House Prices and Inflation

The present paper examines the long-run impact of inflation on homeowner equity by investigating the relationship between house prices and the prices of nonhousing goods and services, rather than return series and inflation rates as in previous empirical studies on the inflation hedging ability of real estate. There are two reasons for this methodological departure from prior practice: (1) while the total return on housing cannot be accurately measured, the total return on housing is fully reflected in housing prices, and (2) given that using returns or differencing a time series leads to a loss of long-run information contained in the series, valuable long-run information can be captured by using prices. Also, unlike previous related studies, we exclude housing costs from goods and services prices to avoid potential bias in estimating how inflation affects housing prices. Monthly data series are collected for existing and for new house prices as well as the consumer price index excluding housing costs for the period 1968–2000. Based on both autoregressive distributed lag (ARDL) models and recursive regressions, the empirical results yield estimated Fisher coefficients that are consistently greater than one over the sample period. Thus, we infer that house prices are a stable inflation hedge in the long run.     

Housing Tenure in a Model of Consumer Choice: A Simple Diagrammatic Analysis

The paper begins with a general model of demand for housing in an intertemporal utility maximization framework. Under standard assumptions the consumer is indifferent between owning and renting. Relaxation of various assumptions would explain tenure choice, but this is mathematically complex. As an alternative, a diagrammatic model of consumer choice over one period is presented which shows the effects of income, savings, housing and other prices, mortgage interest rates, rates of return on alternative investments, and tastes. Again under standard assumptions the consumer is indifferent about housing tenure. The effects on tenure choice of a change in the assumption about the availability of mortgage credit, rates of return on alternative investments and income taxes are demonstrated.     

Has the United States Overinvested in Housing?

Several economists have concluded that housing investment has been excessive relative to industrial investment in the U.S. Most blame provisions of the federal income tax that favor owner-occupied housing.
This paper poses the question within a two-sector neoclassical growth model which permits the social return to housing to differ from that to non-housing. The model is estimated using national income accounts and capital stock data from 1929 to 1983. The conclusion is that the return to housing capital is about half that to non-housing capital and that the housing stock should be about 75% of its 1983 volume.     

Rational Expectations, Market Fundamentals and Housing Price Volatility

This paper derives a forward-looking rational expectations house price model and empirically tests its ability to explain short-run fluctuations in real house prices. A novel approach to proxying the imputed rents of owner-occupied housing, as a function of observable housing market fundamentals, is combined with a housing market arbitrage relation to derive a present value model for real house prices. Tests of the rational expectations, nonlinear cross-equation restrictions reject the joint null hypothesis of rational expectations and the asset-based housing price model for quarterly, single-detached house prices in the city of Vancouver, British Columbia from 1979–1991. The model fails to fully capture observed house price dynamics in two real estate booms but tracks real house prices well in less volatile times, suggesting that prices may temporarily deviate from fundamental values in real estate price cycles.     

An Intertemporal Capital Asset Pricing Model with Owner‐Occupied Housing

This article studies portfolio choice and asset pricing in the presence of owner‐occupied housing in a continuous time framework. The unique feature of the model is that housing is a consumption good as well as a risky asset. Under general conditions, that is, when the utility function is not Cobb–Douglas and the covariance matrix is not block‐diagonal, the model shows that the market portfolio is not mean‐variance efficient, and the traditional capital asset pricing model fails. Nonetheless, a conditional linear factor pricing model holds with housing return and market portfolio return as two risk factors. The model also predicts that the nondurable consumption‐to‐housing ratio (ch) can forecast financial asset returns. The two factor pricing model conditioning on ch yields a good cross‐sectional fit for Fama–French 25 portfolios.     

物业管理问题浅析

物业管理是现阶段房地产发展的重要内容之一，本就现阶段物业问题产生的根源，物业标准物业立法等方面进行分析。     

Institutional Investment,Asset Illiquidity and Post‐Crash Housing Market Dynamics

We examine institutional investors’ entry into the equity side of the single‐family detached housing market using an asset illiquidity framework. We find that institutional investors purchased owner‐occupied houses after the real estate crisis for approximately 6.3–11.8% less than owner‐occupiers. The large discount was in addition to distressed sale and cash purchase discounts which, when combined, highlight the low liquidation value for owner‐occupied housing. The results suggest that asset illiquidity is an important cost of leverage in the owner‐occupied housing market.     

The Impact of Market Imperfections on Real Estate Returns and Optimal Investor Portfolios

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.     

