundant with p values
for a given sample size.”
“When power
is high, researchers using p values to determine statistical
significance should use a lower criterion.”
“… a change
to be more conservative will decrease false alarm rates at the expense
of increasing miss rates. False alarm rates should not be considered in
isolation without also considering miss rates. Rather, researchers
should consider the relative importance for each in deciding the
criterion to adopt.”
“…given that
true null results can be theoretically interesting and practically
important, a conservative criterion can produce critically misleading
interpretations by labeling real effects as if they were null effects.”
“Moving
forward, the recommendation is to acknowledge the relationship between
false alarms and misses, rather than implement standards based solely on
false alarm rates.”
Continued in article
February 6, 2019 Message from Tom Dyckman (now retired from Cornell
University)
Bob:
Here is a new paper you might want to alert your readers too along with
Dave's blog today.
Greenland, S., S. J. Senn, K. R. Rothman, J. B.
Carlin, C. Poole, S. N. Goodman, & D. G. Altman,
2016. Statistical tests, p values, confidence intervals, and power: A guide
to misinterpretations. European Journal of Epidemiology, 31,
337-350.
https://fermatslibrary.com/s/statistical-tests-p-values-confidence-intervals-and-power-a-guide-to-misinterpretations
Abstract
Misinterpretation and abuse of statistical tests, confidence intervals,
and statistical power have been decried for decades, yet remain rampant.
A key problem is that there are no interpretations of these concepts
that are at once simple, intuitive, correct, and foolproof. Instead,
correct use and interpretation of these statistics requires an attention
to detail which seems to tax the patience of working scientists. This
high cognitive demand has led to an epidemic of shortcut definitions and
interpretations that are simply wrong, sometimes disastrously so—and yet
these misinterpretations dominate much of the scientific literature. In
light of this problem, we provide definitions and a discussion of basic
statistics that are more general and critical than typically found in
traditional introductory expositions. Our goal is to provide a resource
for instructors, researchers, and consumers of statistics whose
knowledge of statistical theory and technique may be limited but who
wish to avoid and spot misinterpretations. We emphasize how violation of
often unstated analysis protocols (such as selecting analyses for
presentation based
on the
P values
they produce) can lead to small P values even if the declared test
hypothesis is correct, and can lead to large P values even if that
hypothesis is incorrect. We then provide an explanatory list of 25
misinterpretations of P values, confidence intervals, and power. We
conclude with guidelines for improving statistical interpretation and
reporting.
Continued in article
**How to Mislead With Statistics
How
to Mislead With P-Values
When You’re Selecting Significant Findings, You’re Selecting Inflated
Estimates ---
https://replicationnetwork.com/2019/02/16/goodman-when-youre-selecting-significant-findings-youre-selecting-inflated-estimates/
How Many Ways Can You Misinterpret p-Values, Confidence Intervals,
Statistical Tests, and Power? 25
https://replicationnetwork.com/2019/02/09/how-many-ways-can-you-misinterpret-p-values-confidence-intervals-statistical-tests-and-power-25/
Jensen Comment
The sad thing is that journal editors of leading accounting research journals
seem to not care --- they're addicted to P-values
Bob Jensen's
threads on the recent p-value saga ---
http://faculty.trinity.edu/rjensen/theory01.htm#WhatWentWrong
David Johnstone from Australia gave me permission to broadcast his reply to
the AECM
Dear Sudipta and Bob, thanks for
sending this Sudipta, it was actually written up in the local newspaper
(Sydney Morning Herald) the other day. There has also been a series of
articles on economic modelling that starts with the conclusion and works
back to the argument. People are waking up to rorts slowly but inevitably,
it seems.
There are multi-million dollar
industries (e.g. “accounting research”) that depend on p-levels and would
need a big clean out and recanting/retraining if the tide were to turn. I
think that the funding bodies (e.g. taxpayers) are starting to smell rats,
so life is going to be different for younger researchers in 10 years I
suspect. Much more scepticism about supposed “research”.
I have been toying with writing a book
on the P-level problem. I used to be excited about this stuff, I thought it
was deeply interesting and other people would also find it interesting. I
didn’t realize that most researchers are not intrinsically interested in the
techniques they use, and I also didn’t realize that most will resist
bitterly anything that makes their lives less glamorous and their self-image
less wonderful. This is what I see as the “positive theory of accounting
researchers”.
Great to have a couple of old
fashioned academics to talk to on this.
By the way, all the young
statisticians schooled in Bayesian theory know about the issues with
P-levels, and they are breeding up in computer science and elsewhere.
Tom Dyckman’s paper on P-levels is
coming out in Abacus 2nd issue 2016. In that same issue is an excellent
survey paper by Jeremy Bertomeu on cost of capital etc, which will give that
issue further credibility and hopefully prompt some extra readers to see
Tom’s paper.
David Johnstone
Jensen Comment
Note that the following article has enormous implications for what is taught in
most Ph.D. programs in the social sciences, business, accounting, finance, and
other academic disciplines. Regression analysis has become the key to the
kingdom of academic research, a Ph.D. diploma, journal article publication,
tenure, and performance rewards in the Academy. Now the sky is falling, and soon
researchers skilled mostly at performing regression analysis are faced with the
problem of having to learn how to do real research.
Regression Analysis ---
https://en.wikipedia.org/wiki/Regression_analysis
Richard Nisbett ---
https://en.wikipedia.org/wiki/Richard_E._Nisbett
"The Crusade Against Multiple Regression Analysis A Conversation With Richard
Nisbett," Edge, January 21, 2016 ---
http://edge.org/conversation/richard_nisbett-the-crusade-against-multiple-regression-analysis
A huge range of science projects are done
with multiple regression analysis. The results are often somewhere between
meaningless and quite damaging. ...
I hope that in the future, if I’m successful in
communicating with people about this, that there’ll be a kind of upfront
warning in New York Times articles: These data are based on multiple
regression analysis. This would be a sign that you probably shouldn’t read
the article because you’re quite likely to get non-information or
misinformation. RICHARD NISBETT is a professor of psychology and co-director
of the Culture and Cognition Program at the University of Michigan. He is
the author of Mindware: Tools for Smart Thinking; and The Geography of
Thought.
Richard Nisbett's Edge Bio Page.
THE CRUSADE AGAINST MULTIPLE REGRESSION ANALYSIS
The thing I’m most interested in right now has become a kind of crusade
against correlational statistical analysis—in particular, what’s called
multiple regression analysis. Say you want to find out whether taking
Vitamin E is associated with lower prostate cancer risk. You look at the
correlational evidence and indeed it turns out that men who take Vitamin E
have lower risk for prostate cancer. Then someone says, "Well, let’s see if
we do the actual experiment, what happens." And what happens when you do the
experiment is that Vitamin E contributes to the likelihood of prostate
cancer. How could there be differences? These happen a lot. The
correlational—the observational—evidence tells you one thing, the
experimental evidence tells you something completely different.
The thing I’m most interested in right now has
become a kind of crusade against correlational statistical analysis—in
particular, what’s called multiple regression analysis. Say you want to find
out whether taking Vitamin E is associated with lower prostate cancer risk.
You look at the correlational evidence and indeed it turns out that men who
take Vitamin E have lower risk for prostate cancer. Then someone says,
"Well, let’s see if we do the actual experiment, what happens." And what
happens when you do the experiment is that Vitamin E contributes to the
likelihood of prostate cancer. How could there be differences? These happen
a lot. The correlational—the observational—evidence tells you one thing, the
experimental evidence tells you something completely different.
