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The Journal of Real Estate Finance and Economics

, Volume 47, Issue 4, pp 583–587 | Cite as

Introduction to the Special Issue

  • Wayne ArcherEmail author
  • David Ling
  • Andy Naranjo
Article
  • 695 Downloads

The papers in this special issue grew out of the 2012 session of the FSU/UF Symposium on Critical Issues in Real Estate, hosted at the University of Florida.1 The theme of the symposium was Commercial Real Estate Issues: Markets, Values and Risks. The papers that emerged added new facets to diverse spheres of research. The first three papers are related in that they all contribute to the body of work on commercial property indices. The remaining five papers span a rich variety of subjects, including the dynamics of retail property markets, the effect of information volatility on predictions by commercial property analysts, global IPO performance of REITS, the use and effect of listed prices in commercial real estate transactions, and the role of local market characteristics in commercial mortgage default patterns. Despite the range of subjects, these papers resulted in broad and lively discourse among the participants of the symposium. We trust that they will stir a lively interest for the reader as well.

Property price indices are widely recognized as important for real estate lenders, real estate equity investors, and even as indicators of national financial well-being. London, as one of the most important commercial property markets in the world has long had price indices for office property values. Yet there has not existed a transaction-based index of London office properties. Chegut, Eichholtz and Rodrigues, in “The London Commercial Property Price Index,” report efforts to construct the first such index. Using data on transactions from Estates Gazette Interactive and Real Capital Analytics, they explore various repeat-sales estimation strategies and noise filters to obtain a quarterly index. They find data can support the index running from first quarter of 1997 through fourth quarter of 2011. They test the series against IPD’s London capital valuation series and the MIT Center for Real Estate New York office market repeat sales index series. They find that their index leads the capital valuation series by a year, and clearly signals the financial crisis. Their series also indicates that the London market was affected by the financial crisis much earlier than was the New York market and that it has very low correlation with the New York market.

Commercial real estate indices play an important role in performance evaluation as well as the development and implementation of investment strategies. In their paper entitled, “On Indexing Commercial Real Estate Properties and Portfolios,” Walter I. Boudry, N. Edward Coulson, Jarl G. Kallberg and Crocker H. Liu examine the extent to which commercial real estate indices represent the returns on portfolios of commercial properties. They use a sample of 12,427 repeat sales transactions between the fourth quarter of 2000 and the second quarter of 2011 and find that the aggregate real estate indices (Moody’s REAL CPPI) do a good job of tracking real returns when portfolios of more than 20 properties are considered. At this level, tracking is somewhat less effective than the benchmark of the S&P500 and its component stocks. Compared to the average root mean squared deviation (RMSD) from one asset, randomly selected portfolios with 20 assets reduce the RMSD by 75 % for the S&P500 compared to 66 % for the aggregate index. Their results suggest that the real estate aggregate indices can be effective in hedging and evaluating the performance of direct real estate investment. They also find that tracking at the property type level provides little benefit over using an aggregate index. However, indexing using a property type and location matched index provides lower tracking error for any level of diversification.

Use of repeat sale house price indices in the single-family housing market, where there is typically substantial transaction volume and relative liquidity, has long been considered standard practice for the measurement of price appreciation in a given market. However, the extension of repeat sale methodologies to the measurement of price changes in commercial real estate markets is more recent. In “Transaction Frequency and Commercial Property,” Peter Chinloy, William Hardin, and Zhonghua Wu argue that well-known limitations of repeat sale methodologies may be especially problematic when applied to commercial properties. First, repeat sale methodologies assume that the characteristics of properties in the sample remain unchanged between sales. A commercial property, however, often becomes a repeat sale because the initial buyer had a preset investment strategy which impacted property selection. More specifically, the authors argue that “value-added” investors acquire properties that tend to need renovation, rehabilitation and re-tenanting. Implementation of the investment strategy necessitates identification of properties that would benefit from such activities, requires capital investment over and above the acquisition price, and involves a specific set of managerial skills. Measured price appreciation is likely to be overstated, on average, because it includes the effects of additional capital investment and managerial talent. Moreover, repeat sale measures discard the majority of the available, but often limited, transaction data. This is a costly discard for a market that is illiquid, especially after sorting for property type and location.

