Michael T. Maloney: A Few Memories

Michael T. Maloney passed away this week. We both loved applied price theory and golfed to the exact same handicap.

We both liked sailing too and together sailed around Long Island in less than 24 hours. He frequently asked why we had to spend so much time scouring the ocean for our competition. To this day I don’t know how to answer this question coming from a first-class IO economist, but perhaps he did not want to imitate Ahab too much.

I wish to find better pictures (Skip has several on facebook) but here we are crossing the starting line first in 2011. Below we are about half way down the island on the ocean side.

Our 2011 corrected finish time was the best in that year’s fleet (and many other years’ fleets). We (Mike and me and 2 others) especially liked beating the two U.S. Navy college teams, which had crews of a dozen each, larger boats, and of course government money.

We almost lost Mike a few years ago when he parked in front of his house, went inside, and minutes later saw his Suburban completely crushed by the falling of a large tree.

An indicator of both how he viewed economics as a unified field and how much he enlivened his department is the number of colleagues who published articles with him despite coming from different subfields. Bobby (McCormick), Skip (Sauer), Bob (Tollison), Bruce (Yandle), Bentley (Coffey) and Matt (Lindsay), to name a few. Also many Clemson students.

Mike was particularly saddened when Matt Lindsay passed away in 2015. I hope they are together again.

Updates on Parler's War with Big Tech

Amazon turned off Parler’s servers last night, disconnecting Parler.com from the internet, and with it the social media accounts of almost 20 million people.

Parler CEO also reported (yesterday AM on Fox Business) that attorneys, email, and other suppliers are refusing to supply his company.  Although he said that transferring the company's software and data could be done in about 12 hours, today he wrote that "We will likely be down longer than expected" because of the time it takes to find vendors who are willing to supply the company.  Parler investor Dan Bongino said today that "Parler will be back by the end of the week."

The Jan 6 violence and lawbreaking was reportedly organized on Facebook, but Facebook continues uninterrupted.

I estimate that Parler has 20 million members (no bots), as compared to less than 60 million US accounts on Twitter.

This outrageous situation is best handled by the market, without government interference.  To the 20 million people temporarily disconnected, I say: do not be gullible enough to think that government bureaucrats or politicians represent your interests any better than the big tech employees.  Many of them have built followings on incumbent social media and do not want to work to build that again.  Any new regulations for social media will be written by allies of the incumbents.

[This is not an official Parler communication.  I have no financial interest in Parler.]

Is the Grand Canyon Just a Ditch?

[Originally posted at economics21.org]

The myriad deregulatory actions of the Trump administration are generating considerable cost savings, savings that even conservative critics of regulatory overreach are underestimating. Like the Grand Canyon, the vast scale of these deregulatory efforts (and their results) is hard to fathom.

In just three years the administration has reversed hundreds of regulations, many of which drone on for hundreds of pages. And it’s done so without fear or favor. Many of the regulations reversed had been written and implemented at the behest of special interests, including large banks, trial lawyers, major health insurance companies, big tech companies, labor unions, and foreign drug manufacturers. 

Even officials within the administration underestimate what has been achieved because they tend to grasp only their specific part of the overall picture. Still, I’ve been surprised to see a group of conservatives confidently conclude that the Trump administration “has achieved little” on deregulation. This, sadly, is akin to a human being encountering the immensity of the Grand Canyon only to conclude that it is “just a ditch.”

The daily grind of repealing excessive regulation does not always grab headlines. I don’t blame commentators for being unaware of some, or even most, of the deregulation that has occurred. That is why the Council of Economic Advisers (CEA)—where, until recently, I served as chief economist—dedicated a great deal of manpower preparing a comprehensive and rigorous assessment of deregulation since 2017. That report, released in June, concluded that the past three years of deregulation is comparable to, and probably exceeds, any deregulatory episode in modern U.S. history. That includes the historic deregulations of airlines, trucking, railroads, and energy that were initiated during the Carter administration.

Argue with the CEA report, if you want. Or read David R. Henderson’s summary of the report. But don’t claim that the Grand Canyon is a just a ditch until you have a cursory look at the CEA’s map.

