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Real Estate Price Indices and Price Dynamics: An Overview from an Investments Perspective
Abstract
This article reviews the state of the art in real estate price indexing and the state of knowledge about real estate price dynamics, with a focus on investment property, or income-generating commercial property. Investment properties form a large component of the national wealth and of capital markets and represent a major investment asset class. They are characterized by various types of heterogeneity, including among assets, markets, and data sources, making the study of real estate pricing uniquely challenging. Yet in recent decades, urban economists and econometricians have pioneered major new price indexing methodologies that, combined with new types of data sources, are shedding light on the nature of commercial property price dynamics, revealing both important commonalities and unique differences compared with equities and fixed-income securities pricing. Keywords: commercial property; real estate; price indexing; price dynamics; asset markets
... Real estate assets are traded in private deals, mostly between a single buyer and seller, resulting in a relatively long time to sell a property. Moreover, unique assets are traded infrequently and irregularly through time (Geltner, 2015). This makes liquidity in private real estate markets very different from liquidity in public securities markets, where, unlike for private assets, inventories, order flows and market makers play a role in market liquidity. ...
... They find a statistically significant positive relationship between lagged turnover and contemporaneous capital returns. Devaney et al. (2017) study determinants of variations in transaction activity for a set of 49 US MSA office markets in the period 2002-2015. Van Dijk et al. (2020 note that for the US market, liquidity movements tend to be stronger correlated across markets than price movements. Brounen et al. (2019) study the relation between liquidity and price returns in international listed real estate markets. ...
We examine co-movements in private commercial real estate index returns and market liquidity in the US (apartment, office, retail) and for eighteen global cities, using data from Real Capital Analytics over the period 2005–2018. Our measure of market liquidity is based on the difference between supply and demand price indexes. We document for all analyzed markets much stronger commonalities in changes in market liquidity compared to commonalities in real price index returns. We further provide empirical evidence that space markets are less integrated than capital markets by analyzing co-movements in net-operating-income and cap rate spreads (over similar maturity bond yields). In a theoretical simulation model, we show that the strong integration of capital markets compared to space markets, is in fact the reason why market liquidity co-moves so strongly compared to returns. Our results are of interest for large private real estate investors such as pension funds and other institutional investors who are interested in spreading risk. Our findings imply that fully diversified price return benefits may be difficult to obtain, because market liquidity may dry up in all markets simultaneously, which makes portfolio re-balancing more difficult and costly.
... Another drawback is that appraisers are implicitly backward looking: They produce valuations that fit with their experience; they extrapolate from past transactions. The implication of this backward focus is that indices will tend to lag behind true market developments-and this lag can be substantial (see Cole et al., 1986;Fisher et al., 2007;Geltner, 2015;Diewert and Shimizu, 2017;Silver, 2019). This becomes a particular problem when appraisal-based CPPIs are used to try and detect market turning points. ...
Commercial property price indices (CPPIs) are needed to monitor financial stability, guide investment decisions by firms, and improve national accounts. Due to a lack of suitable data, however, reliable CPPIs are often hard to construct. Here we survey the current state of the CPPI literature and assess the contribution of the recently published Eurostat CPPI report.
... Second, condominium development patterns were spatially concentrated and did not offer much insight for patterns across time and elevation. Commercial real estate was also removed because val- uations are largely dependent on net operating income and investment cycles (Geltner 2015). Figure 2 represents the range of elevations found in each of the selected municipalities and the unincorpo- rated portions of MDC. ...
This article provides a conceptual model for the pathways by which climate change could operate to impact geographies and property markets whose inferior or superior qualities for supporting the built environment are subject to a descriptive theory known as 'Climate Gentrification.' The article utilizes Miami-Dade County, Florida (MDC) as a case study to explore the market mechanisms that speak to the operations and processes inherent in the theory. This article tests the hypothesis that the rate of price appreciation of single-family properties in MDC is positively related to and correlated with incremental measures of higher elevation (the 'Elevation Hypothesis'). As a reflection of an increase in observed nuisance flooding and relative SLR, the second hypothesis is that the rates of price appreciation in lowest the elevation cohorts have not kept up with the rates of appreciation of higher elevation cohorts since approximately 2000 (the 'Nuisance Hypothesis'). The findings support a validation of both hypotheses and suggest the potential existence of consumer preferences that are based, in part, on perceptions of flood risk and/or observations of flooding. These preferences and perceptions are anticipated to be amplified by climate change in a manner that reinforces the proposition that climate change impacts will affect the marketability and valuation of property with varying degrees of environmental exposure and resilience functionality. Uncovering these empirical relationships is a critical first step for understanding the occurrence and parameters of Climate Gentrification.
