An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls
Kaspar Wüthrich () and
Papers from arXiv.org
We introduce new inference procedures for counterfactual and synthetic control methods for policy evaluation. The proposed methods work in conjunction with many different approaches for predicting the counterfactual mean outcome in the absence of a policy intervention. Examples include difference-in-differences, synthetic controls, factor and matrix completion models, and (fused) time series panel data models. The proposed procedures are valid under weak and easy-to-verify conditions and are provably robust against misspecification. Our approach demonstrates an excellent small-sample performance in simulations and is taken to a data application where we re-evaluate the consequences of decriminalizing indoor prostitution.
New Economics Papers: this item is included in nep-ecm
Date: 2017-12, Revised 2019-07
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3) Track citations by RSS feed
Downloads: (external link)
http://arxiv.org/pdf/1712.09089 Latest version (application/pdf)
Working Paper: An exact and robust conformal inference method for counterfactual and synthetic controls (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1712.09089
Access Statistics for this paper
More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().