This paper describes the database on U.S. patents that we have developed over the past decade, with the goal of making it widely accessible for research. We present main trends in U. S. patenting over the last 30 years, including a variety of original measures constructed with citation data, such as backward and forward citation lags, indices of "originality" and "generality", self-citations, etc. Many of these measures exhibit interesting differences across the six main technological categories that we have developed (comprising Computers and Communications, Drugs and Medical, Electrical and Electronics, Chemical, Mechanical and Others), differences that call for further research. To stimulate such research, the entire database-about 3 million patents and 16 million citations-is now available on the NBER website. We discuss key issues that arise in the use of patent citations data, and suggest ways of addressing them. In particular, significant changes over time in the rate of patenting and in the number of citations made, as well as the inevitable truncation of the data, make it very hard to use the raw number of citations received by different patents directly in a meaningful way. To remedy this problem we suggest two alternative approaches: the fixed-effects approach involves scaling citations by the average citation count for a group of patents to which the patent of interest belongs; the quasi-structural approach attempts to distinguish the multiple effects on citation rates via econometric estimation.

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We compare the geographic location of patent citations to those of the cited patents, as evidence of the extent to which knowledge spillovers are geographically localized. We find that citations to U.S. patents are more likely to come from the U.S., and more likely to come from the same state and SMSA as the cited patents than one would expect based only on the preexisting concentration of related research activity. These effects are particularly significant at the local (SMSA) level, and are particularly apparent in early citations. The last decade has seen the development of a significant body of empirical research on R&D spillovers.' Generally speaking, this research has shown that the productivity of firms or industries is dependent not only on their R&D spending, but also on the R&D spending of other firms or other industries. In parallel, economic growth theorists have focussed new attention on the role of knowledge capital in aggregate economic growth, with a prominent modelling role for knowledge spillovers (e.g., Romer, 1986 and Grossman and Helpman, 1991 the belief that universities and other research centers can stimulate regional economic growth2 are predicated on the existence of a geographic component to the spillover mechanism. The existing spillover literature is, however, virtually silent on this point.31. E.g., Jaffe (1986), and Nadiri and Bernstein (1988. For a recent survey and evaluation of this literature, see Griliches (1991).2. See, e.g., Minnesota Department of Trade and Economic Development (1988); Feller (1989); and Smilor, et a! (1989 Glaeser, et a! (1991) characterize the "Marshall-Arrow-Romer" models as focussing on knowledge spillovers within the firms in a given industry. They examine the growth rate of industries in cities as a function of the concentration of industrial activity across cities, within-city industrial diversity, and within-city competition. They find that found that they most often identified major research universities, but that there was some tendency to cite local universities even if they were not the best in their field.4. The existence of this implicit assumption was noted by Glaeser, et al (1991): "After all, intellectual breakthroughs must cross hallways and streets more easily than oceans and continents." Grossman and Helpman (1991) consider international knowledge spillovers explicitly.3 within-city diversity is positively associated with growth of industries in that city, while concentration of an industry within a city does not foster its growth. They interpret this contrast to mean that spillovers across industries are more important than spillovers within industries. As is discussed below, there is evidence from the R&D spillover literature to suggest that across-industry knowledge spillovers are, indeed, important.In this study, we do not consider the industrial identity of either generators or receivers of spillovers, though we do have some information on their technological similarity.Our approach is to seek evidence of spillover-localizat...