Economists have puzzled over the apparent failure of older homeowners to cash out home equity. Casual observation, however, suggests that older homeowners undermaintain their homes. Estimated home equity reduction may thus be biased downward if self-reported home values do not incorporate the market's view of the state of repair. American Housing Survey data show that homeowners over 75 spend approximately $270 less per year on routine home maintenance than younger owners of similar homes and approximately $1,100 less on all home improvement. Older homeowners realize weaker price appreciation than younger owners of similar homes in the same markets over identical horizons by approximately three percent per year. Older homeowners do, thus, take money out of their homes. The large magnitude of depreciation relative to expenditure differences suggests the availability of maintenance projects with positive financial and consumption benefits to a large number of older homeowners. The results are difficult to explain within a standard life cycle model given the near absence of a market for reverse mortgages.

Long term care is one of the few observable triggers for home sale among the elderly. Combined with a thin reverse mortgage market, this helps rationalize weak demand for Long Term Care Insurance (LTCI). Home equity typically tapped primarily in the event of long term care reduces the gain to insurance transfers from healthy states. Households in the Health and Retirement Study with large home equity to wealth ratios have significantly weaker demand for LTCI than other households, even among those so wealthy as to face weak temptation from Medicaid.

For most US households, labor income is the most important source of wealth and housing is the most important risky asset. A natural intuition is thus that households whose incomes covary relatively strongly with housing prices should own relatively little housing. Under plausible assumptions on preferences and distributions, this result holds theoretically. Empirically, I find a significant effect: among US households, a one standard deviation increase in income-house price covariance is associated with a decrease of approximately $7,500 in the value of owner occupied housing. This empirical result implies greater cognizance of the interaction between labor income and asset risk on the part of some households than suggested by most analyses of stock market behavior. The analysis also suggests that many homeowners enter financial markets in a riskier position than typically thought. The results bolster the intuitive appeal of proposals for market- or tax-based risk sharing in housing prices.

Segregation of households on the dimension of income at the jurisdictional level is interesting to economists because, under some conditions, it is an equilibrium condition in the political economy models of jurisdiction choice that follow from [15]. This paper addresses the measurement of household income sorting across jurisdictions and the attribution of observed sorting to a pure Tiebout mechanism. A standard decomposition of income variance into within- and between-jurisdiction components is biased downward by roughly 50 percent due to measurement error and differences between transitory and permanent income. Adjusting US Census data accordingly, an average across US Metropolitan Areas (MSAs) of six to eight percent of income variation can be explained by differences across jurisdictions; approximately 21 percent in the much-studied Boston MSA. Variance decomposition overstates the role of locally provided public goods because jurisdictions are differentiated by both government and location. Comparing pairs of adjacent, randomly defined “neighborhoods” in the Boston MSA, I find that boundaries between physically adjacent jurisdictions explain no more than three to four percent of income variation.

Dense, expensive, litigious, and highly regulated, Manhattan is the quintessential coastal US housing market. Residential construction in Manhattan has fallen relative to total US residential construction over the last 45 years. This time trend has been attributed to tightening local regulation, but is entirely explained away by a combination of the decline of public housing construction and the decreasing national share of construction that is multifamily. Reliance on multifamily housing also helps explain slow construction growth in California and New York State, but not in other Northeast states.

We show that the optimal property tax rate rises with the ratio of land rents to structure and land development costs. California’s high ratio of income to property tax revenue and the distribution of Federal housing subsidies thus appear geographically misplaced. Proportional taxation of non-housing commodities is not optimal, even when elasticities with respect to wages are identical. Absent externalities, the desirability of transportation taxes and “anti-sprawl” growth controls hinge on the relative importance of time versus money in commuting costs.

This dissertation explores the effects of fluctuations in housing values on household saving and investment decisions. Chapter 1 examines the relationship between changes in housing values and household saving decisions. Fluctuations in housing values may affect household saving and consumption by increasing households' perceived wealth, or by relaxing borrowing constraints. Moreover, the increased liquidity of home equity during the recent housing boom may have led household behavior to respond more than in past years to changes in housing wealth. This chapter is the first analysis to provide evidence from household-level microdata suggesting that the housing wealth effect may have increased in line with increased access to housing-collateralized debt. Using data from the Survey of Income and Program Participation for the years 1984 - 2003, I estimate an average elasticity of household active saving with respect to MSA-level house prices of -0.222, which corresponds to a 1 cent decrease in annual active saving when housing wealth increases by 1 dollar. When I estimate housing wealth effects separately between 1984 and 1990, and between 1996 and 2003, I find smaller effects during the earlier period, but large and significant effects during the later period. During the later period, I estimate an average elasticity of household active saving with respect to MSA-level house prices of -1.044, which corresponds to a 3 cent decrease in annual active saving when housing wealth increases by 1 dollar. Further evidence comparing the magnitude of the wealth effect between different subpopulations -- older homeowners versus younger homeowners, and recent homebuyers versus those with longer tenure -- suggests that a relaxation of liquidity constraints, rather than changes in the composition of the homeowner population, is a central factor contributing to the increase in the housing wealth effect.

Chapter 2 explores the connection between growth in housing values, uncertainty over future housing values, and property owners' investments in housing. Residential housing is a significant share of most American households' asset holdings. As such, the decision to build, to buy, or to make significant improvements to a home is driven not only by consumption considerations, but is also an investment decision. By modeling property owners' housing investment decisions using a framework of optimal capital investment where investments are irreversible and there is uncertainty in future asset values, this analysis theoretically predicts and empirically estimates the extent to which property owners respond to changes in the profitability of housing investment by making investments in their stock of housing. Using a unique dataset of residential sales, geographic information, and the universe of building permits issued in Los Angeles between 1999 and 2008, and focusing on nonresident landlords and "improver-movers" - owner-occupiers who make improvements to their properties and subsequently sell the property, I find that when housing values increase, property owners are more likely to make capital investments, and that the value and square footage of these investments is larger. When house price volatility is high, property owners are less likely to make investments. However, conditional on the decision to invest, the value and square footage of investments is larger. This result is shown to be a consequence of property owners' optimally delaying capital investment when uncertainty over future prices is high.

Chapter 3 documents the extent to which residential real estate development is cyclical - exhibiting periods of rapid expansion followed by periods of rapid contraction - using New York City as a case study. This chapter provides an overview of residential development activity in New York City during the years 2000 - 2008. In this analysis, I describe the effects of this real estate "boom" on the housing market in New York City during these years, and characterize the long-term effects of the "boom" and subsequent "bust" in residential development on the composition of the City's housing stock. Economic theories of cyclicality in real estate markets, outlined in this chapter, show that uncertainty over the exact timing of price declines coupled with a long development lag can lead to buildings being completed and new units entering the market even as prices decline. Although the elasticity of housing supply is lower in New York City than in other areas, building activity tends to follow a boom-and-bust pattern similar to other areas. Neighborhoods with higher levels of amenities experienced more growth in residential housing supply, and public involvement in development activity (both to facilitate and to restrict development) became less important for builders as the boom progressed. As building activity slows, City officials and developers are taking steps to ensure that stalled construction sites, rather than becoming eyesores and safety hazards, are preserved for future use.