It is well known that there are #affordability issues in the home purchase market, but there is less information on the single-family rental market, which makes up one-half of residential rentals. The CoreLogic Single Family Rental Index reflects rents paid on single-family houses and condos, and using this index we can dissect rent growth by both price tier and metro area.
Figure 1 shows the 12-month change in our national rental index from 2005 to today. Rents for single-family #homes fell during the Great Recession but then bounced back strongly from their low point in mid-2009 and have been trending up, mirroring home price growth. In October 2017, the index measured rent growth of 2.7 percent from a year ago. We can also show rent changes for the high-end (those rents 25 percent or more above the median rent in that market) and the low end (those rents 25 percent or less below the median in that market). The low-end single-family rental tier lagged the high-end tier from mid-2009 to early 2014, but then the low-end began steadily outpacing the high-end and the difference is growing. This mirrors the same high demand, low- supply forces that have caused low-end home prices to outpace high-end prices, as evidenced by shorter days-on-market and tighter inventory for low-end homes. Investors who entered the market to buy up distressed properties during the housing crisis might be exacerbating this trend in the rental market. High-end rents increased 2 percent in October from a year ago, while low-end rents increased by more than twice as much – 4.2 percent.
We can also look at the difference between low-end and high-end rent growth by metro area. Figure 2 shows that low-end rents have been increasing in the largest 20 markets, with Seattle leading the large metros with the biggest increase in rents at 7.9 percent in October. Austin had the smallest increase in low-end rents of the large metros. In most of the 20 markets shown in the chart, low-end rents are increasing faster than high-end rents, and the trend is happening all over the country, not just in one region. The one exception is Warren, Mich., where low-end and high-end rents are increasing at about the same rate. The biggest spread in low-end and high-end rent increases was in Charlotte, N.C., where the low-end increased 5.6 percent and the high-end showed no increase.
The single-family rental market is an important and often overlooked segment of the #housing market and is affected by rising demand and constrained supply just like the rest of the housing market. The demand and supply pressures are especially apparent for lower-cost homes, for which rents are increasing at a much faster rate than for higher-cost homes
February 06, 2018, Irvine, Calif. –
- Largest Price Gains During 2017 Were in California, Idaho, Nevada, Utah and Washington
- Affordability Continues to Erode, Especially in Low-Price Range
- Home Prices Projected to Increase by 4.3 Percent by December 2018
CoreLogic® (NYSE: CLGX), a leading global property information, analytics and data-enabled solutions provider, today released its CoreLogic Home Price Index (HPI™) and HPI Forecast™ for December 2017, which shows home prices are up both year over year and month over month. Home prices nationally increased year over year by 6.6 percent from December 2016 to December 2017, and on a month-over-month basis home prices increased by 0.5 percent in December 2017 compared with November 2017,* according to the CoreLogic HPI.
Looking ahead, the CoreLogic HPI Forecast indicates that home prices will increase by 4.3 percent on a year-over-year basis from December 2017 to December 2018, and on a month-over-month basis home prices are expected to decrease by 0.4 percent from December 2017 to January 2018. The CoreLogic HPI Forecast is a projection of home prices using the CoreLogic HPI and other economic variables. Values are derived from state-level forecasts by weighting indices according to the number of owner-occupied households for each state.
“The number of homes #for sale has remained very low,” said Dr. Frank Nothaft, chief economist for CoreLogic. “Job growth lowered the unemployment rate to 4.1 percent by year’s end, the lowest level in 17 years. Rising income and consumer confidence has increased the number of prospective homebuyers. The net result of rising demand and limited for-sale inventory is a continued appreciation in home prices.”
According to CoreLogic Market Condition Indicators (MCI) data, an analysis of housing values in the country’s 100 largest metropolitan areas based on housing stock, 35 percent of metropolitan areas have an overvalued housing market as of December 2017. The MCI analysis categorizes home prices in individual markets as undervalued, at value or overvalued by comparing home prices to their long-run, sustainable levels, which are supported by local market fundamentals such as disposable income. Also, as of December, 28 percent of the top 100 metropolitan areas were undervalued and 37 percent were at value. When looking at only the top 50 markets based on housing stock, 48 percent were overvalued, 14 percent were undervalued and 38 percent were at value. The MCI analysis defines an overvalued housing market as one in which home prices are at least 10 percent higher than the long-term, sustainable level, while an undervalued housing market is one in which home prices are at least 10 percent below the sustainable level.
“Home prices continue to rise as a result of aggressive monetary policy, the economic and jobs recovery and a lack of housing stock. The largest price gains during 2017 were in five Western states: California, Idaho, Nevada, Utah and Washington,” said Frank Martell, president and CEO of CoreLogic. “As home prices and the cost of originating loans rise, affordability continues to erode, making it more challenging for both first time buyers and moderate-income families to buy. At this point, we estimate that more than one-third of the 100 largest metropolitan areas are overvalued.”
*November 2017 data was revised. Revisions with public records data are standard, and to ensure accuracy, CoreLogic incorporates the newly released public data to provide updated results.
The CoreLogic HPI™ is built on industry-leading public record, servicing and securities real-estate databases and incorporates more than 40 years of repeat-sales transactions for analyzing home price trends. Generally released on the first Tuesday of each month with an average five-week lag, the CoreLogic HPI is designed to provide an early indication of home price trends by market segment and for the “Single-Family Combined” tier representing the most comprehensive set of properties, including all sales for single-family attached and single-family detached properties. The indexes are fully revised with each release and employ techniques to signal turning points sooner. The CoreLogic HPI provides measures for multiple market segments, referred to as tiers, based on property type, price, time between sales, loan type (conforming vs. non-conforming) and distressed sales. Broad national coverage is available from the national level down to ZIP Code, including non-disclosure states.
CoreLogic HPI Forecasts™ are based on a two-stage, error-correction econometric model that combines the equilibrium home price—as a function of real disposable income per capita—with short-run fluctuations caused by market momentum, mean-reversion, and exogenous economic shocks like changes in the unemployment rate. With a 30-year forecast horizon, CoreLogic HPI Forecasts project CoreLogic HPI levels for two tiers—“Single-Family Combined” (both attached and detached) and “Single-Family Combined Excluding Distressed Sales.” As a companion to the CoreLogic HPI Forecasts, Stress-Testing Scenarios align with Comprehensive Capital Analysis and Review (CCAR) national scenarios to project five years of home prices under baseline, adverse and severely adverse scenarios at state, Core Based Statistical Area (CBSA) and ZIP Code levels. The forecast accuracy represents a 95-percent statistical confidence interval with a +/- 2.0 percent margin of error for the index.