County Child Poverty Rates in the U.S.: A Spatial Econometric Approach

Paul R. Voss, University of Wisconsin at Madison
David D. Long, University of Wisconsin at Madison
Roger B. Hammer, University of Wisconsin at Madison
Samantha Friedman, George Washington University

This paper is a formal reanalysis of earlier work reported by Friedman and Lichter (1998) in which the effects on child poverty of local industrial structure and household/family composition are examined in a multiple regression framework. The original analysis was persuasive and provided an important contribution to the poverty literature. It did not, however, take full advantage of emerging tools in the geospatial analysis and spatial econometrics. Our reanalysis maintains the original theoretical orientation, variable operationalization, and causal structure. However, by explicitly acknowledging spatial externalities and neighborhood structure in the model specification, several improvements to the original specification are achieved. The reanalysis is a convincing demonstration of the need for demographers and other social scientists to examine spatial autocorrelation in their data and to explicitly correct for spatial externalities, if indicated, when performing multiple regression analyses on variables that are spatially referenced.