기술직에서 이공계학위와 인적자원요소의 가치평가 : 미국사례
Science & Engineering Degrees and Human Resource Element Value Estimation in Technology Jobs : the US Case
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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.
Abstract
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.
참고문헌 (16)
- Astebro, T., "Entrepreneurs, Jacks of all trades or Hobos?", Research policy, 40(5), pp.637~649 (2011)
- Beede, D. N., "Women in STEM : A Gender Gap to Innovation, Economics and Statistics Administration Issue Brief No. 04-11", U.S. Department of Commerce, ~ (2011)
- Carnevale, A. P., "The Economic Value of College Majors", Georgetown University Center for Education and the Workforce (2015)
- Coulombe, S., "Human capital quality and the immigrant wage gap", IZA Journal of Migration, 3(1), pp.1~22 (2014)
- Coulombe, S., "Quality of Work Experience and Economic Development : Estimates Using Canadian Immigrant Data", Journal of Human Capital, 8(3), pp.199~234 (2014)
- De Vries, R., "Earnings by Degrees", UK Workforce, ~ (2014)
- Greene, W., "Econometric Analysis" (1991), MacMillan
- 한성신, "한국의 교육투자수익률 및 학위효과: 남녀 비교", 노동경제논집, 30(1), pp.1~30 (2007), 한국노동경제학회
- Skilled Immigration and the Employment Structures of U.S. Firms, "Kerr, S. P.", Harvard Business School, ~, pp.Harvard Business School Working Papers, No. 14-040 (2013)
- 이세재, "이민의 직업선택모델 비교연구：미국의 과학기술직 사례", 산업경영시스템학회지, 29(2), pp.37~42 (2006), 한국산업경영시스템학회
- McNeely, C.L., "The Global Chase for Innovation : Is STEM Education the Catalyst?", Global Studies Review, 8(1), pp.1~ (2012)
- Peri, G., "Highly-Educated Immigrants and Native Occupational Choice", Industrial Relations, 50(3), pp.385~411 (2011)
- Foreign STEM Workers and Native Wages and Employment in U.S. Cities, "Peri, G.", NBER, ~, pp.NBER Working Paper, No. 20093 (2014)
- Do Foreigners Crowd Natives Out of Stem Degrees and Occupations? Evidence from the U.S. Immigration Act of 1990, "Ransom, T.", IZA, ~, pp.IZA Discussion Paper, No. 9920 (2016)
- Analysis of Labor Market Performance by fields of STEM programs in Universities, "Whang, K.", KRIVET, ~, pp.KRIVET Issue Brief 24 (2013)
- Foreign and Native-Born STEM Graduates and Innovation Intensity in the United States, "Winters, J. V.", IZA, ~ (2014)