We study how technological progress in manufacturing and transportation to-gether with migration costs interact to shape the space-economy. Rising labor productivity in the manufacturing sector fosters the agglomeration of activities, whereas falling transport costs associated with technological and organizational in-novations fosters their dispersion. Since these two forces have been at work for a long time, the final outcome must depend on how drops in the costs of producing and trading goods interact with the various costs borne by migrants. Finally, when labor is heterogeneous, the most efficient workers of the less productive region are the first to move to the more productive region.
We develop a monopolistic competition model with heterogeneous agents who self-select into occupations (entrepreneurs and workers) depending on innate ability. The effect of market size on the equilibrium occupational structure crucially hinges on properties of the lower tier utility function—its scale elasticity and relative love for-variety.When combined with the underlying ability distribution, the share of entrepreneurs and income inequality can increase or decrease with market size. When extended to allow for the endogenous sorting of mobile agents between cities, numerical examples suggest that sorting may increase inequality within and between cities.
Standard measures of competitive toughness fail to capture the fact that, as consumers optimize intertemporally, firms operating today compete with (yet non-existent) businesses which will be started tomorrow. We develop a two-tier CES model of dynamic monopolistic competition in which the impact of product differentiation on the market outcome depends crucially on the elasticity of intertemporal substitution (EIS). The degree of product differentiation per se fails to serve as a meaningful indicator of competitive toughness: what matters is its cross-effect with EIS. We also extend the model to the case of non-CES preferences to capture variable markups.
This paper provides an empirical test of spatial wage convergence in Russian cities. Using geo-coded data covering 997 Russian cities and towns from 1996 to 2013, I show that real city wages (i) converge over time and (ii) are significantly affected by the initial levels of real wages in neighboring cities. I also find that cities of the Far North, where a special wage policy is implemented, were converging more slowly than the rest of the country. I find a significant negative impact of regional subsidies on real wages in cities outside the Far North, and that the effect of extractive industries on real wage has become weaker. These results are robust to the radius of spatial interaction, and my conclusions hold if remote settlements are not taken into account.