The CEA began with the surprisingly difficult task of identifying the deregulations that were reducing household and business costs the most. You would think that government numbers could be used to make this assessment, but they are notoriously inaccurate. A Competitive Enterprise Institute study of the 53,838 federal rules finalized between 2001 and 2014 found that only 246 of them (less than 1%) quantified regulatory costs. Lurking in the other 53,592 are some very costly regulations to be discovered by some other method.

Instead, the CEA selected the top 21 regulations based on measures of attention from the public, as expressed by actions in Congress or comments submitted to the regulatory agency during the regulatory process. The CEA then performed a rigorous economic analysis of the selected regulations to estimate their costs and benefits. The arithmetic motivating this procedure is that a sum of the hundreds of costs savings (the entire deregulatory portfolio) is made up largely by the elements of the sum of cost savings from the regulations with the largest costs.

The attention metric led to some interesting discoveries. Take the 2016 prohibition of “junk” health insurance plans (i.e., plans that families like and purchase, in large part because the plans are cheaper than the plans endorsed by bureaucrats) that the Trump administration reversed in 2018. Whereas the typical regulation receives zero comments, this one received thousands. At the same time, the regulators assessed no cost for the rule because the rule was (with a bit of circularity) designated to be “economically insignificant.” Such designation is not supposed to be used unless there is no material adverse effect on a sector of the economy. It is absurd to deny any material adverse effect from a prohibition of a product that two million people would be purchasing (as estimated by the nonpartisan Congressional Budget Office). The CEA estimated that the annual cost of this regulation was $13 billion, which is 130 times the monetary threshold for “economic significance.”

It’s hard to understand the intention of the regulators who designated the rule to be “economically insignificant.” Were they unaware that the rule was getting thousands of comments? Did they think that people bothered to comment on something insignificant? Was it a technical error? Or was it a deliberate attempt to jam through a regulation without revealing much about its costs? Regardless of which answer is correct, we have yet another reason to doubt the cost estimates provided by regulatory agencies.

A similar phenomenon is revealed in the chart below, reproduced from another CEA report on prescription drug prices. It shows something historically unusual happening to prescription drug prices, as measured by the Consumer Price Index calculated by the Bureau of Labor Statistics. Much of the change has to do with deregulation of the entry of generic drugs. The Food and Drug Administration had such a burdensome approval process for generic manufacturers that in some instances only one company was making a generic. A handful of lucky, or well connected, companies were able to sell a drug they did not invent at a price about as high as that charged when the inventor held the monopoly. President Trump’s FDA changed that.

Figure 1 CPI for Prescription Drugs, Jan 1970 to Sep 2019. Source: CEA October 2019.

A little arithmetic helps to assess orders of magnitude (CEA calculations are much more detailed). If prescription drug prices had continued to increase at 4% per year after 2016, that would put them 8% higher after two years. In fact, after deregulation, they fell about 2% over two years, and therefore were roughly 10% below the previous trend. With the average household spending about $2,700 annually on prescriptions—including the taxes they pay to support government programs purchasing prescriptions—that is an annual savings of $270 per household.

These examples, repealing the costly regulation of generic drugs and health insurance, are but two of many such efforts by the Trump administration since 2017. This paragraph, from the CEA report’s conclusion, gives a sense for the broad swath of deregulation:

Since 2017, consumers and small businesses have been able to live and work with more choice and less Federal government interference. They can purchase health insurance in groups or as individuals without paying for categories of coverage that they do not want or need. Small businesses can design compensation packages that meet the needs of their employees, enter into a genuine franchise relationship with a larger corporation, or seek confidential professional advice on the organization of their workplaces. Consumers have a variety of choices as to less expensive wireless and wired Internet access. Small banks are no longer treated as “too big to fail” (they never were) and subject to the costly regulatory scrutiny that goes with that designation.

All told, the CEA report estimates that over the next five to 10 years, the deregulatory efforts of the Trump administration will increase annual real incomes in the United States by $3,100 per household. 

That’s no ditch. 

