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Forecasting The Composition Of Demand For Higher Education Degrees By Genetic Algorithms

Author

Listed:
  • Montserrat Hernández-LÓPEZ

    (Departamento de Economía Aplicada y Métodos Cuantitativos, University of La Laguna)

  • José Juan Cáceres-HERNÁNDEZ

    (Departamento de Economía Aplicada y Métodos Cuantitativos, University of La LagunaTitle:)

Abstract

A genetic algorithm is developed to forecast the relative presence of different university studies in the higher education demand in the field of economics and business/management as a whole. A selection operator is defined that assumes that the better the job opportunities associated with a specific university study, the higher the future demand for such a degree. A transition matrix takes other factors into account which may influence on the changes in demand. The proposed algorithm is applied to the original populations of students enrolled on 2005/2006 to 2007/2008 courses. Then, a new algorithm, whose elements are corrected to adjust the forecasts, is applied to obtain the forecast of the demand composition on the 2009/2010 course. This methodological proposal is shown to be able to provide the type of forecast which is very useful in policy making decisions in the recent process of building the European Higher Education Area.

Suggested Citation

  • Montserrat Hernández-LÓPEZ & José Juan Cáceres-HERNÁNDEZ, 2016. "Forecasting The Composition Of Demand For Higher Education Degrees By Genetic Algorithms," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(3), pages 153-172.
    • Handle: RePEc:cys:ecocyb:v:50:y:2016:i:3:p:153-172
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    More about this item

    Keywords

    higher education; forecasting; genetic algorithms.;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions

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