Wisconsin Families Kept from Poverty Despite State's "Jobless Recovery"

April 25, 2012

Contact: Timothy M. Smeeding, smeeding@lafollette.wisc.edu, (608) 890-1317
Yiyoon Chung, yychung@wisc.edu, (608) 345-4682
Julia Isaacs, jisaacs@urban.org, (608) 890-1316

Wisconsin Poverty Report: How the Safety Net Protected Families from Poverty in 2010

MADISON–A new report by University of Wisconsin–Madison researchers reveals good news for struggling families in Wisconsin that counters official statistics released in fall 2011: Temporary increases in safety net programs and tax credits for working families provided an effective buffer against poverty during the recession and its aftermath.

While the official poverty measure for 2010 (the most recent year for which data are available) reveals a 13.0% overall poverty rate in Wisconsin (the overall rate includes children, working-age adults, and the elderly), the study released by researchers at the Institute for Research on Poverty (IRP) finds a much lower overall rate of 10.3%.

The story for Wisconsin’s children in 2010 is even more dramatic, with official statistics finding an 18.6% child poverty rate and the Wisconsin Poverty Project study revealing a 10.8% child poverty rate, when child and earned income tax credits and increased food assistance are counted (the official measure, devised in the 1960s, counts only pre-tax cash income and so misses the effects of some important government programs that provide a safety net during economic downturns).

While the overall and child poverty rates were lower under the new measure than under the official measure, elderly poverty rates actually were higher under the new approach, from the official rate of 7.6% to the study rate of 9.8%. Researchers attribute the higher rate to seniors’ out-of-pocket medical costs that are counted under the new measure but left out of the official one.

The new findings, revealed in IRP’s fourth annual Wisconsin Poverty Report, resulted from a more modern and complete accounting of resources and expenses, the Wisconsin Poverty Measure (WPM), which was devised at IRP in order to provide researchers, state policymakers, and practitioners with a better gauge of economic security that reflects local cost of living and state policy effects.

The study’s lead investigator, IRP Director Tim Smeeding, said the WPM follows a model similar to the one recommended by a National Academy of Sciences panel and similar to the new federal Supplemental Poverty Measure. Study coauthor Yiyoon Chung notes, “we contribute to the field by applying an alternative measure to a local area (Wisconsin) in ways that reflect the characteristics and policy interests of the state, and by providing explicit and straightforward guidelines that other states and localities can use to develop their own measures.”

Wisconsin is an excellent site for a case study of alternative poverty measures because of the state’s historic importance as an experimental site for national policies, and the provision of resources for this research by the University of Wisconsin–Madison. Wisconsin sees rich interactions of research and community life, largely because of the University of Wisconsin System’s adherence to the “Wisconsin Idea,” which is the principle that university research should improve people’s lives beyond the classroom.

In that spirit of extending the reach of university scholarship, IRP provides technical resources about the methodology used to create the WPM on its website (www.irp.wisc.edu) for researchers in other states who are looking to devise their own place-specific poverty measures.

“The long-term solution to poverty is a secure job that pays well, not an indefinite income support program,” Smeeding emphasizes, “but our report shows that in times of need, a safety that enhances low earnings for working families with children, puts food on the table, and encourages self-reliance–as Wisconsin’s safety net does–makes a difference in combatting market-driven poverty.”

Tables 1 and 2 below present the results of the Wisconsin Poverty Project researchers' analysis of substate areas, which revealed that the overall poverty rate of 10.3 percent (the overall rate includes children, working-age adults, and the elderly) hides substantial variations in poverty across regions.

Estimates for poverty rates using the Wisconsin Poverty Measure for these substate areas range from 16.7 percent in Milwaukee County to 4.2 percent in the area that includes Ozaukee and Washington counties. Milwaukee County and the region including Chippewa and Eau Claire counties were the only places where rates were significantly higher than the state average of 10.3 percent.

While Milwaukee County still shows the highest poverty rate in the state, its rate decreased to 16.7 percent in 2010 from 18.7 percent in 2009. The area including Chippewa and Eau Claire counties had a poverty rate of 14.5 percent in 2010, significantly higher than its rate at 12.1 percent in 2009. Dane County has a poverty rate of 11.9 percent in 2010, lower than its rate of 13.5 percent in 2009. In fact, in contrast with the WPM findings for 2009, Dane County's rate is no longer significantly different from the state average in 2010. Meanwhile, seven areas have rates that are significantly lower than the statewide rate, including Ozaukee/Washington (4.2 percent), Waukesha (5.1 percent), Brown (7.3 percent), and Sheboygan (7.0 percent) counties.

