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What Makes a Test Score? The Respective Contributions of Pupils, Schools, and Peers in Achievement in English Primary Education

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  • Kramarz, Francis

    () (CREST (ENSAE))

  • Machin, Stephen

    () (London School of Economics)

  • Ouazad, Amine

    () (CREST-INSEE)

Abstract

This study develops an analytical framework for evaluating the respective contributions of pupils, peers, and school quality in affecting educational achievement. We implement this framework using rich data from England that matches pupils to their primary schools. The dataset records all English pupils and their test scores in Key Stage 1 (age 7) and Key Stage 2 (age 11) national examinations. The quality of the data source, coupled with our econometric techniques, allows us to assess the respective importance of different educational inputs. We can distinguish school effects, that affect all pupils irrespective of their year and grade of study, from school-grade-year effects. Identification of pupil effects separately from these school-grade-year effects is achieved because students are mobile across schools. Peer effects are identified assuming variations in school-grade-year group composition in adjacent years are exogenous. We estimate three different specifications, the most general allowing Key Stage 2 results to be affected by the Key Stage 1 school(-grade-year) at which the pupil studied. We discuss the validity of our various exogeneity assumptions. Estimation results show statistically significant pupil ability, school and peer effects. Our analysis suggests the following ranking: pupils' ability and background are more important than school time-invariant inputs. Peer effects are significant, but small.

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  • Kramarz, Francis & Machin, Stephen & Ouazad, Amine, 2008. "What Makes a Test Score? The Respective Contributions of Pupils, Schools, and Peers in Achievement in English Primary Education," IZA Discussion Papers 3866, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp3866
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    Cited by:

    1. Amine Ouazad, 2008. "Assessed by a Teacher Like Me: Race, Gender and Subjective Evaluations," CEE Discussion Papers 0098, Centre for the Economics of Education, LSE.
    2. Christofides, Louis N. & Hoy, Michael & Milla, Joniada & Stengos, Thanasis, 2012. "Grades, Aspirations and Post-Secondary Education Outcomes," IZA Discussion Papers 6867, Institute for the Study of Labor (IZA).
    3. Sandra E. Black & Paul J. Devereux & Kjell G. Salvanes, 2013. "Under Pressure? The Effect of Peers on Outcomes of Young Adults," Journal of Labor Economics, University of Chicago Press, vol. 31(1), pages 119-153.
    4. Nikolas Mittag, 2015. "A Simple Method to Estimate Large Fixed Effects Models Applied to Wage Determinants and Matching," CERGE-EI Working Papers wp532, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    5. Jesse Rothstein, 2007. "Do Value-Added Models Add Value? Tracking, Fixed Effects, and Causal Inference," Working Papers 1036, Princeton University, Department of Economics, Center for Economic Policy Studies..
    6. Mittag, Nikolas, 2016. "A Simple Method to Estimate Large Fixed Effects Models Applied to Wage Determinants and Matching," IZA Discussion Papers 10447, Institute for the Study of Labor (IZA).
    7. Richard Buddin & Gena Zamarro, 2008. "Teacher Quality, Teacher Licensure Tests, and Student Achievement," Working Papers 555, RAND Corporation.
    8. Marco Tonello, 2011. "Mechanisms of peer interactions between native and non-native students: rejection or integration?," Working Papers 2011/21, Institut d'Economia de Barcelona (IEB).
    9. Richard Buddin & Gema Zamarro, 2008. "Teacher Quality, Teacher Licensure Tests, and Student Achievement," Working Papers WR-555-IES, RAND Corporation.
    10. Mittag, Nikolas, 2012. "New methods to estimate models with large sets of fixed effects with an application to matched employer-employee data from Germany," FDZ Methodenreport 201201_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    11. Stephen Gibbons & Shqiponja Telhaj, 2016. "Peer Effects: Evidence from Secondary School Transition in England," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(4), pages 548-575, August.
    12. Richard Buddin & Gema Zamarro, 2009. "Teacher Effectiveness in Urban High Schools," Working Papers WR-693-IES, RAND Corporation.
    13. Amine Ouazad & Romain Rancière, 2016. "Credit Standards and Segregation," The Review of Economics and Statistics, MIT Press, vol. 98(5), pages 880-896, December.
    14. Gibbons, Stephen & Machin, Stephen & Silva, Olmo, 2013. "Valuing school quality using boundary discontinuity," LSE Research Online Documents on Economics 45246, London School of Economics and Political Science, LSE Library.
    15. Richard Buddin & Gema Zamarro, 2009. "Teacher Effectiveness in Urban High Schools," Working Papers 693, RAND Corporation.
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    17. Richard Buddin & Gema Zamarro, 2009. "Teacher Qualifications and Middle School Student Achievement," Working Papers WR-671-IES, RAND Corporation.
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    19. Kässi, Otto, 2012. "Uncertainty and Heterogeneity in Returns to Education: Evidence from Finland," MPRA Paper 48738, University Library of Munich, Germany, revised 01 Aug 2013.
    20. Richard K. Mansfield, 2015. "Teacher Quality and Student Inequality," Journal of Labor Economics, University of Chicago Press, vol. 33(3), pages 751-788.
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    23. Cavaco, Sandra & Crifo, Patricia & Rebérioux, Antoine & Roudaut, Gwenael, 2017. "Independent directors: Less informed but better selected than affiliated board members?," Journal of Corporate Finance, Elsevier, vol. 43(C), pages 106-121.
    24. McNally, Sandra, 2010. "Evaluating education policies: the evidence from economic research," LSE Research Online Documents on Economics 57973, London School of Economics and Political Science, LSE Library.
    25. repec:pri:cepsud:159rothstein is not listed on IDEAS

    More about this item

    Keywords

    school effects; school quality; peer effects; education;

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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