Wisconsin Poverty 101 Updated Poverty Fact Sheet:

Institute for Research on Poverty | 3412 Sewell Social Sciences Bldg. | 1180 Observatory Drive | Madison, WI 53706 | www.irp.wisc.eduMorgridge Center for Public Service | Red Gym | 716 Langdon Street | Madison, WI 53706 | www.morgridge.wisc.edu

Prepared by Helen Powling No. 10, 2015–2016Just as the right tool is needed to change a tire, the right measure is needed to understand poverty at the state and local levels. Researchers at the Institute for Research on Poverty at the University of Wisconsin–Madison developed the Wisconsin Poverty Measure (WPM) to provide information the official poverty measure (OPM) cannot, making it the right tool for the job in the Badger State. This fact sheet explores researchers’ most recent findings.

The WPM shows what the OPM does not:• how noncash benefits from food and housing programs and direct

taxes, including refundable tax credits, affect poverty; and

• place-specific, timely data on WI counties and multicounty areas.

A Finer Point on State Poverty under the WPMFrom 2013 to 2014, the statewide overall poverty rate remained flat at about 10.8%, up from 10.2% in 2012 (Fig. 1). Child poverty also stayed the same, at 11.8%, also up from 2012 (Fig. 2). Elderly poverty rose sharply from 2012 to 2013, from 7.4% to 10.0%, and then fell significantly from 2013 to 2014, from 10.0% to 8.3% (Fig. 3). Researchers attribute these bounces (also seen in the OPM) to several factors: inflation adjustments to the WPM thresholds and cost-of-living adjustments to Social Security, and the fact that many elders have incomes just above or below the poverty line, so that small changes in resources move them above or below the poverty line. The WPM elderly rate (8.3%) is higher than the official rate (6.8%) mainly because the WPM counts out-of-pocket medical expenses whereas the OPM does not.

Regional Variation in PovertyThe WPM allows researchers to examine poverty across regions within the state, revealing high poverty rates in some areas, such as Milwaukee and Kenosha (Map 1), and lower rates in many substate areas.

Furthermore, poverty rates examined across subcounty regions show variations that are more dramatic within counties than across the 28 areas in the state depicted in the map below. Within Milwaukee County, for

example, overall poverty rates ranged from about 8.0% in one southern subcounty area to

33.5% in the central city of Milwaukee, suggesting an uneven recovery of jobs and incomes within

counties.

What’s in a Measure?Market-income poverty

is measured by only private income, ignoring all

government taxes and benefits. The OPM adds in the value of

public cash benefits. And the WPM, the most comprehensive,

includes cash benefits and noncash benefits such as food assistance and refundable tax credits.

21.3% 23.2%

24.7% 25.2% 24.4% 24.4% 24.2%

10.2%

12.4% 13.0% 13.5% 12.8% 13.4%12.1% *

11.2%

11.1% 10.3% 10.7% 10.2% 10.9% 10.8%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

2008 2009 2010 2011 2012 2013 2014

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Market-Income-Only Measure Official Measure Wisconsin Poverty Measure

21.5% 23.3%

24.7% 25.6%

23.6% 24.4%

23.0% *

13.3%

17.1% 18.6%

19.4% 17.9%

19.2%*17.6% *

13.6%

12.2% 10.8%

12.2% 11.0%

11.8% 11.8%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

2008 2009 2010 2011 2012 2013 2014

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Market-Income-Only Measure Official Measure Wisconsin Poverty Measure

7.1% 7.4% 7.6% 7.6%

6.2%

9.0%

6.8% *

10.4%

9.6% 9.8%

8.6%

7.4%

10.0%

8.3% *

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

2008 2009 2010 2011 2012 2013 2014

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Official Measure Wisconsin Poverty Measure

Figure 1. Comparing Wisconsin poverty rates under three measures, 2008–2014, reveals a strong safety net using the WPM.

Figure 2. Child poverty rates in Wisconsin decreased significantly from 2013–2014 under the market-income and official poverty measures, whereas the WPM rate was flat.

Figure 3. Elderly poverty rates in Wisconsin under the WPM and OPM, 2008–2014, show significant decreases from 2013–2014 due mostly to Social Security increases.

