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- W2032279134 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." @default.
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- W2032279134 date "2007-01-18" @default.
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- W2032279134 title "Bootstrapping a hedonic price index: experience from used cars data" @default.
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- W2032279134 doi "https://doi.org/10.1007/s10182-006-0015-9" @default.
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