For example, automobiles differ by the basic characteristics of safety, comfort, and fuel economy. Computers differ by memory capacity, display resolution, and speed. Housing differs by accessibility, privacy, cleanliness of the environment, quantity of housing services, and safety. Hedonic pricing attempts to take observations on the overall good or service and obtain implicit prices for the atomistic goods and services. It performs this statistically by regressing the overall price onto the atomistic characteristics.
Economists frequently estimate hedonic pricing models using data from the housing or labor markets.
Both labor and housing markets have a strong spatial component. Wages vary by part of the city and by region of the country while housing prices depend strongly upon location. The use of space helps control for omitted variables correlated with space. Such variables could include crime, air pollution, and other externalities. Insofar as correlations often exist among the omitted and included variables, controlling for space can potentially improve hedonic pricing model parameter estimation and hence estimation of the price of implicit characteristics.