Determinants of the Rate of Return for Nonresidential Real Estate: Inflation Expectations and Market Adjustment Lags

This paper analyzes the economic forces that determine the real rate of return for nonresidential real estate. Our analysis shows that the intermarket variation in the real rate of return is statistically significant, and the rate of return differs by land use and market area, as well as over time in response to changes in macro-economic conditions. We use inflation variables as surrogates for changes in macroeconomic conditions over time. In contrast to earlier studies, we find that nonresidential real estate may not outperform expected inflation. We believe that the impact of expected inflation (and other macroeconomic variables) on real estate rates of return depends upon the interaction of the macro-environment and specific local real estate market conditions. Finally, our empirical evidence suggests that the effects of a given shock dissipate rather quickly in most markets when we take into account locational and property use differences.     

Geographic Portfolio Allocations,Property Selection and Performance Attribution in Public and Private Real Estate Markets

This article examines the effects of geographic portfolio concentrations on the return performance of U.S. public real estate investment trusts versus private commercial real estate over the 1996–2013 time period. Adjusting private market returns for differences in geographic concentrations with public markets, we find that core private market performance falls. Using return performance attribution analysis, we find that the geographic allocation effect constitutes only a small portion of the total return difference between listed and private market returns, whereas individual property selection within geographic locations explains, in part, the documented outperformance of listed versus private real estate market returns.     

The Integration of Commercial Real Estate Markets and Stock Markets

This paper tests whether commercial real estate markets (both exchange-traded and non-exchange-traded) are integrated with stock markets using multifactor asset pricing models. The results support the hypothesis that the market for exchange-traded real estate companies, including REITs, is integrated with the market for exchange-traded (non-real-estate) stocks. Moreover, the degree of integration has significantly increased during the 1990s. However, when appraisal-based returns (adjusted for smoothing) are used to construct real estate portfolio returns, the results fail to support the integration hypothesis, although this may reflect the inability of these estimated private market returns to accurately proxy for commercial real estate returns. Interestingly, the growth rate in real per capita consumption is consistently priced in both commercial real estate markets and stock markets, whereas previous studies have found mixed evidence on the role of consumption in explaining ex ante stock returns.     

Estimating Returns on Commercial Real Estate: A New Methodology Using Latent-Variable Models

Despite their widespreao use as benchmarks of U.S. commercial real estate returns, indexes produced by the National Council of Real Estate Investment Fiduciaries (NCREIF) are subject to measurement problems that severely impair their ability to capture the true risk–return characteristics–especially volatility–of privately held commercial real estate. We utilize latent-variable statistical methods to estimate an alternative index of privately held (unsecuritized) commercial real estate returns. Latent-variable methods have been extensively applied in the behavioral sciences and, more recently, in finance and economics. Unlike factor analysis or other unconditional statistical approaches, latent variable models allow us to extract interpretable common information about unobserved private real estate returns using the information contained in various competing measures of returns that are measured with error. We find that our latent-variable real estate return series is approximately twice as volatile as the aggregate NCREIF total return index, but less than half as volatile as the NAREIT equity index. Overall, our results strongly support the use of latent-variable statistical models in the construction of return series for commercial real estate.     

Real Estate Returns and Risk with Heterogeneous Investors

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.     

Correlation Dynamics and Determinants in International Securitized Real Estate Markets

We find the correlation movements among eight developed securitized real estate markets and among their stock markets are quite synchronized over the period from 1995 through 2012. There is a high degree of correlation dependence with many of the realized correlation series subject to regime switching. Moreover, international correlations of public property returns could be significantly explained by five real estate variables that include global real estate securities market volatility, co‐existence of real estate investment trust (REIT) influence, underlying direct real estate return performance differential, real estate securities volatility differential and real estate securities market size differential after controlling for macroeconomic influence and stock market effect. The importance of the control and real estate variables in explaining the return correlations varies across the economies examined.     

U.S. Office Market Values During the Past Decade: How Distorted Have Appraisals Been?

The leading time series of real estate returns is the Russell-NCREIF (RN) Property Index. The RN series tracks returns, cash flow plus appraised capital gains, for multiple property types. To evaluate the accuracy of the capital-gains component of the office-market return series, this paper constructs two benchmark measures for the present value of projectable office-market cash flows from 1982 to 1991 and compares these with a real value series based on the RN capital-gain component. The RN-based series runs 30% above the highest of the benchmarks throughout the 1986–1989 period. While this overstatement is consistent with the development of a price bubble, failure of the bubble to burst until 1990–1991 is implausible. Real estate experts recognized overvaluation in assessments as early as the spring of 1986.
The RN Office-Market Index was slow to register price declines when the markets first weakened and then overstated the rate of decline once the market began to bottom out. This pattern likely reflects incentives for appraisers to smooth potentially temporary price volatility and for investment managers to maintain appraised values in declining markets. It traces as well as to systematic differences in the character and condition of the properties that lend to trade at different stages of the real estate cycle. These incentives and differences provide reason to believe that other RN indexes were similarly distorted.     