Economic Theory in the White House: The Rebate Rule

The "rebate rule" was proposed by the Dept. of Health and Human Services (HHS) in February 2019.  It would have prohibited rebates in the Medicare Part D prescription drug market.  Chicago Price Theory was intensively used in the White House to project the effects of the rule on market outcomes and the distribution of surplus between senior citizens, taxpayers, and firms at various positions in the supply chain.

HHS described rebates as follows "Prescription drug manufacturers prospectively set the list price ... of the drugs they sell to wholesalers and other large purchasers. Manufacturers also retrospectively pay PBMs or other entities in the drug supply chain, under rebate arrangements, that meet certain volume-based or market-share criteria." (84 FR 2340)  The Part D rebates alone exceed $30 billion per year and this rule by itself was projected to increase the Federal deficit by about $20 billion per year, which is historic as a single regulation.

This proposal to eliminate rebates was obviously controversial, as reported in the news and evidenced by the facts that the rule was proposed, received almost 26,000 comments from the public, and then this Thursday was withdrawn by HHS.  The proposed rule was complicated because it was a vertical (business-to-business) price control in a market that already has nonlinear pricing, nonlinear and interdependent government subsidies, and longstanding price regulations of various kinds.  The President himself described the rule as requiring a 193 IQ in order to understand its effects:

But prescription drugs, look, it's a rigged system, OK, if I told you how crazy it is, the Web, it's the Web, you need 193 I.Q. to even understand.  This web of geniuses, they put this thing to lower drug prices. It has 19 effects here and 27, so we got it down and we're getting it down further. We have the smartest people, the best people in that world working on it.... (President Donald Trump April 27, 2019, Green Bay WI)

[other of the regulations discussed in that speech were analyzed with Chicago Price Theory too.  Several dozen parts of other CEA reports draw closely on specific pages of Chicago Price Theory].

I agree that it would be essentially impossible to understand the economic effects of this rule in a timely manner without the extensive assistance of Chicago Price Theory and Automated Economic Reasoning. An important tool for analyzing nonlinear pricing is affectionately known as "the Murphy football" among Chicago economics students (and I associate with this Klein and Murphy article about competition with nonlinear pricing; see Chapter 5 and Chapter 13 of the text).

The football picture shows, among other things, the distinction between list price and net price (i.e., list minus rebate), but in order to prevent revealing too much of the answer to one of the new book's homework problems, I show it in more abstract form below.

For the same reason, among others, I will not say what was CEA's projected impact of the rule.  But take Chicago Price Theory and perhaps you can join the "web of geniuses."

There is no other textbook that teaches the "Murphy football."

There is no other textbook that brings its students so immediately to rigorous and timely policy applications of economic theory.

Monopolies are unhealthy, but high taxes make the disease worse

Copyright, TheHill.com

Taxes are necessary to fund worthy government activities, but taxes come with side effects. The side effects can be especially harmful in an economy where businesses enjoy monopoly power.

People and businesses individually attempt to reduce their tax burden by doing less of the activities taxed at high rates and more of the activities tax at low rates or by doing activities that aren't taxed at all.

If the primary activities hit with high rates were unpleasant -- pollution is an example -- then thankfully taxes would not only bring revenue to the treasury but also induce people to pollute less.

However, most of the objects of taxation are labor and capital, which are not intrinsically undesirable the way pollution is. The reduction in labor and capital, and ultimately national income, by taxes is a regrettable side effect.

The size of government is ultimately a along the tradeoff between reducing side effects and obtaining tax revenue. 

Former Obama-administration economists, and New York Times economist Paul Krugman, have recently decided to treat corporate income as a kind of pollution that is supposedly a source of tax revenue without adverse consequences. They are confused about how monopolies work. 

We all agree that a real problem with monopolies is that they may charge too much, owing to the fact that by definition they have little concern that a competitor will outbid them. But charging high prices is equivalent to producing too little, because customers' natural reaction to high prices is to buy less.

So the problem with monopolized industries is that they produce too little, and with their lower production levels, they ultimately have less need to hire labor and capital. Taxing monopolies only worsens their low usage of labor and capital. In this way, monopolies are the opposite of pollution.

A second feature of monopolies is that everybody wants to own one! The result is a competition for the ability to have a monopoly. Sometimes this feature of competition for monopoly rights only adds to the problem, as when businesses compete to convince government officials to grant them monopoly power.

