Current Research

Working Papers

Economics of Science

• On the Influence of Top Journals (joint with Sanjeev Goyal, Marco van der Leij and Gustavo Nicolas Paez) [pdf] 

We study the evolution of the influence of journals over the period 1970-2017. In the early 1970's, a number of journals had similar influence, but by 1995, the `Top 5' journals -- QJE, AER, RES, Econometrica, and JPE -- had acquired a major lead. This dominance has remained more or less unchanged since 1995. To place these developments in a broader context, we also study trends in sociology.  The trends there have gone the other way -- the field journals rose in influence, relative to the Top General journals. A model of journals as platforms is developed to understand these trends across time and across disciplines.

• Network effects or rent extraction? Evidence from editorial board rotation (with Bauke Visser)[pdf] 

A department’s yearly publication count in a journal increases when a member of the department joins the journal’s editorial board. The common interpretation of this fact—that during the board member’s tenure, departmental colleagues publish more—is inaccurate. In a sample of 106 economics journals covering 1990-2011, we estimate that of the observed increase in the publication count, 73% is (co-)authored by board members themselves. Their single-authored papers in a journal receive significantly less citations if they are on that journal’s editorial board. We find no evidence that they discover attractive papers among their colleagues that otherwise wouldn’t be published.

Network Economics

• The role of unobservable characteristics in friendship network formation (with Pablo Brañas-Garza and Jaromír Kováríck)  [pdf] 

Inbreeding homophily is a prevalent feature of human social networks with important individual and group-level social, economic, and health consequences. The literature has proposed an overwhelming number of dimensions along which human relationships might sort, without proposing a unified empirically-grounded framework for their categorization. We exploit rich data on a sample of University freshmen, homogeneous in terms of age, race, religion, and education, and contrast the relative importance of observable vs. unobservable characteristics in their friendship formation. We employ Bayesian Model Averaging, a methodology explicitly designed to target model uncertainty and to assess the robustness of each candidate attribute while predicting friendships. We show that, while observable features (e.g. assignment of students to sections, gender, and smoking) are robust key determinants of whether two individuals befriend each other, unobservable attributes, such as personality, cognitive abilities, economic preferences, or socio-economic aspects, are largely sensible to the model specification, and thus not robust predictors of friendships.