Controlling for the Impact of Variable Liquidity in Commercial Real Estate Price Indices

Liquidity in private asset markets is notoriously variable over time. Therefore, indices of changes in market value that are based on asset transaction prices will systematically reflect intertemporal differences in the ease of selling a property. We define and develop a concept of "constant-liquidity value" in the context of a model that is characterized by pro-cyclical volume of trading. We then present an econometric model that allows for estimation of both a standard transaction-based price index and a constant-liquidity index. Our application to the NCREIF database reveals that, in the case of institutional commercial real estate investment, constant-liquidity values tend to lead transaction-based and appraisal-based indices in time, and also to display greater volatility and cycle amplitude. The differences can be significant for strategic investment policy viewed from a mean-variance portfolio optimization perspective.     

Market Efficiency and Return Statistics: Evidence from Real Estate and Stock Markets Using a Present-Value Approach

This paper develops a methodology to identify asset price response to news in the framework of the Campbell–Shiller log-linear present-value equation. We further show that a slow price adjustment in real estate markets not only induces a high serial autocorrelation in excess returns, but also dampens the return volatility and the correlation with excess returns in other asset markets. Using Hong Kong real estate and stock market data, we find that the quarterly real estate price assimilates only about half the effect of market news, whereas the quarterly stock price incorporates the news fully. Our analysis identifies a cumulative price adjustment that recovers lost information in real estate returns due to market inefficiency and thereby restores the real estate return volatility and the correlation between real estate and stock markets.     

Measuring House Price Bubbles

Using data for six metropolitan housing markets in three countries, this article provides a comparison of methods used to measure house price bubbles. We use an asset pricing approach to identify bubble periods retrospectively and then compare those results with results produced by six other methods. We also apply the various methods recursively to assess their ability to identify bubbles as they form. In view of the complexity of the asset pricing approach, we conclude that a simple price–rent ratio measure is a reliable method both ex post and in real time. Our results have important policy implications because a reliable signal that a bubble is forming could be used to avoid further house price increases.     

Evaluating the Costs of Increased Lending in Low and Negative Growth Local Housing Markets

The literatures on default and the evaluation of low downpayment mortgage programs are extended by showing within an options pricing framework how differences in expected price appreciation trends across housing markets can influence default and, thereby, the cost of programs designed to increase mortgage liquidity. An equilibrium mortgage rate reflecting the risk premium required to compensate for expected default-related losses is endogenously determined within the model. Evaluating the entire process by which program losses arise strictly within a rigorous asset pricing framework has potentially important implications for policy evaluation, as the estimated present value of program losses in declining markets where expected default is high is quite sensitive to the choice of the discount rate. The implications of increased lending in low and negative price appreciation local markets are also investigated.     

Structural estimation of price adjustment costs in the European car market

This paper characterizes the price adjustment costs that are consistent with observed price dynamics in the European car market. We estimate a dynamic model of international multiproduct firms that set prices in different currencies while facing price adjustment costs. We find that large price adjustment costs are not needed to rationalize the substantial degree of price inertia we observe in the data. Intuitively, since GDP, wages and exchange rates exhibit such a large degree of autocorrelation, small adjustment costs can explain very persistent prices. Also, accounting for country-specific price sensitivity, wages, GDP and exchange rates, the price adjustment costs should differ substantially across producers and markets to match the data.     

Optimal Valuation of Claims on Noisy Real Assets: Theory and an Application

A theory for valuing claims on noisy real assets is developed and applied. Central to the theory is determination of the dynamics for the best estimate of real asset value. The dynamics of the value estimate are shown to differ from the dynamics of the true asset value only in the arrival rate of information. The rate of information arrival in the value estimate can be faster or slower than information arrival in the true asset value, which can lead to unexpected outcomes in the valuation and exercise of options on noisy real assets. The theory we develop is illustrated through an application. An imperfectly competitive market for real estate development is examined, in which agents compete over the timing of lead investment. Information spillover and free–rider incentives are shown to cause significant delay in lead investment. Delay together with a competitive response once lead investment has occurred explain observed patterns of development in gentrified urban land markets and multistage development projects.     

INPUT PRICE DISCRIMINATION WHEN BUYERS OPERATE IN MULTIPLE MARKETS*

This paper revisits third‐degree price discrimination when input buyers serve multiple product markets. Such circumstances are prevalent since buyers often use the same input to produce different outputs, and even homogenous outputs are routinely sold through different locations. The typical view is that price discrimination stifles efficiency (and welfare) by resulting in price concessions to less efficient firms. When buyers serve multiple markets, price discrimination leads to price breaks for firms in markets with lower demand. When lower demand markets also have less competition, price discrimination can provide welfare gains by shifting output to less competitive markets.     

