Productivity and Selection of Human Capital with Machine Learning By AARON CHALFIN, OREN DANIELI, ANDREW HILLIS, ZUBIN JELVEH, MICHAEL LUCA, JENS LUDWIG, AND SENDHIL MULLAINATHAN* * Chalfin: University of Chicago, Chicago IL 60637 (email: a great deal. Variability in worker productivity
[email protected]); Danieli: Harvard University, Cambridge MA 02138 (email:
[email protected]); Hillis: Harvard (e.g., Gordon, Kane and Staiger, 2006) means University, Cambridge MA 02138 (email:
[email protected]); ∂Y/∂L depends on which new teacher or cop Jelveh: New York University, New York NY 10003 (
[email protected]); Luca: Harvard Business School, Boston, is hired. Heterogeneity in productivity also MA 02163 (email:
[email protected]); Ludwig: University of Chicago, means that estimates for the effect of hiring Chicago IL 60637 and NBER (email:
[email protected]); Mullainathan: Harvard University, Cambridge MA 02138 and NBER one more worker are not stable across contexts (email:
[email protected]). Paper prepared for the American – they depend on the institutions used to Economic Association session “Predictive Cities,” January 5, 2016. This paper uses data obtained from the University of Michigan’s screen and hire the marginal worker. Inter-university Consortium on Political and Social Research. Thanks With heterogeneity in labor inputs, to the National Science Foundation Graduate Research Fellowship Program (Grant No. DGE1144152), and to the Laura and John Arnold economics can offer two contributions to the Foundation, the John D. and Catherine T. MacArthur Foundation, the study of productivity in social policy. The first Robert R. McCormick Foundation, the Pritzker Foundation, and to Susan and Tom Dunn and Ira Handler for support of the University of is standard causal inference around shifts in Chicago Crime Lab.