Evaluating the rate of private return on graduate studies in Iran by using multilevel models

Authors
Abolghasem Mahdavi 1
Zeynab Piroozrahi 2
1 Faculty of Economics, Tehran University
2 Master of Economics, Tehran University
Abstract
The purpose of this study was to examine graduate studies private rate of return in Iran by using multilevel models.   Using latest statistics, applying a multilevel analysis and Mincer earnings function, the effect of university graduate education on employed earnings was investigated. In multilevel analysis method used, major groups activities are considered as second level units. Meanwhile, by measuring the average years of individuals’ unemployment after completing education and adjusting the years after graduation, the estimates of the years of work experience considered to be closer to reality. The most important results of the study showed that the data have a hierarchical structure. In addition, graduate studies have a positive impact on job earnings and the rate of the impact for each additional year of education is 12.3% - a rate that exceeds the opportunity cost of education in developing countries (10%).  The study also indicated that the effect of work experience on earnings is 2.6%. This goes beyond the other incentives to enter graduate studies. This result showed the individuals' economic justification. Employees earnings with graduate degrees in urban areas was 21.4% more than the same group in rural areas, justifying the migration of labor force with graduate degrees to urban areas. Lastly, the return of each additional year of graduate studies is more than the return of each additional year of higher education.

Keywords

1. Afshari, Z. (1998). The effects of higher education and experience on employee's earnings in Iran using Mincerian earnings function. Quarterly Journal of Research & Planning in Higher Education, 6(3), 59-78 (in Persian).
2. Akhgari, O. (2012). Determine the sample size using Bayesian methods in multilevel models. (Master dissertation). Department of Applied Statistics, Tarbiat Modares University (in Persian).
3. Amirkafi, M. (2007). The significance & logic of multilevel models in social research. Journal of Sociology, 7(4), 38-71 (in Persian).
4. Azimi, H. (1993). Circuits of underdevelopment in the Iranian economy. Tehran: Nashre Nei Press (in Persian).
5. Elmi, Z., Karimi Potanlar, S., & Kasraee, K. (2006). The effect of educational attainment on individual income urban area of Iran in (2003-2004): Applying multilevel method. Research Economic Bulletin, 41(3), 249-272 (in Persian).
6. Emadzadeh, M. (2001). Education and income distribution. Journal of Psychology and Educational Sciences, 6(1), 203-227 (in Persian).
7. Gabriel, P.E., & Schmitz, S. (2005). A note on occupational variations in the returns to education in the US labor market. International Journal of Manpower, 26(5), 450-456.
8. Goldstein, H. (1999). Multilevel statistical models. London: Institute of Education. Retrieved from http://www.arnoldpublishers.com/support/goldstein.html
9. Jabal Ameli, F. (2004). Determination of the individual and social rates of return in master and doctoral levels. Quarterly Journal of Research & Planning in Higher Education, 9(4), 75-102 (in Persian).
10. Lashkari, M. (2012). Comparing return of education and experience in Iran and China. 31, 5-38 (in Persian).
11. Mincer, J. (1974). The human capital earnings function in schooling, experience, and earnings. 83-96, New York: Columbia University Press.
12. Naderi, A. (2015). Advanced topics in economics of education. Tehran: University of Tehran Press (in Persian).
13. Naderi, A. (2004). Comparative evaluation of economic return to human capital in Iran’s education labor market. Proceedings of the National Conference on Engineering Reforms in Education, 3, Economics and Planning of Education, Tehran: Institute for Education (in Persian).
14. Naderi, A. (2001, a). Critical evaluation of methodological underpinnings of the empirics of human capital theory. Plan and Budget Bulletin, 60-61, 41-83 (in Persian).
15. Naderi, A. (2001, b). Economics of education and its position in Iran's higher education system. Quarterly Journal of Research & Planning in Higher Education, 7(3), 173-216 (in Persian).
16. Naderi, A., & Mace, J. (2003). Education and earnings: A multilevel analysis. Economics of Education Rev, 22(2), 143-156.
17. Naderi, A. (2013). Evaluation of return to education for professional and business jobs in Iran. Quarterly Journal of New Economy & Commerce, 5(4), 1-27 (in Persian).
18. Naderi, A. (2014). Evaluation of return to education: Issues, challenges and prospects. Research Economic Bulletin, 49(2), 461-429 (in Persian).
19. Naderi, A. (2002, May). Multilevel modeling and their applications in economics. Proceeding of Conference on Non-linear Models, Tehran: Faculty of Economics of Alame- Tabatabaee University (in Persian).
21. Naghsh, Z., & Moghadam, A. (2012). A comparison of multilevel modeling and single-level analysis techniques and their application to TIMSS 2007 data analysis. Journal Training Measurement, 3(8), 133-154 (in Persian).
22. Psacharopoulos, G., & Patrinos, H.A. (2004). Returns to investment in education: A further update. Education Economics, 12(2), 111-134.
23. Roszkowska, S. (2014). Returns to education in Europe: Same or Not?, European Scientific Journal, 10(10), 250-255.
24. Salehi, M.J. (2005). Human resources output measurement in Iran. Quarterly Journal of Research & Planning in Higher Education, 11(1), 139-166 (in Persian).
25. Statistics Center of Iran (2014). Household income and expenditure survey 1392 (in Persian).
26. Statistics Center of Iran (2014). Labor force survey 1392 (in Persian).
27. Todaro, M.P., & Smith, S.C. (2012). Economic development. Translated by Mahmoudi, V., Tehran: Negah Danesh Press (in Persian).
28. Zarouki, Sh. (2006). Investigating the effect of education on worker's income using multilevel analysis during the Third Development Plan (2000-2005). (Master dissertation). Department of Theoretical Economics, Tehran University (in Persian).

  • Receive Date 06 March 2023
  • Revise Date 24 April 2024
  • Publish Date 06 March 2023