In the case of health data, the big problem is
something that’s come to be called the healthy user bias, because the guy
who’s taking Vitamin E is also doing everything else right. A doctor or an
article has told him to take Vitamin E, so he does that, but he’s also the
guy who’s watching his weight and his cholesterol, gets plenty of exercise,
drinks alcohol in moderation, doesn’t smoke, has a high level of education,
and a high income. All of these things are likely to make you live longer,
to make you less subject to morbidity and mortality risks of all kinds. You
pull one thing out of that correlate and it’s going to look like Vitamin E
is terrific because it’s dragging all these other good things along with it.
This is not, by any means, limited to health
issues. A while back, I read a government report in The New York Times on
the safety of automobiles. The measure that they used was the deaths per
million drivers of each of these autos. It turns out that, for example,
there are enormously more deaths per million drivers who drive Ford F150
pickups than for people who drive Volvo station wagons. Most people’s
reaction, and certainly my initial reaction to it was, "Well, it sort of
figures—everybody knows that Volvos are safe."
Continued in article
Drawing Inferences From Very Large Data-Sets
David Johnstone wrote the following:
Indeed if you hold H0 the same and keep
changing the model, you will eventually (generally soon) get a significant
result, allowing "rejection of H0 at 5%", not because H0 is
necessarily false but because you have built upon a false model (of which
there are zillions, obviously).
"Drawing Inferences From Very Large Data-Sets," by David Giles, Econometrics
Beat: Dave Giles� Blog, University of Victoria, April 26, 2013 ---
http://davegiles.blogspot.ca/2011/04/drawing-inferences-from-very-large-data.html
. . .
Granger (1998;
2003
) has
reminded us that if the sample size is sufficiently large, then it's
virtually impossible not to reject almost any hypothesis.
So, if the sample is very large and the p-values associated with
the estimated coefficients in a regression model are of the order of, say,
0.10 or even 0.05, then this really bad news. Much,
much, smaller p-values are needed before we get all excited about
'statistically significant' results when the sample size is in the
thousands, or even bigger. So, the p-values reported above are
mostly pretty marginal, as far as significance is concerned. When you work
out the p-values for the other 6 models I mentioned, they range
from to 0.005 to 0.460. I've been generous in the models I selected.
Here's another set of results taken from a second, really nice, paper by
Ciecieriski et al. (2011) in the same issue of
Health Economics:
Continued in article
Jensen Comment
My research suggest that over 90% of the recent papers published in The
Accounting Review use purchased databases that provide enormous sample sizes
in those papers. Their accountics science authors keep reporting those
meaningless levels of statistical significance.
What is even worse is when meaningless statistical significance tests are
used to support decisions.
"Statistical Significance - Again " by David Giles, Econometrics
Beat: Dave Giles� Blog, University of Victoria, December 28, 2013 ---
http://davegiles.blogspot.com/2013/12/statistical-significance-again.html
Statistical Significance -
Again
With all of this
emphasis on "Big Data", I was pleased to see
this post on the Big Data
Econometrics blog, today.
When you have a sample that
runs to the thousands (billions?), the conventional significance
levels of 10%, 5%, 1% are completely inappropriate. You need to
be thinking in terms of tiny significance levels.
I discussed this in
some detail back in April of 2011, in a post titled, "Drawing
Inferences From Very Large Data-Sets".
If you're of those (many) applied
researchers who uses large cross-sections of data, and then
sprinkles the results tables with asterisks to signal
"significance" at the 5%, 10% levels, etc., then I urge
you read that earlier post.
It's sad to encounter so many
papers and seminar presentations in which the results, in
reality, are totally insignificant!
How Standard Error Costs Us Jobs,
Justice, and Lives, by Stephen T. Ziliak and Deirdre N. McCloskey (Ann
Arbor: University of Michigan Press, ISBN-13: 978-472-05007-9, 2007)
http://www.cs.trinity.edu/~rjensen/temp/DeirdreMcCloskey/StatisticalSignificance01.htm
Page 206
Like scientists today in medical and economic and
other sizeless sciences, Pearson mistook a large sample size for the definite,
substantive significance---evidence s Hayek put it, of "wholes." But it was as
Hayek said "just an illusion." Pearson's columns of sparkling asterisks, though
quantitative in appearance and as appealing a is the simple truth of the sky,
signified nothing.
pp. 250-251
The textbooks are wrong. The teaching is wrong. The
seminar you just attended is wrong. The most prestigious journal in your
scientific field is wrong.
You are searching, we know, for ways to avoid
being wrong. Science, as Jeffreys said, is mainly a series of approximations to
discovering the sources of error. Science is a systematic way of reducing wrongs
or can be. Perhaps you feel frustrated by the random epistemology of the
mainstream and don't know what to do. Perhaps you've been sedated by
significance and lulled into silence. Perhaps you sense that the power of a
Roghamsted test against a plausible Dublin alternative is statistically speaking
low but you feel oppressed by the instrumental variable one should dare not to
wield. Perhaps you feel frazzled by what Morris Altman (2004) called the "social
psychology rhetoric of fear," the deeply embedded path dependency that keeps the
abuse of significance in circulation. You want to come out of it. But perhaps
you are cowed by the prestige of Fisherian dogma. Or, worse thought, perhaps
you are cynically willing to be corrupted if it will keep a nice job
Bob Jensen's threads on the often way analysts, particularly accountics
scientists, often cheer for statistical significance of large sample outcomes
that praise statistical significance of insignificant results such as R2
values of .0001 ---
The Cult of Statistical Significance: How Standard Error Costs Us Jobs, Justice,
and Lives ---
http://www.cs.trinity.edu/~rjensen/temp/DeirdreMcCloskey/StatisticalSignificance01.htm
Those of you interested in tracking The Accounting Review's trends in
submissions, refereeing, and acceptances'rejections should be interested in
current senior editor Mark L.
DeFond's annual report at
http://aaajournals.org/doi/full/10.2308/accr-10477
This has become a huge process involving 18 editors and hundreds of referees.
TAR is still the leading accountics science journal of the American Accounting
Association. However, there are so many new specialty journals readers are apt
to find quality research in other AAA journals. TAR seemingly still does not
publish commentaries and articles without equations and has not yet caught on
the intitiatives of the Pathways Commission for more diversification in
research in the leading AAA research journal. Virtually all TAR editors still
worship p-values in empirical submissions.
"Not Even Scientists Can Easily Explain P-values," by Christie
Aschwanden, Nate Silver's 5:38 Blog, November 30, 2015 ---
http://fivethirtyeight.com/features/not-even-scientists-can-easily-explain-p-values/
P-values have taken quite a beating lately. These
widely used and commonly misapplied statistics have been blamed for giving a
veneer of legitimacy to dodgy study results,
encouraging
bad research practices
and promoting
false-positive study results.
But after writing about p-values again and again,
and recently issuing a correction on a
nearly year-old story over some erroneous
information regarding a study’s p-value (which I’d taken from the scientists
themselves and
their report), I’ve
come to think that the most fundamental problem with p-values is that no one
can really say what they are.
Last week, I attended the inaugural
METRICS conference at Stanford, which brought
together some of the world’s leading experts on meta-science, or the study
of studies. I figured that if anyone could explain p-values in plain
English, these folks could. I was wrong.
Continued in article
Jensen Comment
Why all the fuss? Accountics scientists have a perfectly logical explanation.
P-values are numbers that are pumped out of statistical analysis software
(mostly multiple regression software) that accounting research journal editors
think indicate the degree of causality or at least suggest the degree of
causality to readers. But the joke is on the editors, because there aren't any
readers.
