Non-Random Exposure to Exogenous Shocks: Theory and Application
Abstract/Contents
- 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.
Description
| Type of resource | text |
|---|---|
| Date created | September 9, 2021 |
Creators/Contributors
| Author | Borusyak, Kirill |
|---|---|
| Author | Hull, Peter |
| Organizer of meeting | Diamond, Rebecca |
| Organizer of meeting | van Dijk, Winnie |
| Organizer of meeting | Schneider, Martin |
| Organizer of meeting | Tsivanidis, Nick |
Subjects
| Subject | economics |
|---|---|
| Genre | Text |
| Genre | Working paper |
| Genre | Grey literature |
Bibliographic information
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- License
- This work is licensed under a Creative Commons Attribution 4.0 International license (CC BY).
Preferred citation
- Preferred citation
- Borusyak, K. and Hull, P. (2022). Non-Random Exposure to Exogenous Shocks: Theory and Application. Stanford Digital Repository. Available at https://purl.stanford.edu/yd742pm1922
Collection
SITE Conference 2021
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