IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/10917.html
   My bibliography  Save this paper

Does Taking One Step Back Get You Two Steps Forward? Grade Retention and School Performance in Rural China

Author

Listed:
  • Chen, Xinxin
  • Shi, Yaojiang
  • Rozelle, Scott

Abstract

Despite the rise in grade retention in China recently, little work has been done to understand the impact of grade retention on the educational performance of students in China. This paper seeks to redress this shortcoming and examines this impact on 1649 students in 36 elementary schools in Shaanxi province. With a dataset that was collected from a survey designed specifically to capture school performance of students before and after they were retained, we use Difference-in-Difference, Propensity Score Matching and Difference-in-Difference Matching approaches to analyze the effect of grade retention on school performance. Although the descriptive analysis shows that grade retention helps to improve the scores of the students that were retained, somewhat surprisingly, the results from the multivariate analysis consistently show that there is no significant positive effect of grade retention on school performance of the students. In fact, in some cases (e.g., for the students who repeat grade 2), grade retention is shown to hurt school performance.

Suggested Citation

  • Chen, Xinxin & Shi, Yaojiang & Rozelle, Scott, 2007. "Does Taking One Step Back Get You Two Steps Forward? Grade Retention and School Performance in Rural China," MPRA Paper 10917, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:10917
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/10917/1/MPRA_paper_10917.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eide, Eric R. & Showalter, Mark H., 2001. "The effect of grade retention on educational and labor market outcomes," Economics of Education Review, Elsevier, vol. 20(6), pages 563-576, December.
    2. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    3. Alberto Abadie, 2000. "Semiparametric Estimation of Instrumental Variable Models for Causal Effects," NBER Technical Working Papers 0260, National Bureau of Economic Research, Inc.
    4. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    5. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rajeev Dehejia, 2013. "The Porous Dialectic: Experimental and Non-Experimental Methods in Development Economics," WIDER Working Paper Series wp-2013-011, World Institute for Development Economic Research (UNU-WIDER).
    2. Tymon Słoczyński, 2015. "The Oaxaca–Blinder Unexplained Component as a Treatment Effects Estimator," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(4), pages 588-604, August.
    3. Cadot, Olivier & Fernandes, Ana M. & Gourdon, Julien & Mattoo, Aaditya, 2015. "Are the benefits of export support durable? Evidence from Tunisia," Journal of International Economics, Elsevier, vol. 97(2), pages 310-324.
    4. von Greiff, Jenny, 2009. "Displacement and self-employment entry," Labour Economics, Elsevier, vol. 16(5), pages 556-565, October.
    5. David McKenzie & John Gibson & Steven Stillman, 2010. "How Important Is Selection? Experimental vs. Non-Experimental Measures of the Income Gains from Migration," Journal of the European Economic Association, MIT Press, vol. 8(4), pages 913-945, June.
    6. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
    7. Mano, Yukichi & Akoten, John & Yoshino, Yutaka & Sonobe, Tetsushi, 2014. "Teaching KAIZEN to small business owners: An experiment in a metalworking cluster in Nairobi," Journal of the Japanese and International Economies, Elsevier, vol. 33(C), pages 25-42.
    8. McKenzie, David & Gibson, John & Stillman, Steven, 2006. "How important is selection ? Experimental versus non-experimental measures of the income gains from migration," Policy Research Working Paper Series 3906, The World Bank.
    9. Flores, Carlos A. & Mitnik, Oscar A., 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," IZA Discussion Papers 4451, Institute of Labor Economics (IZA).
    10. Davis, K. & Nkonya, E. & Kato, E. & Mekonnen, D.A. & Odendo, M. & Miiro, R. & Nkuba, J., 2012. "Impact of Farmer Field Schools on Agricultural Productivity and Poverty in East Africa," World Development, Elsevier, vol. 40(2), pages 402-413.
    11. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    12. Heinrich, Carolyn J. & Mueser, Peter R. & Troske, Kenneth & Jeon, Kyung-Seong & Kahvecioglu, Daver C., 2009. "New Estimates of Public Employment and Training Program Net Impacts: A Nonexperimental Evaluation of the Workforce Investment Act Program," IZA Discussion Papers 4569, Institute of Labor Economics (IZA).
    13. Andrea Ichino & Fabrizia Mealli & Tommaso Nannicini, 2008. "From temporary help jobs to permanent employment: what can we learn from matching estimators and their sensitivity?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 305-327.
    14. Liane Faltermeier & Awudu Abdulai, 2009. "The impact of water conservation and intensification technologies: empirical evidence for rice farmers in Ghana," Agricultural Economics, International Association of Agricultural Economists, vol. 40(3), pages 365-379, May.
    15. Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007. "Using State Administrative Data to Measure Program Performance," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 761-783, November.
    16. James R. Meldrum, 2016. "Floodplain Price Impacts by Property Type in Boulder County, Colorado: Condominiums Versus Standalone Properties," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 64(4), pages 725-750, August.
    17. Barbopoulos, Leonidas G. & Adra, Samer, 2016. "The earnout structure matters: Takeover premia and acquirer gains in earnout financed M&As," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 283-294.
    18. Gueorgui Kambourov & Iourii Manovskii & Miana Plesca, 2020. "Occupational mobility and the returns to training," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(1), pages 174-211, February.
    19. Wendimu, Mengistu Assefa & Henningsen, Arne & Gibbon, Peter, 2016. "Sugarcane Outgrowers in Ethiopia: “Forced” to Remain Poor?," World Development, Elsevier, vol. 83(C), pages 84-97.
    20. Ferraro, Paul J. & Miranda, Juan José, 2014. "The performance of non-experimental designs in the evaluation of environmental programs: A design-replication study using a large-scale randomized experiment as a benchmark," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 344-365.

    More about this item

    Keywords

    Educational economics; Human capital;

    JEL classification:

    • O53 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:10917. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.