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Partial identification of the distribution of treatment effects and its confidence sets

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  • Fan, Yanqin
  • Park, Sang Soo

Abstract

In this paper, we study partial identification of the distribution of treatment effects of a binary treatment for ideal randomized experiments, ideal randomized experiments with a known value of a dependence measure, and for data satisfying the selection-on-observables assumption respectively. For ideal randomized experiments, (i) we propose nonparametric estimators of the sharp bounds on the distribution of treatment effects and construct asymptotically valid confidence sets for the distribution of treatment effects; (ii) we propose bias-corrected estimators of the sharp bounds on the distribution of treatment effects; and (iii) we investigate finite sample performances of the proposed confidence sets and the bias-corrected estimators via simulation.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 37148.

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Date of creation: 2009
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Handle: RePEc:pra:mprapa:37148

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Related research

Keywords: Confidence sets; partial identification; distribution; treatment effects;

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Citations

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Cited by:
  1. Matthew Gentry & Tong Li, 2012. "Identifcation in auctions with selective entry," CeMMAP working papers CWP38/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  2. Chiburis, Richard C., 2010. "Semiparametric bounds on treatment effects," Journal of Econometrics, Elsevier, vol. 159(2), pages 267-275, December.
  3. Fan, Yanqin & Park, Sang Soo, 2010. "Confidence sets for some partially identified parameters," MPRA Paper 37149, University Library of Munich, Germany.

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