How Credit Card Debt Burdens Vary Across Cities in California - 2017 Report

The average credit card debt in California as of 2017 is $8,971. However, depending on where you live in the state not only can this average vary, but your income can make your overall card debt seem more or less significant. In this study, we examined the credit card debt-to-income (CDTI) ratio across 150 cities in California. Using this index, we were able to determine the overall burden card debt places on residents of various cities throughout the Golden State. Our findings show that some cities in the state have credit burdens 60% greater than the state average, while in other parts the CDTI was over 50% lower.

Cities With The Highest Credit Card Debt Burden

  • Lynwood, CA

    • Average Credit Card Debt: $8,556
    • CDTI Ratio: 15.04%
    • Average Household Income: $56,878
    • CDTI Compared to State Average: +61%

  • Huntington Park, CA

    • Average Credit Card Debt: $7,007
    • CDTI Ratio: 14.97%
    • Average Household Income: $46,801
    • CDTI Compared to State Average: +61%

  • South Gage, CA

    • Average Credit Card Debt: $8,536
    • CDTI Ratio: 14.92%%
    • Average Household Income: $57,198
    • CDTI Compared to State Average: +60%

  • Compton, CA

    • Average Credit Card Debt: $8,399
    • CDTI Ratio: 14.53%
    • Average Household Income: $57,793
    • CDTI Compared to State Average: +56%

  • Lancaster, CA

    • Average Credit Card Debt: $9,417
    • CDTI Ratio: 14.49%
    • Average Household Income: $65,003
    • CDTI Compared to State Average: +55%

Perhaps unsurprisingly, the cities with the heaviest credit card debt burden are generally the ones with the lowest average household incomes. In many of these cases, the average household credit card debt was actually well below the California average. However, while they carried less card debt, incomes in these cities were also disproportionately lower. Thus, even though their credit card debt was lower than that of other Californians, it weighed more heavily on their finances. While the average debt in these cities was just 7% lower than the state average, their mean incomes were 41% lower.

Cities With The Lowest Credit Card Debt Burden

  • Palo Alto, CA

    • Average Credit Card Debt: $9,415
    • CDTI Ratio: 4.56%
    • Average Household Income: $206,325
    • CDTI Compared to State Average: -51%

  • Cupertino, CA

    • Average Credit Card Debt: $10,392
    • CDTI Ratio: 5.19%
    • Average Household Income: $200,284
    • CDTI Compared to State Average: -44%

  • Thousand Oaks, CA

    • Average Credit Card Debt: $8,293
    • CDTI Ratio: 6.05%
    • Average Household Income: $136,984
    • CDTI Compared to State Average: -35%

  • Newport Beach, CA

    • Average Credit Card Debt: $10,635
    • CDTI Ratio: 6.33%
    • Average Household Income: $168,036
    • CDTI Compared to State Average: -32%

  • Pleasanton, CA

    • Average Credit Card Debt: $11,175
    • CDTI Ratio: 6.44%
    • Average Household Income: $173,569
    • CDTI Compared to State Average: -31%

Affluent cities like Palo Alto and Cupertino can weather credit card debt better than other parts of California. Residents of these cities tend to charge higher amounts to their credit cards, with average credit card balances in some of these places reaching as high as $12,734 -- 43% higher than the average city in the Golden State. However, due to their high incomes this debt was much less significant. The other interesting thing to note about these cities is that a greater percentage of households have at least one credit card. In Palo Alto and Newport Beach over 86% of households have at least one credit card. That is significantly higher than the national average of 72%.

How Did The Severity of Credit Card Debt Vary Geographically?

The map above shows how counties throughout California ranked in our study of credit card debt. The darker a spot on the map, the lower their CDTI was compared to the rest of the state. There was no direct geographic link between the credit card debt burdens within these counties.

Imperial County performed the worst out of all the areas throughout California. In 2014, the county had the second highest percentage of unemployment in the country. Current data also suggests Imperial has the lowest per capita income of any county in Southern California, with 22.6% of its population living below the poverty line. We observed a similar trend of poor financial performance throughout most of the low-ranking areas within our study. Conversely, Marin County, which saw the best performance, is also one of the wealthiest locations within the United States. Marin's CDTI was just 5.75%.

