Scandinavian Working Papers in Economics

Working Paper Series,
IFAU - Institute for Evaluation of Labour Market and Education Policy

No 2016:12: Proxy variables and nonparametric identification of causal effects

Xavier de Luna , Philip Fowler () and Per Johansson
Additional contact information
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.

Keywords: average treatment effect; observational studies; potential outcomes; unobserved confounders

JEL-codes: C14

10 pages, June 30, 2016

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