A Flexible Sample Selection Model: A GTL-Copula Approach
AbstractIn this paper, we propose a new approach to estimating sample selection models that combines Generalized Tukey Lambda (GTL) distributions with copulas. The GTL distribution is a versatile univariate distribution that permits a wide range of skewness and thick- or thin-tailed behavior in the data that it represents. Copulas help create versatile representations of bivariate distribution. The versatility arising from inserting GTL marginal distributions into copula-constructed bivariate distributions reduces the dependence of estimated parameters on distributional assumptions in applied research. A thorough Monte Carlo study illustrates that our proposed estimator performs well under normal and nonnormal settings, both with and without an instrument in the selection equation that fulfills the exclusion restriction that is often considered to be a requisite for implementation of sample selection models in empirical research. Five applications ranging from wages and health expenditures to speeding tickets and international disputes illustrate the value of the proposed GTL-copula estimator.
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Bibliographic InfoPaper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 7003.
Length: 63 pages
Date of creation: Nov 2012
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Find related papers by JEL classification:
- C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models
- C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
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