# No, Most U.S. Gun Owners Don’t Stockpile 17 Or More Guns

Newsweek recently published an article titled: ‘Was Stephen Paddock Normal? Many Gun Owners Keep 17 Firearms on Average.’ It’s based on a study that is all wrong.

Article in The Federalist, October 18, 2017.

# Consumer Reports on Student Loan Debt

(click for larger image)

[Update November 10, 2016: a comment on this article was posted on one of my other blogs.  I have  encouraged the commenter to post it here instead.  Hopefully that will happen soon.]

Consumer Reports, the magazine that used to review cars and appliances to help people choose the best fit for them, has now officially jumped the shark.  The image to the left is the cover of the most recent issue.  And it made my blood boil.

Going to college was not the mistake.  The mistake occurred in the seventh grade when many students decide math is just too hard for them.  (As I noted a few years ago, President Obama is among this group.)  Once they bailed out of the math curriculum, they also lost the chance to major in serious science, engineering, and economics.  And therefore, they lost their chance to obtain a college degree that is actually worth something in today’s job market.

But those who pile up \$100,000 in student loan debt to get a degree in interpretive dance deserve no sympathy.

# Is Algebra Necessary?

” Is Algebra Necessary? “ That was the headline in a New York Times op-ed in 2012. Perhaps New York Times reporters could use a dose.  The following is from the December 28, 2014 issue:

NY Times Lede (click image for a larger version)

Dan Meyer (@ddmeyer) pointed out the problem on Twitter:

Dan Meyer’s Markup (click image for a larger version)

Let’s see. Let x be the number of digital rentals and y be the number of sales. We know x + y = 2,000,000. We also know \$6x + \$15y = \$15,000,000. Any student in my economics principles class who could not solve this would not pass the course. But, for the edification of Times reporters, here’s the solution.

I hope this helps people understand why algebra is useful.

# Hypocrisy at the New York Times

Over the past few years, the editors at the New York Times have, on numerous occasions, supported increasing the minimum wage. So I was surprised by today’s editorial that apparently ignores a group being paid well below any minimum wage in U.S. history. AmeriCorps volunteers (“members” in Times parlance) are paid \$5,645 per year. With about 2,000 work hours in a year, the implied wage is \$2.8225 per hour. This is yet another example of hypocrisy at the New York Times.

But that’s the nominal minimum wage. We need to correct for inflation. Luckily (for me) I compiled that data for another project. Here’s the short version.

The real minimum wage paid to AmeriCorps workers is \$1.21. The lowest real minimum wage in the history of the U.S. minimum wage was \$1.70 — in 1944. (As always, my data and methods are transparent. Click here for the Excel workbook.)

For the record, the above graph shows the real minimum wage from 1938 to the present. I’ve omitted data for some years in which the nominal minimum wage did not change. I did add the data from 1939 through 1944 to my original dataset, correcting one error in that process.

So when will the Times editors come clean and admit that they are being hypocritical about the minimum wage? I’m not holding my breath and you probably shouldn’t either.

# Journalists Should Not Be Allowed to Use Data

After reading Neil Irwin’s column in the August 5 New York Times I have concluded that journalists should not be allowed to use data. I was thinking about doing a detailed analysis of the many errors in this column but decided that would be a waste of my time.  (My lovely wife has me working on a crash project involving learning and implementing Excel Visual Basic.  Believe me, you don’t want to know any more.)

Instead, I’ll offer this quick-and-dirty comment.  Mr. Irwin uses the average percentage of GDP of the various components over the last 20 years.  He then applies those percentages to the CBO estimate of “potential GDP” for the second quarter of 2014.  (Potential GDP is also called full-employment GDP and a few other names that escape my memory right now.)

So what’s wrong with that?  Well, it ignores secular trends in the economy.  Over the past 20 years one of the fastest-growing areas has been consumer spending on services.  Mr. Irwin’s methodology essentially assumes that consumer spending on services as a percentage of GDP has been constant over that period.  And guess what his number one category that “over-performed” over that period?  Consumer spending on services.  What a surprise.

