Evidence of Competition in Research Activity among Economic Department using Spatial Econometric Techniques

Despite the prevalence of both competitive forces and patterns of collaboration within academic communities, studies on research productivity generally treat universities as independent entities. By exploring the research productivity of all academic economists employed at 81 universities and 17 economic research institutes in Austria, Germany, and German-speaking Switzerland, this study determines whether a research unit’s productivity depends on that of neighboring research units. The significant negative relationship that is found implies competition for priority of discovery among individual researchers, as well as the universities and research institutes that employ them. In addition, the empirical results support the hypotheses that collaboration and the existence of economies of scale increase research productivity.Research productivity, Competition, Collaboration, Negative spatial autocorrelation, Geo-referenced point data

Evidence of Competition in Research Activity among Economic Department using Spatial Econometric Techniques

Despite the prevalence of both competitive forces and patterns of collaboration within academic communities, studies on research productivity generally treat universities as independent entities. By exploring the research productivity of all academic economists employed at 81 universities and 17 economic research institutes in Austria, Germany, and German-speaking Switzerland, this study determines whether a research unit’s productivity depends on that of neighboring research units. The significant negative relationship that is found implies competition for priority of discovery among individual researchers, as well as the universities and research institutes that employ them. In addition, the empirical results support the hypotheses that collaboration and the existence of economies of scale increase research productivity

Group Interaction in Research and the Use of General Nesting Spatial Models

This paper tests the feasibility and empirical implications of a spatial econometric model with a full set of interaction effects and weight matrix defined as an equally weighted group interaction matrix applied to research productivity of individuals. We also elaborate two extensions of this model, namely with group fixed effects and with heteroskedasticity. In our setting the model with a full set of interaction effects is overparameterised: only the SDM and SDEM specifications produce acceptable results. They imply comparable spillover effects, but by applying a Bayesian approach taken from LeSage (2014), we are able to show that the SDEM specification is more appropriate and thus that colleague interaction effects work through observed and unobserved exogenous characteristics common to researchers within a group