Update on Homeownership Wealth Trajectories Through the Housing Boom and Bust

Daniel McCue

Senior Research
Associate

The housing crisis and ensuing Great Recession of the late 2000s resulted in millions of homeowners losing their homes to foreclosure and millions more losing substantial amounts of housing wealth as home prices plummeted. These substantial financial losses have raised important questions about the appropriateness of policies to encourage homeownership as a wealth building strategy for low-income and minority households. To study this issue, in 2013 the Joint Center published a paper entitled “Is Homeownership Still an Effective Means of Building Wealth for Low-income and Minority Households? (Was it Ever?)” as part of a 2013 symposium held to reexamine the goals of homeownership and explore lessons learned from the housing crisis.

Since the original paper was completed, additional years of PSID data have become available that allow us to extend the original analysis through 2013, which we have now done in a new JCHS working paper.

The original paper looked specifically at the question of whether homeownership, particularly for low-income and minority families, was an effective means of building wealth during the most tumultuous housing market in recent memory. Studying the 1999-2009 time period, the paper found that even during a time of excessive risk taking in the mortgage market and extreme volatility in house prices, large shares of owners successfully sustained homeownership and created substantial wealth in the process; that renters who became homeowners and sustained it through the period had some of the largest gains in wealth; and that renters who transitioned to ownership but failed to sustain it ended the study period with no less wealth than when they started. Yet while the results were positive in supporting the benefits of sustained homeownership, the study only covered the time period through 2009, which was the latest year of data available at the time, and therefore did not capture the entirety of the housing downturn and related fallout. Indeed, according to the CoreLogic National Home Price Index, house prices did not reach bottom until March of 2011 and much of the foreclosures and distressed exits from homeownership resulting from the downturn occurred well after 2009.

In this new 2016 paper, Update on Homeownership Wealth Trajectories Through the Housing Boom and Bust, with the extended timeframe through 2013 more thoroughly capturing the extent of the housing downturn and its accompanying effects on families’ wealth accumulation, our updated analysis upholds the bottom-line result from the earlier paper: that homeownership was associated with significant gains in household wealth, even when viewed across the tumultuous housing crisis period of 1999-2013. However to sustain gains in household wealth from homeownership, we found it is critically important to sustain homeownership itself. 

Source: Table 4b, working paper

Despite the continued declines in home values and continued high levels of foreclosure beyond 2009, the extended analysis found that homeownership was still associated with sizeable gains in household wealth in 1999-2013 for those who sustained homeownership through 2013, just as the original analysis found for those who owned through 2009. Among those who bought a home after 1999 but had returned to renting by 2013, the net wealth of the typical household in 2013 was back to what it was for these households in 1999, which was similar to the median net wealth of households among those who rented the entire time. As in the earlier study, households who began the study period as homeowners but ended as renters experienced the most significant declines in wealth. The key differences in the updated analysis was that the annual gains in wealth associated with owning a home declined in magnitude and the share of both Hispanic and low-income households that were able to sustain homeownership declined to 60-61 percent.

Note: Values shown are modeled marginal effects in constant 2013 dollars.

Source: Table 6b, working paper

But while those who maintained homeownership experienced meaningful gains in wealth, the relatively high shares among some groups that failed to sustain owning does raise the question of whether homeownership is a risk worth taking. On the other hand, the fact that renters accrued little wealth over the same period points to the limited opportunities that low-income households have outside of homeownership for building a nest egg. Taken together the study’s findings of both the remarkably and persistently low wealth levels of the typical renter and the potential for wealth accumulation when homeownership is maintained underscore the need for policies both to support sustained homeownership as well as to help renters find ways to build wealth outside of homeownership.

How Helpful is the Price-to-Income Ratio in Flagging Bubbles?

by Rocio Sanchez-Moyano
Research Assistant

With the continued growth of house prices across the country, talk of a housing bubble is beginning to reappear in the headlines. House price-to-income ratios are often used to indicate a bubble, as prices have historically had a relatively stable relationship with incomes (both mean and median).  In the US, nationally, the price-to-income ratio remained relatively stable throughout the 1990s.  It began to increase around 2000 and surpassed its long-run average of 3.65 by 2002 (Figure 1).  The national price-to-income ratio continued to increase in the mid-2000s, reaching a high of 4.63 in 2006 before rapidly declining in 2007 and 2008 and eventually hitting a low of 3.26 in 2011.  The classic bubble shape is clearly visible in this trend.  Recent price gains, viewed in this context, do not seem to indicate the return of a bubble; price-to-income ratios today match their early 1990s rates and still have some room for growth before reaching their long-run average.  (Click chart to enlarge.)

