آیا توسعه آموزشی ، نابرابری درآمد را بهبود می بخشد ؟ شواهد و قرائن از داده CHNS سال های 1997 و 2006
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|7378||2010||16 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Economic Systems, Volume 34, Issue 4, December 2010, Pages 397–412
Rapid education expansion and rising income inequality are two striking phenomena occurring in China during the transitional period. Using the China Health and Nutrition Survey (CHNS) data collected in 1997 and 2006, this paper studies how education affects individual earnings during the transitional process. We find that education accounts for only a small fraction of the personal earnings and income gap between different groups. We analyze the underlying mechanism of the impact of education on earning. More educated people tend to enter state-owned sectors, have a low probability of changing jobs in the labor market and work less time; all of these will have a pronounced impact on earning and income inequality. Quantile regression analysis shows that the low-income group's education return rate is lower, which helps little in narrowing the income gap. We decompose the earning gap into four factors: population effect, price effect, labor choice effect and unobservable effect. In explaining the earning gap in China, the price effect is more important than the population effect. The labor choice effect is also significant. We conclude that increasing educational expenditure with no complementary measures such as reforming the education system and establishing a competitive labor market helps less in reducing income inequality.
Education is often considered to exert significant impact on personal income. Education can improve an individual's skills and signal his or her innate productivity, so that workers with a high education attainment often receive high earnings. Expanding education investment is therefore believed to be one of the key measures to reduce poverty and income inequality, particularly in developing countries. As Ashenfelter and Rouse (2000, p. 111) point out, “The school is a promising place to increase the skills and incomes of individuals. As a result, educational policies have the potential to decrease existing, and growing, inequalities in income”. Heckman (2005) also declares that “human capital is the asset that ultimately determines the wealth of China. Fostering access to education will reduce inequality in the long run”. However, during the transitional process, China has witnessed contradictory phenomena. On the one hand, we observe rapid education expansion and even partial over-education. Thanks to the 9-year compulsory education policy initiated in 1986, the enrollment rates of primary and secondary schools rose1 and the average education attainment is quickly increasing too. Furthermore, the education expansion starting since the late 1990s takes place more in high education and high schools. According to the Educational Statistics Yearbook of China 2007 (Ministry of Education of China, 2008), in 1997, the number of students in colleges and universities, high schools, secondary schools and primary schools in every 100 thousands population were 519, 1978, 4408, and 11,287, respectively; the numbers in 2007 were 1924, 3409, 4364, and 8037, respectively. From the aspect of absolute quantity, the college enrollment and total number of students at high education schools in 1998 were 1.08 million and 3.41 million, respectively, while in 2005 the numbers reached 5.05 million and 15.62 million, with a growth rate of 368% and 358%, respectively. On the other hand, the unemployment rate of college graduates has been rising during recent years: only two thirds of college graduates can find a job by graduation. Particularly, students from poor families have more difficulties in job hunting. At the same time, even though China economy has kept a high growth rate (9.8% per year on average) for 30 years, income distribution has been deteriorating and the Gini coefficient for individual income has risen constantly to a relatively high level: from 0.382 in 1988 to 0.452 in 1995 (Zhao et al., 1999), from 0.29 in 1981 to 0.39 in 1995 (World Bank, 1997), from 0.309 in 1981 to 0.447 in 2001 (Ravallion and Chen, 2004), from 0.37 in 1991 to 0.44 in 2000 (Benjamin et al., 2008).2 These seemingly contradictory facts lead us to ask two questions: Does education expansion contribute to income inequality? What are the underlying mechanisms of education's impact on individual income?3 Lai (1997) and Bai (2004) demonstrate that there exists an inverted U-curve relationship between education expansion and income inequality in China; however, their conclusions were based on macro data and the micro influencing mechanisms are not fully explored. Based on the CHNS micro data collected in 1997 and 2006, this paper aims to explore how education affects personal earnings during the transitional process in China. We are interested in the following questions: To what extent does the educational structure and distribution change lead to income inequality? To what extent does the rate of return to education (the higher return to higher education level) play a role? Does education attainment change the behavior of labor supply choice? Do different groups’ rates of return to education vary? The new insights of this paper lie in: (1) we try to explore the underlying mechanisms of the impact of education on income. For instance, how education attainment leads to change in labor supply behavior. Applying the quantile regression method, we try to test whether the low-income group's education return rate is higher; consequently, whether schooling contributes to narrowing the income gap. Using the decomposition method based on the regression, we decompose changes in earning inequality into four factors: population effect (the distribution of education among population), price effect (the return rate to different education levels), labor choice effect (differently educated labor group's different worktimes and unit choices) and unobservable factors (standing for family background and personal unobservable characteristics). (2) We establish a relatively comprehensive earning determination model considering factors such as labor mobility, health and human capital. We also use several alternative income indicators to conduct a return rate estimation, not only of the annual wage income, but also of the total labor income per year; hourly earning is also used as a dependent variable to measure earning more precisely. The paper is organized as follows. Section 2 presents some brief facts about education expansion and income inequality in developed and developing economies. Data source and empirical methodology are introduced in Section 3. Section 4 presents the results of the estimate and factor decompositions, with some further discussion. The last section concludes with policy implications.
نتیجه گیری انگلیسی
Using the CHNS data collected in 1997 and 2006, this paper explores how education affected personal income during the transitional process in China. We find that education explains only a small fraction of personal income and income gap across different income groups. However, more educated people tend to work in the state-owned sector, have a low probability of moving in the labor market and work less time, which increases income inequality. Quantile regression results indicate that the low-income group's education return rate is lower, particularly at the secondary school and high school level, which helps little in narrowing the income gap. We decompose changes in the earning gap into four factors: population effect (the distribution of education among population), price effect (the return to different education levels), labor choice effect (differently educated labor group's different participation rates and working unit choices) and unobservable effect (personal ability and family background). In explaining the income gap in China, price effect and labor choice effect are large relative to population effect. Our study can shed light on education development in other transitional developing countries. The policy implication is that increasing education expenditure with no complementary measures such as reforming the education system and establishing a competitive labor market helps less in reducing income inequality. In the aspect of education reform, government should make access to education easier and reduce education inequality,25 improve schooling quality and reduce partial over-education, and establish a social network between employer and school to help the employer screen capable employees (Rosenbaum and Blinder, 1997). More importantly, constructing a competitive labor market, encouraging workers to flow freely, adjusting different workers’ education return rates to their true productivity, and adjusting wages among industries or sectors through marketization (workers with similar human capital should earn similar wages, even though working in different industries or sectors26) are identified as important measures to narrow the income gap. There are some limitations in our paper. The sample includes only 9 provinces, so we should be cautious about generalizing our conclusion to the whole country.27 Expanding the sample size, enlarging the time scope of analysis and decomposing the Gini coefficient differential of different years are the agendas of our further work.