Friends in Central Places

The Social Network of Informal Collaboration in Financial Economics

"So how should authors maximize the value of the journal review process? They should circulate their papers and give seminars to colleagues to receive constructive criticism before submitting to a journal."

Richard Green, Maureen O’Hara, and G. William Schwert, Joint Editorial, The Journal of Finance (57)2, p. 1032.

The Paper

In Co-Pierre Georg and Michael E. Rose: "Mirror, Mirror, on the Wall, Who is the Most Central of Them All?" (SSRN) we create the social network of informal collaboration based on acknowledgments from more than 2,700 published research papers from six financial economics journals.

Our paper on SSRN »

The Rankings

Who are the most central financial economists of our time? We provide rankings according to two centrality measures compared to the number of times they are acknowledged. We look at two samples (1998-2000 and 2009-2011) and both the network of informal collaboration and the network of formal collaboration.

To the Rankings »

The Networks

How does the social network of informal collaboration actually look like? Find out who knows whom and where you have been acknowledged.

See the Networks (Graph view) »

See the Networks (Ring view) »


Here you can find out a bit more about who we are and why we think this website is a fun project.

Find out »

The Institute

We are affiliated with The African Insitute of Financial Markets and Risk Management (AIFMRM), South Africa's leading finance and risk institute, based at the University of Cape Town.

Learn about AIFMRM »


Do you have questions about our data, the methodology or our papers? Leave a comment or feedback of any kind, we are happy to hear from you!

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Rankflow Diagram for the Top-25 Financial Economists 2009-2011.

Rankflow chart visualizing ranks for the same individual across different categories. Used categories (from left to right) are the number of times acknowledged, betweenness centrality and eigenvector centrality. Betweenness centrality of a researcher is the probability that she is part of shortest path between any two other researchers (see L. Freeman (1977): "A set of measures based on betweenness", Sociometry 40, pp. 35-41). Eigenvector centrality is the weighted sum of neighbors where the weights correspond to the neighbors' eigenvector centrality (see P. Bonacich (1986): "Power and Centrality: A Family of Measures", American Journal of Sociology 92(5), pp. 1170-1182). Color and bandwidth are proportional to rank.