More Than 700 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


Masked by Trust: Bias in Library Discovery ---
https://works.bepress.com/mreidsma/5/

The rise of Google and its integration into nearly every aspect of our lives has pushed libraries to adopt similar "Google-like" search tools, called discovery systems. Because these tools are provided by libraries and search scholarly materials rather than the open web, we often assume they are more "accurate" or "reliable" than their general-purpose peers like Google or Bing. But discovery systems are still software written by people with prejudices and biases, library software vendors are subject to strong commercial pressures that are often hidden behind diffuse collection-development contracts and layers of administration, and they struggle to integrate content from thousands of different vendors and their collective disregard for consistent metadata.  

Library discovery systems struggle with accuracy, relevance, and human biases, and these shortcomings have the potential to shape the academic research and worldviews of the students and faculty who rely on them. While human bias, commercial interests, and problematic metadata have long affected researchers' access to information, algorithms in library discovery systems increase the scale of the negative effects on users, while libraries continue to promote their "objective" and "neutral" search tools.  

Bob Jensen's threads on bias in academe ---
http://faculty.trinity.edu/rjensen/HigherEdControversies2.htm#PoliticalCorrectness

Over 700 examples of how to mislead with statistics ---
Scroll Down

 


**How to Mislead With Statistics

The Consumer Price Index Is Not Economic Reality ---
https://www.bloomberg.com/opinion/articles/2021-04-13/consumer-price-index-cpi-history-is-surprisingly-political


**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: 

        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.


**How to Mislead With Statistics

Evanston bookstore owner suing Amazon over alleged price-fixing scheme that makes it impossible for other retailers to compete ---
https://chicago.suntimes.com/business/2021/3/29/22357482/evanston-bookstore-owner-suing-amazon-price-fixing-scheme-compete

An Evanston bookstore owner wants to take on Amazon.

Nina Barrett, owner of Bookends and Beginnings, signed on as the named plaintiff in a class-action lawsuit filed last week that accuses Amazon of orchestrating a price-fixing scheme with the nation’s leading book publishers that makes it impossible for other retailers to beat their prices.

According to the suit, contracts that Amazon has with the nation’s “Big Five” publishers — Penguin Random House, HarperCollins, Hachette, Macmillan and Simon & Schuster — block the publishers from giving other retailers better prices.

“I, along with most independent bookstore owners in America, feel incredibly frustrated because we’ve seen that the playing field is not level,” Barrett told the Sun-Times. “We have to talk to our customers all the time about why we can’t match Amazon’s pricing.”

     Continued in article

How to Mislead With Statistics

Evanston bookstore owner suing Amazon over alleged price-fixing scheme that makes it impossible for other retailers to compete ---
https://chicago.suntimes.com/business/2021/3/29/22357482/evanston-bookstore-owner-suing-amazon-price-fixing-scheme-compete

An Evanston bookstore owner wants to take on Amazon.

Nina Barrett, owner of Bookends and Beginnings, signed on as the named plaintiff in a class-action lawsuit filed last week that accuses Amazon of orchestrating a price-fixing scheme with the nation’s leading book publishers that makes it impossible for other retailers to beat their prices.

According to the suit, contracts that Amazon has with the nation’s “Big Five” publishers — Penguin Random House, HarperCollins, Hachette, Macmillan and Simon & Schuster — block the publishers from giving other retailers better prices.

“I, along with most independent bookstore owners in America, feel incredibly frustrated because we’ve seen that the playing field is not level,” Barrett told the Sun-Times. “We have to talk to our customers all the time about why we can’t match Amazon’s pricing.”

     Continued in article

Jensen Comment
Giving bookstores lower purchase prices than online vendors (think Amazon) forces publishers to share in the cost of bookstore services that most book buyers don't want to pay for in higher prices for books in local bookstores. These include the typical "middle man" services of wholesalers that many product lines have been eliminating in this era of technology. 

My neighbor in San Antonio for years had a wholesaling company that had exclusive rights for distributing some name brands (think Heinz) to all San Antonio area retailers. This gave him and his family a very comfortable living for many years, but one has to think that in modern times Heinz could probably sell their brands directly to San Antonio retailers at lower prices. My point is that this is somewhat analogous to how Amazon can sell books worldwide online with lower profit margins per book in what accountants call cost-profit-volume (CPV) analysis.

There's no doubt that local bookstores provide services that Amazon online cannot provide. For one thing, there's entertainment and serendipity advantages of customer browsing in bookstores. I love physical, especially in my favorite multi-story bookstore in Denver that has comfortable chairs among their book shelves. The problem is that these days not enough customers are willing to pay extra for the browsing services. The typical customer might browse in a bookstore, find books to purchase, and then go home and place an order with Amazon at lower prices.

