A Quest for Innovation Drivers with Autometrics: Do These Differ Before and After the COVID-19 Pandemic for European Economies?

Jorge Marques, Carlos Santos () and Maria Alberta Oliveira
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Jorge Marques: Business Sciences Department, University of Maia, Avenida Carlos de Oliveira Campos—Castelo da Maia, 4475-690 Maia, Portugal
Carlos Santos: Business Sciences Department, University of Maia, Avenida Carlos de Oliveira Campos—Castelo da Maia, 4475-690 Maia, Portugal
Maria Alberta Oliveira: Business Sciences Department, University of Maia, Avenida Carlos de Oliveira Campos—Castelo da Maia, 4475-690 Maia, Portugal

Economies, 2025, vol. 13, issue 4, 1-41

Abstract: The literature regarding innovation drivers is usually based on variables taken from some theoretical approach and validated within a methodology. Some authors have included COVID-19 as a driver for innovations. In this paper, we address the pandemic from a different viewpoint: trying to find if innovation drivers for European countries are the same in pre- and post-pandemic years. The automated general-to-specific model selection algorithm—Autometrics—is used. The main potentially relevant drivers for which data were available for both years and two proxies of innovation (patents and the Summary Innovation Index) were considered. The final models provided by Autometrics allow for valid inference on retained innovation drivers since they have passed a plethora of diagnostic tests, ensuring congruency. The attractiveness of the research system is the most impactful driver on the index in both years but other drivers indeed differ. SMEs’ business process innovation and their cooperation networks matter only in 2022. We found crowding-out effects of public funding of R&D (in both years, for the index). Sustainability was a driver in both periods. The ranking of common drivers also changes. Non-R&D innovation expenditures, the second most relevant before COVID-19, concedes to digitalization. Surprisingly, when patents are the proxy, digitalization is retained before COVID-19, with the attractiveness of the research system replacing it afterwards. Explanations for our findings are suggested. The main implications of our findings for innovation policy seem to be the facilitating role that the government should have in fostering linkages between stakeholders and the capacity the government might have to improve the attractiveness of the research system. Policies based on the public funding of R&D appear ineffective for European countries.

Keywords: innovation; innovation measure; COVID-19; general-to-specific; crowding-out; intangibles; summary innovation index (search for similar items in EconPapers)
JEL-codes: E F I J O Q (search for similar items in EconPapers)
Date: 2025
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