Policy and Promise for Low Income People in America
POLICY AND PROMISE FOR LOW-INCOME PEOPLE IN AMERICA john a. powell, Executive Director, The Kirwan InstituteMarch 10. 2011 Racial Equity and Federal Policy
Overview Opportunity Matters Historic role of Federal Policy Example Policy: Unemployment Insurance Post-Racialism or Targeted Universalism?
Opportunity MattersStructural Racialization and Systems Dynamics
Why do some people have access to the “goodlife” while others do not?
Our opportunity context mattersSome people ride the “Up” Others have to run up the escalator to reach “Down” escalator to get there opportunity
Opportunity is….Racialized… Spatialized… Globalized…• In 1960, African- • marginalized people • Economic American families in of color and the very poverty were 3.8 times globalization poor have been more likely to be spatially isolated from concentrated in high- opportunity via • Climate change poverty neighborhoods reservations, Jim Crow, than poor whites. Appalachian mountains, ghettos, • the Credit and• In 2000, they were 7.3 barrios, and the Foreclosure crisis times more likely. culture of incarceration.
It’s more than a matter of choice… The Cumulative Impacts of Spatial, Racial and Opportunity Segregation Segregation impacts a number of life-opportunities Impacts on Health School Segregation Impacts on Educational Achievement Exposure to crime; arrest Transportation limitations and other inequitable public services Neighborhood Job segregation Segregation Racial stigma, other psychological impacts Impacts on community power and individual assetsAdapted from figure by Barbara Reskin at: http://faculty.washington.edu/reskin/
From a one- dimensional understanding… • One variable can explain why differential outcomes. …to a multi-dimensional understanding…. • Structural Inequality – Example: a Bird in a cage. Examining one bar cannot explain why a bird cannot fly. But multiple bars, arranged in specific ways, reinforce each other and trap the bird.
...to an understanding of processes and relationships• Understanding the relationships among these multiple dimensions, and how these complex intra- actions change processes • Relationships are neither static nor discrete
We need to think about the ways in which the institutions that mediate opportunity are arranged The order of the structures The timing of the interaction between them The relationships that exist between/among them
Federal PolicyHistoric Examples of Federal Impact onOpportunity
Historic Government Role A series of federal policies have contributed to the disparities we see today School Policy Suburbanization & Homeownership Urban Renewal Public Housing Transportation
Redlining and Opportunity Philadelphia Mortgage Insurance and Redlining Historic Lending and Today’s Opportunity Landscape
Unemployment InsuranceThe Role of Federal Policy in Racial Equity
Blacks and Latinos have endured especiallyhigh unemployment during the latest recession
Blacks and Latinos also are overrepresented among the long-term unemployed (Dec 2010)2520 % of Labor Force15 % of Unemployed % of Long-term Unemployed (5210 weeks+) 5 0 BLACKS LATINOS ASIAN AMERICANSSource: Bureau of Labor Statistics, Current Population Survey
The relationship between race/ethnicityand long-term unemployment holds over time
However, Blacks seem to be somewhat underrepresented and Latinos very underrepresented among UI recipientsThere are 15 states for which we have fairly good race/ethnicity data on UI recipients in 2009. The unemployed in these states include 2.9 million whites, 1.1 million African Americans, and 360,000 Latinos. Recipiency rates by race/ethnicity across 15 states, 2009 45.0% 40.0% 42.8% 41.0% 35.0% 39.1% 30.0% 32.4% 25.0% 20.0% 15.0% 10.0% 5.0% 0.0% Overall White Black Latino Source: BLS Local Area Employment Statistics and DOL Employment and Training Administration, Characteristics of the Insured Unemployed for Calendar Year 2009; BLS Preliminary 2009 Data on Employment Status by State and Demographic Group
There is significant variation in relative recipiency rates by race/ethnicity at the state level Recipiency rates by race/ethnicity in most populous of the 15 states, 200970%60% White recipiency rate Black recipiency rate50% Latino recipiency rate40%30%20%10%0% Ohio Maryland Georgia Illinois North Carolina Pennsylvania TennesseeSource: DOL Employment and Training Administration, Characteristics of the Insured Unemployed for Calendar Year 2009; BLS Preliminary 2009 Data on Employment Status by State and Demographic Group
Even “high income” African American families can ill afford missed paychecksSource: Institute on Assets and Social Policy, “The Racial Wealth Gap Increases Fourfold.” May 2010.
