Risk and return in residential spatial markets: An empiric and theoretic model

The paper is concerned with price and rent fluctuations in predominantly owner-occupied residental real estate. It presents the owner-occupier household as a housing consumer as well as an investor. It conjectures that since risk and return are known to be positively related in financial markets, they might also be thus related in residential real estate markets. If that is so, neighborhoods that are known to yield high returns will be the ones less price and rent stable than low yielding ones.The Capital Asset Pricing Model is not helpful in explaining a possible risk/return relationship in housing markets. Its major assumption about portfolio diversification is contrary to the nature of owner-occupied residential real estate. An owner occupier household, by definition, holds one unit of the asset and acts simultaneously as an investor and consumer of housing. For the capital market investor, investment and consumption decisions are separable. Therefore, a new theoretical model of consumer choice is proposed. Tel-Aviv price and rent data during a volatile market period are used for testing the main risk/return conjecture as well as other related hypotheses stemming from the model. The findings lend support to the conjecture and shed light on possible spatial determinants of owners' risk.     

What Drives Housing Markets: Fundamentals or Bubbles?

This study applies the dynamic Gordon growth model which is in the circumstance of rational bubbles to decompose log price-rent ratio into three parts, i.e., rational bubbles, discounted expected future rent growth rates and discounted expected future returns. The latter two terms represent housing fundamentals. The magnitudes of the components of price-rent ratio’s variance are estimated to distinguish the relative impact of the three parts on housing prices. Using time series data from the housing markets in the four largest cities in China (1991:Q1–2011:Q1 for Shanghai, Guangzhou and Shenzhen; 1993:Q2–2011:Q1 for Beijing), this paper presents a number of empirical findings: (a) the variance of rational bubbles is much larger than the variance of price-rent ratio, and rational bubbles contribute more fluctuations directly to price-rent ratio than the expected returns or the expected rent growth rates do; (b) the covariance between rational bubbles and expected returns or expected rent growth rates is also large; (c) the positive covariance of rational bubbles and expected returns implies that high expected returns coexist with bubbles, which differs from previous findings that lower expected returns drive asset prices; (d) the negative covariance of rational bubbles and expected rent growth rates indicates that the larger the bubbles are, the lower the expected rent growth rates are; (e) the positive covariance of expected returns and expected rent growth rates reveals under-reaction of the housing markets to rents.     

The Dependency of Rent-to-Price Ratio on Appreciation Expectations: An Empirical Approach

Using two unique datasets from different neighborhoods in Houston, TX, which provide us data for houses with similar structure (or even same house), we test the standard model of housing values to determine how the formation of households’ expectations regarding price appreciations affects housing market prices. Using these datasets we are able to address previously encountered problems in the literature such as the lack of adjustment for quality differences, the connection between prices and rents for the different type of housing, and the spatial distribution of housing. We test whether consumer behavior leads to potentially unstable market conditions with price bubbles. Our results suggest that appreciation expectations are based on past price appreciation but at the same time they depend on the fundamental factors such as, locational and structural. These findings show a hybrid consumer behavior of rational and adaptive expectations. Finally, we show how these expectations could sometimes lead to unstable price levels.     

What Drives the Owner‐Occupied and Rental Housing Markets? Evidence from an Estimated DSGE Model

Most dynamic stochastic general equilibrium (DSGE) models with a housing market do not explicitly include a rental market and assume a tight mapping between house prices and rents over the business cycle. However, rents are much smoother than house prices in the data. We match this feature of the data by adding both an owner‐occupied housing market and a rental market in a standard DSGE model. The intertemporal preference shock accounts for more than half of the variation in house prices and contributes to residential investment fluctuations through the liquidity constraint, and nominal rigidity in rental contracts captures the variation in the price‐rent ratio.     

