657 research outputs found
Market Demand, Technological Opportunity and Research Spillovers on R&D Intensity and Productivity Growth
This paper uses sales and patent distribution data to establish the market and technological "positions" of firms. A notion of technological proximity of firms is developed in order to quantify potential R&D spillovers. The importance of the position variables and the potential spilover pool in explaining R&D intensity, patent productivity and TFP growth is explored.I find that both technological and market positions are signifi-cant in explaining R&D intensity, and that the technological effects are significant in explaining patent productivity. I cannot distinguish between the two effects in explaining TFP growth. Spillovers are important in all three contexts. Firms in an area where there is a high level of research by other firms do more R&D themselves, they produce more patents per R&D dollar, and their productivity grows faster, even controlling for the increased R&D and patents. These effects are present controlling for both industry and technological position effects.
Technological Opportunity and Spillovers of R&D: Evidence from Firms' Patents, Profits and Market Value
This paper presents evidence that firms' patents, profits and market value are systematically related to the"technological position" of firms' research programs. Further, firms are seen to "move" in technology space in response to the pattern of contemporaneous profits at different positions. These movements tend to erode excess returns."Spillovers" of R&D are modelled by examining whether the R&D of neighboring firms in technology space has an observable impact on the firm's R&D success. Firms whose neighbors do much R&D produce more patents per dollar of their own R&D,with a positive interaction that gives high R&D firms the largest benefit from spillovers. In terms of profit and market value, however, their are both positive and negative effects of nearby firms' R&D. The net effect is positive for high R&D firms, but firms with R&D about one standard deviation below the mean are made worse off overall by the R&D of others.
Flows of Knowledge from Universities and Federal Labs: Modeling the Flowof Patent Citations Over Time and Across Institutional and Geographic Boundari
The extent to which new technological knowledge flows across institutional and national boundaries is a question of great importance for public policy and the modeling of economic growth. This paper develops a model of the process generating subsequent citations to patents as a lens for viewing knowledge diffusion. We find that the probability of patent citation over time after a patent is granted fits well to a double-exponential function that can be interpreted as the mixture of diffusion and obsolescence functions. The results indicate that diffusion is geographically localized. Controlling for other factors, within-country citations are more numerous and come more quickly than those that cross country boundaries.
Patent Citations and International Knowledge Flow: The Cases of Korea and Taiwan
This paper examines patterns of knowledge diffusion from US and Japan to Korea and Taiwan using patent citations as an indicator of knowledge flow. We estimate a knowledge diffusion model using a data set of all patents granted in the U.S. to inventors residing in these four countries. Explicitly modeling the roles of technology proximity and knowledge decay and knowledge diffusion over time, we have found that knowledge diffusion from US and Japan to Korea and Taiwan exhibits quite different patterns. It is much more likely for Korean patents to cite Japanese patents than US patents, whereas Taiwanese inventors tend to learn evenly from both US and Japanese inventors. The frequency of a Korean patent citing a Japanese patent is almost twice that of the frequency of a Taiwanese patent citing a Japanese patent. We also find that a patent is much more likely to cite a patent from its own technological field than from another field.
How High are the Giants' Shoulders: An Empirical Assessment of Knowledge Spillovers and Creative Destruction in a Model of Economic Growth
The pace of industrial innovation and growth is shaped by many forces that interact in complicated ways. Profit-maximizing firms pursue new ideas to obtain market power, but the pursuit of the same goal by other means that even successful inventions art eventually superseded by others; this known as creative destruction. New ideas not only yield new goods but also enrich the stock of knowledge of society and its potential to produce new ideas. To a great extent this knowledge is non-excludable, making research and inventions the source of powerful spillovers. The extent of spillovers depends on the rate at which new ideas outdate old ones, that is on the endogenous technological obsolescence of ideas, and on the rate at which knowledge diffuses among inventors. In this paper we build a simple model that allows us to organize our search for the empirical strength of the concepts emphasized above. We then use data on patents and patent citations as empirical counterparts of new ideas and knowledge spillovers, respectively, to estimate the model parameters. We find estimates of the annual rate of creative destruction in the range of 2 to 7 percent for the decade of the 1970s, which rates for individual sectors as high as 25 percent. For technological obsolescence, we find an increase over the century from about 3 percent per year to about 12 percent per year in 1990, with a noticeable plateau in the l970s. We find the rate of diffusion of knowledge to be quite rapid, with the mean lag between I and 2 years. Lastly, we find that the potency of spillovers from old ideas to new knowledge generation (as evidenced by patent citation rate) has been declining over the century: the resulting decline in the effective public stock of knowledge available to new inventors is quite consistent with the observed decline in the average private productivity of research inputs
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