Chinloy, Hardin, and Wu posit that the empirical test for an endogenous investment strategy is whether samples composed of properties that frequently transact are taken from the same cohort as infrequently sold properties. The data for repeat sale indices come from the small sample of multiple transaction properties. However, most investors have a longer term investment horizon and the properties they acquire and hold are less likely to be a part of a repeat sale transaction pair. Using multifamily sales from Los Angeles and Chicago over the 1998 to 2011 period, the authors find that the vast majority of unique properties transact only once during the sample period. Properties associated with repeat sales account for just 31 % of unique properties in Los Angeles and 26 % in Chicago. The first sale of a repeat-sale pair in Los Angeles transacts at a statistically significant 4.2 % discount relative to properties selling only once, holding constant physical characteristics, submarket, location, and time of sale. The authors posit that the discount likely reflects unobservable property characteristics related to needed expenditures including renovation and tenant improvements. In contrast, the second sale is associated with a statistically significant 3 % premium relative to properties selling once. In Chicago, first sales of a repeat-sales pair transact at a 7 % discount compared with those selling once; second sales exhibit a 1 % premium over those selling once. Overall, Chinloy, Harding, and Wu conclude that commercial properties that sell frequently are not a random draw from the commercial property market; therefore, price appreciation metrics should not be limited to frequently traded assets.

In real estate markets, characterized by long and harsh cycles, dynamics are a prime concern. This problem is exacerbated by asymmetry since there is evidence to suggest that the dynamics of declining real estate markets differ from the dynamics of rising markets. Hendershott, Jennen and MacGregor, in “Modeling Space Market Dynamics: An Illustration Using Panel Data for US Retail” extend an established body of dynamic market research in two dimensions. First, they extend established techniques of analysis into the realm of retail space markets. Second, they achieve a regional perspective through the use of panel data. Using data provided by CBRE Econometric Advisors, they apply error correction models to a panel of MSA annual retail data spanning nearly three decades, through 2007. The MSAs used represent eleven of the largest retail markets. With models that track rent, vacancy rate and new supply as driven by market demand, they are able to distinguish two groups of retail markets in terms of long run equilibrium rent patterns, price elasticities and short term dynamic responses.

In “Who Says there is a High Consensus among Analysts when Market Uncertainty is High? Some New Evidence from the Commercial Real Estate Market,” James D. Shilling, C.F. Sirmans, and Barrett A. Slade seek to determine whether analyst consensus is a function of the level of price informativeness. Some research argues that a small or declining volume of trading implies less information and lower quality information, and that a lower level of price informativeness will lead analysts to put more weight on their private information at the time of forecasting. This paper contributes to this literature by arguing that when uncertainty is high, there might be a positive option value associated with waiting. In this case, one could conclude that analysts may lack consensus when uncertainty is high. To test this hypothesis, the authors use forecasts of market rent changes and expected returns on investment for office buildings from 2007Q1 to 2011Q2. In the out-of-sample forecast period, transaction volume and price informativeness plummeted as the demand for commercial office buildings dropped off. At the same time, analyst consensus is much lower than predicted from comparisons with a vector error correction model fitted to data before the advent of the financial crisis of 2007–2009. They also find that the level of consensus is much higher among public analysts as compared with private analysts between 2009Q2 and 2010Q2. The authors argue that these results can be rationalized on the basis that amid heavier trading in the public market (owing to greater liquidity and lower transaction costs) and lackluster trading in the private market consensus should be higher in the public market than in the private market.

Most studies of real estate investment trusts (REIT) IPOs have focused primarily on U.S. listed REITs. In contrast to industrial firm IPOs, these studies generally find that REIT IPOs in the U.S. exhibit an abnormally low initial-day return and mixed long-run performance. In their paper entitled, “Are REIT IPOs Unique? The Global Evidence,” Su Han Chan, Jiajin Chen, and Ko Wang take a global REIT approach to provide evidence on broader REIT IPO performance and to also gain further insights into the reported REIT IPO performance relative to industrial firms. Using a large sample of 370 REIT IPOs from four continents (14 different countries) during the 1996–2010 period, they find that REIT IPOs in other countries exhibit a similar initial-day return pattern as in U.S. REIT IPOs; the cause of the low initial-day return is consistent with the fund-like structure of REITs and the re-deployable assets (real estate) they hold; the slightly positive initial-day return is offset by the poor performance in the 190 days subsequent to the IPO; and the change in U.S. REIT IPO performance before and after 1990 is likely due to a change in REIT structures.