November 30, 2015 reply from David Johnstone
Dear
Bob, thankyou for this interesting stuff.
A big
part of the acceptance of P-values is that they easily give the look of
something having been found. So it’s an agency problem, where the
researchers do what makes their research outcomes easier and better looking.
There
is a lot more to it of course. I note with young staff that they face enough
hurdles in the need to get papers written and published without thinking
that the very techniques that they are trying to emulate might be flawed.
Rightfully, they say, “it’s not my job to question everything that I have
been shown and to get nowhere as a result”, nor can most believe that
something so established and revered can be wrong, that is just too
unthinkable and depressing. So the bandwagon goes on, and, as Bob says, no
one cares outside as no one much reads it.
I do
however get annoyed every time I hear decision makers carry on about
“evidence based” policy, as if no one can have a clue or form a vision or
strategy without first having the backing of some junk science by a
sociologist or educationist or accounting researcher who was just twisting
the world whichever way to get significant p-values and a good “story”. This
kind of cargo-culting, which is everywhere, does great harm to good or
sincere science, as it makes it hard for an outsider to tell the difference.
One
thing that does not get much of a hearing is that the statisticians
themselves must take a lot of blame. They had the chance to vote off P
values decades ago when they had to choose between frequentist and Bayesian
logic. They split into two camps with the frequentists in the great majority
but holding the weakest ground intellectually. The numbers are moving now,
as people that were not born when de Finetti, Savage, Lindley, Kadane and
others first said that p-values were ill-conceived logically. Accounting, of
course, being largely ignorant of there being any issue, and ultimately just
political, will not be leading the battle of ideas.
January 28, 2016 reply from Paul Williams
Bob,
Thank you for this. In accounting the problem is
even worse because at least in other fields it is plausible that one can
have "scientific" concepts and categories. Archival research in accounting
can only deal with interpretive concepts and the "scientific" categories are
often constructed for the one study in question. We make a lot of s... up so
that the results are consistent with the narrative (always a neoclassical
economic one) that informs the study. Measurement? Doesn't exist. How can
one seriously believe they are engaged in scientific research when their
"measurements" are the result of GAAP? Abe Briloff described our most
prestigious research (which Greg Waymire claimed in his AAA presidential
white paper "...threatens the discipline with extinction."). as simply "low
level financial statement analysis." Any research activity that is reduced
to a template (in JAE the table numbers are nearly the same from paper to
paper) you know you are in trouble. What is the scientific value of 50
control variables, two focus independent variables (correlated with the
controls), and one dependent variable that is always different from study to
study? This one variable at a time approach can go on into infinity with the
only result being a huge pile of anecdotes that no one can organize into any
coherent explanation of what is going on. As you have so eloquently and
relentlessly pointed out accountants never replicate anything. In archival
research it is not even possible to replicate since the researcher is unable
to provide (like any good scientist in physics, chemistry, biology, etc.) a
log book providing the detailed recipe it would take to actually replicate
what the researcher has done. Without the ability to independently replicate
the exact study, the status of that study is merely an anecdote. Given the
Hunton affair, perhaps we should not be so sanguine about trusting our
colleagues. This is particularly so since the leading U.S. journals have a
clear ideological bias -- if your results aren't consistent with the
received wisdom they won't be published.
Paul
Bob Jensen's threads on statistical mistakes ---
http://www.cs.trinity.edu/rjensen/temp/AccounticsScienceStatisticalMistakes.htm
How Accountics Scientists Should Change:
"Frankly, Scarlett, after I get a hit for my resume in The Accounting Review
I just don't give a damn"
http://www.cs.trinity.edu/~rjensen/temp/AccounticsDamn.htm
One more mission in what's left of my life will be to try to change this
http://www.cs.trinity.edu/~rjensen/temp/AccounticsDamn.htm
"A Scrapbook on What’s Wrong with the Past, Present a nd Future of
Accountics Science," by Bob Jensen, Working Paper 450.06, Date Fluid ---
http://www.cs.trinity.edu/~rjensen/temp/AccounticsWorkingPaper450.06.pdf
The purpose of this paper is to make a case that
the accountics science monopoly of our doctoral programs and publish ed
research is seriously flawed, especially its lack of concern about
replication and focus on simplified arti ficial worlds that differ too much
from reality to creatively discover findings of greater relevance to
teachers of accounting and practitioners of accounting. Accountics
scientists themselves became a Cargo Cult.
Gaming for Tenure as an Accounting Professor ---
http://faculty.trinity.edu/rjensen/TheoryTenure.htm
(with a reply about tenure publication point systems from Linda Kidwell)
**How to Mislead With Statistics and Visualization
The Economist is one of the moat respected magazines in economics:
Here it owns up to some of its mistakes in data
visualization ---
https://medium.economist.com/mistakes-weve-drawn-a-few-8cdd8a42d368
Jensen Comment
Owning up to mistakes is what sometimes make scholars legendary and journals
ever more respected
Mistake: Truncating the scale
Mistake: Choosing the wrong visualisation method
Mistake: Taking the “mind-stretch” a little too far
Mistake: Confusing use of colour
Mistake: Including too much detail
Mistake: Lots of data, not enough space
Bob Jensen's threads on Data Visualization ---
http://faculty.trinity.edu/rjensen/352wpvisual/000datavisualization.htm
**How to Mislead With Statistics
Timing is Everything: Evidence from College Major Decisions ---
http://www.econweb.umd.edu/~pope/westpointtiming.pdf
Jensen Comment
Based on my own anecdotal experience across 40 years of being on the faculty of
four universities I'm suspicious about the conclusions of this study on
causality.
Personally, I think that student choices of major in many, certainly not all,
instances is primarily impacted by parents and/or other relatives for very close
family friends. This is not necessarily the case at the start of the first
semester in college where students still tend to leave their options only. But I
think deep in the backs of their minds the wishes of parents and family friends
come to surface.
I admit to being wrong in many instances and this article often rings true.
Our minister has ten very loving and tightly-knit children. What emerged is a
loved leader among the children named Lauren. She graduated from high school
(all were home schooled) and entered nursing school. She's now a popular cardiac
nurse in the Eastern Main Medical Center in Bangor. Lauren influenced her
younger brother Landon's decision to attend the same nursing school. I'm sure he
was partly influenced by all the job opportunities that opened up to his older
sister. But along the way in college Landon was greatly influenced by a required
course in psychology. Landon changed majors and is now a psychology major bent
on becoming a clinical psychologist. Job opportunities are much more limited
(competitively) as a new graduate in psychology. Go figure!
The accounting profession was greatly worried as virtually all the 50 states
commenced requiring 150 credits to sit for the CPA examination, which for most
aspiring CPAs is tantamount to requiring a masters degree. What would this alone
do to the number of undergraduate accounting majors? We'll never know. The
reason is that at the same time CPA firms and business firms offset this new
academic requirement with greatly expanded undergraduate internship programs. It
turns out in accounting and other academic majors it really helps to have
internships available to most students in a discipline and, get this,
internships that lead to job offers before students even enter their masters
programs (with the job offers being contingent upon getting the masters
degrees).
My point student decisions regarding majors are
probably too variable, complicated, and serendipitous to neatly summarize.
Certainly ranking key factors is extremely misleading.
There are too many interacting variables.
Roundup ---
https://en.wikipedia.org/wiki/Roundup_(herbicide)
Questions
Who pays for multimillion settlements regarding the cancer scare of Roundup
weed killer?
https://www.consumersafetywatch.com/non-hodgkin-lymphoma-roundup/?adwords&gclid=EAIaIQobChMInpnk3vap4QIVgV6GCh3_XgRsEAAYAiAAEgKnF_D_BwE
Jensen Comment
It's a bit like cigarette manufacturer settlements when customers in the future
pay for past settlements. And since farmers and homeowners around the world will
continue to use this product or its equivalent Roundup's legal settlements will
be paid by future customers.
