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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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Author Info

  • Kramarz, Francis

    ()
    (CREST (ENSAE))

  • Machin, Stephen

    ()
    (University College London)

  • 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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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 3866.

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Length: 51 pages
Date of creation: Dec 2008
Date of revision:
Publication status: forthcoming in: Oxford Bulletin of Economics and Statistics
Handle: RePEc:iza:izadps:dp3866

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Keywords: peer effects; school effects; school quality; education;

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References

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Citations

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Cited by:
  1. Sandra E. Black & Paul J. Devereux & Kjell G. Salvanes, 2010. "Under Pressure? The Effect of Peers on Outcomes of Young Adults," Working Papers 201024, Geary Institute, University College Dublin.
  2. 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.
  3. Machin, Stephen, 2011. "Houses and schools: Valuation of school quality through the housing market," Labour Economics, Elsevier, vol. 18(6), pages 723-729.
  4. Richard Buddin & Gema Zamarro, 2009. "Teacher Qualifications and Middle School Student Achievement," Working Papers 671, RAND Corporation Publications Department.
  5. Richard Buddin & Gema Zamarro, 2009. "Teacher Effectiveness in Urban High Schools," Working Papers 693, RAND Corporation Publications Department.
  6. 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).
  7. Ouazad, Amine & Rancière, Romain, 2011. "Credit Standards and Segregation," CEPR Discussion Papers 8300, C.E.P.R. Discussion Papers.
  8. Steve Gibbons & Stephen Machin & Olmo Silva, 2009. "Valuing School Quality Using Boundary Discontinuities," SERC Discussion Papers 0018, Spatial Economics Research Centre, LSE.
  9. Richard Buddin & Gena Zamarro, 2008. "Teacher Quality, Teacher Licensure Tests, and Student Achievement," Working Papers 555, RAND Corporation Publications Department.
  10. 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).
  11. Kässi, Otto, 2012. "Uncertainty and Heterogeneity in Returns to Education: Evidence from Finland," MPRA Paper 43503, University Library of Munich, Germany.
  12. 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].
  13. 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..

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