the marketpulse - corelogic · 2019-11-26 · volume 8, issue 11 november 2019 data as of september...

The MarketPulseNovember 2019

Volume 8, Issue 11

November 2019

Data as of September 2019 (unless otherwise stated)

News Media Contact

Todd Taylor [email protected]

619-938-6829 (office)

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The MarketPulse

Table of ContentsSpecial Report: Amazon HQ2 and the Washington, D.C. Metro Housing Market . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

Jumbo-Conforming Mortgage Rate Spread Trend . . . . . . . . . .6

Four of the Five States with Increases in Delinquency Rates in August also had Increases in Unemployment Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8

Multifamily Ownership and Mortgage Use by Property Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10

In The News . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Charts & Graphs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

10 Largest CBSA – Loan Performance Insights Report August 2019 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Overview of Loan Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Home Price Index State-Level Detail — Combined Single Family Including Distressed . . . . . . . . . . . . . . . . . . . . . 13

Home Price Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

CoreLogic HPI® Market Condition Overview . . . . . . . . . . . . . . . . . . . . . . 15

September 2019 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

September 2024 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Housing Statistics November 2019

HPI® YOY Chg 3.5%

HPI YOY Chg XD 3.1%

NegEq Share (Q2 2019)

3.8%

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On November 13, 2018, Amazon stunned the news cycle by announcing that it was choosing not one, but two sites for the location of its second headquarters (HQ2): Arlington County, Virginia, at Crystal City, and Queens, New York at Long Island City. However, just three months after the announcement, Amazon said it would be withdrawing its intent to open the New York location, instead focusing on job growth in Crystal City and other locations.

Now a year has passed from the announcement, and one burning question remains: Has the news had any noticeable effect on the Washington, D.C. housing market? In this post, we look at not only home price

growth of the metro area, but also of individual zip codes within the region.

In this CoreLogic special report, our findings are threefold. First, we see little evidence the metro area has experienced a large increase in housing prices since the November 2018 announcement. Second, and in contrast, we do find some individual zip codes—especially those near the HQ2 location—have had a strong uptick in price gains since the announcement. Lastly, we discovered that the relationship between

Special Report: Amazon HQ2 and the Washington, D.C. Metro Housing MarketThe Amazon HQ2 Announcement: Have Housing Prices Changed a Year Later?

Ralph McLaughlinDeputy Chief Economist

Ralph McLaughlin holds the title deputy chief economist for CoreLogic in the Office of the Chief Economist. He is responsible for leading economic research and using data and analytics to expand the visibility of the CoreLogic economic policy unit. He also works to enhance research capabilities and tools for clients, industry leaders, the public sector and news media.

Ralph has more than 15 years of experience in housing economics, applied econometrics, real estate development and investment, land use planning, spatial analysis, and economic geography. He previously worked at Trulia and Veritas Urbis Economics. He also served as an assistant professor at the San Jose State University. While at Trulia, he led the company’s housing economics research team, providing buyers with key insights about the economy, housing trends and public policy.

Continued on page 4

Figure 1. DC Metro Division Home Price Growth Muted Since HQ2CoreLogic Home Price Index, Year-Over-Year Change

©2019 CoreLogic, Inc. All Rights Reserved.

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Source: CoreLogic Home Price Index, not seasonally adjusted (November 5, 2019 release)

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proximity to the HQ2 site and home price gains have strengthened remarkably since March 2019.

Regional Home Price Growth Since the HQ2 Announcement MutedThe impact of Amazon choosing the district housing market (which includes both the Washington-Arlington-Alexandria and Silver Spring-Frederick-Rockville metro divisions) for the location of their HQ2 is unclear at best. Looking at the year-over-year change in the monthly CoreLogic Home Price Index (HPI), the data shows that both metro divisions saw little change in the rate of appreciation after November 2018. In September 2018 (the most recent comparison month between 2018 and 2019), annual home price growth in the Washington-Arlington-Alexandria and Silver Spring-Frederick-Rockville metro divisions rested at 3.4% and 2.1%, respectively, but grew slightly to 3.5% and 2.3% by September 2019. This is hardly what one would call a “boom.”

However, when compared to national trends over the same period, there is evidence that these two metro divisions outperformed the broader area. National home price growth descended by nearly two whole percentage points, from 5.3% to 3.5%, as high mortgage

rates and uncertain macroeconomic conditions stymied the market towards the end of 2018 and into the first half 2019. While anecdotal, this does suggest that the HQ2 announcement possibly buoyed the market in what might have otherwise been a period of slowing home price growth for the Washington, D.C. metro area.

Geography Matters: Zips Near Crystal City See Sharp Increase in Price GrowthWhile evidence is somewhat weak that the HQ2 announcement boosted the regional market, our zip code-level analysis shows a different story. Namely, that there is a correlation between proximity to the HQ2 site and the increase of home price appreciation over the past year. Of the top 10 zip codes with the largest increase in year-over-year growth rates, half are within a 5- mile distance of the HQ2 site and eight are within 10 miles.

