Abstract
The article deals with the issue of knowledge spillovers in the European regions. For this purpose, a standard Knowledge Production Function (KPF) approach was extended by the application of spatial econometrics methods. Our analysis started from the construction of the alternative structures of the spatial weight matrices. These matrices were based on technological and institutional proximities, which represent compelling alternatives to geographic proximity regarded as a kind of all-encompassing connectivity measure. The next step in our analysis was the modeling of regional knowledge generation processes. We treated R&D expenditures and human resources in science and technology as the input measures and patent applications to the European Patent Office as the output measure in our basic and extended models. The results show that the scope and direction of knowledge spillovers are sensitive to the type of knowledge (tacit vs. codified) and proximity dimension engaged. These findings contribute to the current debate in the geography of innovation and economics of knowledge literature.
Highlights
The geographical proximity between firms or regions has been considered as a main transmission channel of innovation and knowledge
It is assumed that regional knowledge-intensive specialization, which tends to cluster in dense urban areas, positively affects the total factor productivity (TFP) growth
This paper examines knowledge spillovers using the Knowledge Production Function (KPF) at the regional level for Europe
Summary
The geographical proximity between firms or regions has been considered as a main transmission channel of innovation and knowledge. The most comprehensive approach to knowledge externalities takes into account all aspects of distance between firms or regions, i.e., geographical, social, institutional, technological, and organizational [3] This procedure is consistent with spatial econometric contribution, which often gives up geographical distance in regional studies and takes economic variables to measure distance between spatial units. It better reflects the structure of connections between regions because the country boundaries and geographic distance plays a decreasing role in these relationships [4]
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