Understanding Housing Market Volatility

The Campbell–Shiller present value formula implies a factor structure for the price–rent ratio of housing market. Using a dynamic factor model, we decompose the price–rent ratios of 23 major housing markets into a national factor and independent local factors, and we link these factors to the economic fundamentals of the housing markets. We find that a large fraction of housing market volatility is local and that the national factor has become more important than local factors in driving housing market volatility since 1999, consistent with the findings in Del Negro and Otrok (2007). The local volatilities mostly are due to time variations of idiosyncratic housing market risk premia, not local growth. At the aggregate level, the growth and interest rate factors jointly account for less than half of the total variation in the price–rent ratio. The rest is due to the aggregate housing market risk premium and a pricing error. We find evidence that the pricing error is related to money illusion, especially at the onset of the recent housing market bubble. The rapid rise in housing prices prior to the 2008 financial crisis was accompanied by both a large increase in the pricing error and a large decrease in the housing market risk premium.     

The relationship between rents and prices of owner-occupied housing in Taiwan

This article analyzes the changes of equilibrium rent and equilibrium price of owner-occupied housing in Taiwan, and also computes the rent multiplier and its trend in the past ten years in Taiwan to show how the housing consumption and housing investment change. A hedonic rent equation and a hedonic housing price equation are built first. Then, we apply the Housing Survey Report data from 1979 to 1989, and employ ordinary-least squares method to estimate the two equations. Using estimated coefficients of the two equations, we compute the market rents for owner-occupied housing and the market prices for rental housing. Finally, the rent multipliers are calculated from the market rents and market prices. The article finds that (1) changes of housing prices in Taipei lead to price changes in Kaoshung, and the latter leads Taiwan province; (2) changes of rent are much smaller than the changes of housing price; and (3) housing prices in Taiwan increased drastically. We also find: (1) at the peak of the housing market cycle, the rent multiplier is extremely high; (2) the rent multiplier drops in the year after the peak year because the rent catches up; (3) the rent multiplier in Taipei is greater than that of Kaoshung, and the multiplier in Kaoshung is greater than that of Taiwan province; and (4) overall, the rent multiplier in Taiwan is much greater than that of the United States.     

Efficiency in housing markets: Which home buyers know how to discount?

We test for efficiency in the Swedish co-op market by examining the negative relationship between the sales price and the present value of future monthly payments or ‘rents’. If the co-op housing market is efficient, the present value of co-op rental payments due to underlying debt obligations of the cooperative should be fully reflected in the sales price. However, a one hundred kronor increase in the present value of future rents only leads to an approximately 75 kronor reduction in the sales price. These inefficiencies are larger at the lower end of the housing market and in poorer, less educated regions and appear to reflect both liquidity constraints and the existence of more ‘sophisticated’ buyers in higher educated areas. Overall, our findings suggest that there is some systematic failure to properly discount the future stream of rent payments relative to the up front sales price.     

A censored stochastic volatility approach to the estimation of price limit moves

A censored stochastic volatility model is developed to reconstruct a return series censored by price limits, one popular form of market stabilization mechanisms. When price limits are reached, the observed prices are truncated and the equilibrium prices are unobservable, which makes further financial analyses difficult. The model offers theoretically sound estimates of censored returns and is demonstrated via simulations to outperform existing approaches with respect to the estimates of model parameters, unconditional means, and standard deviations. The algorithm is applied to model stock and futures returns and results are consistent with the simulation outcomes.     

Housing Price Dynamics in Time and Space: Predictability,Liquidity and Investor Returns

It is widely accepted that aggregate housing prices are predictable, but that excess returns to investors are precluded by the transactions costs of buying and selling property. We examine this issue using a unique data set—all private condominium transactions in Singapore during an eleven-year period. We model directly the price discovery process for individual dwellings. Our empirical results clearly reject a random walk in prices, supporting mean reversion in housing prices and diffusion of innovations over space. We find that, when house prices and aggregate returns are computed from models that erroneously assume a random walk and spatial independence, they are strongly autocorrelated. However, when they are calculated from the appropriate model, predictability in prices and in investment returns is completely absent. We show that this is due to the illiquid nature of housing transactions. We also conduct extensive simulations, over different time horizons and with different investment rules, testing whether better information on housing price dynamics leads to superior investment performance.     

