Mortgages

Where Are Homeowners Most Likely to Default?

According to CoreLogic, just 0.6% of mortgaged homes in the U.S. were in foreclosure as of March 2018. But with the current bull market entering a record tenth straight year, many experts believe that the economy may be overdue for a recession. To find out where homeowners are most exposed to the effects of another downturn, our team of mortgage specialists studied over 200 major U.S. cities to see which areas faced the highest risk of default.

We reviewed multiple studies and research reports to identify the root causes of mortgage default and used those variables to calculate risk scores for 200 Census-designated metropolitan statistical areas (MSAs). We ranked the resulting scores both nationally and by region.

Key Takeaways

  • Metropolitan areas in the South were most at risk, accounting for nine of the 10 U.S. cities where homeowners were most likely to default.
  • Among individual states, Texas was home to the 3 highest-risk cities/MSAs in the nation.
  • Visalia-Porterville, California; Flint, Michigan; McAllen-Edinburg-Mission, Texas and Atlantic City-Hammonton, New Jersey were most at risk for default within their respective regions.
  • MSAs in the West fared best overall, boasting eight of the 10 cities with the lowest default risk in the country.
Map of Cites Most at Risk for Mortgage Default

We also ranked the default risk of cities by region, including the South, West, Midwest and Northeast as defined by the U.S. Census Bureau. We've included a full list of the MSAs included in our study as well as a synopsis of our methodology.

Where Are Homeowners Most Likely to Default?

We evaluated areas in the United States where homeowners were most likely to default if we experienced a severe economic downturn. We scored urban locations across the United States based on several key characteristics, including mortgage delinquency rates, unemployment, monthly cash flows and changes in home values relative to mortgage debt outstanding.

The use of these variables was inspired by study findings from the National Bureau of Economic Research, as well publications from both the Federal Reserve Bank and Financial Management Association International. The top 10 most at-risk cities in the nation are presented in the table below.

MSAs Where Homeowners Are Most at Risk for Default

RankMSADelinquencyUnemploymentCash FlowValue/Debt
1McAllen-Edinburg-Mission, TX25219
2Brownsville-Harlingen, TX37120
3Laredo, TX1100456
4Mobile, AL5192640
5Visalia-Porterville, CA8019120
6Gulfport-Biloxi-Pascagoula, MS6211245
7Macon-Bibb County, GA778106
8Fayetteville, NC351782
9Huntington-Ashland, WV-KY-OH12132549
10Shreveport-Bossier City, LA1092889

Cities With Highest Default Risk in the South

The three highest-risk MSAs in our study are located in Texas and are concentrated along the state's border with Mexico. These cities are characterized by high delinquency rates, coupled with low monthly cash flows after subtracting out costs of living. In fact, as many as 7.3% of all mortgages in Laredo, Texas, were behind on their payments by 30 to 89 days.

Highest Default Risk in the South

RankMarket NameDelinquencyUnemploymentCash FlowValue/Debt
1McAllen-Edinburg-Mission, TX25219
2Brownsville-Harlingen, TX37120
3Laredo, TX1100456
4Mobile, AL5192640
5Gulfport-Biloxi-Pascagoula, MS6211245

McAllen-Edinburg-Mission saw overall unemployment rates that were 86% higher than the national average. This problem was further exacerbated by low average incomes in the Brownsville-Harlingen area, which saw per-capita salaries as low as half the national average.

Cities With Highest Default Risk in the Midwest

The riskiest MSAs in the Midwest occupy the heart of the Rust Belt, close to the coasts of Lake Erie and Lake Michigan. This area is marred by high unemployment and stagnant/declining home values; Flint, Michigan, for example, featured an unemployment rate that was 67% above the national average, as of July 2018.

