2011/02/10 by Lutemberg Florencio, Lutemberg de Araújo Florencio, Francisco Cribari‐Neto +5
Economics, Econometrics and Finance · Mathematics · #62J02 #62P05 #62P20 #62P25 #Applications (stat.AP) #Economic and Environmental Valuation #FOS: Computer and information sciences #Housing Market and Economics #Spatial and Panel Data Analysis #msc:62J02 #msc:62P05 #msc:62P20 #msc:62P25 #stat.AP
paper · pdf · doi:10.48550/arxiv.1102.2015
19 pages, 6 Figures
openalex publication_date 2011/02/10 · arxiv created 2011/11/02 · arxiv updated 2011/11/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The valuation of real estates (e.g., house, land, among others) is of extreme importance for decision making. Their singular characteristics make valuation through hedonic pricing methods dificult since the theory does not specify the correct regression functional form nor which explanatory variables should be included in the hedonic equation. In this article we perform real estate appraisal using a class of regression models proposed by Rigby & Stasinopoulos (2005): generalized additive models for location, scale and shape (GAMLSS). Our empirical analysis shows that these models seem to be more appropriate for estimation of the hedonic prices function than the regression models currently used to that end.