中国における私立義務教育規模の規定要因に関する省別パネルデータ分析

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タイトル別名
  • Determinants of the Size of Private Compulsory Education in China: Estimations Based on Provincial Panel Data
  • チュウゴク ニ オケル シリツ ギム キョウイク キボ ノ キテイ ヨウイン ニ カンスル ショウ ベツ パネルデータ ブンセキ

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説明

<p>  China is now facing a period of social transition characterized by rapid urbanization and growing income inequality. With this social change as background, provincial-level policies concerning private education have been implemented since 2003, under the law of the People's Republic of China on the Promotion of Privately-run Schools. In this socio-political environment, the size of private compulsory education has expanded rapidly during the 2000s. The purpose of this study is to clarify the determinants of the size of private elementary and private lower secondary schools by using China’s provincial panel data. The strongly balanced panel data set includes 30 provinces from 2003 to 2011.</p><p>  Two fresh approaches are carried out in this paper. First, in addition to GDP per capita, income per capita and education spending per student, which have been examined individually in previous studies, the effects of the supply factors of “funding for private school” and “social donation”, “the average income of education industry”, “excess demand associated with government expenditure on education”, “urban-rural income gap” and “urbanization” (the ratio of urban population) as symbols of China's social transformation are examined in this paper. Moreover, as a dummy variable, the effects of the policy concerning private education at provincial-level, which are required to be formulated in accordance with the Law of the People's Republic of China on the Promotion of Privately-run Schools, is also examined. Second, as multi-collinearity tests show that collinearity occurs among the variables of GDP per capita, income per capita and education spending per student in a multiple regression, these three variables are individually examined with the above-mentioned variables as control variables, leading to three estimation models for both private elementary and lower secondary schools. Hausman’s specification test is used to choose between fixed-effects and random-effects models. The result shows that the fixed-effects model is more efficient than the random-effects model in all estimations. The estimation model that controls the income per capita shows the highest explanatory power.</p><p>  The results of estimation, with the income per capita being controlled, indicate that the rise of income and the urban-rural income gap result in the expansion of private compulsory education, which are both highly significant at the 1% level. This reflects the fact that there is a strong demand for the private compulsory education from affluent members of the population. The ratio of urban population shows an effect at the 1% significance level with regard to private lower secondary schools, but to private elementary schools.</p><p>  Government expenditure on education has an inhibitory effect on the size of the private compulsory education, supporting the hypothesis that a trade-off relationship exists between government expenditure and the size of private compulsory education in China. As expected, the average income of the education industry also has a negative effect on the size of private compulsory education (at the 1% significance level). The rise in the average income of the education industry has raised costs, including those of teacher salaries in operating private schools.</p><p>  Funding for private schools, which has been considered as a supply factor of profitable entrepreneurship, shows a positive correlation at the 10% significance level with regard to private lower secondary schools and a negative correlation at the 5% significance level to private elementary schools, therefore it is hard to say that this factor has any effect on the expansion of private compulsory education.</p><p>  Social donations have also been expected as a supply factor with an effect on the size of private compulsory education in China. However, contrary to this (View PDF for the rest of the abstract.)</p>

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