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Técnicas para datos multinivel: Aplicación a los determinantes del rendimiento educativo
[Techniques for multilevel data: Application to the determinants of educational performance]

Author

Listed:
  • Herrera Gómez, Marcos
  • Aráoz, M. Florencia
  • de Lafuente, Gisela
  • D'jorge, Lucrecia
  • Granado, M. José
  • Michel Rivero, Andrés
  • Paz Terán, Corina

Abstract

This paper consists of the application of the Hierarchical lineal model (multilevel methodology) which takes in consideration the interaction between individual and aggregated variables. It is intented to measure eterminants of student performance in their last year of school in three departments of Tucuman’s province (educational census year 2000). Data has multilevel structure indeed students belong to different schools. The GEE method “Generalized Estimated Equation”, suitable for conglomerate data, allows to model correlation between students within the same school. So multilevel modeling strategies are more likely to produce unbiased estimators than Least Squares, which suppose independence between observations.

Suggested Citation

  • Herrera Gómez, Marcos & Aráoz, M. Florencia & de Lafuente, Gisela & D'jorge, Lucrecia & Granado, M. José & Michel Rivero, Andrés & Paz Terán, Corina, 2005. "Técnicas para datos multinivel: Aplicación a los determinantes del rendimiento educativo [Techniques for multilevel data: Application to the determinants of educational performance]," MPRA Paper 38736, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:38736
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    References listed on IDEAS

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    1. Carolyn J. Heinrich & Laurence E. Lynn Jr., 1999. "Means And Ends: A Comparative Study Of Empirical Methods For Investigating Governance And Performance," JCPR Working Papers 109, Northwestern University/University of Chicago Joint Center for Poverty Research.
    2. Eric A. Hanushek & Lori L. Taylor, 1990. "Alternative Assessments of the Performance of Schools: Measurement of State Variations in Achievement," Journal of Human Resources, University of Wisconsin Press, vol. 25(2), pages 179-201.
    3. Alejandra Mizala & Pilar Romaguera, 2000. "Determinación de factores explicativos de los resultados escolares en educación media en Chile," Documentos de Trabajo 85, Centro de Economía Aplicada, Universidad de Chile.
    4. Alan B. Krueger, 1999. "Experimental Estimates of Education Production Functions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(2), pages 497-532.
    5. Hanushek, Eric A, 1995. "Interpreting Recent Research on Schooling in Developing Countries," The World Bank Research Observer, World Bank, vol. 10(2), pages 227-246, August.
    6. repec:fth:prinin:379 is not listed on IDEAS
    7. Alejandra Mizala & Pilar Romaguera & Teresa Reinaga, 1999. "Factores que inciden en el rendimiento escolar en Bolivia," Documentos de Trabajo 61, Centro de Economía Aplicada, Universidad de Chile.
    8. Alan Krueger, 1997. "Experimental Estimates of Education Production Functions," Working Papers 758, Princeton University, Department of Economics, Industrial Relations Section..
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    Cited by:

    1. Herrera Gómez, Marcos, 2006. "Efecto de la Competencia de la Educación Privada sobre la Calidad de la Educación Pública [Effect of Private Education Competition on the Quality of Public Education]," MPRA Paper 30772, University Library of Munich, Germany.

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    More about this item

    Keywords

    Análisis Multinivel; GEE; Rendimiento Educativo;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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