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Bootstrapping a Hedonic Price Index |

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.

Bootstrapping a Hedonic Price Index: Experience from Used Cars Data

Published in AStA Advances in Statistical Analysis (formerly called Allgemeines Statistisches Archiv), a journal of the German Statistical Society, DOI 10.1007/s10182-006-0015-9.

The original publication is available at www.springerlink.com.

A self-archived version is available in the working paper series of the Department of Quantitative Economics at the University of Fribourg Switzerland.

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