Non-Random Exposure to Exogenous Shocks: Theory and Applications

47 Pages Posted: 21 Sep 2020 Last revised: 30 Jan 2023

See all articles by Kirill Borusyak

Kirill Borusyak

University College London - Department of Economics

Peter Hull

University of Chicago - Becker Friedman Institute for Economics

Multiple version iconThere are 3 versions of this paper

Date Written: September 2020

Abstract

We develop new tools for estimating the causal effects of treatments or instruments that combine multiple sources of variation according to a known formula. Examples include treatments capturing spillovers in social and transportation networks, simulated instruments for policy eligibility, and shift-share instruments. We show how exogenous shocks to some, but not all, determinants of such variables can be leveraged while avoiding omitted variables bias. Our solution involves specifying counterfactual shocks that may as well have been realized and adjusting for a summary measure of non-randomness in shock exposure: the average treatment (or instrument) across such counterfactuals. We further show how to use shock counterfactuals for valid finite-sample inference, and characterize the valid instruments that are asymptotically efficient. We apply this framework to address bias when estimating employment effects of market access growth from Chinese high-speed rail construction, and to boost power when estimating coverage effects of expanded Medicaid eligibility.

Suggested Citation

Borusyak, Kirill and Hull, Peter, Non-Random Exposure to Exogenous Shocks: Theory and Applications (September 2020). NBER Working Paper No. w27845, Available at SSRN: https://ssrn.com/abstract=3696212

Kirill Borusyak (Contact Author)

University College London - Department of Economics

Drayton House, 30 Gordon Street
30 Gordon Street
London, WC1H 0AX
United Kingdom

Peter Hull

University of Chicago - Becker Friedman Institute for Economics ( email )

Chicago, IL 60637
United States

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