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Censoring of Outcomes and Regressors Due To Survey Nonresponse: Identification and Estimation Using Weights and Imputations

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Author Info

  • Joel L. Horowitz

    (U. of Iowa)

  • Charles F. Manski

Abstract

Survey nonresponse makes identification of population statistics problematic. Except in special cases, identification is possible only if one makes untestable assumptions about the distribution of the missing data. However, non-response does not preclude identification of bounds on population statistics. This paper shows how identified bounds on unidentified population statistics can be obtained under several forms of nonresponse. Organizations conducting major surveys commonly release public-use data files that provide nonresponse weights or imputations to be used for estimating population statistics. The paper shows how to bound the asymptotic bias of estimates using weights and imputations. The results are illustrated with empirical examples based on the National Longitudinal Survey of Youth.

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File URL: http://128.118.178.162/eps/em/papers/9602/9602007.pdf
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Bibliographic Info

Paper provided by EconWPA in its series Econometrics with number 9602007.

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Length: 40 pages
Date of creation: 28 Feb 1996
Date of revision: 06 Mar 1996
Handle: RePEc:wpa:wuwpem:9602007

Note: Zipped using PKZIP v2.04, encoded using UUENCODE v5.15. Zipped file includes 1 files -- ui9512.wpa (TEX, 40 pages);
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  1. repec:att:wimass:9217 is not listed on IDEAS
  2. Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, vol. 63(2), pages 281-302, March.
  3. Manski, C.F., 1990. "The Selection Problem," Working papers 90-12, Wisconsin Madison - Social Systems.
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