Power-law distributions of corporate innovative output: evidence from U.S. patent data

Mincheol Choi and Chang-Yang Lee ()

Scientometrics, 2020, vol. 122, issue 1, No 24, 519-554

Abstract: Abstract This study aims to examine the existence and the characteristics of power laws in the distribution of corporate innovative output. Using a dataset containing information on 1,102,839 U.S. patent applications by 94,103 U.S. private firms during the period of 1976–2000, we find that corporate innovative output, as measured by either simple or quality-adjusted patent counts, follows power-law distributions that theoretically have infinite variances and, in some cases, infinite means. In addition, we find that corporate innovative output is power-law distributed in all technological fields. We further find that the power-law distribution of corporate innovative output tends to be stronger (i.e., the concentration of corporate innovative output in a few firms is more pronounced) in technological fields with more abundant technological opportunities and for firms with higher technological competence.

Keywords: Distribution of corporate innovative output; Power-law distribution; Simple patent count; Quality-adjusted patent count (search for similar items in EconPapers)
JEL-codes: O31 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11192-019-03304-8

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