Measuring Public Sector Efficiency: A Study of Economics Departments at Australian Universities

Madden, Gary; Savage, Scott; Kemp, Steven

doi:10.1080/09645299700000013

Cited by 111 publications

(82 citation statements)

References 15 publications

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“…Mean technical efficiencies computed from department level studies vary as follows: 50 to 60% for UK economics departments (Johnes & Johnes 1992;; around 70% in UK departments of chemistry and physics (Beasley 1990); 65 to 82% in Australian departments of economics (Madden et al 1997); 72% in economics research units in Finland (Korhonen et al 2001); and 82 to 87% in the administration sector of Australian universities (Coelli et al 1998). Evidence from HEI level studies suggests that mean technical efficiency varies from around 70 to 80% (Ahn & Seiford 1993;Ng & Li 2000) to well over 90% (Ahn et al 1989;Breu & Raab 1994 with nearly 90% achieving an efficiency score of 1, compared to around 66% of the engineering universities.…”

Section: Methodsmentioning

confidence: 99%

Measuring the research performance of Chinese higher education institutions using data envelopment analysis

Johnes

2008

China Economic Review

235

110

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This study uses data envelopment analysis (DEA) to examine the relative efficiency of over 100 selected Chinese regular universities. Various models are developed to measure the research efficiency of these higher education institutions (HEIs) using data for 2003 and 2004. The findings show that the level of efficiency depends on whether or not a subjective measure of research output (based on experts' opinions of the HEIs) is included as an output in the model. Mean efficiency is higher when the reputation variable is included (around 90%) than when it is not (mean efficiency is around 55% in this case). However, the rankings of the universities are remarkably insensitive to whether or not this variable is included. Bootstrapping procedures are used to find the 95% confidence intervals for the efficiencies, and indicate that the best and worst performing institutions are significantly different from each other; only the middle-performing 30% of HEIs cannot be distinguished from each other in terms of their performance. Further investigation suggests that regional location, source of funding and whether the university is comprehensive or specialist may all contribute to the observed differences in performance. The regional differences are consistent but not significant at conventional levels of significance; the efficiencies differ significantly by administrative type when the subjective measure of research output is excluded from the analysis; comprehensive universities consistently and significantly outperform specialist institutions. The possibility of regional differences in performance is particularly worrying since the already economically disadvantaged Western region may suffer a continued lag in development if its HEIs are less efficient than those in the better developed Central and coastal regions. JEL classification:I21, I23, C14

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Section: Methodsmentioning

confidence: 99%

Measuring the research performance of Chinese higher education institutions using data envelopment analysis

Johnes

2008

China Economic Review

235

110

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“…The only department input we had was its number of full time equivalent professors. In any event, professors pay-roll add-up to over three fourths of operational costs of Brazilian public universities [for a thorough discussion on academic department inputs see Madden, Savage & Kemp (1997)]. Therefore, applying model (1) to each department at a time, generates a set of performance indices for each department on dimension D. At the end, we get the index of performance of department k under its own choice of weights for the several indicators of D and also under the choice of weights most favorable to each of all other departments (cross-evaluation).…”

Section: Methodsmentioning

confidence: 99%

Data envelopment analysis - DEA and fuzzy sets to assess the performance of academic departments: a case study at Federal University of Santa Catarina - UFSC

Lopes

Lanzer

2002

Pesqui. Oper.

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This paper address the issue of performance evaluation -productivity and quality -of academic departments at an University. A DEA model was used to simulate a process of cross-evaluation between departments. The results of DEA in the dimensions of teaching, research, service and quality were modeled as fuzzy numbers and then aggregated through a weighted ordered aggregator. A single index of performance for each department was generated. The proposal is to identify departments with low performance in one or more dimensions that should receive additional evaluation from an external auditing committee. A by-product of the model is to enlarge the possibility of working with more variables than a conventional DEA model. The model applied to a set of fifty-eight departments of a Brazilian University showed fifteen with low performance. Zero correlation between department teaching, research and service were observed. Weak correlation was detected between research productivity and quality. Weak scale effects were detected.Keywords: data envelopment analysis, productivity analysis, fuzzy logic. ResumoEste artigo trata da avaliação do desempenho -produtividade e qualidade -de departamentos acadêmicos de uma Universidade. Um modelo DEA foi usado para simular um processo de avaliação cruzada entre departamentos. Os resultados de DEA nas dimensões de ensino, pesquisa, extensão e qualidade foram modelados como números difusos e então agregados através de um agregador ponderado. Um único índice de desempenho para cada departamento foi gerado. A proposta é identificar departamentos com fraco desempenho em uma ou mais dimensões que deveriam receber priorização para avaliação por um comitê externo. Um resultado adicional do modelo proposto é a possibilidade de inclusão de um número maior de variáveis do que no DEA convencional. O modelo aplicado a cinqüenta e oito departamentos de uma Universidade Brasileira apontou quinze com baixo desempenho. Nenhuma correlação entre produtividade em ensino, pesquisa e extensão foi observada. Uma correlação fraca foi encontrada entre produtividade em pesquisa e qualidade. Fracos efeitos de escala foram detectados.

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“…The pioneering works on this particular area of research may be enumerated as follows: Johnes and Johnes (1993), Coelli (1996) and Madden, Savage, and Kemp (1997). The first one applies a basic DEA model to the 36 UK university economics departments for the 1989 academic year.…”

Section: Review Of Literaturementioning

confidence: 99%

“…Moreover, the main concern of these aforementioned papers is to address the reliability of DEA to become an appropriate performance indicator for HEIs as clearly put forward by Johnes and Johnes (1993): "We conclude that DEA has a positive contribution to make in the development of meaningful indicators of university performance". Accordingly, subsequent researches on the efficiency analysis of HEIs have been built upon the theoretical as well as methodological framework put forward by Johnes and Johnes (1993), Coelli (1996) and Madden, Savage, and Kemp (1997).…”

Section: Review Of Literaturementioning

confidence: 99%

Measuring Efficiencies of Turkish Public Universities with Non-Parametric Efficiency Estimation Method

Erkoc¹

2016

HUJE

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Abstract:The purpose of this paper is to estimate technical and cost efficiencies of public universities in Turkey between 2005 and 2010 by the means of non-parametric technique named as Data Envelopment Analysis (DEA). In doing so, overall efficiencies of HEIs are computed on the basis of certain production and cost models motivated by different sets of input/output. The results of those models, firstly, have shown that majority of public HEIs in Turkey are performing at unsatisfactory levels although some of them are doing fairly well. Besides after employing bootstrapping procedures, results indicated that efficiency scores are significantly diverging between best and worst performing institutions. Secondly, even though there is not any systemic improvement during this five-year time span, overall efficiencies of public HEIs in Turkey had gone up at the course of 2008-2009 and 2009-2010 academic years. Thirdly, the share of full-time academic staff in the whole faculty and having a medical school are found as the determinants of inefficiencies among HEIs regarding to the estimates of Tobit regression analysis. Consequently, even though those findings might have methodological limitations concerning the DEA, results of the study are recommended to be used as the departure points both for academic and policy-making interests.

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Measuring Public Sector Efficiency: A Study of Economics Departments at Australian Universities

Cited by 111 publications

References 15 publications

Measuring the research performance of Chinese higher education institutions using data envelopment analysis

Measuring the research performance of Chinese higher education institutions using data envelopment analysis

Data envelopment analysis - DEA and fuzzy sets to assess the performance of academic departments: a case study at Federal University of Santa Catarina - UFSC

Measuring Efficiencies of Turkish Public Universities with Non-Parametric Efficiency Estimation Method

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