Notes: Prices are 1991 National Association of Realtors® Median Existing Single-Family Home Prices, indexed by the FHFA Expanded-Data House Price Index.  Incomes are median household incomes.

Sources: JCHS tabulations of FHFA Expanded-Data House Price Index;  US Census Bureau, Moody’s Analytics Estimates.

However, despite the seemingly straightforward relationship between house prices and incomes in Figure 1, this indicator can be difficult to interpret.  To start, many data sources are available for measuring prices.  One used frequently is the National Association of Realtors ® (NAR) Single-Family Median Home Price as it is widely available for many metros and provides an actual house price (rather than an index showing change in values) that can be compared to income levels.  The disadvantage to this measure is that NAR house prices also capture changes in the types of units that are being sold over time and so does not reflect how the value of the same home changes.  Repeat sales indices, like the Federal Housing Finance Authority’s (FHFA) Expanded-Data House Price Index, which was used to produce the figures in this post, are designed to take into account changes in the values of homes themselves by tracking sales of the same homes over time.  However, the FHFA index can be more difficult to interpret since, as an index, it does not provide information about current prices.  Price-to-income ratios using this data must peg the index to a starting or ending house price.

Furthermore, identifying bubbles or other price anomalies from price-to-income ratios can be difficult because it is not clear what is an appropriate baseline value of the measure for comparison.  Even in the aggregate US case, where the ratio did not fluctuate more than one percent in either direction for much of the 1990s, the linear trend is not flat and the long run average is above the 1990s levels.  This becomes even murkier when observing trends at the metro level.  Some metros, like Dallas, had stable price-to-income ratios over the last two decades (Figure 2).  Dallas did not experience a significant bubble in the mid-2000s and its long-run average mirrors the linear trend.  In other metros, like Phoenix, the boom-bust period led to significant fluctuations in the price-to-income ratio after having been relatively stable in the 1990s.  If the 1990s levels are to be considered normal for Phoenix, then current price-to-income ratios remain below average and recent growth in prices can be considered a return to normal after an overcorrection.

For other metros, the price-to-income trend is more difficult to interpret.  Ratios in Cleveland are well below their long-run average, but the historical trend has been drifting downwards, so ratios in recent years could be indicating a reset of the ratio in Cleveland to lower levels.  At another end, San Francisco has experienced a wide range of price-to-income ratios in recent history.  Price-to-income ratios boomed in the late 1980s, decreased throughout much of the 1990s, and then surged through the mid-2000s.  Compared to its long-run average, ratios in San Francisco are above historical norms, but, when the historical trend is considered, prices can continue to increase before they appear “too high.”  Finally, if a fundamental relationship exists between prices and incomes, it is unclear why the ratio can vary significantly from metro to metro.  The national average is around 3.6.  In the metros observed here, Cleveland and Dallas both have historic averages below 3.0 while San Francisco’s is double the national average. (Click chart to enlarge.)

Notes: Prices are 1991 National Association of Realtors® Median Existing Single-Family Home Prices, indexed by the FHFA Expanded-Data House Price Index.  Incomes are median household incomes.

Sources: JCHS tabulations of FHFA Expanded-Data House Price Index;  US Census Bureau, Moody’s Analytics Estimates

Given this variation, what can we make of the price-to-income ratio?  On a national level, this ratio does a relatively good job of identifying substantive shifts in the market.  In the aggregate, there appears to be a “normal” price-to-income ratio and prolonged deviation from this trend can signal an underlying shift.  However, on a metro-by-metro level, where it can be difficult to identify an appropriate baseline value, long-run historical context is necessary to interpret point-in-time estimates.  In markets like Dallas and Phoenix, historical trends are consistent enough that it can be useful to compare the current ratio to past ones.  In others, like Cleveland and San Francisco, the price-to-income ratio on its own is not especially helpful since there is no clear way to identify a “normal” price-to-income ratio.