Yuehao Bai, Meng Hsuan Hsieh, Jizhou Liu, Max Tabord-Meehan
arXiv 23 Sep 2022 · Econometrics · publishedJournal of Applied Econometrics (2023) · 1 citations (OpenAlex)
arXiv:2209.11840 · PDF · DOI · OpenAlex · Extracted main text
In this paper we revisit some common recommendations regarding the analysis of matched-pair and stratified experimental designs in the presence of attrition. Our main objective is to clarify a number of well-known claims about the practice of dropping pairs with an attrited unit when analyzing matched-pair designs. Contradictory advice appears in the literature about whether or not dropping pairs is beneficial or harmful, and stratifying into larger groups has been recommended as a resolution to the issue. To address these claims, we derive the estimands obtained from the difference-in-means estimator in a matched-pair design both when the observations from pairs with an attrited unit are retained and when they are dropped. We find limited evidence to support the claims that dropping pairs helps recover the average treatment effect, but we find that it may potentially help in recovering a convex weighted average of conditional average treatment effects. We report similar findings for stratified designs when studying the estimands obtained from a regression of outcomes on treatment with and without strata fixed effects.
appendix boundary found by appendix_command · 55% of the source is main text. Read the extracted text to check this.
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 | Bruhn, M. and D. McKenzie (2009) In Pursuit of Balance: Randomization in Practice in Development Field Experiments | 0.928 | 5 | 3 | 80% |
| 2 | Groh, M. and D. McKenzie (2016) Macroinsurance for microenterprises: A randomized experiment in post-revolution Egypt | 0.874 | 10 | 2 | 100% |
| 3 | Glennerster, R. and K. Takavarasha (2013) Running Randomized Evaluations: A Practical Guide | 0.843 | 4 | 3 | 75% |
| 4 | Bugni, F. A., I. A. Canay, and A. M. Shaikh (2018) Inference Under Covariate-Adaptive Randomization | 0.843 | 5 | 3 | 60% |
| 5 | Bai, Y., J. P. Romano, and A. M. Shaikh (2021) Inference in Experiments with Matched Pairs* self | 0.769 | 11 | 3 | 45% |
| 6 | King, G., E. Gakidou, N. Ravishankar, R. T. Moore, J. Lakin, M. Varg… (2007) A “politically robust” experimental design for public policy evaluation, with application to the Mexican universal health insura… | 0.737 | 3 | 3 | 67% |
| 7 | Attanasio, O., S. Cattan, E. Fitzsimons, C. Meghir, and M. Rubio-Cod… (2020) Estimating the production function for human capital: results from a randomized controlled trial in Colombia | 0.644 | 3 | 2 | 67% |
| 8 | Casaburi, L. and T. Reed (2022) Using individual-level randomized treatment to learn about market structure | 0.644 | 3 | 2 | 67% |
| 9 | Hjort, J., D. Moreira, G. Rao, and J. F. Santini (2021) How research affects policy: Experimental evidence from 2,150 brazilian municipalities | 0.644 | 3 | 2 | 67% |
| 10 | Little, R. J. and D. B. Rubin (2019) Statistical analysis with missing data | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 39 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Inference for Two-stage Experiments under Covariate-Adaptive Randomization | 0.405 | 1 | 1 |
| 2 | A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances | 0.405 | 1 | 1 |
| 3 | Randomization Inference with Sample Attrition | 0.405 | 1 | 1 |