But it gets worse.  The second largest “over-performing” segment is business inventories.  I don’t even know what that means.

Mr. Irwin, do the world a favor.  The next time you’re tempted to work with data, hire a real economist as a consultant.

# The Invisible Economy is Not the Hidden Economy

The Climbing Wall at Google’s Boulder, CO Campus

Our techniques for measuring economic performance are obsolete, obscuring a complete picture of how we’re faring.

On July 9, an article titled “The Invisible Economy” was published on The Atlantic website. The author, Bill Davidow, makes this claim →

Mr. Davidow, unfortunately does not understand how GDP is calculated — or the reasons many internet services are “free.”  The invisible economy is not the hidden economy (also called the underground economy).  Mr. Davidow’s “invisible economy” is entirely visible and included in GDP

Start with a basic premise: there ain’t no such thing as a free lunch. When goods or services are produced, real resources must be used to produce them. This is the basic premise of both economics and national income accounting.

## A Primer on National Income Accounting

Gross domestic product is the money value of all final goods and services produced in a country during a calendar year. This definition is so standardized that it does not warrant a citation. Here are the salient points of this definition:

1. GDP measures production of new goods and services during a year. The act of production creates income (wages and salaries, interest, profits, and a few other items).
2. These products are valued at current market prices. Simplistically, if an economy produces 1 billion oranges during the year and the market price of those oranges is \$1.50 each, orange production will add \$1.5 billion to GDP. Each country’s GDP is measured in that country’s official currency. (Note my careful avoidance of referring to “sales” of oranges. GDP measures production, not spending or sales.)
3. A final good is either something produced for current consumption, items produced for business investment (buildings, machines, residential construction), and government spending by all levels of government.
4. All production within a country is counted regardless of the home country of the firm engaged in production. Honda, a Japanese firm, has a number of assembly lines in Ohio. The production from each of those plants is added to U.S. GDP. (A related measure, gross national product, measures the value of goods and services based on the home country of the firm that produces the output.)
5. At midnight December 31, the GDP counter is reset to zero. This counter then begins adding up the money value of all goods and services. The counter is stopped at 11:59:59 the following December 31. The value on the counter is that country’s GDP for that year.

Many people believe GDP measures spending. This is incorrect. GDP measures production. Production creates income. Fundamentally this is why national income must equal national product. (See, for example, Karl Case, Ray Fair, and Sharon Oster, Principles of Macroeconomics 11e (2014). Pearson Publishing.  pages 116-117.)

Those who hold the incorrect belief arrive at this conclusion by noticing that the first approximation to GDP adds up three spending items:

1. Consumption spending by households,
2. Business fixed investment by, um, businesses,[1] and
3. Government spending by all levels of government.

What these folks fail to notice is that there are a few other items added to total spending. These three items convert total spending into total production. The three items are:

1. The net change in business inventories. Inventory change measures the difference between domestic spending on domestically produced products and domestic production. If production exceeds spending, inventories rise. The amount by which inventories rise is added to total spending as the first step in converting to production. (Inventory change is included in total business investment, but is not part of business fixed investment.)
2. Exports are products that are produced in a country but sold in another country. Exports, by definition, are not part of domestic spending. But they are part of domestic production. Adding exports to total spending is the second step in converting to production.
3. Imports are products produced in another country but sold to domestic purchasers. Since imports are included in domestic spending, they must be subtracted to arrive at production.

### A Digression on Value Added

Another way GDP can be added up is by summing all the value added in the economy. It’s helpful to understand value added to see how intermediate goods fit into the GDP framework. After all, if national income equals national product, what happens to the income earned by all those workers who produce goods that are not final goods?

