Shift-Share Designs: Theory and Inference*
University of Chicago · Princeton University
Abstract
Abstract We study inference in shift-share regression designs, such as when a regional outcome is regressed on a weighted average of 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, independent…
Citation impact
- FWCI
- 97.60
- Percentile
- 100%
- References
- 64
Authors
3- RARodrigo AdãoCorresponding
University of Chicago
- MKMichal Kolesár
Princeton University
- EMEduardo Morales
Princeton University
Topics & keywords
- Stylized fact
- Inference
- Regression
- Regression analysis
- Null hypothesis
- Confidence interval
- Linear regression
- Standard error