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Using Dea To Evaluate Efficiency Of Higher Education


  • Toth, Reka


The aim of the higher education reform process both in Hungary and in the European countries is establishing a competitive, qualitative higher education with efficiently operating institutions. The question of efficiency needs increased attention not only because of the decline of the state support but also the rapid raise of the student mass. In the education system it’s not easy to measure the output of the services. The situation is more complicated if an organisation or a sector has multiple inputs and outputs. In this case a possible method of determining efficiency is Data Envelopment Analysis. In my paper I’d like to introduce this method and use it to compare the efficiency of higher education systems. Furthermore I am examining whether their efficiency is influenced by the extent of the contribution of the state and the private sector or socio-economic factors like GDP per capita and education level of parents.

Suggested Citation

  • Toth, Reka, 2009. "Using Dea To Evaluate Efficiency Of Higher Education," APSTRACT: Applied Studies in Agribusiness and Commerce, AGRIMBA, vol. 3.
  • Handle: RePEc:ags:apstra:53548

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    References listed on IDEAS

    1. Prasanna Gai & Nicholas Vause, 2006. "Measuring Investors' Risk Appetite," International Journal of Central Banking, International Journal of Central Banking, vol. 2(1), March.
    2. Findley, David F. & Wills, Kellie C. & Monsell, Brian C., 2004. "Seasonal adjustment perspectives on "Damping seasonal factors: shrinkage estimators for the X-12-ARIMA program"," International Journal of Forecasting, Elsevier, vol. 20(4), pages 551-556.
    3. Fabio Fornari, 2005. "The rise and fall of US dollar interest rate volatility: evidence from swaptions," BIS Quarterly Review, Bank for International Settlements, September.
    4. Bollerslev, Tim & Gibson, Michael & Zhou, Hao, 2011. "Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities," Journal of Econometrics, Elsevier, vol. 160(1), pages 235-245, January.
    5. Proietti Tommaso, 2004. "Seasonal Specific Structural Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-22, May.
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