We present a mixed frequency repeat sales model for commercial real estate, taking into account changes in net operating income between the date of buying and selling the property. Moreover, we relate monthly private market index asset returns to lags, up to one year, of daily (REIT) index returns. The underlying daily model enables us to interpolate the monthly private market index returns on a daily basis, and to predict the private market index asset returns going forward. The mixed frequency repeat sales model facilitates daily appraisal of commercial real estate portfolios. We apply the model on sale prices (all property types, and apartments only) in the period January 2006 up to July 2020. We find that the mixed frequency repeat sales model reduces one‐month‐ahead forecasts errors and index revisions, compared to a benchmark model without daily returns. This article is protected by copyright. All rights reserved
Commercial property price indices (CPPIs) should be based on market transaction prices. Yet in monitoring average price changes over time price data can be sparse and the properties transacted each period of a different quality-mix. Due to the heterogeneity of commercial property, CPPI measurement requires a quality-mix adjustment so that the prices of like properties are compared over time with like. An appealing way around this sparse data and quality-mix adjustment problem is to use price data on broadly the same properties over time and avoid transaction price data. Tax or investment appraisal data or market valuations of real estate investment trusts (REITs) are two commonly used alternatives. While convenient, both such series can seriously mislead macroprudential and macroeconomic-policy makers. In this overview paper we point to the deficiencies of these data sources, outline and argue for the use of hedonic methods of quality-mix adjustment that are designed to work with sparse transaction price data in thin heterogeneous commercial property markets.
The repeat sales model is commonly used to construct reliable house price indices in absence of individual characteristics of the real estate. Several adaptations of the original model by Bailey et al. (J Am Stat Assoc 58:933–942, 1963) are proposed in literature. They all have in common using a dummy variable approach for measuring price indices. In order to reduce the impact of transaction price noise on the estimates of price indices, Goetzmann (J Real Estate Finance Econ 5:5–53, 1992) used a random walk with drift process for the log price levels instead of the dummy variable approach. The model that is proposed in this article can be interpreted as a generalization of the Goetzmann methodology. We replace the random walk with drift model by a structural time series model, in particular by a local linear trend model in which both the level and the drift parameter can vary over time. An additional variable—the reciprocal of the time between sales—is included in the repeat sales model to deal with the effect of the time between sales on the estimated returns. This approach is robust can be applied in thin markets where relatively few selling prices are available. Contrary to the dummy variable approach, the structural time series model enables prediction of the price level based on preceding and subsequent information, implying that even for particular time periods where no observations are available an estimate of the price level can be provided. Conditional on the variance parameters, an estimate of the price level can be obtained by applying regression in the general linear model with a prior for the price level, generated by the local linear trend model. The variance parameters can be estimated by maximum likelihood. The model is applied to several subsets of selling prices in the Netherlands. Results are compared to standard repeat sales models, including the Goetzmann model.
This paper presents a hierarchical trend model (HTM) for selling prices of houses, addressing three main problems: the spatial and temporal dependence of selling prices and the dependency of price index changes on housing quality. In this model the general price trend, cluster-level price trends, and specific characteristics play a role. Every cluster, a combination of district and house type, has its own price development. The HTM is used for property valuation and for determining local price indices. Two applications are provided, one for the Breda region, and one for the Amsterdam region, lying respectively south and north in The Netherlands. For houses in these regions the accuracy of the valuation results are presented together with the price index results. Price indices based on the HTM are compared to a standard hedonic index and an index based on weighted median selling prices published by national brokerage organization. It is shown that, especially for small housing market segments the HTM produces price indices which are more accurate, detailed, and up-to-date.
This study examines the feasibility of constructing reliable commercial property price indices using property tax records.
We employ the Clapp and Giacotto (Journal of American Statistical Association, 87(418), 300–306, 1992) assessed-value method to estimate price indices for commercial properties in Florida. The estimated Florida commercial property
price index is compared to the Moody’s/REAL Commercial Property Price Index (CPPI) and to the transaction-based index (TBI)
produced at MIT. Our results are promising, suggesting that this widely-available data source can be used to produce commercial
property price indices for a variety of precise market locations and specific investor segments. A secondary but interesting
objective of this paper is to use our rich and comprehensive database to examine the price performance of two specific subsets
of properties in more detail. First, we narrow our range to focus on just the office sector for Florida. We compare price
movements for the Florida office sector with the comparable CPPI. Estimates produce very similar price movements providing
support to both methods. Second, we contrast the price performance of higher- and lower-valued properties and reject the hypothesis
that their periodic price index levels are equal. The mean price changes of Florida commercial properties assessed at 2.5 million, although not statistically
different. In particular, higher-valued properties had higher mean price changes relative to lower-valued properties during
periods of economic expansion. This economic difference represents an important contribution toward beginning to understand
the relative performance of smaller and investment-grade commercial properties.
