Socio‐economic distance and spatial patterns in unemployment

TLDR

The study investigates whether spatial dependence in Chicago unemployment (1980–1990) aligns with models of locally exchanged information within social networks. The authors estimate non‑parametric correlations across Census tracts using physical distance, travel time, and ethnic/occupational differences, both alone and in pairs, for raw unemployment rates and after conditioning on tract characteristics. They find strong positive spatial dependence in raw unemployment rates across all metrics, but most autocorrelation disappears after conditioning, leaving only physical and occupational distance significant, with racial and ethnic composition being the key explanatory factor. © 2002 John Wiley & Sons, Ltd.

Abstract

Abstract This paper examines the spatial patterns of unemployment in Chicago between 1980 and 1990. We study unemployment clustering with respect to different social and economic distance metrics that reflect the structure of agents' social networks. Specifically, we use physical distance, travel time, and differences in ethnic and occupational distribution between locations. Our goal is to determine whether our estimates of spatial dependence are consistent with models in which agents' employment status is affected by information exchanged locally within their social networks. We present non‐parametric estimates of correlation across Census tracts as a function of each distance metric as well as pairs of metrics, both for unemployment rate itself and after conditioning on a set of tract characteristics. Our results indicate that there is a strong positive and statistically significant degree of spatial dependence in the distribution of raw unemployment rates, for all our metrics. However, once we condition on a set of covariates, most of the spatial autocorrelation is eliminated, with the exception of physical and occupational distance. Racial and ethnic composition variables are the single most important factor in explaining the observed correlation patterns. Copyright © 2002 John Wiley & Sons, Ltd.