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Homeownership: Boon and Bane

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this paper and John Ham, David Hendry and members of the econometrics group at the London School of Economics for their useful comments on an earlier draft
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The conventional wisdom that homeownership is very risky ignores the fact that the alternative, renting, is also risky. Owning a house provides a hedge against fluctuations in housing costs, but in turn introduces asset price risk. In a simple model of tenure choice with endogenous house prices, we show that the net risk of owning declines with a household's expected horizon in its house and with the correlation in housing costs in future locations. Empirically, we find that both house prices, relative to rents, and the probability of homeownership increase with net rent risk. © 2005 MIT Press
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Home ownership increases the incentive to maintain property and neighborhood, as well as decreasing the outflow of rents from low-income zones. However, these benefits are not costless to homeowners. With a mortgage comes the possibility of default, the financial demands of maintenance, a reduction in alternate investment opportunities, an increased exposure to fluctuations in local economic conditions, and a drastic reduction in the liquidity of personal wealth. Recently, policy makers have sought to increase mortgage lending in traditionally underserved markets. In this paper we consider the effects of this policy in light of the risk and return of housing and the current tax treatment of the home mortgage deduction. We find housing to be a relatively poor asset class in which to invest the bulk of family wealth. Trends in housing suggest that a large percentage of homeowners who bought and sold within a five year horizon in the United States over the last twenty years lost money on the investment. Lowering the equity required to purchase a home does little to alleviate the problem. We show that the current tax code - if anything - encourages renting over buying and gentrification of low income housing markets. If the government wishes to encourage home ownership among low income families despite the risks, then we argue that government agencies should share information about the risk and return of home ownership with its citizens. In addition, a direct subsidy through a tax credit may be both warranted and necessary to achieve the desired result.
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This article uses recent measures of the risk and return to investment in housing to estimate the effects of including a single family home in the investor portfolio. We estimate the expected return and standard deviation of that return, as well as its correlation with other major investment classes. Copyright 1993 by Kluwer Academic Publishers
This paper uses long-run equilibrium relationship between consumption and different components of wealth to estimate the effect of changes in housing wealth and financial wealth on consumption. By exploiting this long-run property, it has been shown that a dollar increase in housing wealth increases consumption by seven cents, whereas, a corresponding dollar increase in financial wealth increases consumption by only three cents. This difference in the wealth effect arises because transitory shocks dominate variation in financial wealth, whereas permanent shocks account for most of the variation in housing wealth. This paper also shows that the relative importance of permanent component for housing wealth has witnessed an increase over the last thirty years. Therefore, housing wealth effect has also increased over time.
This article investigates the portfolio choices of homeowners, taking into account the investment constraint introduced by Henderson and Ioannides (1983). This constraint requires housing investment by homeowners to be at least as large as housing consumption. It is shown that when the constraint is binding, the homeowner's optimal portfolio is inefficient in a mean- variance sense. Thus, portfolio inefficiency is not an indication that consumers are irrational or careless in their financial decisions. Instead, inefficiency can be seen as the result of a rational balancing of the consumption benefits and portfolio distortion associated with housing investment. Copyright 1997 by Kluwer Academic Publishers
Article
We have constructed a simple two-sector model of the demand for housing and corporate capital. An increase in the inflation rate, with and with- out an increase in the risk premium on equities, was then simulated with a number of model variants. The model and simulation experiments illustrate both the tax bias in favor of housing (its initial average real user cost was 3 percentage points less than that for corporate capital) and the manner in which inflation magnifies it (the difference rises to 5 percentage points without an exogenous increase in real house prices and 4 percentage points with an exogenous increase). The existence of a capital-market constraint offsets the increase in the bias against corporate capital, but it introduces a sharp, inefficient reallocation of housing from less wealthy, constrained households to wealthy households who do not have gains on mortgages and are not financially const rained. Widespread usage of innovative housing finance instruments would overcome this reallocation but at the expense of corporate capital. Only a reduction in inflation or in the taxation of income from business capital will solve the problem of inefficient allocation of capital. The simulation results are also able to provide an explanation for the failure of nominal interest rates to rise by a multiple of an increase in the inflation rate in a world with taxes. When the inflation rate alone was increased, the ratio of the increases in the risk-free and inflation rates was 1.32. An increase in the risk premium on equities, in conjunction with the increase in inflation, lowered the simulated ratio to 1.10, introduction of a supply price elasticity of 4 and an exogenous increase in the real house price reduced the ratio to 1.03, and incorporation of the credit-market. constraint reduced the ratio to 0.95.
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We examine the link between increases in housing wealth, financial wealth, and consumer spending. We rely upon a panel of 14 countries observed annually for various periods during the past 25 years and a panel of U.S. states observed quarterly during the 1980s and 1990s. We impute the aggregate value of owner-occupied housing, the value of financial assets, and measures of aggregate consumption for each of the geographic units over time. We estimate regression models in levels, first differences and in error-correction form, relating consumption to income and wealth measures. We find a statistically significant and rather large effect of housing wealth upon household consumption.
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This paper reviews the literature that describes the micro-level economic and social consequences of homeownership. We adopt an interdisciplinary approach and include studies from economics, sociology, geography, political science, psychology, and other disciplines. Our focus is on the set of consequences of homeownership in developed countries. Our list of potential outcomes of homeownership includes the impact on household wealth and portfolio choice, mobility, labor force participation, urban structure and segregation, home maintenance, political and social activities, health, demographics, self-esteem, and child outcomes. There is substantial evidence that homeownership has important effects on some household behaviors and outcomes. However, we find that much of the past 30-year's literature on consequences of homeowning is deficient from a theoretical or econometric perspective. We suggest solutions and identify research gaps present in the literature.
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This paper considers estimation and testing of vector autoregressio n coefficients in panel data, and applies the techniques to analyze the dynamic relationships between wages an d hours worked in two samples of American males. The model allows for nonstationary individual effects and is estimated by applying instrumental variables to the quasi-differenced autoregressive equations. The empirical results suggest the absence of lagged hours in the wage forecasting equation. The results also show that lagged hours is important in the hours equation. Copyright 1988 by The Econometric Society.