For the first time in U.S. history we use a Census approach as opposed to an estimate to calculate the size of the U.S. real estate market. Like the Census, there will be some missed observations especially for difficult to classify property and some iconic government property. Land, parking lots and single-family home values are ignored in the values and numbers presented here. But we provide estimates of values at the summary level as of late 2009 and relate these to the concentrations observed by state. A few metropolitan markets and some interesting facts are provided as we slice the data into healthcare, hospitality, retail, multi-family, office and industrial and more. At least 11.5 trillion including owner occupied-property. If we eliminate the specialty property, it is closer to $9.5 trillion. These estimates suggest that inflation-adjusted commercial real estate is worth about the same now as 10 years ago. What is truly amazing is that for some property types, this is about half of replacement cost indicating a long road back before substantial construction occurs.
Purpose
This paper seeks to investigate the nature and magnitude of the distortion in appraisal land price information according to change in the market, with a special focus on the Government's Published Land Prices.
Design/methodology/approach
In Japan, there is an item of land price information, so‐called Koji‐Chika (PLPS: Published Land Price Information System), that is a survey of fair market value by the qualified appraisers. The valuation error of this land price information was analyzed using the following method. First, hedonic price indices were constructed based on both actual transaction prices and the Published Land Prices, they were then compared to detect possible distortions in the governmental price information. Also the possibility of structural change in the Japanese real estate markets was studied and its effect on price indices was considered. Analysis of the Tokyo metropolitan area in Japan took place between 1975 and 1999
Findings
Large and systematic discrepancies between actual transaction prices and the Published Land Prices were identified, which might suggest that there are serious problems in the governmental information system. It is believed that it is necessary to consider this issue in the context of the entire real estate appraisal system in Japan.
Research limitations/implications
Limitations stem from the nature of Japanese data. Future research will seek to look at values on an IPD index.
Originality/value
The land market in Tokyo experienced a so‐called Bubble economy, and the rapid rise and fall of the land price were generated for this period.
Do indexes of house prices behave differently depending on the estimation method? If so, to what extent? To address these questions, we use a unique dataset that we compiled from individual listings in a widely circulated real estate advertisementmagazine. The dataset contains more than 470,000 listings of housing prices between 1986 and 2008, including the period of the housing bubble and its burst.We find that there exists a substantial discrepancy in terms of turning points between hedonic and repeat sales indexes, even though the hedonic index is adjusted for structural changes and the repeat sales index is adjusted in theway Case and Shiller suggested. Specifically, the repeat sales measure signals turning points later than the hedonic measure: for example, the hedonic measure of condominium prices bottomed out at the beginning of 2002, while the corresponding repeat sales measure exhibits a reversal only in the spring of 2004. This discrepancy cannot be fully removed even if we adjust the repeat sales index for depreciation.
Although the correlation between the public and private market pricing of real estate has generated considerable research
effort, the methods utilized in previous studies have failed to capture the dynamic nature of this correlation. This paper
proposes a new statistical method to address this issue. This method, known as the dynamic conditional correlation GARCH model, enables us to study the dynamics of the correlation between the two markets over time and enrich our understanding of the
public and private market pricing of real assets. We find that the correlation between NAV returns and REIT returns is dynamic
for all REIT types and there is a strong degree of persistence in the series of correlation. Our Granger-causality tests show
that price discovery generally takes place in the securitized public market. However, we also find significant variations
across property types and individual firms within each type. Our results indicate that constructing an optimal portfolio requires
firm level analysis of causality and correlation between REIT returns and NAV returns.
KeywordsPrice discovery–REIT returns–NAV returns
Using 70,822 observations on housing prices from 1969 to 1991 from Fairfax County Virginia, this article demonstrates the substantial benefits obtained by modeling the spatial as well as the temporal dependence of the data. Specifically, the spatiotemporal autoregression with twelve variables reduced median absolute error by 37.35% relative to an indicator-based model with twenty-six variables. One-step ahead forecasts also document the improved performance of the proposed spatiotemporal model. In addition, the article illustrates techniques for rapidly computing the estimates and shows how to compute indices for any location.
