This overview of work in the field of innovation and technical change collects 22 contributions that reflect worldwide research efforts and the role of economic incentives in shaping and directing innovative activities. The papers are from the 10th International ADRES conference.

During the past few decades, the interest of economists in the sources of long-term economic growth has led an increasing number of them to focus on the role of innovation in creating that growth. Although some researchers have always been interested in this topic, the groundbreaking work of Solow (1957), Nelson (1959) and Arrow (1962) made many other economists recognize the central role played by innovation in almost all spheres of economic activity. The Economics and Econometrics of Innovation presents a valuable overview of the work of the world's most renowned experts in the field of innovation and technical change. It collects 22 outstanding contributions that reflect the results of the vast, worldwide research efforts and remind us of the importance of economic incentives in shaping and directing innovative activities. The volume presents an edited selection of papers that were first presented at the 10th International ADRES conference. One particular goal of this book is to bring out the complementary nature of the various approaches to innovation, and to facilitate in-depth dialogues both between microeconomists and macroeconomists, and between theoreticians and econometricians. General topics that are considered range from the economy-wide effects of innovation on growth and employment to the variation of individual firm innovative performance; from the analysis of networks and standardization to the role of intellectual property rights and the assessment of knowledge spillovers. Besides the wealth of information presented in the chapters, readers of this volume will also appreciate the value of examining a single question from different angles and by using different methods.

4 UNIVERSITY RESEARCH AND THE SPATIAL DISTRIBUTION OF HIGH TECHNOLOGY INNOVATIONS AND PRIVATE RESEARCH . . . . . . . . 45 4. 1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4. 2. THE INNOVATION, PRIVATE RESEARCH AND UNIVERSITY RESEARCH DATA . . . . 46 4. 3. THE SPATIAL DISTRIBUTION OF HIGH TECHNOLOGY INNOVATIONS . . . . . . . . . . . . . . . . 50 4. 4. THE SPATIAL DISTRIBUTION OF HIGH TECHNOLOGY R&D ACTIVITIES . . . . . . . . . . . 55 4. 5. THE SPATIAL DISTRIBUTION OF HIGH TECHNOLOGY UNIVERSITY RESEARCH AND ITS RELATION TO INNOVATIONS AND INDUSTRIAL RESEARCH . . . . . . . . . . . . . . . . . . . . . . . . 58 4. 6. SUMMARy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 5 LOCAL KNOWLEDGE TRANSFERS: STATE LEVEL ANALYSIS . . . . . . . . . 67 5. 1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5. 2. STATE ANALYSIS AND LOCAL KNOWLEDGE TRANSFERS: SUMMARY OF EARLIER FINDINGS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 5. 3. ALTERNATIVE INDICATORS OF LOCAL UNIVERSITY KNOWLEDGE TRANSFERS 72 EMPIRICAL RESULT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 5. 4. 5. 5. SUMMARy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 6 THE SPATIAL EXTENT OF UNIVERSITY EFFECTS: MSA LEVEL ANALySIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 6. 1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 6. 2. THE MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 6. 2. ESTIMATION ISSUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 6. 3. EMPIRICAL RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 6. 4. SUMMARy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 7 FACTORS GOVERNING UNIVERSITY EFFECTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 7. 1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 7. 2. THE EMPIRICAL MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 7. 3. REGRESSION RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 7. 4. SPATIAL VARIATION IN THE INTENSITY OF UNIVERSITY KNOWLEDGE TRANSFERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 7. 5. THE "CRITICAL MASS" OF AGGLOMERATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 7. 6. SUMMARy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 8 SUMMARY AND CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 APPENDIX A: DEFINING HIGH TECHNOLOGY FOR THE EMPIRICAL STUDY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 APPENDIX B: VARIABLE DEFINITIONS AND SOURCES . . . . . . . . . . . . . . . . . . . . . . . 131 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 INDEX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 List of Tables Table 2. 1.

The emergence of new firm-level data, including the European Community Innovation Survey (CIS), has led to a surge of studies on innovation and firm behaviour. This book documents progress in four interrelated fields: · investigation of the use of new indicators of innovation output · investigation of determinants of innovative behaviour · the role of spillovers, the public knowledge infrastructure and research and development collaboration · The impact of innovation on firm performance Written by an international group of contributors, the studies are based on agriculture and the manufacturing and service industries in Europe and Canada and provide new insights into the driving forces behind innovation.

A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.

Science and technology have long been regarded as important determinants of economic growth. Edwin Mansfield (1971, pp. 1- 2), a pioneer in the economics of technological change, noted: Technological change is an important, if not the most important, factor responsible for economic growth . . . without question, [it] is one of the most important determinants of the shape and evolution of the American economy. Science and technology are even more important in the "new economy," with its greater emphasis on the role of intellectual property and knowledge transfer. Therefore, it is unfortunate that most individuals rarely have the opportunity to explore the economic implications of science and technology. As a result, the antecedents and consequences of technological change are poorly understood by many in the general public. This lack of understanding is reflected in a recent survey conducted by the National Science Board (2000), summarized in Science & Engineering Indicators. ' As shown in Table 1. 1, the findings of the survey indicated that many Americans, despite a high level of interests in such matters, are not as well-informed about technological issues as they are about other policy issues. As shown in the table, individuals self assess, based on a scale from 1 to 100, their interest in science and technology policy issues as being relatively high, yet they self assess their knowledge or informedness about these issues relatively lower.

This book presents a detailed overview of the economics and technological change in all its various dimensions. Topics covered include: * Game-theoretic approaches to the modelling of technological change * Finance and technological change * Technological change in internatonal trade The Handbook will be essential reading for students and researchers of the economics of technological change and industrial organization.

An examination of the role of theory in applied econometrics.

A proposal for moving from price-centric to innovation-centric competition policy, reviewing theory and available evidence on economic incentives for innovation. Competition policy and antitrust enforcement have traditionally focused on prices rather than innovation. Economic theory shows the ways that price competition benefits consumers, and courts, antitrust agencies, and economists have developed tools for the quantitative evaluation of price impacts. Antitrust law does not preclude interventions to encourage innovation, but over time the interpretation of the laws has raised obstacles to enforcement policies for innovation. In this book, economist Richard Gilbert proposes a shift from price-centric to innovation-centric competition policy. Antitrust enforcement should be concerned with protecting incentives for innovation and preserving opportunities for dynamic, rather than static, competition. In a high-technology economy, Gilbert argues, innovation matters.