Other times, businesses and individuals compete to invent a new product that they can successfully monopolize. Yes, it's too bad for the consumer that the new product costs so much -- that's the first feature of monopoly noted above -- but that's better than having no product at all. Taxing the profits of innovators discourages innovation.

An important aspect of taxing monopoly profits is therefore to understand how the monopoly rights are attained and who benefits from the competition for rights. Certainly, the headline "monopolists" of today, like Facebook, Google, Apple, etc., got their monopoly rights from socially valuable innovation and not government favors.

Are we sure that we want to discourage the next generation of innovators?

None of this is to say that monopoly is a sign of a healthy economic system. It's just that taxes probably make the disease worse. A time of rising monopoly is the time for tax cuts, not increases.

NYTimes Packs Five Ungrounded Economic Opinions in Two Sentences

Some misconceptions about tax incidence have been getting a lot of press, but Paul Krugman's column from last week is particularly efficient at perpetuating them:

"How much of a trickle-down effect depends on a bunch of technical factors: what share of corporate profits represents monopoly rents rather than returns to capital, how responsive inflows of foreign capital are to the U.S. rate of return.  Enthusiasts claim that the tax cut will eventually go 100% to workers; most serious modelers think the number is more like 20 or 25 percent."

Of course I am not a "serious modeler", but let's break this down:

1. "Enthusiasts claim that the tax cut will eventually go 100% to workers"

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Actually, the White House Council of Economic Advisers, I, and anyone else using the standard supply and demand model claims that MORE THAN 100% of the tax cut will eventually go to workers. The analysis is in pdf here and executable Mathematica notebook here.

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2. "what share of the capital stock is even affected by the corporate tax rate"

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This extension of the supply and demand model only strengthens the conclusion, because now workers not only have to pay for the revenue received by the treasury and for the productivity lost due to less aggregate capital, but also the productivity lost due to the misallocation of capital between activities covered by the statutory corporate rate and activities not covered. The analysis is here. Perhaps the proponents of this argument are thinking that the tax does less damage when it covers less capital. Maybe, but for sure it brings in less revenue too, and Krugman is referring to damage as a percentage of revenue.

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3. "what share of corporate profits represents monopoly rents rather than returns to capital"

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Krugman and the others do not give any citation to "serious modeling" of monopoly rents (monopoly rents = free lunch is not a serious model by any definition). But it looks to me that adding monopoly rents to the model also strengthens the conclusion, because now workers not only have to pay for the revenue received by the treasury, the productivity lost due to less aggregate capital, the productivity lost due to the misallocation of capital, but also exacerbation of the productivity lost due to monopoly. The analysis is here and in the links therein.

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4. "how responsive inflows of foreign capital are to the U.S. rate of return"

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This is a red herring. All of the models that I have cited make the assumption most charitable to Krugman's conclusions: namely that foreign capital inflows are completely unresponsive (they are closed-economy models!). Nevertheless, they conclude that labor pays more than 100 percent of the corporate-income tax.

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These counterintuitive results, and many more, are treated in the forthcoming Chicago Price Theory textbook by Sonia Jaffe, Robert Minton, Casey B. Mulligan, and Kevin M. Murphy.

Corporate-income Tax Incidence with Imperfect Competition

Summary: Labor Losses in an Economy with Imperfect Competition May Be Even Greater than Labor Losses in a Perfectly Competitive Economy, Which Themselves are Sizable

Two kinds of distortions are both important and easy to handle in the standard models of capital taxation: the distortion in terms of the total amount of capital and the distortion of the distribution of capital among activities that are differentially taxed.  In the long run, the deadweight loss of these distortions and other distortions comes entirely out of wages.

Raising the corporate-income tax rate adds to the total-capital and capital-composition distortions.[1]  Therefore wages are reduced more in the long run than revenue is enhanced (if at all).  In other words, labor pays more than 100 percent of the corporate-income tax.

But proponents of corporate-income taxation have asserted that, not withstanding the above, labor is scarcely harmed by the tax because of the prevalence of “monopoly.”  If such assertions are to be taken seriously, they need to be accompanied by some more detailed economic reasoning, which is provided below.