Value added is the difference between a firm’s total revenue and (roughly) what it pays other businesses for products it uses to produce its output. Let’s consider a simple loaf of bread. While this presentation is simplified (to say the least), it will help you understand value added. The production chain for a loaf of bread is straightforward:

1. A farmer grows wheat. The farmer uses seeds from last year’s crop. Therefore the farmer does not purchase any products from other firms. The farmer sells enough wheat for a loaf of bread to a miller for \$0.20.
2. The miller pays the farmer \$0.20 for wheat, which is then ground into flour. The miller sells the flour to a baker for \$0.80. The miller’s value added is \$0.80 – \$0.20 = \$0.60.
3. The baker adds a few minor items to the flour (yeast, water). We will ignore the costs of those items. The baker produces a delicious loaf of bread which is sold to a grocer for \$1.50. The baker’s value added is \$1.50 – \$0.80 = \$0.70.
4. The grocer puts the loaf of bread on the shelf. At that point it becomes a final good.[2] The price of the loaf of bread is \$2.00. The grocer’s value added is \$2.00 – \$1.50 = \$0.50.

The sum of the value added at each of the four stages of production is \$0.20 + \$0.60 + \$0.70 + \$0.50 = \$2.00. Because of the way value added is calculated, total value added from all the stages of production must equal the price of the final good. Thus, by adding up the money value of all final products, we have implicitly added up the value added that went into making them. This table summarizes value added for this example:

 Producer Price of Output Payment to other firm Value Added Farmer \$0.20 \$0.00 \$0.20 Miller \$0.80 \$0.20 \$0.60 Baker \$1.50 \$0.80 \$0.70 Grocer \$2.00 \$1.50 \$0.50 TOTAL \$2.00

We need to look a little more closely at what, exactly, makes up value added.

What is the difference between a firm’s total revenue and what it pays other firms for intermediate goods? Well, the cost of any input the firm pays for that it doesn’t buy from other firms is part of value added. Those items include labor (wages and salaries), capital[3] (interest and rent), and entrepreneurship (profit). Those are also the major components of national income.

### Who Owns What?

“But,” you may say, “I don’t get any interest, rent, or profits. Who does that income flow to?”

Actually, you may be receiving some of each of those items. Do you have a retirement account? The wealth in that account owns assets (hopefully well-diversified, low cost mutual funds). Those assets earn interest, rent, and/or profits. Vast quantities of stocks and bonds in the U.S. are owned by mutual funds directly — and by households indirectly. Directly or indirectly households own all the factors of production.

Wasn’t that fun? Now let’s see how advertising fits into the GDP framework. Because, after all, it’s advertising that actually pays the bills for “free” internet services. To do this I’ll use Google as an example. Google derives about 90% of its annual revenue from advertising, making them an excellent case study.

## Google, Advertising, and GDP

Advertising creates revenue for Google. This is their gross income before deducting any business costs. Since this article is not yet mind-numbingly dull, let’s take a look at Google’s income statement and balance sheet. In 2013 Google earned net profits of \$12.9 billion on total revenue of \$59.8 billion. Of that revenue, \$50.5 billion was from advertising (84.5%). There is a mysterious “other” revenue entry of \$5 billion. Assuming that is advertising-related, the percentage rises to 92.8%. Google makes money by selling advertising. Period.

And that advertising is part of GDP. Essentially, to calculate Google’s contribution to GDP we need to calculate the company’s gross value added. Luckily for us, the Bureau of Economic Analysis has a nifty paper titled “An Introduction to the National Income and Product Accounts.” Part II of this excellent work shows how to convert business financial statements into NIPA accounts. Following the BEA methodology to the best of my ability, Google’s gross value added for 2013 was \$43.5 billion. (The Excel workbook, based on Google’s 10-K filing with the SEC, is available for downloading by clicking here.)

U.S. GDP for 2013 was \$16.8 trillion. Google’s contribution to that total was 0.26%. The U.S. economy is very, very large indeed. But saying that the internet is “free” implies Google’s gross value added is zero. That’s very far from the truth.

This Guy Lives at Google’s Mountain View, CA Campus

## Confusion by Mr. Davidow

From the article:

There are no accurate numbers for the aggregate value of those services but a proxy for them would be the money advertisers spend to invade our privacy and capture our attention. Sales of digital ads are projected to be \$114 billion in 2014, about twice what Americans spend on pets.

The forecasted GDP growth in 2014 is 2.8 percent and the annual historical growth rate of middle quintile incomes has averaged around 0.4 percent for the past 40 years. So if the government counted our virtual salaries based on the sale of our privacy and attention, it would have a big effect on the numbers.

