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The role of testing noise in the estimation of achievement-based peer effects

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  • Zhang, Hongliang

Abstract

I demonstrate that in the value-added estimation of peer effects using lagged peer achievement, testing noise may generate another bias in addition to the well-known attenuation bias. Such a bias, which I refer to as the “reversion bias,” may arise when some of a student’s current peers happen to be his/her former peers whose performances in the baseline test were subject to the same common testing noise as the student's own. I propose a solution to overcome this problem by exploiting only the variation in the new peers’ portion of the overall peer quality. Using real-world data, I illustrate the existence of this bias and demonstrate the proposed solution.

Suggested Citation

  • Zhang, Hongliang, 2016. "The role of testing noise in the estimation of achievement-based peer effects," Economics of Education Review, Elsevier, vol. 54(C), pages 113-123.
    • Handle: RePEc:eee:ecoedu:v:54:y:2016:i:c:p:113-123
    DOI: 10.1016/j.econedurev.2016.04.008
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    Cited by:

    1. McVicar, Duncan & Moschion, Julie & Ryan, Chris, 2018. "Achievement effects from new peers: Who matters to whom?," Economics of Education Review, Elsevier, vol. 66(C), pages 154-166.
    2. Feng, Han & Li, Jiayao, 2016. "Head teachers, peer effects, and student achievement," China Economic Review, Elsevier, vol. 41(C), pages 268-283.

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    More about this item

    Keywords

    Peer effects; Student achievement; Measurement error; Mean reversion;
    All these keywords.

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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