In socio-economic sciences the RePEc network (Research Papers in Economics) has become an essential source for the gathering and the spread of both existing and new economic research. Furthermore, it is currently the largest bibliometric database in economic sciences containing 33 different indicators for more than 30,000 economists. Based on this bibliographic information RePEc calculates well-known rankings for authors and academic institutions. We provide some cautionary remarks concerning the interpretation of some provided bibliometric measures in RePEc. Moreover, we show how individual and aggregated rankings can be biased due to the employed ranking methodology. In order to select key in-dicators describing and assessing research performance of scientist, we propose to apply principal component analysis in this data-rich environment. This approach allows us to assign weights to each indicator prior to aggregation. We illustrate the approach by providing a new overall ranking of economists based on RePEc data.
RePEc ranking aggregation principal components analysis economics profession