First, note that Google’s advertising revenue is about half of the total cited by Mr. Davidow. But what is the point of the second paragraph? Comparing the dollar amount of advertising with the growth rate of GDP makes no sense at all. Instead let’s look at the dollar amount of GDP. Given the sharp drop in GDP in the first quarter, a safe forecast for 2014 nominal GDP is 2013 GDP, \$16.8 trillion. Digital advertising is therefore likely to be about 0.68% of the total. Again, not much, but well above zero.

## Conclusion

National income accounting is not particularly easy or interesting. But those who try to use GDP should know what they’re talking about. Mr. Davidow has sadly failed this test.

[1] “Investment” as used by economists means the construction of physical capital: buildings, machines, and residential construction. Similarly, “capital” refers to the total quantity of buildings, machines, and residential construction ever produced minus depreciation.

[2] Technically the loaf of bread is added to the store’s inventory, causing inventory to increase. This is actually when the bread is added to GDP. The offsetting transaction will be an increase in consumer spending when the bread is sold.

[3] Remember, “capital” means physical capital: buildings, machines, and residential construction.

# Intellectual Dishonesty at the New York Times

The February 28, 2014 New York Times included yet another editorial favoring an increase in the minimum wage.  But the Times’s editors have no excuse this time. By publishing this editorial they have proved that they are intellectually dishonest. This from the editorial:

One 2013 study by three economists — Arindrajit Dube, T. William Lester and Michael Reich — compared the experiences of businesses in neighboring counties in different states and found less turnover in states that had raised the minimum wage. Workers were less likely to leave on their own, and managers were more likely to keep the workers they had on staff to avoid the cost of recruiting and training replacements.

There’s only one slight, minor problem.  After their previous February 9 editorial on the same subject I sent the editors a long e-mail citing the Neumark, Salas, and Wascher paper and pointing out that this paper refutes both of the studies cited by the Times editors.

Are the Times editors willfully ignorant, or are they just plain stupid?  I just report.  You decide.

# The Minimum Wage Yet Again

## Executive Summary

The New York Times editorial board favors raising the minimum wage to \$11 per hour.  To support their position that this increase will not kill jobs, they cite one published paper by Dube, Lester, and Reich.  This paper has now been thoroughly debunked in recent work by Neumark, Salas, and Wascher.  Raising the minimum wage reduces employment, especially among unskilled workers.  Period.  Prof. Reich should go back to his day job shilling for labor unions.

Which Looks More Like a Business Cycle?

## The New York Times Editorial

The New York Times has raised the subject of the minimum wage yet again.  In a long editorial February 9, 2014, the editors argue in favor of a higher minimum wage.  I encourage everyone to read this editorial, as it serves as a substitute for the Times’s failure to include a comics section in their newspaper. Among the many hilarious statements made, this section stands out:

HOW HIGH SHOULD IT BE? There’s no perfect way to set the minimum wage, but the most important benchmarks — purchasing power, wage growth and productivity growth — demonstrate that the current \$7.25 an hour is far too low. They also show that the proposed increase to \$10.10 by 2016 is too modest.

The Times editors have unknowingly opened a can of worms with this argument.  How high, indeed?  Why not \$25, \$50, or even \$100 per hour? Without some sort of model of the way labor markets work, the Times editors are left pulling numbers out of … the air.  They proceed to do this, finally arriving at \$11. Even this is not enough by historical standards.  According to the Times, the minimum wage should be half the average wage after adjusting the average for productivity increases in excess of wage increases.  That brings them to \$18 per hour, a figure that gives them pause.  They’re pretty sure \$18 is too high, but don’t exactly know why.

Which is, after all, the main question.  If you have no model of how labor markets and the economy work, you are left making up numbers.  Perhaps there’s a better way to approach this problem.

To add one technical note, the Times editors apparently used the average (mean) wage rate.  They should have used the median.  The income distribution is not a normal distribution which means the median is a better measure of its midpoint than the mean.