Highest Default Risk in the Midwest

RankMarket NameDelinquencyUnemploymentCash FlowValue/Debt
1Flint, MI32103258
2Youngstown-Warren-Boardman, OH-PA55114226
3Toledo, OH65225838
4Cleveland-Elyria, OH85189043
5Rockford, IL8128977

It's worth noting that these figures don't account for discouraged workers who may have given up looking for jobs, so the true extent of the number of individuals out of work is likely understated. Rockford, Illinois, saw anemic growth in its real estate market, with home values increasing by an inflation-adjusted 0.5% over the past five years. Compare this figure against the average national rate of real estate appreciation, which typically ranges from 5% to 10% annually.

Cities With Highest Default Risk in the West

Four of the five most at-risk MSAs in the West all hail from California, which also happens to house some of the wealthiest cities in the nation. The highest-risk cities are located further inland, close to Yosemite and Death Valley. Their declining status stands in stark contrast to their wealthier counterparts along the Pacific coast, and show a stunning discrepancy in wealth distribution across the state.

Highest Default Risk in the West

RankMarket NameDelinquencyUnemploymentCash FlowValue/Debt
1Visalia-Porterville, CA8019120
2Fresno, CA114416117
3Bakersfield, CA56269140
4Merced, CA15133180
5Tucson, AZ104502767

Unlike their Silicon Valley counterparts, these areas boast high rates of unemployment and low incomes relative to outstanding home values. Visalia-Porterville, California, has the highest unemployment rate in the nation of 9.3%, with Bakersfield, California, close behind at 8.2%. While some of these regions have also seen moderate growth in home prices, low levels of disposable income have effectively priced out many area residents.

Cities With Highest Default Risk in the Northeast

Residents of the Greater Atlantic City metropolitan area were most at risk for mortgage default. Home values in the area actually declined relative to the total amount of mortgage debt outstanding over the past five years, likely increasing the number of underwater home loans in the area. High unemployment rates, coupled with a city council on the verge of default, could be a recipe for disaster if another economic downturn were to occur.

Highest Default Risk in the Northeast

RankMarket NameDelinquencyUnemploymentCash FlowValue/Debt
1Atlantic City-Hammonton, NJ3114535
2Scranton-Wilkes-Barre-Hazleton, PA1524669
3Erie, PA21364810
4Springfield, MA46318321
5New Haven-Milford, CT24561293

While mortgage lending has slowed elsewhere in the United States, lending activity actually declined across the Northeast in the early part of 2018. This will likely have a negative impact on home prices throughout the region. The Greater New Haven area saw its average area home value decline by 1.6% over the past five years, while home prices in Erie, Pennsylvania, increased by a measly 1.4%, after accounting for inflation.

Full List of Cities

In our analysis of areas most at-risk for homeowner default, we reviewed data from 510 cities and MSAs across the United States with available housing, income and delinquency data. We then distilled the top 200 most populous cities/MSAs in the country, with communities of 221,000 or above, and ranked them in order of risk score. Each individual score was also ranked, including delinquency, unemployment, cash flow and change in market value over debt.

