Modeling spatial variations in household disposable income with Geographically Weighted Regression
AbstractThe purpose of this paper is to analyze the spatially varying impacts of some classical regressors on per capita household income in Spanish provinces. The authors model this distribution following both a traditional global regression and a local analysis with Geographically Weighted Regression (GWR). Several specifications are compared, being the adaptive bisquare weighting function the more efficient in terms of goodness-of-fit. We test for global and local spatial instability using some F-tests and other statistical measures. We find some evidence of spatial instability in the distribution of this variable in relation to some explanatory variables, which cannot be totally solved by spatial dependence specifications. GWR has revealed as a better specification to model per capita household income. It highlights some facets of the relationship completely hidden in the global results and forces us to ask about questions we would otherwise not have asked. Moreover, the application of GWR can also be of help to further exercises of micro-data spatial prediction.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 1682.
Date of creation: 24 Jan 2007
Date of revision:
Geographically Weighted Regression (GWR); spatial non-stationarity; spatial prediction; income; Spanish provinces;
Find related papers by JEL classification:
- R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-02-17 (All new papers)
- NEP-GEO-2007-02-17 (Economic Geography)
- NEP-URE-2007-02-17 (Urban & Real Estate Economics)
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- Griffith, Daniel A., 1992. "A spatially adjusted N-way ANOVA model," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 347-369, September.
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