The top three zip codes with the largest increase in their September 2018 and September 2019 year-over-year growth rates are not immediately adjacent to HQ2. These zip codes are 20815 (Chevy Chase, Maryland), 22180 (Vienna, Virginia) and 22306 (Mount Vernon, Virginia). Each of these areas is at least 7 miles away from HQ2, suggesting little correlation between the

Special Report continued from page 3

Figure 2. Washington, DC Metro Area Zip CodesQuickening of Home Price Growth Clustered Near Amazon HQ2

Zip Code (Area Name)

YOY Home Price Growth, Sep 2018

YOY Home Price Growth, Sep 2019

% Point Difference, Sep 2018–Sep 2019

Distance to Amazon HQ2 (Miles)

20815 (Chevy Chase) -1.1% 11.8% +12.9 Pts. 8.3

22180 (Vienna) -4.8% 6.6% +11.4 Pts. 10.9

22306 (Mt. Vernon) -5.3% 6.1% +11.4 Pts. 7.4

22302* (Alexandria) -1.7% 9.3% +11.0 Pts. 2.6

22206* (Arlington) -1.5% 11.8% +10.4 Pts. 2.2

22201* (Arlington) -1.1% 11.0% +9.8 Pts. 2.6

22311* (Alexandria) -1.3% 8.4% +9.6 Pts. 3.8

20151 (Chantilly) -2.2% 7.2% +9.4 Pts. 20.6

20017 (DC NE) 0.3% 9.4% +9.1 Pts. 6.3

22204* (Arlington) 0.0% 8.6% +8.7 Pts. 2.1

Source: CoreLogic Home Price Index, not seasonally adjusted (November 5, 2019 release) *Denotes adjacency to other top 10 zip

Continued on page 5

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HQ2 announcement and the zip codes that have picked up the most gains in home price appreciation. However, there is a cluster of zip codes in the top-10 list that are all within 4 miles of HQ2 and adjacent to one another. These include 22302 (Alexandria,

Figure 5. Zip Codes Near Amazon HQ2 Picking Up SteamAreas Near HQ2 Appreciated Faster After HQ2 Announcement


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Source: CoreLogic Home Price Index, not seasonally adjusted (November 5, 2019 release); Author’s Calculation

Figure 4. Fortunate Five Zip Codes Booming After HQ2 AnnouncementHome Price Growth Booms to Double Digits in Five Arlington-Alexandria Zips


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HQ2 Announcement

Source: CoreLogic Home Price Index, not seasonally adjusted (November 5, 2019 release)

Figure 3. Zip Codes Near HQ2 See Home Price Growth Pick UpArlinton-Alexandria Zip Code Cluster of Price Appreciation Emerges

Source: CoreLogic Home Price Index, not seasonally adjusted (November 5, 2019 release); Map by R.B. McLaughlin

Continued on page 11

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Before 2013 mortgage rates for jumbo loans were higher than for conforming loans. However, since 2013 the rate-difference narrowed and today jumbo loans typically have a lower interest rate.

An increase in GSE guarantee fee, a reduction in the GSE funding advantage, and portfolio lenders’ desire to hold jumbo loans explain much of the variation in the jumbo-conforming spread.1 Movement in interest rates may also help explain some of the variation in the jumbo-conforming spread, especially since 2013.

The mortgage rate and the jumbo-conforming rate spread are inversely correlated (Figure 1).2 For example, as the mortgage rate dropped during the first eight months of 2019 the spread has gone up. As the mortgage rate dropped the refinance application volume jumped up; because of a limited secondary market for jumbo loans and cutbacks in staffing at many lenders, bottlenecks in jumbo-loan production were reflected in a rise in the spread.

Jumbo-Conforming Mortgage Rate Spread TrendAdjusting for risk, location, and loan-size reduced spread from -30 to -6 basis points during 2013Q2 to 2019Q2

Archana PradhanEconomist

Archana Pradhan is an economist for CoreLogic in the Office of the Chief Economist and is responsible for analyzing housing and mortgage markets trends.

Continued on page 7

Figure 1. Mortgage Rate versus Jumbo-Conforming Spread(A Negative Spread means Jumbo is Less Expensive)

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Note: Correllation Coefficient: −0.65 (April 2013–June 2019)Source: CoreLogic Loan-Level Market Analytics Data and Freddie Mac

Figure 2. Adjusted Quarterly Jumbo-Conforming Spread Estimates2001 Q1–2019 Q2 (Average 2013 Q2–2019 Q2 was −6 Basis Points)

Spread (Basis Points)


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Jumbo-Conforming continued from page 6

However, after controlling for borrower and loan credit risk, location, and loan size characteristics, the spread is near zero (Figure 2).3 The adjusted estimates show that the spread narrowed from an average of negative 30 basis points (with no adjustments for differences in attributes) to negative 6 basis points for the adjusted estimate, averaged from the second quarter of 2013 to the second quarter of 2019.

