Matthew Cefalu, Brian G. Vegetabile, Michael Dworsky, Christine Eibner, Federico Girosi
arXiv 9 Nov 2020 · Statistics — Methodology · 3 citations (OpenAlex)
arXiv:2011.04826 · PDF · DOI · OpenAlex · Extracted main text
This paper illustrates the use of entropy balancing in difference-in-differences analyses when pre-intervention outcome trends suggest a possible violation of the parallel trends assumption. We describe a set of assumptions under which weighting to balance intervention and comparison groups on pre-intervention outcome trends leads to consistent difference-in-differences estimates even when pre-intervention outcome trends are not parallel. Simulated results verify that entropy balancing of pre-intervention outcomes trends can remove bias when the parallel trends assumption is not directly satisfied, and thus may enable researchers to use difference-in-differences designs in a wider range of observational settings than previously acknowledged.
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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 | Daw, Jamie R, Hatfield, Laura A (2018) Matching and regression to the mean in difference-in-differences analysis | 0.935 | 11 | 5 | 82% |
| 2 | Hainmueller, Jens (2012) Entropy balancing for causal effects: A multivariate reweighting method to produce balanced samples in observational studies | 0.843 | 5 | 3 | 60% |
| 3 | Steiner, Peter M, Cook, Thomas D, Shadish, William R (2011) On the importance of reliable covariate measurement in selection bias adjustments using propensity scores | 0.737 | 3 | 3 | 67% |
| 4 | Stuart, Elizabeth A, Huskamp, Haiden A, Duckworth, Kenneth, Simmons,… (2014) Using propensity scores in difference-in-differences models to estimate the effects of a policy change | 0.737 | 3 | 2 | 100% |
| 5 | Eibner, Christine, Khodyakov, Dmitry, Taylor, Erin Audrey, Buttorff,… (2018) First Annual Evaluation Report of the Medicare Advantage Value-Based Insurance Design Model Test self | 0.693 | 8 | 2 | 50% |
| 6 | Rubin, Donald B (2005) Causal inference using potential outcomes: Design, modeling, decisions | 0.511 | 2 | 2 | 50% |
| 7 | Angrist, Joshua D (2008) Mostly harmless econometrics: An empiricist's companion | 0.511 | 2 | 1 | 100% |
| 8 | Arkhangelsky, Dmitry, Athey, Susan, Hirshberg, David A, Imbens, Guid… (2019) Synthetic difference in differences | 0.511 | 2 | 1 | 100% |
| 9 | (2015) Analysis of the bias of matching and difference-in-difference under alternative earnings and selection processes | 0.405 | 1 | 1 | 100% |
| 10 | Chernew, Michael E, Rosen, Allison B, Fendrick, A Mark (2007) Value-Based Insurance Design: By abandoning the archaic principle that all services must cost the same for all patients, we can… | 0.405 | 1 | 1 | 100% |
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