Modeling Spatial Variation in Housing Prices: A Variable Interaction Approach

The absolute location of each real estate parcel in an urban housing market has a unique location-value signature. Accessibility indices, distant gradients and locational dummies cannot fully account for the influence of absolute location on the market price of housing because there are an indeterminable number of externalities (local and nonlocal) influencing a given property at a given location. Furthermore, the degree to which externalities affect real estate values is not only unique at each location but highly variable over space. Hence, absolute location must be viewed as interactive with other determinants of housing value. We present an interactive variables approach and test its ability to explain price variations in an urban residential housing market. The statistical evidence suggests that the value of location, as embodied in the selling price of housing units, may not be separable from other determinants of value. It is recommended that housing valuation models, therefore, be specified to allow site, structural and other independent attributes to interact with absolute location—{ x , y } coordinates—when accounting for intraurban variation in the market price of residential housing. This approach is especially useful when estimating the value of housing for geographic areas where very little is known a priori about the neighborhoods or submarkets.     

激活房地产市场对策研究

商品房空置率居高不下,一直是困扰我国房地产业健康发展的主要问题,文章针对房地产市场中存在的问题,提出了一些解决问题的建议。     

Are There Investor Clienteles in Rental Housing?

The possible existence of investor clientele groups has received little attention in the real estate finance literature. In this paper we develop a clientele model, which in equilibrium produces a clustering of investors by tax characteristics. Low-tax-bracket investors are concentrated in low-value rental housing that attracts rents which are high in relation to property values. On the other hand, only high-tax-bracket investors will be observed in high-value rental housing, and they charge rents that are low in relation to property values. An empirical model is specified and estimated using a cross section of investors in Australian private rental housing markets. Investor clienteles are detected among property investors, though there is a weak diversification effect indicating that clientele effects may be stronger among single property investors.     

Long‐Term Growth in Housing Prices and Stock Returns

A firm's long‐term stock returns are negatively related to past growth in housing prices in the state where the firm is located. The housing price effect is persistent and robust to controlling for the long‐term stock return reversal effect, changes in mortgage interest rates across the states, cyclicality in housing prices and overall local economic conditions. There is no evidence that extant asset pricing models can adequately explain the effect. The study discusses potential explanations for, and the implications of, the cross‐regional housing price effect.     

An Evaluation of Hedonic Price Indexes for Thirty-four Large SMSAs

The purpose of this paper is twofold. First, a set of price indexes are developed for thirty-four metropolitan areas for the years 1975 and 1978. Indexes are also broken down by central city and suburb for twenty two of the metropolitan areas. These indexes measure variation in the price per unit of owner-occupied housing stock and the price per unit of housing services of rental housing. Confidence intervals are constructed for the price indexes. It is found that the indexes are reasonably precise measures in that the typical ratio of the confidence interval to the predicted median rent or value is about 13%. Also, analysis of the confidence intervals indicates substantial and statistically significant variation in the price of housing stock and services among the metropolitan areas studied. One of the major benefits of this set of indexes is that it can be used to address one of the most important questions in real estate — Why do housing prices and rents vary among metropolitan areas and over time? Research projects are currently underway that use the data to address these two questions.     

Rent Controls in Ontario: Roofs or Ceilings?

This paper describes the rent control program in Ontario and discusses the consequences of these controls. It indicates that rent controls caused both a small nominal decline and a large real decline in the per unit value of rental apartments, substantially reduced new rental housing starts, generated a rental housing shortage, created a dual market with significant rent differences between the controlled and uncontrolled (new construction) sectors, and imposed large costs on government in the form of foregone tax revenues and increased rental housing subsidies. The paper also indicates some of the political responses to the developing economic effects, such as the imposition of additional land use controls and increased government spending programs to stimulate new rental construction.     

Real Estate Returns and Risk with Heterogeneous Investors

This article develops a theoretical framework and formulates a unified risk metric that integrates both real estate price risk and uncertainty of time on market (TOM). We demonstrate that real estate sellers with different degrees of financial distress face not only different marketing period risks, but also receive different return distributions upon successful sales. The major findings of this article can be summarized as follows. First, we show that real estate return and risk, which account for both price and TOM risk, are investor specific, varying over investors with different financial circumstances and holding periods. Second, the traditional valuation of real estate return and risk, which is based solely on the return distribution of a successful sale without considering the uncertainty of TOM and the investor's financial circumstances, underestimates real estate risk and exaggerates real estate return. Third, our empirical applications in both residential and commercial real estate markets show that the Sharpe ratio estimated by the traditional approach is seriously overstated—to the largest extent for investors with high financial distress. In addition, we find that, given the typical 5‐ to 7‐year holding period for real estate, the Sharpe ratios estimated by integrating both price and TOM risk are much in line with the performance of financial assets. These findings can help to explain the apparent “risk‐premium puzzle” in real estate.     

