Research

We conduct the first survey experiment to understand public attitudes about the realization rule for capital gains. This rule requires that assets usually must be sold before gains on them are taxed and thus makes taxing capital income much harder. We have three main findings. First, respondents strongly prefer to wait to tax gains on stocks until sale: 75% to 25%. But the flip side is that there is surprisingly strong support for taxing gains on assets at sale or transfer, including at death, in areas where current law never taxes those gains. Second, these stated views change only modestly when randomized participants observe a policy debate composed of videos explaining both the pros and cons of taxing before sale, though the pro and con treatments have large effects individually. And, third, among many possible explanations of these attitudes, we find particular evidence for three: mental accounting; status quo effects; and a desire to tax consumption, not income.

 

Many centralized school admissions systems use lotteries to ration limited seats at oversubscribed schools. The resulting random assignment is used by empirical researchers to identify the effects of schools on outcomes like test scores. I first find that the two most popular empirical research designs may not successfully extract a random assignment of applicants to schools. When are the research designs able to overcome this problem? I show the following main results for a class of data-generating mechanisms containing those used in practice: The first-choice research design extracts a random assignment under a mechanism if the mechanism is strategy-proof for schools. In contrast, the other qualification instrument research design does not necessarily extract a random assignment under any mechanism. The former research design is therefore more compelling than the latter. Many applications of the two research designs need some implicit assumption, such as large-sample approximately random assignment, to justify their empirical strategy.

Competition in health insurance markets may fail to improve health outcomes if consumers are not able to identify high-quality plans. We develop and apply a novel instrumental variables framework to quantify the variation in causal mortality effects across plans and measure how much consumers attend to this variation. We first document large differences in the observed mortality rates of Medicare Advantage plans in local markets. We then show that when plans with high mortality rates exit these markets, enrollees tend to switch to more typical plans and subsequently experience lower mortality. We derive and validate a novel “fallback condition” governing the subsequent choices of those affected by plan exits. When the fallback condition is satisfied, plan terminations can be used to estimate the relationship between observed plan mortality rates and causal mortality effects. Applying the framework, we find that mortality rates unbiasedly predict causal mortality effects. We then extend our framework to study other predictors of plan mortality effects and estimate consumer willingness to pay. Higher-spending plans tend to reduce enrollee mortality, but existing quality ratings are uncorrelated with plan mortality effects. Consumers place little weight on mortality effects when choosing plans. Good insurance plans dramatically reduce mortality, and redirecting consumers to such plans could improve beneficiary health.

We estimate the returns to a broad set of graduate degrees. To control for heterogeneity in preferences and ability, we use fixed effects for combinations of field-specific undergraduate and graduate degrees obtained by the last time we observe an individual. Basically, we compare earnings before the graduate degree to earnings after it. Using National Science Foundation data, we find large differences across graduate fields in earnings effects. The returns often depend on the undergraduate major. The contribution of occupational upgrading to the earnings gain varies across degrees. Finally, simple regression-based estimates of returns to graduate fields are often highly misleading.

Observational evidence suggests that social trust, i.e., trust in others, and the closely related concept of social capital play a critical role in compliance with government policy, particularly in regards to public responsiveness to measures intended to curb the spread of the novel coronavirus. We use a survey experiment to causally estimate the impact of altering social trust on compliance with a range of policies intended to combat the COVID-19 pandemic. Utilizing an instrumental variable approach, we are able to alter reported social trust, but find null effects in regards to compliance with COVID-19 mitigation measures. We speculate on several explanations for this finding.

Staying home and avoiding unnecessary contact is an important part of the effort to contain COVID-19 and limit deaths. Every state in the United States enacted policies to encourage distancing and some mandated staying home. Understanding how these policies interact with individuals' voluntary responses to the COVID-19 epidemic is a critical initial step in understanding the role of these nonpharmaceutical interventions in transmission dynamics and assessing policy impacts. We use variation in policy responses along with smart device data that measures the amount of time Americans stayed home to disentangle the extent that observed shifts in staying home behavior are induced by policy. We find evidence that stay-at-home orders and voluntary response to locally reported COVID-19 cases and deaths led to behavioral change. For the median county, which implemented a stay-at-home order with about two cases, we find that the response to stay-at-home orders increased time at home as if the county had experienced 29 additional local cases. However, the relative effect of stay-at-home orders was much greater in select counties. On the one hand, the mandate can be viewed as displacing a voluntary response to this rise in cases. On the other hand, policy accelerated the response, which likely helped reduce spread in the early phase of the pandemic. It is important to be able to attribute the relative role of self-interested behavior or policy mandates to understand the limits and opportunities for relying on voluntary behavior as opposed to imposing stay-at-home orders.

This is the sixth in a series of papers prepared by a collection of economists and policy experts in the United States, the UK, and the European Union who have studied, and are committed to the improvement of, competition in digital markets. Previous papers addressed consumer protection in online markets, regulating the market for general search services, the concepts of “fairness” and “contestability” as used in the Digital Markets Act, the use of “equitable interoperability” as a “super tool” to restore and encourage competition in online markets, and coherence between US and European approaches to digital regulation.

Democracy is widely believed to contribute to economic growth and public health in the 20th and earlier centuries. We find that this conventional wisdom is reversed in this century, i.e., democracy has persistent negative impacts on GDP growth during 2001-2020. This finding emerges from five different instrumental variable strategies. Our analysis suggests that democracies cause slower growth through less investment and trade. For 2020, democracy is also found to cause more deaths from Covid-19.

We use geospatial data to examine the unprecedented national program currently underway in the United States to distribute and administer vaccines against COVID-19. We quantify the impact of the proposed federal partnership with the company Dollar General to serve as vaccination sites and compare vaccine access with Dollar General to the current Federal Retail Pharmacy Partnership Program. Although dollar stores have been viewed with skepticism and controversy in the policy sector, we show that, relative to the locations of the current federal program, Dollar General stores are disproportionately likely to be located in Census tracts with high social vulnerability; using these stores as vaccination sites would greatly decrease the distance to vaccines for both low-income and minority households. We consider a hypothetical alternative partnership with Dollar Tree and show that adding these stores to the vaccination program would be similarly valuable, but impact different geographic areas than the Dollar General partnership. Adding Dollar General to the current pharmacy partners greatly surpasses the goal set by the Biden administration of having 90% of the population within 5 miles of a vaccine site. We discuss the potential benefits of leveraging these partnerships for other vaccinations, including against influenza.