The Return to Education in IRAN by Using Age Cohorts and Pseudo Panel Data Approach

Document Type : Research Article

Authors

Abstract

Education as an effective social phenomenon has an important role in the realization of the cultural, social, political and economic objectives.The important role of education in individual and social behavior and its effect on economic growth and development process led to a new branch in economics as economics of education. Now the question for society is how education can affect their income increasing process, and how much should be policymakers invested in education? Given the importance of education on earnings, numerous studies have been performed in estimating the returns to education. In traditional approach, Mincer's earning function were used for estimating return of education. Mincer provided an earning function as a semi Logarithmic regression that dependent variable is income and independent variables are years of education and years of experience. The coefficient of years of schooling represents the average rate of return during training.
Using ordinary least squares (OLS) for estimation of returns to education in Mincer's earning function is unobserved heterogeneity among individuals. As a matter of fact, the main problem discussed in the literature on the returns to education is the endogeneity of the schooling variable. Individual choice of years of schooling is not exogenous and tends to be correlated with unobservables in the error term of the earnings function. The likely candidates for these unobservables are ability or motivation, which correlate with years of education and with earnings, giving rise to “ability bias” (Card, 1999). Given the expected positive correlations between ability and both earnings and years of schooling, the standard critique emphasizes an upward bias. To avoid inbreeding bias and individual unobserved heterogeneity, it is better to use panel data, but the main limitation is the lack of longitudinal data, especially in developing countries. As a result, it can be said that in studies which have been done in the field of returns to education, only a few of them have paid attention to the problem of estimation bias. Deaton (1985) used the cohort to solve the problem and suggested pseudo panel data. Each cohort is a group with specific members. Pseudo panel date is following the people's age group in a higher level than Cross-sectional data. The age groups have been made from repeated cross-sectional data from household surveys according to a group of people with specific characteristics.
In this study, we employ the pseudo-panel approach for estimating returns to education in Iran. Pseudo-panel data are constructed from repeated cross sections of Household Expenditure and Income Survey (HEIS) conducted by Statistical Center of Iran during 1991to 2012. The subjects were employee who was born between the years 1937 to 1981. In this study, 22 the period and 9 age group is used to form the cohort. Each cohort has been divided in 5-year period. For example, the ninth age group are 54-50 that are born between 1937-1941.
On the base of results, education has a positive and significant impact on earnings. The relatively high rate of educational return shows that investment in education is economically feasible; therefore, policy makers should pay more attention to its development. Also, the men’s educational return is more than women’s. On the other hand, the relation between age/ experience and income is inverse U. This means that with age / experience of the income increases. But, after reaching the maximum point, it do not expected more age / years of experience lead to an increase in income.

