What is a
housing crisis?
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Housing bubbles
A housing bubble is when prices for houses rise rapidly because of demand and a limited supply or supply that can't keep up with the demand. Speculators enter market, further driving up demand. At some point, the demand decreases or stagnates at the same time that the supply increases. That results in a sharp drop in prices and the bubble bursts. The U.S housing bubble started in 2003, with peak prices occuring in 2006. During this time, metro areas saw huge increases in housing prices. Prices for homes in Las Vegas went up over 80%. New jobs, high profits, and generous mortgage lenders made for risky investments and unreasonable loans.The collapse of the U.S housing market in 2007 resulted in a large number of households with negative equity. As housing prices dropped to new lows, millions of homeowners saw their mortgage debt become higher than their home was worth.
In the years since the crash, cities have been working towards recovery of home values, but this recovery has large variations in both amount and speed of recovery. Though the market crash affected the entire nation, it is important to note that the impact was concentrated in certain parts of the country.
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Why Las Vegas?
The Las Vegas metropolitan area has been one of the top foreclosure markets in the United States and has been heavily impacted by the housing crisis. Sharp patterns of housing price increases and drops have shaped the Las Vegas housing market over the past decade. The diverse makeup and distinct housing market patterns in Las Vegas make it an ideal region to study the evenness of housing market recovery over space.
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Why study recovery patterns?
Using spatial analysis of house price variables and analysis of demographic and housing characteristics, it is possible to predict the housing trajectory and determine areas that will potentially be more distressed in the case of another housing market crash. From the outcomes of these analyses, trends emerge that show what neighbourhood-level demographic and socio-economic indicators are consistent with uneven recovery after housing market crashes. This provides a better understanding of areas within Las Vegas, and potentially other cities, most vulnerable before and after boom and bust cycles in the housing market.
How do we analyze
recovery patterns?
In order to understand how different areas (defined by the zip-code boundaries) behaved during housing market boom, bust, and recovery, clusters of markets were identified over the 2001-2018 period. These clusters are defined by most recovery, average recovery, and
least recovery during the time period of 2001-2018. This was performed using the Zillow value home index (ZVHI) to identify the average single-family home value for the 50 different zip-codes in and around the Las Vegas metro area, then identifying the peak and the bottom of the housing market during the studied time period.
Three time periods were used to examine percent change in median home price; growth (2001-2006), decline (2007-2012), and recovery (2012-2018). The percent change in home price is the variable from which the zip codes are clustered. The map below shows the reuslts of the cluster analysis perfomed in SPSS statisitical software.
Understanding the demographic, socio-economic, and geographic characteristic differences between the clusters is another integral part of the research. Using the multitude of variables obtained from the decennial Census, it is possible to perform a focused analysis of demographic characteristics of each zip-code pre-market bust. A variance analysis was performed to determine what commonalities are found within the zip codes in each cluster. Variables used in the variance analysis were median household income, percent Hispanic, percent black, poverty rates, owner occupancy rates, and distance from city center. From this analysis emerged relationships between demographic characteristics and the degree to which houses in each zip-code recovered. Click through the chart below to explore the variables studied and how the different clusters varied.
What can we learn from these
results?
A strong correlation between high Hispanic populations with lower median incomes and faster home value recovery was uncovered while areas with higher-income and lower populations of color saw less and slower home value recovery. Although faster home value recovery was indicated, another pattern was revealed that suggests areas with more extreme home value changes throughout the study time periods indicates more housing instability which could mean increased vulnerability in the case if another housing market crash. Although these patterns varied from other studies and literature that suggested different outcomes as explained above, further research must be done in different study areas to better understand the range of outcomes that could occur in this type of analysis of home value trajectories.
With the recent surge in home values in large metropolitan areas, specifically in areas with large populations of color and less household wealth, these is a much higher risk of impacts once again if another housing crisis were to occur. In order to address this, efforts to minimize these impacts and support more housing stability must take into account the patterns of housing instability and the uneven recovery patterns uncovered in this study and other like it.
Want to explore the study area more?
Click through the different zip codes to see how housing values have
changed throughout recent market cycles and the patterns they show.