That's classified! Inventing a new patent taxonomy

Stephen Billington and Alan J. Hanna

No 2018-06, QUCEH Working Paper Series from Queen's University Belfast, Queen's University Centre for Economic History

Abstract: Patent studies inform our understanding of innovation. Any study of patenting involves classifying patent data according to a chosen taxonomy. The literature has produced numerous taxonomies, which means patents are being classified differently across studies. This potential inconsistency is compounded by a lack of documentation provided on existing taxonomies, making them diffcult to replicate. Because of this, we develop a new patent taxonomy using machine learning techniques, and propose a new methodology to automate patent classification. We contrast existing taxonomies with our own upon a widely used patent dataset. In a regression analysis of patent classes upon patent characteristics, we show that classification bias exists: the size, statistical significance, and direction of association of coefficients depend upon how a patent dataset has been classified. We recommend investigators adopt our approach to ensure future studies are comparable and replicable.

Keywords: Innovation; Invention; Machine Learning; Patents; Patent Classification; Taxonomy; Economic History (search for similar items in EconPapers)
JEL-codes: K11 N24 N74 O31 O33 (search for similar items in EconPapers)
Date: 2018
New Economics Papers: this item is included in nep-big, nep-his, nep-ino, nep-ipr and nep-law
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Journal Article: That’s classified! Inventing a new patent taxonomy (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:qucehw:201806

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