Xavier de Luna
, Philip Fowler
() and Per Johansson
Xavier de Luna: Department of statistics, USBE, Umeå University, Postal: Umeå, Sweden
Philip Fowler: Department of statistics, USBE, Umeå University, Postal: Umeå, Sweden
Per Johansson: Department of statistics, Uppsala University; The Institute for the Study of Labor IZA, Bonn, Germany; IFAU, Postal: Institute for Evaluation of Labour Market and Education Policy, P O Box 513, SE-751 20 Uppsala, Sweden
Abstract: Proxy variables are often used in linear regression models with the aim of removing potential confounding bias. In this paper we formalise proxy variables within the potential outcome framework, giving conditions under which it can be shown that causal effects are nonparametrically identified. We characterise two types of proxy variables and give concrete examples where the proxy conditions introduced may hold by design.
10 pages, June 30, 2016
Full text files
Questions (including download problems) about the papers in this series should be directed to Monica Fällgren ()
Report other problems with accessing this service to Sune Karlsson ().
This page generated on 2018-01-23 23:33:42.