Yesterday, Secretary Donovan announcedthe findings from HUD's latest paired-testing study of discrimination against minority homeseekers. An Urban Institute team conducted the study, the third national paired-testing studywe've completed for HUD (see video).
What did we find?
When well-qualified minority homeseekers contact housing providers to inquire about recently advertised housing units, they generally are just as likely as equally qualified whites to get an appointment and learn about at least one available housing unit. However, when differences in treatment occur, white homeseekers are more likely to be favored than are minorities. Most important, minority homeseekers are told about and shown fewer homes and apartments than whites.
Here are the numbers:
Click to view the full infographic
Although the most blatant forms of housing discrimination (refusing to meet with a minority homeseeker or provide information about any available units) have declined since HUD's first national paired-testing study in 1977, the forms that persist (providing information about fewer units) raise the costs of housing search for minorities and restrict their housing options.
How did we produce these results?
In a paired test, two people, one white and the other minority, pose as equally qualified homeseekers and inquire about available homes or apartments. Paired testing originated to support the enforcement of federal fair housing protections, essentially catching discrimination in the act. Researchers have adapted the tool to systematically measure how often discrimination occurs across housing markets and what forms it takes.
Despite its power, paired testing can't capture all forms of discrimination that might occur during a housing search. For example, it doesn't encompass differences in advertising practices that may limit a homeseeker’s knowledge about available housing options. And it can't measure differences in treatment that might occur after an initial inquiry––when homeseekers submit applications, seek mortgage financing, or negotiate lease terms. Moreover, the latest results don't reflect the experience of the average or typical minority homeseeker, because testers presented themselves as unambiguously well-qualified for the advertised homes and apartments about which they inquired.
For all these reasons, the latest study probably understates the total level of discrimination that occurs in the marketplace today. Nonetheless, the long-term trends in patterns of discrimination suggest that the attitudes and actions of rental and sales agents have changed over time, and that fair housing enforcement and public education are working.
What do our latest results mean for policy?
Fair housing enforcement and education are still needed as long as significant discrimination persists. And today's discrimination is very difficult for victims to detect, so enforcement strategies can't rely primarily on individual complaints of suspected discrimination. HUD should encourage the local fair housing organizations it funds to conduct more proactive testing, especially in the sales market, where discrimination appears higher than in the rental market.
Proactive testing can reveal discriminatory practices that would otherwise go unpunished. And when housing providers know that testing is ongoing, they are more likely to comply with the law. In addition, more locally targeted testing may be needed to pinpoint the types of neighborhoods, housing providers, or homeseekers where discrimination is most prevalent. In particular, minority homeseekers with lower incomes, less wealth, weaker English language fluency, or blemished credit may face higher levels of discrimination than documented in this national study.
Finally, local fair housing organizations should expand and strengthen their relationships with Hispanic and Asian communities to tackle the discrimination experienced by all people of color. Historically, the fair housing movement has focused on discrimination against blacks. Although some local organizations have extended their scope in light of changing demographic realities, others have yet to do so.
What do these results tell us about the persistence of residential segregation and neighborhood inequality? I’ll have thoughts on that question tomorrow.
Everyone is talking about the safety net, but what does it really mean? Our new interactive tool, the Safety Net Almanac, shows you how the eight largest assistance programs serving low-income families work and how enrollment and spending have varied over time. The programs are
Supplemental Nutrition Assistance Program (SNAP)
Temporary Assistance for Needy Families (TANF)
The earned income tax credit and the child tax credit
Supplemental Security Income
Child Care and Development Fund
Medicaid and the Children’s Health Insurance Program
What makes the safety net so patchy is that some programs have national eligibility and benefit rules, while rules for others vary from state to state. Some are entitlements that provide benefits for as long as individuals meet the eligibility rules, while others are conditional on government budget limits or are only offered for a limited time. Someone might be able to enroll in a program in one state, but not another.
Comparing the caseload data for TANF and SNAP, for example, shows that TANF caseloads have barely increased since the 2008–2009 recession while SNAP caseloads have skyrocketed. Since TANF is not an entitlement, help does not necessarily expand as family needs increase. SNAP is an entitlement program—meaning that every eligible applicant gets benefits—so caseloads have increased as more families’ incomes dropped below the eligibility threshold.
