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Does Private Tutoring Work? The Effectiveness of Private Tutoring: A Nonparametric Bounds Analysis

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  • Stefanie Hof

    () (Swiss Coordination Centre for Research in Education (SKBF))

Abstract

Private tutoring has become popular all over the world. However, the evidence on the effect of private tutoring is inconclusive, therefore, this paper attempts to improve the existing literature by using nonparametric bounds methods to find out if private tutoring yields any substantial returns for the individual. The present examination uses a large representative dataset to identify bounds, first, without imposing assumptions and second, it applies weak nonparametric assumptions to tighten the bounds. Under relatively weak assumptions, I find some evidence that private tutoring improves studentsÕ academic outcome in reading. However, the results indicate a heterogeneous and nonlinear effect of private tutoring.

Suggested Citation

  • Stefanie Hof, 2014. "Does Private Tutoring Work? The Effectiveness of Private Tutoring: A Nonparametric Bounds Analysis," Economics of Education Working Paper Series 0096, University of Zurich, Department of Business Administration (IBW).
  • Handle: RePEc:iso:educat:0096
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    References listed on IDEAS

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    1. Pinkovskiy, Maxim L., 2013. "World welfare is rising: Estimation using nonparametric bounds on welfare measures," Journal of Public Economics, Elsevier, vol. 97(C), pages 176-195.
    2. Gundersen, Craig & Kreider, Brent & Pepper, John, 2012. "The impact of the National School Lunch Program on child health: A nonparametric bounds analysis," Journal of Econometrics, Elsevier, vol. 166(1), pages 79-91.
    3. Stefan Boes, 2013. "Nonparametric analysis of treatment effects in ordered response models," Empirical Economics, Springer, vol. 44(1), pages 81-109, February.
    4. Victor Lavy & Analia Schlosser, 2005. "Targeted Remedial Education for Underperforming Teenagers: Costs and Benefits," Journal of Labor Economics, University of Chicago Press, vol. 23(4), pages 839-874, October.
    5. Brent Kreider & John V. Pepper & Craig Gundersen & Dean Jolliffe, 2012. "Identifying the Effects of SNAP (Food Stamps) on Child Health Outcomes When Participation Is Endogenous and Misreported," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(499), pages 958-975, September.
    6. Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
    7. Charles F. Manski & John V. Pepper, 2009. "More on monotone instrumental variables," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 200-216, January.
    8. Hai-Anh Dang & F. Halsey Rogers, 2008. "The Growing Phenomenon of Private Tutoring: Does It Deepen Human Capital, Widen Inequalities, or Waste Resources?," World Bank Research Observer, World Bank Group, vol. 23(2), pages 161-200, April.
    9. Ono, Hiroshi, 2007. "Does examination hell pay off ? A cost-benefit analysis of "ronin" and college education in Japan," Economics of Education Review, Elsevier, vol. 26(3), pages 271-284, June.
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    Citations

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    Cited by:

    1. Zhang, Yu & Liu, Junyan, 2016. "The effectiveness of private tutoring in China with a focus on class-size," International Journal of Educational Development, Elsevier, vol. 46(C), pages 35-42.
    2. repec:eee:ecmode:v:70:y:2018:i:c:p:1-14 is not listed on IDEAS
    3. John Jerrim & Luis Alejandro Lopez-Agudo & Oscar D. Marcenaro-Gutierrez & Nikki Shure, 2017. "What Happens When Econometrics and Psychometrics Collide? An Example Using PISA Data," DoQSS Working Papers 17-04, Department of Quantitative Social Science - UCL Institute of Education, University College London.

    More about this item

    Keywords

    Partial identification; selection problem; nonparametric bounds method; monotone instrument variable; private tutoring; academic achievement;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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