The Bias of the RSR Estimator and the Accuracy of Some Alternatives

This paper analyzes the implications of cross-sectional heteroskedasticity in the repeat sales regression (RSR). RSR estimators are essentially geometric averages of individual asset returns because of the logarithmic transformation of price relatives. We show that the cross-sectional variance of asset returns affects the magnitude of the bias in the average return estimate for each period, while reducing the bias for the surrounding periods. It is not easy to use an approximation method to correct the bias problem. We suggest an unbiased maximum likelihood alternative to the RSR that directly estimates index returns, which we term MLRSR. The unbiased MLRSR estimators are analogous to the RSR estimators but are arithmetic averages of individual asset returns. Simulations show that these estimators are robust to time-varying cross-sectional variance and that the MLRSR may be more accurate than RSR and some alternative methods.     

Optimal Valuation of Noisy Real Assets

We study the optimal valuation of real assets when true asset values are unobservable. In our model, the observed value cointegrates with the unobserved true asset value to cause serial correlation in the time series of observed values. Autocorrelation as well as total variance in the observed value are used to calculate an efficient unbiased estimate of the true asset value (the time–filtered value). The optimal value estimate is shown to have three time–weighted terms: a deterministic forward value, a comparison of observed values with previously determined time–filtered values, and a convexity correction for incomplete information. The residual variance measures the precision of the value estimate, which can increase or decrease monotonically over time as well as display a linear or nonlinear time trend. We also show how to revise time–filtered estimates based on the arrival of new information. Our results relate to work on illiquid asset markets, including appraisal smoothing, tests of market efficiency, and the valuation of options on real assets.     

There is no place like home: Information asymmetries,local asset concentration,and portfolio returns

Using a unique setting with significant cross‐market information asymmetries and a large sample of individual commercial property holdings, we provide robust evidence showing that local information plays a significant role in the linkage between local asset concentrations and return outperformance. We further document a significant positive relation between local asset concentration and portfolio returns in markets where information asymmetry is most severe. Two novel identification strategies that exploit a local lender's ability to price the local investor's information advantage and exogenous variation in sales price disclosure laws across states confirm an information‐based effect that is distinct from risk‐based or behavioral explanations.     

Variation Across Price Segments and Locations: A Comprehensive Quantile Regression Analysis of the Sydney Housing Market

Standard house price indices measure average movements of average houses in average locations belonging to an average price segment and hence obscure spatial and cross‐sectional variation of price appreciation rates even within a single metropolitan area. This article combines penalized quantile regression techniques with the hedonic imputation approach to reveal such kind of variation. The method is applied to house transactions from Sydney between 2001 and 2014. The analysis finds significant variation across sub‐markets over time and in particular during the boom‐and‐bust cycle peaking in 2004. Appreciation rates were highest for suburban, low‐priced and lowest for inner‐city, high‐priced houses.     

Spatial Linkages in Returns and Volatilities among U.S. Regional Housing Markets

This article investigates spatial linkages in returns, idiosyncratic risks and volatilities across 19 U.S. regional housing markets. Using Case & Shiller housing price indices from 1995 through 2009, we find that interconnections across markets can be “wider” and “stronger” than would normally be expected. They are “wider” because, in addition to geographic closeness, economic proximity is also an important source of influence; they are “stronger” because of the significant contagion effects during the 2007–2009 subprime and financial crises. The increased comovement and interdependence, especially among more geographically diverse regions with similar economic conditions, may help explain the failure of geographic portfolio diversification strategies.     

Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the United States and the Netherlands

This article assesses the predictive power of variables that measure market tightness, such as seller's bargaining power and sale probabilities, on future home prices. Theoretical insights from a stylized search‐and‐matching model illustrate that such indicators can be associated with subsequent home price appreciation. The empirical analysis employs listings data on residential units offered for sale through a real estate broker in the Netherlands and for certain U.S. regions. Individual records are used to construct quarterly home price indices, an index that measures seller's bargaining power and (quality‐adjusted) home sale probabilities. Using conventional time‐series models we show that current sale probabilities and bargaining power can significantly reduce home price appreciation forecast errors and help to predict turning points in local area housing markets. The measures and approaches in this article help to demonstrate ways in which researchers and practitioners can leverage listings data to gain knowledge about the current and future state of the housing market.     

Tracing the source of liquidity for distressed housing markets

We show that profit-seeking institutional investors provide valuable liquidity and spur the recovery of distressed housing markets. Using a quasi-natural experiment wherein investors purchased prepackaged distressed home portfolios from government-sponsored enterprises, we find that transaction prices of properties located within 0.25 miles of bulk-sale properties increased by 1.4% more than homes located farther away. This positive price spillover effect helped reverse the discounts at which such properties were being sold prior to the bulk-sale event. The price spillover effect due to the bulk-sale event is greater for foreclosed homes (4.1%), homes similar to the bulk-sale homes (2.5%), and homes in highly distressed neighborhoods (7.0%). Our results highlight asset disposition through pooling and institutional participation as a potential market-driven channel for the recovery of distressed housing markets.     

