How industrial clusters influence the growth of the regional GDP: A spatial-approach
Vahidin Jeleskovic, Steffen Loeber

TL;DR
This paper uses advanced spatial econometric methods to analyze how industry clusters affect regional GDP growth in German regions, revealing significant sector-specific impacts and spatial interdependencies.
Contribution
It introduces a novel extension of the spatial Durbin model incorporating industry sector indicators to better capture sector-specific effects and address omitted variable bias.
Findings
Significant positive and negative sector impacts on GDP growth.
Spatial effects can have opposite signs, indicating complex inter-sector dynamics.
Accounting for industry sectors improves understanding of regional economic growth.
Abstract
In this paper, we employ spatial econometric methods to analyze panel data from German NUTS 3 regions. Our goal is to gain a deeper understanding of the significance and interdependence of industry clusters in shaping the dynamics of GDP. To achieve a more nuanced spatial differentiation, we introduce indicator matrices for each industry sector which allows for extending the spatial Durbin model to a new version of it. This approach is essential due to both the economic importance of these sectors and the potential issue of omitted variables. Failing to account for industry sectors can lead to omitted variable bias and estimation problems. To assess the effects of the major industry sectors, we incorporate eight distinct branches of industry into our analysis. According to prevailing economic theory, these clusters should have a positive impact on the regions they are associated with.…
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Taxonomy
TopicsSpatial and Panel Data Analysis · Regional Economics and Spatial Analysis · Regional Development and Policy
