NUFE 1 General Education, Vocational Education and Individual Income in Rural China HUANG Bin Center for Public Finance Research Faculty of Public Finance & Taxation Nanjing University of Finance and Economics Russia, 16-22, 2013

NUFE 2 © 2011 Bin HUANG Research Background A large number of international empirical studies have shown that education has great influence on individual income Average private rate of return (ROR) to education is over 10% in developing countries, and world average level is also close to 10% (Psacharopoulos, 1994; Patrinos & Psacharopoulos, 2007 ) Contrast to international optimistic results, estimates of China ’ s ROR to general education are extraordinarily low in both urban and rural areas In rural China, most of previous estimates are below 5%, far lower than world average level.

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4 © 2011 Bin HUANG Two explanations Institutional explanation Institutional segmentation of labor market and other institutional shortcoming weaken the economic value of education in China  However, with the improvement in labor market in recent years, the estimates of ROR to education in China still remain a low level. Technical explanation The ROR to education in China was systematically underestimated due to methodological problems. In many cases, estimates of OLS are biased.  Endogeneity caused by omitting of ability variable and measurement error  It was found in some recent studies that China ’ s ROR to education will rise to some degree after methodological rectifying, but most of these studies focused on urban ROR. There are few studies on ROR to education in rural areas.

NUFE 5 © 2011 Bin HUANG Research Questions What level is present RoR to general education in rural China? And compared to previous estimates, present ROR in rural China is rising or falling? What level is present RoR to vocational education in rural China? And the RoR to vocational education is higher or lower than that to general education?

NUFE 6 © 2011 Bin HUANG Data A rural household survey in 2009~2010 granted by China ’ s National Social Science Fund Twelve villages and six Counties in Zhejiang (Eastern China), Anhui (Middle China) and Shanxi (Western China) provinces Collected 1,587 valid household cases, and 4,503 valid personal cases

NUFE 7 © 2011 Bin HUANG Empirical Model Mincer income function: Dependent variable Personal average monthly income (logged)  Income includes farm income and nonfarm income Independent variable general schooling years Work experience and its square term Dummy variables for vocational education other dummy vairalbes for gender employment field (farm Vs. nonfarm) labor migration (migrant VS. home-worker) eastern, middle or western area Other control variables or instrumental variables

NUFE 8 © 2011 Bin HUANG Tackle Endogeneity Control Variable method (CV) Use parental education as control variables to correct for omitted ability bias  Assume that parental education is correlated with schooling years, and have a direct effect on individual income. Instrumental Variable method (IV) Use parental education as instrumental variables to correct for unobserved ability  Assume that parental education would affect individual education (so can influence individual income indirectly), but is not correlated with individual ability

NUFE 9 © 2011 Bin HUANG Our Strategy We employ diverse methods, including OLS, CV, IV and other methods, to regress the Mincer income function, and test their underlying assumptions respectively. In CV regression, we use parental education as controlling variable. In IV regression, we use five instrumental variables  Parental education and family size are used to rectify the bias of ability variable omitting.  Age and its square term are used to rectify the bias of measurement error of work experience.

NUFE 10 © 2011 Bin HUANG Main Results (I) OLSCVIV RoR to general education 6.5% *** 5.7% *** 13.1% *** Discussion and test of assumptions Higher than most of previous OLS estimates (average 4.5%), but still lower than 10% world average level After controlling parental education, ROR decreases to 5.7%. The effect of parental education is not significant. This implies using parental education is not a good way to rectify the bias of ability omitting After using IV method, ROR to education increases considerably. Hausman test and other assumption tests show that endogeneity exists, and instrumental variables we adopt are all strong enough and valid. *** Significant at the 1% level

NUFE 11 © 2011 Bin HUANG Main Results (II) ROR to education is found to increase with the educational level. ROR to post-compulsory education is 26.5% on the average. It is much higher than ROR to compulsory education (insignificant). Rural labor ’ s education supply structure nowadays in China  In our sample, there are more than 70% of people whose education levels are junior or below. ROR to vocational education and training is higher than ROR to general education. ROR to general education is 10.3%, and RORs to vocational education and training are both over 17%.

NUFE 12 © 2011 Bin HUANG ROR to Education of Different Educational Level

NUFE 13 © 2011 Bin HUANG Policy Implications High return of education also implies that more education inequality will be converted to income disparity, and deteriorate income polarization in rural area. Therefore, central government should pay more attention to the design of fiscal grant for students from poor families in the future. Huge gap of ROR between compulsory and post-compulsory education implies that central government should give upper secondary education a top priority in future development of rural education. Contrast to the high rate of return to vocational training, only less than 3% of people in the sample expressed they had received vocational training organized by government or enterprise before. So, central government should assume more responsibility and play a better role in the future development of vocational education and training in rural areas.

NUFE 14 © 2011 Bin HUANG Thank you Author