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ID:
143391
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| Summary/Abstract |
This paper examines the causal effect of private tutoring on Chinese and mathematics test scores of primary school students in urban China. Because the unobserved determinants of schooling achievement often also influence private tutoring expenditure, the OLS estimate cannot provide a consistent estimate. This paper adopts a heteroskedasticity-based identification strategy proposed by Lewbel (2012) to handle this problem. These estimation results show that, on average, private tutoring expenditure has small but statistically significant effect on the mathematics test score of primary school students, but has no statistically significant effect on the Chinese test score. A 1000 yuan increase in private tutoring expenditure (i.e. 54% of a standard deviation) raises the primary school students' mathematics test score by 1.07 percentage point (i.e. 15% of a standard deviation). The instrumental variable quantile regression combining with Lewbel IV suggests that private tutoring is more likely to improve student achievement at the bottom end of test score distribution. When moving upward to the top end, the effect becomes smaller and even negative although not significant.
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| 2 |
ID:
156461
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| Summary/Abstract |
This paper aims to measure and understand the rural–urban student cognitive ability gap in China. Using the China Education Panel Survey (CEPS) 2013/2014 data, we find that the cognitive ability test scores of urban students are approximately 1.41 points (17%) higher than those of rural students, on average. This difference is equivalent to 37 and 41% of the standard deviation of urban and rural students' test scores, respectively. Instead of the raw test score, when the cognitive ability is estimated with the 3-parameter Logistic item response theory model, the rural–urban gap is somewhat reduced. The regression and Oaxaca–Blinder decomposition analyses show that nearly one-half of the rural–urban gap can be accounted for by differences in observed characteristics, especially number of siblings, parental education, and interaction between parents and teachers. We then discuss the policy implications of these results and propose a few potential ways to reduce the rural–urban gap in students' cognitive abilities.
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