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Do dropout and environmental factors matter? A directional distance function assessment of tunisian education efficiency

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  • Ben Yahia, Fatma
  • Essid, Hédi
  • Rebai, Sonia

Abstract

The purpose of this paper is to investigate the education efficiency in Tunisia based on a sample of secondary schools. We place some special focus on schools resources and corresponding dropout levels. We use the Directional Distance Function (DDF) methodology to simultaneously deal with bad outputs and non-discretionary inputs. Our assessment is based on Data Envelopment Analysis (DEA) method. The data is extracted from the Program for International Student Assessment (PISA) 2012 survey. We generate four models through various inputs and outputs specifications while considering dropout levels and education environment. Our empirical study reveals strong influence between education performance and both school infrastructure and educational resources. In particular, the financial constraints seem to have real effect on the dropout levels.

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  • Ben Yahia, Fatma & Essid, Hédi & Rebai, Sonia, 2018. "Do dropout and environmental factors matter? A directional distance function assessment of tunisian education efficiency," International Journal of Educational Development, Elsevier, vol. 60(C), pages 120-127.
  • Handle: RePEc:eee:injoed:v:60:y:2018:i:c:p:120-127
    DOI: 10.1016/j.ijedudev.2017.11.004
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    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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    More about this item

    Keywords

    Educational economics; Efficiency; Data envelopment analysis; Directional distance function; Undesirable outputs; Non-discretionary inputs;
    All these keywords.

    JEL classification:

    • D2 - Microeconomics - - Production and Organizations
    • I2 - Health, Education, and Welfare - - Education

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