Health Insurance Benefit Mandates and Firm Size Distribution

• Date: 01 June 2018
• Author: James Bailey,Douglas Webber
• Published date: 01 June 2018
• DOI: http://doi.org/10.1111/jori.12164

HEALTH INSURANCE BENEFIT MANDATES AND

FIRM SIZE DISTRIBUTION

James Bailey

Douglas Webber

ABSTRACT

By 2010, the average U.S. state had passed 37 health insurance benefit

mandates (laws requiring health insurance plans to cover certain additional

services). Previous work has shown that these mandates likely increase

health insurance premiums, which in turn could make it more costly for

firms to compensate employees. Using 1996–2010 data from the Quarterly

Census of Employment and Wages and a novel instrumental variables

strategy, we show that there is limited evidence that mandates reduce

employment. However, we find that mandates lead to a distortion in firm

size, benefiting larger firms that are able to self-insure and thus exempt

themselves from these state-level health insurance regulations. This

distortion in firm size away from small businesses may lead to substantial

decreases in productivity and economic growth.

INTRODUCTION

The U.S. states have passed a large and rapidly increasing number of health insurance

benefit mandates. Benefit mandates require health insurance plans to cover a specific

treatment, condition, provider, or type of person (such as acupuncture, autism,

chiropractor visits, or grandchildren of a planholder). These mandates are likely to

increase health insurance premiums in plans that are forced to add new benefits or

provide additional coverage (Kowalski, Congdon, and Showalter, 2008; Bailey, 2013).

Rising health insurance premiums increases labor costs for employers who provide

health insurance to their employees. Those increased costs could lead employers to

reduce health insurance coverage, wages, or employment. Alternatively, firms can

legally escape mandates and lower their costs by self-insuring if they are willing to

bear the risk of paying employees’ health insurance claims. Due to the nature of the

costs associated with pooling risk, large firms can more easily take advantage of this

loophole. Hence, the passage of health insurance benefit mandates may give large

James Bailey, PhD, is Assistant Professor in the Department of Economics and Finance at

Creighton University, 2500 California Plaza, Omaha, NE 68178. James Bailey can be contacted

via e-mail: jamesbailey@creighton.edu. Douglas Webber, PhD, is Assistant Professor in the

Department of Economics at Temple University, Philadelphia, PA. We thank the Mercatus

Center at George Mason University for funding and helpful comments.

© 2016 The Journal of Risk and Insurance. Vol. 85, No. 2, 577–595 (2018).

DOI: 10.1111/jori.12164

577

firms a competitive advantage relative to small firms. In this article, we use a novel

empirical strategy to determine the extent to which health insurance benefit mandates

affect employment and firm size in the United States.

We make four new contributions to the literature in this article. First, we examine the

effect of health insurance mandates, in general, on employment using recent data.

Previous work examined the effects of a single mandate (Gruber, 1994a; Wolaver,

McBride, and Wolfe, 2003; Lahey, 2012; Bailey, 2014) or a handful of specific mandates

(Meer and West, 2011) or examined the effect of mandates only for the 1990s (Kaestner

and Simon, 2002; Mathur, 2010). This is important because the average number of

state mandates has increased by more than 40 percent from the late 90s until 2010 (our

sample period).

Second, we are the first to show empirically that health insurance mandates can lead

to distortions in firm size distribution. As large firms are more easily able to self-

insure and avoid state-level health insurance mandates, leaving small firms with

relatively higher costs, health insurance mandates give a strategic advantage to large

firms.

Third, our identification strategy takes into account the political forces behind the

passage of mandates, rather than assuming mandates are passed at random as is often

done in the prior literature. We overcome the endogeneity problem by using novel

instruments, that is, the political variables that have been determined to affect the

passage of mandates.

1

Fourth, we use a data set novel to the literature on health insurance benefit mandates,

the Quarterly Census of Employment and Wages (QCEW). These administrative data

from the U.S. Bureau of Labor Statistics

2

have provided employment by firm size and

state for virtually all firms in the United States since 1990. Meer and West (2011) argue

convincingly that most previous work on the labor market effects of mandates suffers

from severe attenuation because of reliance on data sets with high sampling error. The

QCEW avoids this sampling error by using administrative data from the full

population of firms rather than self-reported data from a sample of firms.

We find that mandates do not lead to statistically significant decreases in

employment, but do distort the distribution of firm size by increasing the number

of very large firms (greater than 1,000 workers) and reducing the number of small

firms. Such a distortion may have a negative effect on aggregate productivity and job

growth (Haltiwanger, Jarmin, and Miranda, 2013).

1

In an earlier study, Webber and Bailey (2014) find that states with more doctors per capita

passed more mandates, and states with greater political contributions by health insurers

passed fewer. In this study, we therefore use doctors per capita and political contributions by

insurers as our two instruments for the number of mandates in each state. The 2014 study also

finds that other variables that might be expected to affect the passage of mandates, such as the

political party of the governor and state legislature or the proportion of individuals with

private health insurance, were in fact insignificant.

2

The QCEW is publicly available on the Bureau of Labor Statistics Web Site: http://www.bls.

gov/cew/home.htm

578 THE JOURNAL OF RISK AND INSURANCE