Although product characteristics are neither produced nor consumed in isolation, hedonic price models assume that the price of a product reflects embodied characteristics valued by some implicit or shadow prices. In empirical studies, these implicit characteristic prices are coefficients that relate prices and attributes in a regression model. Hedonic price regression models are estimated using secondary data on prices and attributes of different product or service alternatives. In working with longitudinal data, one adds period-specific dummies and uses their regression coefficients to estimate quality-adjusted price indices. In hedonic regression, independent variables typically include performance-related product and service attributes. Such product characteristics represent not only value to the user but also resource cost to the producer. It has been demonstrated however that prices in hedonic regression are not determined completely by technical factors and performance-related characteristics. Brand-name and market-segment effects can explain price distortions and premiums that are charged over and above any allowance made for differences in measurable product performance.