Academic journal article Journal of Real Estate Literature

The Composition of Hedonic Pricing Models

Academic journal article Journal of Real Estate Literature

The Composition of Hedonic Pricing Models

Article excerpt

Abstract

A house is made up of many characteristics, all of which may affect its value. Hedonic regression analysis is typically used to estimate the marginal contribution of these individual characteristics. This study provides a review of recent studies that have used hedonic modeling to estimate house prices. The findings indicate that slanted versus flat roof, sprinkler system, garden bath, separate shower stall, double oven and gated community positively affect selling price while not having attic space, living in an earthquake zone, proximity to a hog farm, proximity to a landfill, proximity to high voltage lines, corporate-owned properties, percentage of Blacks or Hispanics in an area and properties that require flood insurance negatively affect selling price.

Introduction

Home is defined as the social unit formed by a family residing together. A house, on the other hand, is a bundle of characteristics such as size, quality and location. For a number of reasons, valuing a house is difficult. Being a physical asset, each house has its own specific location. Also, a house is a long-term durable good with a long life, which means that houses with substantially different ages can exist at the same time in the same market. Each house has its own unique set of characteristics that affect value. In addition, certain housing characteristics may be valued differently across different geographical areas. For example, a garage may have a greater value in a colder climate whereas a swimming pool may have a greater value in a warmer climate.

In addition to the problem of the presence of different characteristics across houses, homebuyers possess unique utility functions causing them to value characteristics differently. For example, one homebuyer may place a greater value on hardwood floors than another buyer. Thus a certain house with a given set of characteristics may be valued differently by different buyers.

All these factors suggest that housing is not a homogeneous good. Different bundles of characteristics make valuation difficult. The fact that buyers may value individual characteristics differently further complicates the process. Nonetheless, a substantial body of historical research has attempted to explain the value of housing by valuing its individual components. The typical method used to do this is the hedonic pricing model, because it allows the total housing expenditure to be broken down into the values of the individual components. One caveat in using hedonic pricing models is that the results are location-specific and are difficult to generalize across different geographic locations. Because of this, hedonic pricing models are generally used to gain insight into the workings of a particular market. On the other hand, comparing studies across areas may at least establish those characteristics that are consistently valued (either positively or negatively) by homebuyers.

Comparing studies that use hedonic models is complicated by the fact that studies define and measure variables differently. For example, one study may measure bedrooms as simply the number of bedrooms whereas another study may use binary variables (a dummy variable if the house has one bedroom, a second dummy variable if the house has two bedrooms, etc.) The comparability of previous hedonic pricing studies is also complicated and/or limited because of different empirical specifications. Typically, hedonic pricing equations have been estimated using linear or semi-logarithmic models.

Even with its problems, however, hedonic modeling can be (and has been) useful in addressing a number of issues in housing valuation. It has been used in valuing not only the obvious components such as square footage, bathrooms, etc. but has also been useful in measuring the effect of other issues such as school quality, proximity to a landfill or high voltage lines, and the effect of non-market financing.

Malpezzi, Ozanne and Thibodeau (1980) compare housing to a bundle of groceries in that some bundles are bigger than others and contain different items. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.