A List of All Cities We Examined in California

RankCityAverage Household Credit Card DebtAverage Household IncomeCDTI RatioCompared to State Average
1Palo Alto$9,415$206,3254.56%-51%
2Cupertino$10,392$200,2845.19%-44%
3Thousand Oaks$8,293$136,9846.05%-35%
4Newport Beach$10,635$168,0366.33%-32%
5Pleasanton$11,175$173,5696.44%-31%
6Mountain View$9,932$153,5136.47%-31%
7San Rafael$8,475$129,1756.56%-30%
8Walnut Creek$8,420$126,1236.68%-28%
9Sunnyvale$10,298$151,9116.78%-27%
10Encinitas$9,182$133,8776.86%-26%
11Carlsbad$9,163$131,9696.94%-26%
12Camarillo$8,028$113,2957.09%-24%
13San Ramon$12,734$178,6017.13%-24%
14San Jose$9,322$128,1467.27%-22%
15Redwood City$10,272$140,3277.32%-21%
16San Mateo$10,512$142,3087.39%-21%
17Laguna Niguel$10,922$147,4447.41%-21%
18Santa Clara$10,292$135,9587.57%-19%
19Simi Valley$8,787$114,8507.65%-18%
20Yorba Linda$11,817$153,8247.68%-18%
21Milpitas$10,648$138,4207.69%-17%
22Berkeley$8,805$114,0597.72%-17%
23San Francisco$10,273$132,1597.77%-17%
24Livermore$11,128$141,9397.84%-16%
25Alameda$9,338$118,4087.89%-15%
26Redlands$7,582$95,8517.91%-15%
27San Clemente$11,144$138,8698.02%-14%
28Chino Hills$9,718$120,2838.08%-13%
29Davis$7,679$94,4468.13%-13%
30San Buenaventura (Ventura)$7,159$87,6518.17%-12%
31Fremont$11,931$145,7068.19%-12%
32Folsom$10,559$127,2238.30%-11%
33Santa Barbara$8,496$100,8608.42%-10%
34Mission Viejo$11,102$131,0298.47%-9%
35San Diego$8,665$100,8308.59%-8%
36Petaluma$9,817$113,7488.63%-7%
37Rocklin$9,472$108,9248.70%-7%
38Arcadia$10,384$119,3898.70%-7%
39Upland$7,207$81,8568.80%-6%
40Rancho Cucamonga$8,872$100,2848.85%-5%
41Redondo Beach$12,126$136,8358.86%-5%
42South San Francisco$9,984$112,4368.88%-5%
43Huntington Beach$10,482$117,3478.93%-4%
44Oakland$8,347$92,2969.04%-3%
45Lodi$6,515$72,0209.05%-3%
46Clovis$7,961$87,5219.10%-2%
47Santa Monica$10,712$117,3089.13%-2%
48Roseville$9,416$102,4389.19%-1%
49Santa Cruz$8,706$94,2269.24%-1%
50Pasadena$10,143$109,2579.28%0%
51Daly City$9,787$105,3329.29%0%
52Napa$9,171$98,5609.31%0%
California Average$8,917$95,6719.32%0%
53Oceanside$7,882$84,1109.37%1%
54Irvine$12,219$130,1649.39%1%
55Murrieta$8,870$94,0129.43%1%
56Oxnard$7,701$81,4899.45%1%
57Santa Rosa$8,504$89,7329.48%2%
58Union City$11,144$116,9589.53%2%
59Tracy$9,118$95,5439.54%2%
60Elk Grove$9,921$103,8359.55%3%
61San Leandro$8,886$92,2519.63%3%
62La Mesa$7,764$80,0249.70%4%
63Riverside$7,493$76,9729.73%4%
64Torrance$10,555$108,0059.77%5%
65Temecula$9,552$97,5739.79%5%
66Manteca$7,726$78,7839.81%5%
67Corona$9,321$94,8979.82%5%
68Apple Valley$6,555$66,6159.84%6%
69Concord$9,274$94,1159.85%6%
70Vacaville$9,766$98,9489.87%6%
71Hayward$9,400$94,3319.97%7%
72Lake Forest$12,076$120,8299.99%7%
73Richmond$7,920$79,09610.01%7%
74Bakersfield$7,899$78,84510.02%7%
75Escondido$7,427$74,11910.02%8%
76Menifee$7,478$74,09310.09%8%
77Orange$10,931$107,94810.13%9%
78Sacramento$7,461$73,46410.16%9%
79Chino$8,886$86,97710.22%10%
80Stockton$6,760$65,99610.24%10%
81El Cajon$6,935$67,52110.27%10%
82Vista$7,188$69,89110.28%10%
83Santa Clarita$11,731$113,55510.33%11%
84Fresno$6,401$61,57210.40%12%
85San Marcos$8,655$82,93110.44%12%
86Antioch$9,502$90,98610.44%12%
87Fullerton$10,111$96,53110.47%12%
88Chula Vista$9,108$86,92010.48%12%