However, there's a huge difference relative to cigarette consumers. Farmers around the world say they will
still spray Roundup or its equivalent on growing crops ---
https://www.wsj.com/articles/despite-rulings-farmers-remain-loyal-to-roundup-11553175429
This means that virtually all consumers (from meat eaters to bread lovers to
vegetarians) will pay for the legal settlements regarding Roundup.
Big companies do not pay for legal settlements as long as they continue in
business. Their customers pay for those settlements. Exhibit A is how asbestos
settlement dollars are factored into the prices paid by customers for insulation
today.
How long will the Roundup lawsuits keep piling up?
The lawsuits will be slowed down when appeals courts greatly scale back the
damage awards. And lawsuits "might" eventually cease as publicity and product labels
make users of Roundup more responsible for knowingly taking on risks. The link
between Roundup and food consumers, to my knowledge, has never been
scientifically proven. Much awaits more scientific
study on this matter of food risks from Roundup use.
Suppose a link between Roundup and bread or hamburger eventually is proven.
This alone does will not necessarily put an end to Roundup or its equivalent.
I've pointed out previously that use of Roundup will then become a bit like the
Trolley Problem in philosophy ---
https://en.wikipedia.org/wiki/Trolley_problem
The fact of the matter is that until safer herbicides become as effective as
Roundup people around the world will surely pay much more for food and many
people will starve due to lower crop yields providing food without Roundup use.
**How to Mislead With Statistics
These are the 29 countries with the highest taxes on profits for corporations
(supposedly from PwC) ---
https://www.businessinsider.com/these-are-the-29-countries-with-the-highest-taxes-for-corporations-2019-3
Firstly, the outcomes reported in this study do not jive
with other studies looking only at profits taxes. Take Sweden for example. The
above article says the corporate rate for Sweden is 49.1%. Other studies put
that rate at 22% and headed for 21.4% ---
https://www.businessinsider.com/these-are-the-29-countries-with-the-highest-taxes-for-corporations-2019-3#13-sweden-491-17
Even PwC puts the tax rate at 21.4% ---
http://taxsummaries.pwc.com/ID/Sweden-Corporate-Taxes-on-corporate-income
The reason for the difference between 49.1% and 21.4% is
that the Business Insider (World Bank) ranking adds "social contribution" to the
corporate income tax rates. But it is not clear just what constitutes social
contribution and how consistent the "social contribution" add on for each
nation. I think that the definition of "social contribution" is dubious.
Obviously the VAT tax plays a huge role in all of this. But nations vary greatly
in terms of VAT tax relief to companies.
Comparing tax rates between nations is a lot like
comparing poverty between nations. The definitions of "tax" and "poverty" are
different for each nation. I suspect the definition of "social contribution"
also suffers from the same ambiguities.
Also there's a huge problem for multinational companies
since they pay multiple income tax rates, VAT rates, and multiple social
contributions over the nations in which they do business.
You can learn more about the PwC study by going to the PwC
site at
https://www.pwc.com/gx/en/services/tax/publications/paying-taxes-2019/overall-ranking-and-data-tables.html
Also see
https://www.pwc.com/gx/en/services/tax/publications/paying-taxes-2019.html
You can download the report at the above site.
Obviously the VAT tax plays a huge role in all of this.
But nations vary greatly in terms of VAT tax relief and income tax relief to
companies.
In fairness, the full PwC report delves much more into the
difficulties of making tax comparisons between nations. This is not a garbage
study. But some of the summaries like the Business Insider rankings are garbage
aggregations that gloss over difficulties in making rankings and comparisons.
For example, consider Argentina that according the
Business Insider ranking claims Argentina corporations pay profit and social
contribution rates totaling 106%. Obviously, it would
be foolhardy to invest in corporate equity in Argentina unless there was some
way to get a return on investment.
The same problem arises when trying to compare personal
tax rates between nations such as comparing what people pay in taxes in Sweden
versus the USA. One of the big added problems here is failing to compare the
differences in what taxpayers get in return for their taxes. For example, do
those taxes cover basic health care, long-term health care, housing subsidies,
energy subsidies, education for some, education for all, etc.
My point is that sometimes comparing nations by statistics
and charts is worse than having no information --- it's terribly misleading
information.
Students at Rice University are petitioning to prevent Vice President Mike
Pence from speaking at a campus event, citing his "violent intolerance of LGBTQ+
identities."
https://docs.google.com/forms/d/e/1FAIpQLSdGK2ZypQmJsVhvrN9D4JzdBNUN-xJoHmfRqy34cNBMA-ZlYA/viewform?fbzx=-7748057991678917981&fbclid=IwAR3_HuIcbJ8blHXLvE22M-ZAezpJX1caf_75crDbQ6tWAAxEO6SU9S0UkXY&cid=db
Jensen Comment
Mike Pence is a heart beat away from becoming the President of the USA. Rice
students would rather remain ignorant about his domestic and foreign policies
than to let one issue draw a curtain around their learning more about this
leader.
Don't they realize that they could more rigorously campaign against the
re-election of Mike Pence if they learned a few things more about him and his
policies.
Would Rice University students have done the
same thing years ago if Albert Einstein was intolerant of LGBTQ identities?
Political Correctness in Universities Never Quits
I think political
correctness can lead to some kind of paralysis where you don't address reality.
Juan William before he was fired after a distinguished career on NPR.
http://townhall.com/columnists/GuyBenson/2010/10/21/npr_finally_finds_an_excuse_to_fire_juan_williams
The Washington Post:
Conservatives say campus speech is under threat.
That’s been true for most of history ---
https://www.washingtonpost.com/outlook/conservatives-say-campus-speech-is-under-threat-thats-been-true-for-most-of-history/2017/08/11/6aa959fa-7c4b-11e7-9d08-b79f191668ed_story.html?utm_term=.a02b7a26615d
Beloit College: The incident (a pro-capitalism speaker) was
the latest in a string of free expression occurrences on college campuses where
students have intentionally drowned out speakers whose views they find
distasteful ---
Click Here
Capitalism is such a dangerous topic that mention of it should be banned in all
colleges and universities
Black Pro-Life Speaker Disinvited From Cornell ---
https://townhall.com/tipsheet/briannaheldt/2019/03/27/black-prolife-speaker-disinvited-from-cornell-n2543853?utm_source=thdaily&utm_medium=email&utm_campaign=nl&newsletterad=03/28/2019&bcid=b16c6f948f297f77432f990d4411617f&recip=17935167
Jensen Comment
I've repeatedly proclaimed that I'm an economics conservative who favors
progressiveness in abortion rights (including late-term abortions) and gay
rights. And I'm utterly against political correctness in the media and on
campus.
My threads on political correctness ---
http://faculty.trinity.edu/rjensen/HigherEdControversies2.htm#PoliticalCorrectness
When Grading Less Is More
https://www.insidehighered.com/news/2019/04/02/professors-reflections-their-experiences-ungrading-spark-renewed-interest-student?utm_source=Inside+Higher+Ed&utm_campaign=aed948ff1a-DNU_2019_COPY_01&utm_medium=email&utm_term=0_1fcbc04421-aed948ff1a-197565045&mc_cid=aed948ff1a&mc_eid=1e78f7c952
When it comes to grading, less is more. So say a number of scholars who have
shared their recent experiments with “ungrading” in blog posts and on other
social media, sparking renewed discussions about the practice.