We investigate whether the cap rate, that is, the rent-price ratio in commercial real estate incorporates information about future expected real estate returns and future growth in rents. Relying on transactions data spanning several years across fifty-three metropolitan areas in the U.S., we find that the cap rate captures fluctuations in expected returns for apartments, retail, as well as industrial properties. For offices, by contrast, the cap rate does not forecast returns even though adsditional evidence reveals that expected returns on offices are also time-varying. We link this varying success of the cap rate in forecastings commercial property returns to differences in the stochastic properties of their rental growth rates. The growth in office rents has a higher correlation with expected returns and is more volatile than for other property types. Taken together, these characteristics diminish the correlation between the cap rate and the future returns to offices.
The weighted repeat sales price index methodology recently reported in Case and Shiller [5][6] is applied to a dataset of over eight million loans bought by the Federal Home Loan Mortgage Corporation over the last twenty years. Regional price indices are reported and compared to indices from other sources. Statistical issues in the creation of the index, both technical and due to sample selectivity of the Freddie Mac dataset, are extensively discussed. It is found that the new index grows at a rate similar to other indices up until 1985, after which time it grows at a significantly higher rate. Copyright American Real Estate and Urban Economics Association.
Accurate measurement of the returns to real estate investment are essential to sound analysis. This paper improves upon the traditionally employed method-collecting comparable sales data. A dynamic model of real estate appraisal is developed in which agents have incomplete information, heterogeneous search costs, and varying expectations. Various types of simulation analysis of the model indicate it performs best in the sense that the return estimate converges to the true value faster than other simpler rules. Copyright American Real Estate and Urban Economics Association.
Real estate returns, measured unleveraged, have been between those of stocks and bonds over 1960-1982. Due to appraisal smoothing and imperfect marketability, one must be careful about directly comparing measured real estate returns with those on other assets. It is likely, however, that low correlations with stocks and bonds make real estate a diversification opportunity for traditional portfolio managers. In addition, the issue of how various assets are priced is addressed. While stocks are priced primarily on market or beta risk, and bonds are priced primarily on interest rate and default risk, the real estate pricing mechanism includes residual risk and non-risk factors such as taxes, marketability costs and information costs. Copyright American Real Estate and Urban Economics Association.
Indexes of commercial property prices face much scarcer transactions data than housing indexes, yet the advent of tradable derivatives on commercial property places a premium on both high frequency and accuracy of such indexes. The dilemma is that with scarce data a low-frequency return index (such as annual) is necessary to accumulate enough sales data in each period. This paper presents an approach to address this problem using a two-stage frequency conversion procedure, by first estimating lower-frequency indexes staggered in time, and then applying a generalized inverse estimator to convert from lower to higher frequency return series. The two-stage procedure can improve the accuracy of high-frequency indexes in scarce data environments. In this paper the method is demonstrated and analyzed by application to empirical commercial property repeat-sales data.
This chapter develops and estimates improved housing price indexes in the context of an explicit time-variable model and compares them with a number of other studies, estimated in the same context. Just as with a number of other studies, this involves controlling for housing quality via the hedonic price equation approach. Unlike other micro studies using mixed cross-section and time series data (i.e., using the explicit time-variable model), this improvement involves the separation of seasonal and trend-cycle components.
Financial economists have long been interested in the dual-market nature of real estate. Real estate is in a unique position among alternative asset classes in that an active market transacting commercial and residential real estate assets exists alongside public pricing and trading of real estate investment trusts (REITs) on the stock market. This chapter summarizes past research on how these two markets are connected and whether investors in REITs receive a return consistent with the direct real estate market. To investigate this issue, an analysis is conducted using multivariate cointegration techniques on a data set that includes the financial crisis of 2007-2008 and a carefully matched set of control variables. Researchers have previously used matched controls to address this issue. The findings suggest that REITs and the private real estate market adjust together toward a long-run equilibrium. Evidence also indicates that the financial markets lead movements in the real estate market
The idea of a pure-play property portfolio is simply to replicate the returns of a specified target real estate sector without any exposure to other sectors by taking an optimal mix of long and short positions in listed real estate securities, combined with bonds to de-lever the traded equity shares. The goal of this study was to explore the possibility of applying the pure portfolio methodology in Europe, similarly to the way it has been recently launched in the United States, by constructing various demonstration sets of country and sector indices for the major European real estate markets. We used data for the three-year period 2010-2012. We find that the pure-play methodology yields reasonable results for the European-wide office, retail, residential, industrial and multi-use indices. The all-sector country indices for the UK, France, Germany, Italy and Sweden seem to relatively accurately reflect the underlying economic trends in each country, while the Dutch index produced exaggerated negative results during the sample period. The performance of the computed Eurozone and Other-Europe indices are in line with reasonable expectations, among other things mirroring the events in the single currency area during 2011. A number of country-specific sector indices were also constructed. For the UK, office, retail, residential, industrial and multi-use indices were estimated. For France, office, retail and multi-use indices were computed. For Germany and Sweden office and residential sector indices were calculated. While the results for the majority of the country-specific sector indices seem reasonable and reliable, some of them suffer from high volatility or negative autocorrelation. In summary, this study suggests that the currently available data on European REITs and other real estate investment companies may well enable the construction of a number of sector, country, as well as country-specific sector indices for the key European real estate markets.
