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Bootstrapping a Hedonic Price Index: Experience from Used Cars Data

Michael Beer

No 4, DQE Working Papers from Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland

Abstract: 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.

Keywords: hedonic regression; hedonic price indices; bootstrap methods; wild bootstrap; confidence intervals; used cars (search for similar items in EconPapers)
JEL-codes: C43 C15 E31 L62 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-mic, nep-res and nep-ure
Date: 2005-07-22, Revised 2007-01-20
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Published in AStA Advances in Statistical Analysis, 2007, vol. 91, no. 1, pp. 77-92.

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Journal Article: Bootstrapping a hedonic price index: experience from used cars data (2007) Downloads
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