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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
    as

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    References listed on IDEAS

    as
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    More about this item

    Keywords

    school efficiency; school demand; spatial econometrics; spatial dependence;

    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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