Hedonic regression

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In economics, hedonic regression, also hedonic demand theory, is a method of estimating demand or value. It decomposes 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.

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[edit] Hedonic models and real estate valuation

In real estate economics, it is used to adjust for the problems associated with researching a good that is as heterogeneous as buildings. Because buildings are so different, it is difficult to estimate the demand for buildings generically. Instead, it is assumed that a house can be decomposed into characteristics such as number of bedrooms, size of plot, or distance to the city center. A hedonic regression equation treats these attributes (or bundles of attributes) separately, and estimates prices (in the case of an additive model) or elasticity (in the case of a log model) for each of them. This information can be used to construct a price index that can be used to compare the price of housing in different cities, or to do time series analysis. As with CPI calculations, hedonic pricing can be used to correct for quality changes in constructing a housing price index. It can also be used to assess the value of a property, in the absence of specific market transaction data. It can also be used to analyze the demand for various housing characteristics, and housing demand in general. It has also been used to test assumptions in spatial economics.

The Uniform Standards of Professional Appraisal Practice, or USPAP, provides for mass appraisal standards to govern the use of hedonic regressions and other automated valuation models when used for real estate appraisal. Appraisal methodology treats the hedonic regression as essentially a statistically robust form of the sales comparison approach[1]. Hedonic models are commonly used in tax assessment, litigation, academic studies, and other mass appraisal projects.

[edit] Criticisms of hedonic models

Some commentators, including Austrian economists, have criticized the US government's use of hedonic regression in computing its CPI, fearing it can be used to mask the "true" inflation rate and thus lower the interest it must pay on Treasury Inflation-Protected Securities (TIPS) and Social Security cost of living adjustments[2]

However, the same use of hedonic models when analyzing consumer prices in other countries has shown that non-hedonic methods may misstate inflation over time by failing to take quality changes into account[3].

[edit] See also

[edit] References

  1. ^ John A. Kilpatrick, Real Estate Issues in Class Certification
  2. ^ see, for example, Peter von der Lippe, Some Conservative Comments on Hedonic Methods
  3. ^ See, for example, Reis and Silva, Hedonic Price Indexes for New Passenger Cars in Portugal, Economic Modeling23-6, December, 2006, 890-906
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