Every house is different. It is important that house price indexes take account of these quality differences. Hedonic methods which express house prices as a function of a vector of characteristics (such as number of bedrooms and bathrooms, land area and location) are particularly useful for this purpose. I consider here some developments in the hedonic methodology, as it is applied in a housing context, that have occurred in the last three decades. A number of hedonic house price indexes are now available. However, it is often difficult to see how these indexes relate to each other. For this reason I attempt to impose some structure on the literature by developing a taxonomy of hedonic indexes, and then show how existing indexes fit into this taxonomy. Also discussed are some promising areas for future research in the hedonic field. In particular, greater use needs to be made of spatial econometric and nonparametric methods to exploit the increased availability of geospatial data. The main criticisms of the hedonic approach are evaluated and compared with those of the repeat‐sales and stratified median methods. The overall conclusion is that the advantages of the hedonic approach outweigh its disadvantages.
This paper develops a “pseudo repeat sale” estimation sample construction procedure (ps-RS) to construct more reliable and less biased quality-controlled price indices for newly-constructed homes. The method may be useful wherever new housing development is of sufficiently large scale and homogeneous. Such circumstances characterize many emerging market countries, and here we apply the technique in China. We match two very similar new sales within a defined matching space. Here we test three versions of matching spaces – complex, phase, and building. We then regress the within-pair price differentials onto time dummies and the differentials in unit-specific physical attributes. Locational and community variations, as well as many unobservable or difficult to measure physical attribute variations, are cancelled out in the model, and thereby controlled for. The building-version ps-RS index does the best job in this regard because its within-pair differential is the smallest. We further introduce a “hedonic value” distance metric criterion so that one can deal flexibly with the trade-off between the within-pair “similarity” and the sample size. We explicate and demonstrate formal signal-to-noise oriented metrics of index quality, which can be superior to traditional standard errors based metrics, and we use the new metrics to compare index construction methodologies. The ps-RS approach addresses the problem of lack of repeat-sales data in emerging markets and newly constructed properties and the omitted variables problem in the hedonic method. It also addresses the traditional problems with the classical same-property repeat-sales model in terms of small sample sizes and sample selection bias.
ABSTRACT Two easily measured variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with market {3, size, leverage, book-to-market equity, and earnings-price ratios. Moreover, when the tests allow for variation in {3 that is unrelated to size, the relation between market {3 and average return is flat, even when {3 is the only explanatory variable. THE ASSET-PRICING MODEL OF Sharpe (1964), Lintner (1965), and Black (1972)
The nature of private commercial real estate markets presents difficulties for monitoring market performance. Assets are heterogeneous and spatially dispersed, trading is infrequent and there is no central marketplace in which prices and cash flows of properties can be easily observed. Appraisal based indices represent one response to these issues. However, these have been criticised on a number of grounds: that they may understate volatility, lag turning points and be affected by client influence issues. Thus, this paper reports econometrically derived transaction based indices of the UK commercial real estate market using Investment Property Databank (IPD) data, comparing them with published appraisal based indices. The method is similar to that presented by Fisher, Geltner, and Pollakowski (200713.
Fisher , J. ,
Geltner , D. and
Pollakowski , H. 2007. A quarterly transactions-based index of institutional real estate investment performance and movements in supply and demand. Journal of Real Estate Finance and Economics, 34: 5–33. [CrossRef]View all references) and used by Massachusett, Institute of Technology (MIT) on National Council of Real Estate Investment Fiduciaries (NCREIF) data, although it employs value rather than equal weighting. The results show stronger growth from the transaction based indices in the run up to the peak in the UK market in 2007. They also show that returns from these series are more volatile and less autocorrelated than their appraisal based counterparts, but, surprisingly, differences in turning points were not found. The conclusion then debates the applications and limitations these series have as measures of market performance.
This paper discusses a multiple-regression chain-index technique for the construction of an index of quality change, and illustrates its feasibility by reference to a price index for automobiles. The interaction of our quality index with the usual Laspeyre type price index is studied. It is demonstrated that the quality index suggested bears the same relationship to a constant-satisfaction index as does an ordinary price index, and that this index is an appropriate deflator for the CPI.
