Author
Listed:
- Yuehao Bai
- Jizhou Liu
- Max Tabord‐Meehan
Abstract
This paper studies inference in randomized controlled trials with multiple treatments, where treatment status is determined according to a “matched tuples” design. If there are |D| possible treatments, then 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 of size |D|, and finally, within each block, exactly one individual is randomly assigned to each of the |D| treatments. 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 that may be of interest in the analysis of factorial designs. We first establish conditions under which a sample analog estimator is asymptotically normal and construct a consistent estimator of its corresponding asymptotic variance. Combining these results establish 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 is generally invalid. We go on to apply our results to study the asymptotic properties of what we call “fully‐blocked” 2K 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.
Suggested Citation
Yuehao Bai & Jizhou Liu & Max Tabord‐Meehan, 2024.
"Inference for matched tuples and fully blocked factorial designs,"
Quantitative Economics, Econometric Society, vol. 15(2), pages 279-330, May.
Handle:
RePEc:wly:quante:v:15:y:2024:i:2:p:279-330
DOI: 10.3982/QE2354
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:quante:v:15:y:2024:i:2:p:279-330. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/essssea.html .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.