Median-Priced Homes Not Affordable for Average Wage Earners in 68 Percent of U.S. Housing Markets

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73 Percent of Markets Less Affordable Than a Year Ago;
Eight of 10 Highest-Priced Counties Post Negative Net Migration in 2017

IRVINE, Calif. – March 29, 2018 — ATTOM Data Solutions, curator of the nation’s premier property database, today released its Q1 2018 U.S. Home Affordability Report, which shows that median home prices in Q1 2018 were not affordable for average wage earners in 304 of 446 U.S. counties analyzed in the report (68 percent).

The report determined affordability for average wage earners by calculating the amount of income needed to make monthly house payments — including mortgage, property taxes and insurance — on a median-priced home, assuming a 3 percent down payment and a 28 percent maximum “front-end” debt-to-income ratio. That required income was then compared to annualized average weekly wage data from the Bureau of Labor Statistics (see full methodology below).

The 304 counties where a median-priced home in the first quarter was not affordable for average wage earners included Los Angeles County, California; Maricopa County (Phoenix), Arizona; San Diego County, California; Orange County, California; and Miami-Dade County, Florida.

The 142 counties (32 percent of the 446 counties analyzed in the report) where a median-priced home in the first quarter was still affordable for average wage earners included Cook County (Chicago), Illinois; Harris County (Houston), Texas; Dallas County, Texas; Wayne County (Detroit), Michigan; and Philadelphia County, Pennsylvania.

“Coastal markets are the epicenter of the U.S. home affordability crisis, but affordability aftershocks are now being felt further inland as housing refugees migrate from the high-cost coastal markets to lower-priced markets in the middle of the country where good jobs are available,” said Daren Blomquist, senior vice president with ATTOM Data Solutions. “That in turn is pushing home prices above historically normal affordability limits in those middle-America markets.”

Eight of top 10 highest-priced counties post declines in net migration in 2017

The report also incorporated recently released Census bureau data showing net migration of population in 2017 at the county level. Net migration is the difference between the number of people coming to a county and the number of people leaving a county, including both domestic and international migration.

Eight of the top 10 counties with the highest median home prices in Q1 2018 posted negative net migration in 2017: Kings County (Brooklyn), New York (25,484 net migration decrease); Santa Clara County (San Jose), California (5,559 net migration decrease); New York County (Manhattan), New York (3,762 net migration decrease); Orange County, California (3,750 net migration decrease); and San Mateo, Marin, Napa and Santa Cruz counties in Northern California.

The two exceptions among the top 10 highest-priced counties were San Francisco County, California (5,555 net migration increase); and Alameda County, California, also in the San Francisco metro area (1,286 net migration increase) — both of which had large positive international migration outweighing negative domestic migration.

Among the 446 counties analyzed in the affordability report, those with the largest net migration increases in 2017 were Maricopa County (Phoenix), Arizona (49,770 net migration increase); Clark County (Las Vegas), Nevada (36,635 net migration increase); Riverside County, California, in the “Inland Empire” of Southern California (23,397 net migration increase); Denton County, Texas in the Dallas metro area (21,333 net migration increase); and Hillsborough County, Florida, in the Tampa-St. Petersburg metro area (20,603 net migration increase). Median home prices in those five counties ranged from $197,000 in Hillsborough County to $360,000 in Riverside County.

“Home affordability continues to be a symptom relating to a cultural divide of wage earners,” said Michael Mahon, president at First Team Real Estate, covering Southern California. “Median wage earners are finding coastal communities unaffordable across Southern California, which is driving migration of the consumer population to create housing demand booms in such counties as Riverside County — recently recognized as one of the fastest growing counties in the state.”

41 percent of markets less affordable than historic averages

Among the 446 counties analyzed in the report, 181 (41 percent) were less affordable than their historic affordability averages in the first quarter of 2018, up from 35 percent of counties in the previous quarter and up from 24 percent of counties in the first quarter of 2017.

Counties that were less affordable than their historic affordability averages included Los Angeles County, California; Harris County (Houston), Texas; San Diego County, California; Kings County (Brooklyn), New York; and Dallas County, Texas.

Counties with the lowest affordability index (least affordable relative to their own historic affordability averages) were Santa Fe County, New Mexico (72); Grayson County, Texas in the Sherman-Denison metro area (75); Adams County, Colorado in the Denver metro area (77); Ellis County, Texas in the Dallas metro area (78); and Denver County, Colorado (79).

Most affordable counties in Atlantic City, Baltimore, Philadelphia, Cleveland

Among the 446 counties analyzed in the report, 265 (59 percent) were more affordable than their historic affordability averages in the first quarter of 2018, including Cook County (Chicago), Illinois; Maricopa County (Phoenix), Arizona; Orange County, California; Miami-Dade County, Florida; and King County (Seattle), Washington.

Counties with the highest affordability index (most affordable relative to their own historic affordability averages) were Atlantic County (Atlantic City), New Jersey (223); Baltimore City, Maryland (156); Camden County, New Jersey in the Philadelphia metro area (153); Cuyahoga County (Cleveland), Ohio (153); and Howard County, Maryland in the Baltimore metro area (150).