Based on an extensive sample of individual dwelling units, this article estimates the market value, or the implicit prices, of specific aspects of the bundles of residential services consumed by urban households. Quantitative estimates were obtained by regressing market price of owner- and renter-occupied dwelling units on measures of the qualitative and quantitative dimensions of the housing bundle. The measures of residential quality associated with individual dwelling units were obtained by using factor analysis to aggregate some 39 indexes of the quality of narrowly defined aspects of the dwelling units, structures, parcels, and micro-neighborhoods.The analysis indicates that the quality of the bundle of residential services has about as much effect on the price of housing as such objective aspects as the number of rooms, number of bathrooms, and lot size. The analysis also confirms the influence of neighborhood schools on the value of residential properties and indicates that rental properties in the ghetto may be systematically more expensive than those located outside of the ghetto.
This paper reviews the literature on price determination in the private and public real estate markets. In particular, it discusses the processes of appraisal smoothing in the private market and of price discovery between the public and the private markets. In real estate markets, the absence of good quality information on price, whether because of lack of trades or confidentiality, has led to the widespread use of appraisals for market tracking and as the basis for performance measurement. Appraisers have to make an optimum assessment of value, based on fundamental variables and market information, including transactions and a market-wide appraisal index. However, transaction prices are a noisy signal and it is the appraiser's role to extract the signal from the noise in an efficient manner. This involves a process of optimal combination of past and current information and leads to appraisal smoothing. Price discovery is the process by which the opinions of market participants about the value of an asset are combined together into a single statistic—its market price. A development of this basic concept is where two markets have a common component of value and the relevant price information is discovered first in one market and then transmitted to the second market. The process of price discovery is considered between the public and private real estate markets.
Conventional housing price index models assume interperiodparameter stability and typically employ either repeat sales or hedonic methodologies. This paper introduces a method of index construction that combines multiple sales observations with single sale transactions while permitting characteristics prices from hedonic regressions to vary over time. A test for interperiod parameter stability is provided. Each period's data are arranged by location and repeat sales are matched by rows. This construction allows greater use of sample information and acknowledges the unique contribution of repeat sales to the estimation process. It also produces intertemporal error correlations that can be beneficially exploited by the seemingly unrelated regressions (SUH) technique. The paper also demonstrates a significance test for error correlation and discusses the treatment of unequal numbers of observations among index periods.
Executive Summary. This study examines the sensitiv-ity of equity real estate investment trust (REIT) returns to returns on other asset classes, including real estate, using an estimation method that explicitly allows for variation over time in the sensitivities. The results show that the relationship between REIT returns and returns to bonds, small cap stocks, large cap stocks and unse-curitized real estate has changed over time. During the 1990s, REITs began to exhibit a direct link to real estate returns, indicating that REITs do provide portfolios with some exposure to the real estate asset class. The strength of this link, however, is cyclical in nature. The sensitivity of REIT returns to large cap stocks has declined through time. REIT returns exhibit a sensitivity to small cap returns that has a strong cyclical component, with the two becoming more closely linked in REIT market downturns.
We use a matching procedure to construct samples of private residential sales in Singapore for January 1995 to May 2010. Though the matching approach is similar to a repeat sales estimator in pairing each sale with the sale of a comparable property, sample sizes are much larger because the matched properties are not constrained to be identical in each period. An advantage of the matching procedure is that it makes it easy to characterize changes in the full distribution of quality-adjusted sales prices, rather than just the means. We find that the distribution of sales prices shifted much farther to the right at high prices than at lower prices for 1995–2010, and this pattern is particularly evident in the boom periods of 1996 and 2005–2007. The variance of the sale price distribution increased significantly during boom periods.
This chapter presents a time-series model for the selling prices of houses, called the hierarchical trend model. In The Netherlands, this model has been used to value approximately one million houses for property tax purposes without any significant problems. In the city of Amsterdam this model has been operational for more than ten years.
The appropriate functional form for a hedonic price equation cannot in general be specified on theoretical grounds. In this paper, a statistical procedure for the choice of functional form is proposed. A highly general functional form is specified that yields all other functional forms of interest as special cases. Likelihood ratio tests are used to test the appropriateness of alternative forms. The procedure is illustrated using cross section microdata for housing. For the case considered, the functional forms most commonly used in previous studies are strongly rejected.
