Bootstrapping a Hedonic Price Index: Experience from Used Cars Data

Beer, Michael

doi:10.1007/s10182-006-0015-9

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Journal article

Bootstrapping a Hedonic Price Index: Experience from Used Cars Data

Beer, Michael Seminar of Statistics, Dept. of Quantitative Economics, University of Fribourg Switzerland, Bd de Perolles 90, 1700, Fribourg, Switzerland

20.01.2007

Published in:

AStA Advances in Statistical Analysis. - 2007, vol. 91, no. 1, p. 77-92

English 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.

Faculty

Faculté des sciences économiques et sociales et du management

Department

Département d'économie quantitative

Language