How Much Should We Trust Regional-Exposure Designs?

66 Pages Posted: 28 Jul 2023

See all articles by Jeremy Majerovitz

Jeremy Majerovitz

Federal Reserve Bank of St. Louis

Karthik Sastry

Princeton University - Department of Economics

Date Written: July 27, 2023


Many prominent studies in macroeconomics, labor, and trade use panel data on regions to identify the local effects of aggregate shocks. These studies construct regional-exposure instruments as an observed aggregate shock times an observed regional exposure to that shock. We argue that the most economically plausible source of identification in these settings is uncorrelatedness of observed and unobserved aggregate shocks. Even when the regression estimator is consistent, we show that inference is complicated by cross-regional residual correlations induced by unobserved aggregate shocks. We suggest two-way clustering, two-way heteroskedasticity- and autocorrelation-consistent standard errors, and randomization inference as options to solve this inference problem. We also develop a feasible optimal instrument to improve efficiency. In an application to the estimation of regional fiscal multipliers, we show that the standard practice of clustering by region generates confidence intervals that are too small. When we construct confidence intervals with robust methods, we can no longer reject multipliers close to zero at the 95% level. The feasible optimal instrument more than doubles statistical power; however, we still cannot reject low multipliers. Our results underscore that the precision promised by regional data may disappear with correct inference.

Keywords: Applied Econometrics, Regional Data, Shift-Share Instruments

JEL Classification: C12, C18, C21, C23, C26, F16, R12

Suggested Citation

Majerovitz, Jeremy and Sastry, Karthik, How Much Should We Trust Regional-Exposure Designs? (July 27, 2023). Available at SSRN: or

Jeremy Majerovitz

Federal Reserve Bank of St. Louis ( email )

411 Locust St
Saint Louis, MO 63011
United States

Karthik Sastry (Contact Author)

Princeton University - Department of Economics ( email )

Princeton, NJ 08544-1021
United States

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