Entire Population Living in Poverty - Minnesota

Minnesota

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Entire Population Living in Poverty (Percent) – 2010

Data Provided by: Minnesota KIDS COUNT

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4.9% - 7.5%
Carver	4.9%
Scott	5.1%
Wright	5.8%
Washington	5.8%
Dodge	6.9%
Dakota	7.0%
Sherburne	7.2%
Chisago	7.4%
Anoka	7.4%
Wabasha	7.5%
7.6% - 10.8%
Marshall	8.2%
Goodhue	8.3%
Olmsted	8.5%
McLeod	8.5%
Meeker	8.9%
Isanti	8.9%
Murray	8.9%
Nicollet	9.0%
Le Sueur	9.2%
Houston	9.3%
Brown	9.3%
Roseau	9.4%
Wilkin	9.5%
Cook	9.6%
Redwood	9.6%
Douglas	9.6%
Jackson	9.7%
Lac qui Parle	9.8%
Swift	9.9%
Sibley	10.0%
Kittson	10.0%
Chippewa	10.0%
Lincoln	10.0%
Rice	10.3%
Steele	10.4%
Benton	10.5%
Pope	10.5%
Pipestone	10.5%
Waseca	10.7%
Grant	10.8%
Faribault	10.8%
Carlton	10.8%
Rock	10.8%
10.9% - 13.8%
Cottonwood	11.0%

10.9% - 13.8%
Red Lake	11.0%
Lake	11.2%
Renville	11.3%
Big Stone	11.3%
Norman	11.3%
Stevens	11.4%
Watonwan	11.4%
Lyon	11.4%
Pennington	11.5%
Martin	11.6%
Lake of the Woods	11.7%
Polk	11.7%
Stearns	12.1%
Itasca	12.2%
Mower	12.3%
Crow Wing	12.3%
Freeborn	12.3%
Fillmore	12.4%
Yellow Medicine	12.7%
Hubbard	12.8%
Clay	12.8%
Mille Lacs	13.1%
Aitkin	13.1%
Traverse	13.2%
Morrison	13.4%
Otter Tail	13.4%
Kanabec	13.6%
Hennepin	13.7%
Nobles	13.8%
13.9% - 22.1%
Kandiyohi	14.6%
Koochiching	14.6%
Becker	14.6%
Pine	15.2%
Winona	15.4%
Clearwater	15.7%
Cass	16.4%
Wadena	16.8%
Todd	16.9%
Blue Earth	16.9%
Ramsey	17.2%
St. Louis	17.4%
Beltrami	20.8%
Mahnomen	22.1%

Definitions: A model-based estimate of county residents living below the federal poverty threshold. The Census Bureau creates this estimate based on administrative data derived from tax returns, counts of food stamp participants, data from the Bureau of Economic Analysis (BEA), decennial census estimates, intercensal population estimates, and Annual Social and Economic Supplements of the Current Population Survey (CPS). Beginning with the estimates for 2005, data from the American Community Survey are used in the estimation procedure in place of CPS data.

Data Source: U.S. Bureau of the Census, Small Area Income and Poverty Estimates (SAIPE). http://www.census.gov/hhes/www/saipe.html

Note: Maps use the natural break classification method, which reflects patterns in the data by dividing the map into naturally occurring groups. Using statistical tools, this method determines cut-off points for each group by identifying large gaps in data values.

Minnesota Grantee

Minnesota KIDS COUNT Children's Defense Fund Minnesota
555 Park Street, Suite 410
St. Paul, MN 55103

651-855-1184
arzamendia@cdf-mn.org
http://www.cdf-mn.org

Kara Arzamendia, Research Director

Children's Defense Fund-Minnesota provides a strong and effective voice for children.

Kids Count Data Center