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.     

An Approach to Industrial Real Estate Market Segmentation and Valuation Using the Arbitrage Pricing Paradigm

This paper investigates whether a segmented market exists for industrial real estate with respect to risk and return characteristics. Given the existence of industrial market segmentation, the next issue examined is whether a submarket perspective or an integrated real estate market orientation provides better rate of return estimates for individual industrial properties using an Arbitrage Pricing Theory (APT) framework. The results support the existence of regional markets for industrial real estate. A submarket orientation rather than an integrated perspective is also found more appropriate in predicting returns on industrial real estate.     

Integrating Research on Markets for Space and Capital†

This article discusses the importance of recognizing that there are two distinct but interrelated real estate markets: the market for tenant space and the market for investment capital. The use decision is made in the space market whereas the investment decision is made in the capital market. The article points out that past research has tended to focus on a separate analysis of each of these two markets. That is, research historically has focused on understanding how changes in supply and demand affect equilibrium in either the space market or the capital market as if each market was autonomous. A graphical framework is illustrated that can be used to examine the effect of an exogenous shock to market equilibrium from either the market for space or the market for capital.     

Returns and Information Transmission Dynamics in Public and Private Real Estate Markets

This paper examines U.S. public and private commercial real estate returns at the aggregate level and by the four major property types over the 1994–2012 time period. Returns are carefully adjusted for differences between public and private markets in financial leverage, property type focus and management fees. Unconditionally, we find that passive portfolios of unlevered core real estate investment trusts (REITs) outperformed their private market benchmark by 49 basis points (annualized) over the 1994–2012 sample period. Our baseline vector autoregression results suggest that REIT returns do not embed additional commercial real‐estate‐specific information useful in predicting private market returns. These results strongly suggest that equity REIT returns react to fundamental (latent) asset pricing information more quickly than private market returns given their greater liquidity and price revelation. REITs therefore serve as a fundamental information transmission channel to private market returns when asset pricing variables are omitted.     

A Different Look at Commercial Real Estate Returns

Commercial real estate makes up a relatively small percentage of most institutional portfolios, even though the existing literature has consistently reported attractive risk-return characteristics that would suggest much larger allocations. This discrepancy has been explained by a perceived lack of comparability between return series calculated for real estate and those calculated for other asset classes. Just as investors actively involved in the futures markets do not consider individual common stocks to be traded continuously, those active in the stock market do not consider real estate to be traded continuously. In both cases, adjustments to reported returns are necessary to achieve a degree of comparability. This study makes such adjustments, using sales data from properties that help comprise the National Council of Real Estate Investment Fiduciaries / Frank Russell Company (NCREIF/FRC) Index to generate a "transaction-driven" commercial real estate return series. Examination of the risk-return characteristics of this series shows that it is quite different from traditionally reported real estate return series and far more consistent with risk-return characteristics that have been reported for other asset classes.     

The Markets for Real Estate Assets and Space: A Conceptual Framework

In this study, we present a simple analytic framework that divides the real estate market into two markets: the market for real estate space and the market for real estate assets. After describing the size and character of flows and stocks in the U.S. real estate market, we use our framework to demonstrate the important connections between the space and asset markets. We illustrate how these real estate markets are affected by the nation's macroeconomy and financial markets, tracing out the impacts resulting from various exogenous shocks on rents, asset prices, construction and the stock of real estate.     

Workouts, Deep Pockets, and Fire Sales: An Analysis of Distressed Real Estate

This paper presents a conceptual analysis of issues that relate to the management of distressed real estate assets. The paper examines the decision implications of the major characteristics of real estate assets and real estate markets in the light of information and incentive problems that emerge when assets fail to perform as anticipated. The paper focuses on the determination of commitments of additional resources to a troubled property, the identification of efficient holders of distressed assets, and the consideration of policies toward the disposition of distressed assets. The paper concludes that in many instances asset sales, rather than causing further destabilization as suggested by the fire sale image, are likely to contribute to reducing the costs associated with distress.     

