The Impact of the National School Lunch Program on Child Health: A Nonparametric Bounds Analysis December 2009 By John PepperCraig GundersonBrent Kreider 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. Journal of Econometrics Areas of focus Education John Pepper John V. Pepper is a Professor of Economics at the University of Virginia. He received his Ph.D. from the University of Wisconsin in 1996, and his B.A. in Quantitative Economics from Tufts University in 1987. Read full bio Craig Gunderson Brent Kreider Related Content John Pepper Identifying the Effects of Food Stamps on the Nutritional Health of Children when Program participation is Misreported Research The literature assessing the efficacy of the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp Program, has long puzzled over positive associations between SNAP receipt and various undesirable health outcomes such as food insecurity. Assessing the causal impacts of SNAP, however, is hampered by two key identification problems: endogenous selection into participation and extensive systematic underreporting of participation status.Using data from the National Health and Nutrition Examination Survey (NHANES), we extend partial identification bounding methods to account for these two identification problems in a single unifying framework. Deterrence and the Death Penalty: Partial Identification Analysis Using Repeated Cross Sections Research Objectives Researchers have used repeated cross sectional observations of homicide rates and sanctions to examine the deterrent effect of the adoption and implementation of death penalty statutes. The empirical literature, however, has failed to achieve consensus.