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Commuter Income Patterns: Big Counties Support Small

Monday's post on personal income growth got me looking at patterns of commuter inflow and outflow in South Dakota. Commuter inflow is the income folks from, say, Lake County, bring home from their jobs in Minnehaha. Commuter outflow is the income commuters like my prof at DSU makes at work in Lake but then takes home to Minnehaha. Net flow is simply inflow minus outflow. If your county has positive net flow, that means the commuters who live in your county are bringing more income into the county than commuters to your county from elsewhere are taking out.

The Bureau of Economic Analysis calculates net commuter income flow by county (see BEA's Table CA-91). I took their data and calculated what I'm calling a "flow-to-opportunity" ratio. Opportunity here is the total income generated by jobs in a given county, regardless of whether the jobs are done by locals or commuters. BEA gives toal personal income (TPI) for each county; subtract the net flow (watch your negative signs!) and you get opportunity.

The following map breaks South Dakota's counties into rough quintiles by flow-to-opportunity ratio. Gold means lots of commuters working elsewhere and bringing cash home. Blue means lots of out-of-towners coming to a county to work but living elsewhere. All data are from 2009, the most recent county data available.

South Dakota commuter income flow relative to total local income opportunity
(click to enlarge!)

The following table gives specific numbers for each county (all figures are thousands of dollars, from 2009):

County 2009 inflow outflow net flow total personal income NF/(TPI-NF)
Lincoln 1,027,006 168,223 858,783 2,061,794 71.4%
Stanley 44,866 18,692 26,174 114,446 29.7%
McCook 61,140 17,658 43,482 231,231 23.2%
Turner 94,370 26,941 67,429 376,747 21.8%
Meade 268,222 112,499 155,723 877,557 21.6%
Moody 59,480 16,983 42,497 264,508 19.1%
Mellette 9,854 1,411 8,443 53,065 18.9%
Hamlin 41,460 9,358 32,102 202,060 18.9%
Ziebach 9,095 1,413 7,682 52,442 17.2%
Hanson 31,435 7,387 24,048 167,427 16.8%
Sanborn 20,333 4,501 15,832 113,148 16.3%
Bennett 13,502 1,586 11,916 90,672 15.1%
Custer 43,884 8,615 35,269 270,036 15.0%
Edmunds 29,146 5,489 23,657 196,255 13.7%
Butte 44,728 10,078 34,650 287,918 13.7%
Corson 14,610 4,798 9,812 112,491 9.6%
Aurora 16,198 5,833 10,365 119,316 9.5%
Sully 9,333 2,499 6,834 78,740 9.5%
Kingsbury 30,679 11,392 19,287 236,251 8.9%
Bon Homme 27,322 10,632 16,690 231,223 7.8%
Deuel 27,199 15,275 11,924 166,843 7.7%
Clark 12,578 2,956 9,622 137,483 7.5%
Roberts 33,435 11,641 21,794 325,567 7.2%
McPherson 6,885 1,818 5,067 87,180 6.2%
Lake 44,811 18,954 25,857 449,771 6.1%
Clay 68,999 40,920 28,079 546,648 5.4%
Miner 10,611 5,355 5,256 108,577 5.1%
Campbell 3,699 1,114 2,585 53,484 5.1%
Lyman 13,423 7,762 5,661 126,904 4.7%
Brule 16,889 9,205 7,684 208,576 3.8%
Hutchinson 27,635 16,321 11,314 312,339 3.8%
Day 14,086 6,925 7,161 200,874 3.7%
Faulk 4,552 1,069 3,483 105,957 3.4%
Hand 5,429 2,159 3,270 149,278 2.2%
Douglas 9,141 6,463 2,678 130,416 2.1%
Haakon 3,436 1,952 1,484 83,830 1.8%
Spink 16,321 11,332 4,989 356,315 1.4%
Gregory 4,355 2,590 1,765 164,684 1.1%
Beadle 27,120 20,463 6,657 712,477 0.9%
Jackson 6,074 5,483 591 74,205 0.8%
Tripp 6,354 5,157 1,197 197,166 0.6%
Jones 1,259 1,025 234 38,586 0.6%
Potter 3,397 2,770 627 120,885 0.5%
Walworth 6,390 5,652 738 180,935 0.4%
Harding 1,100 1,473 -373 39,785 -0.9%
Marshall 12,814 14,597 -1,783 140,704 -1.3%
Lawrence 70,967 84,593 -13,626 811,093 -1.7%
Charles Mix 6,694 12,427 -5,733 326,105 -1.7%
Brown 16,704 57,739 -41,035 1,586,913 -2.5%
Perkins 1,286 3,800 -2,514 91,613 -2.7%
Union 186,194 209,812 -23,618 764,981 -3.0%
Hyde 3,048 4,383 -1,335 41,369 -3.1%
Fall River 15,807 23,472 -7,665 233,477 -3.2%
Grant 16,982 27,419 -10,437 284,687 -3.5%
Brookings 54,009 94,146 -40,137 1,083,829 -3.6%
Codington 23,958 61,984 -38,026 975,982 -3.8%
Dewey 2,803 11,160 -8,357 166,677 -4.8%
Pennington 110,310 310,136 -199,826 3,779,937 -5.0%
Hughes 22,334 61,956 -39,622 705,953 -5.3%
Yankton 32,872 83,443 -50,571 792,104 -6.0%
Davison 19,475 72,656 -53,181 793,581 -6.3%
Todd 3,678 23,974 -20,296 197,679 -9.3%
Jerauld 6,862 19,330 -12,468 97,807 -11.3%
Minnehaha 299,822 1,473,839 -1,174,017 6,796,310 -14.7%
Shannon 2,268 47,290 -45,022 250,651 -15.2%
Buffalo 2,186 12,089 -9,903 36,652 -21.3%
total 3,182,914 3,362,067 -179,153 31,174,196 -0.6%

