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Discussion on: Instrumented difference-in-differences, by Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy and Dylan S. Small

DiazOrdaz, K; (2022) Discussion on: Instrumented difference-in-differences, by Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy and Dylan S. Small. Biometrics 10.1111/biom.13785. (In press). Green open access

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Abstract

I discuss the assumptions needed for identification of average treatment effects and local average treatment effects in instrumented difference-in-differences (IDID), and the possible trade-offs between assumptions of standard IV and those needed for the new proposal IDID, in one- and two-sample settings. I also discuss the interpretation of the estimands identified under monotonicity. I conclude by suggesting possible extensions to the estimation method, by outlining a strategy to use data-adaptive estimation of the nuisance parameters, based on recent developments.

Type: Article
Title: Discussion on: Instrumented difference-in-differences, by Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy and Dylan S. Small
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1111/biom.13785
Publisher version: https://doi.org/10.1111/biom.13785
Language: English
Additional information: © 2022 The Authors. Biometrics published by Wiley Periodicals LLC on behalf of International Biometric Society. This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/).
Keywords: causal inference, causal machine learning, difference in difference, instrumental variables
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10167840
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