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Measuring School Demand in the Presence of Spatial Dependence. A Conditional Approach

Author

Listed:
  • Laura López-Torres
  • Diego Prior Jiménez

    (Business Department, Universitat Autónoma de Barcelona)

Abstract

Improving educational quality is an important public policy goal. However, its success requires identifying factors associated with student achievement. At the core of these proposals lies the principle that increased public school quality can make school system more efficient, resulting in correspondingly stronger performance by students. Nevertheless, the public educational system is not devoid of competition which arises, among other factors, through the efficiency of management and the geographical location of schools. Moreover, families in Spain appear to choose a school on the grounds of location. In this environment, the objective of this paper is to analyze whether geographical space has an impact on the relationship between the level of technical qu ality of public schools (measured by the efficiency score) and the school demand index. To do this, an empirical application is performed on a sample of 1,695 public schools in the region of Catalonia (Spain). This application shows the effects of spatial autocorrelation on the estimation of the parameters and how these problems are addressed through spatial econometrics models. The results confirm that space has a moderating effect on the relationship between efficiency and school demand, although only in urban unicipalities.

Suggested Citation

  • Laura López-Torres & Diego Prior Jiménez, 2014. "Measuring School Demand in the Presence of Spatial Dependence. A Conditional Approach," Working Papers 1403, Departament Empresa, Universitat Autònoma de Barcelona, revised Jun 2014.
  • Handle: RePEc:bbe:wpaper:1403
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    1. Ruggiero, John, 1998. "Non-discretionary inputs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 111(3), pages 461-469, December.
    2. Corman, H., 2003. "The effects of state policies, individual characteristics, family characteristics, and neighbourhood characteristics on grade repetition in the United States," Economics of Education Review, Elsevier, vol. 22(4), pages 409-420, August.
    3. Hanushek, Eric A & Rivkin, Steven G & Taylor, Lori L, 1996. "Aggregation and the Estimated Effects of School Resources," The Review of Economics and Statistics, MIT Press, vol. 78(4), pages 611-627, November.
    4. Florax, Raymond & Folmer, Henk, 1992. "Specification and estimation of spatial linear regression models : Monte Carlo evaluation of pre-test estimators," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 405-432, September.
    5. Caroline M. Hoxby, 2000. "Does Competition among Public Schools Benefit Students and Taxpayers?," American Economic Review, American Economic Association, vol. 90(5), pages 1209-1238, December.
    6. Krugman, Paul, 1998. "What's New about the New Economic Geography?," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 14(2), pages 7-17, Summer.
    7. Subhash C. Ray, 1991. "Resource-Use Efficiency in Public Schools: A Study of Connecticut Data," Management Science, INFORMS, vol. 37(12), pages 1620-1628, December.
    8. Feng, Li & Sass, Tim R., 2013. "What makes special-education teachers special? Teacher training and achievement of students with disabilities," Economics of Education Review, Elsevier, vol. 36(C), pages 122-134.
    9. Smith, Peter & Mayston, David, 1987. "Measuring efficiency in the public sector," Omega, Elsevier, vol. 15(3), pages 181-189.
    10. Anselin, Luc, 2007. "Spatial econometrics in RSUE: Retrospect and prospect," Regional Science and Urban Economics, Elsevier, vol. 37(4), pages 450-456, July.
    11. Cinzia Daraio & Léopold Simar, 2005. "Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach," Journal of Productivity Analysis, Springer, vol. 24(1), pages 93-121, September.
    12. Julie Harrison & Paul Rouse & Jamie Armstrong, 2012. "Categorical and continuous non-discretionary variables in data envelopment analysis: a comparison of two single-stage models," Journal of Productivity Analysis, Springer, vol. 37(3), pages 261-276, June.
    13. repec:asg:wpaper:1013 is not listed on IDEAS
    14. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    15. Barrow, Lisa, 2002. "School choice through relocation: evidence from the Washington, D.C. area," Journal of Public Economics, Elsevier, vol. 86(2), pages 155-189, November.
    16. Badin, Luiza & Daraio, Cinzia & Simar, Léopold, 2010. "Optimal bandwidth selection for conditional efficiency measures: A data-driven approach," European Journal of Operational Research, Elsevier, vol. 201(2), pages 633-640, March.
    17. Andrew Johnson & John Ruggiero, 2014. "Nonparametric measurement of productivity and efficiency in education," Annals of Operations Research, Springer, vol. 221(1), pages 197-210, October.
    18. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    19. Jerik Hanushek & Dennis Kimko, 2006. "Schooling, Labor-force Quality, and the Growth of Nations," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 1, pages 154-193.
    20. Hanushek, Eric A, 1986. "The Economics of Schooling: Production and Efficiency in Public Schools," Journal of Economic Literature, American Economic Association, vol. 24(3), pages 1141-1177, September.
    21. M. Portela & A. Camanho & A. Keshvari, 2013. "Assessing the evolution of school performance and value-added: trends over four years," Journal of Productivity Analysis, Springer, vol. 39(1), pages 1-14, February.
    22. Kristof De Witte & Mika Kortelainen, 2013. "What explains the performance of students in a heterogeneous environment? Conditional efficiency estimation with continuous and discrete environmental variables," Applied Economics, Taylor & Francis Journals, vol. 45(17), pages 2401-2412, June.
    23. Eric A. Hanushek, 2003. "The Failure of Input-Based Schooling Policies," Economic Journal, Royal Economic Society, vol. 113(485), pages 64-98, February.
    24. López-Torres, Laura & Prior, Diego, 2013. "Do Parents Perceive The Technical Quality Of Public Schools? An Activity Analysis Approach," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 13(3), pages 39-60.
    25. Rubenstein, Ross & Schwartz, Amy Ellen & Stiefel, Leanna & Amor, Hella Bel Hadj, 2007. "From districts to schools: The distribution of resources across schools in big city school districts," Economics of Education Review, Elsevier, vol. 26(5), pages 532-545, October.
    26. Zanzig, Blair R., 1997. "Measuring the impact of competition in local government education markets on the cognitive achievement of students," Economics of Education Review, Elsevier, vol. 16(4), pages 431-441, October.
    27. Léopold Simar, 2003. "Detecting Outliers in Frontier Models: A Simple Approach," Journal of Productivity Analysis, Springer, vol. 20(3), pages 391-424, November.
    28. Johnes, Jill, 2006. "Data envelopment analysis and its application to the measurement of efficiency in higher education," Economics of Education Review, Elsevier, vol. 25(3), pages 273-288, June.
    29. Thieme, Claudio & Prior, Diego & Tortosa-Ausina, Emili, 2013. "A multilevel decomposition of school performance using robust nonparametric frontier techniques," Economics of Education Review, Elsevier, vol. 32(C), pages 104-121.
    30. Jose Manuel Cordero-Ferrera & Francisco Pedraja-Chaparro & Javier Salinas-Jimenez, 2008. "Measuring efficiency in education: an analysis of different approaches for incorporating non-discretionary inputs," Applied Economics, Taylor & Francis Journals, vol. 40(10), pages 1323-1339.
    31. Muniz, M. A., 2002. "Separating managerial inefficiency and external conditions in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(3), pages 625-643, December.
    32. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
    33. Joris Pinkse & Margaret E. Slade, 2010. "The Future Of Spatial Econometrics," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 103-117, February.
    34. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
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    More about this item

    Keywords

    school efficiency; school demand; spatial econometrics; spatial dependence;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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