by Dave Senf
August 2017
The county with the smallest population in Minnesota in 2015 with 3,429 residents was Traverse County, located along the South Dakota border. The county's population accounted for 0.06 percent of Minnesota's 5.4 million population. Traverse County's households also accounted for 0.06 percent of total Minnesota household income in 2015 as household income in the county, as estimated by the America Community Survey (ACS), was $99 million while household income across all Minnesota was $170.9 billion.1
Sparsely populated Traverse County may rank low when it comes to population and household income, but its rank climbs to 20th highest among the 87 counties in Minnesota when its $28,888 per capita household income estimate in 2015 is the gauge. On top of the pile as far as population and household income is concerned was Hennepin County with a 2015 population of 1.2 million and estimated $45.5 billion total household income. That is 22.1 percent of the state's population and 26.6 percent of household income. Hennepin County's per capita household income was $38,011, third highest in the state behind Carver and Washington counties. As shown in Table 1 only seven counties had per capita household income above the 2015 state's $31,529.
| Rank | County | Percentage |
|---|---|---|
| 1 | Carver | 40,131 |
| 2 | Washington | 38,021 |
| 3 | Hennepin | 38,011 |
| 4 | Dakota | 35,800 |
| 5 | Scott | 35,399 |
| 6 | Olmsted | 34,590 |
| 7 | Cook | 33,827 |
| - | Minnesota | 31,529 |
| 8 | Anoka | 31,126 |
| 9 | Wabasha | 30,672 |
| 10 | Pope | 29,823 |
| 78 | Todd | 23,245 |
| 79 | Mille Lacs | 22,868 |
| 80 | Kanabec | 22,786 |
| 81 | Nobles | 22,754 |
| 82 | Clearwater | 22,697 |
| 83 | Beltrami | 21,684 |
| 84 | Wadena | 21,558 |
| 85 | Pine | 21,488 |
| 86 | Lake of the Woods | 20,948 |
| 87 | Mahnomen | 19,142 |
| Source: Author's calculations using American Community Survey, 2011 - 2015 5-year household income estimates.
Per capita income estimates presented here differ slightly from ACS per capita income estimates due to use of differing population estimates used in per capita calculations. |
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County per capita household income in Minnesota varies because of numerous intertwined factors. Since wage and salary income is the leading source of household income in all counties, the difference in wages across counties is a key factor. Industry mix, which influences occupational mix, obviously plays a big role in wage differences across counties. The educational attainment mix of local labor forces shapes local Industry and occupational mixes while at the same time the industry and occupational mix shapes the local educational attainment mix.
Total wage earnings are boosted not only by higher wages but also by higher employment to population ratios and lower unemployment rates. The age structure of a county influences the number of individuals employed no matter what the population size. Counties with a higher percent of their population in prime working ages will, with all other factors held constant, have higher employment to population ratios and thus higher wage earnings per capita. Counties with above average sized senior citizen populations would be expected to have a smaller share of household income generated from wage and salary earnings and a higher share of income coming from Social Security payments. The differences in income sources across Minnesota counties are revealed in ACS household income data.
ACS household income data are based on household surveys and not administration records such as income tax and unemployment insurance records. Responses to two questions in the American Community Survey are compiled to produce county household income estimates. The first question asked respondents about total income over the last 12 months while the second question queried households about the sources of the their income. 2
Households receive income from various sources such as paychecks, Social Security checks, dividend payments, unemployment compensation, or interest payments. The ACS survey groups the various income streams into eight broad categories as shown in Table 2. Wage and salary income is the top source of income in all counties accounting for 77.1 percent of Minnesota household income in 2015. The percent of all household income derived from wage and salary income ranges from a high of 85.4 percent in Scott County to a low of 51 percent in Traverse County. Table 3 shows the counties most and least dependent on wages and salaries for household income in 2015.
