ترکیب سرمایه انسانی و رشد اقتصادی : شواهد از چین با استفاده از تجزیه و تحلیل داده های پانل پویا
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|4873||2011||7 صفحه PDF||سفارش دهید||4962 کلمه|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : China Economic Review, Volume 22, Issue 1, March 2011, Pages 165–171
This study examines the effect of the composition of human capital on economic growth in China, using the Generalized Methods of Moments (GMM) method. The results show that tertiary education plays a more important role than primary and secondary education on economic growth in China. Moreover, the role of the composition of human capital on regional economic growth is relevant to the level of development. The more developed provinces benefit more from tertiary education, while underdeveloped ones depend more on primary and secondary education.
Economic theory has emphasized the important role of human capital on economic growth (Denison, 1962, Lucas, 1988, Romer, 1986 and Schultz, 1961). As education is one of the primary components of human capital, many growth literatures have provided a conceptual framework that links education and growth (Mankiw et al., 1992 and Mulligan and Sala-I-Martin, 1992). An abundance of empirical studies have found a positive relationship between growth and education (Barro, 1991, Levine and Renelt, 1992 and Mankiw et al., 1992), while some recent papers have found that the relationship between changes in average schooling and growth is weak (Benhabib and Spiegel, 1994, Islam, 1995 and Pritchett, 2001). In contrast to the prior studies where human capital is typically treated as a homogeneous concept, recent papers are concerned with the significance and relevance of different types of education (tertiary, secondary and primary) to economic growth. Ramcharan (2004) developed an analytical framework which showed how the composition of human capital stock determined a country's development and concluded that average years of schooling could mask potentially important differences in the composition, which helps to understand why some empirical studies have failed to detect a significant relationship between schooling and growth. Vandenbussche, Aghion, and Meghir (2006) developed a theoretical model showing that skilled labor had a higher growth effect closer to the technological frontier. Most of empirical literatures related to different educational levels were based on evidence provided by cross-country studies (Barro and Lee, 1997, McMahon, 1998 and Petrakis and Stamatakis, 2002). Only a small set of recent papers investigated the relationship between different educational levels and growth in one country. Using time series in India, Self and Grabowski (2004) found that primary education had a strong causal impact on economic growth, with more limited evidence of such an impact for secondary education. Pereira and St. Aubyn (2009) concluded that increasing education at all levels except tertiary had a positive and significant effect on growth in Portugal. Although the prior studies have found the different effects of each educational level on growth, they can't figure out whether the effects are dissimilar in different regions of one country and what is the best composition of human capital in one country. With regard to the studies of human capital in China, most of empirical literatures treated human capital as a homogeneous concept. Some papers incorporated human capital in the growth accounting and found a positive relationship between growth and education (Fleisher & Chen, 1997; H. Li and Huang, 2009, Li and Liu, 2011 and Wang and Yao, 2003), while several studies which included human capital in the regressions to explain regional growth disparity in China found an insignificant effect of human capital on growth (Chen and Fleisher, 1996 and Wei et al., 2001). However, there are several recent papers which investigated the relationship between different educational levels and growth in China. Chi (2008) concluded that tertiary education has a positive and larger impact on GDP growth than primary and secondary education. Fleisher, Li, and Zhao (2010) found that workers with more than elementary school education have a much higher marginal product than labor with no higher than elementary schooling. Lau (2010) found that schooling at the primary level triggers economic growth, while investments in secondary and higher levels of human capital do not favor economic growth. This paper considers the impact of the composition of human capital on China's economic growth, using China's provincial data and the growth regression framework. In order to account for the possibility of dynamics and endogeneity issues, this paper uses the Generalized Methods of Moments (GMM) method which becomes popular recently in the education and growth empirical literatures (Agiomirgianakis et al., 2002, Chi, 2008, Gyimah-Brempong et al., 2006 and Seetanah, 2009). A new variable is introduced, namely the human capital structure which is the percentage of human capital with tertiary education to investigate whether the human capital structure has an inverse-U-shape effect on economic growth, and what is the best composition of human capital in China. In addition, this paper also analyzes whether the effect of human capital and its structure on regional economic growth is relevant to the level of development. The paper is organized as follows. Section 2 describes the variables used in our model and sources of data. Section 3 explains the methodology. Section 4 is the main results. Conclusions are summarized in Section 5.
نتیجه گیری انگلیسی
In this paper, we have attempted to conduct empirical research to investigate the effect of the composition of human capital on China's economic growth. We use panel data set for Chinese provinces over the period of 1997–2006 and use the GMM method to account for the possibility of dynamics and endogeneity issues. This paper not only separates human capital into two educational levels, but also introduces a new variable, namely the human capital structure to investigate what educational levels matter more for growth in China. Most importantly, according to different development levels, the province sample is divided into three groups to find out whether the link between growth and education varies as a result of different levels of economic development. Our empirical results indicate that on the whole, the human capital structure in China is still at the stage of promoting economic growth and tertiary education plays a more important role than primary and secondary education on economic growth. Moreover, the contribution of tertiary educational levels increases as the level of development increases from the western region to central and eastern regions. In other words, the more developed provinces benefit more from tertiary education, while underdeveloped ones depend more on primary and secondary education. As far as policy implications are concerned, this study suggests that China should raise the percentage of workers with tertiary educational attainment to promote economic growth. Moreover, in order to decrease regional disparities, it is better to invest more in all educational levels of the poor provinces, especially to improve primary and secondary education in western China. It should be recognized that this paper uses average years of schooling as an approximation of the stock of provincial human capital which may be somewhat biased due to the labor migration between provinces. Therefore, further research considering labor migration is certainly required.