## “Does It Kill Jobs?”

The Times editors proceed to attempt some economic modeling.  The final section of their editorial is titled “Does It Kill Jobs?”  I was pretty sure I knew their answer already, but pushed bravely ahead.  What I found was this:

The minimum wage is one of the most thoroughly researched issues in economics. Studies in the last 20 years have been especially informative, as economists have been able to compare states that raised the wage above the federal level with those that did not.

The weight of the evidence shows that increases in the minimum wage have lifted pay without hurting employment, a point that was driven home in a recent letter to Mr. Obama and congressional leaders, signed by more than 600 economists, among them Nobel laureates and past presidents of the American Economic Association.

That economic conclusion dovetails with a recent comprehensive study, which found that minimum wage increases resulted in “strong earnings effects” — that is, higher pay — “and no employment effects” — that is, zero job loss.”

The Times thus manages to both credit and discredit the economics profession in three short paragraphs.  First, the editors do not understand the difference between positive economics (economics as a science) and normative economics (favoring or opposing specific economic policies).  Positive economics is a matter of facts.  Economists use mathematics to develop their models and hypotheses.  We then turn to real-world data and statistical tools to test those hypotheses.  Hypotheses that have been confirmed[1] by many different tests become accepted as theories. That is the scientific method used in many other fields as well as economics.  It describes positive economics.

The Times did not bother to ask those economists who signed that petition one simple question: Do they believe that raising the minimum wage will have no impact on employment?  That’s very different from the petition which merely supports increasing the minimum wage.   The language of the petition moves the debate out of positive economic analysis and into the opinions and wrangling of normative economics.

It does not surprise me that the Times editors fail to understand this distinction.  They are, after all, locked in the ivory tower of journalism with walls designed to prevent inconvenient facts from getting in their way.  And the Times is located in one of the most left-leaning cities in the U.S.  What could be more fertile ground for the weeds of belief to overrun the grain of science?

### The Research Supporting the Times’s Position

The paper cited by the times is “Minimum Wage Effects Across State Borders: Estimates Using Contiguous Counties” by Arindrajit Dube, T. William Lester, and Michael Reich was published in the Review of Economics and Statistics in the November, 2010 issue. Following the lead set by Neumark, Salas and Wascher, I will refer to this work as DLR. The authors compare adjacent counties separated by a state line.  They then look at periods during which one state’s minimum wage changed while the other’s stayed the same.  They found no impact on employment.  I won’t bother to describe the details of their methodology for two reasons.  First, it’s wrong.  Second, you can find their paper online easily.  Prof. Reich has it posted on his website.

It happens that there is a second paper using pretty much the same techniques and sharing two of the three co-authors.  The paper is “Do Minimum Wages Really Reduce Teen Employment? Accounting for Heterogeneity and Selectivity in State Panel Data” by Sylvia A. Allegretto, Arindrajit Dube, and Michael Reich in the April, 2011 issue of Industrial Relations.  I’ll call this paper ADR.  The conclusions are identical, although the methodology differs a bit.

If you’re curious about the co-authors, I have a biographical sketch of Michael Reich toward the end of this piece.

### Neumark, Salas, and Wascher Respond

David Neumark, J.M. Ian Salas, and William Wascher (NSW) used the same data that both ADR and DLR used.  Their paper “Revisiting the Minimum Wage − Employment Debate: Throwing Out the Baby With the Bathwater?” (January, 2013. National Bureau of Economic Research Working Paper 18681).  In fact, the title is too kind.  ADR and DLR have apparently thrown out the baby and kept (and published) the bathwater.

I’m going to include three paragraphs from their paper, but here’s the summary. (Note that this is my interpretation of their findings.  Errors are mine.) First, ADR and DLR cherry-picked the time period they used to produce their results.  Using different time periods invalidates their results.  Second, both papers use a linear trend to remove influences specific to each state.  But a linear trend cannot, by definition, model, say, a business cycle. In order to model nonlinearity a second-order term must be included.  To get points of inflection you must include a third-order term.  (Examples are in the Excel workbook.) NSW find statistically significant coefficients for the second, third, fourth, and fifth order terms.

