Physical Sciences and Mathematics Commons^™

A Monte Carlo Analysis Of Hedonic Models Using Traditional And Spatial Approaches, Helen R. Neill, David M. Hassenzahl, Djeto D. Assane

Public Policy and Leadership Faculty Publications

Hedonic regression analysis of single family homes typically includes structural variables, locational variables and neighborhood quality characteristics. When nearby properties are related, Dubin (1988) reports that error terms are spatially autocorrelated. Estimation methods for these spatially autocorrelated error terms or hereafter, spatial approaches, include maximum likelihood estimation (MLE) and kriging techniques such as kriged maximum likelihood estimation (KMLE). Unfortunately these spatial methods require massive computer resources and are limited to significantly fewer observations than traditional ordinary least squares (OLS). This paper investigates the combination of spatial approaches and Monte Carlo analysis, a method that approximates large data sets. A question …