A Comparison of Three Methods of Estimation in the Context of Spatial Modeling

Gaurav Ghosh () and Fernando Carriazo ()
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Gaurav Ghosh: E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), http://www.eonerc.rwth-aachen.de/fcn

No 9/2009, FCN Working Papers from E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN)

Abstract: We empirically compare the accuracy and precision of representative Least Squares, Maximum Likelihood and Bayesian methods of estimation. Using an approach similar to the jackknife, each method is repeatedly applied to subsamples of a data set on the property market in Bogotá, Colombia to generate multiple estimates of the underlying explanatory spatial hedonic model. The estimates are then used to predict prices at a fixed set of locations. A nonparametric comparison of the estimates and predictions suggests that the Bayesian method performs best overall, but that the Likelihood method is most suited to estimation of the independent variable coefficients. Significant heterogeneity exists in the specific test results.

Keywords: Spatial Econometrics; Bayesian Statistics; Hedonic Valuation (search for similar items in EconPapers)
Pages: 37 pages
Date: 2009-11
New Economics Papers: this item is included in nep-ecm, nep-geo and nep-ure
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:ris:fcnwpa:2009_009

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