2.2 Regression Model for Commercial Mortgage Spreads Following Titman et al. (2005), we estimate a model for commercial mortgage spreads that includes a variety of property and mortgage characteristics. We also include a proxy for the degree of tenant diversification and fixed effects for each month. We specify our regression model as follows: We summarize all of the variables used in our model in Table 2, and each variable is discussed below. [Insert Table 2 around here.] In our primary model specification, we use a series of dummy variables representing the L1 categories to investigate the impact of tenant diversification on mortgage spreads. The dummy variable specification for L1% allows us to control for a potential nonlinear relationship between tenant diversification and mortgage spreads. Because we expect more diversified properties to be less risky, we expect the spread to decrease as the degree of tenant diversification increases. However, larger tenants create positive business externalities for smaller tenants. Additionally, it is possible that larger tenants are more creditworthy than smaller tenants and that the larger tenants provide a more stable source of cash flow for property owners. If this is the case, then the benefits of diversification will dissipate as diversification increases due to the absence of a large, stable tenant. Thus, our model allows us to examine if borrowers on diversified properties benefit by receiving lower spreads than borrowers with a less diversified tenant base, and if so, if there are limits to which the degree of tenant diversification benefits borrowers.
2.2 Regression Model for Commercial Mortgage Spreads Following Titman et al. (2005), we estimate a model for commercial mortgage spreads that includes a variety of property and mortgage characteristics. We also include a proxy for the degree of tenant diversification and fixed effects for each month. We specify our regression model as follows: We summarize all of the variables used in our model in Table 2, and each variable is discussed below. [Insert Table 2 around here.] In our primary model specification, we use a series of dummy variables representing the L1 categories to investigate the impact of tenant diversification on mortgage spreads. The dummy variable specification for L1% allows us to control for a potential nonlinear relationship between tenant diversification and mortgage spreads. Because we expect more diversified properties to be less risky, we expect the spread to decrease as the degree of tenant diversification increases. However, larger tenants create positive business externalities for smaller tenants. Additionally, it is possible that larger tenants are more creditworthy than smaller tenants and that the larger tenants provide a more stable source of cash flow for property owners. If this is the case, then the benefits of diversification will dissipate as diversification increases due to the absence of a large, stable tenant. Thus, our model allows us to examine if borrowers on diversified properties benefit by receiving lower spreads than borrowers with a less diversified tenant base, and if so, if there are limits to which the degree of tenant diversification benefits borrowers.