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).
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