Optimally Combining Censored and Uncensored Datasets
Abstract
Economists and other social scientists often face situations where they have access to two datasets that they can use but one set of data suffers from censoring or truncation. If the censored sample is much bigger than the uncensored sample, it is common for researchers to use the censored sample alone and attempt to deal with the problem of partial observation in some manner. Alternatively, they simply use only the uncensored sample and ignore the censored one so as to avoid biases. It is rarely the case that researchers use both datasets together, mainly because they lack guidance about how to combine them. In this paper, we develop a simple semiparametric framework for combining the censored and uncensored datasets 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. We also demonstrate how refreshment samples for this application can be created by combining cohort information across census datasets. Results from a small simulation experiment suggest that the estimator proposed in this paper can work very well in finite samples.Download Info
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Paper provided by University of Connecticut, Department of Economics in its series Working papers with number 2005-10.Length: 49 pages
Date of creation: Apr 2005
Date of revision: Oct 2007
Handle: RePEc:uct:uconnp:2005-10
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Related research
Keywords: Censoring; Empirical Likelihood; GMM; Refreshment samples; Truncation;Other versions of this item:
- Devereux, Paul J. & Tripathi, Gautam, 2009. "Optimally combining censored and uncensored datasets," Journal of Econometrics, Elsevier, vol. 151(1), pages 17-32, July.
- Paul J. Devereux & Gautam Tripathi, 2008. "Optimally combining Censored and Uncensored Datasets," Working Papers 200820, School Of Economics, University College Dublin.
- Devereux, Paul J. & Tripathi, Gautam, 2008. "Optimally Combining Censored and Uncensored Datasets," CEPR Discussion Papers 6990, C.E.P.R. Discussion Papers.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models
- C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-06-03 (All new papers)
- NEP-ECM-2006-06-03 (Econometrics)
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Maria K. Humlum & Jannie H.G. Kristoffersen & Rune Vejlin, 2012. "Timing of College Enrollment and Family Formation Decisions," Economics Working Papers 2012-01, School of Economics and Management, University of Aarhus.
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