Abstract
We study how knowledge about the social network of an individual
researcher, as embodied in his coauthor relations, helps us in developing
a more accurate prediction of his or her future productivity. We find
that incorporating information about coauthor networks leads to a modest
improvement in the accuracy of forecasts on individual output, over and
above what we can predict based on the knowledge of past individual output.
Second, we find that the informativeness of networks dissipates over
the lifetime of a researcher’s career. This suggests that the signaling content
of the network is quantitatively more important than the flow of ideas.