Abstract
Migration is one of the main ways of alleviating poverty in developing countries, including China. However, there are concerns about the potential negative effects of migration on the educational achievement of the children that are left behind in villages when one or both of their parents out-migrate to cities. This paper examines changes in school performance before and after the parents of students out-migrate. Surprisingly, we find that there is no significant negative effect of migration on school performance. In fact, we find that educational performance improves in migrant households in which the father out-migrates.
Similar content being viewed by others
Notes
Although the ages of children ranged from 6 to 16, only few children in the sample were older than 14.
The results of our analyses, however, do not depend on the choice of using the second term scores from the first and fifth grades. As a robustness check, we also used average scores for the whole year instead of just for the second semester. In another check, we compared scores that averaged scores from first and second grade to scores that averaged scores from fourth and fifth grade. Our results remain largely the same in these cases.
There are several issues to discuss when considering our measure of income. The value of the house only includes the part of the house used for domicile purposes and the value of assets that were used for farming and non-farm businesses was not included. Yuan is the Chinese currency. One dollar was about 7.6 yuan during the time of our survey. Finally, we admit that we only have a rough proxy for income. Because of this it is possible that we will not be able to identify the impact of income on grades (since the coefficient of the variable could be biased down to zero). The cross sectional variation for income (using our measure), however, does show that there is at least a negative correlation (richer households have children with higher grades). In fact, there are reasons to expect a positive effect of income on grades. The literature (eg, Kandel and Kao, 2001) has shown that the positive relationship between the father's migration and the school performance partly stems from the financial resources provided migration, which lowers the likelihood of children's labor force participation and increases resources for consumption of education-related goods.
The term, wealth, when used in the rest of the paper will refer to the value of housing assets only.
Scores may also differ among households with different household demographic compositions. According to our data, students from households in which there are no siblings (70.3 points) scored slightly lower than those from households with siblings in 2006 (71.5 points). Such a finding is consistent with Brown and Park's study (2002), which found that children with older siblings have significantly higher test scores than their peers.
Graphs of distributions of propensity scores that show the common support are available upon request.
This is achieved by using the STATA command ‘nnmatch.’
In Table 2 we only report the coefficients on the treatment variable. The rest of the results are suppressed for brevity but are available from the authors upon request. We report the results for 24 different regressions.
There is also another potential source of endogeneity that we are not able to account for in the analysis. It is possible that unaccounted for shocks, either in the local economy or in individual households, affect both parents’ migration activities and students’ grades. If these shocks systematically affect all the households, then it is possible that our coefficients also are biased due to the fact that we did not account for this type of unobservable heterogeneity. In this case, it is difficult to determine the direction of the bias. These shocks could be either negative (eg, the family suffers a crop failure or family sickness) or positive (eg, the family receives an inheritance or enjoys a bumper crop) and can lead to negative or positive bias in our estimates.
References
Abadie, A and Imbens, GW . 2002: Simple and bias-corrected matching estimators. Technical report, Department of Economics, UC Berkeley.
Abadie, A and Imbens, GW . 2006: Large sample properties of matching estimators for average treatment effects. Econometrica 74: 235–267.
Battistella, G and Conaco, MCG . 1998: The impact of labour migration on the children left behind: A study of elementary school children in the Philippines. Journal of Social Issues in Southeast Asia 13: 220–241.
Benjamin, D, Brandt, L and Giles, J . 2005: The evolution of income inequality in rural China. Economic Development and Cultural Change 53: 769–824.
Blau, DM . 1999: The effect of income on child development. Review of Economics and Statistics 81: 261–276.
Brown, PH and Park, A . 2002: Education and poverty in rural China. Economics of Education Review 21: 523–541.
Caliendo, M and Kopeinig, S . 2008: Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys 22: 31–72.
Cox Edwards, A and Ureta, M . 2003: International migration, remittances, and schooling: Evidence from El Salvador. Journal of Development Economics 72: 429–461.
de Brauw, A and Giles, J . 2007: Migrant labor markets and the welfare of rural households in the developing world: Evidence from China. Working paper, Michigan State University.
de Brauw, A, Huang, J, Rozelle, S, Zhang, L and Zhang, Y . 2002: The evolution of China's rural labor markets during the reforms. Journal of Comparative Economics 30: 329–353.
Dehejia, RH and Wahba, S . 1999: Causal effects in nonexperimental studies: Reevaluating the evaluation of training programs. Journal of the American Statistical Association 94: 1053–1062.
