Brent Kreider

Tax incidence in differentiated product oligopoly

Abstract We analyze the incidence of ad valorem and unit excise taxes in an oligopolistic industry with differentiated products and price-setting (Bertrand) firms. Both taxes may be passed on to consumers by more than 100 percent, and an increase in the tax rate can increase short run firm profits (and hence the long run number of firms). We provide summary conditions for these effects to arise. The conditions depend on demand curvatures and are written in elasticity form. Surprisingly, the analysis largely corroborates Cournot results with homogeneous demand.

Bounding the effects of food insecurity on children's health outcomes.

Previous research has estimated that food insecure children are more likely to suffer from a wide array of negative health outcomes than food secure children, leading many to claim that alleviating food insecurity would lead to better health outcomes. Identifying the causal impacts is problematic, however, given endogenous selection into food security status and potential mismeasurement of true food security status. Using recently developed nonparametric bounding methods and data from the 2001-2006 National Health and Nutritional Examination Survey (NHANES), we assess what can be identified about the effects of food insecurity on child health outcomes in the presence of nonrandom selection and nonclassical measurement error. Under relatively weak monotonicity assumptions, we can identify that food security has a statistically significant positive impact on favorable general health and being a healthy weight. Our work suggests that previous research has more likely underestimated than overestimated the causal impacts of food insecurity on health.

Disability and Employment: Reevaluating the Evidence in Light of Reporting Errors

Measurement error in health and disability status has been widely accepted as a central problem for social science research. Long-standing debates about the prevalence of disability, the role of health in labor market outcomes, and the influence of federal disability policy on declining employment rates have all emphasized issues regarding the reliability of self-reported disability. In addition to random error, inaccuracy in survey datasets may be produced by a host of economic, social, and psychological factors that can lead respondents to misreport work capacity. We develop a nonparametric foundation for assessing how assumptions on the reporting error process affect inferences on the employment gap between the disabled and nondisabled. Rather than imposing the strong assumptions required to obtain point identification, we derive sets of bounds that formalize the identifying power of primitive nonparametric assumptions that appear to share broad consensus in the literature. Within this framework, we introduce a finite-sample correction for the analog estimator of the monotone instrumental variable (MIV) bound. Our empirical results suggest that conclusions derived from conventional latent variable reporting error models may be driven largely by ad hoc distributional and functional form restrictions. Under relatively weak nonparametric assumptions, nonworkers appear to systematically overreport disability.

The impact of the National School Lunch Program on child health: A nonparametric bounds analysis

Children in households reporting the receipt of free or reduced-price school meals through the National School Lunch Program (NSLP) are more likely to have negative health outcomes than observationally similar nonparticipants. Assessing causal effects of the program is made difficult, however, by missing counterfactuals and systematic underreporting of program participation. Combining survey data with auxiliary administrative information on the size of the NSLP caseload, we extend nonparametric partial identification methods that account for endogenous selection and nonrandom classification error in a single framework. Similar to a regression discontinuity design, we introduce a new way to conceptualize the monotone instrumental variable (MIV) assumption using eligibility criteria as monotone instruments. Under relatively weak assumptions, we find evidence that the receipt of free and reduced-price lunches improves the health outcomes of children.

Disability and Employment

Measurement error in health and disability status has been widely accepted as a central problem in social science research. Long-standing debates about the prevalence of disability, the role of health in labor market outcomes, and the influence of federal disability policy on declining employment rates have all emphasized issues regarding the reliability of self-reported disability. In addition to random error, inaccuracy in survey datasets may be produced by a host of economic, social, and psychological factors that can lead respondents to misreport work capacity. We develop a nonparametric foundation for assessing how assumptions on the reporting error process affect inferences on the employment gap between the disabled and nondisabled. Rather than imposing the strong assumptions required to obtain point identification, we derive sets of bounds that formalize the identifying power of primitive nonparametric assumptions that appear to share broad consensus in the literature. Within this framework, we introduce a finite-sample correction for the analog estimator of the monotone instrumental variable (MIV) bound. Our empirical results suggest that conclusions derived from conventional latent variable reporting error models may be driven largely by ad hoc distributional and functional form restrictions. We also find that under relatively weak nonparametric assumptions, nonworkers appear to systematically overreport disability.

Food Stamps and Food Insecurity: What Can Be Learned in the Presence of Nonclassical Measurement Error?.

Policymakers have been puzzled to observe that food stamp households appear more likely to be food insecure than observationally similar eligible nonparticipating households. We reexamine this issue allowing for nonclassical reporting errors in food stamp participation and food insecurity. Extending the literature on partially identified parameters, we introduce a nonparametric framework that makes transparent what can be known about conditional probabilities when a binary outcome and conditioning variable are both subject to nonclassical measurement error. We find that the food insecurity paradox hinges on assumptions about the data that are not supported by the previous food stamp participation literature.

The efficiency of indirect taxes under imperfect competition

This paper considers the relative efficiency of ad valorem and unit taxes in imperfectly competitive markets. We provide a simple proof that ad valorem taxes are welfare-superior to unit taxes in the short run when production costs are identical across firms. The proof covers differentiated products and a wide range of market conduct. Cost asymmetries strengthen the case for ad valorem taxation under Cournot competition, but unit taxation may be welfare-superior under Bertrand competition with product differentiation. Ad valorem taxation is superior with free entry under Cournot competition, but not necessarily under price competition when consumers value variety.

Explaining Applications to the U.S. Disability System: A Semiparametric Approach

This study investigates the determinants of applications for U.S. disability benefits between 1986 and 1993 using a semiparametric discrete factor procedure separately for men and women. Approximating a dynamic optimization model, the estimation accounts for a variety of potential biases that were unaddressed in prior studies. Our results indicate different responses of men and women to variations in policy measures. Past labor earnings and fringe benefits as well as benefit eligibility and benefit amounts clearly affect application behavior.

Health Insurance and the Homeless

There is very little known about health care utilization among the homeless or about the role of health insurance on utilization patterns. Many health care reform proposals advocate expanding health insurance coverage for various segments of society, including the homeless. Although homeless people who lack health insurance face strong financial barriers to health services, providing them with health insurance may not appreciably increase their demand for health care if they also face important non-financial barriers. We investigate the relationship between insurance and utilization for this group based on estimates from an empirical model of medical care use and insurance coverage. Using our estimates, we simulate potential effects of policy changes on various types of utilization, including use of mental health services and treatment for alcohol or other drug abuse.

Identification of Expected Outcomes in a Data Error Mixing Model With Multiplicative Mean Independence

We consider the problem of identifying a mean outcome in corrupt sampling where the observed outcome is drawn from a mixture of the distribution of interest and another distribution. Relaxing the contaminated sampling assumption that the outcome is statistically independent of the mixing process, we assess the identifying power of an assumption that the conditional means of the distributions differ by a factor of proportionality. For binary outcomes, we consider the special case that all draws from the alternative distribution are erroneous. We illustrate how these models can inform researchers about illicit drug use in the presence of reporting errors.