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A Bayesian approach to assessing the robustness of hedonic property value studies
Author(s) -
Atkinson Scott E.,
Crocker Thomas D.
Publication year - 1987
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.3950020103
Subject(s) - prior probability , covariate , econometrics , bayesian probability , collinearity , property (philosophy) , range (aeronautics) , robustness (evolution) , computer science , bayesian inference , data set , statistics , mathematics , artificial intelligence , philosophy , materials science , biochemistry , chemistry , epistemology , composite material , gene
Hedonic price models are widely employed to estimate implicit prices for bundled attributes. Residential property value studies dominate these applications. Using a representative cross‐sectional property value data set, we employ Bayesian methods to translate a range of priors in covariate selection typical of hedonic property value studies into a range of posterior estimates. We also formulate priors regarding measurement error in individual covariates and compute the ranges of resulting posterior means. Finally, we empirically demonstrate that a greater and more systematic use of prior information drawn from one's own data and from other studies can break the collinearity deadlock in this data.