Assessment of TFP in European and American higher education institutions – application of Malmquist indices
Abstract
In this study we apply Malmquist methodology, based on the estimation of distance measures through Data Envelopment Analysis (DEA), to a sample of 500 universities (in 10 European countries and the U.S.) over the period 2000 to 2010 in order to assess and compare their productivity. On average, a rise in TFP is registered for the whole European sample (strongest for Dutch and Italian HEIs), while the productivity of American HEIs suffered a slight decline. Additionally, we show that productivity growth is negatively associated with size of the institution and revenues from government, and positively with regional development in the case of the European sample, while American HEI productivity growth is characterised by a negative association with GDP and a positive one with the share of government resources out of total revenue.
First published online: 24 Nov 2016
Keyword : total factor productivity, higher education, Malmquist index, DEA, nonparametric methods
How to Cite
Wolszczak-Derlacz, J. (2018). Assessment of TFP in European and American higher education institutions – application of Malmquist indices. Technological and Economic Development of Economy, 24(2), 467–488. https://doi.org/10.3846/20294913.2016.1213197
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Akviran, N. K. 2001. Investigating technical and scale efficiencies of Australian universities through data envelopment analysis, Socio-economic Planning Sciences 35: 57–80. http://dx.doi.org/10.1016/S0038-0121(00)00010-0
Altbach, P. G.; Gumport, P. J.; Berdahl, R. O. 2011. American Higher Education in the Twenty-First Century: Social, Political, and Economic Challenges. 3rd ed. Baltimore: The Johns Hopkins University Press.
Bonaccorsi A.; Daraio C. 2005. Exploring size and agglomeration effects on public research productivity, Scientometrics 63(1): 87–120. http://dx.doi.org/10.1007/s11192-005-0205-3
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Bonaccorsi, A.; Daraio, C.; Simar, L. 2007. Efficiency and productivity in European universities: exploring trade-offs in the strategic profile, in A. Bonaccorsi, C. Daraio (Eds.). Universities and Strategic knowledge creation: specialization and performance in Europe. Cheltenham/Northampton, Massachusetts: Edward Elgar Publishing, 144–206. http://dx.doi.org/10.4337/9781847206848.00012
Bonaccorsi, A.; Daraio, C.; Simar, L. 2014. Efficiency and economies of scale and scope in European universities. A directional distance approach, Technical Report No. 8. Sapienza University of Rome.
Brennan, S.; Haelermans, C.; Ruggiero, J. 2014. Nonparametric estimation of education productivity incorporating nondiscretionary inputs with an application to Dutch schools, European Journal of Operational Research 234: 809–818. http://dx.doi.org/10.1016/j.ejor.2013.10.030
Caves, D. W.; Christensen, L. R.; Diewert, W. E. 1982. The economic theory of index numbers and the measurement of input, output, and productivity, Econometrica 50(6): 1393–1414. http://dx.doi.org/10.2307/1913388
Eurydice. 2015. National Student Fee and Support Systems in European Higher Education 2014/15.
Färe, R.; Grosskopf, S.; Lindgren, B.; Roos, P. 1992. Productivity change in Swedish pharmacies 1980–1989: a nonparametric Malmquist approach, Journal of Productivity Analysis 3: 85–102. http://dx.doi.org/10.1007/978-94-017-1923-0_6
Färe, R.; Grosskopf, S.; Lovell, C. A. K. 1994. Production frontiers. Cambridge University Press.
Farrell, M. J. 1957. The measurement of productivity efficiency, Journal of The Royal Statistical Society. Series A (General) 120(3): 253–281. http://dx.doi.org/10.2307/2343100
Førsund, F. R.; Kalhagen, K. O. 1999. Efficiency and productivity of Norwegian colleges. Memorendum No 11/99. Department of Economics University of Oslo.
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Parteka, A.; Wolszczak-Derlacz, J. 2013. Dynamics of productivity in higher education – cross-European evidence based on bootstrapped Malmquist indices, Journal of Productivity Analysis 40(1): 67–82. http://dx.doi.org/10.1007/s11123-012-0320-0
Sav, G. T. 2012. Stochastic cost frontier and inefficiency estimates of public and private universities: does government matter?, International Advances in Economic Research 18(2): 187–198. http://dx.doi.org/10.1007/s11294-012-9353-4
Sav, G. T. 2013. Effects of financial source dependency on public university operating efficiencies: data envelopment single-stage and Tobit two-stage evaluations, Review of Economics & Finance 3: 63–73.
