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Two-way fixed effects instrumental variable regressions in staggered DID-IV designs

Sho Miyaji

arXiv 26 May 2024 · Econometrics · 1 citations (OpenAlex)

arXiv:2405.16467 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Many studies run two-way fixed effects instrumental variable (TWFEIV) regressions, leveraging variation in the timing of policy adoption across units as an instrument for treatment. This paper studies the properties of the TWFEIV estimator in staggered instrumented difference-in-differences (DID-IV) designs. We show that in settings with the staggered adoption of the instrument across units, the TWFEIV estimator can be decomposed into a weighted average of all possible two-group/two-period Wald-DID estimators. Under staggered DID-IV designs, a causal interpretation of the TWFEIV estimand hinges on the stable effects of the instrument on the treatment and the outcome over time. We illustrate the use of our decomposition theorem for the TWFEIV estimator through an empirical application.

Citation extraction

30
references
140
in-text mentions
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distinct cited
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Miller and Segal (2019) Do female officers improve law enforcement quality? Effects on crime reporting and domestic violence1.000394100%
2Miyaji (2024) Instrumented Difference-in-Differences with heterogeneous treatment effects self1.000144100%
3de Chaisemartin and D'Haultfuille (2020) Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects1.00085100%
4Sun and Abraham (2021) Estimating dynamic treatment effects in event studies with heterogeneous treatment effects1.00075100%
5Callaway and Sant'Anna (2021) Difference-in-Differences with multiple time periods1.00054100%
6Goodman-Bacon (2021) Difference-in-differences with variation in treatment timing0.93522682%
7Imbens and Angrist (1994) Identification and Estimation of Local Average Treatment Effects0.92843100%
8Athey and Imbens (2022) Design-based analysis in Difference-In-Differences settings with staggered adoption0.84333100%
9Imai and Kim (2021) On the Use of Two-Way Fixed Effects Regression Models for Causal Inference with Panel Data0.84333100%
10de Chaisemartin and D'Haultfuille (2018) Fuzzy Differences-in-Differences0.81142100%

Showing the top 10 of 30 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Instrumented Difference-in-Differences with Heterogeneous Treatment Effects0.94164
2Triple Instrumented Difference-in-Differences0.40511