Hedonic Pricing

Hedonic pricing evaluates the benefit of a non-market characteristic (e.g., pollution, fatality risk) on market prices. It is most commonly applied to variations in residential prices reflecting the value of local environmental attributes.


  • Value of sound walls: The difference in price between houses adjacent to a freeway with a sound wall and similar houses adjacent to a similar freeway without a sound wall.
  • Value of reduced travel time to central city: The difference in price between similar houses located at different travel time distances from the central city.

The basic premise of the hedonic pricing method is that the price of a marketed good is related to its characteristics, or the services it provides. For example, the price of a car reflects the characteristics of that car—transportation, comfort, style, luxury, safety features, fuel economy, etc. The individual characteristics of a car or other good can be valued by looking at how its price people changes when controlling for other characteristics.

Uses of Hedonic Pricing

Hedonic pricing is a convenient method for estimating transportation-related benefits and disbenefits affecting residential property values. These can be negative benefits of transportation facilities such as freeway noise, or positive benefits such as improved access to activities.

Application of the Hedonic Pricing Method Using Residential Prices

Step 1

The first step is to collect data on residential property sales in the region for a specific time period (usually one year). The required data include:

  • selling prices and locations of residential properties
  • property characteristics that may affect selling prices, such as lot size, number and size of rooms, and number of bathrooms
  • neighborhood characteristics that may affect selling prices, such as property taxes, crime rates, and quality of schools
  • accessibility characteristics that may affect prices, such as distances to work and availability of public transportation
  • environmental characteristics that may affect prices

Data on housing prices and characteristics are available from municipal offices, multiple listing services, and other sources.

Step 2

Once the data are collected and compiled, the next step is to statistically estimate a function that relates property values to property characteristics. Regression analysis is typically used to estimate the influence of various property characteristics.

A model for a set of factors determining house prices could be:

P = f (D, S, V, E, H, T)

P = Price

D = Distance from the nearest central business district
S = Size of house
V = Rating of view
E = School quality
H = Proximity to highway
T = Proximity to transit

This is called a hedonic price function. The regression typically uses the logarithms of the values for the various factors. A statistical analysis package such as the Regression function in Microsoft Excel or SPSS can be used for the computations of the following type of equation:

ln (P) = ln β0 + β1 ln (D) + β2 ln (S) + β3 ln (V) + β4 ln (E) + β5 ln (H) + β6 ln (T) + e

The β values represent the role that each factor plays in the value of the residence. For example β5 is the value of each unit of proximity to the highway.

Advantages of the Hedonic Pricing Method

  • The method's main strength is that it can be used to estimate values based on actual choices.
  • Property markets are relatively efficient in responding to information, so they can be good indications of value.
  • Property records are typically very reliable.
  • Data on property sales and characteristics are readily available through many sources and can be related to other secondary data sources to obtain descriptive variables for the analysis.
  • The method is versatile, and can be adapted to consider several possible interactions between market goods and transportation benefits.

Issues and Limitations

  • The scope of benefits that can be measured is limited to things that are related to housing prices.
  • The method will only capture people's willingness to pay for perceived differences in attributes.
  • The method assumes that people have the opportunity to select the combination of features they prefer, given their income. However, the housing market may be distorted by outside influences, like taxes or interest rates.
  • The method is relatively complex to implement and interpret, requiring a high degree of statistical expertise.
  • The results depend heavily on model specification.
  • Large amounts of data must be gathered and manipulated.

Case Study Example of the Hedonic Pricing Method


The town of Southold, Long Island, New York has coastlines on both the Peconic Bay and Long Island Sound. Compared to the rest of Long Island, it is a relatively rural area, with a large amount of farmland. However, population and housing density are rapidly increasing in the town, resulting in development pressures on farmland and other types of open space.


The Peconic Estuary Program is considering various management actions for the Estuary and surrounding land areas. In order to assess some of the values that may result from these management actions, a hedonic valuation study was conducted, using 1996 housing transactions.


The study found that the following variables that are relevant for local environmental management had significant effects on property values in Southold:

  • Open Space: Properties adjacent to open space had, on average, 12.8% higher per-acre value than similar properties located elsewhere.
  • Farmland: Properties located adjacent to farmland had, on average, 13.3% lower per-acre value. Property values increased very slightly with greater distance from farmland.
  • Major Roads: Properties located within 20 meters of a major road had, on average, 16.2% lower per-acre value.
  • Zoning: Properties located within an area with two- or three-acre zoning had, on average, 16.7% higher per-acre value.
  • Wetlands: For every percentage point increase in the portion of a parcel classified as a wetland, the average per-acre value increased by 0.3%.


Based on the results of this study, managers could, for example, calculate the value of preserving a parcel of open space, by calculating the effects on property values adjacent to the parcel. For a hypothetical simple case, the value of preserving a 10 acre parcel of open space, surrounded by 15 "average" properties, was calculated as $410,907.


Boardman, A., D. Greenberg, A. Vining, and D. Weimer. Cost-Benefit Analysis: Concepts and Practice. pp. 339-344.

King, D.M. and M. Mazzotta, Ecosystem Evaluation (website). Available at: http://www.ecosystemvaluation.org/hedonic_pricing.htm.

Uyeno, D., S. Hamilton, and A. Biggs, "Density of Residential Land Use and the Impact of Airport Noise." Journal of Transport Economics and Policy, 27, no. 1, 1993.