An Examination of the Informational Value of Self-Reported Innovation Questions

Zheng Tian, Timothy Wojan and Stephan J. Goetz

Working Papers from U.S. Census Bureau, Center for Economic Studies

Abstract: Self-reported innovation measures provide an alternative means for examining the economic performance of firms or regions. While European researchers have been exploiting the data from the Community Innovation Survey for over two decades, uptake of US innovation data has been much slower. This paper uses a restricted innovation survey designed to differentiate incremental innovators from more far-ranging innovators and compares it to responses in the Annual Survey of Entrepreneurs (ASE) and the Business R&D and Innovation Survey (BRDIS) to examine the informational value of these positive innovation measures. The analysis begins by examining the association between the incremental innovation measure in the Rural Establishment Innovation Survey (REIS) and a measure of the inter-industry buying and selling complexity. A parallel analysis using BRDIS and ASE reveals such an association may vary among surveys, providing additional insight on the informational value of various innovation profiles available in self-reported innovation surveys.

Keywords: Self-reported innovation; substantive and incremental innovation; latent innovation measure; logistic regression (search for similar items in EconPapers)
JEL-codes: O00 O30 (search for similar items in EconPapers)
Pages: 25 pages
Date: 2022-10
New Economics Papers: this item is included in nep-cse, nep-ent, nep-ino, nep-sbm and nep-tid
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https://www2.census.gov/ces/wp/2022/CES-WP-22-46.pdf First version, 2022 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:cen:wpaper:22-46

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