Working Paper: CEPR ID: DP7479
Authors: Klaus Desmet; Esteban Rossi-Hansberg
Abstract: We present a theory of spatial development. A continuum of locations in a geographic area choose each period how much to innovate (if at all) in manufacturing and services. Locations can trade subject to transport costs and technology diffuses spatially across locations. The result is an endogenous growth theory that can shed light on the link between the evolution of economic activity over time and space. We apply the model to study the evolution of the U.S. economy in the last few decades and find that the model can generate the reduction in the employment share in manufacturing, the increase in service productivity in the second part of the 1990s, the increase in land rents in the same period, as well as several other spatial and temporal patterns.
Keywords: dynamic spatial models; growth; innovation; land rent; evolution; structural transformation; technology diffusion; trade
JEL Codes: E32; O11; O18; O33; R12
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| higher transport costs (L91) | increased clustering of economic activity (R11) |
| increased clustering of economic activity (R11) | affects innovation rates (O39) |
| dynamics of innovation across different locations (O36) | reduction in the employment share in manufacturing (O14) |
| dynamics of innovation across different locations (O36) | increase in service productivity (O49) |
| increased service sector innovation (O35) | spatial concentration (R32) |
| service productivity growth (O49) | real wage growth (J39) |
| service productivity growth (O49) | increase in land values (R52) |
| changes in transport costs (R41) | significant effects on spatial dynamics (R12) |
| elasticity of substitution between sectors (F16) | significant effects on spatial dynamics (R12) |