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Does private tutoring increase parental choice and improve student achievement, or does it exacerbate social inequalities and impose heavy costs on households, possibly without improving student outcomes? Private tutoring is now a major component of the education sector in many developing countries, yet education policy too seldom acknowledges or makes use of it. This survey of the literature examines the extent of private tutoring, identifies the factors that explain its growth, and analyzes its cost-effectiveness in improving student academic performance. It also presents a framework for assessing the efficiency and equity effects of tutoring. The results suggest that even taking equity concerns into account, tutoring can raise the effectiveness of the education system under certain reasonable assumptions. Guidance is offered for attacking corruption and other problems that diminish the benefits of private tutoring. JEL codes: I21, I22, D10. Developing country policymakers recognize that education is a key determinant of individual productivity and economywide growth. But their sector diagnoses and policy attention have focused on public schools. Much less attention has been paid to the private school sector, and policy discussion rarely mentions what is emerging as a third important education sector: the private tutoring industry. In many countries, private tutoring has arisen as a parallel education sector that provides supplementary instruction to students enrolled in the public school system. Substantial private tutoring industries can be found in countries as economically and geographically diverse as Cambodia,
We propose a new approach to develop vulnerability lines that are explicitly anchored to the idea of a subset of the population at risk of falling into poverty. We suggest that lines developed in this way can also be applied for the purpose of identifying the middle class (or "secure"). We illustrate that such vulnerability lines can be straightforwardly estimated with panel data, drawing on data from the USA and Vietnam. Importantly, given the relative scarcity of panel datasets, we show further that our method can be applied to synthetic panel datasets. We demonstrate this by means of an illustration using repeated cross-section data from India. Our results indicate that in Vietnam and India during the 2000s, the population shares that can be designated as poor and as secure have, respectively, been falling and expanding, with the vulnerable share of the population remaining fairly stable. Sharply contrasting trends are seen in the USA.JEL Codes: C14, D31, I32
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