In general, today’s jumbo loans have a higher credit underwriting standard than conforming loans (Figure 3). Comparing jumbo and conforming loans originated in 2018, jumbo loans had higher average credit scores by 26 points, lower LTV by 6 percentage points and lower DTI by 3 percentage points. These differences help account for much of the jumbo-conforming spread over the past several years.

For more on CoreLogic’s perspectives on the U.S. housing economy, please visit our Insights area of corelogic.com.

1 See AEI working paper https://www.aei.org/research-products/working-paper/jumbo-rates-rates-causes-implications/ and https://www.corelogic.com/blog/2018/08/why-are-jumbo-loans-cheaper-than-conforming-loans.aspx

2 Only 30-year fixed-rate conventional home-purchase loans were included for both conforming mortgage loans and jumbo mortgage loans for this analysis.

3 https://www.corelogic.com/blog/2018/10/jumbo-conforming-spread-risk-location-scale-economies-affect-rate.aspx

Figure 3. Averages Credit Risk Variables for Homebuyers with 30-Year Fixed Conventional Mortgages


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Source: CoreLogic Loan-Level Market Analytics Data

https://www.corelogic.com/insights-index.aspx

https://www.aei.org/research-products/working-paper/jumbo-rates-rates-causes-implications/ and https




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� The nation’s overall delinquency rate was 3.7% in August.

� The foreclosure inventory rate for August was 0.4%, where it has stood since November 2018.

1 Data in this report is provided by TrueStandings Servicing. https://www.corelogic.com/products/truestandings-servicing.aspx

In August 2019, 3.7% of home mortgages were in some stage of delinquency1, down from 3.9% a year earlier and the lowest for the month of August in more than 20 years, according to the latest CoreLogic Loan Performance Insights Report. The measure, also known as the overall delinquency rate, includes all home loans 30 days or more past due, including those in foreclosure. For the month of August historically, the share of delinquent mortgages peaked in 2010 at 11.1%. Since March 2018, the overall delinquency rate each month has been lower than during the pre-crisis period of 2000

through 2006, when the rate averaged 4.7%.

The serious delinquency rate—defined as 90 days or more past due, including loans in foreclosure—was 1.3% in August 2019, down from 1.5% in August 2018. The serious delinquency rate for this August was below the average of 1.5% for the 2000–2006 pre-crisis period and far below the peak of 7.5% in February 2010. The foreclosure inventory rate—the share of mortgages in some stage of the foreclosure process—was 0.4% in

Four of the Five States with Increases in Delinquency Rates in August also had Increases in Unemployment RatesLoan Performance Insights Report Highlights: August 2019

Molly BoeselPrincipal, Economist, Office of the Chief Economist

Molly Boesel holds the title principal, economist for CoreLogic in the Office of the Chief Economist and is responsible for analyzing and forecasting housing and mortgage market trends.

Continued on page 9

Figure 1. Current- to 30-Day Transition Rate


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August 2019, down from 0.5% a year earlier. August’s foreclosure rate was the lowest for that month in at least 20 years2 and was below the average pre-crisis level of 0.6%. Rising home prices have led to record amounts of home equity, reducing the risk of foreclosure.

The share of mortgages that were 30 to 59 days past due—considered early-stage delinquencies—was 1.8% in August 2019, unchanged from August 2018. The share of mortgages 60 to 89 days past due was 0.6% in August 2019, also unchanged from August 2018.

In addition to delinquency rates, CoreLogic tracks the rate at which mortgages transition from one stage of delinquency to the next, such as going from current to 30 days past due. Figure 1 shows that in August 2019 the current- to 30-day transition rate remained well below levels during the housing crisis. The August current- to 30-day rate was 0.8%, unchanged from a year earlier. The 30- to 60-day transition rate was 16.1% in August, up from 14.9% in August 2018, and the 60- to 90-day transition rate was 25.8% in August, up from 24.6% a year earlier.

2 The data in this report date back to January 1999.3 Metropolitan areas used in this report are the ten most populous Metropolitan Statistical Areas. The report uses Metropolitan Divisions where available.

Figure 2 shows the states with the highest and lowest share of mortgages 30 days or more delinquent. In August 2019, that rate was highest in Mississippi at 7.3% and lowest in Colorado at 1.7%. Five states logged an annual gain in their overall delinquency rate in August 2019. Iowa saw an increase of 0.2 percentage points, and Minnesota, Nebraska, Wisconsin and Rhode Island all posted an increase of 0.1 percentage points. The rise in overall delinquency in Iowa, Minnesota, Nebraska, and Wisconsin coincided with a rise in the state unemployment rate during the twelve months through August 2019.

