arXiv 3 Jun 2023 · Econometrics
arXiv:2306.01969 · PDF · DOI · OpenAlex · Extracted main text
Policy evaluation in empirical microeconomics has been focusing on estimating the average treatment effect and more recently the heterogeneous treatment effects, often relying on the unconfoundedness assumption. We propose a method based on the interactive fixed effects model to estimate treatment effects at the individual level, which allows both the treatment assignment and the potential outcomes to be correlated with the unobserved individual characteristics. This method is suitable for panel datasets where multiple related outcomes are observed for a large number of individuals over a small number of time periods. Monte Carlo simulations show that our method outperforms related methods. To illustrate our method, we provide an example of estimating the effect of health insurance coverage on individual usage of hospital emergency departments using the Oregon Health Insurance Experiment data.
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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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Hsiao, C., Steve Ching, H., and Ki Wan, S (2012) A panel data approach for program evaluation: measuring the benefits of political and economic integration of Hong Kong with mai… | 1.000 | 9 | 3 | 100% |
| 2 | Xu, Y (2017) Generalized synthetic control method: Causal inference with interactive fixed effects models | 1.000 | 9 | 3 | 100% |
| 3 | Abadie, A., Diamond, A., and Hainmueller, J (2010) Synthetic control methods for comparative case studies: Estimating the effect of california’s tobacco control program | 1.000 | 5 | 3 | 100% |
| 4 | Bai, J (2009) Panel data models with interactive fixed effects | 0.928 | 4 | 3 | 100% |
| 5 | Li, K. T. and Bell, D. R (2017) Estimation of average treatment effects with panel data: Asymptotic theory and implementation | 0.843 | 4 | 3 | 75% |
| 6 | Taubman, S. L., Allen, H. L., Wright, B. J., Baicker, K., and Finkel… (2014) Medicaid increases emergency-department use: evidence from Oregon's Health Insurance Experiment | 0.644 | 4 | 1 | 100% |
| 7 | Finkelstein, A., Taubman, S., Wright, B., Bernstein, M., Gruber, J.,… (2012) The Oregon Health Insurance Experiment: evidence from the first year | 0.511 | 2 | 1 | 100% |
| 8 | Abadie, A., Diamond, A., and Hainmueller, J (2015) Comparative politics and the synthetic control method | 0.405 | 1 | 1 | 100% |
| 9 | Abadie, A. and Cattaneo, M. D (2018) Econometric methods for program evaluation | 0.405 | 1 | 1 | 100% |
| 10 | Acemoglu, D., Johnson, S., Robinson, J. A., and Yared, P (2008) Income and democracy | 0.405 | 1 | 1 | 100% |
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