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On Policy Evaluation with Aggregate Time-Series Shocks

Dmitry Arkhangelsky, Vasily Korovkin

arXiv 31 May 2019 · Econometrics · 3 citations (OpenAlex)

arXiv:1905.13660 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We develop an estimator for applications where the variable of interest is endogenous and researchers have access to aggregate instruments. Our method addresses the critical identification challenge -- unobserved confounding, which renders conventional estimators invalid. Our proposal relies on a new data-driven aggregation scheme that eliminates the unobserved confounders. We illustrate the advantages of our algorithm using data from Nakamura and Steinsson (2014) study of local fiscal multipliers. We introduce a finite population model with aggregate uncertainty to analyze our estimator. We establish conditions for consistency and asymptotic normality and show how to use our estimator to conduct valid inference.

Citation extraction

37
references
107
in-text mentions
37
distinct cited
2
self-citations
17,071
main-text words

appendix boundary found by appendix_command · 60% of the source is main text. Read the extracted text to check this.

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
1Rodrigo Adao, Michal Kolesár, and Eduardo Morales (2019) Shift-share designs: Theory and inference1.00063100%
2Guido W Imbens and Joshua D Angrist (1994) Identification and estimation of local average treatment effects1.00063100%
3Kirill Borusyak, Peter Hull, and Xavier Jaravel (2022) Quasi-experimental shift-share research designs1.00053100%
4Adam M Guren, Alisdair McKay, Emi Nakamura, and Jón Steinsson (2020) Housing wealth effects: The long view1.00053100%
5Emi Nakamura and Jon Steinsson (2014) Fiscal stimulus in a monetary union: Evidence from us regions0.95229786%
6Gabriel Chodorow-Reich, Plamen T Nenov, and Alp Simsek (2021) Stock market wealth and the real economy: A local labor market approach0.84333100%
7Guido W Imbens and Davide Viviano (2023) Identification and inference for synthetic controls with confounding0.81142100%
8Alberto Abadie, Susan Athey, Guido W Imbens, and Jeffrey M Wooldridge (2023) When should you adjust standard errors for clustering?0.73732100%
9Jushan Bai (2009) Panel data models with interactive fixed effects0.73732100%
10Kirill Borusyak and Peter Hull (2023) Nonrandom exposure to exogenous shocks0.73732100%

Showing the top 10 of 37 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
1Forecasted Treatment Effects with Short Panels0.40511
2Causal Models for Longitudinal and Panel Data: A Survey0.40511
3Microfoundations and the Causal Interpretation of Price-Exposure Designs0.40511