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Peer effects and measurement error: The impact of sampling variation in school survey data (evidence from PISA)

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  • Micklewright, John
  • Schnepf, Sylke V.
  • Silva, Pedro N.

Abstract

Investigation of peer effects on achievement with sample survey data on schools may mean that only a random sample of the population of peers is observed for each individual. This generates measurement error in peer variables similar in form to the textbook case of errors-in-variables, resulting in the estimated peer group effects in an OLS regression model being biased towards zero. We investigate the problem using survey data for England from the Programme for International Student Assessment (PISA) linked to administrative microdata recording information for each PISA sample member's entire year cohort. We calculate a peer group measure based on these complete data and compare its use with a variable based on peers in just the PISA sample. We also use a Monte Carlo experiment to show how the extent of the attenuation bias rises as peer sample size falls. On average, the estimated peer effect is biased downwards by about one third when drawing a sample of peers of the size implied by the PISA survey design.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ecoedu:v:31:y:2012:i:6:p:1136-1142
    DOI: 10.1016/j.econedurev.2012.07.015
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    References listed on IDEAS

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    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. Jacob M. Markman & Eric A. Hanushek & John F. Kain & Steven G. Rivkin, 2003. "Does peer ability affect student achievement?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(5), pages 527-544.
    3. John Micklewright & Sylke V. Schnepf & Chris Skinner, 2012. "Non-response biases in surveys of schoolchildren: the case of the English Programme for International Student Assessment (PISA) samples," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 175(4), pages 915-938, October.
    4. Entorf, Horst & Lauk, Martina, 2006. "Peer effects, social multipliers and migrants at school: an international comparison," Darmstadt Discussion Papers in Economics 164, Darmstadt University of Technology, Department of Law and Economics.
    5. Jerry Hausman, 2001. "Mismeasured Variables in Econometric Analysis: Problems from the Right and Problems from the Left," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 57-67, Fall.
    6. 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.
    7. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    8. Ludger Woessmann & Paul E. Peterson (ed.), 2007. "Schools and the Equal Opportunity Problem," MIT Press Books, The MIT Press, edition 1, volume 1, number 026223257x, April.
    9. Robert Haveman & Barbara Wolfe, 1995. "The Determinants of Children's Attainments: A Review of Methods and Findings," Journal of Economic Literature, American Economic Association, vol. 33(4), pages 1829-1878, December.
    10. 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.
    11. 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.
    12. Ron W Zimmer & Eugenia F Toma, 2000. "Peer effects in private and public schools across countries," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 19(1), pages 75-92.
    13. 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.
    14. Nicole Schneeweis & Rudolf Winter-Ebmer, 2008. "Peer effects in Austrian schools," Studies in Empirical Economics, in: Christian Dustmann & Bernd Fitzenberger & Stephen Machin (ed.), The Economics of Education and Training, pages 133-155, Springer.
    15. Aaron Sojourner, 2013. "Identification of Peer Effects with Missing Peer Data: Evidence from Project STAR," Economic Journal, Royal Economic Society, vol. 123(569), pages 574-605, June.
    16. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    17. Simon Burgess & Brendon McConnell & Carol Propper & Deborah Wilson, 2004. "Sorting and Choice in English Secondary Schools," The Centre for Market and Public Organisation 04/111, The Centre for Market and Public Organisation, University of Bristol, UK.
    18. Henry, Gary T. & Rickman, Dana K., 2007. "Do peers influence children's skill development in preschool?," Economics of Education Review, Elsevier, vol. 26(1), pages 100-112, February.
    19. Geoffrey Woodhouse & Min Yang & Harvey Goldstein & Jon Rasbash, 1996. "Adjusting for Measurement Error in Multilevel Analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(2), pages 201-212, March.
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    Cited by:

    1. 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.
    2. Frattini, Tommaso & Meschi, Elena, 2019. "The effect of immigrant peers in vocational schools," European Economic Review, Elsevier, vol. 113(C), pages 1-22.
    3. Ana Balsa & Carlos Díaz, 2018. "Social interactions in health behaviors and conditions," Documentos de Trabajo/Working Papers 1802, Facultad de Ciencias Empresariales y Economia. Universidad de Montevideo..
    4. Lidon Moliner & Francisco Alegre, 2020. "Effects of peer tutoring on middle school students’ mathematics self-concepts," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-17, April.
    5. Ballatore, Rosario Maria & Paccagnella, Marco & Tonello, Marco, 2020. "Bullied because younger than my mates? The effect of age rank on victimisation at school," Labour Economics, Elsevier, vol. 62(C).
    6. Bernhard Christopher Dannemann, 2020. "Better Off On Their Own? How Peer Effects Determine International Patterns of the Mathematics Gender Achievement Gap," Working Papers V-433-20, University of Oldenburg, Department of Economics, revised Nov 2020.
    7. Giannelli, Gianna Claudia & Rapallini, Chiara, 2016. "Immigrant student performance in Math: Does it matter where you come from?," Economics of Education Review, Elsevier, vol. 52(C), pages 291-304.
    8. Jerrim, John & Lopez-Agudo, Luis Alejandro & Marcenaro-Gutierrez, Oscar D. & Shure, Nikki, 2017. "What happens when econometrics and psychometrics collide? An example using the PISA data," Economics of Education Review, Elsevier, vol. 61(C), pages 51-58.
    9. Ryan Yeung & Phuong Nguyen-Hoang, 2016. "Endogenous peer effects: Fact or fiction?," The Journal of Educational Research, Taylor & Francis Journals, vol. 109(1), pages 37-49, January.
    10. Schnepf, Sylke, 2018. "Insights into survey errors of large scale educational achievement surveys," JRC Working Papers in Economics and Finance 2018-05, Joint Research Centre, European Commission.
    11. 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.
    12. Vardardottir, Arna, 2015. "The impact of classroom peers in a streaming system," Economics of Education Review, Elsevier, vol. 49(C), pages 110-128.
    13. Lopez-Agudo, Luis Alejandro & González-Betancor, Sara M. & Marcenaro-Gutierrez, Oscar David, 2021. "Language at home and academic performance: The case of Spain," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 16-33.

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    More about this item

    Keywords

    Peer effects; Measurement error; School surveys; Sampling variation; PISA;
    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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