Keywords

References

افشاری، زهرا (1374). «نرخ بازدهی تعلیم و تربیت در ایران»، مجله علمی-پژوهشی علوم انسانی دانشگاه الزهرا، شماره 13 و 14: 174-157.
انتظاری، یعقوب؛ روحانی، شادی و حیدری، فاطمه (1393). «بازدهی اقتصاد کلان آموزش عالی در کشور ایران»، فصلنامه پژوهش و برنامه‌ریزی در آموزش عالی، 72: 50-25.
راغفر، حسین؛ موسوی، میر حسین و اصل، زمزم‏السادات (1992). «بررسی اثرات ویژگی­های خانوار بر مخارج مصرفی (کاربردی از مدل­سازی داده­های شبه پانل)»، فصلنامهمطالعات اقتصادی کاربردی، 8(2): 1-12.
راغفر، حسین و باباپور، میترا (1993). «تجزیه و تحلیل رفتار بین نسلی هزینه مصرفی خانوارهای شهری با استفاده از داده‌های شبه تابلویی»، فصلنامهمطالعات اقتصادی کاربردی، 10(3): 177-199.
رامشی، رقیه؛ نادری، ابوالقاسم و نامی، کلثوم (1393). «ارزیابی نرخ بازده آموزش در ایران برحسب جنسیت دانش‌آموختگان شاغل و نوع آموزش»، دوفصلنامهمطالعاتبرنامه‏ریزیآموزشی، 5: 31-11.
کشاورز حداد، غلامرضا و نوراشرف‏الدین، سید میثم (1394). «نرخ بازدهی خصوصی آموزش در مناطق شهری ایران: روش رگرسیون چندک»، مجله تحقیقات اقتصادی، 4: 1016-989.
کمیجانی، اکبر و علمی، زهرامیلا (1384). «اثر سرمایه انسانی بر درآمد»، اقتصاد کشاورزی و توسعه، 72: 111-91.
علمی، زهرامیلا (1381). اثر سرمایه‌ی انسانی و سرمایه‌گذاری دولت در سرمایه‌ی انسانی در چارچوب مدل‌های رشد درون‌زا در ایران، رساله‌ی دکتری به راهنمایی اکبر کمیجانی، دانشگاه تهران.
علمی، زهرامیلا؛ کریمی پتانلار، سعید و کسرایی، کامران (1384). «اثر آموزش بر درآمد افراد شهری در ایران با استفاده از روش مدل‌های چندسطحی در سال 1382»، مجله تحقیقات اقتصادی، 74: 272-249.
عمادزاده، مصطفی (1382). اصول اقتصاد آموزش و پرورش، چاپ بیستم، اصفهان، جهاد دانشگاهی.
لشکری، محمد (1391). «مقایسه بازده آموزش و تجربه در ایران و چین»، مجله راهبرد توسعه، 31: 38-5.
مرکز آمار ایران، داده‏های طرح هزینه درآمد خانوار شهری به تفکیک سال‏های 1370 الی 1391.
نادری، ابوالقاسم (1390). «ارزیابی نرخ بازده سرمایه‌گذاری آموزشی برای مشاغل تخصصی و بازرگانی در ایران»، فصلنامه اقتصاد و تجارت نوین،  23 و 24: 27-1.
Anker, R. (1998). “Gender and Jobs: Sex Segregation of Occupation in the World”. Genva, ILO.
Ashenfelter, O.; Harmon, C. and Hessel, O. (1999). “A Review of Estimates of the Schooling/Earnings Relationship, with tests for Publication Bias”. Labor Economics, 6(4): 453-470.
Card, D. (2001). “Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems”. Econometrica, 69(5): 1127-1160.
Card, D. and Lemieux, T. (2001). “Can Falling Supply Explain the Rising Return to College for Younger Men? A Cohort-Based Analysis”, The Quarterly Journal of Economics, 116(2): 705-746.
Conneely, K. and Uusitalo, R. (1997). Estimating heterogeneous treatment effects in the Becker schooling model, Mimeo, Industrial Relation Section, Princeton University.
Deaton, A. (1985). “Panel data from a time series of cross-sections”. Journal of Econometrics, 30: 109-126.
Grilliches, Z. (1977). “Estimating the Returns to Schooling: Some Econometric Problems”. Econometrica, 45(1): 1-22
Harmon, C. and Walker, I. (1995); "Estimates of the Economic Return to Schooling for the United Kingdom". American Economic Review, 85(5): 1278-86.
Heckman, J.; Lochner, L. and Petra, T. (2005); "Earnings functions, Rate of return, and Treatment Effects: The Mincer Equation and Beyond". NBER Working Paper: 11544.
Himaz, R. and Aturupane, H. (2016); "Return to education in sir lanka: a pseudo panel approach". Education Economics, 24(3): 300-311.
Kane, T. and Rouse, C. (1993). Labor Market Returns to Two-and Four-Year Colleges: Is a Credit and Do Degree Matter?. NBER Working Papers: 4268.
Kelly, E.; Philip, J. and Smyth, E. (2010); "The Economic Returns to Field of Study and Competencies among Higher Eeducation Graduates in Ireland", Economics of Education Review, 29(4): 650-657.
Mincer, J. (1958). "Investment in Human Capital and Personal Income Distribution", Journal of Political Economy.pp: 281-302.
Mincer, J. (1974). "Progress in Human Capital Analysis of the Distribution of Earning", Center for Economic Analysis of Human Bihavior and Social Institutions National Bureau of Economic Research and University of Stanford.
Mincer, J. (1974). “Sclooling, experience and earnings”. New Yourk, National bureau of economic research, 41-63.
Moock, P.; Patrinos, H. and Venkataraman, M. (2003). “Education and earnings in a transition economy: the case of Vietnam”. Economics of Education Review, 22: 503-510.
Montenegro, C. and patrinos, H. (2013). “Return to schooling around the world”. World development report.
Patrinos, H. A. and Psacharopoulos, G. (2010). “Returns to Education in Developing Countries”, International Encyclopedia of Eeducation, 305-312.
Polacheck, S. (2007). “Earning Over the Lifecycle: The Mincer Earning Funtion and lts Application”. Iza Discution 3181.
Psacharopoulos, G. and Liyard, R. (1979). “Human Capital and Earnings: British Evidence and a Critique”. The Review of Economic Studies, 46(3): 485-503
Psacharopoulos, G. (1985). “Returns to Education: A Further International Update and Implications”. The Journal of Human Resources 20(4): 583-604.
Psacharopoulos, George, (1994). “Returns to investment in education: A global update”, World Development, Elsevier, 22(9): 1325-1343.
Psacharopulos, G. and Patrinos, H.A. (2004). “Investment in Education; A Further Update”, Education Economics, 12(2): 111-134
Salehi-Isfahani, D.; Insan, T. and Ragui, A. (2009). “A Comparative study of Returns to Education of Urban Men in Egypt, Iran, and Turkey”, Middle East Development Journal, 1(2): 145-187
Trostel, P.; Walker, I. and Woolley, P. (2002). “Estimates of the economic return to schooling for 28 countries”. Labour economics, 9: 1-16.
Verbeek, M. (2008). A Guide to Modern Econometrics, John Wiley & Sons, Ltd.
Verbeek, M. and Nijman, T. (1992). “Can cohort data be treated as genuine panel data?”, EmpiricalEconomics, 17(1): 9-23.
Warunsiri, S. and McNown, R. (2010). “The return to education in Thiland: a pseudo panel approach”, World Development, 1616-1625.
Journal of Applied Economics Studies in Iran
Volume 6, Issue 22
July 2017
Pages 145-170

Files

Share

How to cite

Statistics