Figure 3 shows the 30-plus-day past-due rate for August 2019 for 10 large metropolitan areas.3 The New York metro had the highest rate at 5.1%. Miami, with the second-highest rate at 5%, saw a sharp decrease in the overall delinquency rate, falling from 5.9% in August 2018. Houston also saw a large year-over-year decrease, from 5.3% in August 2018 to 4.7% in August 2019. San Francisco had the lowest 30-plus-day delinquency rate in August 2019 at 1.2%.

Figure 2. States with the Highest and Lowest Rate of Mortgages at Least 30 Days Past DueAugust 2019


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Figure 3. Percentage of Mortgages at Least 30 Days Pas Due for the Ten Largest Metropolitan AreasAugust 2019


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Source: CoreLogic

Four of the Five States continued from page 8

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Apartment buildings vary greatly by size and amenities. Of the more than 600,000 properties with at least five rental apartments across the U.S., about 70% have less than 25 apartments while there are nearly one thousand properties with more than a thousand rental homes. Larger and newer buildings often have various amenities too, such as a fitness center and parking.

Ownership of apartment buildings is widely dispersed, with about 300,000 different owners, or an average of two properties per owner. But at the same time, ownership of apartment units is concentrated with large property management and investment firms owning very large buildings. (Exhibit 1) An analysis of CoreLogic’s public records found that small properties tend to be owned by investors who owned just one or two properties: investors who owned no more than 50 rental apartments accounted for 85% of all owners but only 16% of all rental apartments. In contrast, investors who owned more than 50 units were 15% of all owners but had 84% of all rental units. And investors who held more than one thousand apartments numbered about 1% of all owners but held more than one-third of all apartments.

The ownership distribution of properties and apartment units also has changed very little in the last decade. We found these percentages also held true ten years ago.

We also found that mortgage finance varies by property size, with the least use for small and very large apartment buildings. (Exhibit 2) The placement of a mortgage to finance the property tended to be highest for properties with between 100 and 500 apartments.

Financing for small buildings with less than 25 homes tends to be conventional loans from a bank or private investor and may carry higher financing costs. Mortgage loans on mid-sized properties have access to secondary market funds which may increase access and reduce cost. Properties with more than a thousand units may be owned by a large investment or management firm that have a cheaper alternative to a mortgage to finance their property.

Multifamily Ownership and Mortgage Use by Property SizeSmall properties: often owned by single owner, less likely to have a mortgage

Dr. Frank NothaftExecutive, Chief Economist, Office of the Chief Economist

Frank Nothaft holds the title executive, chief economist for CoreLogic. He leads the Office of the Chief Economist and is responsible for analysis, commentary and forecasting trends in global real estate, insurance and mortgage markets.

Figure 2 Mortgage Finance Peaks for Buildings with 100–500 ApartmentsPercent of Properties with a Mortgage


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Figure 1. A Small Percentage of Multifamily Investors Own Most Appartments

Apartments Owned5 to 49 Units

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Share of all Multifamily Rental Apartments 16% 84%

Source: CoreLogic.

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In The News

CNBC – November 19 Renting a single-family house just got more expensiveThe supply of rental homes is shrinking, and that continues to push rent prices higher, particularly …

Reuters – October 29U.S. consumer confidence slips, housing stabilizingU.S. consumer confidence fell for a third straight month in October amid concerns about the short-term outlook for business conditions and job prospects,…

Wall Street Journal – October 29Housing Market Gaining Modest Strength, Indicators ShowThree indicators released on Tuesday show the housing market is gaining modest strength in the latter half of the year thanks to lower mortgage rates.

New York Times – October 31The Housing Market Needs More Than Low Mortgage RatesThe Federal Reserve is hoping that its latest interest-rate cut will help keep the economy safely at cruising altitude.

Bloomberg – October 31 Trump Accidentally Sparks U.S. Housing Rebound With Trade WarsDonald Trump, America’s first property-developer president, helped lift the housing market out of its recent slump. All it took was chaotic tweeting, and an unpredictable trade war that’s put investors on edge.

Realtor.com – November 13Thanks, Amazon! Home Price in These Washington, DC, Areas Are SkyrocketingThanks to Amazon and its incursion of well-paid employees, real estate prices in the online retailing behemoth’s hometown of Seattle have soared to …


Virginia), 22206 (Arlington, Virginia), 22201 (Arlington), 22311 (Alexandria) and 22204 (Arlington). Each of these has swung from having negative or near-flat price growth just before the HQ2 announcement to near double-digit appreciation in September of this year.

