Shift-Share Designs: Theory and Inference

Rodrigo Adão, Michal Kolesár and Eduardo Morales

No 24944, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We study inference in shift-share regression designs, such as when a regional outcome is regressed on a weighted average of observed sectoral shocks, using regional sector shares as weights. We conduct a placebo exercise in which we estimate the effect of a shift-share regressor constructed with randomly generated sectoral shocks on actual labor market outcomes across U.S. Commuting Zones. Tests based on commonly used standard errors with 5% nominal significance level reject the null of no effect in up to 55% of the placebo samples. We use a stylized economic model to show that this overrejection problem arises because regression residuals are correlated across regions with similar sectoral shares, independently of their geographic location. We derive novel inference methods that are valid under arbitrary cross-regional correlation in the regression residuals. We show that our methods yield substantially wider confidence intervals in popular applications of shift-share regression designs.

JEL-codes: C13 C26 F16 F22 (search for similar items in EconPapers)
Date: 2018-08
New Economics Papers: this item is included in nep-lab and nep-ure
Note: ITI LS
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Citations: View citations in EconPapers (34)

Published as Rodrigo Adão & Michal Kolesár & Eduardo Morales, 2019. "Shift-Share Designs: Theory and Inference*," The Quarterly Journal of Economics, vol 134(4), pages 1949-2010.

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