We have three goals in this paper. First, we demonstrate how an econometric model can be used to make citations a potentially useful measure of knowledge flows, by controlling for the effects of truncation, changes in citation patterns, and technology field effects. Second, we explore for the first time the citation patterns among all combinations of the G-5 countries, the U.S., Great Britain, France, Germany and Japan. This gives a much richer picture of the geographic dimension of citation diffusion, by examining the extent and speed of diffusion of citations within and among all combinations of these countries. This permits us to estimate the extent and nature of “localization” of citations within each of these countries, to examine differences among the countries in their apparent absorption of foreign technology, and to identify some interesting pairwise interactions. Finally, we add the dimensions of “institutional localization” and “technological localization” to the modeling, and examine the interactions between localization in these dimensions and in geography.


Consider a researcher or inventor working on a given technological problem at a given time in a given geographic location and institutional setting. This inventor might find it easier, cheaper or faster to solve her technological problem by virtue of access to knowledge created earlier by other inventors and researchers. For linguistic color and convenience, call the invention that is facilitated by some earlier piece of research the “descendant” and the earlier work that contributed to it the “antecedent.” The question we want to ask is: how is the probability that a given descendant will benefit from a specific antecedent affected by the time, geographic location, institutional setting and technological nature of each, and by the relationship between the two along each of these dimensions. In particular, we are interested in the extent of “localization” in geography, institutional setting and technology space, and how localization interacts with time. That is, is a descendant more likely to benefit from an antecedent that is nearby geographically, comes from within the same institution, and is technologically similar, and does this increased likelihood of benefiting from nearby antecedents vary with the length of time elapsed.