Dehejia, RH and Wahba, S . 2002: Propensity score-matching methods for nonexperimental causal studies. Review of Economics and Statistics 84: 151–161.
Du, Y, Park, A and Wang, S . 2005: Migration and rural poverty in China. Journal of Comparative Economics 33: 688–709.
Duncan, GJ, Brooks-Gunn, J and Klebanov, PK . 1994: Economic deprivation and early childhood development. Child Development 65: 296–318.
Fredriksson, P and Öckert, B . 2005: Is early learning really more productive? The effect of school starting age on school and labor market performance. IZA Discussion papers, 1659, Institute for the Study of Labor.
Giles, J . 2006: Is life more risky in the open? Household risk-coping and the opening of China's labor markets. Journal of Development Economics 81: 25–60.
Glewwe, P and Jacoby, HG . 2004: Economic growth and the demand for education: Is there a wealth effect? Journal of Development Economics 74: 33–51.
Hanson, GH and Woodruff, C . 2004: Emigration and educational attainment in Mexico. Working paper, University of California, San Diego.
Hanushek, EA . 1992: The trade-off between child quantity and quality. The Journal of Political Economy 100: 84–117.
Heckman, JJ . 2005: China's human capital investment. China Economic Review 16: 50–70.
Kandel, W and Kao, G . 2001: The impact of temporary labor migration on Mexican children's educational aspirations and performance. International Migration Review 35: 1205–1231.
Li, X . 2004: The investigation on the rural migrant children (in Chinese). Journal of Women Study in China 10: 35–37.
McKenzie, D and Rapoport, H . 2006: Can migration reduce educational attainment? Evidence from Mexico. The World Bank Policy Research Working paper series no. 3952.
McKenzie, D and Rapoport, H . 2007: Network effects and the dynamics of migration and inequality: Theory and evidence from Mexico. Journal of Development Economics 84: 1–24.
Princiotta, D, Flanagan, KD and Hausken, EG . 2006: Fifth grade: Findings from the Fifth grade follow-up of the early childhood longitudinal study, Kindergarten class of 1998–99. National Center for Education Statistics No. 2006–2038.
Rosenbaum, PR and Rubin, DB . 1983: The central role of the propensity score in observational studies for causal effects. Biometrika 70: 41–55.
Rozelle, S, Guo, L, Shen, M, Hughart, A and Giles, J . 1999: Leaving China's farms: Survey results of new paths and remaining hurdles to rural migration. The China Quarterly 158: 367–393.
Smith, J and Todd, P . 2005: Does matching overcome LaLonde's critique of nonexperimental estimators? Journal of Econometrics 125: 305–353.
Steelman, LC and Mercy, JA . 1980: Unconfounding the confluence model: A test of sibship size and birth-order effects on intelligence. American Sociological Review 45: 571–582.
Tan, S and Wang, X . 2004: The study on the migrant children (in Chinese). Journal of Education in Hubei 20: 11–12.
Todaro, MP . 1989: Economic Development in the Third World. Longman: New York.
Wang, Y and Wu, X . 2003: A case study of the migrant children (in Chinese). Investigation of the Youth 4: 7–10.
Wu, N . 2004: The problems on the rural migrant children (in Chinese). Unpublished Manuscript, China National Institute for Education Research.
Zhou, Q and Wu, H . 2004: A mother of 13 years old. XinhuaNet, May 26.
Acknowledgements
The authors would like to thank Chengfang Liu, Renfu Luo who have spent uncountable days coordinating the survey and cleaning data. A special thanks to all the enumerators, school principals and students. We are also grateful for the useful comments from Belton Fleisher and two anonymous referees. We acknowledge grants to support field research from The Ford Foundation (Beijing), Chinese Academy of Sciences (KSCX2-YW-N-039) and support for follow-up research from the National Natural Science Foundation of China (70803047). The Natural Science Foundation of Zhejiang Province (Y607420) and the Social Sciences Foundation of Zhejiang Province (07CGLJ005YBQ).
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Chen, X., Huang, Q., Rozelle, S. et al. Effect of Migration on Children's Educational Performance in Rural China. Comp Econ Stud 51, 323–343 (2009). https://doi.org/10.1057/ces.2008.44
Published:
Issue Date:
DOI: https://doi.org/10.1057/ces.2008.44