Tag Archives | Housing risk

Can Owning a Home Hedge the Risk of Moving?

Conventional wisdom holds that one of the riskiest aspects of owning a house is the uncertainty surrounding its sale price, especially if one moves to another housing market. However, households who sell a house typically buy another house, whose purchase price is also uncertain. We show that for such households, home owning often hedges their net exposure to housing market risk, because their sale price covaries positively with house prices in their likely new market. That expected covariance is much higher than previously recognized because there is considerable heterogeneity across city pairs in how much house prices covary and households tend to move between the highly correlated housing markets. Taking these two considerations into account increases the estimated median expected correlation in real house price growth across MSAs from 0.35 to 0.60. Moreover, we show that households’ decisions whether to own or rent are sensitive to this “moving-hedge” value. We find that the likelihood of home owning for a mobile household is more than one percentage point higher when the expected house price covariance rises by 38 percent (one standard deviation). This effect attenuates as a household’s probability of moving diminishes and thus the moving-hedge value declines.

Can Owning a Home Hedge the Risk of Moving? with Nicholas Souleles, American Economic Journal-Economic Policy vol 5, number 2 (May 2013), pp. 282-312 (PDF)

Timing the Housing Market

We create reliable measures of the cost of owning and the cost of renting that enable us to compare the level of rents and ownership costs across MSAs. We show that households can predict whether renting or owning will end up being less expensive ex post. This exercise is more robust than trying to predict house price changes or housing returns because much of that uncertainty is inframarginal in the optimal own/rent decision, which depends only on the which tenure mode is cheaper. We show that households can profitably time the home ownership decision. Using several simple trading rules, we estimate that households can save as much as 50 percent of annual rental costs over a five-year period by timing the decision of when to buy a home. The potential savings varies across cities.

Timing the Housing Market with Cindy Soo, Mimeo, March 30, 2013

House Price Moments in Boom-Bust Cycles

This paper describes six stylized patterns among housing markets in the United States that potential explanations of the housing boom and bust should seek to explain. First, individual housing markets in the U.S. experienced considerable heterogeneity in the amplitudes of their cycles. Second, the areas with the biggest boom-bust cycles in the 2000s also had the largest boom-busts in the 1980s and 1990s, with a few telling exceptions. Third, the timing of the cycles differed across housing markets. Fourth, the largest booms and busts, and their timing, seem to be clustered geographically. Fifth, the cross sectional variance of annual house price changes rises in booms and declines in busts. Finally, these stylized facts are robust to controlling for housing demand fundamentals – namely, rents, incomes, or employment – although changes in fundamentals are correlated with changes in prices.

House Price Moments in Boom-Bust Cycles in Edward Glaeser and Todd Sinai(eds.),, Housing and the Financial Crisis University of Chicago Press (forthcoming 2013) (PDF)

Safety in Renting

A recent decline in the home ownership rate raises the possibility that people now realize that home owning is too risky for some. However, we should not forget that renting also is risky for others. This article outlines two sources of risk that owning avoids and renting does not – by owning, low-mobility households can lock in their housing costs and all households can hedge themselves against changes in the cost of housing from moving – and a source of risk that renting avoids: Uncertainty over the sale price of a house. The article shows which kinds of households would best avoid risk by choosing renting, or owning. The recent decline in the home ownership rate does not appear to be driven solely by natural renters returning to renting, and the article issues a challenge to landlords to find ways to make renting less risky for natural owners.

Safety in Renting , Wharton Real Estate Review(2012) (PDF)

Does Home Owning Smooth the Variability of Future Housing Consumption?

We show that the hedging benefit of owning a home reduces the variability of housing consumption after a move. When a current home owner’s house price covaries positively with housing costs in a future city, changes in the future cost of housing are offset by commensurate changes in wealth before the move. Using Census micro-data, we find that the cross-sectional variation in house values subsequent to a move is lower for home owners who moved between more highly covarying cities. Our preferred estimates imply that an increase in covariance of one standard deviation reduces the variance of subsequent housing consumption by about 11 percent. Households at the top end of the covariance distribution who are likely to have owned large homes before moving get the largest reductions, of up to 40 percent relative to households at the median.

Does Home Owning Smooth the Variability of Future Housing Consumption? with Andrew Paciorek, Journal of Urban Economics vol. 71(2012), 244-257 (PDF)

Understanding and Mitigating Rental Risk

The decision of whether to rent or own a home should involve an evaluation of the relative risks and the relative costs of the two options. It is often assumed that renting is less risky than homeownership, but that is not always the case. Which option is riskier depends on the risk source and household characteristics.
This article provides a framework for understanding the sources of risk for renters. It outlines the most important determinants of risk: volatility in the total cost of obtaining housing, changes in housing costs after a move, and the correlation of rents with incomes. The article characterizes the magnitudes of those risks and discusses how the effects of risk vary across renter types and U.S. metropolitan areas. In addition, the article shows that renters spend less of their cash flow on housing than do otherwise equivalent owners and, thus, are better able to absorb housing cost risk
This article provides a framework for understanding the sources of risk for renters. It outlines the most important determinants of risk: volatility in the total cost of obtaining housing, changes in housing costs after a move, and the correlation of rents with incomes. The article characterizes the magnitudes of those risks and discusses how the effects of risk vary across renter types and U.S. metropolitan areas. In addition, the article shows that renters spend less of their cash flow on housing than do otherwise equivalent owners and, thus, are better able to absorb housing cost risk

Understanding and Mitigating Rental Risk , Cityscape vol.13, number 2 (July 2011) 105-125 (PDF)

Commitment, Risk and Consumption: Do Birds of a Feather Have Bigger Nests?

