Estimation of Causal Effects in Experiments with Multiple Sources of Noncompliance

35 Pages Posted: 7 Apr 2009 Last revised: 23 Jul 2010

See all articles by John Engberg

John Engberg

RAND Corporation

Dennis Epple

Carnegie Mellon University; National Bureau of Economic Research (NBER); CESifo (Center for Economic Studies and Ifo Institute)

Jason Imbrogno

Carnegie Mellon University - David A. Tepper School of Business

Holger Sieg

University of Pennsylvania - Department of Economics; National Bureau of Economic Research (NBER)

Ron Zimmer

Michigan State University

Date Written: April 2009

Abstract

The purpose of this paper is to study identification and estimation of causal effects in experiments with multiple sources of noncompliance. This research design arises in many applications in education when access to oversubscribed programs is partially determined by randomization. Eligible households decide whether or not to comply with the intended treatment. The paper treats program participation as the outcome of a decision process with five latent household types. We show that the parameters of the underlying model of program participation are identified. Our proofs of identification are constructive and can be used to design a GMM estimator for all parameters of interest. We apply our new methods to study the effectiveness of magnet programs in a large urban school district. Our findings show that magnet programs help the district to attract and retain students from households that are at risk of leaving the district. These households have higher incomes, are more educated, and have children that score higher on standardized tests than households that stay in district regardless of the outcome of the lottery.

Suggested Citation

Engberg, John B. and Epple, Dennis and Imbrogno, Jason and Sieg, Holger and Zimmer, Ron, Estimation of Causal Effects in Experiments with Multiple Sources of Noncompliance (April 2009). NBER Working Paper No. w14842. Available at SSRN: https://ssrn.com/abstract=1373350

John B. Engberg

RAND Corporation ( email )

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Dennis Epple (Contact Author)

Carnegie Mellon University ( email )

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National Bureau of Economic Research (NBER)

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CESifo (Center for Economic Studies and Ifo Institute) ( email )

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Jason Imbrogno

Carnegie Mellon University - David A. Tepper School of Business ( email )

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Holger Sieg

University of Pennsylvania - Department of Economics ( email )

Ronald O. Perelman Center for Political Science
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United States

National Bureau of Economic Research (NBER)

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Ron Zimmer

Michigan State University ( email )

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