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Bootstrapping a Hedonic Price Index: Experience from Used Cars Data

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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.

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Bibliographic Info

Paper provided by Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland in its series DQE Working Papers with number 4.

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Length: 15 pages
Date of creation: 22 Jul 2005
Date of revision: 20 Jan 2007
Publication status: Published in AStA Advances in Statistical Analysis, 2007, vol. 91, no. 1, pp. 77-92.
Handle: RePEc:fri:dqewps:wp0004

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Keywords: hedonic regression; hedonic price indices; bootstrap methods; wild bootstrap; confidence intervals; used cars;

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  1. James G. MacKinnon, 2002. "Bootstrap inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 35(4), pages 615-645, November.
  2. Brachinger, Hans Wolfgang, 2002. "Statistical Theory of Hedonic Price Indices," DQE Working Papers 1, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland, revised Aug 2003.
  3. 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.
  4. Jack Triplett, 2004. "Handbook on Hedonic Indexes and Quality Adjustments in Price Indexes: Special Application to Information Technology Products," OECD Science, Technology and Industry Working Papers 2004/9, OECD Publishing.
  5. 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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Cited by:
  1. Brachinger, Hans Wolfgang & Beer, Michael, 2009. "The Econometric Foundations of Hedonic Elementary Price Indices," DQE Working Papers 12, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland.

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