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A sample selection model with Skew-normal distribution
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Ogundimu, Emmanuel O. and Hutton, Jane (2015) A sample selection model with Skew-normal distribution. Scandinavian Journal of Statistics, 43 (1). pp. 172-190. doi:10.1111/sjos.12171 ISSN 0303-6898.
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Official URL: http://dx.doi.org/10.1111/sjos.12171
Abstract
Non-random sampling is a source of bias in empirical research. It is common for the outcomes of interest (e.g. wage distribution) to be skewed in the source population. Sometimes, the outcomes are further subjected to sample selection, which is a type of missing data, resulting in partial observability. Thus, methods based on complete cases for skew data are inadequate for the analysis of such data and a general sample selection model is required. Heckman proposed a full maximum likelihood estimation method under the normality assumption for sample selection problems, and parametric and non-parametric extensions have been proposed. We generalize Heckman selection model to allow for underlying skew-normal distributions. Finite-sample performance of the maximum likelihood estimator of the model is studied via simulation. Applications illustrate the strength of the model in capturing spurious skewness in bounded scores, and in modelling data where logarithm transformation could not mitigate the effect of inherent skewness in the outcome variable.
Item Type: | Journal Article | ||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||
Journal or Publication Title: | Scandinavian Journal of Statistics | ||||||
Publisher: | Wiley-Blackwell Publishing Ltd. | ||||||
ISSN: | 0303-6898 | ||||||
Official Date: | March 2015 | ||||||
Dates: |
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Volume: | 43 | ||||||
Number: | 1 | ||||||
Page Range: | pp. 172-190 | ||||||
DOI: | 10.1111/sjos.12171 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Restricted or Subscription Access |
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