The identification of important innovations using tail estimators
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.
|Date of creation:||Feb 2008|
|Date of revision:||Feb 2008|
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