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Estimation of Causal Effects in Experiments with Multiple Sources of Noncompliance / John Engberg, Dennis Epple, Jason Imbrogno, Holger Sieg, Ron Zimmer.
- Format:
- Book
- Author/Creator:
- Engberg, John.
- Series:
- Working Paper Series (National Bureau of Economic Research) no. w14842.
- NBER working paper series no. w14842
- Language:
- English
- Physical Description:
- 1 online resource: illustrations (black and white);
- Place of Publication:
- Cambridge, Mass. National Bureau of Economic Research 2009.
- Summary:
- 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.
- Notes:
- Print version record
- April 2009.
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