Yuehao Bai, Jizhou Liu, Max Tabord-Meehan
arXiv 8 Jun 2022 · Econometrics · publishedQuantitative Economics (2024) · 6 citations (OpenAlex)
arXiv:2206.04157 · PDF · DOI · OpenAlex · Extracted main text
This paper studies inference in randomized controlled trials with multiple treatments, where treatment status is determined according to a "matched tuples" design. Here, by a matched tuples design, we mean an experimental design where units are sampled i.i.d. from the population of interest, grouped into "homogeneous" blocks with cardinality equal to the number of treatments, and finally, within each block, each treatment is assigned exactly once uniformly at random. We first study estimation and inference for matched tuples designs in the general setting where the parameter of interest is a vector of linear contrasts over the collection of average potential outcomes for each treatment. Parameters of this form include standard average treatment effects used to compare one treatment relative to another, but also include parameters which may be of interest in the analysis of factorial designs. We first establish conditions under which a sample analogue estimator is asymptotically normal and construct a consistent estimator of its corresponding asymptotic variance. Combining these results establishes the asymptotic exactness of tests based on these estimators. In contrast, we show that, for two common testing procedures based on t-tests constructed from linear regressions, one test is generally conservative while the other generally invalid. We go on to apply our results to study the asymptotic properties of what we call "fully-blocked" 2^K factorial designs, which are simply matched tuples designs applied to a full factorial experiment. Leveraging our previous results, we establish that our estimator achieves a lower asymptotic variance under the fully-blocked design than that under any stratified factorial design which stratifies the experimental sample into a finite number of "large" strata. A simulation study and empirical application illustrate the practical relevance of our results.
appendix boundary found by appendix_command · 52% 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 | Li, X., Ding, P. and Rubin, D. B (2020) Rerandomization in $2^K$ factorial experiments | 1.000 | 6 | 3 | 100% |
| 2 | Fafchamps, M., McKenzie, D., Quinn, S. and Woodruff, C (2014) Microenterprise growth and the flypaper effect: Evidence from a randomized experiment in ghana | 0.961 | 9 | 5 | 89% |
| 3 | Dasgupta, T., Pillai, N. S. and Rubin, D. B (2015) Causal inference from $2^k$ factorial designs by using potential outcomes | 0.950 | 7 | 3 | 86% |
| 4 | Branson, Z., Dasgupta, T. and Rubin, D. B (2016) Improving covariate balance in 2K factorial designs via rerandomization with an application to a New York City Department of Edu… | 0.909 | 8 | 4 | 75% |
| 5 | Bai, Y., Romano, J. P. and Shaikh, A. M (2021) Inference in Experiments with Matched Pairs* self | 0.814 | 26 | 6 | 54% |
| 6 | Wu, C. J. and Hamada, M. S (2011) Experiments: planning, analysis, and optimization, vol. 552 | 0.811 | 4 | 2 | 100% |
| 7 | Bai, Y (2022) Optimality of Matched-Pair Designs in Randomized Controlled Trials self | 0.794 | 6 | 4 | 50% |
| 8 | de Chaisemartin, C. and Ramirez-Cuellar, J (2022) At what level should one cluster standard errors in paired and small-strata experiments? | 0.737 | 3 | 2 | 100% |
| 9 | de Mel, S., McKenzie, D. and Woodruff, C (2013) The demand for, and consequences of, formalization among informal firms in sri lanka | 0.644 | 2 | 2 | 100% |
| 10 | Athey, S. and Imbens, G. W (2017) The econometrics of randomized experiments | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 30 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.