This paper estimates the effect of education on participation in criminal activity among men accounting for endogeneity of schooling. Crime is a negative externality with enormous social costs, so if education reduces crime, then schooling may have large social benefits that are not taken into account by individuals.The paper begins by analyzing the effect of schooling on incarceration using Census data and changes in state compulsory attendance laws over time as an instrument for schooling. Changes in these laws have a significant effect on educational achievement, and we reject tests for reverse causality. Moreover, increases in compulsory schooling ages are not correlated with increases in state resources devoted to fighting crime. Both OLS and IV estimates agree and suggest that additional years of secondary schooling reduce the probability of incarceration with the greatest impact associated with completing high school. Differences in educational attainment between black and white men can explain as much as 23% of the black-white gap in male incarceration rates.We corroborate our findings on incarceration using FBI data on arrests that distinguish among different types of crimes. The biggest impacts of education are associated with murder, assault, and motor vehicle theft. We also examine the effect of schooling on self-reported crime in the NLSY and find that our estimates for imprisonment and arrest are caused by changes in criminal behavior and not educational differences in the probability of arrest or incarceration conditional on crime. Given the consistency of our estimates, we calculate the social savings from crime reduction associated with high school graduation among men. The externality is about 14-26% of the private return, suggesting that a significant part of the social return to completing high school for men comes in the form of externalities from crime reduction. * We are grateful to Daron Acemoglu and Josh Angrist for their data on compulsory attendance laws and useful suggestions. We thank

for comments on the first draft. We thank Greg Duncan for helpful comments on the second draft. We thank Jeff Campbell, Jeff Grogger and Chris Taber for comments on this draft. Finola Kennedy of University College Dublin directed us to the apt quote from Marshall that begins this chapter. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Numerous studies regress log earnings on schooling and report estimated coefficients as "Mincer rates of return". A more recent literature uses instrumental variables. This chapter considers the economic interpretation of these analyses and how the availability of repeated cross section and panel data improves the ability of analysts to estimate the rate of return. We consider under what conditions the Mincer model estimates an ex post rate of return. We test and reject the model on six cross sections of U.S. Census data. We present a general nonparametric approach for estimating marginal internal rates of return that takes into account tuition, income taxes and forms of uncertainty. We also contrast estimates based on a single cross-section of data, using the synthetic cohort approach, with estimates based on repeated cross-sections following actual cohorts. Cohort-based models fitted on repeated cross section data provide more reliable estimates of ex post returns. Accounting for uncertainty affects estimates of rates of return. Accounting for sequential revelation of information calls into question the validity of the internal rate of return as a tool for policy analysis. An alternative approach to computing economic rates of return that accounts for sequential revelation of information is proposed and the evidence is summarized. We distinguish ex ante from ex post returns. New panel data methods for estimating the uncertainty and psychic costs facing agents are reviewed. We report recent evidence that demonstrates that there are large psychic costs of schooling. This helps to explain why persons do not attend school even though the financial rewards for doing so are high. We present methods for computing distributions of returns ex ante and ex post. We review the literature on IV estimation. The link of the estimates to the economics is not strong. The traditional instruments are weak, and this literature has not produced decisive empirical estimates. We exposit new methods that interpret the economic content of different instruments within a unified framework. Terms of use: Documents in D I S C U S S I O N P A P E R S E R I E S JEL Classification: C31Keywords: rate of return to schooling, internal rate of return, uncertainty, psychic costs, panel data, distribution

No abstract