n this paper, we propose a model of national innovation production that formalizes the role of trade partnerships as a channel of knowledge spillovers across countries. The model is used to investigate the energy efficiency technological domain in the European Union (EU) using a panel database covering 19 EU countries for the time span 1990–2015. The model is estimated by using a novel empirical strategy which allows to assess the knowledge spillover effects benefiting a country depending on its relative position in the trade network, and correct for common endogeneity concerns. We show that being central in the trade network is a significant determinant of a country’s innovative performance, and that learning-by-exporting mechanisms are responsible for increased innovation performances. We further reveal that neglecting network effects may significantly reduce our understanding of domestic innovation patterns. Finally, we find that the benefits obtained from knowledge diffusion varies with the domestic absorptive capacity and policy mix composition. Our main implication is that policy design informed by network-based case studies could help maximizing the exploitation of positive knowledge spillovers.
Network-driven positive externalities in clean energy technology production. The case of energy efficiency in the EU residential sector / Costantini, Valeria; Leone Sciabolazza, Valerio; Paglialunga, Elena. - In: THE JOURNAL OF TECHNOLOGY TRANSFER. - ISSN 0892-9912. - (2022). [10.1007/s10961-022-09928-y]
Network-driven positive externalities in clean energy technology production. The case of energy efficiency in the EU residential sector
Leone Sciabolazza, Valerio
Membro del Collaboration Group
;
2022
Abstract
n this paper, we propose a model of national innovation production that formalizes the role of trade partnerships as a channel of knowledge spillovers across countries. The model is used to investigate the energy efficiency technological domain in the European Union (EU) using a panel database covering 19 EU countries for the time span 1990–2015. The model is estimated by using a novel empirical strategy which allows to assess the knowledge spillover effects benefiting a country depending on its relative position in the trade network, and correct for common endogeneity concerns. We show that being central in the trade network is a significant determinant of a country’s innovative performance, and that learning-by-exporting mechanisms are responsible for increased innovation performances. We further reveal that neglecting network effects may significantly reduce our understanding of domestic innovation patterns. Finally, we find that the benefits obtained from knowledge diffusion varies with the domestic absorptive capacity and policy mix composition. Our main implication is that policy design informed by network-based case studies could help maximizing the exploitation of positive knowledge spillovers.File | Dimensione | Formato | |
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