Analyzing just the top 10 zip codes isn’t a big enough sample to draw meaningful conclusions about the effects of HQ2 on the Washington, D.C. housing market. So, we took our research one step further and examined the correlation between zip code proximity to the HQ2 site and year-over-year change in the CoreLogic HPI on a month-by-month basis from September 2018 to September 2019. As you can see from the animation below, the correlation between a zip code’s home price appreciation rate and distance in miles from the HQ2 location was flat in September 2018 and remained so through February 2019, when average zip code appreciation was about 3%. From March 2019, you can see the price gradient rise more sharply the closer to HQ2 a zip code is. By September 2019, a clear negative gradient emerges whereby appreciation in zip codes near HQ2 was, on average, much higher than zip codes near the fringe.

While not casual, the anecdotal evidence from this blog does suggest the announcement of HQ is starting to show signs that house prices in Northern Virginian submarkets—in particular, those close to Crystal City—are rising at rates much faster than last year and faster than submarkets further away.

CORELOGIC ANNOUNCES GENERAL COUNSEL APPOINTMENT

On November 6, CoreLogic announced that Francis Aaron Henry joined the company as chief legal officer. In this role, Aaron will oversee all global legal and compliance functions for CoreLogic and serve on the company’s executive committee.

Aaron joins CoreLogic from MoneyGram International Inc., a leading global money transfer company, where he served as executive vice president, general counsel and corporate secretary for the past seven

years. Prior to MoneyGram, Aaron served in senior legal roles at Western Union and First Data Corporation, and he also held a series of progressively more responsible positions at several respected regional law firms.

“Aaron is a talented, high-impact leader and we are excited to have him on our executive team,” said Frank Martell, CEO of CoreLogic. “Aaron’s experience building high-performing teams, combined with a strong knowledge of global regulatory matters, compliance, government and external affairs, privacy and litigation management will serve him well in his new role.”

Mr. Henry earned his Bachelor of Arts in Economics from the University of Michigan and holds a Juris Doctorate from George Washington University Law School.

https://www.cnbc.com/2019/11/19/renting-a-single-family-house-just-got-more-expensive.html

https://www.reuters.com/article/us-usa-economy/u-s-consumer-confidence-slips-housing-stabilizing-idUSKBN1X822G?feedType=RSS&feedName=businessNews&utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+reuters%2FbusinessNews+%28Business+News%29&utm_content=Google+Feedfetcher

https://www.wsj.com/articles/home-price-growth-ticks-up-raising-hopes-for-rebound-11572354053

https://www.nytimes.com/2019/10/31/business/economy/fed-mortgage-rates.html

https://www.bloomberg.com/news/articles/2019-10-31/trump-s-trade-war-tumult-hands-surprise-boost-to-housing-market

https://www.realtor.com/news/trends/thanks-amazon-home-price-in-these-washington-dc-areas-are-skyrocketing/

12

Charts & Graphs

“Delinquency rates are at 14-year lows, reflecting a decade of tight underwriting standards, the benefits of prolonged low interest rates and the improved balance sheets of many households across the country. Despite this month’s near record-low serious delinquency rate, several metros in hurricane-ravaged areas of the Southeast have experienced higher delinquency rates of late. We expect to see these metros to return to pre-disaster delinquency rates over the next several months.”Frank Martell President and CEO of CoreLogic

10 Largest CBSA – Loan Performance Insights Report August 2019

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Rate August 2018 (%)

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Boston-Cambridge-Newton MA-NH 3.0 1.0 0.3 3.1 1.1 0.4

Chicago-Naperville-Elgin IL-IN-WI 4.2 1.6 0.6 4.2 1.8 0.6

Denver-Aurora-Lakewood CO 1.6 0.4 0.1 1.6 0.4 0.1

Houston-The Woodlands-Sugar Land TX 4.7 1.4 0.3 5.3 2.3 0.3

Las Vegas-Henderson-Paradise NV 3.2 1.3 0.5 3.6 1.7 0.7

Los Angeles-Long Beach-Anaheim CA 2.2 0.6 0.2 2.4 0.7 0.2

Miami-Fort Lauderdale-West Palm Beach FL 5.0 1.9 0.9 5.9 3.2 1.0

New York-Newark-Jersey City NY-NJ-PA 5.1 2.5 1.2 5.5 2.9 1.4

San Francisco-Oakland-Hayward CA 1.2 0.3 0.1 1.4 0.4 0.1

Washington-Arlington-Alexandria DC-VA-MD-WV 3.3 1.2 0.3 3.4 1.3 0.4

Source: CoreLogic August 2019

Overview of Loan PerformanceNational Delinquency News


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0.6

0.3

0.9 1.0

0.4

3.9

1.8

0.6

0.3

1.0 1.2

0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

Perc

enta

ge R

ate

2.78x5.93; no legend, no horizontal axis labels; 7ptloan performance aug 2019: national overview

90-119 DaysPast Due

120+ DaysPast Due

60-89 DaysPast Due

30 Days or MorePast Due

30-59 DaysPast Due

90+ Days(not in fcl)

