The authors assume that firms invest in R&D not only to generate innovations, but also to learn from competitors and extraindustry knowledge sources (e.g., university and government labs). This argument suggests that the ease of learning within an industry will both affect R&D spending, and condition the influence of appropriability and technological opportunity conditions on R&D. For example, they show that, contrary to the traditional result, intraindustry spillovers may encourage equilibrium industry R&D investment. Regression results confirm that the impact of appropriability and technological opportunity conditions on R&D is influenced by the ease and character of learning. Copyright 1989 by Royal Economic Society.

Innovation and Learning: The Two Faces of R & D

This survey reviews the growing use of patent data in economic analysis. After describing some of the main characteristics of patents and patent data, it focuses on the use of patents as an indicator of technological change. Cross-sectional and time-series studies of the relationship of patents to R&D expenditures are reviewed, as well as scattered estimates of the distribution of patent values and the value of patent rights, the latter being based on recent analyses of European patent renewal data. Time-series trends of patents granted in the U.S. are examined and their decline in the 1970s is found to be an artifact of the budget stringencies at the Patent Office. The longer run downward trend in patents per R&D dollar is interpreted not as an indication of diminishing returns but rather as a reflection of the changing meaning of such data over time. The conclusion is reached that, in spite of many difficulties and reservations, patent data remain a unique resource for the study of technical change.

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Patent Statistics as Economic Indicators: A Survey

Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Estimation and Inference in Econometrics

The article outlines the production function approach to the estimation of the returns to R&D and then proceeds to discuss in turn two very difficult problems: the measurement of output in R&D intensive industries and the definition and measurement of the stock of R&D 'capital'. Multicollinearity and simultaneity are taken up in the next section and another section is devoted to estimation and inference problems arising more specifically in the R&D context. Several recent studies of returns to R&D are then surveyed, and the paper concludes with suggestions for ways of expanding the current data base in this field.

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Issues in assessing the contribution of research and development to productivity growth

To solve a problem, needed information and problem-solving capabilities must be brought together. Often the information used in technical problem solving is costly to acquire, transfer, and use in a new location-is, in our terms, "sticky." In this paper we explore the impact of information stickiness on the locus of innovation-related problem solving. We find, first, that when sticky information needed by problem solvers is held at one site only, problem solving will be carried out at that locus, other things being equal. Second, when more than one locus of sticky information is called upon by problem solvers, the locus of problem solving may iterate among these sites as problem solving proceeds. When the costs of such iteration are high, then, third, problems that draw upon multiple sites of sticky information will sometimes be "task partitioned" into subproblems that each draw on only one such locus, and/or, fourth, investments will be made to reduce the stickiness of information at some locations.

Information stickiness appears to affect a number of issues of importance to researchers and practitioners. Among these are patterns in the diffusion of information, the specialization of firms, the locus of innovation, and the nature of problems selected by problem solvers.

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Sticky Information and the Locus of Problem Solving: Implications for Innovation

The history of economic development shows that few countries have achieved sustained economic growth without first, or simultaneously, developing their agricultural sector.' In most developing countries, agriculture is the most important economic activity providing income, employment, and foreign exchange. Without an efficient agricultural sector, a country is severely constrained in its ability to feed itself or import foreign products for domestic consumption and development. Rapid technological advances in agriculture have occurred since World War II. These advances have induced great changes in agricultural production and also highlighted the importance of a rapid and efficient transfer of advanced knowledge to the farmer. When farmers become aware of the availability of new technology, they may have inaccurate perceptions of the related costs and benefits, as information availability may be limited. As farmers' decisions are based on their perceptions, their resource allocation and technology choice will deviate from the social optimum if perceptions do not coincide with the correct attributes of the technology. Both society and the farmers as individuals would gain from improved information, and theoretically there should exist a market for information. However, information on improved agricultural technology is often a public good because the provider of the information cannot exclude other potential users from free access to information provided to one user, and the value of the information is not directly affected by the number of users. While many instances of market activities in various aspects of agricultural information are observed (e.g., specialized information on pest man

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The economic impact of agricultural extension : a review

Induced Innovation: Technology, Institutions, and Development

Foreword (Vernon W. Ruttan). Preface. Introduction. 1) The Evolution of the U.S. System. 2) The Development of a System of Agricultural Sciences. 3) The Agricultural Scientist. 4) Resources and Their Allocation. 5) The Private Sector, Biotechnology and R&D for Agriculture. 6) International Dimensions of U.S. Agricultural Research. 7) Economics of the Provision of Public Agricultural Research. 8) Research Contributions to Agricultural Productivity. 9) The SAES-USDA System: Challenges for the 21st Century. Glossary/Acronyms. Index.

Science for Agriculture: A Long-Term Perspective

This paper reviews both theoretical and empirical studies of technological change in developing countries. It assesses the contribution that these studies have made to technology strategy and offers suggestions for further economic research. Our review of theoretical studies by economists concludes that most such studies have offered little policy insight. This is largely because of limited empirical verification. The older economic growth theories (of the 1950s and 1960s) did not treat technology as an economic activity. More recent \"endogenous\" growth theories, however, can be credited with reviving interest in technology and technology policy. Some empirical testing and verification of these models is now underway and with more empirical studies this line of research could be quite valuable. Search models and induced innovation models have made contributions to the extent that they have influenced empirical work. Most recent game-theoretic studies have yet to demonstrate policy relevance because of limited empirical verification. The field of the economics of technology is thus primarily an empirical field. A great deal of the relevant empirical work in the field has been guided by the growth accounting framework developed in the 1950s. Total factor productivity calculations have served as the basis for statistical studies relating productivity to variables measuring inventive activity, infrastructure and policy environments. The agricultural sector has been extensively studied in this context and a large number of estimates of returns to investment in agricultural R&D have now been reported. These studies show that such investments have had a high payoff in both developed and developing countries. They also show that agricultural technology is subject to high levels of technological distance (i.e., location-specificity) and that the degree of simple transfer (spillover) of technology from developed to developing countries has been very low. Empirical evidence for industrial technology in developing countries is much less complete. Rates of return studies for private sector R&D in developed countries show that privately captured returns are comparable to returns on other relatively risky investments but that \"social\" returns are much higher (roughly comparable to the high social returns for agricultural research). The few studies available for developing countries suggest that this is so for these countries as well. The paper concludes that developing countries cannot expect to achieve technologydriven economic growth without significant investment in technology infrastructure and without developing a conducive environment for such investment and for accessing foreign origin technology. Of the approximately 100 less developed countries, only 25 or so have made sufficient investments in technology infrastructure to achieve rapid economic growth. And of these only ten or so have actually realized such growth because of adverse policy environments.

https://www.econstor.eu/bitstream/10419/160630/1/cdp709.pdf

Technological change and technology strategy

Of the diverse factors motivating technological change, one factor that has received increasing attention in the recent past has been the protection of intellectual property rights. Given fairly recent changes in the international policy ethos where a regime of stronger intellectual property protection has become a fait accompli for most developing countries, it is of some significance to ask whether more stringent protection of intellectual property does indeed encourage innovation. And this is the question which this paper examines, utilising cross-country panel data on R&D investment, patent protection and other country-specific characteristics spanning the period 1981-1990. The evidence unambiguously indicates the significance of intellectual property rights as incentives for spurring innovation.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID275322_code010710530.pdf?abstractid=275322

Robert E. Evenson

Papers

The economic impact of agricultural extension : a review

Induced Innovation: Technology, Institutions, and Development

Science for Agriculture: A Long-Term Perspective

Technological change and technology strategy

Does Intellectual Property Protection Spur Technological Change