The abbreviated version is this: if policy goals (e.g., fighting monopolies) are pursued with oblique policy instruments (e.g., the corporate-income tax or, in New-Keynesian fashion, monetary policy), then unintended consequences abound.

Market Power is Uneven

Any reasonable view of market power has to acknowledge that market power is uneven: that industries, regions, etc., have different percentage gaps between price and marginal cost; between factor prices and marginal products.  If market power is important, then even a low-rate corporate-income tax likely adds significantly to already existing distortions because the tax-free economy is not well approximated as first best (in terms of the amount of capital or its composition).[2]

Rent Seeking: People Like Profits and Will Pursue Them

A third type of distortion has to do with rent seeking, which refers to activities that people and businesses do to obtain market power or government favors.  These include advertising, inventing new products, merging businesses, or lobbying public officials.

A number of factors determine the direction of the effect of corporate taxation on the deadweight losses associated with rent seeking (hereafter, DWRS).  One is whether the social return to rent seeking exceeds the private return.  Arguably inventing new products or merging businesses could benefit consumers beyond its benefit to the businesses taking these actions. One element in the rent seeking calculus is therefore to quantify the gap between social and private return.  The gap may well be negative, but it is usually too extreme to assert that all rent seeking is a waste.

The second element is the direction and magnitude of the effect of the corporate tax on rent seeking.  Are corporations more rent-seeking intensive than noncorporations?  Are corporations able to deduct their rent-seeking efforts from income for the purpose of determining their corporate-income tax liability?  Will the extra treasury revenue itself motivate socially costly rent seeking to influence how it is distributed?  This last point is particularly important because, in the neighborhood of a zero tax rate, the corporate tax creates far more tax revenue than it destroys rewards to monopoly (at large tax rates, see below).

These are all reasons why a higher corporate rate could encourage rent-seeking.[3]  To the extent that the corporate tax encourages rent seeking in some instances and discourages it in others, we need to know the net effect, weighted by the social benefit or damage associated with each instance.

With all of these factors determining the DWRS, we cannot rule out the possibility that corporate taxation adds to DWRS and therefore adds to the amount that the tax reduces wages as compared to the amount it would reduce wages in an economy with no rent seeking, which itself is in excess of the amount of revenue obtained from the tax.  If so, we can conclude even more confidently that labor pays more than 100 percent of the corporate-income tax because all three types of deadweight loss are adding to the tax’s burden on labor (a specific and rigorous demonstration is here as pdf and here as executable Mathematica notebook).

An interesting and ironic case is when rent seeking is labor-intensive, or otherwise deductible from the corporate income tax.  Here the corporate tax encourages rent seeking by reducing the price of rent-seeking inputs.  Ironically, if you use monopoly as a pejorative term, then you have to acknowledge that yet another cost of the corporate-income tax is wasteful rent seeking.  On the other hand, if you think that monopoly rents motivate socially valuable R&D, then one of the benefits of the corporate tax is that it encourages that R&D (but see my advice below on using less oblique policy measures).

A Proper Tax-Incidence Formula Does Not Merely Enter the "Monopoly Profit Share" as a Subtraction

The amount of DWRS is related to the amount of rents to be sought, which we might roughly describe as the “share of corporate profits that represent monopoly rents.”  The amount would be small if there are few rents to be had.

In contrast, the amount of the other two deadweight losses (capital amount and composition) depends on the level of the tax rate.  At high tax rates, the capital amount and composition dominate DWRS, and labor is paying more than 100 percent of the corporate-income tax at the margin.

Note that even if the corporate-income tax reduces DWRS more than enough to offset what it adds to the other two deadweight losses, that does not mean that labor benefits from the tax.  It means that labor pays less than 100 percent of it.  Moreover, for the reasons cited above, simply subtracting the monopoly-rent share in a tax-incidence analysis is a wild exaggeration, if not directionally incorrect, of how the true incidence differs from simpler models that have no DWRS.

