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Measuring the efficiency of teaching activities in Italian universities: An information theoretic approach

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  • Laureti, Tiziana
  • Secondi, Luca
  • Biggeri, Luigi

Abstract

The measurement of teaching efficiency of Italian universities has become a topic of much interest and debate in recent years. The aim of this study is to fully explore the potential of panel data in the analysis of teaching efficiency both by modelling human capital formation in the university as a series of sub-processes and by using various models to account for observed and unobserved factors which generate heterogeneity. The new approach for estimating a stochastic frontier model based on the Generalized Maximum Entropy method provides further insights into the measurement of university teaching performance. The evolution of efficiency throughout the entire study period was also analyzed.

Suggested Citation

  • Laureti, Tiziana & Secondi, Luca & Biggeri, Luigi, 2014. "Measuring the efficiency of teaching activities in Italian universities: An information theoretic approach," Economics of Education Review, Elsevier, vol. 42(C), pages 147-164.
  • Handle: RePEc:eee:ecoedu:v:42:y:2014:i:c:p:147-164
    DOI: 10.1016/j.econedurev.2014.07.001
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    as
    1. Johnes, Geraint & Johnes, Jill, 1993. "Measuring the Research Performance of UK Economics Departments: An Application of Data Envelopment Analysis," Oxford Economic Papers, Oxford University Press, vol. 45(2), pages 332-347, April.
    2. Peter C. Smith & Andrew Street, 2005. "Measuring the efficiency of public services: the limits of analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 401-417, March.
    3. Philip Andrew Stevens, 2005. "A Stochastic Frontier Analysis of English and Welsh Universities," Education Economics, Taylor & Francis Journals, vol. 13(4), pages 355-374.
    4. repec:ebl:ecbull:v:30:y:2010:i:1:p:587-596 is not listed on IDEAS
    5. Johnes, Jill, 1996. "Performance assessment in higher education in Britain," European Journal of Operational Research, Elsevier, vol. 89(1), pages 18-33, February.
    6. Randall Campbell & Kevin Rogers & Jon Rezek, 2008. "Efficient frontier estimation: a maximum entropy approach," Journal of Productivity Analysis, Springer, vol. 30(3), pages 213-221, December.
    7. Antreas Athanassopoulos & Estelle Shale, 1997. "Assessing the Comparative Efficiency of Higher Education Institutions in the UK by the Means of Data Envelopment Analysis," Education Economics, Taylor & Francis Journals, vol. 5(2), pages 117-134.
    8. Malcolm Abbott & Chris Doucouliagos, 2009. "Competition and efficiency: overseas students and technical efficiency in Australian and New Zealand universities," Education Economics, Taylor & Francis Journals, vol. 17(1), pages 31-57.
    9. Gerhard Kempkes & Carsten Pohl, 2010. "The efficiency of German universities-some evidence from nonparametric and parametric methods," Applied Economics, Taylor & Francis Journals, vol. 42(16), pages 2063-2079.
    10. Izadi, Hooshang & Johnes, Geraint & Oskrochi, Reza & Crouchley, Robert, 2002. "Stochastic frontier estimation of a CES cost function: the case of higher education in Britain," Economics of Education Review, Elsevier, vol. 21(1), pages 63-71, February.
    11. Berger, Allen N. & Mester, Loretta J., 1997. "Inside the black box: What explains differences in the efficiencies of financial institutions?," Journal of Banking & Finance, Elsevier, vol. 21(7), pages 895-947, July.
    12. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    13. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
    14. Avkiran, Necmi K., 2001. "Investigating technical and scale efficiencies of Australian Universities through data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 35(1), pages 57-80, March.
    15. Di Pietro, Giorgio & Cutillo, Andrea, 2008. "Degree flexibility and university drop-out: The Italian experience," Economics of Education Review, Elsevier, vol. 27(5), pages 546-555, October.
    16. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    17. Johnes, Geraint & Johnes, Jill, 2009. "Higher education institutions' costs and efficiency: Taking the decomposition a further step," Economics of Education Review, Elsevier, vol. 28(1), pages 107-113, February.
    18. Tommaso Agasisti & Carlo Salerno, 2007. "Assessing the Cost Efficiency of Italian Universities," Education Economics, Taylor & Francis Journals, vol. 15(4), pages 455-471.
    19. Zoghbi, Ana Carolina & Rocha, Fabiana & Mattos, Enlinson, 2013. "Education production efficiency: Evidence from Brazilian universities," Economic Modelling, Elsevier, vol. 31(C), pages 94-103.
    20. Chambers,Robert G., 1988. "Applied Production Analysis," Cambridge Books, Cambridge University Press, number 9780521314275, December.
    21. William Greene, 2004. "Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization's panel data on national health care systems," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 959-980.
    22. repec:kap:iaecre:v:14:y:2008:i:1:p:76-89 is not listed on IDEAS
    23. Miika Linna, 1998. "Measuring hospital cost efficiency with panel data models," Health Economics, John Wiley & Sons, Ltd., vol. 7(5), pages 415-427.
    24. 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.
    25. Lakshmi Balasubramanyan & Spiro Stefanou & Jeffrey Stokes, 2012. "An entropy approach to size and variance heterogeneity in U.S. commercial banks," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(3), pages 728-749, July.
    26. Tommaso Agasisti & Geraint Johnes, 2010. "Heterogeneity and the evaluation of efficiency: the case of Italian universities," Applied Economics, Taylor & Francis Journals, vol. 42(11), pages 1365-1375.
    27. Geraint Johnes & Astrid Schwarzenberger, 2011. "Differences in cost structure and the evaluation of efficiency: the case of German universities," Education Economics, Taylor & Francis Journals, vol. 19(5), pages 487-499, January.
    28. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    29. Golan, Amos, 2008. "Information and Entropy Econometrics — A Review and Synthesis," Foundations and Trends(R) in Econometrics, now publishers, vol. 2(1–2), pages 1-145, February.
    30. Johnes, Geraint, 1997. "Costs and Industrial Structure in Contemporary British Higher Education," Economic Journal, Royal Economic Society, vol. 107(442), pages 727-737, May.
    31. F. Belloc & A. Maruotti & L. Petrella, 2011. "How individual characteristics affect university students drop-out: a semiparametric mixed-effects model for an Italian case study," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2225-2239.
    32. Breu, Theodore M. & Raab, Raymond L., 1994. "Efficiency and perceived quality of the nation's "top 25" National Universities and National Liberal Arts Colleges: An application of data envelopment analysis to higher education," Socio-Economic Planning Sciences, Elsevier, vol. 28(1), pages 33-45.
    33. Jesus Felipe, 1998. "On the interpretation of coefficients in multiplicative-logarithmic functions: a reconsideration," Applied Economics Letters, Taylor & Francis Journals, vol. 5(6), pages 397-400.
    34. Alfons Lansink & Elvira Silva & Spiro Stefanou, 2001. "Inter-Firm and Intra-Firm Efficiency Measures," Journal of Productivity Analysis, Springer, vol. 15(3), pages 185-199, May.
    35. L. Kurkalova & A. Carriquiry, 2003. "Input- and Output-Oriented Technical Efficiency of Ukrainian Collective Farms, 1989–1992: Bayesian Analysis of a Stochastic Production Frontier Model," Journal of Productivity Analysis, Springer, vol. 20(2), pages 191-211, September.
    36. Pedro Macedo & Elvira Silva, 2010. "A stochastic production frontier model with a translog specification using the generalized maximum entropy estimator," Economics Bulletin, AccessEcon, vol. 30(1), pages 587-596.
    37. Johnes, Jill, 2006. "Measuring teaching efficiency in higher education: An application of data envelopment analysis to economics graduates from UK Universities 1993," European Journal of Operational Research, Elsevier, vol. 174(1), pages 443-456, October.
    38. Shinji Yane & Sanford Berg, 2013. "Sensitivity analysis of efficiency rankings to distributional assumptions: applications to Japanese water utilities," Applied Economics, Taylor & Francis Journals, vol. 45(17), pages 2337-2348, June.
    39. Amos Golan & Jeffrey M. Perloff & Edward Z. Shen, 2001. "Estimating A Demand System With Nonnegativity Constraints: Mexican Meat Demand," The Review of Economics and Statistics, MIT Press, vol. 83(3), pages 541-550, August.
    40. Tommaso Agasisti & Antonio Dal Bianco, 2006. "Data envelopment analysis to the Italian university system: theoretical issues and policy implications," International Journal of Business Performance Management, Inderscience Enterprises Ltd, vol. 8(4), pages 344-367.
    41. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    42. Dino Rizzi, 2001. "L'efficienza dei dipartimenti dell'Università Ca' Foscari di Venezia via DEA e DFA," ECONOMIA PUBBLICA, FrancoAngeli Editore, vol. 2001(3).
    43. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
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    Cited by:

