Seller and search behavior in the Belgian housing market

This paper analyzes online real estate listings to estimate the listing price elasticity of search activity for the individual seller for both the rental and sales market. This elasticity is an essential parameter in the literature modeling the process of selling a home, as it indicates the extend to which potential buyers will react to the listing price. Furthermore, we argue that our estimates are an approximation for the average price elasticity of demand facing the individual seller, which is an indication for the amount of competition in the market. A novel dataset tracking real estate advertisements on a daily basis allows to control for unobserved heterogeneity between properties by using property fixed effects, exploiting the variation caused by changes in listing prices and search behavior throughout the listing process. The findings indicate that a one percent increase in the listing price reduces search activity for the property by 6.7 percent for the sales market and 6.6 percent for the rental market. Additionally, we find that an increase in the number of listings in a market segment enhances the listing price elasticity.