DOI QR코드

DOI QR Code

The wage determinants of college graduates using Heckman's sample selection model

Heckman의 표본선택모형을 이용한 대졸자의 임금결정요인 분석

  • Cho, Jangsik (Division of Mathematics and Applied Statistics, Kyungsung University)
  • 조장식 (경성대학교 수학응용통계학부)
  • Received : 2017.08.21
  • Accepted : 2017.09.18
  • Published : 2017.09.30

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.

본 연구에서는 한국고용정보원에서 실시한 "2014년 대졸자 직업이동 경로조사" 자료를 활용하여 대졸자의 임금결정요인을 분석하였다. 일반적으로 임금은 개인의 취업여부와 임금의 크기에 대한 두 가지의 복합적인 정보를 담고 있으나, 많은 선행연구에서는 임금의 크기에 대한 정보만을 활용하여 선형 회귀분석을 수행함으로써 표본선택에 위한 편의 (sample selection bias) 문제가 발생하게 된다. 이런 문제점을 극복하기 위해 본 연구에서는 Heckman의 표본선택 모형을 분석에 활용하였다. 주요 분석 결과를 요약하면 다음과 같다. 먼저 Heckman의 표본선택 모형에 대한 타당성은 통계적으로 유의함을 알 수 있었다. 남자는 여자에 비해서 취업확률과 임금의 크기 모두 통계적으로 유의하게 높게 나타났으며, 연령이 증가하고 부모의 소득이 증가 할수록 취업확률과 임금의 크기 모두 높게 나타났다. 또한 대학만족도가 높아질수록, 그리고 취득한 자격증 수가 증가할수록 취업확률과 임금 모두 증가하는 경향이 있는 것으로 나타났다.

Keywords

References

  1. Cho, J. S. (2011). Determinants of job finding using student's characteristic information. Journal of the Korean Data & Information Science Society, 22, 849-856.
  2. Green, W. (2003). Econometrics (5th edition), Prentice hall, New Jersey.
  3. Heckman, J. J. (1976). The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models. Annals of Economic and Social Measurement, 5, 475-492.
  4. Jung, J. S. and Kim, H. H. (2009). Analysis on the influential factors on private tutoring expenditure of Korean college students. The Journal of Economics and Finance of Education, 18, 89-122.
  5. Kim, H. H. (2011). An analysis of impacts of family income on financing experience and cumulative amount of student loan : Focusing on private junior college graduate. The Journal of Economics and Finance of Education, 20, 183-203.
  6. Lee, J. H., Kim, D. J. and Kim, J. (2016). Leave of absence and labor market performance: Focus on female college graduates under the age of 39. The Journal of Women and Economics, 13, 1-20.
  7. Park, S. I. and Cho, J. S. (2015). Determinants of employee’s wage using hierarchical linear model. Journal of the Korean Data & Information Science Society, 26, 65-75. https://doi.org/10.7465/jkdi.2015.26.1.65
  8. Park, S. I. and Cho, J. S. (2016). The wage determinants applying sample selection bias. Journal of the Korean Data & Information Science Society, 27, 1317-1325. https://doi.org/10.7465/jkdi.2016.27.5.1317
  9. Ryu, J. S. and Cho, J. S. (2016a). The employment path and employment determinants of the vocational high school graduates. Journal of Regional Studies, 24, 199-218.
  10. Ryu, J. S. and Cho, J. S. (2016b). The wage determinants of the vocational high school graduates using mixed effects model. Journal of the Korean Data & Information Science Society, 27, 935-946. https://doi.org/10.7465/jkdi.2016.27.4.935
  11. Tobin, J. (1958). Estimation of relationships for limited dependent variables. Econometrica, 26, 24-36. https://doi.org/10.2307/1907382