The boom and bust of US housing prices from various geographic perspectives (original) (raw)
Related papers
Anatomy of the Beginning of the Housing Boom: U.S. Neighborhoods and Metropolitan Areas, 1993-2009
2011
We provide novel estimates of the timing, magnitudes, and potential determinants of the start of the last housing boom across American neighborhoods and metropolitan areas (MSAs) using a rich new micro data set containing 23 million housing transactions in 94 metropolitan areas between 1993 and 2009. We also match transactions data with loan information, enabling us to observe household income and other demographics for each neighborhood. Five major findings are reported. First, the start of the boom was not a single, national event. Booms, which are defined by the global breakpoint in an area's price appreciation series, begin at different times over a decade-long period from 1995-2006. Second, the magnitude of the initial jump in house price appreciation at the start of the boom is economically, not just statistically, significant. On average, log house prices are over four points higher during the first year of the boom relative to the previous twelve month period for both MSAs and neighborhoods. There is no evidence that price growth was trending up prior to the start of the boom. Third, local income is the only potential demand shifter found that also had an economically and statistically significant change around the time that local housing booms began. Contemporaneous local income growth is large enough to account for half or more of the initial jump in house price appreciation. While these estimates indicate that the beginning of the boom was fundamentally justified on average, they do not imply that what followed was rational. Fourth, there is important heterogeneity in that result. Income growth is large and jumps at the same time as house price appreciation in areas that boomed early and have inelastic supplies of housing, but not in late booming areas and those with elastic supply sides. Fifth and finally, none of the demand-shifters analyzed show positive pre-trends, but some such as the share of subprime lending, do lag the beginning of the boom. This suggests that key players in the lending market more responded to the boom, rather than caused it to start.
Assessing High House Prices: Bubbles, Fundamentals and Misperceptions
Journal of Economic Perspectives, 2005
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.
Booms and busts in housing markets: Determinants and implications
This study looks at the characteristics and determinants of booms and busts in housing prices for a sample of eighteen industrialised countries over the period 1980-2007. From an historical perspective, we find that recent housing booms have been amongst the longest in the past four decades. Estimates of a Multinomial Probit model suggest that domestic credit and interest rates have a significant influence on the probability of booms and busts occurring. Moreover, international liquidity plays a significant role for the occurrence of housing booms and-in conjunction with banking crises-for busts. We also find that the deregulation of financial markets has strongly magnified the impact of the domestic financial sector on the occurrence of booms.
A substantial literature argues that the recent housing crash in the United States naturally followed from a series of legal and technical transformations that took place in that nation's financial sector. While a number of new practices were applied fairly evenly across the nation, their repercussions were not at all manifested evenly. In this paper we analyze the trajectories of quality-adjusted house-price increases during the period 1984-2006. We develop models where year-to-year house prices certainly respond to ongoing changes in either wages or income, but where these responses vary dramatically across the nation's largest cities. We find that much of this variability is captured by city-specific initial conditions, which include differences in land-use regulation, taxes, and population size as well as the remarkable variation in the geographies of both human-created and natural amenities. The importance of some initial conditions is shown to strengthen, while the importance of other conditions weakens, over the study period. case of air quality.
2016
We all know that housing prices have followed a boom-and-bust trajectory over the past fifteen years, but which segments of the population experienced the sharpest rise and fall—and in which parts of the country? Using transaction-level data from multiple large urban counties, I analyze the entire distribution, breaking down the change in housing prices into quantiles. I measure the change in the distribution in house prices in each city, determine how much of the change can be explained by quality variables, and investigate what differences between the cities might be causing the variation in their housing price distributions—especially during the housing bubble, which some cities experienced more acutely than others. This analysis allows me to identify which segments of the population were most sensitive to the boom-andbust—and in which cities—with policy implications for the role of the housing market in social equity and financial stability going forward. **The author can be con...
Housing supply and housing bubbles
Like many other assets, housing prices are quite volatile relative to observable changes in fundamentals. If we are going to understand boom-bust housing cycles, we must incorporate housing supply. In this paper, we present a simple model of housing bubbles that predicts that places with more elastic housing supply have fewer and shorter bubbles, with smaller price increases. However, the welfare consequences of bubbles may actually be higher in more elastic places because those places will overbuild more in response to a bubble. The data show that the price run-ups of the 1980s were almost exclusively experienced in cities where housing supply is more inelastic. More elastic places had slightly larger increases in building during that period. Over the past five years, a modest number of more elastic places also experienced large price booms, but as the model suggests, these booms seem to have been quite short. Prices are already moving back towards construction costs in those areas.
Monetary Policy and the House Price Boom across U.S. States
SSRN Electronic Journal, 2000
The authors use a dynamic factor model estimated via Bayesian methods to disentangle the relative importance of the common component in the Office of Federal Housing Enterprise Oversight's house price movements from state-or region-specific shocks, estimated on quarterly state-level data from 1986 to 2004. The authors find that movements in house prices historically have mainly been driven by the local (state-or region-specific) component. The recent period (2001-04) has been different, however: "Local bubbles" have been important in some states, but overall the increase in house prices is a national phenomenon. The authors then use a VAR to investigate the extent to which expansionary monetary policy is responsible for the common component in house price movements. The authors find the impact of policy shocks on house prices to be very small. JEL classification: C11, E58, R31
Economic impacts of the housing market: a panel data approach
Usually housing is viewed in the context of consumption resulting from other economic drivers such as income and employment. Here, we study how two key local economic measures, the gross metropolitan product (GMP) and unemployment rate, respond to shocks in home value appreciation, home sales, and new construction, respectively. Our analysis relies upon a large panel of 158 metropolitan statistical areas (MSAs) in the United States from 1983 to 2002. Location-related MSA characteristics and time-specific macro economic variables are both controlled. We find a statistically significant impact of home appreciation and home sales on these economic measures with home appreciation having a stronger impact than home sales. However, the magnitude of the impact of housing shocks is modest, at least when we compare it to the impact of a shock in the population growth rate.