“My core hypothesis was
that student learning would actually be improved by eliminating instructor
grading from the course,” Marcus Schultz-Bergin, assistant lecturer
of philosophy at Cleveland State University, wrote
of going gradeless this
semester in a personal blog post that has since been shared on the popular
philosophy site Daily Nous.
“My
hope” for students, Schultz-Bergin continued, “is that the reflection they
engaged in, and the discussions we had, will lead to a significant
commitment in the second half of the course to really achieve what they set
out for themselves so that when they tell me they earned an A they can
really mean it.”
Thus far, he added, the experiment in his undergraduate philosophy of law
course "has had its ups and downs. There are definitely some things I will
change going forward, but I do think the gradeless approach can work well in
a course like this.”
Experts in ungrading say it’s still relatively rare in higher education, due
in part to inertia with respect to pedagogical innovation, the culture of
assessment and professors’ anxieties about going gradeless. How will
students respond? What will colleagues say? What will administrators think?
Continued in article
Jensen Comment
I would've loved my 40 years of teaching more if I never had to assign grades
(other than maybe Pass/Fail).
But I would've felt that in assigning only a P or an F I was less
professional. Grading is important at most any level of education. Personally, I
worked harder to learn from the fifth grade onward in courses where teachers
were harder graders. Part of it was probably my competitive nature. But mostly I
wanted to bring home report cards to make my parents proud of me when they
signed each report card.
I don't think I would've liked having to write a letter of performance for
each student who never took an exam. Sure I could write about innovative ideas
students had in essays, but it's very hard to compare innovative ideas for each
and every student since innovative ideas are often impractical with unachievable
goals.
My own experience in as a teacher in college is that competitive grades were
the main motivating factor for my better students and often even my struggling
students who dug in harder to improve their grades as each semester progressed.
How many students really take a pass/fail course so they won't have to work
as hard in that course?
Grades are a way that students can demonstrate ability when they tend to do
poorly on standardized tests. You may not be doing
minority students any favors when you take away course grades that show deeper
work ethics and abilities.
Some colleges force high schools to choose the top 10% of each graduating
class such as the 10% rule for admissions for automatic admission in to
state-supported Texas universities ---
https://en.wikipedia.org/wiki/Texas_House_Bill_588
How do you select the top 10% of a high school's graduating class if there are
no course grades?
Many graduate schools (including medical schools and law schools) claim they
are looking more heavily into grades to counter poor standardized test scores
like the GRE, GMAT, MCAT, LSAT, etc. Without grades it would seem to me that
they become more reliant on standardized tests. Letters of recommendation from
former professors are either hard to get in this age of lurking lawyers and in
this age where class sizes are so huge that professors really don't get to know
all their students very well. Letters of recommendations rarely say anything
negative such that if their are 3,000 applicants to fill 400 slots in a medical
school, those letters of recommendation from Lake Wobegon are of little help in
the screening process ---
https://en.wikipedia.org/wiki/Lake_Wobegon
I'm not saying that students should not be allowed to take an occasional
Pass/Fail course, especially if it's outside their major field of study. What I
am saying is that pass/fail should not go mainstream.
Bob Jensen's treads on assessment are at
http://faculty.trinity.edu/rjensen/assess.htm
**How to Mislead With Statistics and Biased Media Reporting
(the externality of motivating the police to do less and less and less)
Here are the stories about police misconduct uncovered so far by a new
media partnership ---
https://www.latimes.com/local/lanow/la-me-police-files-roundup-20190319-story.html
Jensen Comment
It would also be nice if the media partnership also reported good conduct deeds
by law enforcement. The real problem about reporting misconduct is that "no
action" can easily go undetected. For example, in Baltimore police are now
suspected pf simply looking the other way in the presence of rising street
crimes and traffic crimes. Or the police might create long delays until a
relatively formidable armed squad can be assembled before entering dangerous
public housing complexes and domestic dispute residences.
And police departments can be simply overwhelmed (think Chicago and
Baltimore) by the number of murders and rapes such that "investigations" become
badly understaffed and underfunded.
Meanwhile minorities are the most impacted by reduced
police protections just like urban school children and their teachers are
subjected to more bullying and gang violence.
Teachers in NYC now complain that in some districts inmates have overtaken the
asylum ---
https://www.manhattan-institute.org/html/school-discipline-reform-and-disorder-evidence-nyc-schools-10103.html
**How to Mislead With "Unvetted" Forecasts/Predictions
Elon Musk ---
https://en.wikipedia.org/wiki/Elon_Musk
The Securities and Exchange Commission says an "unvetted"
tweet Elon Musk sent in February claiming that Tesla would produce 500,000
vehicles in 2019 was a "blatant violation" of a court settlement between
himself, Tesla, and the agency ---
https://www.businessinsider.com/sec-responds-to-elon-musk-in-contempt-of-court-claim-2019-3
·
The Securities and Exchange Commissionsays a tweet Elon
Musk sent in February claiming that Tesla would produce 500,000 vehicles
in 2019 was a "blatant violation" of a court settlement between himself,
Tesla, and the agency.
·
Among other things, that settlement requires Tesla to
appoint a "Twitter czar" who vets Musk's tweets for information material
to Tesla before publishing.
·
The SEC, citing Musk's own words, accuses him of not
doing that and says "there was never any good faith effort to comply
with the Court's order."
·
Musk's lawyers criticized the SEC's latest filing on
Monday, accusing the agency of making new allegations against the Tesla
CEO.
Continued in article
Jensen Comment
Musk keeps trying to manipulate Tesla's stock and bond market prices with
dubious forecasts (although in its best week Tesla did produce 7,000 vehicles
before laying off workers to reduce expenses).
It's not so much that 500,000 per year is entirely unreachable. The issue is
that Musk agreed in court to have such predictions "vetted" before making them
public.
This is no longer limited to a dispute between the SEC and Elon Musk. It's now a
contempt of court violation --- which is a much more scary violation for Musk to
face up to in court.
Ironically, no enforcement agency requires that President Trump's tweets be
vetted, although the national media seems to have taken on that job.
Trump and Musk seem to be in competition to see how
long tweeted lies will be tolerated --- by voters (in the case of
Trump) and by investors (in the case of Musk).
The SEC's mandate is to protect investors from fraud and market manipulations.
From the CFO Journal's Morning Ledger on
February 27, 2019
The latest
legal action between U.S. securities regulators and
Tesla
Inc. Chief Executive Elon Musk highlights the challenge facing regulators
and boards when it comes to reining in a wealthy chief executive whose
identity is closely tied to the value of the company he or she leads, CFO
Journal’s Tatyana Shumsky and Nina Trentmann report.
Round two.
The Securities and Exchange Commission on Monday asked a federal judge
to hold Mr. Musk in contempt of court
over
social-media messages he made last week about Tesla’s projected production
volumes. The regulator said the tweets violated the terms of a fraud
settlement he reached with the SEC in September because they weren’t
preapproved by Tesla officials. U.S. District Judge Alison Nathan on Tuesday
ordered Mr. Musk to respond
to the claims by March 11.
Crime and punishment.
Mr.
Musk’s personal wealth, estimated in the billions, could
cushion the impact of potential financial penalties. And
any action that curtails his
leadership responsibilities
risks hurting the value of Tesla because Mr. Musk’s identity
is closely intertwined with the company’s value, says Bonnie
Hancock, executive director of the Enterprise Risk
Management Initiative at the North Carolina State University
Poole College of Management.
Effective measures.