InForeclosure

August 2018August 2019

Source: CoreLogic August 2019

13

State

Month- Over-Month

Percent Change Year-Over-Year

Forecasted Month- Over-Month

Percent Change

Forecasted Year-Over-Year Percent Change

Alabama −0.2% 4.1% 0.3% 5.3%

Alaska 0.1% 2.8% 0.4% 6.7%

Arizona 0.5% 5.8% 0.3% 5.1%

Arkansas 0.0% 3.7% 0.3% 4.5%

California −0.1% 1.7% 0.3% 9.4%

Colorado 0.2% 4.5% 0.2% 4.7%

Connecticut 0.0% 0.0% 0.3% 7.0%

Delaware 0.2% 2.1% 0.3% 4.6%

District of Columbia −0.5% 2.7% 0.3% 4.5%

Florida 0.3% 3.9% 0.3% 5.7%

Georgia 0.2% 4.3% 0.3% 4.8%

Hawaii 0.0% 1.8% 0.1% 4.9%

Idaho 1.1% 11.8% 0.5% 5.0%

Illinois −0.2% 1.2% 0.3% 6.4%

Indiana 0.8% 6.7% 0.4% 5.4%

Iowa 0.1% 2.7% 0.3% 5.5%

Kansas 0.2% 5.0% 0.3% 4.9%

Kentucky 0.2% 3.9% 0.3% 4.6%

Louisiana 0.0% 1.4% 0.2% 2.7%

Maine 0.1% 8.0% 0.3% 6.4%

Maryland −0.2% 2.1% 0.2% 4.6%

Massachusetts −0.1% 2.9% 0.3% 6.7%

Michigan 0.5% 5.0% 0.4% 7.4%

Minnesota 0.0% 4.4% 0.2% 4.1%

Mississippi 0.3% 4.9% 0.3% 4.3%

Missouri 0.6% 5.2% 0.3% 5.5%

Montana 0.6% 6.1% 0.4% 5.0%

Nebraska 0.1% 4.5% 0.2% 4.5%

Nevada 0.0% 3.5% 0.2% 8.6%

New Hampshire 0.5% 5.2% 0.4% 7.1%

New Jersey 0.5% 2.1% 0.4% 6.5%

New Mexico 0.5% 7.3% 0.4% 4.7%

New York 0.7% 0.9% 0.3% 6.0%

North Carolina 0.3% 4.4% 0.3% 4.6%

North Dakota −0.7% 1.0% 0.3% 4.4%

Ohio 0.4% 5.2% 0.3% 5.1%

Oklahoma 0.5% 2.9% 0.3% 3.9%

Oregon 0.2% 3.9% 0.3% 6.4%

Pennsylvania −0.5% 3.0% 0.2% 5.5%

Rhode Island 0.9% 4.5% 0.4% 5.7%

South Carolina 0.5% 3.8% 0.3% 5.5%

South Dakota 0.1% 7.0% 0.3% 4.5%

Tennessee 0.6% 5.5% 0.3% 4.4%

Texas −0.3% 2.9% 0.1% 2.1%

Utah 0.6% 8.0% 0.3% 4.7%

Vermont 0.4% 3.6% 0.0% 4.3%

Virginia 0.0% 3.5% 0.3% 5.1%

Washington 0.0% 4.2% 0.2% 5.5%

West Virginia 0.9% 3.3% 0.3% 5.2%

Wisconsin 0.1% 5.7% 0.2% 5.0%

Wyoming 1.0% 5.1% 0.4% 3.1%

Source: CoreLogic September 2019

Home Price Index State-Level Detail — Combined Single Family Including DistressedSeptember 2019

14

Charts & Graphs (continued)

“Mortgage rates were a full percentage point lower this September compared to a year ago, boosting affordability for first-time buyers and supporting a rise in homeownership. In addition to lower interest rates, personal income grew faster than home prices during the past year. This provided an additional lift for first-time buyer affordability and helped to boost the homeownership rate to the highest level in more than five years.”Dr. Frank Nothaft Chief Economist for CoreLogic

Home Price IndexPercentage Change Year Over Year


-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019Including Distressed

3.04x5.67; 7pt typehpi as of sept 2019

Source: CoreLogic September 2019

15

CoreLogic HPI® Market Condition OverviewSeptember 2019

Source: CoreLogic CoreLogic HPI Single Family Combined Tier, data through September 2019. CoreLogic HPI Forecasts Single Family Combined Tier, starting October 2019.

Legend

■ Normal

■ Overvalued

■ Undervalued

CoreLogic HPI® Market Condition OverviewSeptember 2024

Source: CoreLogic CoreLogic HPI Single Family Combined Tier, data through September 2019. CoreLogic HPI Forecasts Single Family Combined Tier, starting October 2019.

Legend

■ Normal

■ Overvalued

■ Undervalued

16

Variable Definition

Total Sales The total number of all home-sale transactions during the month.