And guess what?  Using the correct methodology and time period, there are, in fact, significant effects on employment.  NSW slice and dice this about as finely as is possible.

Here are three relevant paragraphs from their paper.  Note that the paper is copyright © 2014 by David Neumark, J.M. Ian Salas, and William Wascher.  I have included these quotations with explicit permission of the authors.  You may not copy any of the next three paragraphs without their permission.  I have edited the material slightly, removing footnote numbers.

In each column, we tested the statistical significance of the higher-order terms added relative to the previous column (in column (1) we tested the significance of the squared time interactions). These were significant for the 2nd-, 3rd-, 4th- and 5th-order terms (p-values < 0.001). Thus, linear state-specific trends are too restrictive. (p. 12)

As reported in column (5) of Table 2, when the panel data model with state-specific trends is estimated in this way the estimated effects of minimum wages are much more strongly negative and are statistically significant: The estimated minimum wage effect is –0.178, compared with –0.165 in Table 1 without the state-specific linear trends and –0.074 (and insignificant) with them. Thus, removing the state-specific trends in a way that excludes the recessions at the beginning and end of the sample leads to stronger evidence of disemployment effects. (p. 13)

Thus, among the analyses we have carried out, the only way to generate the results in ADR (2011) – that inclusion of state-specific time trends eliminates the negative effects of minimum wages – is to include in the sample period the recessionary period of the early 1990s or the recent Great Recession, and to let these periods have a strong influence on the estimated trends by use of a highly restrictive specification for those trends. Moreover, the evidence suggests that the linear state-specific trends used by ADR for these sample periods are influenced by the recessions in ways that apparently contaminate their estimates of minimum wage effects on teen employment. More generally, our evidence shows that the estimated effects of minimum wages on teen employment are negative and significant with or without the inclusion of controls for long-term trends in teen employment when those long-term trends are estimated in ways that are not highly sensitive to the business cycle. This evidence invalidates ADR’s (2011) conclusion that “Lack of controls for spatial heterogeneity in employment trends generates biases toward negative employment elasticities in national minimum wage studies” (p. 206). (p. 14)

If you don’t understand the previous three paragraphs, then re-read my summary above them.  Or take a look at the graphs at the beginning of this article. Comparing a linear model with a fifth-order polynomial shows clearly that you can’t model a business cycle with a straight line. (The parameters of each model were estimated using regression analysis on a single data set.

## Michael Reich

We’ve encountered Prof. Reich beforeHe is the director of the Institute for Research on Labor and Employment at U.C. Berkeley. The IRLE is a well-known home for union shills.  But this time Prof. Reich has gone too far.  The two papers discussed here are, at best, misleading.  At worst they are outright academic fraud.

A few decades back, Prof. Reich was co-author of The Capitalist System: A Radical Analysis of American Society (cited in the references at the end of this piece).  The late Evsey Domar reviewed this book in the Journal of Political Economy in 1974.  His review, titled “Poor Old Capitalism: A Review Article,” is scathing. (Full citation in the References below.) Here are two paragraphs from page 1312:

So the end result is just another utopia, recognized by the authors as such (pp. 392, 530). It is an old-fashioned anarchist utopia that would delight Kropotkin and Proudhon (and Furier), but hardly please Marx, if he remained true to his own spirit. In its treatment of economic problems, it is not superior to Thomas More’s original creation, and it is greatly inferior to Edward Bellamy’s Looking Backward ([1888] 1960), now nearly 100 years old. And Bellamy was not even an economist!

There is no harm in describing utopias if one does not take them seriously. But what is the use of criticizing capitalism, or any other existing economic system, in a supposedly scholarly and analytical manner, by comparing it with an ideal, which can be made as wonderful as the authors’ imagination allows? Surely more effective methods can be found. The ineptitude shown by the contributors and the editors (well-trained young economists of known ability) merely damages their own cause: it makes capitalism look better than it is. Instead of winning converts, they are more likely to repel even those who have no love for capitalism and are searching for better alternatives.

## Conclusion

Once you do the analysis correctly, raising the minimum wage reduces employment.  Period.  Will this end the debate?  Of course not.  Low-information individuals are globally abundant today.  These folks won’t let facts get in the way of their beliefs.

