Peter Hull

University of Chicago
5757 South University Avenue
Chicago, IL 60637

E-Mail: EmailAddress: hidden: you can email any NBER-related person as first underscore last at nber dot org
NBER Program Affiliations: HC , LS
NBER Affiliation: Faculty Research Fellow
Institutional Affiliation: University of Chicago

NBER Working Papers and Publications

April 2020Measuring Racial Discrimination in Bail Decisions
with David Arnold, Will S. Dobbie: w26999
We develop new quasi-experimental tools to measure racial discrimination in the context of bail decisions. Observational comparisons of white and black pretrial release rates suffer from omitted variables bias when there are unobserved racial differences in pretrial misconduct potential. We show that the bias in these observational comparisons is a function of average white and black misconduct risk, which can be estimated from the quasi-random assignment of bail judges. Estimates from New York City show that less than one-third of the release rate disparity between white and black defendants is explained by unobserved differences in misconduct potential, with more than two-thirds explained by racial discrimination. We then develop a hierarchical marginal treatment effects model that impos...
September 2018Quasi-Experimental Shift-Share Research Designs
with Kirill Borusyak, Xavier Jaravel: w24997
Many studies use shift-share (or “Bartik”) instruments, which average a set of shocks with exposure share weights. We provide a new econometric framework for such designs in which identification follows from the quasi-random assignment of shocks, allowing exposure shares to be endogenous. This framework is centered around a numerical equivalence: conventional shift-share instrumental variable (SSIV) regression coefficients are equivalently obtained from a transformed regression where the shocks are used directly as an instrument. This equivalence implies a shock-level translation of the SSIV exclusion restriction, which holds when shocks are as-good-as-randomly assigned and large in number, with sufficient dispersion in their average exposure. We discuss and illustrate several practical in...
November 2015Leveraging Lotteries for School Value-Added: Testing and Estimation
with Joshua Angrist, Parag A. Pathak, Christopher Walters: w21748
Conventional value-added models (VAMs) compare average test scores across schools after regression-adjusting for students’ demographic characteristics and previous scores. This paper tests for VAM bias using a procedure that asks whether VAM estimates accurately predict the achievement consequences of random assignment to specific schools. Test results from admissions lotteries in Boston suggest conventional VAM estimates are biased, which motivates the development of a hierarchical model describing the joint distribution of school value-added, bias, and lottery compliance. We use this model to assess the substantive importance of bias in conventional VAM estimates and to construct hybrid value-added estimates that optimally combine ordinary least squares and lottery-based instrumental var...

Published: Joshua D. Angrist & Peter D. Hull & Parag A. Pathak & Christopher R. Walters, 2017. "Leveraging Lotteries for School Value-Added: Testing and Estimation," The Quarterly Journal of Economics, Oxford University Press, vol. 132(2), pages 871-919. citation courtesy of

December 2014Charters Without Lotteries: Testing Takeovers in New Orleans and Boston
with Atila Abdulkadiroğlu, Joshua D. Angrist, Parag A. Pathak: w20792
Lottery estimates suggest oversubscribed urban charter schools boost student achievement markedly. But these estimates needn’t capture treatment effects for students who haven’t applied to charter schools or for students attending charters for which demand is weak. This paper reports estimates of the effect of charter school attendance on middle-schoolers in charter takeovers in New Orleans and Boston. Takeovers are traditional public schools that close and then re-open as charter schools. Students enrolled in the schools designated for closure are eligible for “grandfathering” into the new schools; that is, they are guaranteed seats. We use this fact to construct instrumental variables estimates of the effects of passive charter attendance: the grandfathering instrument compares students ...


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