April 6-7, 2017
Amy Finkelstein of MIT, Raj Chetty of Stanford University, and Nathaniel Hendren of Harvard University, Organizers
Behavioral Responses to Taxation
Caroline Hoxby, Stanford University and NBER
The Returns to Online Education
Shanthi Ramnath, Department of the Treasury, and Patricia Tong, RAND Corporation
The Persistent Reduction in Poverty from Filing a Tax Return
Low-income households not required to file often fail to receive benefits provided through the tax code. In 2008, the U.S. government made people with at least $3,000 in earnings eligible for a stimulus payment if they filed a tax return. Using eligibility for this credit as an instrument for filing, Ramnath and Tong find with administrative data that filing reduces the probability of living in poverty in future years, which is a result of increases in EITC claiming, workforce attachment, and earnings. These results demonstrate temporary incentives to participate in the tax system have persistent real effects on economic activity and poverty.
Magne Mogstad, the University of Chicago and NBER, and Thibaut Lamadon and Bradley J. Setzler, the University of Chicago
Earnings Dynamics, Mobility Costs and Transmission of Firm and Market Level Shocks
Randall Akee, the University of California at Los Angeles, and Maggie Jones and Sonya Porter, US Census Bureau
Adding Insult to Injury: Racial Disparity in an Era of Increasing Income Inequality
Using unique linked data, Akee, Jones, and Porter examine income inequality and mobility across racial and ethnic groups in the United States. Their data encompass the universe of tax filers in the U.S. for the period 2000 to 2014, matched with individual-level race and ethnicity information from multiple censuses and American Community Survey data. Authors document both income inequality and mobility trends over the period. They find significant stratification in terms of average incomes by race and ethnic group and distinct differences in within-group income inequality. The groups with the highest incomes — Whites and Asians — also have the highest levels of within-group inequality and the lowest levels of within-group mobility. The reverse is true for the lowest-income groups: Blacks, American Indians, and Hispanics have lower within-group inequality and immobility. On the other hand, their low-income groups are also highly immobile when looking at overall, rather than within-group, mobility. These same groups also have a higher probability of experiencing downward mobility compared with Whites and Asians. Akee, Jones, and Porter also find that within-group income inequality increased for all groups between 2000 and 2014, and the increase was especially large for Whites. In regression analyses using individual-level panel data, they find persistent differences by race and ethnicity in incomes over time. Authors also examine young tax filers (ages 25-35) and investigate the long-term effects of local economic and racial residential segregation conditions at the start of their careers. They find persistent long-run effects of racial residential segregation at career entry on the incomes of certain groups. The picture that emerges from their analysis is of a rigid income structure, with mainly Whites and Asians confined to the top and Blacks, American Indians, and Hispanics confined to the bottom.
Jake Mortenson, Joint Committee on Taxation, and Andy Whitten, Department of the Treasury
Bunching to Maximize Tax Credits: Evidence from the U.S. Tax Schedule
Mortenson and Whitten document bunching at tax kinks using a panel of 258 million income tax returns in the United States from 1996 to 2014. During this period bunching grew by 700%. While most bunchers are self-employed, a substantial number of wage earners also bunch by misreporting income. The vast majority of bunching occurs at kinks maximizing tax credits, particularly at the kink that maximizes taxpayer refunds. Many taxpayers follow the refund-maximizing kink from year to year, selectively maximizing the appropriate tax credit(s). The researchers argue that this behavior is incompatible with recently developed methods for identifying elasticities via bunching patterns.
Annette Alstadsæter, Norwegian University of Life Sciences; Niels Johannesen, the University of Copenhagen; and Gabriel Zucman, the University of California at Berkeley and NBER
Tax Evasion and Inequality
Alex Rees-Jones, the University of Pennsylvania, and Dmitry Taubinsky, Dartmouth College and NBER
Heuristic Perceptions of the Income Tax: Evidence and Implications for Debiasing (NBER Working Paper No. 22884)
Using an incentivized tax forecasting task, Rees-Jones and Taubinsky estimate the prevalence of previously discussed heuristics for constructing mental representations of nonlinear incentive schemes. They find strong evidence for "ironing" (linearizing the tax schedule using one's average tax rate), no evidence for "spotlighting" (linearizing the tax schedule using one's marginal tax rate), and they identify features of the remaining misperceptions that are not captured by existing models. The researchers then embed these misperceptions in a standard model of income taxation and study their welfare consequences. They find that their estimated misperceptions increase social welfare because they are helpful in achieving redistributive goals.