    1. Yaisawarng, Suthathip & Ng, Ying Chu, 2014. "The impact of higher education reform on research performance of Chinese universities," China Economic Review, Elsevier, vol. 31(C), pages 94-105.
    2. Gralka, Sabine, 2018. "Stochastic frontier analysis in higher education: A systematic review," CEPIE Working Papers 05/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    3. Facundo Quiroga-Martínez & Esteban Fernández-Vázquez & Catalina Lucía Alberto, 2018. "Efficiency in public higher education on Argentina 2004–2013: institutional decisions and university-specific effects," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 27(1), pages 1-18, December.
    4. Guarini, Giulio & Laureti, Tiziana & Garofalo, Giuseppe, 2018. "Territorial and individual educational inequality: A Capability Approach analysis for Italy," Economic Modelling, Elsevier, vol. 71(C), pages 247-262.
    5. A.P. Gorina, 2016. "Issues and Prospectives of the Educational Service Market Modernization," European Research Studies Journal, European Research Studies Journal, vol. 0(3B), pages 227-238.
    6. Vanesa D’Elia & Gustavo Ferro, 2019. "Empirical Efficiency Measurement in Higher Education: An Overview," CEMA Working Papers: Serie Documentos de Trabajo. 708, Universidad del CEMA.
    7. M.G. Leontev & N.G. Bondarenko & T.A. Shebzuhova & S.S. Butko & L.I. Egorova, 2018. "Improving the Efficiency of University Management: Teacher’s Performance Monitoring as a Tool to Promote the Quality of Education," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 527-540.
    8. Calogero Guccio & Marco Ferdinando Martorana & Isidoro Mazza, 2016. "Efficiency assessment and convergence in teaching and research in Italian public universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1063-1094, June.

    More about this item

    Keywords

    University teaching efficiency; Heterogeneity; Stochastic frontier approach; Generalized Maximum Entropy method; Panel data;

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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