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- W2108583736 abstract "Most econometric applications entail uncertainly in the choice of model. Anexample is the possible use of hedonic regressions for quality adjustment of price index numbers for radio services. Economic theory suggests that a hedonic regression specification ought to include price-determining characteristics of a good as regressors, but gives no guidance as to which characteristics are likely to be price determining. In this paper I argue that Bayesian techniques provide a natural methodology for both choosing a best model and combining inferences across models to better reflect and measure the uncertainly faced by the data analyst. Empirical analysis of hedonic regressions for radio advertising prices is used to illustrate the techniques." @default.
- W2108583736 created "2016-06-24" @default.
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- W2108583736 date "1991-07-01" @default.
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- W2108583736 title "A Bayesian approach to regression selection and estimation, with application to a price index for radio services" @default.
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- W2108583736 doi "https://doi.org/10.1016/0304-4076(91)90013-4" @default.
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