Functional regression over irregular domains: Variation in the shadow price of living space

Arnab Bhattacharjee, Liqian Cai, Tapabrata Maiti

Research output: Contribution to journalArticle

4 Citations (Scopus)
31 Downloads (Pure)

Abstract

Hedonic house price models need to account for spatial heterogeneity - the variation in the functional surface of shadow prices. In this context, the complexity of spatial domains raises issues for the traditional spatial smoothing methods. Specifically, discontinuities in the spatial surface need to be accounted for, including for example, irregular boundaries, peninsulas and interior holes. Motivated by an application to housing markets, we develop a method for estimating the functional surface of a regression coefficient that varies over such a complex spatial domain. Spatially varying coefficients for a specific regressor are estimated by a combination of three spline smoothing problems, the penalties of which are based on a partial differential operator integrated only over the problem domain by using finite element analysis. The effect of additional regressors is also allowed. We verify finite sample performance using a simulation study. As an illustration, the method is applied to data from the Aveiro-Ílhavo urban housing market in Portugal.
Original languageEnglish
JournalSpatial Economic Analysis
Early online date15 Mar 2017
DOIs
Publication statusE-pub ahead of print - 15 Mar 2017

Fingerprint Dive into the research topics of 'Functional regression over irregular domains: Variation in the shadow price of living space'. Together they form a unique fingerprint.

  • Cite this