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International Technological Specialization in Important Innovations: Some Industry-Level Explorations Carolina Castaldi* and Bart Los** *University of Utrecht & GGDC, **University of Groningen & GGDC. EUKLEMS Consortium Meeting (Brussels, March 16 – 17, 2007)
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International Technological Specialization in Important Innovations:Some Industry-Level ExplorationsCarolina Castaldi* and Bart Los***University of Utrecht & GGDC, **University of Groningen & GGDC EUKLEMS Consortium Meeting (Brussels, March 16 – 17, 2007) This project is funded by the European Commission, Research Directorate General as part of the 6th Framework Programme, Priority 8, "Policy Support and Anticipating Scientific and Technological Needs".
Introduction • Lisbon agenda: goals with respect to dynamism and competitiveness of European economy. • Innovation is a key factor • Problem: innovation is hard to measure • R&D expenditures are input indicators • Surveys (CIS) sometimes subjectively filled out • Patent counts imperfect measure • Objectives of this project: • Add to the literature on patent-related innovation measures • Gain industry-specific knowledge about the ability of European countries to generate important innovations, relative to the U.S., Japan and Asian Tigers.
Measures of innovation output:patent indicators • Body of literature on patents as output indicator (Schmookler, Scherer, Griliches, etc). Conclusion: patents useful but noisy indicator of innovation • Patents very heterogeneous in importance (Hall, Pakes, Schankerman, Harhoff, etc.) • In some industries, patenting is not seen as the most appropriate method to protect intellectual property (Cohen, Walsh, Nelson) • Patent offices are not always functioning as they should, with imperfect examination procedures of ‘prior art’ (Jaffe, Lerner) • Citation counts can help in identifying important indicators (Trajtenberg, Jaffe, Hall)
Raw Patent Counts per Country Table 1 (p.h.w.: per 10,000 hrs worked) In 1998: HU: 10.6; CZ: 2.4; PL: 1.0
Problems to cope with… • Point of departure: patents that receive more citations in subsequent patents are more important • Problem 1: Patenting behavior varies across industries • Problem 2: Citation behavior varies over time • Problem 3: Citations are not received immediately • Important innovations determined by constructing citation-based rankings by industry and year of grant for all patents issued; • Distinction between important innovations and other innovations based on stylized fact concerning frequency distributions.
Stylized fact: Fat tails • Curved part: lognormally distributed • Linear part: Pareto distributed • Hill estimator for fatness of tail: erratic behavior if observations not Pareto distributed • Drees-Kaufmann procedure to estimate cut-off point • Important innovations act as “focal point” for subsequent research (Silverberg & Verspagen, Sanditov) Bootstrapping to obtain confidence intervals
Data Sources • NBER Patent-Citations Datafile • Numbers of citations (1975-1999) to all utility patents granted by USPTO in 1963-1999 • Our subset: 1970-1999 (>2.4M patents, of which 1.0M to non-US inventors) • Country of first inventor • USPTO’s PATSIC-CONAME Database • Industry of manufacture (OTAF: 42 industries) • “Fractional counting” in case of multiple OTAF codes • Matching to 20 EUKLEMS industries • 26 countries
Proportions of Important (Patented) Innovations by Industry (averages, 1970-1998)
Proportion of Important Innovations over Time (all manufacturing) (unweighted averages of industry-specific proportions)
Technology Life Cycles(number of important innovations: 1970-1998) computers ins wire RTV ships electronics aircraft machinery food metal prod oil
…. and Contributions toEurope’s Important Innovations(by period)
Specialized in Important Innovations? US: 2.0 – 2.6%; Taiwan: 0.0 – 0.65%
Specialized in Important Innovations?(industry-level results, 1990-1994) aircraft chemicals cars plastics
Further research • Use of OECD PatStat database on international patent citations instead of NBER database • More systematic analysis of distribution of cut-off point estimator • Industry-of-use instead of industry-of-manufacture (Johnson’s concordance), to link innovation indicator to EUKLEMS productivity indicators • Study of relationship between important innovations and industry profitability using core EUKLEMS data • Investigations to see whether techniques can be found to reduce time lag in identification process