There's also value when bookstore vendors have wide knowledge of related books. A customer might rave over a recent book she or he read and then ask a bookstore vendor:  "Are their similar books to this marvelous book?"

Some bookstores may provide tea, wine, and treats to browsers.

It's a little like the transition from full service (check the tire pressure, check the oil, and wash the windshield) gasoline stations of my youth to no service (my current  local self service station having zero attendants) gasoline station in Franconia, NH in my retirement. If given a choice, most drivers prefer not to pay extra for fuel accompanied by full services. 

If publishers sold books to Amazon for higher prices than to bookstores it would be a little like refiners selling fuel for less to full service filling stations. Customers would end up paying higher prices for fuel whether they buy from full service or self-service filling stations. The bottom line is that retail customers would be paying for services that most (not all) do not want to pay for when having no choice but to pay the higher prices. 

In other words, Amazon would have to charge more to recover the higher price Amazon pays for books. Bookstores would not charge less than Amazon, because of higher overhead and lower volume. Both Amazon and a bookstore might charge about the same price, a price that's higher than Amazon currently charges for books because of lower overhead.

 


**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

Sudipta Basu

Temple University - Department of Accounting

Dmitri Byzalov

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

Basu, Sudipta and Byzalov, Dmitri, Modeling Skewness Determinants in Accounting Research (November 30, 2020). Available at SSRN: https://ssrn.com/abstract=3740197 or http://dx.doi.org/10.2139/ssrn.3740197
 

**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

NBER: Misdemeanor Prosecution ---
https://www.nber.org/papers/w28600

Communities across the United States are reconsidering the public safety benefits of prosecuting nonviolent misdemeanor offenses. So far there has been little empirical evidence to inform policy in this area. In this paper we report the first estimates of the causal effects of misdemeanor prosecution on defendants' subsequent criminal justice involvement. We leverage the as-if random assignment of nonviolent misdemeanor cases to Assistant District Attorneys (ADAs) who decide whether a case should move forward with prosecution in the Suffolk County District Attorney's Office in Massachusetts. These ADAs vary in the average leniency of their prosecution decisions. We find that, for the marginal defendant, nonprosecution of a nonviolent misdemeanor offense leads to large reductions in the likelihood of a new criminal complaint over the next two years. These local average treatment effects are largest for first-time defendants, suggesting that averting initial entry into the criminal justice system has the greatest benefits. We also present evidence that a recent policy change in Suffolk County imposing a presumption of nonprosecution for a set of nonviolent misdemeanor offenses had similar beneficial effects: the likelihood of future criminal justice involvement fell, with no apparent increase in local crime rates.

...

We find that the marginal nonprosecuted misdemeanor defendant is 33 percentage points less likely to be issued a new criminal complaint within two years post-arraignment (58% less than the mean for complier" defendants who are prosecuted; p < 0.01). We find that nonprosecution reduces the likelihood of a new misdemeanor complaint by 24 percentage points (60%; p < 0.01), and reduces the likelihood of a new felony complaint by 8 percentage points (47%; not significant). Nonprosecution reduces the number of subsequent criminal complaints by 2.1 complaints (69%; p < .01); the number of subsequent misdemeanor complaints by 1.2 complaints (67%; p < .01), and the number of subsequent felony complaints by 0.7 complaints (75%; p < .05). We see significant reductions in subsequent criminal complaints for violent, disorderly conduct/theft, and motor vehicle offenses.

Jensen Comment
Firstly, if less than half are "less likely" to repeat the offenses what happens to those that are "more likely" to repeat offenses?

Secondly, there is such a wide variety of misdemeanor crimes that lumping them together and looking at averages can be misleading. Examples of misdemeanors include prostitution, drug possession, non-violent mugging, vandalism, trespassing, public intoxication, public defecation, reckless driving, indecent exposure, peeking tommery, and shoplifting. Indeed not prosecuting some of these crimes might lower the odds of repeating the offense, but I find it hard to believe that not prosecuting for prostitution and shoplifting is going to lead to a lower likelihood of prostitution and shoplifting.

