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Productivity analysis of Belarusian higher education system

Author

Listed:
  • Alexandr Gedranovich
  • Mykhaylo Salnykov

    (Belarusian Economic Research and Outreach Center (BEROC))

Abstract

In this paper we explore the issue of the measurement of productivity in the context of higher education. We suggest applying data envelopment analysis (DEA) to estimate the productivity scores for universities of Belarus. This assessment will help to find out (a) if it possible to construct alternative tier-based ratings using DEA and peeling procedure; (b) what determines the difference in productivity between public and private universities; (c) what policy should be undertaken in order to improve the performance of universities.

Suggested Citation

  • Alexandr Gedranovich & Mykhaylo Salnykov, 2012. "Productivity analysis of Belarusian higher education system," BEROC Working Paper Series 16, Belarusian Economic Research and Outreach Center (BEROC).
  • Handle: RePEc:bel:wpaper:16
    as

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    File URL: http://www.beroc.by/webroot/delivery/files/WP16_eng_Gedranovich_Salnykov.pdf
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    References listed on IDEAS

    as
    1. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    2. Wilson, Paul W, 1993. "Detecting Outliers in Deterministic Nonparametric Frontier Models with Multiple Outputs," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 319-323, July.
    3. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    4. Johnes, Jill, 2006. "Data envelopment analysis and its application to the measurement of efficiency in higher education," Economics of Education Review, Elsevier, vol. 25(3), pages 273-288, June.
    5. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    6. Jean-Charles Billaut & Denis Bouyssou & Philippe Vincke, 2010. "Should you believe in the Shanghai ranking?," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(1), pages 237-263, July.
    7. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    9. Abbott, M. & Doucouliagos, C., 2003. "The efficiency of Australian universities: a data envelopment analysis," Economics of Education Review, Elsevier, vol. 22(1), pages 89-97, February.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Universities; Ratings; Data envelopment analysis; Super-efficiency; Assuarance region; Peeling;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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