Title

Estimating class-specific parametric models using finite mixtures: an application to a hedonic model of wine prices

Document Type

Article

Publication Date

5-18-2016

Publication Title

Journal of Applied Statistics

Volume

43

First Page

1253

Last Page

1261

Keywords

finite mixture models, hedonic price models, latent class models, local polynomial regression clustering, wine markets

Abstract

© 2015 Taylor & Francis. Hedonic price models are commonly used in the study of markets for various goods, most notably those for wine, art, and jewelry. These models were developed to estimate implicit prices of product attributes within a given product class, where in the case of some goods, such as wine, substantial product differentiation exists. To address this issue, recent research on wine prices employs local polynomial regression clustering (LPRC) for estimating regression models under class uncertainty. This study demonstrates that a superior empirical approach – estimation of a mixture model – is applicable to a hedonic model of wine prices, provided only that the dependent variable in the model is rescaled. The present study also catalogues several of the advantages over LPRC modeling of estimating mixture models.

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