Thirdly, not prosecuting some crimes leads to lowering the possibility of such crimes. For example, if shoplifting becomes too rampant big box stores (think Walmart and Target) may either close down or certainly not build new stores in the parts of a community where shoplifting is more likely.  One time I shopped in a convenience store in downtown Baltimore where customers were not allowed to touch the merchandise until is was paid for. Clerks behind bulletproof glass retrieved the merchandise and collected the money before the merchandise was passed in drawers to customers. The effect of not prosecuting crimes thereby leads to higher prices of merchandise and/or increased costs of having to travel much further to shop in stores. More dramatically if non-violent mugging and panhandling becomes more likely due to non-prosecution tourists will avoid the high risk areas such that crime statistics go down for the wrong reasons. Wiill tourists flock to Los Angeles and Portland, Oregon since these cities no longer prosecute misdemeanors? The only people flocking to such places may be drug addicts (which is what happened in San Francisco).

Fourthly, and most importantly, there may be huge changes in the data being collected. For example, if misdemeanors are no longer prosecuted after January 1, 2022 it may well be that victims may no longer report crimes and/or police arrest far fewer criminals after January 1, 2022 because their arrests will not be prosecuted. Hence, there may be increases in these misdemeanors that are no longer getting into the crime database.

Lastly, the use of p-values in statistical inference has fallen out of favor with the American Statistical Association because they are too unreliable ---
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

 


**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

Here's how much every US state (and Washington DC) pays its teachers and how much they spend on each student ---
Click Here

Rank (Teacher Salary Average. Spending Per Student)

01 New York ($87,543, $24,040)
02 California ($84,649, $12,498)
03 Massachusetts ($83,622 ,$17,058)
04 Washington, DC ($79,350, $22,759)
05 Connecticut ($78,247, $20,635)
06 New Jersey ($76,376, $20,021)
07 Maryland ($73,444, $14,762)
08 Washington ($72,965, $12,995)
09 Alaska ($70,877, $17,726)
10 Pennsylvania ($70,258, $16,395)

...

42 Indiana ($51,508, $10,262)
43 South Carolina ($51,485, $10.856)
44 Missouri ($50,817, $10,810)
45 Arizona ($50,381, $8,329)
46 West Virginia ($50,238, $11,334)
47 Louisiana ($50,217, $11,452)
48 Arkansas ($49,822, $10,139)
49 South Dakota ($49,220, $10,073)
50 Florida ($48,800, $9,346)
51 Mississippi ($45,192, $8,935)

Jensen Comment
Broad generalizations are misleading. We might say that it costs about half as much to live in Mississippi as in New York, but this is not entirely true because it costs much more than double to live in New York City and much less than double to live in Poughkeepsie, New York.

One might conclude that southern states pay teachers a lot less, but why do South Dakota, Indiana, and Arizona rank down among the low paying southern states? Some southern states (think Georgia) are not in the bottom 10 in terms of average teacher salaries. There are all sorts of statistical problems when dealing with average salaries without considering dispersions around the mean. In New York for example the  salaries highly skewed upward by the immense number New York City high salaries, These very high average salaries skew the state's mean upwards relative to what it would be if New York City was taken out of the mean calculation.

There are also statistical concerns about the spending per student numbers shown above.
There are many factors affecting spending per student. Vermont and Georgia at ranks 17 and 18 have nearly identical average teacher salaries (about $61,000) And yet Vermont's spending per student is a whopping $19,340 compared to Georgia's spending per student at $10,810. This is due mostly to a policy of allowing miniscule rural towns in Vermont to have their own unconsolidated school districts. The Vermont joke is that some school districts have more supervisory board members than the numbers of students in their very rural schools. The good news is that the student/teacher ratio is very, very low in Vermont while administrator/student ratios are also very high. This is probably a very good thing from a pedagogical standpoint but a bad thing from an accounting standpoint. It cost a lot extra to heat and maintain school buildings for only a few students.

In Georgia school districts tend to be more consolidated giving rise to a lower average spending per student. Vermont could greatly lower its spending per student by consolidating more districts, but this would also increase the student/teacher ratios and make students be bussed relatively long distances across mountain passes in the winter. New Hampshire at rank 19 spends less per student ($16,893) than Vermont ($19,340), but this is due in part to having a population of 1,400,000 compared to Vermont's sparse 644,000 population over roughly the same land mass and terrain. New Hampshire has more populated school districts due heavily to having over twice as many residents in the state. This in turn is due to New Hampshire's attraction of having no income tax and no sales tax, whereas Vermont taxes everything it can think of to tax. One thing very high taxes do is keep the population low.

The above type of reasoning does not apply to all states. What Mississippi and Florida spend per student is just plain miserable no matter how you look at it. But look at how much more New York state spends per student relative to California. Go figure why New York spends nearly twice as much per student!