Advice: Forgo Oblique and Uncertain Policy Instruments

Perhaps most important, the deadweight costs of capital amount and composition are direct consequences of the corporate tax.  In contrast, the benefit, if any, of corporate taxation coming through DWRS is indirect and uncertain, and presumably we could do better by attacking these problems more directly with antitrust enforcement, policing election fraud, supporting well-designed systems to encourage the supply of intellectual property, etc.

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[1] The capital-composition distortion could in principle get better if (a) the non-corporate tax rate were sufficiently greater than the corporate rate and (b) little of the corporate activity could avoid the tax (e.g., through loopholes).

[2] We might get lucky that the corporate tax falls on the sectors that already have too much capital and sales, although the assertion that the corporate sector is full of monopolies suggests the opposite (the usual complaint about monopolies is that they charge too much and produce too little).  There is also the concern that the corporate tax falls on sectors that are labor-intensive (Harberger 1962) thereby depressing the aggregate demand for labor even beyond its effect on the capital stock.

[3] Arguably the people and businesses most productive at rent seeking have already obtained tax exemptions for themselves, so that raising the tax rate only encourages more exemption seeking.

Your job cannot be automated? Then you need to worry!

Copyright, TheHill.com

One of the greatest labor force changes of the 20th century was the movement of workers out of farming. In 1900, more than two out of five workers were in agriculture. Now it is less than two workers out of every 100.

It's not that people stopped eating. Rather, farm machinery and innovation increased the amount of food that could be produced per farm worker by more than a factor of 10. Food got cheaper and that got people to buy more food, but not 10 times as much. The end result has been fewer jobs in agriculture.

Automation is expected to come to other industries and occupations, and it is tempting to forecast less employment for them too. A variety of studies are using engineering information to determine which jobs will be automated next.

While automation may be a question of engineering, job loss is even more a question of economics. A key part of the agriculture story is that people were unwilling to purchase all of the food that farmers were capable of producing, even though food was getting cheaper. But not all industries share this with agriculture. 

Suppose that the automation in agriculture had only been for chicken farming and not for any other food production. Chicken would have gotten cheaper relative to beef, fish, vegetables, fruit, etc., and that would have caused people to buy more chicken and less of other types of food.

Many -- even most -- of the extra chickens produced would have been purchased by consumers, and there would have been less need to reduce employment in chicken farming. 

The most dramatic job losses would have occurred in the food industries like beef and fish that were not automated and that compete with chicken. In other words, jobs that are difficult to automate from an engineering perspective may be exactly the jobs pushed to extinction by automation because they cannot compete.

It all depends on the competitive landscape and how willing are consumers, encouraged by lower prices, to absorb the extra output made possible by automation.

Trucking is a modern example, because engineers are predicting that machines will soon do a lot of the driving formerly done by trucking employees. But the result may be more jobs for people in trucking and fewer jobs for people in railroads, airlines and shipping that compete with trucking (unless they also get more productive at the same time that trucking does).

Another example has occurred in my own profession: Two or three generations ago, a large fraction of economists were employed manually performing the arithmetic of statistical analysis. Then, computers came along to automate that arithmetic, without really automating the tasks done by theoretical economists.

The result was an increase in the fraction of economists doing statistical work, because universities, businesses and government wanted more statistical analysis when computers made it became cheaper and more accurate. The fraction of economists doing theoretical work fell, precisely because their tasks were not automated.

So the more interesting economic question for a worker is not whether his job can be automated but whether he or she will miss out on automation to occur in the workplace of his or her primary competitors.

The ACA's Employer Penalty is Distorting Business

Taxes and regulations are known to affect the size distribution of businesses, due to the fact that smaller businesses are less subject to enforcement.  Large informal sectors are an obvious result in developing countries, but measurement challenges have hindered quantifying the size distortions’ impact on developed-country employment and productivity.  This paper uses new and unique data that is readily linked to a specific regulation: the 2010 Affordable Care Act’s (ACA) employer mandate.  The mandate’s size provision took effect in 2015 and is especially interesting, not only due to its notoriety, but because of its bright-line threshold and enforcement by monetary penalty.  This paper quantifies the size incentive of that penalty, develops a framework for combining evidence on size with evidence on voluntary compliance, and uses a new survey of businesses to quantify the number of businesses that changed from large to small as a consequence of the law.