RankMarket NameDelinquencyUnemploymentCash FlowValue/Debt
1McAllen-Edinburg-Mission, TX25219
2Brownsville-Harlingen, TX37120
3Laredo, TX1100456
4Mobile, AL5192640
5Visalia-Porterville, CA8019120
6Gulfport-Biloxi-Pascagoula, MS6211245
7Macon-Bibb County, GA778106
8Fayetteville, NC351782
9Huntington-Ashland, WV-KY-OH12132549
10Shreveport-Bossier City, LA1092889
11El Paso, TX8631818
12Jackson, MS4483899
13Hickory-Lenoir-Morganton, NC91322311
14Flint, MI32103258
15Fort Smith, AR-OK17101644
16Atlantic City-Hammonton, NJ3114535
17Columbus, GA-AL4135759
18Scranton-Wilkes-Barre-Hazleton, PA1524669
19Youngstown-Warren-Boardman, OH-PA55114226
20New Orleans-Metairie, LA111633153
21Erie, PA21364810
22Beaumont-Port Arthur, TX1987276
23Fresno, CA114416117
24Bakersfield, CA56269140
25Montgomery, AL20794416
26Merced, CA15133180
27Lafayette, LA281545113
28Memphis, TN-MS-AR14405964
29Clarksville, TN-KY45263737
30Kingsport-Bristol-Bristol, TN-VA43941735
31Greensboro-High Point, NC26644078
32Spartanburg, SC131534350
33Tallahassee, FL631021433
34Waco, TX231083488
35Toledo, OH65225838
36Ocala, FL116411195
37Lakeland-Winter Haven, FL624924119
38Winston-Salem, NC361094947
39Springfield, MA46318321
40Augusta-Richmond County, GA-SC33658031
41Tuscaloosa, AL49425192
42Corpus Christi, TX422560122
43Tyler, TX181336571
44New Haven-Milford, CT24561293
45Tucson, AZ104502767
46Binghamton, NY9237754
47Utica-Rome, NY73665434
48Lubbock, TX301544183
49Albuquerque, NM103385229
50Wilmington, NC581205628
51Killeen-Temple, TX398855127
52Yakima, WA156323141
53Cleveland-Elyria, OH85189043
54Deltona-Daytona Beach-Ormond Beach, FL138951575
55Chico, CA155275151
56Rockford, IL8128977
57Dayton, OH96437827
58Canton-Massillon, OH70339630
59Hagerstown-Martinsburg, MD-WV275712060
60Birmingham-Hoover, AL221109298
61Columbia, SC1615510154
62Roanoke, VA54175708
63South Bend-Mishawaka, IN-MI591116290
64Baton Rouge, LA2623139121
65York-Hanover, PA47891421
66Knoxville, TN4512164123
67Spokane-Spokane Valley, WA170292996
68Myrtle Beach-Conway-North Myrtle Beach, SC-NC1271033969
69Evansville, IN-KY761575768
70Wichita, KS90808436
71Reading, PA408113525
72Greenville-Anderson-Mauldin, SC501587384
73Asheville, NC11215919125
74Chattanooga, TN-GA6410476112
75Little Rock-North Little Rock-Conway, AR491607493
76Savannah, GA721348932
77Tulsa, OK3413993102
78Stockton-Lodi, CA1331250168
79Allentown-Bethlehem-Easton, PA-NJ524414912
80Salisbury, MD-DE1055810223
81Pensacola-Ferry Pass-Brent, FL831128742
82College Station-Bryan, TX11916113149
83Buffalo-Cheektowaga-Niagara Falls, NY745910974
84Kalamazoo-Portage, MI936710339
85Akron, OH1014510557
86Gainesville, FL1301404679
87Modesto, CA119681177
88Duluth, MN-WI1211418817
89Champaign-Urbana, IL142607961
90Port St. Lucie, FL1444622170
91Rochester, NY758212646
92Springfield, MO11816836108
93Davenport-Moline-Rock Island, IA-IL7213513314
94Philadelphia-Camden-Wilmington, PA-NJ-DE-MD375116572
95Eugene, OR1876821141
96San Antonio-New Braunfels, TX29148121139
97Pittsburgh, PA6069137107
98Virginia Beach-Norfolk-Newport News, VA-NC5216212770
99Syracuse, NY668314348
100Peoria, IL983415822
101Louisville/Jefferson County, KY-IN8270130101
102Providence-Warwick, RI-MA899098142
103Lansing-East Lansing, MI1466110666
104Topeka, KS12310510765
105Amarillo, TX38178124106
106Tampa-St. Petersburg-Clearwater, FL13912247154
107Charlotte-Concord-Gastonia, NC-SC53123138114
108Oklahoma City, OK58163113137
109New York-Newark-Jersey City, NY-NJ-PA1097191155
110Lafayette-West Lafayette, IN1151569981
