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  A Novel Technology-Industry Concordance Table Based on Linked Inventor-Establishment Data

Dorner, M., & Harhoff, D. (2017). A Novel Technology-Industry Concordance Table Based on Linked Inventor-Establishment Data. Max Planck Institute for Innovation and Competition Research Paper, No. 17-10.

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https://ssrn.com/abstract=2966603 (Preprint)
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https://doi.org/10.1016/j.respol.2018.02.005 (Publisher version)
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Also published in: Research Policy, Vol. 47, No. 4 (2018), 768-781
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 Creators:
Dorner, Matthias1, Author           
Harhoff, Dietmar1, Author           
Affiliations:
1MPI for Innovation and Competition, Max Planck Society, ou_2035292              

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Free keywords: patents, international patent classification, industry classification, concordance, linked inventor-establishment data
 Abstract: Mapping technologies into industries is frequently required in empirical innovation studies, but many concordances only provide coarse mappings. We develop novel concordance tables between industries and technologies making use of linked inventor-employee patent data for Germany. The data comprise 235,933 patents filed between 1999 and 2011 at the European Patent Office. Data on inventors are matched and disambiguated with social security records available at the Institute for Employment Research. Employment data recorded in this database include detailed industry codes describing the industrial activities of the inventors’ establishments. The linked inventor-establishment microdata allow us to identify the precise industry of origin of inventions, combine them with technology classifications from the inventors’ patents and to generate novel concordance tables. We evaluate our approach by comparing the concordance tables with existing work, and we discuss the validity of patent statistics by industries as indicators for innovation.

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Language(s): eng - English
 Dates: 2017-08-30
 Publication Status: Published online
 Pages: 35
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 Table of Contents: -
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 Identifiers: -
 Degree: -

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Title: Max Planck Institute for Innovation and Competition Research Paper
Source Genre: Series
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Pages: - Volume / Issue: No. 17-10 Sequence Number: - Start / End Page: - Identifier: -