Adjusting for Non-Linear Age Effects in the Repeat Sales Index

A true constant quality real estate price index should measure the general change in price level free from any change in quality over time. In recent years, the repeat-sales method has been widely used to construct constant quality property price indices. Since buildings depreciate over time, a simple repeat-sales index would underestimate the growth in property prices. The major problem of controlling the effects of age constant in a repeat-sales model arises from the exact multicollinearity between the age variable and the time dummy variables. In this study, we derive a solution that is theoretically sound and practical by allowing the age effects to be non-linear. In case of leasehold properties, we further incorporated interest rates into the model because the effects of age on real estate prices depend theoretically on interest rates. A sample of residential units in Hong Kong sold more than once from Quarter 2 of 1991 to Quarter 1 of 2001 (more than 11,000 repeat sales pairs) are used for the empirical analysis.     

Aggregation Bias in Repeat-Sales Indices

The repeat-sales methodology has become a standard approach for estimating real estate price indices. This article examines the underlying assumptions inherent in the repeat sales model and provides an empirical test for both included and omitted variables as sources of aggregation bias. The results indicate that virtually all price indices may be biased, the degree of bias being dependent upon the number of variables examined and the instability of their parameters over time.     

Price Indices Based on the Hedonic Repeat-Sales Method: Application to the Housing Market

Shiller (1993) proposes the hedonic repeated-measures (HRM) approach to measuring constant quality price indices for heterogeneous assets such as some bonds and real estate. We derive a mathematical relationship between the coefficients of the HRM model and those from the standard repeat-sales model, and we demonstrate how hedonic characteristics should be chosen for inclusion in the HRM model. Empirical estimates using Fairfax, Virginia, housing transactions data show that the HRM price index evaluated at the mean of the hedonic variable is virtually identical to the standard repeat sales index, just as predicted by our mathematical relationship. But the HRM allows estimation of different price paths for heterogeneous assets. We demonstrate that use of assessed value as the only hedonic characteristic allows parsimonious HRM estimates.     

Are REITs real estate? Evidence from international sector level data

The aim of this study is to examine whether securitized real estate returns reflect direct real estate returns or general stock market returns using international data for the U.S., U.K., and Australia. In contrast to previous research, which has generally relied on overall real estate market indices and neglected the potential long-term dynamics, our econometric evaluation is based on sector level data and caters for both the short-term and long-term dynamics of the assets as well as for the lack of leverage in the direct real estate indices. In addition to the real estate and stock market indices, the analysis includes a number of fundamental variables that are expected to influence real estate and stock returns significantly. We estimate vector error-correction models and investigate the forecast error variance decompositions and impulse responses of the assets. Both the variance decompositions and impulse responses suggest that the long-run REIT market performance is much more closely related to the direct real estate market than to the general stock market. Consequently, REITs and direct real estate should be relatively good substitutes in a long-horizon investment portfolio. The results are of relevance regarding the relationship between public and private markets in general, as the ‘duality’ of the real estate markets offers an opportunity to test whether and how closely securitized asset returns reflect the performance of underlying private assets. The study also includes implications concerning the recent financial crisis.     

Home Price Risk, Local Market Shocks, and Index Hedging

All real estate markets are local, or so the conventional wisdom goes. But just how local is local? I address this question empirically using over 75,000 repeat-sales transactions from a large suburban county of Washington D.C.. I construct and evaluate a variety of local home price indices defined by geography, price, and home type. I also calculate ??house-specific?? indices using locally weighted regressions with maximized kernel bandwidths. On the whole, local indices add a moderate amount of explanatory power relative to metropolitan indices. In my sample, the metropolitan index explains 50?C75% of the variation in home price shocks, and local indices add 3?C7% more. In an index hedging framework, homeowners should be willing to pay 5?C10% to hedge with a local index versus a metropolitan index alone.     