The key size threshold in the ACA is 50 full-time equivalent employees (FTEs), which establishes the legal definition of a “large” business that is subject to the employer mandate.  Momentarily ignoring the distinction between FTEs and total employment, I display in Figure 1 a time series of the share of employment by small businesses, by a 50-total-employees criterion, among private businesses sized 25-99.  The data is sourced from the tables prepared by the Agency for Healthcare Research and Quality from the insurance/employer component of the Medical Expenditure Panel Survey. Both the 2015 and 2016 shares are well outside the range observed in the recent history 2008-14, and in the direction to be expected given that large employers were subject to a new regulation.

Garicano, Lelarge, and Van Reenen (2016) show how the distortionary effects of size-dependent regulations appear muted when the observer uses a different measure of size than regulators do.  This is the case in Figure 1, which looks at total employment as opposed to the full-time equivalents specified by the ACA and has total employment binned rather broadly (25-49 and 50-99).  Both Garicano, Lelarge, and Van Reenen (2016) and Gurio and Roys (2014) therefore obtain size measures that are especially close to regulator measures and find large size distortions in the French economy.  They do not link the distortions to specific regulations, but instead focus on France where there are many size-dependent regulations thought to be binding.  One of their estimation methods is to compare the actual firm size distribution to a Pareto distribution and measure the nonmonotonicity of the actual distribution in the neighborhood of the threshold.

The Mercatus-Mulligan data used in this paper has five measurement advantages.  First, it separately measures full- and part-time employment and therefore can produce good proxies for FTEs.  Second, the size distortion can be linked to a specific and relatively new regulation, which permits a before-after analysis as shown in Figure 1.  Third, voluntary compliance – that is, offering employer-sponsored health insurance (ESI) even when exempt from the mandate – can be measured.  This allows the measurement of size distortions to focus on businesses for which the employer mandate is binding.  Fourth, the survey was not conducted at the corporate level and therefore did not require any corporation’s approval to publish results.  Rather, individuals were confidentially surveyed, and these individuals happened to be managers at businesses.  If the sample aggregate happens to reveal politically-incorrect business practices, such a finding cannot impugn any particular business.  Fifth, the managers of the sample businesses were asked whether and how the law changed their hiring practices, with answers that can be compared to size and compliance.

Before-after comparisons between the Census Bureau business survey and the Mercatus-Mulligan survey show little change in the size distribution of businesses between 2012 and 2016, except among businesses in the total-employment range 40-74.  Among the latter businesses, the employment percentage of those with less than fifty employees has increased from 37 to 45, and this does not count the fact that a number of 49ers reduce employment below 50 full-time-equivalent employees (FTEs) without reducing their total employment below 50.  Annual time series from the MEPS-IC show an extraordinary jump in the employment percentage of those with less than fifty employees, beginning in 2015, which is the same year when the large-employer designation began its 50-FTE threshold.

            The size distortion is closely linked with whether a business offers employer-sponsored health insurance (ESI) to its employees.  Even by comparison with businesses employing fewer than 30 full-time workers, the propensity to offer ESI is low among employers with 30-49 full-time employees.  The size of this dip in the ESI propensity indicates the prevalence of 49er businesses: they do not offer ESI and thereby keep employment low enough to avoid the ACA’s large-employer designation.  The cross-section finding is my second and strongest piece of evidence that the ACA’s employer mandate is pushing a significant number of businesses below the 50-FTE threshold.

My point estimate is that the United States has 38,327 49er businesses that collectively employ 1.7 million people.  This translates to roughly 250,000 positions that are absent from 49er businesses because of the ACA, but the Mercatus-Mulligan sample by itself is not well suited for accurately assessing the average number of positions that the 38,327 49er businesses eliminated.  The sample also indicates that businesses continue to adjust their employment over time.  For example, many of them reported that, because of the ACA, they hire fewer workers or at least fewer full-time workers, but tried not to adjust the situations of their existing employees.  If the ACA and its employer mandate remains in place, perhaps the prevalence of 49er businesses will increase over time.

