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The identification of important innovations using tail estimators Author info | Abstract | Publisher info | Download info | Related research | Statistics Carolina Castaldi ()
Bart Los ()
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International differences in economic performance are often attributed to differences in innovative performance. Much empirical work supports this contention, but problems in quantifying innovative output prevent researchers from drawing a clear picture. Innovations are very heterogeneous regarding their importance, with only very few innovations yielding substantial returns. Citation frequencies are one measure of the value of innovations. We use a recently introduced technique based on results from Extreme Value Theory to estimate the characteristics of the tail of the distribution of citations. We identify important innovations as those that receive a number of citations higher than the ‘cutoff point’ of the tail of the distributions of citations. The data come from the NBER Patent-Citations Database. We provide estimates of the proportions of important patents for 31 technological categories and discuss emerging patterns. Possible implications for technology policy and innovation management are also drawn.
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Paper provided by Utrecht University, Department of Innovation Studies in its series Innovation Studies Utrecht (ISU) working paper series with number
08-07.
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Date of creation: Feb 2008Date of revision:
Feb 2008Handle: RePEc:uis:wpaper:0807Contact details of provider: Web page: http://nwi.geo.uu.nl
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