Simar, L.; Wilson, P. W. 1999. Estimating and bootstrapping Malmquist indices, European Journal of Operational Research 115: 459–471. http://dx.doi.org/10.1016/S0377-2217(97)00450-5
Staiger, D.; Stock, J., 1997. Instrumental variables regression with weak instruments, Econometrica 65: 557–586. http://dx.doi.org/10.2307/2171753
Unesco-IUS/OECD/Eurostat data collection manual. 2004. Data collection on education systems. Paris: OECD.
Varga, A.; Horváth, M. 2013. Institutional and regional factors behind university patenting in Europe: an exploratory spatial analysis using EUMIDA data, in 35th DRUID Celebration Conference 2013, 17–19 June 2013, Barcelona, Spain.
Wilson, P. W. 2008. FEAR 1.0: A software package for frontier efficiency analysis with R, Socio-Economic Planning Sciences 42: 247–254. http://dx.doi.org/10.1016/j.seps.2007.02.001
Wolszczak-Derlacz, J.; Parteka, A. 2011. Efficiency of European public higher education institutions: a two-stage multicountry approach, Scientometrics 89(3): 887–917. http://dx.doi.org/10.1007/s11192-011-0484-9
Worthington, A. C. 2001. An empirical survey of frontier efficiency measurement techniques in education, Education Economics 9(3): 245–268. http://dx.doi.org/10.1080/09645290110086126
Yang, H.; Pollitt, M. 2012. Incorporating undesirable outputs into Malmquist TFP indices with an unbalanced data panel of Chinese power plants, Applied Economics Letters 19: 227–283. http://dx.doi.org/10.1080/13504851.2011.572843
Agasisti, T.; Pérez-Esparrells, C. 2010. Comparing efficiency in a cross-country perspective: the case of Italian and Spanish state universities, Higher Education 59(1): 85–103. http://dx.doi.org/10.1007/s10734-009-9235-8
Agasisti, T.; Pohl, C. 2012. Comparing German and Italian public universities: convergence or divergence in the higher education landscape?, Managerial and Decision Economics 33: 71–85. http://dx.doi.org/10.1002/mde.1561
Aghion, P.; Dewatripont, M.; Hoxby, C.; Mas-Colell, A.; Sapir, A. 2010. The governance and performance of universities: evidence from Europe and the US, Economic Policy 25(61): 7–59. http://dx.doi.org/10.1111/j.1468-0327.2009.00238.x
Aguilera-Barchet, B. 2012. A higher education for the twenty-first century: European and US approaches, Centre for European Studies.
Akviran, N. K. 2001. Investigating technical and scale efficiencies of Australian universities through data envelopment analysis, Socio-economic Planning Sciences 35: 57–80. http://dx.doi.org/10.1016/S0038-0121(00)00010-0
Altbach, P. G.; Gumport, P. J.; Berdahl, R. O. 2011. American Higher Education in the Twenty-First Century: Social, Political, and Economic Challenges. 3rd ed. Baltimore: The Johns Hopkins University Press.
Bonaccorsi A.; Daraio C. 2005. Exploring size and agglomeration effects on public research productivity, Scientometrics 63(1): 87–120. http://dx.doi.org/10.1007/s11192-005-0205-3
Bonaccorsi, A.; Daraio, C. (Eds.). 2007. Universities and strategic knowledge creation: specialization and performance in Europe. Cheltenham/Northampton, Massachusetts: Edward Elgar Publishing.
Bonaccorsi, A.; Daraio, C.; Simar, L. 2007. Efficiency and productivity in European universities: exploring trade-offs in the strategic profile, in A. Bonaccorsi, C. Daraio (Eds.). Universities and Strategic knowledge creation: specialization and performance in Europe. Cheltenham/Northampton, Massachusetts: Edward Elgar Publishing, 144–206. http://dx.doi.org/10.4337/9781847206848.00012
Bonaccorsi, A.; Daraio, C.; Simar, L. 2014. Efficiency and economies of scale and scope in European universities. A directional distance approach, Technical Report No. 8. Sapienza University of Rome.
Brennan, S.; Haelermans, C.; Ruggiero, J. 2014. Nonparametric estimation of education productivity incorporating nondiscretionary inputs with an application to Dutch schools, European Journal of Operational Research 234: 809–818. http://dx.doi.org/10.1016/j.ejor.2013.10.030
Caves, D. W.; Christensen, L. R.; Diewert, W. E. 1982. The economic theory of index numbers and the measurement of input, output, and productivity, Econometrica 50(6): 1393–1414. http://dx.doi.org/10.2307/1913388
Eurydice. 2015. National Student Fee and Support Systems in European Higher Education 2014/15.
