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Article

Estimating Endogenous Treatment Effects Using Latent Factor Models with and without Instrumental Variables

1
Department of Humanities and Social Sciences, Indian Institute of Technology Bombay, Mumbai 400076, India
2
The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, School of Pharmacy, University of Washington, Seattle, WA 98195, USA
*
Author to whom correspondence should be addressed.
Received: 6 November 2020 / Revised: 7 March 2021 / Accepted: 9 March 2021 / Published: 17 March 2021
(This article belongs to the Special Issue Health Econometrics)
We provide evidence on the least biased ways to identify causal effects in situations where there are multiple outcomes that all depend on the same endogenous regressor and a reasonable but potentially contaminated instrumental variable that is available. Simulations provide suggestive evidence on the complementarity of instrumental variable (IV) and latent factor methods and how this complementarity depends on the number of outcome variables and the degree of contamination in the IV. We apply the causal inference methods to assess the impact of mental illness on work absenteeism and disability, using the National Comorbidity Survey Replication. View Full-Text
Keywords: treatment effect; latent factor models; instrumental variable; mental illness; disability treatment effect; latent factor models; instrumental variable; mental illness; disability
MDPI and ACS Style

Banerjee, S.; Basu, A. Estimating Endogenous Treatment Effects Using Latent Factor Models with and without Instrumental Variables. Econometrics 2021, 9, 14. https://0-doi-org.brum.beds.ac.uk/10.3390/econometrics9010014

AMA Style

Banerjee S, Basu A. Estimating Endogenous Treatment Effects Using Latent Factor Models with and without Instrumental Variables. Econometrics. 2021; 9(1):14. https://0-doi-org.brum.beds.ac.uk/10.3390/econometrics9010014

Chicago/Turabian Style

Banerjee, Souvik, and Anirban Basu. 2021. "Estimating Endogenous Treatment Effects Using Latent Factor Models with and without Instrumental Variables" Econometrics 9, no. 1: 14. https://0-doi-org.brum.beds.ac.uk/10.3390/econometrics9010014

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