In “List Price Information in the Negotiation of Commercial Real Estate Transactions: Is Silence Golden?” Dean Gatzlaff and Peng Liu argue that property-, market-, and transaction-specific information are critical to the process of establishing buyer offer prices. However, it is also well known that cognitive reasoning and human behavior can influence the processing of this information and decision making outcomes. Consistent with the anchoring heuristic, a high list price relative to market value has been found to be positively associated with the negotiated transaction price in single-family housing markets. In contrast, unusually high (or low) list prices may serve as a signal that conveys information to potential buyers about the sellers’ motivations and/or atypical property features.

In contrast to housing markets, the use (or non-use) of list price information has not been addressed in commercial real estate markets. Moreover, unlike in the housing market, income-producing commercial properties are often offered for sale by owners without a list price. Given the possible strategic influence of anchoring and signaling, why sellers of commercial properties do not always use list price information to “anchor” a property’s value and/or convey information is a puzzle. This paper contributes to the literature by (1) examining the underlying determinants of the use of list prices and (2) evaluating the relationship between the use of list price information and subsequent transaction prices. The data used in this study come from the CoStar group. A complete set of property- and transaction-specific variables for each of the characteristics of interest, including the seller’s list price if used, is obtained by the authors for the January 2006 to December 2011 period.

Gatzlaff and Liu report that larger, more complex, and multi-tenant properties are less likely to be marketed with a list price. After controlling for property- and market-specific factors, the prices of properties sold that use list prices are, on average, lower than those sold without list prices. These price differences vary by price cohort and economic condition. The authors note that their findings do not imply that list prices cause transaction prices to be lower, but rather that their use is correlated with lower prices. The results support the notion that some sellers do not reveal list price information in order to maintain an information advantage and to avoid truncating higher than expected offers, especially during periods of growth or when marketing complex properties. In this environment, list prices may be effectively used to signal additional information (e.g., seller motivations) to the market. Thus, asymmetric information and signaling are argued to play a dominant role in explaining the sellers’ strategic non-use of list price information in the commercial property market.

Defaults on commercial property mortgage loans reached extremely high levels during the Great Recession, but the incidence of the defaults was uneven. The “usual factors” contributing to default turn out to be insufficient to explain the variation in commercial default experience across local markets. An, Deng, Nichols and Sanders, in “Local Traits and Securitized Commercial Mortgage Default,” extend research on commercial mortgage default in two respects: they present the first published systematic analysis of actual default experience among CMBS loans, and they account for local economic conditions as factors in loan defaults. Specifically, in addition to property type, option value, insolvency, macroeconomic conditions and other customary factors, they account for local house price changes, local commercial market conditions and local unemployment, all at the MSA level. Using a sample of 30,000 loans originated and securitized from 1998 to 2012, they confirm that the local economic factors contribute significantly in explaining defaults and have greater explanatory power than the standard factors alone. In particular, they derive significant explanatory power from local rental rate changes, absorption rates, vacancy rates, unemployment rates and house price appreciation. Further, they explore whether house price changes seem to have a direct “spillover” effect on commercial property defaults, or whether house price indices are more of a signal of economic conditions. They conclude that both lagged values of local house price indices and an index of commercial land values provide significant, independent signals of subsequent commercial property market conditions.

Footnotes

  1. 1.

    The FSU/UF Symposium on Critical Issues in Real Estate is cosponsored by the Kelley A. Bergstrom Center for Real Estate Studies at the University of Florida, The Center for Real Estate Education & Research at Florida State University and The DeVoe L. Moore Center at Florida State University.

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Warrington College of Business AdministrationUniversity of FloridaGainesvilleUSA

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