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Estimating the extreme behaviors of students performance using quantile regression -- evidences from Taiwan

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  • Sheng-Tung Chen
  • Hsiao-I. Kuo
  • Chi-Chung Chen

Abstract

The two-stage least squares approach together with quantile regression analysis is adopted here to estimate the educational production function. Such a methodology is able to capture the extreme behaviors of the two tails of students' performance and the estimation outcomes have important policy implications. Our empirical study is applied to the case of students' scores in the Basic Competence Test in Taiwan. The empirical estimation outcomes between traditional OLS and quantile regression on peer-group effects, school characteristics, and family characteristics are diverse and depend on students' ability. Such findings have important implications for parents as well as for government.

Suggested Citation

  • Sheng-Tung Chen & Hsiao-I. Kuo & Chi-Chung Chen, 2012. "Estimating the extreme behaviors of students performance using quantile regression -- evidences from Taiwan," Education Economics, Taylor & Francis Journals, vol. 20(1), pages 93-113, December.
    • Handle: RePEc:taf:edecon:v:20:y:2012:i:1:p:93-113
    DOI: 10.1080/09645292.2010.545517
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    References listed on IDEAS

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    Cited by:

    1. Shim Jeungbo, 2017. "Does Diversification Drive Down Risk-adjusted Returns? A Quantile Regression Approach," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 11(2), pages 1-32, July.

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