2018
DOI: 10.2139/ssrn.3225819
|View full text |Cite
|
Sign up to set email alerts
|

Sensitivity of University Rankings: Implications of Stochastic Dominance Efficiency Analysis

Abstract: To create their rankings, university-ranking agencies usually combine multiple performance measures into a composite index. However, both rankings and index scores are sensitive to the weights assigned to performance measures. This paper uses a stochastic dominance e ciency methodology to obtain two extreme, case-weighting vectors using the Academic Ranking of Worldwide Universities (ARWU) and Times Higher Education (THE) data, both of which lead to the highest and lowest index outcomes for the majority of uni… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
4
0

Year Published

2019
2019
2021
2021

Publication Types

Select...
4

Relationship

3
1

Authors

Journals

citations
Cited by 4 publications
(5 citation statements)
references
References 48 publications
1
4
0
Order By: Relevance
“…This result is coherent with the literature that has reported greater levels of noise in the middle and lower parts of the rankings (e.g. Pinar et al 2019;Sorz et al 2015).…”
Section: Additional Testsupporting
confidence: 90%
See 1 more Smart Citation
“…This result is coherent with the literature that has reported greater levels of noise in the middle and lower parts of the rankings (e.g. Pinar et al 2019;Sorz et al 2015).…”
Section: Additional Testsupporting
confidence: 90%
“…Sorz et al (2015) analyze the THE and ARWU rankings from 2010 to 2014 and find inconsistent fluctuations in the rank and score for universities below position 50. Pinar et al (2019) find that ARWU and THE rankings are very sensitive to weight variations, especially for middle-and low-ranked universities.…”
Section: Reputational Signals and Reputational Biases In Global Rankingsmentioning
confidence: 84%
“…In a related literature in finance, a more general, multivariate problem is that of testing whether a given portfolio is stochastically efficient relative to all mixtures of a discrete set of alternatives (Post 2003;Kuosmanen 2004;Roman et al 2006), while others address this problem with various proposed SDE tests (Post and Versijp 2007;Scaillet and Topaloglou 2010;Linton et al 2014;Arvanitis and Topaloglou 2017;Fang and Post 2017;Post and Poti 2017). These SDE tests are used to examine the existence of alternative ways of combining assets that dominate the benchmark market or welfare index to obtain best-and worst-case scenarios of wellbeing (e.g., Pinar et al 2013Pinar et al , 2015Pinar et al , 2017Pinar et al , 2019Agliardi et al 2015;Pinar 2015;Mehdi 2019) and risk indices (see e.g., Agliardi et al 2012Agliardi et al , 2014. For instance, Pinar et al (2013) used SDE methodology to obtain the best-case scenario combination of dimensions of the Human Development Index (HDI), where a full diversification of weights of HDI dimensions were used to obtain the most optimistic measurement of HDI among countries.…”
Section: Sde Methodologymentioning
confidence: 99%
“…Furthermore, the use of multiple criteria, which is the case for the REF (i.e. environment, impact and outputs), in assessing university performance has been long criticized (see e.g., Saisana et al, 2011;Pinar et al, 2019). These multidimensional indices are risky as some of the index components have been considered redundant (McGillivray, 1991;McGillivray and White, 1993).…”
Section: Introductionmentioning
confidence: 99%