In this paper we disentangle reservation prices of buyers and sellers for commercial real estate at the city level. To do so, we further develop and extend the Fisher et al. (2003, 2007) methodology to a repeat sales indexing framework. This has the advantage that it takes care of all unobserved heterogeneity, which is an important consideration in commercial real estate. Furthermore, it allows for the construction of supply and demand indexes without the need for many property characteristics or assessed values. A key innovation in our methodology, which also enables granular index production, is our use of a Bayesian, structural time series model for index estimation. By introducing these new methodological developments, we are able to estimate reliable, robust supply and demand indexes for all major metropolitan areas in the US. Here we focus on two very different urban markets: New York and Phoenix. Consistent with the notion of pro-cyclical liquidity, we find that buyers reservation prices move much more extremely and earlier than sellers reservation prices. Our results show that the demand indexes in both New York and Phoenix went down a full year earlier than the supply indexes during the crisis.
Keywords: Liquidity, Price index, Commercial real estate.
JEL classifications: R30, C11, C41.
Working paper no. 583