The influence of house, seller, and locational factors on the probability of sale

Abstract Ability to model the probability of individual house sales would be of benefit in a number of real estate contexts. Existing housing literature models the probability of a house sale using mainly property characteristics or macroeconomic variables. However, the use of only property characteristics typically yields a poor model fit. This study investigates the relative roles of property characteristics, seller mortgage origination variables, and locational factors in terms of explaining the probability of individual house sales. Homeowner information such as their time horizon of staying in the house and their stage in the life cycle should have an important impact on house sale decisions. Although obtaining such information is typically difficult, mortgage choices made at loan origination may help reveal such information. In addition, the measurable characteristics of neighbors and the geographic clustering of house sales, ceteris paribus , may aid in modeling house sales. Incorporating the property characteristics, mortgage origination variables, and locational factors increases the pseudo- R 2 of a probit model from under 1 percent when only using property characteristics to over 23 percent when using property, mortgage, and spatial information. The results are consistent through a particularly large housing cycle in both Las Vegas County in Nevada and Maricopa County in Arizona from 2006 to 2010, and for a variety of sub samples.