The Times editorial board already had their collective mind made up before they wrote this editorial.  Frankly, their attempt to justify their conclusion with economic analysis is a complete failure.  Call them low-information editors.

## References

Allegretto, Sylvia A., Arindrajit Dube, and Michael Reich. 2011. “Do Minimum Wages Really Reduce Teen Employment? Accounting for Heterogeneity and Selectivity in State Panel Data.” Industrial Relations, Vol. 50, No. 2, April, pp. 205-240.

Domar, Evsey D. “Poor Old Capitalism: A Review Article” 1974. Journal of Political Economy, 1974, vol. 82, no. 6 pp. 1301-1313

Dube, Arindrajit, T. William Lester, and Michael Reich. 2010. “Minimum Wage Effects Across State Borders: Estimates Using Contiguous Counties.” Review of Economics and Statistics, Vol. 92, No. 4, November, pp. 945-64.

Editorial Board, New York Times 2014. “The Case for a Higher Minimum Wage,” February 9, 2014. http://www.nytimes.com/2014/02/09/opinion/sunday/the-case-for-a-higher-minimum-wage.html

Edwards, Richard C., Michael Reich, and Thomas B. Weisskopf 1972. The Capitalist System: A Radical Analysis of American Society. Englewood Cliffs, N.J. Prentice-Hall, 1972.

Neumark, David, David, J.M. Ian Salas, and William Wascher 2013. “Revisiting the minimum wage-employment debate: throwing out the baby with the bathwater?” National Bureau of Economic Research Working Paper 18681 (January, 2013). http://www.nber.org/papers/w18681

[1] Technically, classical hypothesis testing cannot confirm a hypothesis.  Hypotheses can only be rejected or not rejected.  Shout out to Prof. Michael Hurd who drummed this into my head quite a few decades back.

# The Minimum Wage Again

In today’s New York Times Magazine (December 22, 2013) author Annie Lowrey argues in favor of raising the minimum wage. I will present fairly detailed rebuttals shortly, but one paragraph can save you a bit of reading:

The Times is just plain wrong.  The true minimum wage is zero.  That’s what you make when you lose your job because the minimum wage was raised.

Raise the minimum wage to \$50!

### Work Cited by Ms. Lowrey

Ms.Lowrey refers to a single paper, the infamous “study” done by Alan Krueger and David Card when both were at Princeton.  That work has been discredited almost since the moment it appeared.

She also quotes Michael Reich, a “professor of economics at the University of California, Berkeley.”  She failed to add that Dr. Reich is also the Director of the Institute for Research on Labor and Employment, a well-known organization that shills for unions. He is a co-author of The Capitalist System: A Radical Analysis of American Society. His partners in this project were Richard C. Edwards (Author) and Thomas E. Weisskopf (Editor).

Prof. Evsey Domar of M.I.T. published a scathing review of this work in the Journal of Political Economy (Vol. 82, No. 6, Nov. – Dec., 1974, pages 1301-1313).  An excerpt from that review is at the end of this article.  I will just add that, if anything, citing Krueger, Card, and Michael Reich makes me more likely to believe raising the minimum wage reduces employment.

One of the most difficult facts of life for people to accept is that demand curves slope downward.  When you raise the price of something, a smaller quantity will be purchased.  This has been confirmed in millions of empirical studies.  Yet when it comes to the labor market some economists — albeit self-styled economists — throw out centuries of economics research and engage in magical thinking.

How the Minimum Wage Actually Works

### Review of My Previous Articles

I’ve written about the minimum wage before (click here and here).  I’ll just repeat a few facts here.

