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Competition among schools and educational quality: Tension between various objectives of educational policy

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  • Gajardo, Felipe
  • Grau, Nicolás

Abstract

Using Chilean data for fourth grade students, this research studies the effect of competition among schools on the results of standardized tests, academic self-esteem and motivation, the climate within the school, civic participation, and healthy lifestyle habits. To address the potential bias due to the endogeneity of the competition among schools, an instrumental variable approach is implemented, using instruments associated with the size of each “educational market.” The results show that an increase of one standard deviation in competition among schools generates a moderate increase in standardized test results (0.06 standard deviations) and a more significant decrease in the other indicators of quality (between 0.02 and 0.16 standard deviations). Therefore, the results suggest a tension in the school between various objectives of educational policy, in which pressure to improve standardized test scores resulting from competition among schools could produce an undesired effect of deterioration in other dimensions of quality.

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  • Gajardo, Felipe & Grau, Nicolás, 2019. "Competition among schools and educational quality: Tension between various objectives of educational policy," International Journal of Educational Development, Elsevier, vol. 65(C), pages 123-133.
    • Handle: RePEc:eee:injoed:v:65:y:2019:i:c:p:123-133
    DOI: 10.1016/j.ijedudev.2018.03.004
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    Cited by:

    1. Diego Amador & Juan-Andrés Castro & Nicolás Grau, 2019. "Telling schools apart: the role of preferences, constraints, and the ability to differentiate between schools in parents' choices," Documentos CEDE 17343, Universidad de los Andes, Facultad de Economía, CEDE.
    2. Lazaretti, Lauana Rossetto & Aniceto França, Marco Túlio, 2020. "School competition and performance indicators: evidence from the creation of federal education institutions in Brazil," International Journal of Educational Development, Elsevier, vol. 77(C).
    3. Rebai, Sonia & Ben Yahia, Fatma & Essid, Hédi, 2020. "A graphically based machine learning approach to predict secondary schools performance in Tunisia," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).

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