Testing for the Unconfoundedness Assumption Using an Instrumental Assumption

Xavier de Luna () and Per Johansson
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Xavier de Luna: Department of Statistics, Umeå School of Business and Economics, Umeå University, SE-90187 Umeå, Sweden

Journal of Causal Inference, 2014, vol. 2, issue 2, 187-199

Abstract: The identification of average causal effects of a treatment in observational studies is typically based either on the unconfoundedness assumption (exogeneity of the treatment) or on the availability of an instrument. When available, instruments may also be used to test for the unconfoundedness assumption. In this paper, we present a set of assumptions on an instrumental variable which allows us to test for the unconfoundedness assumption, although they do not necessarily yield nonparametric identification of an average causal effect. We propose a test for the unconfoundedness assumption based on the instrumental assumptions introduced and give conditions under which the test has power. We perform a simulation study and apply the results to a case study where the interest lies in evaluating the effect of job practice on employment.

Keywords: average treatment effect; job practice; nonparametric identification (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:bpj:causin:v:2:y:2014:i:2:p:13:n:2

DOI: 10.1515/jci-2013-0011

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