International Real Estate Returns: A Multifactor, Multicountry Approach

We examine the risk and return characteristics of publicly traded real estate companies from 14 countries over the period 1990 to 2001. Our data are monthly country-level commercial real estate indexes constructed by the European Public Real Estate Association (EPRA). We find substantial variation in mean real estate returns and standard deviations across countries. Using various global- and country-level factor models, we find that there is evidence of a strong global market risk component, measured relative to the Morgan Stanley Capital International world index, in most countries. However, even after controlling for the effects of global market risk, an orthogonalized country-specific market risk factor is highly significant, especially for real estate indexes in Asia–Pacific markets. We find that a country-specific value risk factor has some explanatory power in addition to the country-specific market factor, but U.S.-based market, value and size risk factors do not provide any additional explanatory power. These findings imply that the international diversification opportunities with real estate companies are more complex than previously thought.     

On the Value of Environmental Certification in the Commercial Real Estate Market

A significant part of the global carbon externality stems from the real estate sector. Environmental certification is often hailed as an effective means to resolve the information asymmetry that may prevent markets from effectively pricing the energy performance of buildings. This study analyzes the adoption and financial outcomes of environmentally certified commercial real estate over time. We document that nearly 40% of space in the 30 largest U.S. commercial real estate markets holds some kind of environmental certification in 2014, as compared to less than 5% in 2005. Tracking the rental growth of 26,212 office buildings, we measure the performance of environmentally certified real estate over time. We document that certified office buildings, on average, have slightly higher rental, occupancy and pricing levels, but do not outperform non‐certified buildings in rental growth over the 2004–2013 period. Further performance attribution analysis indicates that local climate conditions, local energy prices and the extent of certification lead to significant heterogeneity in market pricing. On aggregate, these findings provide some evidence on the efficiency of the market in the adoption and capitalization of environmental characteristics in the commercial real estate market.     

Price Signaling and Return Chasing: International Evidence from Maturing REIT Markets

This article examines the liquidity of international real estate securities across 10 markets over the period 1990–2015. We apply and compare results for four different measures of liquidity, and find that while liquidity has increased consistently, wide variations still exist across markets, with the United States and Japan in the lead. Our results also suggest that the introduction of local REIT regimes did not have any pervasive effects on stock liquidity. When we study the relationship between liquidity and returns, we document new and consistent evidence for international return chasing behavior, whose pattern is a function of local market efficiency, listed real estate market maturity and stock ownership dispersion. The introduction of REIT regimes seems to weaken the importance of extra performance over and above general equity returns as investors tend to allocate funds to real estate securities within real estate rather than equity portfolios.     

Return Risk and Cash Flow Risk with Long-term Riskless Leases in Commercial Real Estate

This paper presents a conceptual analysis of some of the key fundamentals that underlie the risk characteristics of commercial real estate returns. In particular, the relationship between the property's return risk and its cash flow risk is explored. This relationship is important because it is the return risk that should matter most to investors, yet it is the cash flow risk or market risk about which we may have the most objective information and the most intuition. This is because real estate assets are generally unsecuritized and trade too infrequently to observe time series of returns (including appreciation) that could be used to directly study the risk characteristics of the returns. By explicitly incorporating the possibility of cash flows governed by riskless long-term leases, this paper also explores the relationship between lease term and both cash flow risk and return risk.     

Economic Depreciation of Residential Real Estate: Microlevel Space and Time Analysis

Three elements in the study of real estate depreciation that warrant further consideration are uncovered: the spatial variation of depreciation on a micro scale, the variability of depreciation within a single market across time and the recognition of land value as an influence in modeling real property prices. Taken together, these three dimensions provide an opportunity to further expand the understanding of residential economic depreciation while enhancing the predictive power of real estate market models. The analytical results, utilizing a land-value-adjusted hedonic model, indicate that both the intramarket location and the year in which the property sold have significant impacts on the observed rate of economic depreciation. Such information is vitally important to policymakers and others interested in accurate modeling of real estate markets.     

Transactions-Driven Commercial Real Estate Returns: The Panacea to Asset Allocation Models?

A transactions-driven commercial real estate return series is generated in this study to determine whether the reliance on appraised values in the estimation of real estate returns is the source of the reported underpricing of real estate relative to stocks, bonds, and bills when analyzed in a traditional mean-variance setting. The reported underpricing of commercial real estate would be rational if transactions-driven returns exhibit more variance than appraisal-driven returns. While we find that transactions-driven real estate returns have greater variance than appraisal-driven returns for individual properties, most of the individual property risk is idiosyncratic and diversified away at the portfolio level. Real estate continues to be a dominate asset class in mean-variance allocation models even when represented with transactions-driven indices.¹