Hedonic regression

In economics, hedonic regression, also sometimes called hedonic demand theory, is a revealed preference method for estimating demand or value of a characteristic of a differentiated good. It decomposes the item being researched into its constituent characteristics and obtains estimates of the contributory value for each. This requires that the composite good (the item being researched and valued) can be reduced to its constituent parts and that those resulting parts are in some way valued by the market. Hedonic models are most commonly estimated using regression analysis, although some more generalized models such as sales adjustment grids are special cases which do not.

Hedonic models are commonly used in real estate appraisal, real estate economics, environmental economics, and Consumer Price Index (CPI) calculations. For example, in real estate economics, a hedonic model might be used to estimate demand or willingness to pay for a housing characteristic such as the size of the home or number of bedrooms. In environmental applications, hedonic models are often used to estimate the capitalization of environmental amenities into home prices by estimating the impact of a nearby amenity (such as a park) on home prices, holding other housing characteristics fixed. 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.

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