Previous studies have shown that foreclosure often results in vandalism, disinvestment and other negative spillover effects in the neighborhood. This paper extends these views into a formal theoretical model through pricing based on comparables. We project that the spillover effect of a foreclosure on neighborhood property values depends on two factors: the discount of foreclosure sale and the weight placed on the foreclosed property as a comparable in the valuation. The former is related to housing cycle and the latter varies by time of foreclosure and its distance from the subject property. Empirical results based on a 2006 sample show that this effect is significant within a radius of 0.9 km (roughly 10 blocks) and within 5 years from its liquidation. The most severe impact is an 8.7% discount on neighborhood property values, which gradually drops to anywhere between −1.2 to −1.7% for foreclosures liquidated within the past 5 years. These spillover effects vary slightly when the sample selection bias is taken into account. Based on an alternative sample of purchase transactions in 2003, the estimated spillover effects in booming years are reduced by half, confirming on the important role played by housing cycles. Copyright Springer Science+Business Media, LLC 2009Foreclosure, Spillover, Valuation,

This article addresses the micro-analytic foundations of illiquidity and price dynamics in the real estate market by integrating modern portfolio theory with models describing the real estate transaction process. Based on the notion that real estate is a heterogeneous good that is traded in decentralized markets and that transactions in these markets are often characterized by costly searches, we argue that the most important aspects defining real estate illiquidity in both residential and commercial markets are the time required for sale and the uncertainty of the marketing period. These aspects provide two sources of bias in the commonly adopted methods of real estate valuation, which are based solely on the prices of sold properties and implicitly assume immediate execution. We demonstrate that estimated returns must be biased upward and risks downward. These biases can be significant, especially when the marketing period is highly uncertain relative to the holding period. We also find that real estate risk is closely related to investors' time horizons, specifically that real estate risk decreases when the holding period increases. These results are consistent with the conventional wisdom that real estate is more favorable to long-term investors than to short-term investors. They also provide a theoretical foundation for the recent econometric literature, which finds evidence of smoothing of real estate returns. Our findings help explain the apparent risk-premium puzzle in real estate-that is, that ex post returns appear too high, given their apparent low volatility-and can lead to the formal derivation of adjustments that can define real estate's proper role in the mixed-asset portfolio. The Risk-Premium Puzzle in Real EstateProper pricing, evaluation of investment performance and allocation of real estate in a mixed-asset portfolio have persisted as vexing research issues. Real estate is highly heterogeneous, thinly traded over relatively long holding periods and traded through a transactions process that is typically not a simultaneous bid auction but instead is a sequential bid process without recall, which may involve significant transaction costs. Thus, it displays characteristics of illiquidity, but a type of illiquidity that may depart from that displayed by thinly traded securities. * Fannie Mae, Washington DC 20016 or len lin@fanniemae.com.

This article develops a theoretical framework and formulates a unified risk metric that integrates both real estate price risk and uncertainty of time on market (TOM). We demonstrate that real estate sellers with different degrees of financial distress face not only different marketing period risks, but also receive different return distributions upon successful sales. The major findings of this article can be summarized as follows. First, we show that real estate return and risk, which account for both price and TOM risk, are investor specific, varying over investors with different financial circumstances and holding periods. Second, the traditional valuation of real estate return and risk, which is based solely on the return distribution of a successful sale without considering the uncertainty of TOM and the investor's financial circumstances, underestimates real estate risk and exaggerates real estate return. Third, our empirical applications in both residential and commercial real estate markets show that the Sharpe ratio estimated by the traditional approach is seriously overstated-to the largest extent for investors with high financial distress. In addition, we find that, given the typical 5- to 7-year holding period for real estate, the Sharpe ratios estimated by integrating both price and TOM risk are much in line with the performance of financial assets. These findings can help to explain the apparent "risk-premium puzzle" in real estate. Copyright 2008 American Real Estate and Urban Economics Association

This article develops a model and provides a closed-form formula to uncover the theoretical relationship between real estate price and time on market (TOM). Our model shows a nonlinear positive price-TOM relationship, and it identifies three economic factors that affect the impact of TOM on sale price. We demonstrate that conventional metrics for real estate return and risk, which are borrowed in a naïve fashion from finance theory, do not account for marketing period risk and tend to overestimate real estate returns and underestimate real estate risks. Our model provides a simple way to correct such bias. This theory helps to explain the apparent "risk-premium puzzle" in real estate. Copyright 2008 American Real Estate and Urban Economics Association

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