Optimally combining censored and uncensored datasets

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Title: Optimally combining censored and uncensored datasets
Authors: Devereux, Paul J.
Tripathi, Gautam
Permanent link: http://hdl.handle.net/10197/744
Date: Sep-2008
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.
Type of material: Working Paper
Publisher: University College Dublin. School of Economics
Copyright (published version): UCD School of Economics 2008
Subject LCSH: Sampling (Statistics)
Economics--Statistical methods
Language: en
Status of Item: Not peer reviewed
Appears in Collections:Economics Working Papers & Policy Papers

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