

Wage premium in STEM careers
https://doi.org/10.32609/0042-8736-2023-11-28-50
Abstract
In this study, we explore wage dynamics of STEM and nonSTEM professionals during their working life. We analyze wage differences along the wage distribution and with labor market experience. The main novelty in the paper is decomposing the wage growth in separate effects of experience, cohort and time, and accounting for potential depreciation. The identification used in this procedure is based on the ideas of the human capital theory. The empirical realization employs data from the Russian Longitudinal Monitoring Survey. It shows that Russian STEM graduates accumulate human capital at a slower rate than nonSTEM graduates do. However, STEM skills acquired by the beginning of the career are less exposed to obsoleteness than nonSTEM. This reflects a stronger cohort effect for the latter group, and is an implication of the systemic change and the transformational recession during the 1990s
About the Authors
V. E. GimpelsonUniversity of Wisconsin—Madison; National Research University Higher School of Economics
United States
Madison
D. I. Zinchenko
National Research University Higher School of Economics
Russian Federation
Moscow
E. M. Chernina
Russian Federation
Moscow
References
1. Аистов А. В. (2018). Доходы респондентов разных поколений // Прикладная эконометрика. Т. 50, № 2. С. 23—42. [Aistov A. V. (2018). Age-earnings profiles of different generations. Applied Econometrics, Vol. 50, No. 2, pp. 23—42. (In Russian).]
2. Гимпельсон В. Е. (2019). Возраст и заработная плата: стилизованные факты и российские особенности // Экономический журнал Высшей школы экономики. Т. 23, № 2. С. 185—237. [Gimpelson V. E. (2019). Age and wage: Stylized facts and Russian evidence. HSE Economic Journal, Vol. 23, No. 2, pp. 185—237. (In Russian).] https://doi.org/10.17323/1813-8691-2019-23-2-185-237
3. Гимпельсон В. Е., Зинченко Д. И. (2021). «Физики» и «лирики»: кто российскому рынку более ценен? // Вопросы экономики. № 8. С. 5—36. [Gimpelson V. E., Zinchenko D. I. (2021). “Physicists” and “lyricists”: Whom the Russian labor marketvalues higher? Voprosy Ekonomiki, No. 8, pp. 5—36. (In Russian).] https://doi.org/10.32609/0042-8736-2021-8-5-36
4. Atalay E., Phongthiengtham P., Sotelo S., Tannenbaum D. (2020). The evolution of work in the United States. American Economic Journal: Applied Economics, Vol. 12, No. 2, pp. 1—34. https://doi.org/10.1257/app.20190070
5. Becker G. (1975). Human capital: A theoretical and empirical analysis, with special reference to education. 2nd ed. New York: National Bureau of Economic Research. Ben-Porath Y. (1967). The production of human capital and the life cycle of earnings. Journal of Political Economy, Vol. 75, No. 4, Part 1, pp. 352—365. https://doi.org/10.1086/259291
6. Chernina E., Gimpelson V. (2023). Do wages grow with experience? Deciphering the Russian puzzle. Journal of Comparative Economics, Vol. 51, No. 2, pp. 54—563. https://doi.org/10.1016/j.jce.2023.01.005
7. Deming D. J. (2023). Multidimensional human capital and the wage structure. NBER Working Paper, No. 31001. https://doi.org/10.3386/w31001
8. Deming D. J., Noray K. L. (2018). STEM careers and the changing skill requirements of work. NBER Working Paper, No. 25065. https://doi.org/10.3386/w25065
9. Fang H., Qiu X. (2021). “Golden ages”: A tale of the labor markets in China and the United States. NBER Working Paper, No. 29523. https://doi.org/10.3386/w29523
10. Heckman J. J., Lochner L., Taber C. (1998). Explaining rising wage inequality: Explorations with a dynamic general equilibrium model of labor earnings with heterogeneous agents. Review of Economic Dynamics, Vol. 1, No. 1, pp. 1—58. https://doi.org/10.1006/redy.1997.0008
11. Kinsler J., Pavan R. (2015). The specificity of general human capital: Evidence from college major choice. Journal of Labor Economics, Vol. 33, No. 4, pp. 933—972. https://doi.org/10.1086/681206
12. Koenker R. (2005). Quantile regression (Econometric Society Monographs). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9780511754098
13. Koenker R., Bassett Jr. G. (1978). Regression quantiles. Econometrica, Vol. 46, No. 1, pp. 33—50. https://doi.org/10.2307/1913643
14. Jedwab R., Romer P., Islam A. M., Samaniego R. (2023). Human capital accumulation at work: Estimates for the world and implications for development. American Economic Journal: Macroeconomics, Vol. 15, No. 3, pp. 191—223. https://doi.org/10.1257/mac.20210002
15. Lagakos D., Moll B., Porzio T., Qian N., Schoellman T. (2018). Life cycle wage growth across countries. Journal of Political Economy, Vol. 126, No. 2, pp. 797—849. https://doi.org/10.1086/696225
16. Mincer J. (1974). Schooling, experience and earnings. New York: Columbia University Press for National Bureau of Economic Research.
17. Münich D., Svejnar J., Terrell K. (2005). Returns to human capital under the communist wage grid and during the transition to a market economy. Review of Economics and Statistics, Vol. 87, No. 1, pp. 100—123. https://doi.org/10.1162/0034653053327559
18. Neuman S., Weiss A. (1995). On the effects of schooling vintage on experience-earnings profiles: Theory and evidence. European Economic Review, Vol. 39, No. 5, pp. 943—955. https://doi.org/10.1016/0014-2921(94)00019-V
19. Rosen S. (1975). Measuring the obsolescence of knowledge. In: F. T. Juster (ed.). Education, income, and human behavior. New York: McGraw-Hill, pp. 199—232.
20. Rubinstein Y., Weiss Y. (2006). Post schooling wage growth: Investment, search and learning. In: E. Hanushek, F. Welch (eds.). Handbook of the economics of education, Vol. 1. Ch. 1. Amsterdam: North Holland, pp. 1—67. https://doi.org/10.1016/S1574-0692(06)01001-4
21. Xue Y., Larson R. C. (2015). STEM crisis or STEM surplus? Yes and yes. Monthly Labor Review, Vol. 138, No. 5, pp. 1—13. https://doi.org/10.21916/mlr.2015.14
Supplementary files
Review
For citations:
Gimpelson V.E., Zinchenko D.I., Chernina E.M. Wage premium in STEM careers. Voprosy Ekonomiki. 2023;(11):28-50. (In Russ.) https://doi.org/10.32609/0042-8736-2023-11-28-50