Efficiency and Mergers in <scp>E</scp>nglish Higher Education 1996/97 to 2008/9: Parametric and Non‐parametric Estimation of the Multi‐input Multi‐output Distance Function

Johnes, Jill

doi:10.1111/manc.12030

Cited by 68 publications

(68 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This value is slightly lower than commonly observed within the literature of higher education using this approach. However, Johnes (2014) With an estimated overall efficiency of 0.730, the mean efficiency of Model 3 lies in between the other two values, as anticipated. The residual efficiency corresponds to the efficiency of Model 2, both in absolute terms and over time.…”

Section: Resultssupporting

confidence: 73%

See 1 more Smart Citation

Persistent inefficiency in the higher education sector: evidence from Germany

Gralka

2018

Education Economics

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractEvaluations of the Higher Education Sector are receiving increased attention, due to the rising expenditures and the absence of efficiency enhancing market pressure. To what extent universities are able to eliminate inefficiency is a question that has only partially been answered. This paper argues that heterogeneity among universities as well as persistent inefficiency hinder the institutions to achieve full efficiency -at least in the short run. Two standard and one novel specification of the Stochastic Frontier Analysis are applied to a new, comprehensive set of panel data to show how the standard efficiency evaluation changes when both aspects are taken into account. It is the first time that the idea of persistent inefficiency is considered in the analysis of the German Higher Education Sector. The comparison reveals that the disregard of heterogeneity distorts the estimation results towards lower efficiency values. The newly introduced specification improves the accuracy of the heterogeneity assumption and exposes that inefficiency tends to be long term and persistent rather than short term and residual. This implies that increasing efficiency requires a comprehensive change of the university structure.

show abstract

Section: Resultssupporting

confidence: 73%

“…The values are similar to Kempkes and Pohl (2010) and Johnes and Schwarzenberger (2011) 12 Amongst other things, this allows to include the fact that HE Institutions experience strongly varying non-completion rates [Johnes (2014)]. …”

Section: The Case Of German Universitiesmentioning

confidence: 90%

Persistent inefficiency in the higher education sector: evidence from Germany

Gralka

2018

Education Economics

View full text Add to dashboard Cite

show abstract

“…they will merge but have not yet done so) have the lowest average efficiency, while non‐merging universities have average efficiency which is in the middle of those observed for her two groups. These results seem to be largely in line with previous findings for the HE sector based on static models (Hu and Liang, ; Mao et al , ; Johnes, ).…”

Section: Resultssupporting

confidence: 92%

Dynamics of Inefficiency and Merger in English Higher Education From 1996/97 to 2008/9: A Comparison of Pre‐Merging, Post‐Merging and Non‐Merging Universities Using Bayesian Methods

Johnes

Tsionas

2018

The Manchester School

Self Cite

View full text Add to dashboard Cite

This paper investigates inefficiency/merger dynamics in the English higher education sector from 1996–97 to 2008–9. Merging can lead to greater efficiency, and this is the motivation for encouraging merger in the English higher education sector in a period of austerity. But inefficiency can also contribute towards the decision to merge, meaning that the relationship is two‐way. Although there is literature on the effects of merging in higher education, the dynamics are typically not modelled. This paper examines the differences in efficiency between pre‐merging, post‐merging and non‐merging universities, and explores the evolution of the effects over time following the merger. We develop a dynamic model of inefficiency and merger the estimation of which relies on Bayesian techniques organized around the use of Markov chain Monte Carlo. We find that typically merger delivers efficiency gains in the first instance, but these plateau soon after merger. Moreover, there is a wide dispersion around mean efficiency and there is a substantial group of mergers where the probability of efficiency improvement is relatively low. The policy implication is that merging universities is not a universal solution to improving their efficiency.

show abstract

“…The authors note that it would be interesting to extend the study to examine the relationship between size and productivity growth and in particular to the question of whether merging institutions might increase productivity; the effect of merging on both efficiency and productivity is largely unresearched (Johnes, 2014). While there are some mergers in this dataset, the small number precludes a more detailed study at present but is something which might be possible as the database increases.…”

Section: Assessing Aspects Of Efficiency and Productivity In Tertiarymentioning

confidence: 99%