89Citrus Heights$6,999$66,77010.48%12%
90Indio$7,232$68,55210.55%13%
91Vallejo$8,332$78,78710.58%13%
92Fairfield$9,767$92,01710.61%14%
93Glendale$9,159$86,15410.63%14%
94Tustin$11,693$109,72310.66%14%
95Costa Mesa$10,439$96,34910.83%16%
96Pittsburg$9,122$83,61710.91%17%
97Monterey Park$8,843$80,80810.94%17%
98Redding$7,278$66,34610.97%18%
99Los Angeles$9,161$83,43810.98%18%
100Moreno Valley$7,669$69,61011.02%18%
101Rancho Cordova$8,359$75,53511.07%19%
102Modesto$7,822$70,31411.12%19%
103Ontario$7,587$67,93911.17%20%
104Fontana$9,188$82,23411.17%20%
105Burbank$10,345$92,56811.18%20%
106National City$6,484$57,90011.20%20%
107Carson$10,146$89,39911.35%22%
108Rialto$7,513$65,89411.40%22%
109La Habra$10,174$89,01811.43%23%
110Hemet$5,503$48,09111.44%23%
111Chico$7,788$67,86111.48%23%
112Yuba City$8,343$72,62811.49%23%
113Whittier$10,349$89,93311.51%23%
114Anaheim$10,242$88,93711.52%24%
115Buena Park$10,452$90,55611.54%24%
116Hesperia$7,034$60,66711.59%24%
117Long Beach$9,320$80,36511.60%24%
118San Bernardino$6,162$52,54211.73%26%
119Lakewood$11,472$97,80111.73%26%
120West Covina$10,287$87,35811.78%26%
121Visalia$8,782$74,12111.85%27%
122Westminster$9,357$77,94712.00%29%
123Turlock$8,396$69,81312.03%29%
124Downey$9,775$81,09512.05%29%
125Gardena$8,391$69,15512.13%30%
126Salinas$8,435$69,29512.17%31%
127Alhambra$9,214$75,49912.20%31%
128Garden Grove$9,816$79,04512.42%33%
129Victorville$7,207$57,92012.44%33%
130Santa Maria$8,573$68,14012.58%35%
131Montebello$8,445$66,29712.74%37%
132Tulare$8,116$63,53112.77%37%
133Merced$7,714$60,17912.82%38%
134Perris$7,624$59,41412.83%38%
135Hawthorne$8,341$64,50912.93%39%
136Bellflower$8,799$67,23313.09%40%
137Inglewood$7,819$59,12213.23%42%
138Santa Ana$9,516$71,64513.28%43%
139Pomona$9,030$67,55913.37%43%
140Pico Rivera$9,605$71,39413.45%44%
141Palmdale$10,012$73,48213.62%46%
142Baldwin Park$9,298$67,65413.74%47%
143Norwalk$10,412$75,24513.84%48%
144Madera$7,567$54,18713.97%50%
145El Monte$7,947$56,06114.18%52%
146Lancaster$9,417$65,00314.49%55%
147Compton$8,399$57,79314.53%56%
148South Gate$8,536$57,19814.92%60%
149Huntington Park$7,007$46,80114.97%61%
150Lynwood$8,556$56,87815.04%61%

Methodology

The study was based on reports generated from Nielsen Demographic Data. The Nielsen Financial CLOUT data set provides geography-based estimates of market penetration and user household dollar volume for a wide range of financial products and services. According to the company’s methodology, “the databases were generated using statistical models developed from the Nielsen Market Audit.” The models the company uses are built on three years worth of survey results, from approximately 75,000 respondents.

The biggest limited factor of the study is that the Nielsen survey data is based on online-only respondents. This creates a potential bias in the findings, as the sample isn’t truly representative of the entire California population.

To simplify our report, we looked at data from 150 of the most populated cities throughout California. Our report omits areas designated as villages or census designated places.

Sources: Nielsen CLOUT Financial Data
New York Federal Reserve Bank Community Credit Study

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