中国一线城市房租形成机理和调控对策

房租是由房屋租赁市场的需求和供给两个方面决定的,而房屋租赁市场的需求和供给都受到房屋交易市场所形成的房价的影响。房价对房屋租赁市场需求的影响主要是由于房屋租赁市场和房屋交易市场的替代效应所导致,房价对房屋租赁市场供给的影响主要由房屋租售比和房价的上涨幅度决定。我国一线城市房价近十年的平均年上涨率为10%左右,这导致了我国一线城市的房屋租售比维持在极低的水平。随着房价的平稳,房租必然大幅上涨,故必须采取措施增加一线城市房屋租赁市场的供给,以供给量的大幅增加稳定房租。     

The Choice of Methodology for Computing Housing Price Indexes: Comparisons of Temporal Aggregation and Sample Definition

Housing transactions are executed and recorded daily, but are routinely pooled into longer time periods for the measurement and analysis of housing price trends. We utilize an unusually rich data set, covering essentially all arm's length housing sales in Sweden for a dozen years, in an attempt to understand the effect of temporal aggregation upon estimates of housing prices and their volatilities. This rich data set also provides a unique opportunity to compare the results using the conventional weighted repeat sales model (WRS) to those based on a research strategy which incorporates all available information on house sales. The results indicate the clear importance of temporal disaggregation in the estimation of housing prices and volatilities—regardless of the model employed.The appropriately disaggregated model is then used as a benchmark to compare estimates of the course of housing prices produced by the two models during the twelve year period 1981–1993. These results indicate that much of the difference between estimates of price movements can be attributed to the data limitations which are inherent in the repeat sales approach. The results, thus, suggest caution in the interpretation of government-produced price indices or those produced by private firms based on the repeated sales model.     

Findings from a Cross-Sectional Housing Risk-Factor Model

Housing data from the last 25 years show that returns to residential real estate in the U.S. can be volatile and vary significantly among locations. The variations in returns are driven by economically as well as geographically and psychologically motivated factors, but so far, no asset pricing model that adequately explains systematic risks in cross-sectional housing returns is widely accepted. This paper proposes an asset pricing model for housing returns that includes a market-wide return factor, an economically motivated factor derived from income growth, a geographically based factor derived from land supply elasticity and a momentum factor, which is psychological in nature. The model explains well the systematic risks in housing returns and is robust to different portfolio segmentations. Moreover, the model illustrates that local risk factors indirectly capture the risk previously attributed to market-wide price changes. While housing is not actively traded when compared to other financial assets, understanding the risk-factors that explain housing return in cross-section provides important insight for real estate investors, builders, real estate future traders, homeowners, banks and other mortgage lenders.     

Price Indices Based on the Hedonic Repeat-Sales Method: Application to the Housing Market

Shiller (1993) proposes the hedonic repeated-measures (HRM) approach to measuring constant quality price indices for heterogeneous assets such as some bonds and real estate. We derive a mathematical relationship between the coefficients of the HRM model and those from the standard repeat-sales model, and we demonstrate how hedonic characteristics should be chosen for inclusion in the HRM model. Empirical estimates using Fairfax, Virginia, housing transactions data show that the HRM price index evaluated at the mean of the hedonic variable is virtually identical to the standard repeat sales index, just as predicted by our mathematical relationship. But the HRM allows estimation of different price paths for heterogeneous assets. We demonstrate that use of assessed value as the only hedonic characteristic allows parsimonious HRM estimates.     

A general equilibrium model of housing consumption and investment

This article develops an applied general equilibrium model for analyzing the effects of tax policy on housing consumption and investment. The model incorporates housing tenure choice and consumption decisions in an explicit model of household portfolio choice that recognizes that the demand for owner-occupied housing depends on the after-tax returns from housing capital and other investments. Asset returns are stochastic so that asset holdings are determined by the desired risk-return relationships of households. Owner-occupied housing has a unique position because it has both a consumption role in providing housing services and an investment role. The model is then used to evaluate the effects of tax policy on the size and composition of the housing stock. Potential tax changes include a flat rate income tax and taxation of the imputed rent from owner-occupied housing.     

