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It is known that in most countries, students of private schools outperform students in public schools in international assessments. However, the empirical literature recognises that assessing the true effect of private school attendance requires addressing selection and sorting issues on both observables and unobservables. The existing empirical evidence on the private school effect mostly covers OECD and Latin American countries, with little evidence on other parts of the world. There is recent emerging country specific evidence doubting the existence of a private school advantage. I use PISA 2012 data for Mathematics and two different methodologies to derive baseline and bias-corrected estimates of the private-dependent and independent school effect for 40 countries. A robust private school advantage if found only in a handful of countries. Public schools perform equally well as private subsidised schools and outperform independent schools. Accounting for both peer effects and selection is necessary when evaluating school effectiveness, especially in the case of independent schools.

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This paper uses a new dataset, the 2009 Rural Urban Migration in China (RUMiC) to estimate returns to schooling in China using an instrumental variable (IV) methodology. After identifying a set of instruments, we conduct comprehensive validity and relevance testing of different combinations of instruments as well as robustness analysis of our estimates for rural to urban migrants and urban residents in China. We find that our estimates are in a fairly tight band for all four sub-samples examined (urban men, urban women, migrant men and migrant women). Estimates for men range from about 9.5% for urban workers to about 10-10.5% for migrant workers and are slightly higher than the corresponding estimates for women, which range from 7.5% for female urban workers to 8-9.5% for female migrant workers. Thus, private returns to education in urban China in 2009 were substantial and of similar magnitude to those for other transition countries, as well as to worldwide and developing country averages. We also find that the attenuation bias due to measurement error is generally large and more important in the migrant sample compared to the urban sample.