Estimating Difference-in-Differences in Time-To-Event Models: Some Simulation Results

30 Pages Posted: 30 May 2024

See all articles by David A. Hsieh

David A. Hsieh

Duke University - Fuqua School of Business; Duke University - Department of Economics; National Bureau of Economic Research (NBER)

Date Written: May 30, 2024

Abstract

This paper uses a simulation experiment to compare the distributional properties of three estimators for the difference-indifferences in time-to-event models. When events are observed in continuous time and subject heterogeneity are observed, the Cox (1972) estimator is the appropriate estimator. When events are observed in fixed time intervals, and subject heterogeneity is not observed, the same estimator is biased. The non-parametric maximum likelihood estimator (which corrects for fixed interval sampling and unobserved heterogeneity) is nearly unbiased. The linear probability estimator is severely biased and can have the wrong sign in some cases.

Keywords: time-to-event models, survival models, difference-in-differences estimation, competing risks, maximum likelihood estimation, proportional hazard models

Suggested Citation

Hsieh, David Arthur, Estimating Difference-in-Differences in Time-To-Event Models: Some Simulation Results (May 30, 2024). Available at SSRN: https://ssrn.com/abstract=4848953 or http://dx.doi.org/10.2139/ssrn.4848953

David Arthur Hsieh (Contact Author)

Duke University - Fuqua School of Business ( email )

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