| Income Source | Percent of Houshold Income Statewide | Income Included |
|---|---|---|
| Wage or Salary Income | 77.1 | Total money earnings received for work as an employee. Includes wages, salary, commissions, tips, cash bonuses earned before any deductions. |
| Social Security Income | 6.4 | Social Security pensions and survivor benefits, prior to deductions for medical insurance and railroad retirement insurance checks from U.S. government. Medical reimbursements are not included. |
| Self-Employment Income | 5.1 | Net money income (gross receipts minus operation expenses) for individuals operating a farm as an owner, renter, or sharecropper. Net money income (gross receipts minus operation expenses) from one's own business, professional enterprise, or partnership. |
| Interest, Dividends, Net Rental Income | 4.6 | Interest on savings or bonds, dividends from stockholdings, net income from rental of property to others. Does not include realized capital gains. |
| Retirement Income | 4.5 | Retirement income from company pension, union pension, government pension, military pension, and U.S. Railroad pension. Retirement income from KEOGH plan or Simplified Employee Pension (SEP), and any other type of pension, retirement account or annuity such as IRA, ROTH IRA, 401(k), 403(b) account. |
| All Other Types of Income | 1.7 | Includes unemployment compensation, worker's compensation, Veterans Affairs (VA) payment, alimony, and child support. |
| Supplemental Security Income | 0.5 | Survivor income which is paid to spouses or children of deceased person or regular income from a disability pension paid to those unable to work due to disability from companies or unions; federal, state, or local governments; and the U.S. military. Does not include Social Security payments. |
| Public Assistance Income | 0.1 | General assistance and Temporary Assistance to Needy Families (TANF). Does not include noncash benefits such as SNAP payments, energy assistance, or Medicaid or Medicare reimbursements. |
| Source: American Community Survey and Puerto Rico Community Survey 2015 Subject Definitions, page 80. | ||
| Rank | County | Percentage |
|---|---|---|
| 1 | Scott | 85.4 |
| 2 | Carver | 84.3 |
| 3 | Sherburne | 82.4 |
| 4 | Wright | 81.6 |
| 5 | Dakota | 81.5 |
| 6 | Anoka | 81.3 |
| 7 | Olmsted | 80.3 |
| 8 | Washington | 80.2 |
| 9 | Hennepin | 80.1 |
| 10 | Benton | 78.8 |
| - | Minnesota | 77.1 |
| 78 | Cass | 58.9 |
| 79 | Pipestone | 58.9 |
| 80 | Norman | 58.5 |
| 81 | Big Stone | 58.4 |
| 82 | Cottonwood | 57.9 |
| 83 | Kittson | 57.5 |
| 84 | Grant | 57.2 |
| 85 | Aitkin | 56.9 |
| 86 | Lac qui Parle | 54.4 |
| 87 | Traverse | 51.0 |
| Source: Author's calculations using American Community Survey, 2011 - 2015 5-year household income estimates | ||
The counties where households depend on wage and salary payments the most are urban counties where wages and salaries are above average and the share of population in the prime working years, 25 to 54 years, is high. The counties where households are least dependent on wage and salary income are primarily agriculture-based counties where farm income, which is reported in the ACS as self-employment income, accounts for a large share of household income. Table 4 displays the high and low rankings for self-employment income. Nine of the top 10 self-employment income counties are Southwest Minnesota farm counties while the other, Norman, is a farm county in the Red River Valley above Moorhead.
