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School system evaluation by value-added analysis under endogeneity

  • MANZI, Jorge

    (Measurement Center MIDE UC, Pontificia Universidad Católica de Chile, Chile)

  • SAN MARTIN, Ernesto

    (Measurement Center MIDE UC & Dep. Of Statistics, Pontificia Universidad Católica de Chile, Chile)

  • VAN BELLEGEM, Sébastien

    ()

    (Toulouse School of Economics, France; Université catholique de Louvain, CORE, B-1348 Louvain-la-Neuve, Belgium)

Value-added analysis is a common tool in analysing school performances. In this paper, we analyse the SIMCE panel data which provides individual scores of about 200,000 students in Chile, and whose aim is to rank schools according to their educational achievement. Based on the data collection procedure and on empirical evidences, we argue that the exogeneity of some covariates is questionable. This means that a nonvanishing correlation appears between the school-specific effect and some covariates. We show the impact of this phenomenon on the calculation of the value-added and on the ranking, and provide an estimation method that is based on instrumental variables in order to correct the bias of endogeneity. Revisiting the definition of the value-added, we propose a new calculation robust to endogeneity that we illustrate on the SIMCE data.

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Paper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2010046.

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Date of creation: 01 Jul 2010
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Handle: RePEc:cor:louvco:2010046
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  1. Peter Ebbes & Ulf Böckenholt & Michel Wedel, 2004. "Regressor and random-effects dependencies in multilevel models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(2), pages 161-178.
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  3. Hanushek, Eric A., 2006. "School Resources," Handbook of the Economics of Education, Elsevier.
  4. Claudio Sapelli & Bernardita Vial, 2002. "The Performance of Private and Public Schools in the Chilean Voucher System," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 39(118), pages 423-454.
  5. Christopher F Baum, 2006. "An Introduction to Modern Econometrics using Stata," Stata Press books, StataCorp LP, number imeus, November.
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  7. Joshua Angrist & Alan B. Krueger, 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments," NBER Working Papers 8456, National Bureau of Economic Research, Inc.
  8. Fiona Steele & Anna Vignoles & Andrew Jenkins, 2007. "The effect of school resources on pupil attainment: a multilevel simultaneous equation modelling approach," LSE Research Online Documents on Economics 26481, London School of Economics and Political Science, LSE Library.
  9. Winfried Pohlmeier & Luc Bauwens & David Veredas, 2007. "High frequency financial econometrics. Recent developments," ULB Institutional Repository 2013/136223, ULB -- Universite Libre de Bruxelles.
  10. Jee-Seon Kim & Edward Frees, 2007. "Multilevel Modeling with Correlated Effects," Psychometrika, Springer, vol. 72(4), pages 505-533, December.
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