The Matthew effect in economics reconsidered

Daniel Birkmaier and Klaus Wohlrabe

Journal of Informetrics, 2014, vol. 8, issue 4, 880-889

Abstract: We apply the test of Ijiri and Simon (1974) to a large data set of authors in economics. This test has been used by Tol (2009, 2013a) to identify a (within-author) Matthew effect for authors based on citations. We show that the test is quite sensitive to its underlying assumptions and identifies too often a potential Matthew effect. We propose an alternative test based on the pure form of Gibrat's law. It states that stochastic proportionate citation growth, i.e. independent of its size, leads to a lognormal distribution. By using a one-sided Kolmogorov–Smirnov test we test for deviations from the lognormal distribution which we interpret as an indication of the Matthew effect. Using our large data set we also explore potential empirical characteristics of economists with a Matthew effect.

Keywords: Matthew effect; Gibrat's law; Kolmogorov–Smirnov (search for similar items in EconPapers)
JEL-codes: A12 A14 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1751157714000819
Full text for ScienceDirect subscribers only

Related works:
Working Paper: The Matthew Effect in Economics Reconsidered (2014)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:8:y:2014:i:4:p:880-889

DOI: 10.1016/j.joi.2014.08.005

Access Statistics for this article

Journal of Informetrics is currently edited by Leo Egghe

More articles in Journal of Informetrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().