County child poverty rates in the US: a spatial regression approach

We apply methods of exploratory spatial data analysis (ESDA) and spatial regression analysis to examine intercounty variation in child poverty rates in the US. Such spatial analyses are important because regression models that exclude explicit specification of spatial effects, when they exist, can lead to inaccurate inferences about predictor variables. Using county-level data for 1990, we reexamine earlier published results [Friedman and Lichter (Popul Res Policy Rev 17:91–109, 1998)]. We find that formal tests for spatial autocorrelation among county child poverty rates confirm and quantify what is obvious from simple maps of such rates: the risk of a child living in poverty is not (spatially) a randomly distributed risk at the county level. Explicit acknowledgment of spatial effects in an explanatory regression model improves considerably the earlier published regression results, which did not take account of spatial autocorrelation. These improvements include: (1) the shifting of ‘‘wrong sign’’ parameters in the direction originally hypothesized by the authors, (2) a reduction of residual squared error, and (3) the elimination of any substantive residual spatial autocorrelation. While not without its own problems and some remaining ambiguities, this 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. Substantively, the analysis improves the estimates of the joint effects of placeinfluences and family-influences on child poverty. P. R. Voss (&) Æ D. D. Long Department of Rural Sociology, University of Wisconsin-Madison, 340 Agriculture Hall, 1450 Linden Drive, Madison, WI 53706, USA e-mail: [email protected] R. B. Hammer Department of Sociology, Oregon State University, Corvallis, OR 97331, USA S. Friedman Department of Sociology and Anthropology, Northeastern University, 500 Holmes Hall, Boston, MA 02115, USA 123 Popul Res Policy Rev (2006) 25:369–391 DOI 10.1007/s11113-006-9007-4 County child poverty rates in the US: a spatial regression approach Paul R. Voss Æ David D. Long Æ Roger B. Hammer Æ Samantha Friedman Received: 24 August 2004 / Accepted: 27 November 2004 / Published online: 16 November 2006 Springer Science+Business Media B.V. 2006