My main point is that spending per student is a very misleading number because there are so many heterogeneous efficiencies and inefficiencies blended into that one number. In Vermont high spending per student leads to very small numbers of students per teacher. But in New York high spending per student is not generally such a good thing for student/teacher ratios like high spending is in Vermont. Spending per student is highly skewed by the cost of everything in New York City.

 


**How to Mislead With Statistics

Those hidden factors affecting research outcomes
https://marginalrevolution.com/marginalrevolution/2021/03/testing-todd.html


R
esearchers make hundreds of decisions about data collection, preparation, and analysis in their research. We use a many‐analysts approach to measure the extent and impact of these decisions. Two published causal empirical results are replicated by seven replicators each. We find large differences in data preparation and analysis decisions, many of which would not likely be reported in a publication. No two replicators reported the same sample size. Statistical significance varied across replications, and for one of the studies the effect's sign varied as well. The standard deviation of estimates across replications was 3–4 times the mean reported standard error.

Jensen Comment
Accounting researchers rarely discover such problems because those researchers rarely replicate the works of one another.

574 Shields Against Validity Challenges in Plato's Cave ---
http://faculty.trinity.edu/rjensen/TheoryTAR.htm

 


**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

The Gender Gap in Pandemic Job Losses Has Been Wildly Exaggerated ---
https://reason.com/2021/05/11/the-gender-gap-in-pandemic-job-losses-has-been-wildly-exaggerated/

Jobs data casts doubt on the idea that the COVID-19 pandemic is uniquely setting women back.

For more than a year, the U.S. has been flooded with gloomy headlines and dire predictions about women and work. "The pandemic is devastating a generation of working women," opined one Washington Post writer in February. Citing data showing that 2.5 million women dropped out of the workforce since the COVID-19 pandemic began, Vice President Kamala Harris said "the pandemic has put decades of the progress we have collectively made for women workers at risk."

Harris called it a "national emergency"—albeit one that could be fixed by greenlighting the Biden administration's coronavirus spending plan.

And so the narrative typically goes: women's employment prospects are in crisis; the way out is passing the Democrats' preferred economic policies. (See Matt Welch in Reason's June print issue for more on this rhetoric.)

But the magnitude of this gender gap has never been as great as many have made it out to be. And recent data cast further doubt on the "she-cession" narrative. At the end of April 2021, the unemployment rate for women was slightly lower than the unemployment rate for men. And the women's labor force participation rate had recovered more than the men's rate had.

Just How Big Are These Gender Gaps Now? 

To read headlines about gender and job losses, one might get the impression that U.S. women are faring drastically worse on the coronavirus-era employment front than men are. Yet such losses have never been as drastically gendered as many doomsayers let on.

"Labor force participation—defined as all civilians working full or part time, as well as those who are unemployed but looking for work—fell dramatically for both genders between March and April 2020," noted Gallup. In April 2020, men's labor force participation was at 97.8 percent of its February 2020 level and women's labor force participation was 96.9 percent of its February 2020 level—a gender gap of just 0.9* percentage points.

he labor force participation rate is a separate measure than the unemployment rate, which is concerned with how many people are out of work and actively seeking a job. On unemployment, U.S. women are also faring better than their male counterparts (though "better" here does come with some caveats, since unemployment numbers don't include people out of a job and not seeking a new one).

In April 2021, the unemployment rate for U.S. men ages 20 and older was at 6.1 percent, down 7 percentage points from its April 2020 peak. For women ages 20 and older, it was at 5.6 percent—down 9.9 percentage points since the previous April.

Put another way, women's unemployment rate is now just 2.5 percentage points higher than it was in pre-pandemic times, while men's unemployment rate is 2.9 percentage points higher.

The Truth Behind the Panic 

It is true that American women initially lost more jobs to COVID-19 than their male counterparts did (in contrast to the typical recession pattern).

In February 2020, the civilian unemployment rate for women age 20 and up was 3.1 percent, according to BLS data. For men, it was 3.2 percent. But by the end of April 2020, the unemployment rate for women had jumped to 15.5 percent, while for men it only jumped to 13.1 percent.

Two explanations for this discrepancy have emerged. First, women tend to outnumber men as the primary caregivers for children and elderly or ailing family members, leaving them more vulnerable to work disruptions when schools and child care centers shut down, when kids need homeschooling, or when relatives need care. Second, women are more highly concentrated in retail, leisure, and hospitality jobs, which were more heavily affected by pandemic-related closures, restrictions, and mandates.

While the first factor has gained the most attention, the second one may be the bigger culprit.

