AStA Advances in Statistical Analysis

, Volume 91, Issue 1, pp 77–92 | Cite as

Bootstrapping a hedonic price index: experience from used cars data

Original Paper

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 

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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  1. 1.Seminar of Statistics, Dept. of Quantitative EconomicsUniversity of Fribourg SwitzerlandFribourgSwitzerland

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