From LATE to ATE
A Bayesian Approach
Published Dec 28, 2023
We develop a Bayesian model that produces a posterior distribution of the marginal treatment effect (MTE) function. The method can be used even when the MTEs are not identified — as is the case in RCTs with imperfect compliance — thereby producing posterior distributions of unidentified estimands such at the overall average treatment effect (ATE) or the average effect on the always takers. While we focus on the case of RCTs with imperfect compliance, the model is general and allows for non-binary instruments and/or additional exogenous variables. Using the model, we show for the Oregon Health Insurance Experiment that the main source of the uncertainty in the ATE is not uncertainty due to the non-identifiability of the full MTE function and instead traditional statistical uncertainty, i.e., uncertainty in the true values of the observed moments due to the finite sample-size.
Topics
Document Details
- Copyright: RAND Corporation
- Availability: Web-Only
- Year: 2023
- Pages: 53
- DOI: https://doi.org/10.7249/WRA2499-1-v2
- Document Number: WR-A2499-1-v2
Citation
RAND Style Manual
Chicago Manual of Style
Opper, Isaac M., From LATE to ATE: A Bayesian Approach, RAND Corporation, WR-A2499-1-v2, 2023. As of September 24, 2024: https://www.rand.org/pubs/working_papers/WRA2499-1-v2.html
Opper, Isaac M., From LATE to ATE: A Bayesian Approach. Santa Monica, CA: RAND Corporation, 2023. https://www.rand.org/pubs/working_papers/WRA2499-1-v2.html.
Research conducted by
Funding for this research was provided by gifts from RAND supporters and income from operations. The research was conducted within RAND Education and Labor.
This publication is part of the RAND working paper series. RAND working papers are intended to share researchers' latest findings and to solicit informal peer review. They have been approved for circulation by RAND but may not have been formally edited or peer reviewed.
This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited; linking directly to this product page is encouraged. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial purposes. For information on reprint and reuse permissions, please visit www.rand.org/pubs/permissions.
RAND is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.