Risk and Return in the U.S. Housing Market: A Cross-Sectional Asset-Pricing Approach

This article carries out an asset-pricing analysis of the U.S. metropolitan housing market. We use ZIP code–level housing data to study the cross-sectional role of volatility, price level, stock market risk and idiosyncratic volatility in explaining housing returns. While the related literature tends to focus on the dynamic role of volatility and housing returns within submarkets over time, our risk–return analysis is cross-sectional and covers the national U.S. metropolitan housing market. The study provides a number of important findings on the asset-pricing features of the U.S. housing market. Specifically, we find (i) a positive relation between housing returns and volatility, with returns rising by 2.48% annually for a 10% rise in volatility, (ii) a positive but diminishing price effect on returns and (iii) that stock market risk is priced directionally in the housing market. Our results on the return-volatility-price relation are robust to (i) metropolitan statistical area clustering effects and (ii) differences in socioeconomic characteristics among submarkets related to income, employment rate, managerial employment, owner-occupied housing, gross rent and population density.     

Another Take on Real Estate's Role in Mixed‐Asset Portfolio Allocations

This article examines real estate's role in institutional mixed‐asset portfolios using both private‐ and public‐real estate indices, as a means of examining varying real estate‐related risk/return opportunities. In so doing, this article also examines the effects of: (1) increasing the investment horizon, (2) placing constraints on the maximum allocation to any one asset class, and (3) varying the risk preferences of investors. The empirical results suggest—using infinite‐horizon returns and all of the caveats that accompany such a perspective—that real estate allocations of approximately 10–15% of the mixed‐asset portfolio represent an upper bound for most investors. For those investors preferring low‐risk portfolios, (unlevered) private real estate is the vehicle serving this allocation preference; for those investors preferring high‐risk portfolios, public real estate (with its embedded leverage of 40–50%) is the vehicle serving this allocation preference—with such vehicles serving as substitutes for a variety of noncore real estate strategies. In some sense, the distinction between private and public real estate is more about the use of leverage. For those investors preferring moderate‐risk portfolios, an intermediate‐leverage approach seems optimal.     

Public Versus Private Real Estate Equities: A More Refined, Long-Term Comparison

In this article we compare public and private real estate equities. In so doing, we control for three of the main differences between these investment alternatives: property-type mix, leverage and appraisal smoothing. With these two restated indices, we then run tests to determine in a statistical sense whether the restated means and volatilities of the two series were different from one another. The clear answer is that they were not. The results of the statistical tests combined with the fact that the average difference between the two (restated) return series has substantially narrowed (to approximately 60 basis points) in the more recent (1993–2001) period jointly suggest a seamless real estate market in which public- and private-market vehicles display a long-run synchronicity. This has important implications for portfolio management. First, public- and private-market vehicles ought to be viewed as offering investors a risk/return continuum of real estate investment opportunities. Second, while the "platform" did not matter in terms of observed return characteristics, the platform may matter with regard to liquidity, governance, transparency, control, executive compensation and so forth; an apparent clientele effect hints at these issues being valued differently by large and small investors.     

Another Look at Tenure Choice, Inflation, and Taxes

The purpose of this paper is to explore the impact of inflation on the demand for housing. The first part of the paper presents a theoretical model that identifies the effects of inflation on the after-tax cost of housing and the choice between rental and owner-occupied housing. The second part discusses the results of a simulation model that measures the effect of inflation on the aggregate demand for housing, the aggregate homeownership rate, and the price of housing. The paper concludes that while inflation can be expected to increase the aggregate demand for housing and the price of housing relative to the general price level, inflation should ultimately lead to lower rates of homeownership. A corollary that is probably more relevant today is that lower inflation rates should reduce the real value of the housing stock and increase the homeownership rate. The paper also contains forecasts of the impact of the Tax Reform Act (TRA) of 1986 upon housing demand and the probability of homeownership for a variety of households.     

Real Estate in a Mixed‐Asset Portfolio: The Role of the Investment Horizon

In this article, three oft‐mentioned special characteristics of the real estate asset market—high transaction costs, marketing period risk and return predictability—are addressed in analyzing the role of U.K. commercial real estate investments in a mixed‐asset portfolio. Due to favorable horizon effects in risk and return, the allocation to real estate in a portfolio with stocks, bonds and cash increases strongly with the investment horizon. Examining the relative importance of return predictability, transaction costs and marketing period risk for the optimal allocation to real estate, the article finds that the consideration of return predictability is very important, except for short‐term horizons. Accounting for transaction costs is crucial for short‐ and medium‐term investors. Marketing period risk appears to be negligible. Traditional mean‐variance analysis—that is, ignoring return predictability, transaction costs and marketing period risk—can be very misleading.