Agglomeration and Growth : Cross-Country Evidence

We investigate the impact of within-country spatial concentration of economic activity on country-level growth, using cross-section OLS and dynamic panel GMM estimation. Agglomeration is measured alternatively through measures of urbanization and through indices of spatial concentration based on data for sub-national regions. Across estimation techniques, data sets and variable definitions, we find evidence that supports the "Williamson hypothesis": agglomeration boosts GDP growth only up to a certain level of economic development. The critical level is estimated at some USD 10,000, corresponding roughly to the current per-capita income level of Brazil or Bulgaria. This implies that the tradeoff between national growth and inter-regional equality may gradually lose its relevance

Agglomeration and Growth: Cross-Country Evidence

We investigate the impact of within-country spatial concentration of economic activity on country-level growth, using cross-section OLS and dynamic panel GMM estimation. Agglomeration is measured alternatively through urbanization shares and through indices of spatial concentration based on data for sub-national regions. Across estimation techniques, data sets and variable definitions, we find evidence that supports the "Williamson hypothesis": agglomeration boosts GDP growth only up to a certain level of economic development. The critical level is estimated at some USD 10,000, corresponding roughly to the current per-capita income level of Brazil or Bulgaria. Hence, the tradeoff between national growth and inter-regional equality may gradually lose its relevance. Our results also imply that, in terms of foregone growth, the cost of policies that inhibit economic agglomeration is highest in the poorest countries

Growth, Agglomeration and Convergence: a Space-time Analysis for European Regions

Abstract This paper sheds empirical light on the relationship between agglomeration and economic growth and its impact on the convergence hypothesis. Using a sample of 208 European regions over 25 years, ‘standard’ growth regressions are estimated using panel data techniques. Both the effect of agglomeration within one's own region and the interregional aspect of agglomeration are looked at. The estimation results show that, on average, denser regions grow slower than other regions, indicating a net negative effect of agglomeration. However, being located close to other growing regions is found to stimulate growth in one's own region. The implied convergence rate is also affected when the inter- and intraregional aspects of agglomeration are taken into account, where the former (latter) results in lower (slightly higher) convergence estimates.Economic growth, agglomeration, spatial econometrics, C23, R11, R12,