FHA/VA Financing and Price Discounts

This study examines the effects of FHA and VA mortgage financing on home prices. FHA and VA borrowers receive higher loan-to-value ratios (LVRs) and payment to income (PTIs) ratios relative to conventional underwriting standards. These more lenient standards are offset by the payment of additional financing costs in the form of default insurance premiums and origination fees. The hypothesis for this study is that the origination fees (in the form of insurance premiums and the funding fees) associated with FHA and VA financing will (1) be capitalized into buyer reservation values and (2) result in price discounts relative to conventional loans with lower LVRs. Using a database of nearly 9,000 homes sales in the San Antonio, TX area, we perform hedonic analyses that indicate that both types of government backed financing are associated with reductions in selling prices. The results of this study may imply a cost shifting behavior on the part of buyers and an implicit subsidy on the part of sellers. Our preferred regressions find that the price discounts for FHA underwriting are about 4% (3.81% to 4.14%) relative to conventional financing. VA discounts, as expected, are smaller, ranging from about 2% to 3.46%. Given the prior literature, we hypothesize that the results are likely a result of the fact that FHA and VA homebuyers are able to shift some costs to sellers.

Thoroughfares and Apartment Values

While the monocentric urban models were once adequate for predicting the declining rent gradients for North American cities, the advent of a transportation system with major arteries such as turnpikes, thoroughfares and commuter rails has distorted the rent gradient for many cities. In this study we examine the rent (or value) gradient for the City of Philadelphia with special reference to the impact of two major urban thoroughfares on apartment values. We find that apartment values decline by approximately 2.2% and 3.8% per block from major thoroughfares, while holding distance to the CBD and standard variables constant. As to be expected, distance to the CBD still continues to exert a dominant influence on apartment values in spite of the impacts of the thoroughfares. The findings are consistent with Ôaxial growth theory.

Historic Districts and Land Values

We measure the net effect of historic districting on the value of federally certified historic sites. The impact could be either positive or negative depending on the tension between positive externality effects and the constraints on property rights. Since federally certified historic parcels are not severely encumbered by regulations, we expect positive externality effects to dominate any negative effects of constraining rights. We find that the net effect of historic districting on land values is significantly positive. We also find that while residential parcels within historic districts attract a huge price premium of 131%, the premium associated with nonresidential parcels within historic districts is statistically insignificant.

The Risk-Return Attributes of International Real Estate Equities

This paper examines the risk and return attributes of international real estate equities over the 1980-1988 time period. The empirical results indicate that international real estate equities offer higher returns as well as greater total and systematic risk than U.S.-based REITs. The results also indicate that international real estate equities are weakly positively correlated with the return on REITs. International real estate equities achieve higher values for both the Treynor and Jensen measures than either the S&P 500 Index or the World Equities Index. International real estate equities also outperform domestic real estate companies on a risk-adjusted basis. However, international real estate equities underperform the World Equities Index using the Sharpe Index which suggests that international real estate equities carry significant unsystematic risk.

Mispricing and Optimal Time on the Market

This study is an empirical examination of the relationship between pricing and optimal time on the market (TOM). First, estimates of optimal TOMs for our data set are generated using a linear programming model. Next, a workable measure of pricing is provided based on predicted listing prices and predicted sales prices. We are then able to measure directly the relationship between pricing and optimal TOM. The results of our analysis indicate that both overpricing and underpricing would prevent the achievement of optimal TOM and result in suboptimal sales prices.