IDEAS home Printed from https://ideas.repec.org/p/qss/dqsswp/1212.html
   My bibliography  Save this paper

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
    as

    Download full text from publisher

    File URL: https://repec.ucl.ac.uk/REPEc/pdf/qsswp1212.pdf
    Download Restriction: no
    ---><---

    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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.
    2. Victor Lavy & Analia Schlosser, 2011. "Mechanisms and Impacts of Gender Peer Effects at School," American Economic Journal: Applied Economics, American Economic Association, vol. 3(2), pages 1-33, April.
    3. Michele Raitano & Francesco Vona, 2013. "Peer heterogeneity, school tracking and students' performances: evidence from PISA 2006," Applied Economics, Taylor & Francis Journals, vol. 45(32), pages 4516-4532, November.
    4. Martin Foureaux Koppensteiner, 2012. "Class Assignment and Peer Group Effects: Evidence from Brazilian Primary Schools," Discussion Papers in Economics 12/03, Division of Economics, School of Business, University of Leicester.
    5. Michele Raitano & Francesco Vona, 2010. "Peer Heterogeneity, Parental Background and Tracking: Evidence from PISA 2006," Documents de Travail de l'OFCE 2010-23, Observatoire Francais des Conjonctures Economiques (OFCE).
    6. Áureo de Paula, 2015. "Econometrics of network models," CeMMAP working papers CWP52/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Jones, Sam, 2016. "How does classroom composition affect learning outcomes in Ugandan primary schools?," International Journal of Educational Development, Elsevier, vol. 48(C), pages 66-78.
    8. Frattini, Tommaso & Meschi, Elena, 2019. "The effect of immigrant peers in vocational schools," European Economic Review, Elsevier, vol. 113(C), pages 1-22.
    9. Wennberg, Karl & Norgren, Axel, 2021. "Models of Peer Effects in Education," Working Papers 21/3, Stockholm School of Economics, Center for Educational Leadership and Excellence.
    10. Laura Moritz & Lena Kuhn & Ihtiyor Bobojonov, 2023. "The role of peer imitation in agricultural index insurance adoption: Findings from lab‐in‐the‐field experiments in Kyrgyzstan," Review of Development Economics, Wiley Blackwell, vol. 27(3), pages 1649-1672, August.
    11. Balsa, Ana & Gandelman, Néstor & Roldán, Flavia, 2015. "Peer Effects in the Development of Capabilities in Adolescence," Research Department working papers 820, CAF Development Bank Of Latinamerica.
    12. Shure, Nikki, 2021. "Non-cognitive peer effects in secondary education," Labour Economics, Elsevier, vol. 73(C).
    13. Lang, Kevin & Siniver, Erez, 2011. "Why is an elite undergraduate education valuable? Evidence from Israel," Labour Economics, Elsevier, vol. 18(6), pages 767-777.
    14. Ruijs, Nienke, 2017. "The impact of special needs students on classmate performance," Economics of Education Review, Elsevier, vol. 58(C), pages 15-31.
    15. Sida Peng, 2019. "Heterogeneous Endogenous Effects in Networks," Papers 1908.00663, arXiv.org.
    16. Vardardottir, Arna, 2015. "The impact of classroom peers in a streaming system," Economics of Education Review, Elsevier, vol. 49(C), pages 110-128.
    17. 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.
    18. Rangvid, Beatrice Schindler, 2019. "Returning special education students to regular classrooms: Externalities on peers’ reading scores," Economics of Education Review, Elsevier, vol. 68(C), pages 13-22.
    19. Chen, Xi & Kanbur, Ravi & Zhang, Xiaobo, 2011. "Peer effects, risk pooling, and status seeking: What explains gift spending escalation in rural China?," IFPRI discussion papers 1151, International Food Policy Research Institute (IFPRI).
    20. 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.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:qss:dqsswp:1212. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr Neus Bover Fonts (email available below). General contact details of provider: https://edirc.repec.org/data/dqioeuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.