Yuehao Bai, Hongchang Guo, Azeem M. Shaikh, Max Tabord-Meehan
arXiv 24 Jul 2023 · Econometrics · publishedJournal of Business and Economic Statistics (2024)
arXiv:2307.13094 · PDF · DOI · OpenAlex · Extracted main text
This paper studies inference for the local average treatment effect in randomized controlled trials with imperfect compliance where treatment status is determined according to "matched pairs." By "matched pairs," we mean that units are sampled i.i.d. from the population of interest, paired according to observed, baseline covariates and finally, within each pair, one unit is selected at random for treatment. Under weak assumptions governing the quality of the pairings, we first derive the limit distribution of the usual Wald (i.e., two-stage least squares) estimator of the local average treatment effect. We show further that conventional heteroskedasticity-robust estimators of the Wald estimator's limiting variance are generally conservative, in that their probability limits are (typically strictly) larger than the limiting variance. We therefore provide an alternative estimator of the limiting variance that is consistent. Finally, we consider the use of additional observed, baseline covariates not used in pairing units to increase the precision with which we can estimate the local average treatment effect. To this end, we derive the limiting behavior of a two-stage least squares estimator of the local average treatment effect which includes both the additional covariates in addition to pair fixed effects, and show that its limiting variance is always less than or equal to that of the Wald estimator. To complete our analysis, we provide a consistent estimator of this limiting variance. A simulation study confirms the practical relevance of our theoretical results. Finally, we apply our results to revisit a prominent experiment studying the effect of macroinsurance on microenterprise in Egypt.
appendix boundary found by appendix_command · 62% 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 | Groh, M. and McKenzie, D (2016) Macroinsurance for microenterprises: A randomized experiment in post-revolution egypt | 1.000 | 10 | 4 | 100% |
| 2 | Bai, Y., Liu, J., Shaikh, A. M. and Tabord-Meehan, M (2023) On the efficiency of finely stratified experiments self | 0.928 | 4 | 3 | 100% |
| 3 | Bai, Y., Romano, J. P. and Shaikh, A. M (2022) Inference in experiments with matched pairs self | 0.888 | 20 | 6 | 70% |
| 4 | Bai, Y., Jiang, L., Romano, J. P., Shaikh, A. M. and Zhang, Y (2023) Covariate adjustment in experiments with matched pairs self | 0.885 | 13 | 4 | 69% |
| 5 | Resnjanskij, S., Ruhose, J., Wiederhold, S. and Woessmann, L (2021) Can mentoring alleviate family disadvantage in adolscence? a field experiment to improve labor-market prospects | 0.843 | 3 | 3 | 100% |
| 6 | Bai, Y., Liu, J. and Tabord-Meehan, M (2023) Inference for Matched Tuples and Fully Blocked Factorial Designs self | 0.644 | 2 | 2 | 100% |
| 7 | Glennerster, R. and Takavarasha, K (2014) Running randomized evaluations: A practical guide | 0.644 | 2 | 2 | 100% |
| 8 | Frölich, M (2007) Nonparametric iv estimation of local average treatment effects with covariates | 0.511 | 4 | 2 | 25% |
| 9 | Imbens, G. W. and Angrist, J. D (1994) Identification and estimation of local average treatment effects | 0.511 | 2 | 1 | 100% |
| 10 | Athey, S. and Imbens, G. W (2017) The econometrics of randomized experiments | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 22 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.