Mikhail Golosov and Aleh Tsyvinski, Yale University and NBER, and Maxim Troshkin, University of Minnesota
Optimal Dynamic Taxes
Golosov, Tsyvinski, and Troskin develop a methodology for deriving formulas that facilitate interpretation of the forces that determine optimal labor and savings distortions, as well as taxes, in dynamic settings. The formulas for the labor wedges extend the static optimal taxation analysis of Diamond (1998) and Saez (2001) to dynamic settings. Compared to the static analysis, the dynamic nature of the problem offers three novel insights. First, the opportunity to provide incentives dynamically adds a force lowering labor distortions. Second, labor distortions in dynamic settings may differ significantly from those in static settings because a key determinant of the former is the conditional, rather than the unconditional, distribution of skill shocks. The conditional distribution of shocks differs significantly from the unconditional one. Third, the persistence of shocks manifests itself as an increase in the redistributionary motive of the government. Finally, these researchers derive a novel formula to analyze the determinants of the savings distortions. Their second set of results numerically simulates the optimal labor and savings distortions. Their analysis is conducted for a realistically calibrated economy based on the empirical income distributions. The computed optimal dynamic distortions differ significantly from the optimal static distortions, highlighting the importance of the forces in the theoretical analysis. The welfare gain of switching from an optimal static system to the dynamic one is large. Their third contribution is a novel implementation of the optimal allocations. They show that a tax system based on consolidated income accounts (CIA) implements the optimum. The labor income tax depends on the current labor income and on the balance on the CIA. The savings tax depends only on the amount of savings. The CIA balance is updated as a function of the labor income and the previous balance.
Brian G. Knight, Brown University and NBER, and Nathan Schiff, University of British Columbia
Spatial Competition and Cross-Border Shopping: Evidence from State Lotteries
Knight and Schiff investigate competition between jurisdictions in the context of cross-border shopping for state lottery tickets. They first develop a simple theoretical model in which consumers choose between state lotteries and face a trade-off between travel costs and the price of a fair gamble, which is declining in the size of the jackpot and the odds of winning. Given this trade-off, the model predicts that per-resident sales should be more responsive to prices in small states with densely populated borders, relative to large states with sparsely populated borders. The empirical analysis focuses on the multi-state games of Powerball and Mega Millions, and the identification strategy is based upon high-frequency variation in prices due to the rollover feature of lottery jackpots. The empirical results support the predictions of the model. The magnitude of these effects is large, suggesting that states do face competitive pressures from neighboring lotteries, but the effects vary significantly across states.
Roger H. Gordon and Julie Berry Cullen, University of California, San Diego and NBER
Income Redistribution in a Federal System of Governments
The literature on fiscal federalism, dating back to work by Musgrave and Oates, argued that the Federal government should have primary responsibility for income distribution: states and localities have a comparative disadvantage when undertaking redistribution because they face the threat of exit of net payers and in-migration of net recipients. However, we see states and localities in the United States actively engaged in redistribution, with over 40 percent over overall state and local revenue coming from income and sales taxes. In their paper, Julie Berry Cullen and Roger H. Gordon develop a positive model of the respective roles of Federal and state governments in income distribution. In general, redistribution by states creates positive fiscal externalities to other states because of migration, but negative fiscal externalities to the national government through changes in reported taxable income. If the Federal government chooses its policies to assure that the net externalities are zero, then Berry and Gordon forecast that 1) it will play no role in redistribution if there is no migration, and 2) with migration it will choose redistribution policies so as to fully offset any fiscal externalities across states. They then use of the characterization of equilibrium state and Federal policies to back out the extent of distributional concerns and migration responses that would lead to the tax schedules observed in practice. The resulting welfare weights on different income groups and inferred migration elasticities seem plausible, suggesting that such a positive model can successfully explain the observed division of responsibilities for redistribution between state and Federal governments seen in the United States.
James Sallee, University of Chicago, and Joel Slemrod, University of Michigan and NBER
Notches - where small changes in behavior lead to large changes in a tax or subsidy - figure prominently in many policies, but have been rarely examined by economists. Sallee and Slemrod analyze a class of notches associated with policies in the United States and Canada aimed at improving vehicle fuel economy. They provide several pieces of evidence showing that automakers respond to notches in fuel economy policy by precisely manipulating fuel economy ratings so as to just qualify for more favorable treatment. They then describe the welfare consequences of this behavior and derive a welfare summary statistic applicable to many contexts. Finally, as a way of estimating the consumer willingness to pay for fuel economy, they use a comparison of the amount of strategic manipulation that occurs surrounding tax notches to the amount surrounding presentation notches in fuel economy label rules.
Michael Anderson, University of California, Berkeley; Carlos Dobkin, University of California, Santa Cruz and NBER; and Tal Gross, University of Miami
The Effect of Health Insurance Coverage on the Use of Medical Services (NBER Working Paper No. 15823)
Substantial uncertainty exists regarding the causal effect of health insurance on the utilization of care. Most studies cannot determine whether the large differences in health care utilization between the insured and the uninsured are attributable to insurance status or to other unobserved differences between the two groups. Anderson, Dobkin, and Gross exploit a sharp change in insurance coverage rates that results from young adults "aging out" of their parents' insurance plans to estimate the effect of insurance coverage on the utilization of emergency department (ED) and inpatient services. Using the National Health Interview Survey (NHIS) and a census of emergency department records and hospital discharge records from seven states, they find that aging out results in an abrupt 5 to 8 percentage point reduction in the probability of having health insurance. They find that not having insurance leads to a 40 percent reduction in ED visits and a 61 percent reduction in inpatient hospital admissions. The drop in ED visits and inpatient admissions is entirely due to reductions in the care provided by privately owned hospitals, with particularly large reductions at for-profit hospitals. The results imply that expanding health insurance coverage would result in a substantial increase in care provided to currently uninsured individuals.
Till Von Wachter, Columbia University and NBER; Jae Song, Social Security Administration; and Joyce Manchester, Congressional Budget Office
Trends in Employment and Earnings of Allowed and Rejected Applicants to the Social Security Disability Insurance Program
Vivi Alatas, World Bank; Abhijit Banerjee and Benjamin A. Olken, MIT and NBER; Rema Hanna, Harvard University and NBER; and Julia Tobias, Stanford University
Targeting the Poor: Evidence from a Field Experiment in Indonesia
In developing countries, identifying the poor for redistribution or social insurance is challenging because the government lacks information about people's incomes. Alatas, Banerjee, Hanna, Olken, and Tobias reports a field experiment conducted in 640 Indonesian villages that investigated two main approaches to this problem: proxy-means tests, where a census of hard-to-hide assets is used to predict consumption, and community-based targeting, where villagers rank everyone from richest to poorest. When poverty is defined using per-capita expenditure and the common PPP$2 per day threshold, the researachers find that community-based targeting performs worse in identifying the poor than proxy-means tests, particularly near the threshold. This worse performance does not appear to be due to elite capture. Instead, communities appear to be systematically using a different concept of poverty: the results of community-based methods are more correlated with how individual community members rank each other and with villagers' self-assessments of their own status. Consistent with this, the community-based methods result in higher satisfaction with beneficiary lists and the targeting process.