Bootstrapping a hedonic price index: experience from used cars data
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 a certain good. Bootstrap resampling methods provide a tool for quantifying sampling errors. Following some general reflections on hedonic elementary price indices, this paper proposes a case-based, a model-based, and a wild bootstrap approach for estimating confidence intervals for hedonic price indices. Empirical results are obtained for a data set on used cars in Switzerland. A simple 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.
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Volume (Year): 91 (2007)
Issue (Month): 1 (March)
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- Jonathan Murray & Nicholas Sarantis, 1999. "Price-Quality Relations and Hedonic Price Indexes for Cars in the United Kingdom," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 6(1), pages 5-27.
- James G. MacKinnon, 2002. "Bootstrap inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 35(4), pages 615-645, November.
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- Bruce Curry & Peter Morgan & Mick Silver, 2001. "Hedonic regressions: mis-specification and neural networks," Applied Economics, Taylor & Francis Journals, vol. 33(5), pages 659-671.
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