What do these numbers tell us about where we live and work in South Dakota? These numbers fit what I found looking at similar data a couple years ago: big communities support surrounding small communities. Consider Minnehaha County, our outflow champ. Sioux Falls residents driving elsewhere for work bring just under $300 million back to town, but folks from Harrisburg, Lennox, Montrose, Chester, and Madison pull $1.47 billion out of Sioux Falls and the rest of Minnehaha County. jobs in Pennington and Lawrence counties, support a lot of commuters from Butte, Meade, and Custer counties.

The West River reservations show a similar trend, with income flowing from higher population areas to lower population areas. Shannon County (Pine Ridge) and Todd County (Rosebud) support a number of commuters who appear to live off-reservation in Bennett and Mellette counties. Much less income enters Shannon and Todd counties from locals working elsewhere. That may fit with a comment Mr. Kurtz left yesterday: commuting costs money, and folks in Shannon and Todd, two of the poorest counties in the nation, have much less freedom to hop in the car everyday and drive to work somewhere else. But there just may be a lot more jobs available for commuting workers on Pine Ridge and Rosebud: Shannon and Todd are much more populous (13,586 and 9612) than Bennett and Mellette (3431 and 2048).

Income flow on the Cheyenne River Reservation remains within the boundaries of the reservation. Ziebach on the west side enjoys a strong positive net flow, while Dewey sees strong negative net flow. The population-net flow trend on the reservation holds: Dewey has a larger population than Ziebach (5301 to 2801).

Now go figure this one out: South Dakota as a whole experiences a slight negative net flow. Add up the net flows, and you get a net negative $179 million. That's only 0.6% of our $31.4 billion in total income opportunity, but it still means there's a slight surplus of income earned by folks who think South Dakota's a nice place to work but not the place they choose to live. Check the data, form your geographical own hypotheses!

3 Comments

  1. Troy Jones 2011.04.27

    The slight ouflow is the same reason Minnehaha supports the surrounding counties in South Dakota- It attracts a few people from Minnesota and Iowa. The only real offset to this is South Dakotans who work in Sioux City.

  2. caheidelberger Post author | 2011.04.27

    I wondered about exactly that, Troy. Sioux Falls and Yankton are the only major population centers right on the border in SD. And Troy, your're right: Sioux City is the only border-state city positioned to offset such outflows with job opportunities.

    We clearly see Minnehaha and Yankton supporting surrounding areas with net negative income flow. Sure enough, Knox County, Neb., across the bridge from Yankton, sees net positive flow of $19.4 million. East from Sioux Falls, Lyon County, Iowa, sees net positive flow of $65 million, and Rock County, MN, sees positive $39.7 million.

    But check out the Sioux City area. Woodbury County, which has most of Sioux City, has net negative flow of $58 million, a remarkably small number compared to Minnehaha's outflow of $1.2 billion, even factoring in different population. Plymouth County, which includes North Sioux City, swamps that with a net inflow of $91 million. If Union County is drawing any of Sioux City's income, they're losing much more elsewhere, since Union County's net flow is negative, $23 million. And Dakota County, Neb., with the packing plant and such in S. Sioux City has net negative flow of $93 million. (Anyone care to vounteer to color these flows on a map of the entire country?)

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