Labor force participation for women with children did indeed drop more than it did for men with children, "consistent with the theory that working mothers disproportionately took themselves out of the labor force to care for children who were no longer able to attend day care or school," noted Gallup. Yet "the drops among women without children and men without children are also sizable," which "suggests that factors other than child care have significantly influenced decisions to leave the workforce."

"Overall, these labor force patterns seem largely tied to occupational differences between women and men," according to Gallup's analysis of BLS data. "Occupations with a higher share of women have exhibited lower labor force participation rates and higher unemployment rates throughout the pandemic."

Either explanation suggests that—for both women and men—the drop is more likely short-term than long-term.

A Call to Arms? 

Given the current state of recovery, "it does not make sense to enact permanent programs, such as government-run paid family and medical leave, subsidized childcare, and universal pre-K with the justification of fixing a COVID -19 disparity that no longer exists," argues Heritage Foundation research fellow Rachel Greszler in a new report.

"Policymakers can do far more to help women and families by removing government-imposed barriers to flexible work, to employer-provided paid family and medical leave, and to accessible and affordable childcare than by adding costly and bureaucratic new programs and upending the labor market in ways that would limit families' incomes and choices," she posits.

 

By February 2021, labor force participation for both sexes had ticked back up somewhat. And while women were still seeing a less full recovery, the gap was again less than one percentage point. Compared to February 2020, men's February 2021 labor force participation was 2.2 percent smaller and women's was 3.1 percent smaller.

That's not nothing—"the gap in labor force changes amounts to roughly 493,000 more women than men being absent from the labor force since the pandemic began," Gallup pointed out in early March. But it's also not evidence that women have been uniquely devastated by pandemic-related job losses, especially when—contra previous economic downturns—many of the circumstances that initially created the job losses will remedy quickly as life returns to a more normal pace.

Indeed, that already seems to be happening, according to data from the Bureau of Labor Statistics (BLS).

In April 2021, the labor force participation rate for U.S. men 20 and older was 69.8 percent, down from 71.6 percent in February 2020. For women, it was 61.7 percent in April, down from the 63.3 percent in February 2020. So, while women's labor force participation was lower than men's at the start of the pandemic and still is, women are now slightly closer than men are to their pre-pandemic participation level, with the April 2021 labor force participation rate for men 1.8 percentage points lower and the rate for women down 1.6 percentage points.

Continued in article

 


**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 £21bn.

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 ruralsprawling 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.”

·        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:

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 temporarely 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 MadrigalThe 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 Kongs 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.

Revenue

US$21.46 billion (2018)

Operating income

US$-0.39 billion (2018)

Net income

US$−0.98 billion (2018)

Total assets

US$29.74 billion (2018)

Total equity

US$4.92 billion (2018)

Owner

Elon Musk (21.7%)[3]

Number of employees

45,000[4] (2018)

 

Ford Motor Company ---
https://en.wikipedia.org/wiki/Ford_Motor_Company

 

Revenue

US$160.33 billion (2018)[2]

Operating income

US$3.27 billion (2018)[2]

Net income

US$3.67 billion (2018)[2]

Total assets

US$256.54 billion (2018)[2]

Total equity

US$35.93 billion (2018)[2]

Owners

·         The Vanguard Group (5.82%)[3]

·         Evercore Wealth Management (5.58%)

·         Ford family
(2% equity; 40% voting power)
[3][4]

Number of employees

199,000 (2018)

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 ("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.

Revenue

US$21.46 billion (2018)

Operating income

US$-0.39 billion (2018)

Net income

US$−0.98 billion (2018)

Total assets

US$29.74 billion (2018)

Total equity

US$4.92 billion (2018)

Owner

Elon Musk (21.7%)[3]

Number of employees

45,000[4] (2018)

 

Ford Motor Company ---
https://en.wikipedia.org/wiki/Ford_Motor_Company

 

Revenue

US$160.33 billion (2018)[2]

Operating income

US$3.27 billion (2018)[2]

Net income

US$3.67 billion (2018)[2]

Total assets

US$256.54 billion (2018)[2]

Total equity

US$35.93 billion (2018)[2]

Owners

·         The Vanguard Group (5.82%)[3]

·         Evercore Wealth Management (5.58%)

·         Ford family
(2% equity; 40% voting power)
[3][4]

Number of employees

199,000 (2018)

 

 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 naïveté 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:

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
 TripAdvisorHajj 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 naïve 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.”

 

To read the paper, go to
https://arxiv.org/abs/1905.13494

 


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&region=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:

 

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.

Th$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

A World Beyond p < 0.05

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; 2003has 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 tha