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An analysis on the determinants of brain-drain using bivariate probit model
Journal of the Korean Data & Information Science Society 2019;30:23-31
Published online January 31, 2019;  https://doi.org/10.7465/jkdi.2019.30.1.23
© 2019 Korean Data and Information Science Society.

Sungik Park1 · Jangsik Cho2

1International Trade and Commerce, Kyungsung University
2Division of Mathematics and Applied Statistics, Kyungsung University
Correspondence to: Professor, Division of Mathematics and Applied Statistics, Kyungsung University, Busan 48434, Korea. E-mail: jscho@ks.ac.kr
Received December 26, 2018; Revised January 11, 2019; Accepted January 11, 2019.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In general, only the employed are under study to analyze the determinants of brain-drain. In this way, the selection of samples for the employed will result in a sample selection bias by excluding the research subjects from the population systematically. In this study, we use bivariate probit model with sample selection to solve the problem of sample selection bias. The main results of the analysis are summarized as follows. First, we note that the bivariate probit model with sample selection used to analyze the determinants of brain-drain is statistically significant. Second, the probabilities of male employment and male brain-drain were higher than those of female. However, as the age increases, the probability of employment is high, but the probability of brain-drain is low. Third, the probability of university graduate employment was lower than that of college graduates, but the probability of brain-drain was higher. Finally, the probability of brain-drain in the Seoul metropolitan area is relatively low compared to other areas in the university location, and the probability of brain-drain is higher as the wage and company size increase.
Keywords : Bivariate probit model, brain-drain, sample selection bias, simple probit model.