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The wage determinants of college graduates using Heckman’s sample selection model
Journal of the Korean Data & Information Science Society 2017;28:1099-107
Published online September 30, 2017
© 2017 Korean Data & Information Science Society.

Jangsik Cho1

1Division of Mathematics and Applied Statistics, Kyungsung University
Correspondence to: Jangsik Cho
Professor, Division of Mathematics and Applied Statistics, Kyungsung University, Busan, 48434, Korea. E-mail : jscho@ks.ac.kr
Received August 21, 2017; Revised September 16, 2017; Accepted September 18, 2017.
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 this study, we analyzed the determinants of wages of college graduates by using the data of 「2014 Graduates Occupational Mobility Survey」conducted by Korea Employment Information Service. In general, wages contain two complex pieces of information about whether an individual is employed and the size of the wage. However, in many previous researches on wage determinants, sample selection bias tends to be generated by performing linear regression analysis using only information on wage size. We used the Heckman sample selection models for analysis to overcome this problem. The main results are summarized as follows. First, the validity of the Heckman’s sample selection model is statistically significant. Male is significantly higher in both job probability and wage than female. As age increases and parents’ income increases, both the probability of employment and the size of wages are higher. Finally, as the university satisfaction increases and the number of certifications acquired increased, both the probability of employment and the wage tends to increase.
Keywords : Censored data, Heckman’s sample selection model, Sample selection bias