Mr. Musk’s settlement deal with the SEC in part required
that Tesla officials preapprove statements from him that
could affect the company’s stock price. Steven Peikin,
co-director of the SEC’s division of enforcement, said in
October that the regulator deployed one of its most
effective tools—a tailor-made directive—to prevent potential
harm to investors caused by a lack of oversight of Mr.
Musk’s communications. |
|
“The SEC has bent over backwards to allow
Tesla to continue to get the benefits of
Musk’s creative genius, but they have also
attempted to put in place procedures and
methodologies to prevent shareholders from
being misled by his tweets.” |
— Harvey Pitt, former chairman of the SEC. |
|
|
|
Consumer Reports
no longer recommends buying a Model 3 --- because it's too unreliable.
How far does the First Amendment protect the right of CEOs to manipulate market
prices (bonds and stocks) ---
ELON MUSK (think Tesla) FILES HIS DEFENSE: Says SEC seeks to violate his
First Amendment rights, and its filing 'smacks of retaliation and censorship'
---
https://www.businessinsider.com/musk-response-to-contempt-of-court-2019-3
Jensen Comment
There's a real threat to capital markets if he wins on this one. At risk is the
scaring off of investors in the markets, investors who fear market manipulation
beyond which the SEC can fight these days.
But there's a second risk --- should he be allowed to defy a court order?
I think there's huge risk in using the First Amendment to defend against
contempt of court.
**How to Mislead With Statistics
Gini Coefficient of Poverty
Jensen Comment
The Gini Coefficient is one of the most misleading statistics in economics. It
supposedly measures the gap between the rich and poor in any nation. However,
the terms "rich" and "poor" are highly relative. For example, the USA has a high
Gini Coefficient indicating a gap between the rich and poor. However, South
Sudan has very nearly the same Gini Coefficent where the poor of the USA would
be considered well off in South Sudan. Think of how rich a person would be in
the South Sudan with housing subsidies, food stamps, Medicaid, vehicles, HDTV,
and welfare.
Chile is a high Gini Coefficient nation with about the same score as Zambia,
but the poor in Chile are not nearly as desperate as the poor in Zambia. The
level of income for the poor in Chile is the highest in all of Latin and South
America ---
http://en.wikipedia.org/wiki/Miracle_of_Chile
At one point Canada and North Korea had about the same Gini Coefficient,
although the index is no longer computed for North Korea ---
http://en.wikipedia.org/wiki/List_of_countries_by_income_equality#List
"Countries With the Widest Gap Between Rich and Poor," by Alexander
E.M. Hess, Vince Calio and Thomas C. Frohlich, Business Insider, May 20,
2014 ---
http://247wallst.com/special-report/2014/05/20/countries-with-the-widest-gap-between-rich-and-poor/?utm_source=247WallStDailyNewsletter&utm_medium=email&utm_content=MAY212014A&utm_campaign=DailyNewsletter
Jensen Comment
Denmark has the lowest (best) Gini Coefficient but its public education and
health care systems are lacking and rank below those of Morocco ---
http://www.cs.trinity.edu/~rjensen/temp/SunsetHillHouse/SunsetHillHouse.htm
Other measures of inequality and poverty ---
http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTPOVERTY/EXTPA/0,,contentMDK:20238991~menuPK:492138~pagePK:148956~piPK:216618~theSitePK:430367,00.html
Measuring Poverty Around the World ---
https://www.amazon.com/Measuring-Poverty-around-Anthony-Atkinson/dp/0691191220/ref=sr_1_1?crid=3U3VG9LDKEH9M&keywords=measuring+poverty+around+the+world&qid=1559895304&s=gateway&sprefix=measuring+poverty+arou%2Caps%2C118&sr=8-1/marginalrevol-20
**How to Mislead With Statistics
Research: Better-Managed Companies Pay Employees More Equally ---
https://hbr.org/2019/03/research-better-managed-companies-pay-employees-more-equally?utm_medium=email&utm_source=newsletter_monthly&utm_campaign=finance_not_activesubs&referral=00209&deliveryName=DM31879
Jensen Comment
This article is a mixed bag. It does a poor job of defining "better managed." On
the other hand, it does a good job in admitting and explaining that does
not understand reasons for the findings.
What is also misleading is that it does not explain that organizations vary a
great deal regarding pay needed for expertise. There's a huge difference between
Apple Corporation that depends upon expensive engineers in a huge R&D operation
versus Blue Cross needing a much greater proportion of lower-paid employees
processing insurance claims. It also does not account for different types of pay
structures such when pay varies a great deal within a category of employment due
to sales commissions and related pay schemes where doctors and lawyers in a firm
are paid according to the fees they generate.
As to the results of the article itself I like Reason Number 3 for explaining
the differences. Some firms that limit wages and benefits by outsourcing both
high-end and low-end employees. I worked at a university that outsourced its
cleaning services. In the case of teaching courses it also outsourced some of
the most expensive teachers such as accounting teachers and computer science
teachers. Such outsourcing leads to compression of outlier labor expenses thus
making it look (misleadingly) like there;s a smaller difference between
high-paid and low paid-workers.
I might add that outsourcing itself can be misleading.
Hiring an adjunct to teach tax accounting or PERL programming in a college is
not the same as having tenured faculty teach those courses. Tenured faculty
serve other missions of the university such as research and service that adjunct
faculty do not usually serve. Hence cheaper experts are not always better
experts in terms of all missions of the organization.
My point here is that outsourcing the highest and
lowest paid workers in an organization is not optimal for the good of society if
the only thing it does is make it look like you are reducing the gap between
highest and lowest paid employees.
**How to Mislead With Governmental Accounting
"How Much Do We Really Owe?," by John Goodman, Forbes, August 7,
2014 ---
http://www.forbes.com/sites/johngoodman/2014/08/07/how-much-do-we-really-owe/
First the good news: the official federal deficit
is only 3% of GDP – way below the 10% figure it reached only a few years
ago. Now the bad news: The real deficit is more than ten times that amount.
The U.S. government’s deficit is expected to be
$514 billion this year, according to the
Congressional
Budget Office (CBO). That’s the number you get
when you look at cash flow. It means the government will spend $514 billion
more than it takes in during the 2014 fiscal year.
But this kind of accounting ignores federal
government liabilities that will become due in future years. For example,
over the course of a year millions of people earn Social Security and
Medicare benefits as well as other government entitlement benefits that will
have to be paid in future years. When you total all that up (and subtract
expected future revenues to pay those benefits), we added $5 trillion in
debt last year according to Boston University economist
Larry Kotlikoff.
Another way to look at the problem is to consider
not just one year’s deficit, but the total amount of debt that government
has accumulated. US debt held by the public is currently $12.6 trillion, or
about 75% of the size of our economy the way the CBO measures things. But in
arriving at that number, the CBO doesn’t recognize promises to pay Social
Security checks and medical bills as real obligations.
Take a senior citizen who is expecting an interest
payment on a government bond next month and who is also expecting a Social
Security check. The way the CBO looks at the world, the interest payment on
the bond is a real obligation of the government. But the Social Security
check isn’t.
That’s a strange way of accounting and Kotlikoff
and his colleagues reject it. Instead they project the value of all the
promises we have made under Social Security and other entitlement programs –
benefits that ordinary citizens believe they have earned – and subtract
expected future revenues, given the current tax law. The difference is an
unfunded liability that is every bit as real as promises to make future
interest payments on bonds and Treasury bills.
