Introduction and main findings

Over the past several years, the OECD has quantified the impact of structural policies on employment, productivity, and GDP per capita (e.g. OECD 2003, 2006). The results from these studies, which have built on a vast academic literature, have contributed to a better understanding of the main channels linking policies to labor and product market outcomes in OECD countries. In doing so, they have also underscored the limits to the understanding of economic growth: only a limited part of the cross-country dispersion in GDP levels and growth rates can be explained by quantifiable policy levers, at least on the basis of standard macro-growth regression analysis.

This paper examines how much of the cross-country dispersion in economic performance can be accounted for by economic geography factors. To do so, an augmented Solow model is used as a benchmark. The choice is motivated by the fact that this model has served as the basic framework in previous work on the determinants of growth, thereby ensuring some continuity. It has long been recognized, however, that while providing a useful benchmark to assess the contributions of factor accumulation as a source of differences in GDP per capita, the basic Solow growth model ignores potentially important determinants. For instance, it leaves a large portion of growth to be explained by the level of technology, which is assumed to grow at a rate set exogenously.