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The impact of sampling variation on peer measures: a comment on a proposal to adjust estimates for measurement error

Author

Listed:
  • Pedro N. Silva

    (Instituto Brasileiro de Geografia e Estatística, Rio de Janeiro)

  • John Micklewright

    (Department of Quantitative Social Science, Institute of Education, University of London)

  • Sylke V. Schnepf

    (Southampton Statistical Sciences Research Institute and School of Social Sciences, University of Southampton)

Abstract

Investigation of peer effects on pupil’s achievement with survey data on samples of schools and pupils within schools may mean that only a random sample of peers is observed for each individual pupil. This generates classical measurement error on peer variables. Hence under OLS model fitting the estimated peer group effects in a regression model are biased towards zero (attenuation). A simple adjustment for this kind of measurement error was proposed by Neidell and Waldfogel (2008). We review the derivation of the simple adjustment and suggest that it is not properly justified.

Suggested Citation

  • Pedro N. Silva & John Micklewright & Sylke V. Schnepf, 2012. "The impact of sampling variation on peer measures: a comment on a proposal to adjust estimates for measurement error," DoQSS Working Papers 12-12, Quantitative Social Science - UCL Social Research Institute, University College London.
    • Handle: RePEc:qss:dqsswp:1212
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    File URL: https://repec.ucl.ac.uk/REPEc/pdf/qsswp1212.pdf
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    References listed on IDEAS

    as
    1. Andreas Ammermueller & Jörn-Steffen Pischke, 2009. "Peer Effects in European Primary Schools: Evidence from the Progress in International Reading Literacy Study," Journal of Labor Economics, University of Chicago Press, vol. 27(3), pages 315-348, July.
    2. Matthew Neidell & Jane Waldfogel, 2010. "Cognitive and Noncognitive Peer Effects in Early Education," The Review of Economics and Statistics, MIT Press, vol. 92(3), pages 562-576, August.
    3. Ammermüller, Andreas & Pischke, Jörn-Steffen, 2006. "Peer Effects in European Primary Schools: Evidence from PIRLS," ZEW Discussion Papers 06-027, ZEW - Leibniz Centre for European Economic Research.
    4. Øystein Kravdal, 2006. "A simulation-based assessment of the bias produced when using averages from small DHS clusters as contextual variables in multilevel models," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 15(1), pages 1-20.
    5. Micklewright, John & Schnepf, Sylke V. & Silva, Pedro N., 2012. "Peer effects and measurement error: The impact of sampling variation in school survey data (evidence from PISA)," Economics of Education Review, Elsevier, vol. 31(6), pages 1136-1142.
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    1. Micklewright, John & Schnepf, Sylke V. & Silva, Pedro N., 2012. "Peer effects and measurement error: The impact of sampling variation in school survey data (evidence from PISA)," Economics of Education Review, Elsevier, vol. 31(6), pages 1136-1142.

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    More about this item

    Keywords

    Peer effects; measurement error; school surveys; sampling variation.;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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