The accurate measurement of housing and real estate prices is of real theoretical importance and is crucial to understanding the operation of the housing market. Two basic techniques - hedonic and repeat sales methods - for measuring and analyzing the structure of housing prices have been developed. This paper presents an explicit model for combining samples of single sales and multipule sales for the analysis of housing prices and the computation of more efficient price indices. The procedure is based upon an explicit error structure, incorporating a random walk in housing prices. It is also based upon robust generalized least-squares methods to improve the efficiency of estimation. The technique is illustrated using a unique sample of condominium sales during a 12-year period in downtown Los Angeles.
Combining data from several sources, we build a database of home values, the cost of housing structures, and residential land values for 46 large US metropolitan areas from 1984 to 2004. Our analysis of these new data reveal that since the mid-1980s residential land values have appreciated over a much wider range of cities than is commonly believed. And, since 1998, almost all large US cities have seen significant increases in real residential land prices. Averaging across the cities in our sample, by year-end 2004, the value of residential land accounted for about 50 percent of the total market value of housing, up from 32 percent in 1984. An implication of our results is that housing is much more land intensive than it used to be, meaning that the future course of home prices—the average rate of appreciation and volatility—is likely to be determined even more by demand factors than was the case even ten or twenty years ago.
Using a time-varying approach, this paper examines the dynamics of volatility
in the REIT sector. The results highlight the attractiveness and suitability of
using GARCH based approaches in the modeling of daily REIT volatility. The
paper examines the influencing factors on REIT volatility, documenting the
return and volatility linkages between REIT sub-sectors and also examines the
influence of other US equity series. The results contrast with previous studies
of monthly REIT volatility. Linkages within the REIT sector and with related
sectors such as value stocks are diminished, while the general influence of
market sentiment, coming through the large cap indices is enhanced. This would
indicate that on a daily basis general market sentiment plays a more
fundamental role than more intuitive relationships within the capital markets.
A model of the single-family housing market is proposed in which households that move are both buyers and sellers. Households move when a stochastic process leaves them dissatisifed with their current unit. Household buyers expend costly search effort to find a better house, while sellers hold two units until a buyer is found. The vacancy rate, fixed in the short run, determines the expected length of sale and search, which play a central role in the reservation prices of buyer and seller. Market prices, the result of bargaining, lie between these two. The model yields a strong theoretical relationship (inverse) between vacancy and prices, which with competitive supply explains the existence of longer-run "structural" vacancy. Copyright 1990 by University of Chicago Press.
We analyze a bias in transaction-based price indexes due to the presence of seller reservation prices. We develop a model in which the ratio of sellers' reservation prices to the market value affects trading volume and biases of observed transaction prices: when trading volume decreases (increases), index returns are estimated with an upward (downward) bias. We propose a new econometric procedure to mitigate the bias, and use simulations to demonstrate the effectiveness of the procedure. We construct a reserve-conditional unbiased index for the Los Angeles housing market, which substantially differs from a traditional repeat sale index. Copyright (c) 2006 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.
This paper introduces an improved procedure for estimating capital asset price indexes. We jointly estimate conventional hedonic and repeat sales models via maximum - likelihood procedures, thereby taking advantage of the unique features of the individual models and using all the data that are available. Our model captures depreciation within the repeat sales model and accounts for serial correlation in hedonic data. The improvement in precision obtained by estimating the joint model is illustrated by smaller standard errors and narrower interval estimates for the resulting price indexes. We also carry out a simulation experiment that shows estimation errors significantly smaller using the joint estimation technique than either of the individual models or the GLS estimator of Case and Quigley (1991). © 2000 by the President and Fellows of Harvard College and the Massachusetts Institute of Technolog
Several studies of housing price trends recommend combining statistical analysis to repeat sales of residential properties. Recently, price indices derived from these techniques have formed the basis for inferences about the "efficiency" of housing markets. This paper presents an improved methodology which combines inflation on repeat sales of unchanged properties, on repeat sales of improved properties, and on single sales, all in one joint estimation. Empirical evidence, based upon a rich sample of transactions on single family houses in a single neighborhood, indicates the clear advantages of the proposed methodology, at least in one typical application. Copyright 1991 by MIT Press.
Experiments were conducted to test the hypothesis that transaction price feedback may bias valuation judgment. Among participating appraisers, evidence of asymmetrical response was found. The group receiving transaction feedback indicating that current judgments were "too low" responded with judgments in subsequent, unrelated valuations that were significantly higher than the group that received no feedback. The response from "too high" feedback was in the expected direction (lower value judgments) but was not significant. Additionally, valuation dispersion of around 10% revealed in these experiments is consistent with studies of valuation variability and may reflect an upper bound of typical commercial appraisal dispersion. Copyright 2001 by the American Real Estate and Urban Economics Association.