Manasi Deshpande, the University of Chicago and NBER, and Yue Li, SUNY Albany
Who is Screened Out? Application Costs and the Targeting of Disability Programs
Deshpande and Li study the effect of application costs on the number and composition of disability applicants and recipients using the closings of Social Security Administration field offices, which provide assistance with filing disability applications. Using administrative data from the Social Security Administration, they find that field office closings reduce the number of disability allowances by 13 percent in areas surrounding the closed office and by 10 percent in areas surrounding neighboring offices, with effects persistent for at least two years after a closing. The closings disproportionately reduce applications among potential applicants from lower socioeconomic backgrounds and among those with moderately severe conditions. The researchers' estimates suggest that about three-quarters of the reduction in disability applications in areas around closed field offices is attributable to increased congestion at neighboring offices and the remaining amount to increased travel times and costs of information gathering.
Judd B. Kessler, the University of Pennsylvania and NBER, and Hunt Allcott, New York University and NBER
The Welfare Effects of Nudges: A Case Study of Energy Use Social Comparisons (NBER Working Paper No. 21671)
"Nudge"-style interventions are often deemed "successful" if they cause large behavior change, but they are rarely subjected to full social welfare evaluations. Allcott and Kessler combine a field experiment with a simple theoretical framework to evaluate the welfare effects of one especially policy-relevant intervention, home energy social comparison reports. In their sample, the reports increase social welfare, although traditional evaluation approaches overstate welfare gains by a factor of 3.7. Overall, the welfare gains from home energy reports might be overstated by $620 million. The researchers develop a prediction algorithm for optimal targeting; this would double the welfare gains.
Public Economics Program Meeting Joint with Insurance Working Group
Johannes Spinnewijn and Camille Landais, London School of Economics; David G. Seim and Peter Nilsson, Stockholm University; and Arash Nekoei, Institute for International Economic Studies at Stockholm University
Adverse Selection in Unemployment Insurance: Evidence and Implications
Liran Einav, Stanford University and NBER; Amy Finkelstein; and Neale Mahoney, the University of Chicago and NBER
Provider Incentives and Health Care Costs: Evidence from Long-Term Care Hospitals (NBER Working Paper No. 23100)
Einav, Finkelstein, and Mahoney study the design of provider incentives in the post-acute care setting — a high-stakes but under-studied segment of the healthcare system. They focus on long-term care hospitals (LTCHs) and the large (approximately $13,000) jump in Medicare payments they receive when a patient's stay reaches a threshold number of days. The descriptive evidence indicates that discharges increase substantially after the threshold, and that the marginal patient discharged after the threshold is in relatively better health. Despite the large financial incentives and behavioral response in a high mortality population, the researchers are unable to detect any compelling evidence of an impact on patient mortality. To assess provider behavior under counterfactual payment schedules, they estimate a simple dynamic discrete choice model of LTCH discharge decisions. When they conservatively limit themselves to alternative contracts that hold the LTCH harmless, they find that an alternative contract can generate Medicare savings of about $2,100 per admission, or about 5% of total payments. More aggressive payment reforms can generate substantially greater savings, but the accompanying reduction in LTCH profits has potential out-of-sample consequences. The researchers' results highlight how improved financial incentives may be able to reduce healthcare spending, without negative consequences for industry profits or patient health.
Michael D. Whinston, MIT and NBER; Benjamin R. Handel, the University of California at Berkeley and NBER; and Igal Hendel, Northwestern University and NBER
The Welfare Impact of Long-term Health Insurance Contracts
Reclassification risk is a major concern in health insurance. Regulation, like the ACA, prescribes community rating to contend with reclassification risk. However, community rating can lead to problems of adverse selection. Handel, Hendel, and Whinston use a rich data set with individual-level information on health risk to empirically study an alternative solution: dynamic contracts. They compare equilibria under four contractual arrangements: (i) spot contracts, (ii) first-best long-run contracts with two-sided commitment, (iii) long-term contracts with one-sided commitment, and (iv) ACA-like markets with spot contracts and community rating. Empirically, dynamic contracts with one-sided commitment deliver a substantial welfare gain over spot contracts by attenuating reclassification risk. Dynamic contracts achieve close to the first-best for consumers with flat net income paths who are willing to front-load payments to facilitate long-run insurance. Consumers with increasing net income growth over their lifetimes prefer ACA-like community rating over dynamic contracts. However, lower risk aversion, sufficient switching costs, or government insurance of pre-age-25 health risks can raise the welfare achieved under dynamic contracts above the level in ACA-like markets.