Calculating obligations in this way, Kotlikoff
estimates that the total unfunded liability of the federal government is
$210 trillion, or about 12 times the size of our economy. Writing in The New
York Times, Kotlikoff says:
“The fiscal gap — the difference between our
government’s projected financial obligations and the present value of all
projected future tax and other receipts — is, effectively, our nation’s
credit card bill. Eliminating it, would require an immediate, permanent 59
percent increase in federal tax revenue. An immediate, permanent 38 percent
cut in federal spending would also suffice. The longer we wait, the worse
the pain. If, for example, we do nothing for 20 years, the requisite federal
tax increase would be 70 percent, or the requisite spending cut, 43
percent.”
And the tax increase, by the way, doesn’t work
unless the money is sequestered and invested. It can’t just be deposited in
the Treasury’s bank account and spent on other things.
Bob Jensen's threads on the USA's entitlements disaster ---
http://www.trinity.edu/rjensen/Entitlements.htm
Bob Jensen's threads on the sad state of governmental accounting ---
http://www.trinity.edu/rjensen/Theory02.htm#GovernmentalAccounting
**How to Mislead With Voting Laws
Colorado Will Allocate Their Electoral College Delegates Based On National
Popular Vote Winner ---
Click Here
Jensen Comment
Since Colorado only has about 1.5 % of the voters that determine the popular
vote outcome in the USA it's not clear why a candidate from either party would
even visit Colorado or invest in trying to win votes in Colorado. More
importantly voters in Colorado lose any clout in influencing candidates on
matter particular to Colorado. For example, Colorado is particularly fond on
legalization of marijuana. Suppose one of both candidates declares wanting to
step of Federal enforcement of marijuana laws. Voters in Colorado have given up
entirely on trying to influence a presidential candidate's position of marijuana
law enforcement.
In Iowa, Illinois, Nebraska, and other corn-growing states there is strong
support for increasing ethanol content of gasoline. In fact former candidate Al
Gore said his main reason for supporting ethanol legislation was to get the
Midwest vote when he was running for the presidency. If the corn-growing states
did what Colorado just did with the Electoral College, those states would have
virtually zero impact on presidential candidates supporting their wishes.
What makes matters worse is that Colorado just passed the power of electing a
president of the USA to the high-population states like California, New York,
Texas, etc.
Why do Colorado voters want to lose any influence on electing the President?
Of course it's possible that the popular vote could be divided by a only a small
number of votes such that Colorado's rubber stamp helps elect the winner. The
important thing to note, however, is that Colorado voters most likely did not
decide the winner. Colorado's rubber stamp went to the voters in California,
Texas, New York, and other highly populated states of the USA.
Farmers in the USA and Australia say they will continue to spray crops
with Roundup in spite of recent lawsuits ---
https://geneticliteracyproject.org/2019/03/25/many-farmers-endorse-glyphosate-as-safe-weed-killer-while-bayer-battles-roundup-cancer-lawsuits/
Jensen Comment
Lawsuits like the recent huge jury awards in California will probably get scaled
back significantly after appeals.
Jensen Comment
Suppose there is no herbicide that can be deemed totally risk free. Further
suppose that herbicides enormously add yield to food crops around the world.
This becomes a classic case for student debates about ethics and morality. It's
an extension of the classic Trolley Problem in philosophy ---
https://en.wikipedia.org/wiki/Trolley_problem
I might add that the cancer risk concerning Roundup is still hotly debated in
science.
The debate becomes even more interesting if the competition becomes between
nations. The USA is a land of lawyers where too many large lawsuits can end use
of a product. But in many (most?) other nations lawyers have much less societal
power. It may well boil down to a world in which USA farm productivity is
greatly curtailed relative to farm productivity in the rest of the world.
**How to Mislead
With Statistics
Epic miscalls
and landslides unforeseen: The exceptional catalog of polling failure ---
https://theconversation.com/epic-miscalls-and-landslides-unforeseen-the-exceptional-catalog-of-polling-failure-146959
**How to Mislead With Statistics
Paul Krugman Rejected by His Peers ---
Click Here
http://townhall.com/columnists/johncgoodman/2015/01/17/paul-krugman-rejected-by-his-peers-n1944174?utm_source=thdaily&utm_medium=email&utm_campaign=nl&newsletterad=
Questionable Integrity of Paul Krugman: How to Mislead With Statistics
"Paul Krugman's Interesting Semantic And Statistical Dodge On Tax Rates,"
by Tim Worstall, Forbes, September 26, 2014 ---
http://www.forbes.com/sites/timworstall/2014/09/26/paul-krugmans-interesting-semantic-and-statistical-dodge-on-tax-rates/
Nobel Laureate economist and political activist Paul Krugman is sometimes
known to cherry pick data or even invent data in order to make a political point
---
Paul Krugman ---
http://en.wikipedia.org/wiki/Paul_Krugman
. . .
Krugman's columns have drawn criticism as well as
praise. A 2003 article in The Economist[ questioned Krugman's
"growing tendency to attribute all the world's ills to George Bush," citing
critics who felt that "his relentless partisanship is getting in the way of
his argument" and claiming errors of economic and political reasoning in his
columns. Daniel Okrent, a former The New York Times ombudsman, in his
farewell column, criticized Krugman for what he said was "the disturbing
habit of shaping, slicing and selectively citing numbers in a fashion that
pleases his acolytes but leaves him open to substantive assault.
"The Missing Data in Krugman’s German Austerity Narrative" Daniel J.
Mitchell, Townhall, February 25, 2014 ---
http://finance.townhall.com/columnists/danieljmitchell/2014/02/25/the-missing-data-in-krugmans-german-austerity-narrative-n1800047?utm_source=thdaily&utm_medium=email&utm_campaign=nl
There’s an ongoing debate about
Keynesian economics, stimulus spending, and
various
versions of fiscal austerity,
and regular readers know I do everything possible to explain that you can
promote added prosperity by reducing the
burden of government spending.
. . .
But here’s the problem with his article. We know
from the (misleading) examples above
(not quoted here) that he’s complained about supposed
austerity in places such as the United Kingdom and France, so one would
think that the German government must have been more profligate with the
public purse.
After all, Krugman wrote they haven’t “imposed a
lot of [austerity] on themselves.”
So I followed the advice in Krugman’s “public
service announcement.” I didn’t just repeat what people have said. I dug
into
the data to see what
happened to government spending in various nations.
And I know you’ll be shocked to see that Krugman
was wrong. The Germans have been more frugal (at least in the sense of
increasing spending at the slowest rate) than nations that supposedly are
guilty of “spending cuts.”
"About Those Income Inequality Statistics An answer to Paul Krugman,"
by Bret Stephens, The Wall Street Journal, January 3, 2014 ---
http://online.wsj.com/news/articles/SB10001424052702304325004579298502492870522?mod=djemEditorialPage_h
Let me do something
New York Times
NYT -0.13% columnist
Paul Krugman isn't exactly famous for doing, at
least not graciously: acknowledge a mistake.
In my Dec. 31 column on income inequality, I used a
data set from the U.S. Census Bureau to make the case that incomes in the
U.S. have been growing across the board, even if the incomes of the wealthy
have grown faster than those of others further down the income scale. But I
wrote those lines looking at a set of numbers that had not been adjusted for
inflation.
Professor Krugman, in a post on his New York Times
blog, takes me to task for this. Had I done so looking at the
inflation-adjusted table, it would have shown the incomes of the bottom 20%
essentially stagnating since 1979 (and long before then, too), though it
also would have shown incomes for the top 20% rising far less dramatically.
That was an error, roughly of the kind the Nobel
Laureate economist made last August when he confused an x for a
1/x. As is his charming wont, Mr. Krugman accuses me not of making an
honest mistake, but of "pulling a fast one."
