Working Paper: NBER ID: w18447
Authors: Alessandra Fogli; Enoch Hill; Fabrizio Perri
Abstract: This paper documents, using county level data, some geographical features of the US business cycle over the past 30 years, with particular focus on the Great Recession. It shows that county level unemployment rates are spatially dispersed and spatially correlated, and documents how these characteristics evolve during recessions. It then shows that some of these features of county data can be generated by a model which includes simple channels of transmission of economic conditions from a county to its neighbors. The model suggests that these local channels are quantitatively important for the amplification/muting of aggregate shocks.
Keywords: Geography; Business Cycle; Unemployment; Spatial Correlation; Great Recession
JEL Codes: E32; R12
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| unemployment in one county (J64) | unemployment in neighboring counties (J69) |
| high demand in one county (R22) | low unemployment in that county (J68) |
| unemployment spikes in a few counties (J64) | increased spatial dispersion of unemployment rates (J69) |
| increased spatial dispersion of unemployment rates (J69) | decreased spatial correlation (C49) |
| strong local connections (Y80) | greater unemployment increases during large shocks (J64) |
| strong local connections (Y80) | resilience during small shocks (E32) |
| geographic factors (R12) | dynamics of unemployment during business cycles (J64) |