“Affordable home prices that are still accessible to the average wage earner are helping to spur positive net migration to some Ohio counties, particularly in the Columbus and Cincinnati metro areas,” said Matthew L. Watercutter, broker of record for HER Realtors, covering the Dayton, Columbus and Cincinnati markets in Ohio. “But affordability could start to become a bigger challenge in Ohio if home price appreciation continues to outpace wage growth in most of the state’s markets as it did in the first quarter.”

73 percent of markets post worsening affordability compared to year ago

A total of 326 of the 446 counties analyzed in the report (73 percent) posted a year-over-year decrease in their affordability index, meaning that home prices were less affordable than a year ago, including Los Angeles County, California; San Diego County, California; Miami-Dade County, Florida; Queens County, New York; and Riverside County, California.

A total of 120 of the 446 counties analyzed in the report (27 percent) posted a year-over-year increase in affordability index, meaning that home prices were more affordable than a year ago, including Cook County (Chicago), Illinois; Harris County (Houston), Texas; Maricopa County (Phoenix); Arizona; Orange County, California; and Kings County (Brooklyn), New York.

Highest share of income needed to buy in Brooklyn, Santa Cruz, San Francisco, Maui

Nationwide an average wage earner would need to spend 29.1 percent of his or her income to buy a median-priced home in the first quarter of 2018, slightly below the historic average of 29.6 percent of income.

Counties where an average wage earner would need to spend the highest share of income to buy a median-priced home in Q1 2018 were Kings County (Brooklyn), New York (119.0 percent); Santa Cruz County, California (108.8 percent); Marin County, California in the San Francisco metro area (106.3 percent); Maui County, Hawaii (94.1 percent); and New York County (Manhattan), New York (92.5 percent).

Counties where an average wage earner would need to spend the lowest share of income to buy a median-priced home were Baltimore City, Maryland (10.2 percent); Bibb County (Macon), Georgia (11.0 percent); Wayne County (Detroit), Michigan (11.3 percent); Clayton County, Georgia in the Atlanta metro area (12.0 percent); and Rock Island County (Quad Cities), Illinois (13.4 percent).

Home price appreciation outpacing wage growth in 83 percent of markets

Home price appreciation outpaced average weekly wage growth in 370 of the 446 counties analyzed in the report (83 percent), including Los Angeles County, California; Harris County (Houston), Texas; Maricopa County (Phoenix), Arizona; San Diego County, California; and Orange County, California.

Average weekly wage growth outpaced home price appreciation in 76 of the 446 counties analyzed in the report (17 percent), including Cook County (Chicago), Illinois; Duval County (Jacksonville), Florida; San Francisco County, California; Suffolk County (Boston), Massachusetts; and Lake County, Illinois in the Chicago metro area.

Report Methodology
The ATTOM Data Solutions U.S. Home Affordability Index analyzes median home prices derived from publicly recorded sales deed data collected by ATTOM Data Solutions and average wage data from the U.S. Bureau of Labor Statistics in 446 U.S. counties with a combined population of more than 221 million. The affordability index is based on the percentage of average wages needed to make monthly house payments on a median-priced home with a 30-year fixed rate mortgage and a 3 percent down payment, including property taxes, home insurance and mortgage insurance. Average 30-year fixed interest rates from the Freddie Mac Primary Mortgage Market Survey were used to calculate the monthly house payments. Only counties with sufficient home price and wage data quarterly back to Q1 2005 were used in the analysis.

The report determined affordability for average wage earners by calculating the amount of income needed to make monthly house payments — including mortgage, property taxes and insurance — on a median-priced home with, assuming a 3 percent down payment and a 28 percent maximum “front-end” debt-to-income ratio (see full methodology below).

For instance, the nationwide median home price of $229,500 in the first quarter of 2018 would require an annual gross income of $57,009 for a buyer putting 3 percent down and not exceeding the recommended “front-end” debt-to-income ratio of 28 percent — meaning the buyer would not be spending more than 28 percent of his or her income on the house payment, including mortgage, property taxes and insurance. That required income is higher than the $54,847 annual income earned by an average wage earner based on the most recent average weekly wage data available from the Bureau of Labor Statistics, making a median-priced home nationwide not affordable for an average wage earner.

About ATTOM Data Solutions
ATTOM Data Solutions blends property tax, deed, mortgage, foreclosure, environmental risk, natural hazard, and neighborhood data for more than 155 million U.S. residential and commercial properties multi-sourced from more than 3,000 U.S. counties. A rigorous data management process involving more than 20 steps validates, standardizes and enhances the data collected by ATTOM, assigning each property record with a persistent, unique ID — the ATTOM ID. With more than 29.6 billion rows of transactional-level data and more than 7,200 discrete data attributes, the 9TB ATTOM data warehouse powers real estate transparency for innovators, entrepreneurs, disrupters, developers, marketers, policymakers, and analysts through flexible delivery solutions, including bulk file licenses, APIs and customized reports.

Media Contact:
Christine Stricker
949.748.8428
christine.stricker@attomdata.com

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Please contact us if you have questions about the underlying data referenced in this article, or would like to have access to that data in the form of custom reports, API or bulk files.

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