111Riverside-San Bernardino-Ontario, CA1005277179
112Harrisburg-Carlisle, PA10312415024
113Fort Wayne, IN9716611886
114Indianapolis-Carmel-Anderson, IN8416413282
115Cincinnati, OH-KY-IN1108414577
116Huntsville, AL8611315551
117Lancaster, PA8713614855
118Lexington-Fayette, KY127114112124
119Las Vegas-Henderson-Paradise, NV1524768171
120Prescott, AZ1857235167
121Palm Bay-Melbourne-Titusville, FL16411567148
122Miami-Fort Lauderdale-West Palm Beach, FL12010620191
123Orlando-Kissimmee-Sanford, FL13614271157
124Detroit-Warren-Dearborn, MI11130122169
125Milwaukee-Waukesha-West Allis, WI16114311163
126Durham-Chapel Hill, NC106144117138
127Jacksonville, FL132125114133
128Norwich-New London, CT7991166104
129Salem, OR17185110110
130Worcester, MA-CT779217285
131Columbus, OH10896140128
132St. Louis, MO-IL101126147103
133Charleston-North Charleston, SC61176136145
134Albany-Schenectady-Troy, NY12812717115
135Cape Coral-Fort Myers, FL16812863165
136Atlanta-Sandy Springs-Roswell, GA67129157144
137Fayetteville-Springdale-Rogers, AR-MO129183100135
138Houston-The Woodlands-Sugar Land, TX7973151162
139Richmond, VA8816916373
140Phoenix-Mesa-Scottsdale, AZ14186119163
141Olympia-Tumwater, WA15974141116
142Boise City, ID15018495129
143Hartford-West Hartford-East Hartford, CT916219213
144Bellingham, WA1897582158
145Trenton, NJ9476175130
146Chicago-Naperville-Elgin, IL-IN-WI12297160126
147Kennewick-Richland, WA1605316491
148Grand Rapids-Wyoming, MI13214515394
149Green Bay, WI16817912862
150Dallas-Fort Worth-Arlington, TX68146161159
151Kansas City, MO-KS107116169131
152Baltimore-Columbia-Towson, MD6954190109
153Cedar Rapids, IA13819215253
154Charlottesville, VA12418915987
155Lincoln, NE174185115132
156Crestview-Fort Walton Beach-Destin, FL16317786178
157Nashville-Davidson--Murfreesboro--Franklin, TN95167156161
158Colorado Springs, CO166137146143
159Los Angeles-Long Beach-Anaheim, CA1695561192
160Omaha-Council Bluffs, NE-IA158170162111
161North Port-Sarasota-Bradenton, FL178138104184
162Portland-South Portland, ME15419017097
163Sacramento--Roseville--Arden-Arcade, CA182117131172
164Raleigh, NC135149181118
165Bridgeport-Stamford-Norwalk, CT14077191134
166Reno, NV180150134175
167Anchorage, AK1432019880
168Des Moines-West Des Moines, IA145197177100
169Salinas, CA1863985193
170Appleton, WI17718017952
171Ogden-Clearfield, UT135165187105
172Bremerton-Silverdale, WA19087178136
173Vallejo-Fairfield, CA16598154186
174Fargo, ND-MN179198116174
175San Diego-Carlsbad, CA184151108189
176Sioux Falls, SD164199173146
177Santa Cruz-Watsonville, CA2009330199
178Madison, WI191196176115
179Portland-Vancouver-Hillsboro, OR-WA193130167181
180Ann Arbor, MI173107168190
181Salt Lake City, UT157171185160
182Manchester-Nashua, NH148193188147
183Austin-Round Rock, TX149172180182
184Provo-Orem, UT148173186166
185Greeley, CO125186194156
186Boston-Cambridge-Newton, MA-NH153147193173
187Fort Collins, CO196195174164
188San Luis Obispo-Paso Robles-Arroyo Grande, CA19417494196
189Denver-Aurora-Lakewood, CO175181183176
190Minneapolis-St. Paul-Bloomington, MN-WI172194195152
191Santa Maria-Santa Barbara, CA192131123197
192Naples-Immokalee-Marco Island, FL18199144198
193Seattle-Tacoma-Bellevue, WA188118189185
194Oxnard-Thousand Oaks-Ventura, CA176119196187
195Santa Rosa, CA199182125195
196Urban Honolulu, HI183200182183
197Washington-Arlington-Alexandria, DC-VA-MD-WV113152200150
198Boulder, CO197191184188
199San Francisco-Oakland-Hayward, CA195187197194
200San Jose-Sunnyvale-Santa Clara, CA198188199200

