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.     

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     

房产

城市别墅全享价值,五期临河珍藏火热公开 距离徐家汇仅约20分钟车程的银都名墅,以近7成的土地面积建造江南园林景观。是一座城市中的森林公园。银都名墅专门挑选30年以上的成年桦树.种植在中国居住文化里象徵阖家兴旺的竹林。     

Commercial Real Estate Returns

In the commercial real estate market, which is perceived to be relatively inefficient, investors have comparative advantages; hence there are significant costs to diversification. This paper presents for the first time a series of market (or quasi-market) returns for a large data base. This data base is believed to be the most complete commercial real estate data base yet constructed. The paper empirically evaluates the benefits of diversification along various dimensions within the commercial real estate opportunity set. The analysis confirms certain aspects of prior work concerning inflation protection and diversification opportunities while concluding that even investment grade real estate investments are heterogeneous assets.     

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.     

A Note on Ranking Real Estate Research Journals

An understanding of how thirty real estate journals are perceived for promotion and tenure and for professional applicability was sought by surveying members of the two most important real estate academic organizations. Several subgroup comparisons were made revealing some common perceptions but a significant amount of disagreement as well. Among findings robust across the surveyed community were that the Journal of the American Real Estate and Urban Economics Association (changed to Real Estate Economics in 1995) is the most important outlet for promotion and tenure and the Appraisal Journal is the most important outlet for professional applicability. Two distinct journal groupings emerged: an academic group composed of eight journals and a professional group of twenty.     

Diversification Categories in Investment Real Estate

This paper continues previous work evaluating the benefits of diversification and analyzes the various dimensions within the commercial real estate opportunity set. The database is large and extends through the 1982 downturn in property values. Due to the low levels of systematic risk, current distinctions by region and property type make little sense in a world of costly diversification. More exacting categories combining property type, SMSA growth rate and lease maturity offer promise for more efficient diversification within the real estate portfolio.     

The Land Development Corporation: A System for Selling Rural Real Estate

This research illustrates ways in which rural real estate is converted into potential vacation home sites by large land development corporations. The individual and previously disorganized approach to selling property is replaced by an organized framework that is designed to create a demand for rural real estate.
Unfortunately, development is progressing without serious or adequate consideration being given to a number of specific problems. Developers and local governmental officials often fail to consider the environmental impact of these developments, the adequacy of service facilities being provided or the direct and indirect public costs associated with this type of developmental activity. Because of these shortcomings and others, serious questions arise concerning the desirability of this kind of developmental activity for rural areas.     

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.     

The Real Estate Pricing Puzzle

The state-of-the-art with respect to pricing real estate is similar to that with respect to pricing securities just prior to the development of the CAPM. Reading the entrails of real estate markets, however, has proven a formidable task, and the problem is not limited to inadequate data. Perhaps the most important lesson to date is that available pricing models are not up to the task.     

房地产投资的量度

根据天津市多年来房地产供求关系的有关资料,将最小二乘法和马尔可夫(Markov)预测法相结合,对天津市(城区)的房地产需求趋势进行了预测,并根据预测结果对未来的房地产需求情况进行了分析,经验证用这种数学模型预测出的结果与事实相符。     

Temporal Aggregation in Real Estate Return Indices

Temporal aggregation is defined as the use of spot valuations of properties occuring over an interval of time to impute the spot value of a property or of a real estate value index as of a single point in time. Temporal aggregation may characterize not only appraisal-based indices but also indices based directly on transaction prices, such as the National Real Estate Index (NREI) and regression-based indices such as hedonic or repeat-sales indices. This paper analyzes the effect of temporal aggregation on the smoothing of the time series second moments in the resulting real estate return index. Assuming true spot returns are uncorrelated, temporal aggregation-induced smoothing will cause the empirically observed real estate index to understate the own-variance by one-third and the beta by one-half. This amount of bias in the second moments can have major implications for the real estate share in an optimal portfolio. Thus, empirical-based investment analysis could be led astray by smoothing even if the real estate return index is "transaction-based" rather than "appraisal-based."     

对我国发展房地产投资信托的思考

我国房地产正出于飞速发展时期，巨大的投资需要造成了庞大的融资需求，而近来房地产信贷门槛的提高导致房地产融资成本提高。房地产行业迫切需要银行外的融资渠道，以解决开发和经营的资金问题。从房地产投资信托定义和基本原则入手，将房地产投资信托与其他融资方式进行比较，分析其优势，探讨其运营模式，并提出相关建议。     

Capital Structure Decisions in Real Estate Investment

This study examines the financing decisions of real estate investors and the choice of capital structure when acquiring income-producing properties. Drawing from the literature in finance and real estate, we develop a capital structure model for real estate investment and derive six hypotheses regarding the relationship of the overall loan-to-value ratio chosen by an investor to selected characteristics of the investment. The hypotheses are then tested using financing data from a sample of apartment and commercial transactions over a fifteen-year period in a specific real estate market. The empirical findings strongly support the importance of depreciation deductions, financial distress costs, capital constraints, tax rates, and interest rates as determinants of the capital structure of real estate investors.     

The 1989–92 Credit Crunch for Real Estate: A Retrospective

This study surveys a broad range of information to establish the degree to which real estate lending and construction activity decreased in the 1989–92 period owing to a "credit crunch." It reviews the conditions that led up to the contraction in mortgage lending and construction and then documents the extent to which the evidence is consistent with a credit crunch in lending for residential and nonresidential construction, permanent financing of income properties, and residential mortgage lending. Also, this study weighs the relative importance of the credit crunch and other factors that contributed to the falloff in real estate lending and contrasts the recent period with earlier credit crunch episodes.     

A Simple Search and Bargaining Model of Real Estate Markets

This paper examines the impact of brokers on buyers' and sellers' search behavior and on the transaction prices in real estate markets. It is shown that the seller and the buyer search less intensively if the house is listed with a broker. The seller gets a higher price when he employs a broker, but the increase in price is smaller than the commission fee. More specifically, the portion of the commission covered by the increase in price is directly related to the bargaining powers of the buyer and the seller. In the special case where the price is determined according to the Nash bargaining solution, the increase in price is shown to be half of the commission fee. It is also shown that an increase in the commission rate increases the equilibrium price but decreases the equilibrium search intensities.     

Clustering Methods for Real Estate Portfolios

A clustering algorithm is applied to effective rents for twenty-one metropolitan U.S. office markets, and to twenty-two metropolitan markets using vacancy data. It provides support for the conjecture that there exists a few major "families" of cities: including an oil and gas group and an industrial Northeast group. Unlike other clustering studies, we find strong evidence of bicoastal city associations among cities such as Boston and Los Angeles. We present a bootstrapping methodology for investigating the robustness of the clustering algorithm, and develop a means for testing the significance of city associations. While the analysis is limited to aggregate rent and vacancy data, the results provide a guideline for the further application of cluster analysis to other types of real estate and economic information.