Higher than state poverty rate

No statistically signi�cant di�erencefrom state rate

Lower than statepoverty rate

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Brown

Manitowoc

Sheboygan

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Calu

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Je�erso

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Waukesha

SaukColumbia Dodge

Waushara

Juneau

Adams

Mar

quette

Green

Lake

Waupaca

Outagamie

Shawano

MenomineeOconto

Marinette

Forest

Florence

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KewauneePepin

Bu�alo

Washburn

Trem

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Jackson

La C

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Monroe

Vernon

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Crawford

Grant

Richland

Iowa

Lafayette

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Walworth

Racine

Kenosha

Douglas Bay�eld

Burnett

Vilas

Lincoln

Sawyer

Rusk

Taylor

Price

Ashland

Iron

Polk Barron

St Croix

Oneida

Langlade

Marathon

Pierce

Dunn

Eau Claire

Chippewa

Clark

Map 1. Comparing 2014 poverty rates to state rate of 10.8% reveals significant variation.

Figures 1–3 Source: IRP tabulations using 2008–2014 American Community Survey data.

Notes: * = The difference between 2013 and 2014 was statistically significant.

For a list of the sources used for this brief and further reading, visit www.irp.wisc.edu/publications/factsheets.htm.

What Does Policy Have to Do with It?

Jobs, Policies, and Poverty

Wisconsin added 60,000 jobs in 2014, but the WPM poverty rate did not decline for a few reasons. New jobs were mostly low wage or part time. In addition, there were reductions in the effects of antipoverty policies such as Supplemental Nutrition Assistance Program (SNAP) and refundable tax credits such as the Earned Income Tax Credit (EITC) due to roll-backs in expansions begun in the Great Recession. Finally, medical expenses and work-related costs increased.

The first four sets of bars in Figs. 4–6 show how programs and policies that the WPM counts reduced poverty from 2008–2014. The last two sets of bars show how work expenses and out-of-pocket medical costs increase the WPM poverty rate. Figure 4 is for the population overall. Figure 5 is for families with children. Figure 6 is for the elderly.

Greatest Antipoverty Effect

SNAP (FoodShare in WI) food assistance benefits had the greatest impact on reducing overall state poverty in 2014, reducing the percentage of people in poverty by approximately 1.9 percentage points. The size of this effect has fallen over the past few years as SNAP benefits have contracted in Wisconsin.

Second Best

Tax provisions such as the EITC had the next best antipoverty effects in Wisconsin. The effects were lower in 2014 than in 2010/2011. In earlier years there was also the Making Work Pay tax credit (in effect in 2009 and 2010), a refundable tax credit from which most wage earners benefited; and a 2 percentage point reduction in payroll taxes (which was in effect in 2011 and 2012).

Policies Particularly Beneficial to Children

The WPM shows that both SNAP and tax credits had a larger effect on reducing child poverty than overall poverty, but both show declining effects after 2010/2011. Although the net impact of the EITC and other tax provisions diminished in 2014 as compared to the earlier years (Fig. 5), it was still substantial, reducing child poverty by 4.5 percentage points.

Childcare, Medical Expenses Strain Budgets

The increased impact of work-related expenses on poverty since 2011 found by the WPM is consistent with rising costs for work-related expenses like childcare in an economy with more people working yet flat or falling wages for low-skill workers (Fig. 5). The steady decline in public spending on childcare subsidies under the Wisconsin Shares program since 2008 also may contribute to families’ rising out-of-pocket work expenses. Among the elderly, medical expenses not covered by insurance are the biggest expense that increases their poverty rates (Fig. 6), less so in 2014 because benefit increases offset higher medical costs.

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2008/2009 2010/2011 2012/2013 2014

Figure 4. The effects of taxes, public benefits, and expenses on overall poverty in Wisconsin varied over time, 2008–2014.

Figure 5. Work-related costs had significant poverty-increasing effects on families with children.

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Figure 6. Out-of-pocket medical expenses drove up poverty to the greatest extent among the elderly.

Figures 4–6 Source: IRP tabulations using 2008–2014 American Community Survey data.

