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School system evaluation by value-added analysis under endogeneity

Author

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  • 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)

Abstract

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.

Suggested Citation

  • MANZI, Jorge & SAN MARTIN, Ernesto & VAN BELLEGEM, Sébastien, 2010. "School system evaluation by value-added analysis under endogeneity," CORE Discussion Papers 2010046, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Handle: RePEc:cor:louvco:2010046
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    References listed on IDEAS

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    1. Joshua D. Angrist & Alan B. Krueger, 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 69-85, Fall.
    2. Christopher F Baum, 2006. "An Introduction to Modern Econometrics using Stata," Stata Press books, StataCorp LP, number imeus, April.
    3. Fiona Steele & Anna Vignoles & Andrew Jenkins, 2007. "The effect of school resources on pupil attainment: a multilevel simultaneous equation modelling approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(3), pages 801-824.
    4. Rabah Amir, 2005. "Supermodularity and Complementarity in Economics: An Elementary Survey," Southern Economic Journal, Southern Economic Association, vol. 71(3), pages 636-660, January.
    5. Winfried Pohlmeier & Luc Bauwens & David Veredas, 2007. "High frequency financial econometrics. Recent developments," ULB Institutional Repository 2013/136223, ULB -- Universite Libre de Bruxelles.
    6. Jee-Seon Kim & Edward Frees, 2006. "Omitted Variables in Multilevel Models," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 659-690, December.
    7. Jee-Seon Kim & Edward Frees, 2007. "Multilevel Modeling with Correlated Effects," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 505-533, December.
    8. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164.
    9. 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.
    10. Hanushek, Eric A., 2006. "School Resources," Handbook of the Economics of Education, Elsevier.
    11. Joshua Angrist & Alan Krueger, 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments," Working Papers 834, Princeton University, Department of Economics, Industrial Relations Section..
    12. Paredes, Ricardo D. & Paredes, Valentina, 2009. "Chile: academic performance and educational management under a rigid employment regime," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), December.
    13. 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.
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    Cited by:

    1. Van Keilegom, Ingrid & Vanhems, Anne, 2016. "Estimation of a semiparametric transformation model in the presence of endogeneity," TSE Working Papers 16-654, Toulouse School of Economics (TSE).
    2. Jorge Manzi & Ernesto San Martín & Sébastien Van Bellegem, 2014. "School System Evaluation by Value Added Analysis Under Endogeneity," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 130-153, January.
    3. Alejandro Carrasco & Ernesto San Mart’n, 2012. "Voucher system and school effectiveness: Reassessing school performance difference and parental choice decision-making," Estudios de Economia, University of Chile, Department of Economics, vol. 39(2 Year 20), pages 123-141, December.

    More about this item

    Keywords

    value-added; school effectiveness; multilevel model; endogeneity; instrumental variables;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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