A Bracketing Relationship for Long-Term Policy Evaluation with Combined Experimental and Observational Data
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| Format: | Preprint |
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2024
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| _version_ | 1866910304777011200 |
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| author | Park, Yechan Sasaki, Yuya |
| author_facet | Park, Yechan Sasaki, Yuya |
| contents | Combining short-term experimental data with observational data enables credible long-term policy evaluation. The literature offers two key but non-nested assumptions, namely the latent unconfoundedness (LU; Athey et al., 2020) and equi-confounding bias (ECB; Ghassami et al., 2022) conditions, to correct observational selection. Committing to the wrong assumption leads to biased estimation. To mitigate such risks, we provide a novel bracketing relationship (cf. Angrist and Pischke, 2009) repurposed for the setting with data combination: the LU-based estimand and the ECB-based estimand serve as the lower and upper bounds, respectively, with the true causal effect lying in between if either assumption holds. For researchers further seeking point estimates, our Lalonde-style exercise suggests the conservatively more robust LU-based lower bounds align closely with the hold-out experimental estimates for educational policy evaluation. We investigate the economic substantives of these findings through the lens of a nonparametric class of selection mechanisms and sensitivity analysis. We uncover as key the sub-martingale property and sufficient-statistics role (Chetty, 2009) of the potential outcomes of student test scores (Chetty et al., 2011, 2014). |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2401_12050 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Bracketing Relationship for Long-Term Policy Evaluation with Combined Experimental and Observational Data Park, Yechan Sasaki, Yuya Econometrics Combining short-term experimental data with observational data enables credible long-term policy evaluation. The literature offers two key but non-nested assumptions, namely the latent unconfoundedness (LU; Athey et al., 2020) and equi-confounding bias (ECB; Ghassami et al., 2022) conditions, to correct observational selection. Committing to the wrong assumption leads to biased estimation. To mitigate such risks, we provide a novel bracketing relationship (cf. Angrist and Pischke, 2009) repurposed for the setting with data combination: the LU-based estimand and the ECB-based estimand serve as the lower and upper bounds, respectively, with the true causal effect lying in between if either assumption holds. For researchers further seeking point estimates, our Lalonde-style exercise suggests the conservatively more robust LU-based lower bounds align closely with the hold-out experimental estimates for educational policy evaluation. We investigate the economic substantives of these findings through the lens of a nonparametric class of selection mechanisms and sensitivity analysis. We uncover as key the sub-martingale property and sufficient-statistics role (Chetty, 2009) of the potential outcomes of student test scores (Chetty et al., 2011, 2014). |
| title | A Bracketing Relationship for Long-Term Policy Evaluation with Combined Experimental and Observational Data |
| topic | Econometrics |
| url | https://arxiv.org/abs/2401.12050 |