Rushing to Overpay: Modeling and Measuring the REIT Premium

We explore the questions of why Real Estate Investment Trusts (REITs) pay more for real estate than non-REIT buyers and by how much. First, we develop a search model where REITs optimally pay more for property because (1) they are willing, due to cost of capital advantages and, (2) they are occasionally rushed, due to external regulatory time constraints and internal incentives to deploy capital quickly. Second, using commercial real estate transactions, we find that the extant hedonic pricing models contain an unobserved explanatory variables bias leading to inflated estimates of the REIT premium. Third, using a repeat-sales methodology that controls for unobserved property characteristics, we derive more plausible estimates of the REIT premium. Consistent with our model, we also find the REIT-buyer premium depends on the size of the REIT advantage, the rush to deploy, and the relative presence of REITs in the market.     

The Construction of Residential Housing Price Indices: A Comparison of Repeat-Sales,Hedonic-Regression,and Hybrid Approaches

This article examines a number of hypotheses that underpin the repeat-sales and hedonic approaches to the construction of housing price indices, as well as the practical problems associated with the implementation of either approach. We also examine a hybrid procedure that combines elements of both the repeat-sales and hedonic-regression techniques. For our sample of individual home sales in Oakland and Fremont California over an 18-year period, repeat-sales methods are subject to sample selection bias; the maintained assumption of time constancy of implicit prices of housing attributes is violated; the repeat-sales estimator is extremely sensitive to influential observations; and the usual method used to correct for heteroskedasticity in repeat-sale housing returns is inappropriate in our sample. Hedonic techniques are better suited to contend with index number problems per se, as they can accommodate changing attribute prices over time. They also appear to give rise to more reliable estimates of price indices, as unusual observations have less effect on estimated price indices. Drawbacks of the hedonic approach include the usual concern with omitted attributes, and their effect on the estimated price index.     

Corporate real estate's impact on the takeover market

This article explores the issues and problems associated with corporate real estate ownership as viewed through the takeover market. The perception held by managers is that corporate real estate assets are unique, specialized assets. This perception conflicts with financial theory which states that the market values all corporate assets based only on their expected future cash flows. Thus corporate real estate assets are priced according to their cash flows and are like other corporate assets. This study tests the hypothesis that corporate real estate is a specialized asset by examining the impact real estate assets have on the takeover market. The study uses a logit regression model in order to attempt to predict which firms become takeover targets. If corporate real estate in general is a specialized asset, then real estate is expected to be an important variable in predicting takeover targets. Although the logit model has little predictive accuracy, results from the prediction model suggest that corporate real estate plays a significant part in determining the likelihood of a firm's becoming a takeover target. The greater the real estate holdings, the greater the likelihood of a firm's becoming a takeover target.     

Assessing the Real Estate Pricing Puzzle: A Diagnostic Application of the Stochastic Discounting Factor to the Distribution of REIT Returns

This article applies a general asset-pricing framework and the volatility bounds methodology of Hansen and Jagannathan (1991) to REIT returns. The state of real estate asset pricing remains somewhat of a puzzle relative to the identification of state variables and the structural form of models. This article offers a framework whereby real estate asset-pricing models and data can be diagnosed to answer questions about the shortcomings. In addition, several nominated discount processes are investigated for success in pricing real estate securities. Although the nominated specifications demonstrate some success in satisfying the restrictions on the first and second moments of the real estate returns distribution, they do not successfully price the securities under a no-arbitrage condition. This result calls into question previous real estate performance studies that employ these risk-adjustment processes.     

Dynamics of Private and Public Real Estate Markets

Using five assets (T-bills, bonds, stocks, and both public and private real estate), this study investigates how cointegration of capital markets affects the dynamics of public and private real estate markets. The results show that the price indices of the five assets are nonstationary and cointegrated. Some implications for the long-term equilibrium relationship for portfolio diversification, price discovery and prediction are discussed. In a Granger causality framework, error-correction augmented VAR models (VECM) and unrestricted VAR models are compared with respect to the conclusion regarding the interaction between public and private real estate returns. VECM is also shown to improve the prediction of private real estate returns relative to an unrestricted VAR model. These results raise questions about previous research studies regarding the dynamics between public and private real estate returns. It is shown that the long-term equilibrium relationship establishes a feedback between the two real estate markets, but the private market seems to informationally lead the public one. Possible explanations are also explored.