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).

Low effective rate not an argument against corporate tax cut

Copyright, TheHill.com

President Trump says that U.S. corporations face the highest tax rates in the world, whereas opponents of his tax reform say that “actual” corporate tax rates are in line with other countries. What gives?

The president is referring to the rate that applies to taxable corporate income, known as the “statutory rate.” The federal statutory rate is 35 percent, and the combined federal-state corporate rate is typically about 39 percent. This rate is greater than anywhere in the industrialized world.

But the statutory rate does not apply to all of the income-generating activities of corporations, because some of those activities create deductions that can be subtracted from business income for corporate-tax purposes.

Debt-financed activities are a good example, because the income they generate goes corporate-tax free to the extent that it can be distributed to investors as interest income.

Intellectual property investments are another example, because they are not obviously attached to a physical location, thereby helping accountants assign their returns to Ireland and other low-tax jurisdictions.

As a result, corporations are paying less than 39 percent of their income to state and local treasuries. The Government Accountability Office estimates 17 percent, which it calls the “effective rate.”

It might seem that the 22-percentage-point difference results in a free lunch for corporations at the government’s expense. But the opponents of corporate tax reform are mistaken to ignore the fact that the corporate tax has corporations paying a lot more than the checks they write to government treasuries.

The Internal Revenue Service (under the Obama administration) estimated that corporations and partnerships pay over $100 billion annually in complying with business-tax laws, including their costs of recording, keeping and hiring paid tax professionals. Compliance costs are not checks written to the government, but are real costs nonetheless.

In fact, the high compliance costs are a symptom of the low effective rate because business-tax deductions are a complicated enterprise. Corporations are paying for some of their 22-point savings in terms of the extra compliance costs that come with complicated tax strategies.

More important, our economy is less productive because taxes have induced investors to pursue tax-favored activities beyond what value creation would dictate. The most vivid example is the housing sector, where returns have been depressed by a factor of two or three because those returns are essentially tax free.

In other words, by having so many deductions, the corporate tax involves a substantial hidden tax on businesses beyond what they pay the government, with the extra payment in terms of lost income.

The chart below illustrates by splitting the economy into two kinds of activities: those that pay full tax and those that are tax favored.

If nobody adjusted their investment plans, the tax-favored activities would be a great deal — they would earn the amount up to the dashed line and owe no tax. But there is no free lunch. The tax favors induce investors to engage more in those activities.

Their movement depresses the income accruing there — otherwise nobody would be willing to do the activities subject to full tax. The chart illustrates this by showing how the income ultimately earned has been depressed enough so that the net-of-tax earnings is the same for both types of activities.

The low effective corporate tax rate is therefore not an argument against President Trump’s call for tax reform. That low rate is further evidence of the economic damage done by the tax, as businesses pay to comply and pay by accepting comparatively low-return investments.

Because the effective rate only counts costs in the form of payments to government, a low effective rate is telling us that cutting the corporate tax will benefit economic performance far more than it will cost government treasuries.

Does Communism have a universal constant? From the October Revolution to Bernie Sanders

To acknowledge the 100th anniversary of the Russian revolution, I have assembled data -- from Holmes (2009), Pipes (2001), Fontova (2013), and others -- on Communist regimes that lasted more than 5 years.

[Communists] openly declare that their ends can be attained only by the forcible overthrow of all existing social conditions. Let the ruling classes tremble at a Communistic revolution. The proletarians have nothing to lose but their chains. They have a world to win. Working men of all countries, unite!

The Communist Manifesto.

(1) The chart below counts Communist state killings -- war deaths not included -- of its own people by purge, massacre, concentration camp, forced migration, famine, or escape attempt.

The counts are expressed as a percentage of population. 6% is a typical result.

You might say, "94% of people survive Communist regimes." But that's a lot less than the percentage of people who survived history's major tragedies. The U.S. Civil War was especially deadly, but "only" killed 2% of the population and, unlike the 6% above, this counts war deaths (civilian deaths were more like 0.2%). AIDS/HIV killed "only" 2% of Africa's population.

(2) Facts about Communist results are not part of the standard training in economics. Indeed, as recently as 1989, they were denied by some of our best and brightest. E.g., Samuelson and Nordhaus' best-selling textbook asserted "the Soviet economy is proof that, contrary to what many skeptics had earlier believed, a socialist command economy can function and even thrive."