Possible explanations: It may be that…1. Blacks and Latinos more likely to live/work in low- coverage states (geographic distribution/bad-luck )2. Blacks and Latinos less likely to meet state eligibility criteria (worker status issue/bad luck)3. Disparities by race/ethnicity are not coincidental; the Unemployment Insurance program is “racialized” in design and by the role of bureaucratic discretion in its implementation4. Unemployed Blacks/Latinos less likely to apply for UI5. Undocumented immigrants more likely to count among the unemployed than to receive UI benefits
1. Relative to Whites, Blacks and Latino populations are unfavorably distributed in re state UI recipiency rates Distribution of US population by race/ethnicity and state recipiency rates – low (20%-41%), medium (41%-50%), and high (51%-69%) – in November 2009 100% 90% 27% 27% 32% 80% 33% 70% 60% 20% 37% 31% High 50% 32% Medium 40% Low 30% 53% 20% 35% 36% 38% 10% 0% White population Black population Latino population Entire populationSource: U.S. Census Bureau, "Estimates of the Resident Population by Race and Hispanic Origin for the United States and States: July 1, 2008 (SC-EST2008-04),“ and ProPublica, “Is Your States Unemployment System in Danger? November 2009/ http://www.propublica.org/special/is-your-states-unemployment-system-in-danger-603
2. Blacks and Latinos overrepresented among unemployed workers most likely to be ineligible Among unemployed, African Americans less likely than whites to be “job losers” in 4th quarter, 2010 58% and Blacks and 64% of whites were “job losers” (vs. new entrants, reentrants, etc) Blacks and Latinos disproportionately low-income. The EPI estimated that in 2009: Blacks were 11% of the workforce, but 18% of workers affected minimum wage increase to $7.25/hr. Hispanics were 14% of the workforce and 19% of workers affected by increase.
3. Is UI racialized in design and through the role of discretion in its implementation? If so, one would expect, for example: A positive association between recipiency rates and proportion African American and/or Latino A positive association between wrongful denial of UI benefits and proportion Black and/or Latino Relatively favorable results to African Americans and Latinos in states that rely more on automation Greater denial of African Americans and Latinos than of similarly situated White claimants
Black-White Implicit Association Test Results Strong preference for Blacks 2% Moderate preference for Blacks 4% Slight preference for Blacks 6% Little to no preference 17% Slight preference for Whites 16% Moderate preference for Whites 27% Strong preference for Whites 27% 0% 5% 10% 15% 20% 25% 30%N = 732,881
A few proven behavioral implications of implicit bias In “shooter game,” mistakes follow clear pattern: people shoot more unarmed blacks and fail to shoot armed whites Doctors’ implicit racial attitudes unequal treatment for Latinos and Blacks compared to Whites Resumes with “white-sounding” names (Emily, Greg, Jill, Todd) receive 50% more call-backs than those with “black-sounding” (Jamaal, Latoya, Tyrone, Lakesha) names. Neighborhoods with White-only residents evaluated much more favorably than same neighborhoods with black residents or racially mixed residents More or less implicit bias corresponds to comfort level and body language in interracial interactions“Emergency Treatment May Only Be Skin Deep.” Science Daily 11 Aug. 2007
Back to UI -- states with higher proportions of Black Americans do also have lower coverage rates Black state population shares x recipiency rates (2010) (Correlation = -0.40) 0.6 0.5 0.4 IUR/TUR Recipiency 0.3 0.2 0.1 0 0.000 0.100 0.200 0.300 0.400 0.500 0.600 Pct. of State Population African AmericanSource: http://www.doleta.gov/unemploy/chartbook/chartrpt.cfm
Same is true for Latinos, but the relation- ship is weaker than for African Americans Latino state population shares x recipiency rate (2010) (Correlation = -0.16) 0.6 0.5 0.4 IUR/TUR Recipiency 0.3 0.2 0.1 0 0.000 0.050 0.100 0.150 0.200 0.250 Pct. of State Population LatinoSource: http://www.doleta.gov/unemploy/chartbook/chartrpt.cfm
For Whites, the reverse is true: the greater the White proportion, the higher the coverage rate White population shares & recipiency rates (2010) (Correlation = 0.22) 0.600 0.500 0.400 IUR/TUR Recipiency 0.300 0.200 0.100 0.000 0.000 0.200 0.400 0.600 0.800 1.000 1.200 Pct. of State Population WhiteSource: http://www.doleta.gov/unemploy/chartbook/chartrpt.cfm
The distribution of the black population nationally has not changed dramatically between 1930 and 2000 1930 2000 31
State shares of B’s/L’s were positively associated with impropermonetary denial rates, not with separation/non-separation errors (Correlation = .27) 45% 40% Improper monetary denial rates 35% 30% 25% 20% 15% 10% 5% 0% 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Percent of state population that is Black and LatinoSource: DOL Employment and Training Administration, Benefit Accuracy Measurement, Denied Claims Accuracy Report 2009. http://www.ows.doleta.gov/unemploy/bam/2009/Denied_Claims_Accuracy_Rates_CY_2009.xls
Potential ResponsesTo possibility of racial/ethnic bias: Make race/ethnicity data collection mandatory for all UI applicants Conduct audit tests for bias in claims processing Reduce bureaucratic discretion through still-greater use of automation Offer de-biasing training
Potential Responses (cont.)Expanding access and speeding transfer: Support wider state adoption of modernization reforms Require employers to distribute UI information to displaced workers Change the benefit calculation formula to aid low-income workers Allow workers to bank their benefits over time