Todd M. Sinai

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.

The Asset Price Incidence of Capital Gains Taxes: Evidence from the Taxpayer Relief Act of 1997 and Publicly-Traded Real Estate Firms

We provide new evidence that corporate-level investment subsidies can be substantially capitalized into asset prices by examining the relative stock price performance of publicly traded companies in the real estate industry that should have been differentially affected by the capital gains tax rate reduction enacted in the Taxpayer Relief Act of 1997. By comparing real estate firms that have an organizational structure that allow property sellers to defer capital gains taxes and plan to use it to acquire property with those that do not, we isolate the effect of the tax cut from industry trends and firm-level heterogeneity. When we examine the time period surrounding the reduction in the capital gains tax rate, our results suggest the tax change was substantially capitalized into lower share prices for these firms and that the benefit of the sellers capital gains tax deferral accrued mainly to the buyer of an appreciated property. The validity of our estimation strategy is supported by further tests showing that these firms did not experience any relative movement in share prices during the previous year when capital gains tax rates did not change.

The (Un)Changing Geographical Distribution of Housing Tax Benefits: 1980 to 2000

Using tract-level data from the 1980, 1990, and 2000 censuses, we estimate how the income-tax-related benefits to owner-occupiers are distributed spatially across the United States. Even though the top marginal tax rate has fallen substantially since 1979 and the tax code more generally has become less progressive, the tax subsidy per household or owner was almost unchanged between 1979 and 1989 and then rose substantially between 1989 and 1999. Geographically, gross program benefits have been and remain spatially targeted. At the state level, Californias owners have received a disproportionate share of the subsidy flows over the past two decades. Their share of the gross benefits nationally has fluctuated from 19 to 22 percent. Depending on the year, these percentages represent from 1.8 to 2.3 times Californias share of the nations owners. The median ratio of the share of tax benefits to the share of owners has declined over time, from 0.83 in 1979 to 0.76 in 1999. Examining the data at the metropolitan-area level finds an even more dramatic spatial targeting and a spatial skewness that is increasing over time. Comparing benefit flows in 1979 in the top 20 areas versus those in the bottom 20 areas finds that owners in the highest subsidy areas received from 2.7 to 8.0 times the subsidy reaped by owners in the bottom group. By 1999, the analogous calculation finds owners in the top 20 areas receiving from 3.4 to 17.1 times more benefits than owners in any of the 20 lowest recipient areas. Despite the increasing skewness, the top subsidy recipient areas tend to persist over time. In particular, the high-benefit-per-owner areas are heavily concentrated in California and the New York City-Boston corridor. While taxes are somewhat higher in these places, it is high and rising house prices that appear most responsible for the large and increasing skewness in the spatial distribution of benefits.

The Spatial Distribution of Housing-Related Tax Benefits in the United States

Using 1990 Census tract-level data, we estimate how tax subsidies to owner-occupied housing are distributed spatially across the United States, calculating their value as the difference in taxes currently paid by home owners and the taxes owners would pay if there were no preference for investing in ones home relative to other assets. The

Feedback between Real Estate and Urban Economics

164 billion national tax subsidy is highly skewed spatially with a few areas receiving large subsidies and most areas receiving small ones. If the program were self-financed on a lump sum basis, less than 20 percent of states and 10 percent of metropolitan areas would have net positive subsidies. These few metropolitan areas are situated almost exclusively along the California coast and in the Northeast from Washington, DC to Boston. At the state level, California stands out because it receives 25 percent of the national aggregate subsidy flow while being home to only 10 percent of the countrys owners. At the metropolitan area level, owners in just three large CMSAs receive over 75 percent of all positive net benefits. And within a number of the larger metropolitan areas, the top quarter of owners receives 70 percent or more of the total subsidy flowing to the metro area.

Understanding and Mitigating Rental Risk

This paper considers the implications of increasing land supply constraints in the United States on urban demand. First, because shifts in demand are now capitalized more into the price of land, house prices in some metropolitan areas have grown increasingly unaffordable to typical households. This might have an effect on the fundamental character of such cities. Second, the effect of home owners’ financial interests as landowners on their decisions about what regulations or investments in their communities to support may become stronger. Third, researchers may now be able to better use land prices to make inferences about urban demand. However, interpreting real estate prices still is tricky.

Network Effects, Congestion Externalities, and Air Traffic Delays: Or Why Not All Delays Are Evil

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 Finally, potential policy approaches to rental housing that avoid increasing rent risk are discussed. A simple way to maintain renters’ capacity to absorb rent risk is to avoid subsidies that result in an incentive to consume a larger rental housing quantity. Targeting rental subsidies to more mobile households or those living in low-volatility cities, where renting is less risky, should be considered. Long-term leases would provide an intermediate position between renting annually and owning but are currently rare.