Valuing Homeownership

Housing tenure decision combines financial, economic and socio-psychological factors. This paper considers the global premium associated to homeownership. On the one hand, homeownership is associated to private benefits of being an owner. On the other hand, overinvestment in housing is harmful to diversification and distorts portfolio management. This trade-off, similar to the one associated to corporate private benefits of control, is the cornerstone of our theoretical model based on the expected utility maximization. The originality of the model comes from its simplicity. Furthermore, the empirical implementation of the model, using price and rent data normalized by square-meter, exhibits a homeownership premium for houses in the Brussels Region reaching at least 9% of the housing price. The findings are robust to several methodological refinements. In particular, they confirm the link between liquidity constraints and house prices documented in the literature. However, the premium may largely vary from one place to another, according to tax laws, cultural habits and social status associated to tenure.     

Hedging Housing Risk*

An unusually rich source of data on housing prices in Stockholm is used to analyze the investment implications of housing choices. This empirical analysis derives market-wide price and return series for housing investment during a 13-year period, and it also provides estimates of the individual-specific, idiosyncratic, variation in housing returns. Because the idiosyncratic component follows an autocorrelated process, the analysis of portfolio choice is dependent upon the holding period. We analyze the composition of household investment portfolios containing housing, common stocks, stocks in real estate holding companies, bonds, and t-bills. For short holding periods, the efficient portfolio contains essentially no housing. For longer periods, low-risk portfolios contain 15 to 50 percent housing. These results suggest that there are large potential gains from policies or institutions that would permit households to hedge their lumpy investments in housing. We estimate the potential value of hedges in reducing risk to households, yet yielding the same investment returns. The value is surprisingly large, especially to poorer homeowners.     

Selectivity,Quality Adjustment and Mean Reversion in the Measurement of House Values*

This paper develops a model of price formation in the housing market which accounts for the non-random selection of those dwellings sold on the market from the stock of existing houses. The model we develop also accounts for changes in the quality of dwellings themselves and tests for mean reversion in individual house prices. The model is applied to a unique body of data representing all dwellings sold in Sweden's largest metropolitan area during the period 1982–1999. The analysis compares house price indices that account for selectivity, quality change and mean reversion with the conventional repeat sales models used to describe the course of metropolitan housing prices. We find that the repeat sales method yields systematically large biased estimates of the value of the housing stock. Our comparison suggests that the more general approach to the estimation of housing prices or housing wealth yields substantially improved estimates of the course of housing prices and housing wealth.     

Housing Collateral, Consumption Insurance, and Risk Premia: An Empirical Perspective

In a model with housing collateral, the ratio of housing wealth to human wealth shifts the conditional distribution of asset prices and consumption growth. A decrease in house prices reduces the collateral value of housing, increases household exposure to idiosyncratic risk, and increases the conditional market price of risk. Using aggregate data for the United States, we find that a decrease in the ratio of housing wealth to human wealth predicts higher returns on stocks. Conditional on this ratio, the covariance of returns with aggregate risk factors explains 80% of the cross‐sectional variation in annual size and book‐to‐market portfolio returns.     

Robust portfolio optimization with a generalized expected utility model under ambiguity

This paper proposes a robust approach maximizing worst-case utility when both the distributions underlying the uncertain vector of returns are exactly unknown and the estimates of the structure of returns are unreliable. We introduce concave convex utility function measuring the utility of investors under model uncertainty and uncertainty structure describing the moments of returns and all possible distributions and show that the robust portfolio optimization problem corresponding to the uncertainty structure can be reformulated as a parametric quadratic programming problem, enabling to obtain explicit formula solutions, an efficient frontier and equilibrium price system. We would like to thank Prof. Zengjing Chen from School of Mathematics and System Sciences, Shandong University for helpful suggestions, and to thank the anonymous referee for valuable comments.     

Duration of Residence in the Rental Housing Market

This paper estimates a proportional hazard model of duration of residence in rental housing over 1987–1998 based on a unique dataset from the BLS-CPI housing sample together with American Housing Survey and other metropolitan economic data. The paper employs an innovative semi-parametric estimation approach for group duration analysis of the proportional hazard model. Results of the analysis indicate that the duration of residence in rental housing varies significantly across individual units and market segments, and is effected by tenant, dwelling, and market characteristics. An improved understanding of duration of residence offers new insights as regards fluctuations in tenant turnover, building occupancy, and rent flows, as well as new confidence in pro forma assumptions critical to rental housing development.