The Almanac’s interactive graphics allow you to explore national- and state-level caseload and cost trends. It’s a go-to resource for basic program rules and their legislative histories. Users can also download the data for their own analysis.
Over the past 25 years, there’s been a notable shift in relative wealth from the young to the old. The US2010 project’s recent report, based on data collected through the Survey of Consumer Finances, finds average wealth among families under age 35 dropped from 21 percent of the overall mean in 1983 to 17 percent in 2007, and that of age group 35-44 declined from 71 percent to 58 percent.
Losses in wealth among those under age 35 were especially dramatic between 2007 and 2010. In 2010, wealth for families under 35 relative to the national average was only 10 percent, and the 35- to 44-year-olds was only 41 percent, while the 55- to 64-year-olds held 181 percent of the national average.
Using the same data source, another new study from the Federal Reserve Bank of St. Louis also finds that young families were hit harder in the Great Recession. For young families under 40, average net worth dropped about 44 percent between 2007 and 2010, compared with about 18 percent for middle-aged families aged 40-61, or about 10 percent for families 62 or older.
No matter how you look at it—average or median, percentage changes or one group relative to overall, different age cutoff points for the “young,” even different data sources and different time periods—Generation X and Y are becoming “lost generations.” Today’s political discussions often focus on preserving the wealth and benefits of older Americans and baby boomers. But there is an abundance of consistent, data-supported evidence that proves young Americans are falling behind on wealth accumulation—and considering the lack of attention given to the young in government budgets, it’s a serious concern.
In order to solve the federal government’s budget problems, some policymakers have called for cuts in spending on social services, assuming the nonprofit sector can fill the gaps.
What many fail to realize is that the nonprofit sector relies on government support to provide these crucial social services. In fact, in 2010, nearly one out of every three dollars given to public charities came from government sources. So, in addition to rendering them unable to fill any gaps, cuts in funding would force nonprofits to cut nearly one-third of their own services.
While nonprofits are dependent upon the public sector for funding, the government is dependent on the nonprofit sector to provide services to its constituents.
To examine the relationship between government and nonprofit organizations, the Urban Institute conducted a national survey of human service nonprofits in 2009. The survey found that nonprofits that reported problems (like late payments, contracts not covering the full cost of service, complex reporting requirements, etc.) with their government contracts and grants were more likely than nonprofits without problems to freeze or reduce employee salaries, lay off employees, and draw down on their reserves.
Overall, the survey revealed large-scale systematic problems in government-nonprofit contracting and grants processes that adversely affected the ability of many nonprofits to serve their clients. That said, government funding is absolutely necessary to help nonprofits achieve their missions. When nonprofits have difficulty obtaining government funding, the organizations and those they serve suffer. Cuts in federal funding would make this a more common occurrence.
While the survey provided insight into the relationship between the government and nonprofit organizations, many questions were raised about the government’s perspective on nonprofit contracting and grants processes, as well as a need to greater understand trends and improvements in the processes that are underway.
The Center on Nonprofits and Philanthropy at the Urban Institute is in the process of conducting a national survey of all nonprofit organizations (except hospitals and higher education institutions) to compare to the 2009 results. We are also conducting a case study in Maryland to highlight promising practices implemented at the state and local level to improve the government-nonprofit relationship. This follow-up work also seeks to capture the government perspective on its relationship with nonprofits through interviews and a survey of government officials.
As the public and nonprofit sectors rely on each other to provide services, understanding and improving their relationship is a high priority.
What’s the status of arrestee DNA collection in the United States?
Over the past decade, there’s been a large increase in DNA profiles in the National DNA Index System (NDIS). Many are associated with individuals whose DNA was collected at arrest or charging, which is authorized through legislation passed by Congress and more than half the states throughout the country.
Though it’s been argued that the practice is a violation of the Fourth Amendment, the Supreme Court ruled it constitutional for those arrested for serious crimes. Some states may have been waiting to see how the case was decided, so it’s possible that more will adopt arrestee DNA legislation.
In theory, collecting DNA from arrestees effectively expands DNA databases because you’re drawing from a larger population. An underlying assumption is that more DNA profiles in databases will lead to more opportunities for profiles to be linked to evidence from unsolved crimes.
