Hedonic regression

In economics, hedonic regression or hedonic demand theory is a revealed preference method of estimating demand or value. It breaks down the item being researched into its constituent characteristics, and obtains estimates of the contributory value of each characteristic. This requires that the composite good being valued can be reduced to its constituent parts and that the market values those constituent parts. Hedonic models are most commonly estimated using regression analysis, although more generalized models, such as sales adjustment grids, are special cases of hedonic models.

An attribute vector, which may be a dummy or panel variable, is assigned to each characteristic or group of characteristics. Hedonic models can accommodate non-linearity, variable interaction, or other complex valuation situations.

Hedonic models are commonly used in real estate appraisal, real estate economics, and Consumer Price Index (CPI) calculations. In CPI calculations hedonic regression is used to control the effect of changes in product quality. Price changes that are due to substitution effects are subject to hedonic quality adjustments.

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.

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