تقاضا برای بیمه سلامت در میان آمریکایی های فاقد بیمه: نتایج یک آزمایش پیمایشی و پیامدهایی برای سیاست

Most existing work on the demand for health insurance focuses on employees’ decisions to enroll in employer-provided plans. Yet any attempt to achieve universal coverage must focus on the uninsured, the vast majority of whom are not offered employer-sponsored insurance. In the summer of 2008, we conducted a survey experiment to assess the willingness to pay for a health plan among a large sample of uninsured Americans. The experiment yields price elasticities of around one, substantially greater than those found in most previous studies. We use these results to estimate coverage expansion under the Affordable Care Act, with and without an individual mandate. We estimate that 35 million uninsured individuals would gain coverage and find limited evidence of adverse selection.

Expanding coverage to the roughly 50 million Americans who lack health insurance has long been a key public policy concern, and one that has received enormous attention in recent years.1 Most notably, the Affordable Care Act of 2010 (ACA) attempts to cover these individuals via a combination of an expansion of Medicaid and subsidies to purchase private insurance on state-run health insurance exchanges, as well as a mandate for most individuals to obtain coverage.2 Relying on existing research to predict the effects of such a fundamental reform on the currently uninsured is potentially problematic, because existing work generally focuses on the decision to enroll in employer-sponsored health insurance. The currently uninsured are rarely offered the opportunity to purchase insurance through an employer (Kaiser Family Foundation, 2004), calling into question the utility of existing estimates for understanding insurance demand of this population. Not only are uninsured individuals substantially poorer than the average worker offered employer insurance, but the decision to, say, purchase subsidized insurance from a state exchange might fundamentally differ from the decision to enroll in an employer-sponsored health plan, which takes place in the context of co-workers, an employer and potentially benefits counselors. To address these concerns, we devised survey questions specifically designed to elicit the expressed willingness to pay among the uninsured for a comprehensive health plan. Existing data on the uninsured are generally limited in part because many respondents must be screened in order to yield a sample of uninsured people large enough to generate precise estimates, given that more than 80 percent of Americans are covered by some form of health insurance. Fortunately, for a two-week period during the summer of 2008, the Gallup Poll included our questions in their ongoing survey of 1000 individuals a day. We asked respondents whether they would purchase a comprehensive health plan for a given monthly premium, and then lowered the price in several stages for those who initially said they would not purchase it. To the best of our knowledge, our dataset is the first to elicit self-reported willingness-to-pay for health insurance among a large sample of uninsured Americans. Our results suggest that subsidizing the purchase of insurance plans would significantly reduce the population of the uninsured. For example, we estimate that about 60 percent of the uninsured would voluntarily enroll for an annual premium of $2000. Under the current specification of subsidies in the ACA, we estimate that between 33 and 35 million uninsured individuals would gain coverage by 2016 as a result of the law. We also estimate that stripping the individual mandate from the law—the constitutionality of which has been challenged in federal court—would lead to between six and eleven million fewer individuals gaining coverage. The Gallup data include extensive information on health status, and thus allow us to gauge the extent of implied adverse selection for a given subsidy schedule. We find, consistent with past literature, that less healthy individuals have lower price elasticities of demand.3 However, when we calculate the prices individuals would actually face under the ACA subsidy schedule, we find no evidence that less healthy individuals would be more likely to enroll, with or without a mandate. As enrollment is a function of both elasticities and the price points individuals face, other subsidy schedules may well lead to adverse selection; indeed Chandra et al. (2011) find that the individual mandate was important in limiting adverse selection under Massachusetts’ 2006 health reform, which, as we discuss, mirrors the ACA in important respects. With or without a mandate, we find no evidence that those predicted to take-up private insurance are less healthy than those who are already privately insured, suggesting premiums for the latter group should not increase due to a change in the composition of the private insurance pool. We calculate elasticities of take-up with respect to premium price of around 1.0, significantly larger than those typically found in past studies. There are several reasons why our estimated demand curve may differ from those found in past studies. First, as mentioned earlier, almost all past work is based on individuals’ decisions to join employer-provided health plans, a decision few of the uninsured actually face. In fact, our elasticities are quite similar to those found among another group of individuals not offered employer-provided insurance, the self-employed (Gruber and Poterba, 1994). Second, past studies generally need to impute prices for those who do not have insurance or cannot recall their premium price, which likely downwardly biases estimated price sensitivities. Given that in the current environment, prices can be undefined (e.g., insurance companies can deny coverage to applicants with pre-existing conditions), assuming that each individual faces a finite going price can lead to underestimates of consumer demand as some individuals will be assumed to be turning down an offer when in fact they were denied coverage. We find that uninsured individuals are more likely to have been denied coverage in the past, suggesting that the bias induced by assuming that the going price applies to everyone could be especially important in estimating demand among the currently uninsured. Finally, even if the researcher can correctly determine the plan's price, plan features (e.g., deductibles, copayments, provider networks) can vary extensively and in ways the researcher cannot always observe. Thus, an individual who chooses not to purchase health insurance at a relatively low price may appear to have low demand, whereas she may in fact be reacting to the low quality of the offered plan. Even some employer plans can initially exclude coverage for a pre-existing condition, so an individual who chooses not to enroll could be viewed by the researcher as having limited demand when she in fact could have very high demand for a more comprehensive insurance plan.

We collect new data on uninsured Americans’ willingness-to-pay for a health insurance plan. As this group is not usually offered health insurance by their employers (the primary providers of health insurance in the US) they are generally excluded from observational data used in the vast majority of past research, which focuses on employer-provided insurance. Yet the preferences of these individuals are key to formulating a policy that could achieve universal coverage. Instead of relying on observational data, we present uninsured individuals with different premium prices and ask whether they would pay that price to enroll in a health plan equivalent to those offered federal employees. We find elasticities of take-up with respect to price around one, far larger in magnitude than those found in past work. Our results suggest that directly subsidizing the purchase of a private health plan would significantly shrink the uninsured population—for example, more than 60 percent of the uninsured would take up the plan at an annual premium of $2000, and we estimate that 35 million individuals would gain coverage under the specifications of the ACA. Part of the difference between our result and those in past work is that our sample of uninsured individuals is much poorer than the samples of people offered employer-provided insurance used in past papers and the rich and poor may have difference price elasticities (indeed, relatively richer people in our sample have lower elasticities). Moreover, as we focus on plans to subsidize premium prices, we estimate elasticities based on variation around a lower price point than most existing papers, which could lead to different estimated elasticities even if our subjects have the same demand function as subjects in past work. It may also be that our methodology—which has the advantages of random variation in premium prices and a homogenous insurance product, but some of the disadvantages associated with hypothetical-valuation studies—may also contribute to the difference. While we cannot directly address every critique of hypothetical valuation, we find little evidence of common problems such as anchoring and acquiescence bias. Concerns about hypothetical valuation notwithstanding, the large elasticity estimates our results generate suggest that extrapolating the effects of premium subsidies for the uninsured from the elasticities generated in past papers could considerably under-estimate the coverage rates these policies could achieve.