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기술직에서 이공계학위와 인적자원요소의 가치평가 : 미국사례 KCI 등재

Science & Engineering Degrees and Human Resource Element Value Estimation in Technology Jobs : the US Case

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한국산업경영시스템학회지 (Journal of Society of Korea Industrial and Systems Engineering)
한국산업경영시스템학회 (Society of Korea Industrial and Systems Engineering)
초록

In the international businesses human resource elements acquired in different countries might have different values in varied industries due to the different quality of education and experiences in the original countries. Using selection models to evaluate expected values in earnings equation of human resource elements such as education and experiences etc. acquired in sending countries, system equations are expanded to examine also the values of science and engineering degrees in technology jobs with selectivity bias correction. This paper used the US census survey data of 2015 on earnings, academic degrees, occupations etc. The US has long maintained the policy of accepting more STEM workers than any other countries and helped maintaining own technological leadership. Assuming per capita GDP gap between the sending country and the US downgrades immigrant human resource quality, it rarely affects occupational selection but depresses earnings on average by two or more years’ worth of education. Immigrant quality index in the sense of GDP gap appears to be a valid tool to assess the expected earnings of the worker with. Engineering degrees increase significantly the probability of selecting not only engineering jobs but also general management jobs, as well as increasing the expected earning additionally over nine years’worth of education. Getting a technology job is additionally worth about four years of education. Economics and business degrees are worth additionally almost six years of education but humanities degrees depress expected earnings. Since years after immigration does not very fast enhance earnings capacity, education level and English language ability might be more useful criteria to expect better future earnings by.

목차
1. 서 론
 2. 배경과 기존연구
 3. 모델과 데이터
 4. 직업과 소득분석
 5. 결 론
 Acknowledge
 References
저자
  • 이세재(금오공과대학교 산업공학부) | Sae Jae Lee (School of Industrial Engineering, Kumoh National Insitute of Technology)
  • 이현수(금오공과대학교 산업공학부) | Hyun Soo Lee (School of Industrial Engineering, Kumoh National Insitute of Technology) Corresponding author