VoxEU has a new paper based on network analysis called , which seeks to identify who is in what amounts to a club. The authors make clear that a major aim of the piece is to give career advice to younger scholars.
A key section:
The ﬂow of information within the profession will likely be determined by the structure of the social network of informal collaboration rather than the pure co-author network. Our network captures a dimension that Oettl (2012) terms helpfulness. Commenters spend time to review a paper, comment and make suggestions.
Two things seemed interesting about the results. One was that despite the wide-spread stereotype of women being “helpful,” being female was negatively correlated with all the network rankings the authors looked at. So the authors confirm that it would be better for your career in economics if you could manage not to be female.
The second was that the authors looked at an economics department ranking versus the amount of influence suggested by the network measures. Members of the NBER (which is mixed ideologically but has left-leaning academics in its ranks) and CEPR (which is center left) was correlated well with formal influence, but negatively correlated with informal influence. Does this point to subtle or overt bias among which papers get published, since the network analysis was based who was thanked by authors of articles in top finance journals? Given how the paper discusses the importance of the dissemination of “new” ideas through theses informal networks, when most “new” ideas in economics are old wine in new bottles. Thus these informal networks appear likely to be venues for introducing and propagating what I’ve called “leading edge conventional wisdom,” which is the most attractive set of views to be touting at any point in time.
By Co-Pierre Georg, Senior Lecturer at the African Institute of Financial Markets and Risk Management, University of Cape Town; Research Economist, Deutsche Bundesbank and Michael E. Rose, PhD student at the African Institute of Financial Markets and Risk Management, University of Cape Town. Originally published at
Informal collaboration is an integral part of academia. Studies of academic collaboration have mostly focused on formal collaboration, as measured by co-authorships. This column instead constructs a network of informal collaboration in financial economics, exploiting acknowledgements of assistance appearing in published papers. Three rankings of financial economists are constructed based on acknowledgement occurrence and centrality. Being helpful is not found to predict centrality in the informal collaboration network.
While annual economics job market conferences like the AEA or AFA can be forbidding to fresh graduates anxious to secure their dream job, they also pose great opportunities to engage with colleagues about your research. Competition to present a paper at these conferences is tough and discussants are often leading experts in their ﬁeld. How important is this informal collaboration for authors to learn about new developments in their ﬁeld, or how a research paper is received by their peers?
With few notable exceptions, the existing literature studies formal collaboration – that is, co-authorship only. But co-authorship is less prevalent in economics compared to other disciplines such as biology (Laband and Tollison 2000). Consequently, when writing a research paper in economics and ﬁnance, most collaboration is informal, for example, through commentary from colleagues, back during seminar presentations, discussions of the paper at conferences, or even during the referee process after submitting a paper to a journal.
In a recent paper, we collect acknowledgements of 2,782 research papers published in six journals in ﬁnancial economics (Georg and Rose 2015). The Journal of Finance (JF), The Review of Financial Studies (RFS), the Journal of Financial Economics (JFE), the Journal of Financial Intermediation (JFI), the Journal of Money, Credit & Banking (JMCB), and the Journal of Banking and Finance (JBF). We look at two points in time: an early sample from 1998 to 2000, and a late sample from 2009 to 2011.
Looking at the raw ﬁgures, the intensive and the extensive margin of informal collaboration increases with the impact factor of the journal. For instance, the average JF article in 2011 acknowledged more than 12 scholars, the JBF counterpart acknowledges less than four; in 2011, every JF article acknowledges social informal collaboration, but only nine out of 10 JBF articles. The global trend between 1998 and 2011, however, is to acknowledge more informal collaboration. After manual consolidation and cleaning, we are left with 3,919 authors (of which about 50% are also acknowledged) and an additional 5,542 commenters. We connect two academics in the undirected social network of collaboration with a weight of 1 whenever they co-author a paper and additionally with a weight of 1/n whenever one acknowledges the other on a paper with n authors.1
The ﬂow of information within the profession will likely be determined by the structure of the social network of informal collaboration rather than the pure co-author network. Our network captures a dimension that Oettl (2012) terms helpfulness. Commenters spend time to review a paper, comment and make suggestions. For this reason the social network of informal collaboration contains more than twice as many researchers as a pure co-author network. Interestingly, only half of all authors are ever acknowledged, while only one out of four commenters authors a paper in our dataset. The network also connects more academics. In the late sample 98% of all economists are connected in an uninterrupted series of links in the social network of informal collaboration, while an uninterrupted path exists only for 20% of all authors in the co-author network.
Links in the general interest journals (JF, JFE, RFS) typically form the core of the network, while links in ﬁeld journals (JFI, JMCB, JBF) typically connect researchers in the periphery. Figure 1b shows the giant component of the social network of informal collaboration for the late sample. The roughly 34,000 links are colour-coded. Links from general interest journals are red, links from ﬁeld journals are blue, and the few links occurring in both types of journals are purple.
The network is heterogeneous. Some academics are much more central than others. Network centralities provide insights on the role speciﬁc individuals play in the transmission of information or the inﬂuence they exert on neighbours (Jackson 2014, Ballester et al 2006). Examining co-author networks in economics, Ductor et al (2014) write, for example: “Communication in the course of research collaboration involves the exchange of ideas. So we expect that a researcher who is collaborating with highly creative and productive people has access to more new ideas. This, in turn, suggests that a researcher who is close to more productive researchers may have early access to new ideas. As early publication is a key element in the research process, early access to new ideas can lead to greater productivity.” The two most prominent centrality measures are ‘betweenness’ and eigenvector centrality. Both are related but distinct – betweenness centrality measures the importance in the transmission of information, while eigenvector centrality points to the best connected group (i.e., opinion leaders) in the network.
Figure 1. Social networks using published research articles, 2009-2011