How industrial clusters influence the growth of the regional GDP: A spatial-approach

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. Our findings indeed reveal highly significant impacts, which can be either positive or negative, of specific sectors on local GDP growth. Spatially, we observe that direct and indirect effects can exhibit opposite signs, indicative of heightened competitiveness within and between industry sectors. Therefore, we recommend that industry sectors should be taken into consideration when conducting spatial analysis of GDP. Doing so allows for a more comprehensive understanding of the economic dynamics at play.