Using China Health and Nutrition Survey(CHNS) data between 1989 and 2011, this paper measures the returns to education in China based on the Mincer earnings function and reaches the following findings through an analy...Using China Health and Nutrition Survey(CHNS) data between 1989 and 2011, this paper measures the returns to education in China based on the Mincer earnings function and reaches the following findings through an analysis of the tendency of continuous variations over a long timeframe: returns to education are on the rise within the range of samples both under relative and absolute scenarios; returns to different levels of education are characterized by increasing marginal return; no significant difference exists between the returns to junior middle school and the returns to primary school education. Further discussions consider that the requirements of job positions for the overall competence of personnel, differentiated decline of corporate demand for recruitment, lack of an evaluation system in the labor market, information asymmetry in the job market, the development strategy adopted in a particular stage of history and the current slow progress of economic transition have jointly led to the underemployment of college graduates and the great enthusiasm of parents investing in higher education for their children. Conclusions of this paper not only have important practical relevance to the ongoing implementation of China's innovation-driven development strategy, but offer inspirations for the new round of educational reform as well.展开更多
This paper empirically analyzes the factors affecting personal income in urban China using survey data of the ＂Preference and Life Satisfaction Survey＂ conducted by the Global COE project of Osaka University from 20...This paper empirically analyzes the factors affecting personal income in urban China using survey data of the ＂Preference and Life Satisfaction Survey＂ conducted by the Global COE project of Osaka University from 2009 to 2013. We consider education level as an endogenous variable, and both ordinary least squares （OLS） regression and instrumental variable （IV） regression are performed. We find a number of factors, such as sex, age, education, and marriage that significantly affect personal income. In addition, differences between different occupations are also investigated.展开更多
文摘Using China Health and Nutrition Survey(CHNS) data between 1989 and 2011, this paper measures the returns to education in China based on the Mincer earnings function and reaches the following findings through an analysis of the tendency of continuous variations over a long timeframe: returns to education are on the rise within the range of samples both under relative and absolute scenarios; returns to different levels of education are characterized by increasing marginal return; no significant difference exists between the returns to junior middle school and the returns to primary school education. Further discussions consider that the requirements of job positions for the overall competence of personnel, differentiated decline of corporate demand for recruitment, lack of an evaluation system in the labor market, information asymmetry in the job market, the development strategy adopted in a particular stage of history and the current slow progress of economic transition have jointly led to the underemployment of college graduates and the great enthusiasm of parents investing in higher education for their children. Conclusions of this paper not only have important practical relevance to the ongoing implementation of China's innovation-driven development strategy, but offer inspirations for the new round of educational reform as well.
文摘This paper empirically analyzes the factors affecting personal income in urban China using survey data of the ＂Preference and Life Satisfaction Survey＂ conducted by the Global COE project of Osaka University from 2009 to 2013. We consider education level as an endogenous variable, and both ordinary least squares （OLS） regression and instrumental variable （IV） regression are performed. We find a number of factors, such as sex, age, education, and marriage that significantly affect personal income. In addition, differences between different occupations are also investigated.