(3) Another example: this year's New York Times commemorated the Russian revolution with fantastic claims such as "Women had better sex under socialism." That article shows a photo of a smiling woman on "a collective farm near Moscow" without mentioning how the Communist system left women and men so malnourished that their bodies no longer functioned normally. Take a look at the birth rate in Ukraine under Stalin:

. 

Click here for a similar picture for China under Mao.

(4) The above are examples of the intellectual class indulging their fantasies about the effects of apparently well-intentioned public policies. But the more general phenomenon was that results were suppressed, both outside and inside the Communist countries, because they were unpleasing to those in power.

(5) Disastrous results can more easily become public when there is competition both in the media and in the public sector. Obviously the Communist regimes operate in a one-party system. But even in our political system, the competition is far from perfect, and both media and state officials sometimes work together to attract attention away from negative results.

It is not so easy to have a government that tightly controls economic resources, but is unable and unwilling to exercise control over ideas. 

Perhaps even Senator Bernie Sanders, who has admired more than one Communist regime and insists that government should freely provide everything from health care to college to housing, might now notice as much: his presidential campaign was one of the most recent victims of the Party Line and political collusion.

Stanford University findings on the ACA and the labor market

Stanford Economics Professor Mark Duggan was quoted as concluding that

"While the Affordable Care Act had a significant effect on health insurance coverage, it did not have a substantial effect on the U.S. labor market as many had expected" and

"the Affordable Care Act has not had the negative effect on jobs the law’s critics claimed it would."

He was referring to a working paper distributed by the National Bureau Economic of Research, which states that

“labor market outcomes in the aggregate were not significantly affected.”

Theirs is a working paper and I'm sure that the authors are eager to add data and analysis, so I understand the above conclusions to have been modestly offered. With that said, it is worth recognizing that the above conclusions are not what the working paper shows.

1. Table 4 (the paper's first table on labor market outcomes) shows that the ACA reduced nationwide labor force participation by 349,190 in 2016, plus however much the ACA reduced labor force participation in a geographic area that was fully insured before the ACA, which I call the HFIA (Hypothetically Fully Insured Area).  This effect is economically significant and, when combined with items (2) and (3) below, is easily in line with "the negative effect on jobs that the law's critics claimed it would be."

   [Admittedly, the 349,190 is probably not statistically significant by the usual criteria, but the quotes above are not claiming that either side could be correct. Rather they claim to decisively reject "critics" who made claims right in line with the Duggan-Goda-Jackson point estimate. See below for the derivation of the 349,190]

2. The paper assumes, without much explanation, that the HFIA part of the ACA's impact is zero.  But other work has shown that near-elderly insured people were given a tremendous incentive to retire early.  In other words, basic economics tells us that the HFIA part is likely positive (i.e., in the same direction as the 349,190) and we should not assume it to be close to zero until we have further measurement.

3. The empirical methods in the paper, which emphasize differences among geographic areas such as Medicaid expansion states versus other states, are not designed to detect effects of the employer penalty.  The employer penalty is the same amount throughout the nation.  The penalty creates large labor-market distortions; those distortions that have been measured in other studies have proven to be similar across geographic areas.  Moreover, the employer penalty did not apply until the 2016 coverage year, whereas 8/9 of the working paper's data is before that date. This is an especially serious problem for the low-income population, where the employer penalty in effect has them working 50-60 days per year for the government, on top of the implicit and explicit employment/income taxes they would pay even without the ACA (this fact is nowhere mentioned in the paper). For this reason, the authors' claim than that "lower income individuals were actually incentivized to work more" is especially incredible.

To derive the 349,190, look at the first "Out of the labor force" column of that table.  The first row says that the M variable reduces out of the force by 0.0847 on average for each working-age person in the U.S.  The second row says that the E variable increases out of the labor force by 0.0962.  The mean of the M and E variables are, respectively, 0.073 and 0.086 (p. 11 of the paper). So, relative to the HFIA, their regression says that the U.S. has increased out of the labor force by 0.0021 per working-age person:

0.0021 = 0.073*(-0.0847) + 0.086*(.0962)

To get a number of people, multiply by the number of working age people (difference between these two), and you get 349,190.