The urban knowledge economy and employment growth: a spatial structural equation modeling approach

Many European governments have been stimulating their urban economies by focusing on knowledge economy potentials of metropolitan regions, especially R&D-based indicators. We analyze employment growth in terms of conventional determinants—investments, wages, income, and specialization indices of industrial, distribution and business services activities—and three latent knowledge economy components (density of knowledge workers, R&D and innovativeness) for the Netherlands based on a sample of 496 municipalities. We apply a structural equation model (SEM) made up of a measurement model that relates the latent knowledge economy components to their observable indicators and a structural model that estimates the impacts of the determinants on employment growth. In addition to the conventional determinants and the knowledge economy components, the SEM accounts for spatial spillover effects, degree of urbanization and core-periphery dichotomy. The latent variables ‘density of knowledge workers’ and ‘innovativeness’ have significant and strong impacts. Since they are more common in larger than smaller urban agglomerations, we conclude that the impacts of these variables on employment growth are stronger in the former than the latter. The latent variable ‘R&D-intensity’ is not significantly, positively related to urban employment growth. This suggests that policy should emphasize innovation output and knowledge workers density rather than R&D to capture urban growth potentials in the knowledge economy.