TY - JOUR AU - Engberg,John AU - Epple,Dennis AU - Imbrogno,Jason AU - Sieg,Holger AU - Zimmer,Ron TI - Estimation of Causal Effects in Experiments with Multiple Sources of Noncompliance JF - National Bureau of Economic Research Working Paper Series VL - No. 14842 PY - 2009 Y2 - April 2009 UR - http://www.nber.org/papers/w14842 L1 - http://www.nber.org/papers/w14842.pdf N1 - Author contact info: John Engberg Rand Corporation 4570 5th Avenue Pittsburgh, PA 15213 E-Mail: engberg@rand.org Dennis N. Epple Tepper School of Business Carnegie Mellon University Posner Hall, Room 257B Pittsburgh, PA 15213 Tel: 412/268-1536 Fax: 412/268-7357 E-Mail: epple@cmu.edu Jason Imbrogno Tepper School of Business Carnegie Mellon University Pittsburgh, PA 15213 E-Mail: jpi@cmu.edu Holger Sieg Department of Economics University of Pennsylvania 3718 Locust Walk Philadelphia, PA 19104 Tel: 215 898 7194 Fax: 215-573-2057 E-Mail: holgers@econ.upenn.edu Ron Zimmer Erickson Hall Michigan State University East Lansing, MI 48824 E-Mail: rzimmer@msu.edu AB - 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. ER -