| Rank | County | Percentage |
|---|---|---|
| 1 | Lac qui Parle | 20.6 |
| 2 | Traverse | 19.5 |
| 3 | Grant | 17.0 |
| 4 | Jackson | 16.4 |
| 5 | Norman | 16.2 |
| 6 | Yellow Medicine | 16.2 |
| 7 | Redwood | 15.8 |
| 8 | Cottonwood | 15.6 |
| 9 | Renville | 15.4 |
| 10 | Murray | 15.2 |
| - | Minnesota | 5.1 |
| 78 | Sherburne | 4.2 |
| 79 | Chisago | 4.1 |
| 80 | Koochiching | 4.1 |
| 81 | St. Louis | 3.8 |
| 82 | Scott | 3.7 |
| 83 | Ramsey | 3.6 |
| 84 | Dakota | 3.6 |
| 85 | Anoka | 3.6 |
| 86 | Washington | 3.5 |
| 87 | Olmsted | 3.4 |
| Source: Author's calculations using American Community Survey, 2011 - 2015 5-year household income estimates | ||
The counties with low reliance on self-employment income are for the most part urban counties. Despite all the hype about a rapidly expanding 1090 or gig economy, urban household report they are far less dependent on self-employment income than rural households. Urban areas, the supposed ground-zero of rapid growth in independent contractors such as Uber drivers, remains overwhelmingly dependent on wage and salary jobs for household income, at least according to ACS households responses to questions about income sources.
Farm counties unexpectedly top the rankings when it comes to percent of household income derived from interests, dividends, and net rental income (Table 5). All the counties in the top 10 in this income group are farm counties including four counties that made the most self-employment income dependent list. Net rental income of farmland is what propels farm counties to the top of counties most dependent on interests, dividends, and net rental income. Combining the percent of household income accounted for by self-employment income with percent accounted for by interests, dividends, and net rental income in farm counties highlights the significance of farm-related income in those counties. Households in the four counties listed in both Tables 4 and 5 (Cottonwood, Norman, Renville, and Traverse) on average depend on self-employment and interests, dividends, and net rental payments for 25.2 percent of their income. The percent of household income derived from self-employment and interests, dividends, and net rental payments statewide is 9.7 percent.
| Rank | County | Percentage |
|---|---|---|
| 1 | Pipestone | 12.5 |
| 2 | Traverse | 10.2 |
| 3 | Kittson | 10.1 |
| 4 | Watonwan | 9.5 |
| 5 | Pope | 8.5 |
| 6 | Renville | 8.4 |
| 7 | Lincoln | 8.0 |
| 8 | Rock | 7.9 |
| 9 | Cottonwood | 7.8 |
| 10 | Norman | 7.7 |
| - | Minnesota | 4.6 |
| 78 | Anoka | 2.8 |
| 79 | Chisago | 2.7 |
| 80 | Pennington | 2.7 |
| 81 | Wadena | 2.6 |
| 82 | Sherburne | 2.6 |
| 83 | Wright | 2.6 |
| 84 | Carlton | 2.4 |
| 85 | Isanti | 2.4 |
| 86 | Kanabec | 2.3 |
| 87 | Benton | 2.0 |
| Source: Author's calculations using American Community Survey, 2011 - 2015 5-year household income estimates | ||
If your grandparents or other relatives have retired to a lakeside cabin Up North then Table 6 and 7 shouldn't be a surprise. The counties in Minnesota lake regions are the top counties when it comes to highest percent of household income stemming from Retirement income and from Social Security income. Six of the lake counties rank in the top 10 in both Retirement and Social Security income. Most counties will see their percent of household income derived from Retirement and Social Security income increase over the next 10 years as the bulk of baby boomers complete their move into retirement. The percent of household income generated from wage and salary income on the other hand will be slowly tailing off.
