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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

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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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Publisher 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

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Find related papers by JEL classification:
C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General
C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
C5 - Mathematical and Quantitative Methods - - Econometric Modeling
C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

References listed on IDEAS
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  1. Manski, C.F., 1990. "The Selection Problem," Working papers 90-12, Wisconsin Madison - Social Systems.
  2. repec:att:wimass:199217 is not listed on IDEAS
  3. 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. [Downloadable!] (restricted)
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