Färe, R.; Grosskopf, S.; Lindgren, B.; Roos, P. 1992. Productivity change in Swedish pharmacies 1980–1989: a nonparametric Malmquist approach, Journal of Productivity Analysis 3: 85–102. http://dx.doi.org/10.1007/978-94-017-1923-0_6
Färe, R.; Grosskopf, S.; Lovell, C. A. K. 1994. Production frontiers. Cambridge University Press.
Farrell, M. J. 1957. The measurement of productivity efficiency, Journal of The Royal Statistical Society. Series A (General) 120(3): 253–281. http://dx.doi.org/10.2307/2343100
Førsund, F. R.; Kalhagen, K. O. 1999. Efficiency and productivity of Norwegian colleges. Memorendum No 11/99. Department of Economics University of Oslo.
Johnes, J. 2004. Efficiency measurement, in G. Johnes, J. Johnes (Eds.) The International Handbook on the Economics of Education. Cheltenham: Edward Elgar, 613–742. http://dx.doi.org/10.4337/9781845421694.00021
National Center for Education Statistics. 2015. Digest of Education Statistics, 2013. Institute of Education Sciences. U.S. Department of Education, Washington, DC.
Nazarko, J.; Šaparauskas, J. 2014. Application of DEA method in efficiency evaluation of public higher education institutions, Technological and Economic Development of Economy 20(1): 25–44. http://dx.doi.org/10.3846/20294913.2014.837116
OECD. 2002. Frascati manual. Proposed standard practice for surveys on research and experimental development. OECD, Paris.
Panagiotis, R. 2014. Meta-regression analysis of higher education productivity growth studies. Master’s thesis, University of Macedonia [online], [cited 20 November 2014]. Available from Internet: https://dspace.lib.uom.gr/dspace/bitstream/2159/16057/3/RavanosPanagiotisMsc2014.pdf
Parteka, A.; Wolszczak-Derlacz, J. 2013. Dynamics of productivity in higher education – cross-European evidence based on bootstrapped Malmquist indices, Journal of Productivity Analysis 40(1): 67–82. http://dx.doi.org/10.1007/s11123-012-0320-0
Sav, G. T. 2012. Stochastic cost frontier and inefficiency estimates of public and private universities: does government matter?, International Advances in Economic Research 18(2): 187–198. http://dx.doi.org/10.1007/s11294-012-9353-4
Sav, G. T. 2013. Effects of financial source dependency on public university operating efficiencies: data envelopment single-stage and Tobit two-stage evaluations, Review of Economics & Finance 3: 63–73.
Simar, L.; Wilson, P. W. 1999. Estimating and bootstrapping Malmquist indices, European Journal of Operational Research 115: 459–471. http://dx.doi.org/10.1016/S0377-2217(97)00450-5
Staiger, D.; Stock, J., 1997. Instrumental variables regression with weak instruments, Econometrica 65: 557–586. http://dx.doi.org/10.2307/2171753
Unesco-IUS/OECD/Eurostat data collection manual. 2004. Data collection on education systems. Paris: OECD.
Varga, A.; Horváth, M. 2013. Institutional and regional factors behind university patenting in Europe: an exploratory spatial analysis using EUMIDA data, in 35th DRUID Celebration Conference 2013, 17–19 June 2013, Barcelona, Spain.
Wilson, P. W. 2008. FEAR 1.0: A software package for frontier efficiency analysis with R, Socio-Economic Planning Sciences 42: 247–254. http://dx.doi.org/10.1016/j.seps.2007.02.001
Wolszczak-Derlacz, J.; Parteka, A. 2011. Efficiency of European public higher education institutions: a two-stage multicountry approach, Scientometrics 89(3): 887–917. http://dx.doi.org/10.1007/s11192-011-0484-9
Worthington, A. C. 2001. An empirical survey of frontier efficiency measurement techniques in education, Education Economics 9(3): 245–268. http://dx.doi.org/10.1080/09645290110086126
Yang, H.; Pollitt, M. 2012. Incorporating undesirable outputs into Malmquist TFP indices with an unbalanced data panel of Chinese power plants, Applied Economics Letters 19: 227–283. http://dx.doi.org/10.1080/13504851.2011.572843