| Rank | County | Percentage |
|---|---|---|
| 1 | Aitkin | 11.5 |
| 2 | Cook | 11.1 |
| 3 | Cass | 10.2 |
| 4 | Itasca | 9.7 |
| 5 | Hubbard | 9.4 |
| 6 | Lake | 9.0 |
| 7 | Crow Wing | 8.4 |
| 8 | Pope | 8.0 |
| 9 | Koochiching | 7.9 |
| 10 | St. Louis | 7.8 |
| - | Minnesota | 4.5 |
| 78 | Wilkin | 3.4 |
| 79 | Watonwan | 3.3 |
| 80 | Wright | 3.3 |
| 81 | Waseca | 3.2 |
| 82 | Sibley | 3.1 |
| 83 | Yellow Medicine | 3.1 |
| 84 | Scott | 2.9 |
| 85 | Jackson | 2.8 |
| 86 | Nobles | 2.8 |
| 87 | Carver | 2.7 |
| Source: Author's calculations using American Community Survey, 2011 - 2015 5-year household income estimates | ||
| Rank | County | Percentage |
|---|---|---|
| 1 | Aitkin | 16.7 |
| 2 | Koochiching | 13.5 |
| 3 | Cass | 13.2 |
| 4 | Wadena | 12.9 |
| 5 | Hubbard | 12.7 |
| 6 | Itasca | 12.6 |
| 7 | Lake | 12.1 |
| 8 | Lake of the Woods | 12.1 |
| 9 | Pine | 11.9 |
| 10 | Clearwater | 11.6 |
| - | Minnesota | 6.4 |
| 78 | Dodge | 6.3 |
| 79 | Anoka | 5.9 |
| 80 | Olmsted | 5.4 |
| 81 | Wright | 5.2 |
| 82 | Washington | 5.1 |
| 83 | Dakota | 5.0 |
| 84 | Sherburne | 4.8 |
| 85 | Hennepin | 4.7 |
| 86 | Scott | 3.6 |
| 87 | Carver | 3.5 |
| Source: Author's calculations using American Community Survey, 2011 - 2015 5-year household income estimates | ||
Retirement and Social Security income as a percent of all household income for the six counties that are on both the top Retirement and Social Security lists averages 23.1 percent which is double the statewide 10.9 percent. Future Income growth in these counties relative to statewide income growth will be depend heavily on how many Minnesotans retire Up North rather than heading south to Arizona or Florida.
Analyzing county household income sources, including how sources vary from county to county, provides valuable insights into the driving forces behind local economies. Tracking household income changes over time is another useful tool for understanding how local economies are evolving. Unfortunately the five-year period, rather than one-year period, household income estimates that are available for most Minnesota counties tend to smooth away some of the more interesting actual year-to-year changes.
Comparing Anoka County's five-year and one-year per capita household income estimates from 2009 through 2015, as in Figure 1, underscores the tricky nature of five-year estimates. Anoka's per capita household five-year period estimates are smooth since five years of responses are combined to generate the estimates. One-year estimates show more variance between 2009 and 2015 as would be expected given the Great Recession. The one-year estimates provide a much more realistic picture of household income over that period. Per capita household income more likely increased 16.5 percent between 2011 and 2015 as suggested by the one-year estimates than the 5.0 percent as suggested by the five-year estimates. Five-year estimates are the only available estimates for many income measures, such as median and mean household income, for most Minnesota counties. Conclusions about changes in county-level income measures based on five-year estimates should be made with caution.
ACS household income data for Minnesota and all 87 counties for the seven five-year periods (2005-2009 through 2011-2015) are available graphically on Tableau Public.3 Household income data by the eight income sources can be viewed from four perspectives. The first is the actual ACS estimates, the second is as a percent of total household income, the third is as a percent of statewide income source, and the fourth perspective shows a per capita view. Counties can be view all at once or separately, one year at a time or for the complete 2009 – 2015 time period.
1The household income data presented here are five-year periods of survey responses starting with the 2005-2009 period and ending with the 2011-2015 period. When 2015 is used in this article, the data being referred to are the 2011-2015 period estimates. Only 14 counties in Minnesota have large enough populations to produce reliable one-year estimates of household income. Household estimates for the other counties are only available for five-year periods since multiple year responses have larger sample sizes and are therefore more reliable. The household data analyzed here use five-year period data for Minnesota and the 87 counties.
2Two other commonly used household income datasets are the Bureau of Economic Analysis (BEA) personal income data and the IRS's adjusted gross income data. Because of different concepts of income the three income estimates differ significantly.
