The knowledge cost approach as a theory of endogenous technological change: evidence from European regions.

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Title: The knowledge cost approach as a theory of endogenous technological change: evidence from European regions.
Authors: Antonelli, Cristiano1 (AUTHOR) cristiano.antonelli@unito.it, Pialli, Guido2 (AUTHOR) g.pialli@ucl.ac.uk
Source: Journal of Technology Transfer. Aug2026, Vol. 51 Issue 4, p2198-2221. 24p.
Subjects: Knowledge transfer, Technological progress, Industrial productivity, Technological innovations
Abstract: The paper discusses the knowledge cost approach as a comprehensive framework to account for endogenous technological change and test it to explain productivity differences across European regions. The assessment of the limited transferability of knowledge and the appreciation of the intentional efforts required to use knowledge spillovers question the assumptions of automatic, spontaneous, homogenous, symmetric and universal effects of knowledge spillovers conjectured by the New Growth Theory. The knowledge cost approach, instead, stresses the localized, idiosyncratic and contextual effects of knowledge spillovers that are strong -only- in high-quality innovation systems. If the access and absorption of knowledge in high-quality innovation systems is cheaper, the cost of knowledge falls below equilibrium levels and its use in the technology production function contributes to higher total factor productivity growth rates. Using a sample of 192 European regions for which we estimate productivity growth for the period from 2005 to 2020, we confirm that regions with lower knowledge costs exhibit higher Total Factor Productivity growth rates. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Technology Transfer is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Technology+Transfer%22">Journal of Technology Transfer</searchLink>. Aug2026, Vol. 51 Issue 4, p2198-2221. 24p.
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  Data: <searchLink fieldCode="DE" term="%22Knowledge+transfer%22">Knowledge transfer</searchLink><br /><searchLink fieldCode="DE" term="%22Technological+progress%22">Technological progress</searchLink><br /><searchLink fieldCode="DE" term="%22Industrial+productivity%22">Industrial productivity</searchLink><br /><searchLink fieldCode="DE" term="%22Technological+innovations%22">Technological innovations</searchLink>
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  Data: The paper discusses the knowledge cost approach as a comprehensive framework to account for endogenous technological change and test it to explain productivity differences across European regions. The assessment of the limited transferability of knowledge and the appreciation of the intentional efforts required to use knowledge spillovers question the assumptions of automatic, spontaneous, homogenous, symmetric and universal effects of knowledge spillovers conjectured by the New Growth Theory. The knowledge cost approach, instead, stresses the localized, idiosyncratic and contextual effects of knowledge spillovers that are strong -only- in high-quality innovation systems. If the access and absorption of knowledge in high-quality innovation systems is cheaper, the cost of knowledge falls below equilibrium levels and its use in the technology production function contributes to higher total factor productivity growth rates. Using a sample of 192 European regions for which we estimate productivity growth for the period from 2005 to 2020, we confirm that regions with lower knowledge costs exhibit higher Total Factor Productivity growth rates. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Technology Transfer is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10961-025-10216-8
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      – SubjectFull: Industrial productivity
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