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Using archetypoid analysis to classify institutions and faculties of economics

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  • Klaus Wohlrabe

    (Ifo Institute, Center for Macroeconomics and Surveys)

  • Sabine Gralka

    (TU Dresden)

Abstract

We use archetypoid analysis as a new tool to categorize institutions and faculties of economics. The approach identifies typical characteristics of extreme (archetypal) values in a multivariate data set. Each entity under investigation is assigned relative shares of the identified archetypoid, which show the affiliation of the entity to the archetypoid. In contrast to its predecessor, the archetypal analysis, archetypoids always represent actual observed units in the data. The approach therefore allows to classify institutions in a rarely used way. While the method has been recognized in the literature, it is the first time that it is used in higher education research and as in our case for institutions and faculties of economics. Our dataset contains seven bibliometric indicators for 298 top-level institutions obtained from the RePEc database. We identify three archetypoids, which are characterized as the top-, the low- and the medium-performer. We discuss the assignment of shares of the identified archetypoids to the institutions in detail. As a sensitivity analysis we show how the classification changes when for four and five archetypoids are considered.

Suggested Citation

  • Klaus Wohlrabe & Sabine Gralka, 2020. "Using archetypoid analysis to classify institutions and faculties of economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 159-179, April.
    • Handle: RePEc:spr:scient:v:123:y:2020:i:1:d:10.1007_s11192-020-03366-z
    DOI: 10.1007/s11192-020-03366-z
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    13. Sabine Gralka & Klaus Wohlrabe & Lutz Bornmann, 2018. "How to Measure Research Efficiency in Higher Education? Research Grants vs. Publication Output," CESifo Working Paper Series 7055, CESifo.
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    Cited by:

    1. Sabine Gralka & Klaus Wohlrabe, 2022. "Classifying top economists using archetypoid analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 29(14), pages 1342-1346, August.
    2. Klaus Wohlrabe & Constantin Bürgi, 2021. "What is the benefit from publishing a working paper in a journal in terms of citations? Evidence from economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4701-4714, June.
    3. Alexandra Baumann & Klaus Wohlrabe, 2020. "Where have all the working papers gone? Evidence from four major economics working paper series," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2433-2441, September.
    4. Piotr Śpiewanowski & Oleksandr Talavera, 2021. "Journal rankings and publication strategy," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3227-3242, April.
    5. Denitsa Angelova & Maya Göser & Stefan Wimmer & Johannes Sauer, 2021. "How efficient are German life sciences? Econometric evidence from a latent class stochastic output distance model," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-20, March.

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    More about this item

    Keywords

    Archetypoid analysis; Classification; RePEc; Faculty of economics; Economic institutions;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions

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