Functional regression over irregular domains
AbstractWe develop a method for estimating the functional surface of a regression coefficient that varies over a complex spatial domain with irregular boundaries, peninsulas and interior holes. The method is motivated by, and applied to, data on housing markets, where the central object of inference is estimation of spatially varying effects of living space on house prices. For this purpose, we extend a method of spline smoothing over an irregular domain to the functional regression model. Spatially varying coefficients for a specific regressor are estimated by a combination of three smoothing problems, allowing for additional regressors with spatially fixed coefficients. The estimates adapt well to the irregular and complex spatial domain. Implicit prices for living space vary spatially, being high in the city centre and other desirable locations, and declining towards the periphery along gradients determined by major roads.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. 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.
Bibliographic InfoPaper provided by Spatial Economics and Econometrics Centre, Heriot Watt University in its series SEEC Discussion Papers with number 1301.
Date of creation: 2013
Date of revision:
Contact details of provider:
Postal: Edinburgh EH14 4AS
Phone: +44(0)131 451 3497
Fax: +44(0)131 451 3497
Web page: http://www.sml.hw.ac.uk/departments/accountancy-economics-finance.htm
More information through EDIRC
Delaunay triangulation; Finite element; Housing markets; Spatial functional regression; Spline smoothing;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2014-02-02 (All new papers)
- NEP-ECM-2014-02-02 (Econometrics)
- NEP-GEO-2014-02-02 (Economic Geography)
- NEP-URE-2014-02-02 (Urban & Real Estate Economics)
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.:
- Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
- A S Fotheringham & M E Charlton & C Brunsdon, 1998. "Geographically weighted regression: a natural evolution of the expansion method for spatial data analysis," Environment and Planning A, Pion Ltd, London, vol. 30(11), pages 1905-1927, November.
- Simon N. Wood & Mark V. Bravington & Sharon L. Hedley, 2008. "Soap film smoothing," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(5), pages 931-955.
- David O'Donnell & Alastair Rushworth & Adrian W. Bowman & E. Marian Scott & Mark Hallard, 2014. "Flexible regression models over river networks," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(1), pages 47-63, 01.
- Daniel P. McMillen, 2010. "Issues In Spatial Data Analysis," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 119-141.
- Daniel P. McMillen & Christian L. Redfearn, 2010. "Estimation And Hypothesis Testing For Nonparametric Hedonic House Price Functions," Journal of Regional Science, Wiley Blackwell, vol. 50(3), pages 712-733.
- Luc Anselin & Nancy Lozano-Gracia & Uwe Deichmann & Somik Lall, 2010. "Valuing Access to Water—A Spatial Hedonic Approach, with an Application to Bangalore, India," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(2), pages 161-179.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Colin Miller).
If references are entirely missing, you can add them using this form.