Total Sales 12-Month sum The total number of all home-sale transactions for the last 12 months.

Total Sales YoY Change 0.3%

12-Month sum Percentage increase or decrease in current 12 months of total sales over the prior 12 months of total sales

New Home Sales The total number of newly constructed residentail housing units sold during the month.

New Home Sales 0.9%

Median Price The median price for newly constructed residential housing units during the month.

Existing Home Sales The number of previously constucted homes that were sold to an unaffiliated third party. DOES NOT INCLUDE REO AND SHORT SALES.

REO Sales Number of bank owned properties that were sold to an unaffiliated third party.

REO Sales Share The number of REO Sales in a given month divided by total sales.

REO Price Discount The average price of a REO divided by the average price of an existing-home sale.

REO Pct The count of loans in REO as a percentage of the overall count of loans for the reporting period.

Short Sales The number of short sales. A short sale is a sale of real estate in which the sale proceeds fall short of the balance owed on the property's loan.

Short Sales Share The number of Short Sales in a given month divided by total sales.

Short Sale Price Discount The average price of a Short Sale divided by the average price of an existing-home sale.

Short Sale Pct The count of loans in Short Sale as a percentage of the overall count of loans for the month.

Distressed Sales Share The percentage of the total sales that were a distressed sale (REO or short sale).

Distressed Sales Share 0.4%

(sales 12-Month sum) The sum of the REO Sales 12-month sum and the Short Sales 12-month sum divided by the total sales 12-month sum.

HPI MoM Percent increase or decrease in HPI single family combined series over a month ago.

HPI YoY Percent increase or decrease in HPI single family combined series over a year ago.

HPI MoM Excluding Distressed Percent increase or decrease in HPI single family combined excluding distressed series over a month ago.

HPI YoY Excluding Distressed Percent increase or decrease in HPI single family combined excluding distressed series over a year ago.

HPI Percent Change 0.2%

from Peak Percent increase or decrease in HPI single family combined series from the respective peak value in the index.

90 Days + DQ Pct The percentage of the overall loan count that are 90 or more days delinquent as of the reporting period. This percentage includes loans that are in foreclosure or REO.

Stock of 90+ Delinquencies YoY Chg Percent change year-over-year of the number of 90+ day delinquencies in the current month.

Foreclosure Pct The percentage of the overall loan count that is currently in foreclosure as of the reporting period.

Percent Change Stock of Foreclosures from Peak

Percent increase or decrease in the number of foreclosures from the respective peak number of foreclosures.

Pre-foreclosure Filings The number of mortgages where the lender has initiated foreclosure proceedings and it has been made known through public notice (NOD).

Completed Foreclosures A completed foreclosure occurs when a property is auctioned and results in either the purchase of the home at auction or the property is taken by the lender as part of their Real Estate Owned (REO) inventory.

Negative Equity Share The percentage of mortgages in negative equity. The denominator for the negative equity percent is based on the number of mortgages from the public record.

Negative Equity The number of mortgages in negative equity. Negative equity is calculated as the difference between the current value of the property and the origination value of the mortgage. If the mortgage debt is greater than the current value, the property is considered to be in a negative equity position. We estimate current UPB value, not origination value.

Months' Supply of Distressed Homes 0.4%

(total sales 12-Month avg) The months it would take to sell off all homes currently in distress of 90 days delinquency or greater based on the current sales pace.

Price/Income Ratio CoreLogic HPI™ divided by Nominal Personal Income provided by the Bureau of Economic Analysis and indexed to January 1976.

Conforming Prime Serious Delinquency Rate

The rate serious delinquency mortgages which are within the legislated purchase limits of Fannie Mae and Freddie Mac. The conforming limits are legislated by the Federal Housing Finance Agency (FHFA).

Jumbo Prime Serious Delinquency Rate

The rate serious delinquency mortgages which are larger than the legislated purchase limits of Fannie Mae and Freddie Mac. The conforming limits are legislated by the Federal Housing Finance Agency (FHFA).

17

Variable Definition

Total Sales The total number of all home-sale transactions during the month.

Total Sales 12-Month sum The total number of all home-sale transactions for the last 12 months.

Total Sales YoY Change 0.3%

12-Month sum Percentage increase or decrease in current 12 months of total sales over the prior 12 months of total sales

New Home Sales The total number of newly constructed residentail housing units sold during the month.

New Home Sales 0.9%

Median Price The median price for newly constructed residential housing units during the month.

Existing Home Sales The number of previously constucted homes that were sold to an unaffiliated third party. DOES NOT INCLUDE REO AND SHORT SALES.

REO Sales Number of bank owned properties that were sold to an unaffiliated third party.

REO Sales Share The number of REO Sales in a given month divided by total sales.

REO Price Discount The average price of a REO divided by the average price of an existing-home sale.