Another assumption is that by collecting DNA sooner in a case—for example, at arrest—crimes may be solved faster.
Who can be subjected to DNA collection?
It depends on the state. Thirteen collect from all felonies, while fourteen limit collection to a subset of felonies, typically involving violence, sexual assault, and property crimes. Seven also collect from individuals arrested or charged with select misdemeanors. One state, Oklahoma, authorizes DNA collection at arrest from “any alien unlawfully present under federal immigration law.”
Federal law authorizes collection from all arrestees and non-US citizens detained by the US government.
What about those who are arrested, but ultimately not charged with, or convicted of, a crime?
In most states that authorize DNA collection from arrestees, individuals who are not charged or convicted may request that their DNA profile be removed from the database. It’s up to them to initiate the process, which usually requires obtaining a court order that is then sent to the laboratory.
Labs in these states have indicated that few removals (or expungements, as they’re officially called) actually occur, effectively resulting in profiles that are stored in the database for an indeterminate amount of time.
A few laws (like Maryland’s) require the state to automatically remove an arrestee DNA profile from the database if the individual isn’t charged or convicted. Automatic expungement can be resource-intensive for laboratories, as they are generally responsible for tracking case outcomes in these states.
What are some of the challenges to implementation?
The two biggest challenges are costs and time, with most of the burden falling on the state labs, which will need to hire and train new staff, change existing processes, and train collection agencies. Implementation will likely also result in more administrative work, such as verifying sample eligibility, identifying duplicate submissions, and monitoring compliance.
Is arrestee DNA collection actually worth it? Does it result in more convictions?
It’s hard to say. Most states do not reclassify arrestee profiles as convicted offender profiles upon conviction. A match—or hit—linking an arrestee profile to crime scene evidence may occur after the individual has been convicted and would have submitted a sample anyway. At the NDIS level, the FBI does not yet report data on hits associated with arrestee profiles.
Most states that provided data for this study indicated the number of hits associated with arrestee profiles, but they didn’t break down the data further to identify how many were associated with profiles from arrestees who were not subsequently convicted, or how many occurred between arrest and conviction.
Two states were able to determine the number of hits attributed to arrestee profiles that would not have occurred—or would have occurred later—if DNA was only collected upon conviction. In these states, arrestee profiles did increase the number of resulting hits, investigations aided, and successful prosecutions.
When couples decide to get married, the IRS is not the first institution they have in mind, but marriage can significantly affect how much taxpayers owe the federal government. Low-income earners—and low-income single mothers in particular—are especially vulnerable to marriage penalties through the tax code.
Most married couples owe less tax by filing jointly than they would if they were single: a marriage bonus. But low-income couples and high-income dual-earner couples still tend to face marriage penalties. In the extreme, consider a mother earning about $16,000 a year. If she has one child, she’ll qualify for about $3,200 from the earned income tax credit (EITC) and $1,000 from the child tax credit. (She also qualifies for food assistance from the Supplemental Nutrition Assistance Program --formerly food stamps-- and might qualify for child care and housing subsidies, depending on where she lives.)
If she were to marry a man earning about $25,000 a year, she would lose 90 percent of her EITC. That means that, together, they would owe almost $2,800 more in federal income taxes as a married couple than they would if they’d just decided to shack up. (Benefits outside the tax system are often sensitive to whether the couple lives together, but taxes are concerned only with marital status.)
What can we do to fix this imbalance?
One option would be to separate work and family credits in the tax code, with family credits reflecting the cost of maintaining a home and work credits incentivizing employment for low-income workers. All benefits would therefore be unrelated to marriage. Alternatively, newly married mothers could be given a marriage “grace period” during which they would continue receiving their pre-marriage benefits.
Both of those plans have problems, though. The first is potentially quite costly and may result in a politically untenable number of “losers” who would end up paying more in taxes. The second would not tax all married couples equally, which creates a new unfairness in the tax code.
Another solution, New Mothers Tax Relief, mitigates both of those problems by extending substantial EITC benefits to low- and moderate-income working couples until they jointly earn $40,000. The credits would then phase out by about $58,000.
