Citations, journal ranking and multiple authorships reconsidered: evidence from almost one million articles

Abstract

In this paper we reconsider the investigation by Moosa (2016) using a much larger data set of almost one million articles listed in RePEc. This article provides new insights into the effects of co-authorship on citation counts and the correlation between quality of papers and quality of the publishing journal. Our evidence is partially in contrast to the results reported in Moosa (2016). We find a positive correlation between the h-index of a journal and the quality of papers measured in terms of citations. This correlation becomes almost perfect using a non-linear model. Results from a regression of citation counts on the number of authors show evidence of a positive and significant effect of coauthorship on the quality of a paper when time effects and large sets of top-cited articles are taken into account. The inclusion of time effects and the large data set, that allows to differentiate between top-cited cohorts, add further insights to the existing literature.

Corruption in economics: a bibliometric analysis and research agenda

“…To explore the literature, we conducted a bibliometric citation analysis of 4,488 articles on corruption in economics (Yuret 2014(Yuret , 2018Rath and Wohlrabe 2015a;Zupic and Čater 2015;Sommer and Wohlrabe 2016;Meyer and Wohlrabe 2017;Bahoo, Alon, and Paltrinieri 2019;Bahoo 2020). Our analysis contributes to the literature by answering the following questions: (1) What are the leading research streams in the literature on corruption in economics?…”

Network Effects and Research Collaborations

“…1,2 Teaming up allows researchers to exploit synergies and economies of scale by pooling ideas, skills, time, and funds. While there is no consensus on the effect of co-authorship relations on the amount and quality of research output, most recent studies that control for the endogenous nature of co-authorship formation find a positive relation with overall and authors' individual productivity (Ductor et al, 2014;Ductor, 2015;Sommer and Wohlrabe, 2017). 3 Moreover, through collaborations, knowledge spills over directly to co-authors (Azoulay et al, 2010;Borjas and Doran, 2015), as well as indirectly to the broader network of collaborating researchers (Hsieh et al, 2018).…”

Network Effects and Research Collaborations

“…1,2 Teaming up allows researchers to exploit synergies and economies of scale by pooling ideas, skills, time, and funds. While there is no consensus on the effect of co-authorship relations on the amount and quality of research output, most recent studies that control for the endogenous nature of co-authorship formation find a positive relation with overall and authors' individual productivity (Ductor et al, 2014;Ductor, 2015;Sommer and Wohlrabe, 2017). 3 Moreover, through collaborations, knowledge spills over directly to co-authors (Azoulay et al, 2010;Borjas and Doran, 2015), as well as indirectly to the broader network of collaborating researchers (Hsieh et al, 2018).…”