Time periods are typically highly aggregated for repeat sales estimators because of the small number of observations available in some periods. We use a flexible Fourier expansion to account for time, which we treat as a continuous variable. Our estimator saves degrees of freedom and enables us to estimate the price index efficiently even for times with few sales. We present estimated price indexes for the City of Chicago, Cook County, and several suburbs. Copyright 2001 by the American Real Estate and Urban Economics Association.
This study examines the usefulness of time-varying parameter techniques for constructing reliable transaction-based commercial price indices for metropolitan areas. Time-varying parameter techniques allow the implicit prices of differing quality characteristics to vary intertemporally, overcoming the potential bias imposed by holding implicit prices fixed and simply interpreting time dummy variables as in a conventional hedonic approach. This paper empirically investigates three time-varying parameter methods (Chained, Laspeyres, and Paasche) and considers the potential for sample selection bias. Precision measures are constructed to examine the reliability of the respective indices. Copyright Blackwell Publishers Ltd 2001.
This paper examines the securitized (public) and unsecuritized (private) commercial property markets in the United States and the United Kingdom for evidence of price discovery. Appraisal-based returns are corrected for smoothing, without presupposing the true returns to be uncorrelated or unpredictable across time. Real Estate Investment Trusts (REITs) and property company returns are corrected for leverage. We find evidence that price discovery occurs in the securitized market structure in both countries, and that this price information does not fully transmit to the unsecuritized markets for a year or more. In Britain, the unsecuritized market appears to be more closely and immediately linked to the securitized market than is the case in the U.S. Copyright American Real Estate and Urban Economics Association.
This paper analyzes the risks and returns of different types of real estate-related firms traded on the New York and American stock exchanges (NYSE and AMEX). We examine the relation between real estate stock portfolio returns and returns on a standard appraisal-based index, and find that lagged values of traded real estate portfolio returns can predict returns on the appraisal-based index after controlling for persistence in the appraisal series. The stock market reflects information about real estate markets that is later imbedded in infrequent property appraisals. Additional analysis suggests that the differences in the return and risk characteristics across different types of traded real estate firms can be explained in part by appealing to real estate market fundamentals relating to the degree of dependence of the real estate firm upon rental cash flows from existing buildings. These findings highlight the heterogeneity of securitized real estate-related firms. Copyright American Real Estate and Urban Economics Association.
This paper compares housing price indices estimated using three models with several sets of property transaction data. The commonly used hedonic price model suffers from potential specification bias and inefficiency, while the weighted repeat-sales model presents potentially more serious bias and inefficiency problems. A hybrid model combining hedonic and repeat-sales equations avoids most of these sources of bias and inefficiency. This paper evaluates the performance of each type of model using a particularly rich local housing market database. The results, though ambiguous, appear to confirm the problems with the repeat sales model but suggest that systematic differences between repeat-transacting and single-transacting properties lead to bias in the hedonic and hybrid models as well. Copyright American Real Estate and Urban Economics Association.
This study investigates the consequences of several imperfections associated with real estate markets on pricing and optimal investor portfolios from a CAPM context. CAPM assumptions are relaxed to recognize illiquidity, the consumption and investment attributes of owner-occupied housing, and a mildly segmented market structure. The study finds that relaxing the CAPM assumptions lead to a separate pricing paradigm for financial assets, income-producing real estate and owner-occupied housing respectively, that a "dividend effect" arises for real estate as the result of illiquidity, and that illiquidity reduces the extent to which investors hold real estate in their portfolios. Copyright American Real Estate and Urban Economics Association.
This study investigates whether the composition of the market portfolio leads to different inferences on real estate performance. As a point of departure, this paper first explores whether the omission of assets in a market proxy leads to a biased measurement of investment performance. The study finds that ranking investment performance is not meaningless even though investment performance is inaccurately measured. Furthermore, the composition of the market proxy does not necessarily lead to different inferences on real estate investment performance although superior real estate investment performance arises from the omitted asset phenomenon and also from smoothing bias in general. Copyright American Real Estate and Urban Economics Association.
This paper estimates the systematic risk (or "beta") of unsecuritized investment grade commercial real estate, as represented by the FRC and PRISA indices of institutional real estate holdings. Systematic risk defined with respect to national consumption is compared to systematic risk defined with respect to the stock market. Also, the risk estimates are explicitly adjusted to account for "smoothing" in appraisal-based aggregate level returns data. The systematic risk of these real estate indices appears to be virtually zero with respect to the stock market, even after correcting for smoothing, but substantially positive with respect to national consumption. Copyright American Real Estate and Urban Economics Association.
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. Copyright American Real Estate and Urban Economics Association.
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. Copyright American Real Estate and Urban Economics Association.