For couples earning between $36,000 and $58,000 a year, New Mothers Tax Relief would provide at least $2,000 more in benefits than the current EITC program, reducing financial difficulties that often create marital tensions. The proposal limits total program costs by extending benefits only to families with children younger than six. Most important, for this vulnerable group of unmarried parents with young children, the federal tax code would be mostly removed from the decision to marry.
Two months ago I said that worry over March’s “weak” jobs growth report of just 88,000 new jobs was misplaced – that preliminary estimate was likely to change significantly. It did get adjusted – first to 138,000 and then to a final 142,000.
You really don’t need to hear it from me again, but the same caution must apply to today’s moderate report of 175,000 new jobs. Why?
My worry two months ago was that focusing too much attention on a notoriously volatile preliminary estimate (see the interactive chart below) could unduly influence policy decisions. (Even worse was the nail-biting in this week’s headlines ahead of the report, fretting that a too-strong number could also harm the economy. Huh?)
The real issue here is that one number – the national total number of nonfarm jobs – is a really blunt instrument for assessing the state of a vast economy. For one thing, it misses a whole host of other indicators critical to the health of the jobs market - the unemployment rate, the labor force participation rate, or the effectiveness of safety net programs like unemployment insurance, for example.
Assessing true economic recovery (or decline) requires a more nuanced approach. With the exception of the government and manufacturing sectors (manufacturing was a bright spot early in the recovery), there has been steady (if anemic) national growth across most of the economy – total private jobs, services, financial activities, goods production, and health care and education – indicating resilient growth that’s not over-reliant on any one industry (housing construction, for example).
But that’s still not the whole story. As the interactive map above shows, some parts of the country are recovering from the recession better than others. Albuquerque, for example, has lost jobs since the end of the recession in every sector except government and health and education. Regardless of the strength of today’s jobs report, Albuquerque’s economy is struggling.
In contrast, Austin, TX has gained jobs in nearly every sector since the end of the recession, indicating a more robust and balanced recovery. In general--but not always--Southern and Midwestern metros have gained jobs across sectors, while some Western and Northeastern metros have struggled.
A final thought: the economy could theoretically gain many jobs each month without a drop in the unemployment rate (due to population growth) or the unemployment rate could fall with no gain in jobs (as discouraged people give up looking). Looking at just one number rarely tells the whole story.
Suburban poverty is in the headlines again these weeks after the publication of Brookings researchers Elizabeth Kneebone and Alan Berube’s new book, Confronting Suburban Poverty in America, which augments previous empirical work with fascinating case studies. But with the suburban poverty rates hovering around 11 percent, relative to 21 percent in cities, the question arises: is it suburban poverty or resilience that they are finding?
The story Brookings tells is about the higher poverty growth rates in the suburbs. However, growing suburban poverty is tracking increases in national and metropolitan poverty rates. The questions then become, why does suburban poverty remain so much lower than urban poverty, and why is it not changing faster?
There are at least five possible explanations for this suburban resilience:
The first is that communities are able to absorb poverty that is relatively low and not spatially concentrated. Suburban municipalities, schools, and voluntary associations have enough capacity to cope with 11 percent poverty. It is in the city neighborhoods with poverty rates of 30 percent or higher that systems break down.
The second is that this suburban poverty, which is led by immigrants, is somehow different. Not only do immigrant groups rely on networks of extended family, but also they do not experience as much racial discrimination as have the urban poor, particularly African Americans, historically.
Another possibility is that accessibility – to jobs, services, and amenities – is not the type of challenge in suburbs that it is portrayed to be. Although transit services are inadequate, many low-income households rely on cars to manage their complex suburban lives. For the low-income, the issue is not how to get to social services once a month, but whether you can borrow a car from family every day.
A fourth explanation is that many suburbs continue to exclude low-income households, whether through zoning or discouraging the construction of affordable housing.
Or, these findings could just be an artifact of the analytic approach. The Brookings research designates almost all places not named in the Census official metropolitan area name as suburbs – meaning that cities like Gary, Indiana are combined with Gaithersburg, Maryland. This turns suburban poverty into a fuzzy concept.