Methodology

We considered variables, identified by the National Bureau of Economic Research, that were likely to influence the chance of foreclosure, including delinquency rates, unemployment rates, monthly cash flows after meeting expenses, and changes in home values relative to outstanding mortgage debt. These scores were normalized and weighted to produce scores for each city/MSA. The results were then ranked, in order of highest to lowest risk for default.

The full study factored in no less than seven variables, sourced from reputable sources. Income, housing and employment data were obtained from S&P Global Market Intelligence. Figures for monthly housing costs were obtained from the U.S. Census Bureau's American Census Survey. Income tax rates and subsistence figures were sourced from the IRS and Department of Veterans Affairs, respectively. Delinquency rates were collected from the Consumer Financial Protection Bureau. We transformed our variables into four separate measurements and ranked each MSA according to these categories.

Delinquency

This factor tracked the percentage of all mortgages outstanding that were 30 to 89 days behind on their mortgage payment. Areas with high rates of delinquency in the current market are likely to see more conversions to foreclosure during times of distress. We used each MSA's average delinquency rate as a leading indicator for homeowner default. Higher delinquency rates were viewed as greater risks and were assigned higher scores.

Unemployment

Unemployment tracked the percentage of unemployed members of the working age population in each city/MSA. Unemployment represents a major barrier to a household's ability to cover its mortgage payments. We employed each city’s/MSA's respective unemployment rate as a proxy for a negative household-level income shock. Higher percentages indicated a greater likelihood of default and received higher scores.

Monthly After-tax Cash Flows

A household's likelihood of default is a factor of its after-tax monthly cash flows, subtracting out housing payments and minimum costs of living. 2018 household median income was adjusted according to the 2018 IRS income tax table and netted out monthly housing costs, which included mortgage payments, taxes, homeowners insurance and HOA dues. We then subtracted a subsistence factor of $902.48, which accounts for a household's basic costs of living. The resulting cash flows were ranked from lowest to highest, with the lowest cash flows being most at risk of default, and assigned higher scores.

Change in Equity Relative to Mortgage Debt

This synthetic ratio tracked the likelihood that a household will "strategically default" on its home loan. Strategic default occurs when homeowners with the ability to pay choose to default on their mortgages instead, because the outstanding debt exceeds what the property is actually worth. This factor was responsible for a large number of defaults during the Great Recession, as borrowers simply walked away from rapidly depreciating properties on which they held little-to-no equity interest.

We calculated this ratio by measuring the change in median home value for each city/MSA between 2013 and 2018, and then dividing the difference by the average value of secured real estate debt outstanding. Secured real estate debt included all first and second mortgages, factoring in both home equity loans and lines of credit (HELOCs). Lower and negative ratios reflect a higher likelihood of strategic default, and were assigned higher scores.

Factor Weights

Due to the variable impact of each data point, we chose to overweight and underweight certain measures to help fine-tune our results. Monthly cash flow, in particular, was found to be one of the strongest determinants of default under the NBER study, while homeowners already delinquent on their mortgages were considered more likely to default during economic downturns. We, therefore, decided to overweight these factors relative to other variables.

Kenny Zhu

Kenny covers Banking and Mortgage content for ValuePenguin and has worked in the financial industry since 2013. He produces studies, guides and opinion pieces on consumer finance. Prior to joining ValuePenguin, Kenny was a Senior Investment Analyst at PFM Asset Management LLC, where he helped manage fixed income portfolios on behalf of public sector clients. He holds a Bachelors of Science from Carnegie Mellon University, where he majored in International Relations & Politics.

Editorial Note: The content of this article is based on the author’s opinions and recommendations alone. It has not been previewed, commissioned or otherwise endorsed by any of our network partners.

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