My mistake is all the more unfortunate because
the basic point I was making is right: Americans are getting richer across
the entire income spectrum, even if they are getting richer at very
different rates. That much is confirmed by data from the Congressional
Budget Office. The CBO finds that between 1979 and 2007 income for poor
households grew by 18%, for the middle classes by nearly 40%, and for the
top 81-99% by 65%. It's the top 1% who have made out very handsomely, with a
jump of 275% over nearly three decades.
The difference between the Census Bureau and CBO
data comes down to the complicated (and ultimately subjective) way in which
"income" is defined. The Census Bureau data relies on a definition of income
that is pre-tax but post-transfer cash income. But it also excludes the
non-cash benefits that go to many of the poor, such as food stamps,
Medicaid, CHIP (children's Medicaid) and housing subsidies. (and now
more free or subsidized medical care and medications)
By contrast, the CBO numbers measure after-tax,
after-transfer income. It also includes non-cash transfers. Those benefits
may not be fungible, but they do have value. And they vindicate my core
point: "The richer have outpaced the poorer in growing their incomes, just
as runners will outpace joggers who will, in turn, outpace walkers." What
mattered, I said, was that "the walking man walks."
My column also noted that President Obama erred
when he said the top 10% take half of aggregate income; in fact, it's the
top 20% who take half the income, according to Census Bureau data. Mr.
Krugman takes issue with this, too, saying the Census Bureau figures are
pretty much worthless when it comes to quantifying the aggregate incomes of
the very rich. Much better, he says, is data from a controversial study by
two left-wing French economists, Emmanuel Saez and Thomas Piketty, which is
in line with President Obama's contention.
Talk about a fast one. As Greg Mankiw, chairman of
the Harvard Economics department, notes, Saez-Piketty has its own set of
very large problems: "The data are on tax units rather than households, they
do not include many government transfer payments, they are pre-tax rather
than post-tax, they do not adjust for changes in household size, and they do
not include nontaxable compensation such as employer-provided health
insurance."
Ultimately, debates about income inequality are
never going to be settled because both "income" and "inequality" are very
hard to measure. Is the best measure of inequality wage inequality,
income inequality, or consumption inequality? If a poor family today can now
afford a car, an air conditioner, a computer and other goods unaffordable or
unavailable to the poor of 35 years ago, can they really be said to have
stagnated economically? How do changes in the tax code affect the ways in
which income can be reported, sheltered and measured? What is the true money
value of health insurance?
And so on and on. The argument I made in my column
is that inequality should only matter to Americans if, Russia-like, the rich
are getting richer at the expense of the poor.
Neither the Census Bureau nor the CBO figures show
that.
None of this is to excuse the fact that I goofed in
my use of data. My apologies. As for Mr. Krugman, he should bear in mind
something the public editor of the New York Times once said about him: "Paul
Krugman has the disturbing habit of shaping, slicing and selectively citing
numbers in a fashion to please his acolytes but leaves him open to
substantive assaults."
"Is Paul Krugman Leaving Princeton In Quiet Disgrace?" by Ralph Benki,
Forbes, July 14, 2014 ---
http://www.forbes.com/sites/ralphbenko/2014/07/14/is-paul-krugman-leaving-princeton-in-quiet-disgrace/
Professor Paul Krugman is
leaving Princeton. Is he leaving in disgrace?
Not long, as these things go, before his departure
was announced Krugman thoroughly was indicted and publicly eviscerated for
intellectual dishonesty by Harvard’s Niall Ferguson in a hard-hitting
three-part series in the Huffington Post, beginning
here, and with a coda in
Project Syndicate, all
summarized at Forbes.com. Ferguson, on
Krugman:
Where I come from … we do not fear bullies. We
despise them. And we do so because we understand that what motivates
their bullying is a deep sense of insecurity. Unfortunately for Krugtron
the Invincible, his ultimate nightmare has just become a reality. By
applying the methods of the historian – by quoting and contextualizing
his own published words – I believe I have now made him what he richly
deserves to be: a figure of fun, whose predictions (and proscriptions)
no one should ever again take seriously.
Princeton, according to
Bloomberg News, acknowledged Krugman’s
departure with an extraordinarily tepid comment by a spokesperson. “He’s
been a valued member of our faculty and we appreciate his 14 years at
Princeton.”
Shortly after Krugman’s departure was announced
no less than the revered Paul Volcker, himself a Princeton alum, made a
comment — subject unnamed — sounding as if directed at Prof. Krugman. It
sounded like “Don’t let the saloon doors hit you on the way out. Bub.”
To the
Daily Princetonian (later reprised by the
Wall Street Journal, Volcker
stated with refreshing bluntness:
The responsibility of any central bank is price
stability. … They ought to make sure that they are making policies that
are convincing to the public and to the markets that they’re not going
to tolerate inflation.
This was followed by a show-stopping statement:
“This kind of stuff that you’re being taught at Princeton disturbs me.”
Taught at Princeton by … whom?
Paul Krugman, perhaps? Krugman, last year, wrote
an op-ed for the New York Times entitled Not
Enough Inflation. It betrayed an
extremely louche, at best, attitude toward inflation’s insidious
dangers. Smoking gun?
Volcker’s comment, in full context:
The responsibility of the government is to have
a stable currency. This kind of stuff that you’re being taught at
Princeton disturbs me. Your teachers must be telling you that if you’ve
got expected inflation, then everybody adjusts and then it’s OK. Is that
what they’re telling you? Where did the question come from?
Is Krugman leaving in disgrace? Krugman really
is a disgrace … both to Princeton and to the principle of monetary
integrity. Eighteenth century Princeton (then called the College of New
Jersey) president John Witherspoon, wrote, in his
Essay on Money:
Let us next consider the evil that is done by
paper. This is what I would particularly request the reader to pay
attention to, as it was what this essay was chiefly intended to show,
and what the public seems but little aware of. The evil is this: All
paper introduced into circulation, and obtaining credit as gold and
silver, adds to the quantity of the medium, and thereby, as has been
shown above, increases the price of industry and its fruits.
“Increases the price of industry and its fruits?”
That’s what today is called “inflation.”
Inflation is a bad thing. Period. Most of all it
cheats working people and those on fixed incomes who Krugman pretends to
champion. Volcker comes down squarely, with Witherspoon, on the side of
monetary integrity. Krugman, cloaked in undignified sanctimony, comes down,
again and again, on the side of … monetary finagling.
Krugman consistently misrepresents his
opponents’ positions, constructs fictive
straw men, addresses marginal figures, and
ignores inconvenient truths set forward by figures of probity such as the
Bank of England and the
Bundesbank,
thoughtful work such as that by Member of
Parliament (with a Cambridge Ph.D. in economic history) Kwasi Kwarteng, and,
right here at home, respected thought leaders such as
Steve Forbes and
Lewis E. Lehrman (with whose
Institute this
writer has a professional affiliation).
Continued in article
Bob Jensen's threads on professors who cheat ---
http://www.trinity.edu/rjensen/Plagiarism.htm#ProfessorsWhoPlagiarize
**How to Mislead With Statistics
There's a
Lake Wobegon Effect Inside Every New York K-12 School
"Cuomo’s Grade Inflation," by Alysia Finley, The Wall Street Journal,
December 22, 2014 ---
http://www.wsj.com/articles/political-diary-cuomos-grade-inflation-1419279956?tesla=y&mod=djemMER_h&mg=reno64-wsj
Nothing quite motivates New York Gov. Andrew Cuomo
like bad publicity. Last Thursday—mere days after the state’s new and
putatively improved