Hedonic regression  

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In real estate and property studies, the hedonic regression (P = f1, f2, f3, ..., fn) is often used to study the impact of a number of factors that affect housing prices

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.

See also

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