Empirical studies in geographical economics

Since the seminal work of Krugman (1991) led the way, many researchers have further analyzed and explained the intricate connections between international trade flows, factor mobility, agglomeration and production; see Brakman et al. (2009) for an overview of the literature. As explained in Brakman and Van Marrewijk (Chapter 3 of this volume), there are now three ‘core’ models of new economic geography, or ‘geographical economics’, as we prefer to label it: (i) Krugman’s model based on labor mobility; (ii) the solvable human capital model based on Forslid and Ottaviano (2003); and (iii) the intermediate goods model based on Krugman and Venables (1995). All these models give rise to similar dynamics and core–periphery patterns with path-dependency and multiple long-run equilibria. This chapter focuses on empirical studies that stay relatively close to the core models in geographical economics. Our contribution is limited to providing an update of the contributions regarding four key features of geographical economics as identified by Head and Mayer (2004a, p. 2616): A large market potential raises local factor prices. ● A large market will increase demand for local factors of production and this raises factor rewards. Regions surrounded by or close to regions with high real income (indicating strong spatial demand linkages) will have relatively higher wages. ● A large market potential induces factor inflows. Footloose factors of production will be attracted to those markets where firms pay relatively high factor rewards. In the Krugman core model footloose workers move to the region with highest real wage and similarly firms prefer locations with good market access. ● Reduction in trade costs induces agglomeration, at least beyond a critical level of transport or trade costs. For a large range of transport costs a change in these costs may not lead to a change in the equilibrium degree of agglomeration, but if a shock moves the economy beyond its break or sustain point the economy goes from spreading to agglomeration, or vice versa, respectively. This also implies that more economic integration (interpreted as a lowering of transport costs) should at some point lead to (more) agglomeration of the footloose activities and factors of production. ● Shock sensitivity. Changes in the economic environment can (but need not!) trigger a change in the equilibrium spatial distribution of economic activity. This hypothesis goes to the heart of the idea that geographical economics models are characterized by multiple equilibria.