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Optimally combining Censored and Uncensored Datasets

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  • Paul J. Devereux

    (University College Dublin)

  • Gautam Tripathi

    (University of Connecticut)

Abstract

We develop a simple semiparametric framework for combining censored and uncensored samples so that the resulting estimators are consistent, asymptotically normal, and use all information optimally. No nonparametric smoothing is required to implement our estimators. To illustrate our results in an empirical setting, we show how to estimate the effect of changes in compulsory schooling laws on age at first marriage, a variable that is censored for younger individuals. Results from a small simulation experiment suggest that the estimator proposed in this paper can work very well in finite samples.

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File URL: http://www.ucd.ie/economics/research/papers/2008/WP08.20.pdf
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Bibliographic Info

Paper provided by School Of Economics, University College Dublin in its series Working Papers with number 200820.

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Length: 42 pages
Date of creation: 19 Sep 2008
Date of revision:
Handle: RePEc:ucn:wpaper:200820

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Cited by:
  1. Xiaohong Chen & Han Hong & Denis Nekipelov, 2011. "Nonlinear Models of Measurement Errors," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 901-37, December.
  2. Powdthavee, Nattavudh & Adireksombat, Kampon, 2010. "From Classroom to Wedding Aisle: The Effect of a Nationwide Change in the Compulsory Schooling Law on Age at First Marriage in the UK," IZA Discussion Papers 5019, Institute for the Study of Labor (IZA).
  3. Humlum, Maria Knoth & Kristoffersen, Jannie H. G. & Vejlin, Rune Majlund, 2014. "Timing of College Enrollment and Family Formation Decisions," IZA Discussion Papers 7905, Institute for the Study of Labor (IZA).

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