This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

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

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Paul Voss ()
David Long
Roger Hammer
Samantha Friedman
Abstract

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 re-examine 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 place-influences and family-influences on child poverty. Copyright Springer Science+Business Media B.V. 2006

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://hdl.handle.net/10.1007/s11113-006-9007-4
File Format: text/html
File Function:
Download Restriction: Access to full text is restricted to subscribers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Publisher Info
Article provided by Springer in its journal Population Research and Policy Review.

Volume (Year): 25 (2006)
Issue (Month): 4 (August)
Pages: 369-391
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:kap:poprpr:v:25:y:2006:i:4:p:369-391

Contact details of provider:
Web page: http://www.springerlink.com/link.asp?id=102983

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords: Child poverty; Exploratory spatial data analysis; Spatial error models; Spatial lag models; Spatial regression;

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Can, Ayse & Megbolugbe, Isaac, 1997. "Spatial Dependence and House Price Index Construction," The Journal of Real Estate Finance and Economics, Springer, vol. 14(1-2), pages 203-22, Jan.-Marc. [Downloadable!] (restricted)
  2. Nelson, Gerald C. & Geoghegan, Jacqueline, 2002. "Deforestation and land use change: sparse data environments," Agricultural Economics, Blackwell, vol. 27(3), pages 201-216, November. [Downloadable!] (restricted)
  3. Munroe, Darla K. & Southworth, Jane & Tucker, Catherine M., 2002. "The dynamics of land-cover change in western Honduras: exploring spatial and temporal complexity," Agricultural Economics, Blackwell, vol. 27(3), pages 355-369, November. [Downloadable!] (restricted)
  4. Case, Anne, 1992. "Neighborhood influence and technological change," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 491-508, September. [Downloadable!] (restricted)
  5. Vance, Colin & Geoghegan, Jacqueline, 2002. "Temporal and spatial modelling of tropical deforestation: a survival analysis linking satellite and household survey data," Agricultural Economics, Blackwell, vol. 27(3), pages 317-332, November. [Downloadable!] (restricted)
  6. Pace, R Kelley & Barry, Ronald & Sirmans, C F, 1998. "Spatial Statistics and Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 5-13, July. [Downloadable!] (restricted)
    Other versions:
  7. Case, Anne C. & Rosen, Harvey S. & Hines, James Jr., 1993. "Budget spillovers and fiscal policy interdependence : Evidence from the states," Journal of Public Economics, Elsevier, vol. 52(3), pages 285-307, October. [Downloadable!] (restricted)
  8. Christopher H. Wheeler, 2001. "A Note on the Spatial Correlation Structure of County-Level Growth in the U.S," Journal of Regional Science, Blackwell Publishing, vol. 41(3), pages 433-449. [Downloadable!] (restricted)
  9. Bell, Kathleen P. & Irwin, Elena G., 2002. "Spatially explicit micro-level modelling of land use change at the rural-urban interface," Agricultural Economics, Blackwell, vol. 27(3), pages 217-232, November. [Downloadable!] (restricted)
  10. Muller, Daniel & Zeller, Manfred, 2002. "Land use dynamics in the central highlands of Vietnam: a spatial model combining village survey data with satellite imagery interpretation," Agricultural Economics, Blackwell, vol. 27(3), pages 333-354, November. [Downloadable!] (restricted)
  11. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November. [Downloadable!] (restricted)
  12. Nelson, Gerald C., 2002. "Introduction to the special issue on spatial analysis for agricultural economists," Agricultural Economics, Blackwell, vol. 27(3), pages 197-200, November. [Downloadable!] (restricted)
  13. Walker, Robert & Moran, Emilio & Anselin, Luc, 2000. "Deforestation and Cattle Ranching in the Brazilian Amazon: External Capital and Household Processes," World Development, Elsevier, vol. 28(4), pages 683-699, April. [Downloadable!] (restricted)
Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Paul Voss, 2007. "Demography as a Spatial Social Science," Population Research and Policy Review, Springer, vol. 26(5), pages 457-476, December. [Downloadable!] (restricted)
Statistics
Access and download statistics

Did you know? IDEAS also computes impact factors for journals and working paper series.

This page was last updated on 2009-11-25.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.