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Bootstrapping a hedonic price index: experience from used cars data

Beer, Michael

In: AStA Advances in Statistical Analysis, 2007, vol. 91, no. 1, p. 77-92

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    Titre
    • Bootstrapping a hedonic price index: experience from used cars data
    Auteur
    • Beer, Michael. Seminar of Statistics, Dept. of Quantitative Economics, University of Fribourg Switzerland, Bd de Perolles 90, 1700, Fribourg, Switzerland
    Type de document
    • Postprint
    Langue
    • Inglese
    Publié dans
    • AStA Advances in Statistical Analysis, 2007, vol. 91, no. 1, p. 77-92. Springer-Verlag
    Autre version électronique
    Identifiant OAI-PMH
    • oai:doc.rero.ch:315906
    Summary
    Every hedonic price index is an estimate of an unknown economic parameter. It depends, in practice, on one or more random samples of prices and characteristics of acertain good. Bootstrap resampling methods provide atool for quantifying sampling errors. Following some general reflections on hedonic elementary price indices, this paper proposes acase-based, amodel-based, and awild bootstrap approach for estimating confidence intervals for hedonic price indices. Empirical results are obtained for adata set on used cars in Switzerland. Asimple and an enhanced adaptive semi-logarithmic model are fit to monthly samples, and bootstrap confidence intervals are estimated for Jevons-type hedonic elementary price indices