            By definition, the 49er businesses have less than 50 FTEs and do not offer ESI.  But it appears that a majority of them had been offering it in the prior year.  Employers with 30-49 FTEs are also disproportionately likely to report that they hire less or have shorter work schedules because of the ACA.  This is my third finding pointing toward an economically significant effect of the ACA on the size distribution of businesses.  To my knowledge, this is the first paper to find a business-size distortion that is readily visible in aggregate U.S. data.  It is also remarkable that the distortion can be linked to a specific regulation with a precisely known penalty for violations.

            Individual-based surveys of businesses are rarely used in economics, but that is bound to change as the survey industry is becoming more efficient (i.e., cheaper for the researcher).  It is worth noting the contrast between the Mercatus-Mulligan survey design and in-depth studies of a particular business (e.g., (Einav, Knoepfle, Levin, & Sundaresan, 2014; Handel & Kolstad, 2015)).  The former design has the advantage of representing a wide range of industries and geographic areas.  Moreover, this study is not sponsored by any business and therefore does not require a corporation’s approval for its release.  Corporate approval is a concern for studies of a particular business, especially when the topic involves public-relations-sensitive issues such as distorting business practices to lessen the cost of well-intended federal regulations.  Another dividend from using a professional survey research firm is that every respondent completed the survey.

            This paper does not put its estimates into an equilibrium framework. Future research needs to estimate the number of eliminated positions at 49er businesses that resulted in jobs created at businesses that compete with 49ers in product or labor markets.  To the extent that the employer mandate shifts employment from 49ers to other businesses, future research needs to assess the aggregate productivity loss from the shifts, recognizing that the ACA’s large-employer definition is just a vivid example of a more general pre-existing enforcement phenomenon.  Even without the ACA, businesses are taxed and regulated, and understand that adding to their payroll tends to increase the enforcement of those rules, albeit not discretely at 50 FTEs (Bigio & Zilberman, 2011; Bachas & Jensen, 2017).  One ingredient in such productivity calculations would be the number of positions shifted, which I found to be roughly 250,000.

From the equilibrium perspective, another interpretation of my cross-section finding – the nonmonotonic relationship between ESI and employer size around the threshold – is that businesses below the threshold did not adjust their size but merely dropped their coverage, in which case, I have mislabeled them as 49ers.  Indeed, I find that such businesses are disproportionately likely to have dropped their coverage in the past year.  However, this alternative explanation does not by itself explain why (i) so many businesses were added to the 25-49 (total employment) size category, (ii) so few were added 50-99, or (iii) coverage rates are not particularly low for businesses with less than 30 FTEs.

The implementation of the employer penalty in January 2015 coincides with a sudden slowdown in the post-recession recovery in aggregate work hours per capita, with 2016 national employment about 800,000 below the trend prior to the implementation of the employer penalty (Mulligan, 2016).  This paper’s estimates permit us to gauge the aggregate importance of the 49er phenomenon, not counting the marginal employment impact on non-ESI businesses that continue to employ 50 or more FTEs.  If 250,000 positions were the aggregate employment effect of 49ers (see the equilibrium caveat above), that would be about one third of the recovery slowdown.  Perhaps more important would be the social value of those positions, given that employment and income are substantially taxed by payroll, income, and sales taxes even without the ACA thereby creating a wedge between the positions’ social and private values.  If that wedge were $20,000 annually, that would be $5 billion of lost annual social value, plus the usual Harberger triangle, which is 38,327 businesses in the quantity dimension and up to $68,987 annually in the price dimension (about $1 billion annually).

How government employment can undermine democracy

Citizens in a democracy can criticize their government and its laws without government reprisal.  But what happens when your government is not only the enforcer of law, but also your boss?  Your boss, of course, is less willing to have you in his employ if you are speaking out against him.

An example from last weekend:

I spoke to a young woman who was shortly due to sit examinations to become a judge. She thought there was a good chance that her role in assisting the local [Catalan] referendum process would destroy her chances of becoming a judge, and said that one of her fellow students was too scared to even vote for the same reason.

Of course a judge is an occupation naturally in the public sector, but the point is: the more occupations that are pushed from private to public sector (or any huge employer -- but what private organization employs as many as government?), the more people who are unwilling to speak out against harmful government policies.