Are USDA reports still news to changing crop markets?

This study investigates whether major USDA reports still provide important news to changing crop markets. The news component of each report, or market “surprise,” is measured as a difference between the USDA estimate and its private expectation in corn, soybeans, and wheat markets. Changes in the relevance of USDA information are assessed by examining changes in the magnitude of market surprises and shifts in the futures price reaction to these surprises, which isolates the impact of each report. The stable size of market surprises over time suggests that competition from alternative data sources has not reduced the news component of USDA crop reports. Increasing price reaction to most reports, including those facing competition from alternative information sources, suggests that value of public information may be enhanced in uncertain markets affected by structural changes.     

Do Low‐Price Guarantees Guarantee Low Prices? Evidence from Competition between Amazon and Big‐Box Stores

It has long been understood in theory that price‐match guarantees can be anticompetitive, but to date, scant empirical evidence is available outside of some narrow markets. This paper broadens the scope of empirical analysis, studying a wide range of products sold on a national online market. Using an algorithm that extracts data from charts, I obtain a novel source of data from online price trackers. I examine prices of goods sold on Amazon before and after two big‐box stores (Target and Best Buy) announced a guarantee to match Amazon's prices. Employing both difference‐in‐difference and regression‐discontinuity approaches, I robustly estimate a positive causal effect of six percentage points. The effect was heterogeneous, with larger price increases for initially lower‐priced items. My results support anticompetitive theories which predict price increases for Amazon, a firm that did not adopt the guarantee, and are consistent with plausible mechanisms for the heterogeneous impact.     

REAL OPTIONS VOLATILITY ESTIMATION WITH CORRELATED INPUTS

Real Options Analysis (ROA) provides a framework for valuing reactive and proactive managerial flexibility in investment decisions. Estimating the volatility parameter for a real options model is challenging because there are typically no historical returns for the underlying asset and no current market prices. A previously developed method of using simulation to estimate the volatility parameter for a real investment is demonstrated. The effects of serial price correlation and price-demand cross-correlation on volatility parameters developed with this method are explained. Finally, managerial implications of these findings are discussed.     

Do House Price Levels Anticipate Subsequent Price Changes within Metropolitan Areas?

This research examines the relationship between hedonically controlled housing price levels and subsequent changes in those prices across locations within MSAs. Are areas with a high price relative to an “imputed rent” paying for higher appreciation? In an efficient market (e.g., Gordon Growth Model), as fundamentals (impute rent) differ across locations and change over time, anticipation of these should generate a positive correlation between (residual) price levels and subsequent price changes. We undertake these tests in four different MSAs using a panel of repeat‐sale house price indices that have been scaled to price levels with the hedonic attributes of the house and ZIP code. In three markets we find that identical houses in higher priced ZIP codes subsequently appreciate faster. In one market we find that there is little statistical difference.     

The Substitutability of Real Estate Assets

This paper investigates the degree of substitutability between securitized real estate assets and real estate assets whose prices are appraisal-based. Given the insensitivity of unsecuritized asset's returns to the returns on stock market indices, equilibrium asset pricing models cannot be used to compare these two avenues of investment. Two assets are deemed substitutable if the information sets underlying unbiased, minimum error variance estimates of their pricing parameters are identical. The empirical evidence shows that the prices of the transactions-based assets—real estate investment trusts and the stock price index of the home building industry—follow a random walk while the prices of the appraisal-based assets—FRC/NCREIF indices—do not. The variance decompositions of the vector autoregressions also show that the level of economic activity helps predict the price indices of appraisal-based assets while the stock market index and the term structure of interest rates are better predictors of the prices of transactions-based assets     

房地产的虚拟性与宏观经济稳定

本文从虚拟经济的角度深入剖析了房地产的虚拟资产特性，指出房地产是一种虚拟资产．房地产这种虚拟资产的特性是其虚拟性介于普通商品和金融资产之间。文章同时指出．正是房地产的这种虚拟资产特性使其成为联系实体经济和虚拟经济的纽带。除了扰动作用以外，房地产更能起到稳定经济的作用。这表现在两个方面：一方面。与金融资产相比．房地产价格具有相对的稳定性．这使其成为商业银行发放贷款的重要的抵押品；另一方面，房地产价格的长期稳定增长对货币发行量的稳定增长有重要影响。可见，房地产的虚拟资产特性对于银行贷款和货币供给的稳定增长．从而对整个经济的稳定增长具有重要意义。