Implementation of MGWR-SAR models for investigating a local particularity of European regional innovation processes

Andrea Furková ()
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Andrea Furková: University of Economics in Bratislava

Central European Journal of Operations Research, 2022, vol. 30, issue 2, No 15, 733-755

Abstract: Abstract This study puts emphasis on spatial effects, spatial autocorrelation and heterogeneity in the context of European regional innovation activities. The main aim of the paper was a simultaneous consideration of both spatial effects following a new class of data generating processes, mixed geographically weighted regression—spatial autoregressive model. The basis of the analysis was 220 European regions. As a proxy for innovation output Patent Cooperation Treaty applications were considered. As three innovative inputs were opted: scientific publications among the top-10% most cited publications worldwide; Research & Development expenditure in the business sector, and small and medium-sized enterprises introducing product or process innovations. The paper was intended to answer the research question such as the question of spatial differentiation of the model parameters, as we assumed heterogeneous responses of regional innovation output to innovation inputs. This is very important in terms of regional policy measures, which should be heterogeneous if spatially varying parameters are verified. In relation to spatial spillover effects, not only the question whether spatial spillover effects affect the regional innovation was addressed but also whether a unique spatial process drives the dependence across the full study area or there are separate spatial processes driving each region. The results suggested a spatial differentiation of all the parameters under the consideration and spatial spillovers have been indicated as a significant factor in increasing innovation. Consequently, this implies more place-based innovation and industrial regional policy strategies.

Keywords: European innovation; Mixed geographically weighted regression—spatial autoregressive model; Spatial autocorrelation; Spatial heterogeneity (search for similar items in EconPapers)
JEL-codes: O31 R12 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10100-021-00764-3

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