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Quality of migrant schools in China: evidence from a longitudinal study in Shanghai

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Abstract

As spaces in public schools are limited, a substantial number of migrant children living in Chinese cities but without local hukou are enrolled in private migrant schools. This paper studies the quality of migrant schools using data collected in Shanghai in 2010 and 2012. Although students in migrant schools perform considerably worse than their counterparts in public schools, the test score difference in mathematics has almost been halved between 2010 and 2012, due to increased financial subsidy from the government. We rule out alternative explanations for the convergence in test scores. We also conduct a falsification test and find no relative changes in the performance of migrant school students based on a follow-up survey of a new cohort of students in 2015 and 2016, a period with no changes in financial subsidies to migrant schools.

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Notes

  1. The 5 districts are representative of Shanghai in many aspects. Huangpu is Shanghai’s traditional urban core and the city center. Yangpu is located in the northeast of the city, historically an industrial area but now predominantly composed of residential communities. Pudong district is located east of the Huangpu river and encompasses large areas including downtown areas such as Lujiazui and other more suburban and rural areas. Minhang is a typical suburban area with a lot of manufacturing firms; thus, it has attracted many migrants. Baoshan is a suburban district in the north of Shanghai.

  2. The regression results are shown in Appendix Table 14. The attrition regression shows that attrition patterns by student characteristics and family background are statistically indifferent between migrant schools and public schools.

  3. The regression results are qualitatively the same when we include all schools in the 2015–2016 study. Results are available upon request.

    Table 8 Falsification tests using the 2015–2016 surveys
  4. Nevertheless, recently, there have been some signs of Shanghai moving away from its “supportive” stance toward educating migrant children, including raising the minimum requirements for migrant children to enroll in both migrant and public schools. Whether such policies are transitory or not and their long run effects remains to be seen.

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Acknowledgments

The authors would like to thank the anonymous referees for helpful comments and suggestions. We thank Jimmy Chan and seminar participants at Peking University, the Chinese University of Hong Kong, Lingnan University, and the 8th Asian Conference on Applied Eonomics/Econometrics for their valuable comments. All errors are our own.

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Correspondence to Shuaizhang Feng.

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The authors declare that they have no conflict of interest.

Funding

Feng’s research is supported by the Program for Innovative Research Team of Shanghai University of Finance and Economics (2014110310), the National Science Foundation of China (70803029), The National Science Foundation for distinguished young scholars (project number: 71425005), the Chang Jiang Scholars Program (project number: T2012069), and the Program for New Century Excellent Talents in University (NCET-12-0903) sponsored by the Ministry of Education of China. Chen’s research is supported by the National Science Foundation of China (71303149), the Program for Innovative Research Team of Shanghai University of Finance and Economics (2014110310), and the Shanghai Soong Ching Ling Foundation (Lu Jiaxian and Gao Wenying Special Fundation). We also acknowledge partial financial support from the CUHK International Development Fund and the Worldwide Universities Network (WUN) on a project “Migration with and without children: Causes and Economic, Social and Psychological Consequences.”

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Responsible editor: Klaus F. Zimmermann

Appendix

Appendix

Table 13 Per pupil funding for migrant schools in Shanghai (RMB)
Table 14 Regression results on probability of attrition between the two waves

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Chen, Y., Feng, S. Quality of migrant schools in China: evidence from a longitudinal study in Shanghai. J Popul Econ 30, 1007–1034 (2017). https://doi.org/10.1007/s00148-016-0629-5

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