Raising the minimum wage reduces employment.  In a survey article, David Neumark and William Wascher (National Bureau of Economic Research, Inc, NBER Working Papers: 12663, 2006) summarize the results of 102 empirical studies of the impact of the minimum wage on employment. These studies were all done after 1990.  To economists that means the studies were done carefully and correctly using the appropriate statistical techniques.  Of the 33 studies the authors selected as being the “most credible” 85 percent found a significant negative impact of a higher minimum wage on employment.  William Even and David Macpherson have also published an extensive study that focuses on the impact on members of the labor force between 18 and 24 who are not high school graduates.  They looked at a sample of about 600,000 males between 16 and 24 years old without a high school diploma.  They examine the impact on three groups: whites, Hispanic, and black. Among white males in this group, the authors find that each 10 percent increase in a federal or state minimum wage decreased employment by 2.5 percent; for Hispanic males, the figure is 1.2 percent. But among black males in this group, each 10 percent increase in the minimum wage decreased employment by 6.5 percent.  (No, this is not evidence of racism. The job choices made by each of the groups account for most of the differences.)

### Conclusion

Perhaps the Times should talk to some real economists the next time they decide to write about economics.  Instead, they persist in finding economists with views that match the writers’ and editors’ world views.  Which makes the Times even more of a joke than it is already.

Excerpt from Prof. Domar’s Review

This is from pages 1302-1303:

“An analysis of capitalism, like any analysis, can be expected to consist of two parts: first, a logical formulation of a hypothesis showing how this or that evil is caused by capitalism; and, second, an empirical testing of the hypothesis against the reality of capitalist and noncapitalist systems. There is no shortage of logical formulations, of different degrees of plausibility, in the book. But there is almost a complete absence of empirical verification. Since the evils are both complex and not easily quantifiable, the authors (that is, the editors and the contributors) could not be required, at least at this stage, to come forth with a battery of regression equations, but surely, as a first step, they could have made an attempt to examine historical trends and to establish the presence or absence of each evil in other capitalist and noncapitalist countries. In particular-most fortunate for this attempt-there are now several socialist countries, some of them quite advanced and most of them sharing our common cui tural background. On one of them-the Soviet Union-there exists a large literature in English, while the others have not been neglected either.

But no comparisons of any importance are made in the book. We discover that there is not a single socialist country in the world! The Soviet Union and the other East European countries are referred to as “state socialism” (pp. 4, 277, 281, 362, 524-25) or as “so-called socialist” (p. 277). They are treated with disdain and together with the state-capitalist countries (England, France, or Sweden) are declared not to be “model societies of socialism to be emulated” (p. 4). Worse than that, “The state socialist countries of the Soviet Union and Eastern Europe are to true socialism what ‘the monsters of the paleolithic era are to present animal species: clumsy, abortive, prototypes”‘ (p. 4).

If countries which have been regarded by themselves and by others to be socialist have turned out to be so1nething else, surely an explanation is in order. Since none is provided in the book, let me suggest two alternatives. Lenin, Stalin, and, by implication, all other socialist leaders-including Tito and Mao–never intended to build socialism. (2) They did try, but failed miserably, ending up with “Paleolithic monsters,” in fact.

I will leave the choice and the consideration of the sad implications of each alternative to the reader.”

# The Times Has Discovered That Costs Matter in Obamacare

Designing Obamacare by Henry Payne (http://townhall.com/political-cartoons/henrypayne/2013/10/18/112967)

Today’s New York Times includes a front-page article that left me gasping with a combination of laughter and indignation. Apparently the Times has discovered that costs matter in Obamacare.  Here’s the headline and the link:

“New Health Law Frustrates Many in Middle Class”

The long article includes this little gem (emphasis added):

“The Chapmans acknowledge that they are better off than many people, but they represent a little-understood reality of the Affordable Care Act. While the act clearly benefits those at the low end of the income scale — and rich people can continue to afford even the most generous plans — people like the Chapmans are caught in the uncomfortable middle: not poor enough for help, but not rich enough to be indifferent to cost.”

Perhaps this was “little-understood” by the geniuses who run the New York Times. But many economists, including me, pointed out that costs and prices would inevitably rise given the mandates and rules included in Obamacare.  It would sure have been nice if the Times editors and reporters had paid some attention to us.  Instead we were belittled as “Republican fear-mongers.”  Except it turns out we were right.  The very least the Times could do is ask each of these families who they voted for in the last presidential election.

Thanks a lot, mainstream media.  I hope you’re happy with the disaster you’ve imposed on a once-great economy.