Table 1. Poverty Rates in Wisconsin by County or Multicounty Area under the Wisconsin Poverty Measure with Upper and Lower Bounds, 2010

 

Wisconsin Poverty Measure
(%)

Confidence Interval: Lower Bound (%)

Confidence Interval:
Upper Bound
(%)

Difference from State Average

County

Milwaukee

16.7

15.1

18.4

Higher

Dane (Madison)

11.9

10.4

13.3

NS

Waukesha

5.1

3.7

6.6

Lower

Brown (Green Bay)

7.3

5.1

9.4

Lower

Racine

11.1

8.5

13.7

NS

Kenosha

11.8

9.0

14.7

NS

Rock (Janesville)

11.1

8.7

13.5

NS

Marathon (Wausau)

7.5

4.6

10.4

NS

Sheboygan

7.0

4.9

9.2

Lower

La Crosse

9.7

6.9

12.5

NS

Multi-County Area

Ozaukee/Washington

4.2

2.8

5.7

Lower

Jefferson/Walworth

9.8

7.5

12.1

NS

Chippewa/Eau Claire

14.5

11.3

17.6

Higher

Calumet/Outagamie/Winnebago (Appleton)

7.5

5.8

9.1

Lower

Columbia/Dodge/Sauk (Baraboo)

6.7

4.9

8.5

Lower

5-county area (Menomonie)

10.8

8.8

12.7

NS

5-county area (Dodgeville)

7.6

6.0

9.2

Lower

6-county area (Manitowoc)

9.6

7.5

11.7

NS

7-county area (Fond du Lac)

9.4

7.4

11.4

NS

8-county area (Sparta)

9.3

7.2

11.4

NS

9-county area (Stevens Point, Crandon)

9.0

7.5

10.4

NS

10-county area (Superior)

10.1

8.3

11.9

NS

State Average

10.3

9.8

10.7

Source: IRP tabulations of 2010 American Community Survey data.
Notes: NS = Not statistically significant. In this analysis, each region's difference from the state average was assessed as not statistically significant if the 90% confidence intervals for each region's statistics and the state's overall statistics overlap.

Table 2. Poverty Rates in Milwaukee, Dane, and Brown Counties under the Wisconsin Poverty Measure with Upper and Lower Bounds, 2010

 

Wisconsin
Poverty
Measure
(%)

Confidence Interval:
Lower Bound
(%)

Confidence Interval:
Upper Bound (%)

Difference from State Average

Milwaukee County (Overall)

16.7

15.1

18.4

Higher

Outer Northwest and East

20.4

16.0

24.7

Higher

Inner North

22.2

17.9

26.5

Higher

Central

35.6

29.4

41.7

Higher

South

15.9

11.9

19.9

Higher

Brown Deer, Glendale, Shorewood,  
Wauwatosa, Whitefish Bay, Other

5.3

2.8

7.9

Lower

Southern Suburbs1

7.0

5.1

8.9

Lower

Dane County (Overall)

11.9

10.4

13.3

NS

Madison

18.4

16.0

20.9

Higher

Fitchburg, Middleton, Stoughton,
Sun Prairie, Other

6.4

4.6

8.2

Lower

Brown County (Overall)

7.3

5.1

9.4

Lower

Green Bay

7.5

4.3

10.7

NS

Rest of Brown County

7.1

4.2

10.0

NS

Source: IRP tabulations using 2010 American Community Survey data.
Note: NS = Not statistically significant. In this analysis, each region's difference from the state average was assessed as not statistically significant if the 90% confidence intervals for each region's statistics and the state's overall statistics overlap.
1 The area includes Cudahy, Franklin, Greendale, Greenfield, Oak Creek, South Milwaukee, and West Allis.

This publication was supported by grant number 3 U01 PE000003-06S3 from the U.S. Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation (ASPE), and ASPE grant number AE00102 awarded by the Substance Abuse and Mental Health Services Administration (SAMHSA). Its contents are solely the responsibility of the author(s) and do not necessarily represent the official views of ASPE or SAMHSA.