Note: SNAP = Supplemental Nutrition Assistance Program, also known as “FoodShare” in Wisconsin. To simplify the figures, effects averaged over two years are shown for 2008/2009, 2010/2011, and 2012/2013; for year-to-year impacts in 2008 to 2013, see earlier Wisconsin Poverty Reports.

Sources and Suggested Further ReadingWisconsin Poverty 101 Updated

www.irp.wisc.edu Poverty Fact Sheet 10, 2015–2016

Bartfeld, Judith, Craig Gundersen, Timothy M. Smeeding, and James P. Ziliak. 2015. “SNAP Trends and Antipoverty Impacts.” Focus on Policy No. 7. Institute for Research on Poverty: University of Wisconsin–Madison. Available at http://www.irp.wisc.edu/publications/policybriefs/pdfs/PB7-SNAP-Trends-Antipoverty-Impacts.pdf.

Center on Budget and Policy Priorities. 2015. “Chart Book: The Earned Income Tax Credit and The Child Tax Credit.” Available at http://www.cbpp.org/research/federal-tax/chart-book-the-earned-income-tax-credit-and-child-tax-credit#PartOne.

Center on Budget and Policy Priorities. 2015. “Safety Net Programs Lift Millions From Poverty, New Census Data Show.” Available at http://www.cbpp.org/blog/safety-net-programs-lift-millions-from-poverty-new-census-data-show.

Chung, Yiyoon, Julia Isaacs, and Timothy M. Smeeding. 2013. “Advancing Poverty Measurement and Policy: Evidence from Wisconsin during the Great Recession,” Social Service Review 87(3, September): 525–555.

Congressional Budget Office. 2015. “The Effects of Potential Cuts in SNAP Spending on Households with Different Amounts of Income.” Available at https://www.cbo.gov/publication/49978.

Congressional Budget Office. 2012. “The Supplemental Nutrition Assistance Program.” Available at https://www.cbo.gov/publication/43173.

Haveman, Robert, Rebecca Blank, Robert Moffitt, Timothy Smeeding, and Geoffrey Wallace. 2014. “The War on Poverty: Measurement, Trends, and Policy,” Journal of Policy and Management 34(3): 593–638.

Johnson, David, and Smeeding, Timothy. “A Consumer’s Guide to Interpreting Various U.S. Poverty Measures” Fast Focus 14. Available at http://www.irp.wisc.edu/publications/fastfocus/pdfs/FF14-2012.pdf

Levine, M. V. 2014. “Is Wisconsin Becoming a Low-Wage Economy? Employment Growth in Low-, Middle-, and High-Wage Occupations: 2000–2013.” Center for Economic Development Data Brief. University of Wisconsin–Milwaukee.

Smeeding, Timothy M., and Katherine A. Thornton. 2016. Wisconsin Poverty Report: Poverty Levels Flat on Average but More Diverse within State in 2014. Institute for Research on Poverty, University of Wisconsin–Madison. Available at http://www.irp.wisc.edu/research/WisconsinPoverty/pdfs/WI-PovertyReport2016.pdf.

Tiehen, Laura, Dean Jolliffe, and Timothy Smeeding. 2013. “The Effect of SNAP on Poverty” IRP Discussion Paper No. 1415-13. Available at http://www.irp.wisc.edu/publications/dps/pdfs/dp141513.pdf.

United States Census Bureau. 2014. “Comparative Economic Characteristics: 2014 America Community Survey 1-Year Estimates.” See https://www.census.gov/programs-surveys/acs/guidance/comparing-acs-data/2014.html.

United States Census Bureau. 2014. “Income, Poverty, and Health Insurance Coverage: 2014.” Available at http://www.census.gov/content/dam/Census/newsroom/press-kits/2015/20150916_ip_slides.pdf.

United States Census Bureau. 2014. “Measuring America: How Census Measures Poverty.” Available at http://www.census.gov/library/infographics/poverty_measure-how.html.

Wisconsin Department of Children and Families. Wisconsin Shares Website. “Child Care Expenditures by Quarter, 4th Quarter 1997 through 4th Quarter 2015.” Available at http://dcf.wisconsin.gov/childcare/WISHARES/cceq.htm.