We show that incorporating consumption commitments into a standard model of precautionary saving can complicate the usual relationship between risk and consumption. In particular, we present a model where the presence of plausible adjustment costs can cause a mean-preserving increase in unemployment risk to lead to increased consumption. The predictions of this model are consistent with empirical evidence from dual-earning couples. Couples who share an occupation face increased risk as their unemployment shocks are more highly correlated. Such couples spend more on owner-occupied housing than other couples, spend no more on rent, and are more likely to rent than own. This pattern is strongest when the household faces higher moving costs, or when unemployment insurance provides a less generous safety net.

Commitment, Risk and Consumption: Do Birds of a Feather Have Bigger Nests? with Stephen Shore, Review of Economics and Statistics vol . 92, number 2 (May 2010), pp 408-424 (PDF)

Spatial Variation in the Risk of Home Owning

Spatial Variation in the Risk of Home Owning in Edward Glaeser and John Quigley(eds.),, Housing Markets and the Economy, Risk Regulation, and Policy Lincoln Institute of Land Policy(2009), pp 83-112 (PDF)

U.S. House Price Dynamics and Behavorial Finance

We examine the relative roles of fundamentals and psychology in explaining U.S. house price dynamics. Using metropolitan area data, we estimate how the house price-rent ratio responds to fundamentals such as real interest rates and taxes (via a user cost model) and availability of capital, and behavioral conjectures such as backwards-looking expectations of house price growth and inflation illusion. We find that user cost and lagged five-year house price appreciation rate are the most important determinants of changes in the price-rent ratio and lending market efficiency also is capitalized into house prices, with higher prices associated with lower origination costs and a greater use of subprime mortgages. We find no evidence in favor of behavioral explanations based on the one-year lagged house price growth rate or the inflation rate. The causes of a house price boom appear to vary over time, with interest rate fundamentals mattering more than backwards-looking price expectations in the house price run-up of the 2000s and vice versa during the 1980s boom.

U.S. House Price Dynamics and Behavorial Finance with Christopher Mayer in C. Foote, L. Goette and S Meier(eds.),, Policymaking Insights from Behavorial Economics Federal Reserve Bank of Boston, 2000, pp 261-308 (PDF)

Net Worth and Housing Equity in Retirement

This paper documents the trends in the life-cycle profiles of net worth and housing equity between 1983 and 2004. The net worth of older households significantly increased during the housing boom of recent years. However, net worth grew by more than housing equity, in part because other assets also appreciated at the same time. Moreover, the younger elderly offset rising house prices by increasing their housing debt, and used some of the proceeds to invest in other assets. We also consider how much of their housing equity older households can actually tap, using reverse mortgages. This fraction is lower at younger ages, such that young retirees can consume less than half of their housing equity. These results imply that ‘consumable’ net worth is smaller than standard calculations of net worth.

Net Worth and Housing Equity in Retirement with Nicholas Souleles in J. Ameriks and O. S. Mitchell(eds.), Recalibrating Retirement Spending and Saving Oxford: Oxford University Press (2008), pp 46-77 (PDF)

Assessing High House Prices: Bubbles, Fundamentals and Misperceptions

We construct measures of the annual cost of single-family housing for 46 metropolitan areas in the United States over the last 25 years and compare them with local rents and incomes as a way of judging the level of housing prices. Conventional metrics like the growth rate of house prices, the price-to-rent ratio, and the price-to-income ratio can be misleading because they fail to account both for the time series pattern of real long-term interest rates and predictable differences in the long-run growth rates of house prices across local markets. These factors are especially important in recent years because house prices are theoretically more sensitive to interest rates when rates are already low, and more sensitive still in those cities where the long-run rate of house price growth is high. During the 1980s, our measures show that houses looked most overvalued in many of the same cities that subsequently experienced the largest house price declines. We find that from the trough of 1995 to 2004, the cost of owning rose somewhat relative to the cost of renting, but not, in most cities, to levels that made houses look overvalued.

Assessing High House Prices: Bubbles, Fundamentals and Misperceptions with Charles Himmelberg and Christopher Mayer, Journal of Economic Perspectives vol. 19, number 4 (Fall 2005), pp. 67-92 (PDF)

Owner-Occupied Housing as a Hedge Against Rent Risk

Many people assume that the most significant risk in the housing market is that homeowners are exposed to fluctuations in house values. However, homeownership also provides a hedge against fluctuations in future rent payments. This paper finds that, even though house price risk endogenously increases with rent risk, the latter empirically dominates for most households so housing market risk actually increases homeownership rates and house prices. Further, the net effect of rent risk on the demand for homeownership increases with a household’s expected length of stay in its home, as the cumulative rent volatility rises and the discounted house price risk falls. Using CPS data, the difference in the probability of homeownership between households with long and short expected lengths of stay is 2.9 to 5.4 percentage points greater in high rent variance places than low rent variance places. The sensitivity to rent risk is greatest for households that devote a larger share of their budgets to housing, and thus face a bigger gamble. Similarly, the elderly who live in high rent variance places are more likely to own their own homes, and their probability of homeownership falls faster with age (as their horizon shortens). This aversion to rent risk might help explain why older households do not consume much of their housing wealth. Finally, we find that house prices capitalize not only expected future rents, but also the associated rent risk premia. At the MSA level, a one standard deviation increase in rent variance increases the house price-to-rent ratio by 2 to 4 percent.

Owner-Occupied Housing as a Hedge Against Rent Risk with Nicholas Souleles, Quarterly Journal of Economics vol. 120, number 2 (May 2005), pp. 763-789 (PDF)