Using Archetypoid Analysis to Classify Institutions and Faculties of Economics

25 Pages Posted: 23 Jan 2020

See all articles by Klaus Wohlrabe

Klaus Wohlrabe

CESifo (Center for Economic Studies and Ifo Institute) - Ifo Institute

Sabine Gralka

Dresden University of Technology

Date Written: 2019

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.

Keywords: archetypoid analysis, classification, RePEc, faculty of economics, economic institutions

JEL Classification: C380, I210, I230

Suggested Citation

Wohlrabe, Klaus and Gralka, Sabine, Using Archetypoid Analysis to Classify Institutions and Faculties of Economics (2019). CESifo Working Paper No. 8023, Available at SSRN: https://ssrn.com/abstract=3523527 or http://dx.doi.org/10.2139/ssrn.3523527

Klaus Wohlrabe (Contact Author)

CESifo (Center for Economic Studies and Ifo Institute) - Ifo Institute ( email )

Poschinger Str. 5
Munich, 01069
Germany

Sabine Gralka

Dresden University of Technology ( email )

Münchner Platz 2 - 3
Dresden, 01069
Germany

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
38
Abstract Views
263
PlumX Metrics