REO Pct The count of loans in REO as a percentage of the overall count of loans for the reporting period.

Short Sales The number of short sales. A short sale is a sale of real estate in which the sale proceeds fall short of the balance owed on the property's loan.

Short Sales Share The number of Short Sales in a given month divided by total sales.

Short Sale Price Discount The average price of a Short Sale divided by the average price of an existing-home sale.

Short Sale Pct The count of loans in Short Sale as a percentage of the overall count of loans for the month.

Distressed Sales Share The percentage of the total sales that were a distressed sale (REO or short sale).

Distressed Sales Share 0.4%

(sales 12-Month sum) The sum of the REO Sales 12-month sum and the Short Sales 12-month sum divided by the total sales 12-month sum.

HPI MoM Percent increase or decrease in HPI single family combined series over a month ago.

HPI YoY Percent increase or decrease in HPI single family combined series over a year ago.

HPI MoM Excluding Distressed Percent increase or decrease in HPI single family combined excluding distressed series over a month ago.

HPI YoY Excluding Distressed Percent increase or decrease in HPI single family combined excluding distressed series over a year ago.

HPI Percent Change 0.2%

from Peak Percent increase or decrease in HPI single family combined series from the respective peak value in the index.

90 Days + DQ Pct The percentage of the overall loan count that are 90 or more days delinquent as of the reporting period. This percentage includes loans that are in foreclosure or REO.

Stock of 90+ Delinquencies YoY Chg Percent change year-over-year of the number of 90+ day delinquencies in the current month.

Foreclosure Pct The percentage of the overall loan count that is currently in foreclosure as of the reporting period.

Percent Change Stock of Foreclosures from Peak

Percent increase or decrease in the number of foreclosures from the respective peak number of foreclosures.

Pre-foreclosure Filings The number of mortgages where the lender has initiated foreclosure proceedings and it has been made known through public notice (NOD).

Completed Foreclosures A completed foreclosure occurs when a property is auctioned and results in either the purchase of the home at auction or the property is taken by the lender as part of their Real Estate Owned (REO) inventory.

Negative Equity Share The percentage of mortgages in negative equity. The denominator for the negative equity percent is based on the number of mortgages from the public record.

Negative Equity The number of mortgages in negative equity. Negative equity is calculated as the difference between the current value of the property and the origination value of the mortgage. If the mortgage debt is greater than the current value, the property is considered to be in a negative equity position. We estimate current UPB value, not origination value.

Months' Supply of Distressed Homes 0.4%

(total sales 12-Month avg) The months it would take to sell off all homes currently in distress of 90 days delinquency or greater based on the current sales pace.

Price/Income Ratio CoreLogic HPI™ divided by Nominal Personal Income provided by the Bureau of Economic Analysis and indexed to January 1976.

Conforming Prime Serious Delinquency Rate

The rate serious delinquency mortgages which are within the legislated purchase limits of Fannie Mae and Freddie Mac. The conforming limits are legislated by the Federal Housing Finance Agency (FHFA).

Jumbo Prime Serious Delinquency Rate

The rate serious delinquency mortgages which are larger than the legislated purchase limits of Fannie Mae and Freddie Mac. The conforming limits are legislated by the Federal Housing Finance Agency (FHFA).

Source: CoreLogicThe data provided is for use only by the primary recipient or the primary recipient's publication or broadcast. This data may not be re-sold, republished or licensed to any other source, including publications and sources owned by the primary recipient's parent company without prior written permission from CoreLogic. Any CoreLogic data used for publication or broadcast, in whole or in part, must be sourced as coming from CoreLogic, a data and analytics company. For use with broadcast or web content, the citation must directly accompany first reference of the data. If the data is illustrated with maps, charts, graphs or other visual elements, the CoreLogic logo must be included on screen or website. For questions, analysis or interpretation of the data, contact CoreLogic at [email protected]. Data provided may not be modified without the prior written permission of CoreLogic. Do not use the data in any unlawful manner. This data is compiled from public records, contributory databases and proprietary analytics, and its accuracy is dependent upon these sources.

For more information please call 866.774.3282The MarketPulse is a newsletter published by CoreLogic, Inc. ("CoreLogic"). This information is made available for informational purposes only and is not intended to provide specific commercial, financial or investment advice. CoreLogic disclaims all express or implied representations, warranties and guaranties, including implied warranties of merchantability, fitness for a particular purpose, title, or non-infringement. Neither CoreLogic nor its licensors make any representations, warranties or guaranties as to the quality, reliability, suitability, truth, accuracy, timeliness or completeness of the information contained in this newsletter. CoreLogic shall not be held responsible for any errors, inaccuracies, omissions or losses resulting directly or indirectly from your reliance on the information contained in this newsletter.

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the marketpulse - corelogic · 2019-11-26 · volume 8, issue 11 november 2019 data as of september...

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