In fact, recent work by Rolf Pendall, Margaret Weir, and Chris Narducci for the Building Resilient Regions network suggests the importance of narrowing focus. Comparing Chicago and Denver, they find that the suburbs best able to deal with poverty are larger jurisdictions where poverty is relatively dispersed. This raises the possibility that concentrated poverty remains the issue, not urban versus suburban.
It is not clear, then, that government policy is failing to provide a social safety net in the suburbs. To the extent that accessibility is an issue, we need to be sure that family networks – and their cars – are available. If the issue is subsistence – access to school lunch or health clinics – then the county level is probably the most efficient way to deliver services, as it does already. If the problem is not enough tax revenues to cover police and fire services, then perhaps we need to shift those to the county level too, as is already happening in many suburbs.
We continue to view and analyze cities and suburbs as separate constructs, even though sociological research since Herbert Gans’ TheLevittowners has shown that people in cities and suburbs are both, well, people, with similar values and needs. So perhaps what we need is a new pro-people strategy, not a new anti-poverty strategy.
Photoillustration by Tim Meko, Urban Institute. Source image from Flickr user Les Taylor (CC BY-NC-SA 2.0)
About 15 percent of Americans are living in poverty and many more experience one or more spells of poverty over the course of a year. Thanks to Alan Berube and Elizabeth Kneebone’s new book, Confronting Suburban Poverty in America,people are talking about this bleak reality and what to do about it.
Over the past few months, the two of us have been focusing on an even more distressing reality: the 6.6 percent of Americans—more than 20 million adults and children—who live in deep poverty.
Deep poverty is commonly defined as having cash income below half the poverty line—in 2012, that’s less than $1,000 a month for a family of four. Other measures change this picture slightly, but even the Census Bureau’s new Supplemental Poverty Measure puts deep poverty at about 5 percent after factoring in cash transfers, tax credits, and tax liabilities, as well as major expenses like the cost of commuting to work, out-of-pocket medical costs, and child support payments.
People suffering from deep poverty are diverse and their circumstances defy simple characterizations. Their needs reflect multiple and often interacting disadvantages. They include single mothers and their children, people who are homeless or formerly incarcerated, disabled veterans, and people with serious mental illnesses. They include many immigrants. While people of color have among the highest levels of poverty, the poor and deeply poor are predominantly white. About half of those living in deep poverty are under age 25. Most deeply poor adults aren’t working.
Many people in deep poverty face significant personal challenges: disabilities and other major health problems, very low levels of education and work skills, criminal background histories, and limited social networks that can buffer them in hard times. Any of these challenges makes working difficult and research shows that combinations of multiple challenges make it especially hard for people to escape deep poverty. They also make it hard to provide a stable and nurturing environment for children.
Over the course of months and years, many people cycle in and out of poverty. A job loss, a divorce, a natural disaster, or time away from work to care for a newborn or tend to an ill family member can all push a family into poverty—even deep poverty—temporarily. Many of these families climb back out of poverty fairly quickly. Indeed, about half the people who fall into poverty are poor for less than a year, and about three-quarters are poor for less than four years.
But about a third of people who become poor in a given year will remain poor for half or more of the next 10 years. Persistent poverty year after year is very debilitating. Children raised in persistently poor families have far worse outcomes later in life than those who were poor for just a year or two.
Poverty is, by definition, a lack of income. But deep and persistent poverty reflects deficits that are much more profound. Addressing them requires intensive and sustained supports that span conventional policy and programmatic silos. The work requirements and other conditions imposed by many of today’s federal safety-net programs may make sense for people experiencing short spells of poverty, but they are clearly failing to meet the needs of people in deep and persistent poverty.
As the nation tackles poverty in the aftermath of the Great Recession—and develops strategies that reflect new economic and geographic realities—let’s remember people living in deep and persistent poverty. The portfolio of anti-poverty tools deployed in any community should include the intensive, multi-faceted, and long-lasting supports needed by individuals and families trapped in deep and persistent poverty.
Photograph by JOAKIM ESKILDSEN from "Below the Line: Portraits of American Poverty," photo-essay commissioned by Time magazine, November 2011, and forthcoming in Joakim Eskildsen and Natsha Del Toro, American Realities (Steidl). Used with permission.