Uncovering GPTS with Patent Data

This paper asks the question: Can we see evidence of General Purpose Technologies in patent data? Using data on three million US patents granted between 1967 and 1999, and their citations received between 1975 and 2002, we construct a number of measures of GPTs, including generality, number of citations, and patent class growth, for patents themselves and for the patents that cite the patents. A selection of the top twenty patents in the tails of the distribution of several of these measures yields a set of mostly ICT technologies, of which the most important are those underlying transactions on the internet and object-oriented software. We conclude with a brief discussion of the problems we encountered in developing our measures and suggestions for future work in this area.

General Purpose Technologies "Engines of Growth?"

Whole eras of technical progress and economic growth appear to be driven by a few key technologies, which we call General Purpose Technologies (GPT's). Thus the steam engine and the electric motor may have played such a role in the past, whereas semiconductors and computers may be doing as much in our era. GPT's are characterized by pervasiveness (they are used as inputs by many downstream sectors), inherent potential for technical improvements, and innovational complementarities', meaning that the productivity of R&D in downstream sectors increases as a consequence of innovation in the GPT. Thus, as GPT's improve they spread throughout the economy, bringing about generalized productivity gains. Our analysis shows that the characteristics of GPT's imply a sort of increasing returns to scale phenomenon, and that this may have a large role to play in determining the rate of technical advance; on the other hand this phenomenon makes it difficult for a decentralized economy to fully exploit the growth opportunities offered by evolving GPT's. In particular; if the relationship between the GPT and its users is limited to arms-length market transactions, there will be "too little, too late" innovation in both sectors. Likewise, difficulties in forecasting the technological developments of the other side may lower the rate of technical advance of all sectors. Lastly, we show that the analysis of GPT's has testable implications in the context of R&D and productivity equations, that can in principle be estimated.

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.

The "Names Game": Harnessing Inventors' Patent Data for Economic Research

The goal of this paper is to lay out a methodology and corresponding computer algorithms, that allow us to extract the detailed data on inventors contained in patents, and harness it for economic research. Patent data has long been used in empirical research in economics, and yet the information on the identity (i.e. the names and location) of the patents’ inventors has seldom been deployed in a large scale, primarily because of the “who is who” problem: the name of a given inventor may be spelled differently across her/his patents, and the exact same name may correspond to different inventors (i.e. the “John Smith” problem). Given that there are over 2 million patents with 2 inventors per patent on average, the “who is who” problem applies to over 4 million “records”, which is obviously too large to tackle manually. We have thus developed an elaborate methodology and computerized procedure to address this problem in a comprehensive way. The end result is a list of 1.6 million unique inventors from all over the world, with detailed data on their patenting histories, their employers, co-inventors, etc. Forty percent of them have more than one patent, and 70,000 have more than 10 patents. We can trace those multiple inventors across time and space, and thus study the causes and consequences of their mobility across countries, regions, and employers. Given the increasing availability of large computerized data sets on individuals, there may be plenty of opportunities to deploy this methodology to other areas of economic research as well.

Ivory Tower Versus Corporate Lab: An Empirical Study of Basic Research and Appropriability

We explore the use of patent citations to measure the "basicness" and appropriability of inventions. We propose that the basicness of research underlying an invention can be characterized by the nature of the previous patents cited by an invention; that the basicness of research outcomes relates to the subsequent patents that cite an invention; and that the fraction of citing patents that are assigned to the same organization as the original invention is a measure of appropriabiity. We test the validity of these presumptions by comparing the value of our measures for university and corporate patents, and find that many of the measures do conform to our a priori belief that university research and research outcomes are more basic and harder to appropriate than those of corporations. We also find some evidence that basicness of outcomes is correlated with basicness of research, and that appropriability is lower for basic outcomes.

Innovation in Israel 1968-97: A Comparative Analysis Using Patent Data

The israeli high tech sector is widely regarded as a hotbed of cutting-edge technologies, and as the growth engine of the israeli economy in the nineties and beyond. In this paper we present a close-up portrait of innovation in Israel for the past 30 years, with the aid of highly detailed patent data. We use for that purpose all israeli patents taken in the US (over 7,000), as well as US patents and patents from other countries for comparative purposes. The time path of israeli patenting reveals big jumps in the mid eighties and then again in the early nineties, reflecting underlying shocks' in policy and in the availability of relevant inputs. Israeli ranks high in terms of patents per capita, compared to the G7, the Asian Tigers' and a group of countries with similar GDP per capita. Finland is strikingly similar, Taiwan's patenting has grown extremely fast and is now on par with Israel, South Korea is rapidly closing the gap. The technological composition of israeli innovations reflects quite well world-wide technological trends, except that Computers and Communications, the fastest growing field in the US, has grown even faster in Israel. The weak side resides in the composition of israeli assignees, the actual owners of the intellectual property rights: just 35% of israeli patents were assigned to israeli corporations, a much lower percentage than in most other countries. Relatively large shares went to foreign assignees, to Universities and the Government, and to private inventors. On the other hand israeli patents are of good quality' in terms of citations received (and getting better over time): US patents command on average more citations, but not in Computers and Communications or in Biotechnology, and Israeli patents are significantly better than those of the reference group of countries.

Patient Welfare and Patient Compliance: An Empirical Framework for Measuring the Benefits from Pharmaceutical Innovation

The main goal of this paper is to develop an empirical framework for evaluating the patient welfare benefits arising from pharmaceutical innovation. Extending previous studies of the welfare benefits from innovation (Trajtenberg, 1990; Hausman, 1996), this paper unpacks the separate choices made by physicians and patients in pharmaceutical decisionmaking and develops an estimable econometric model which reflects these choices. Our proposed estimator for patient welfare depends on (a) whether patients comply with the prescriptions they receive from physicians and (b) the motives of physicians in their prescription behavior. By focusing on compliance behavior, the proposed welfare measure reflects a specific economic choice made by patients. We review evidence that the rate of noncompliance ranges up to 70%, suggesting an important gulf between physician prescription behavior and realized patient welfare. Since physicians act as imperfect but interested agents for their patients, the welfare analysis based on compliance must account for the nonrandom selection of patients into drugs by their physicians. The key contribution of this paper resides in integrating the choices made by both physicians and patients into a unified theoretical framework and suggesting how the parameters of such a model can be estimated from data.