by Deona Hooper, MSW
New York City Police Officer Lawrence DePrimo was caught on camera by an Arizona tourist performing a random act of kindness for a homeless man sitting on the sidewalk with no shoes or socks. According to news reports, the officer went into Sketchers to purchase socks and a pair of all weather waterproof boots for the man who turned out to be a homeless veteran.
The tourist saw him purchasing the boots and followed the officer outside in order to use her mobile phone to capture the above picture. She then posted the picture on the NYPD Facebook page which has gone viral with over 3 million hits. The officer did not know the picture had been taken until it was posted to the NYPD’s Facebook page. View the news reporting video by Newsy.
Why Housing Affordability Needs To Be Reevaluated
Traditionally, academics and policymakers have determined whether an individual or family can afford to live somewhere by simply dividing their housing costs by their income. If at least 30 percent of a person’s or family’s income goes to housing and related expenses like utilities, then their household is said to be “cost burdened.” The ratio is not determined by economic or social analysis; rather, it is simply the number Congress chose in 1981, which has not been changed nor updated since. Although this approach is easy to understand, it falls short of accurately reflecting the financial burdens people actually experience. This is a problem because many federal housing programs rely on this 30 percent measure to determine rent.
Measuring Housing Affordability
This ratio-based approach breaks down for Americans with extremely low incomes. If wages decline, a middle-class family could potentially downsize its home or related expenses. When people live below the poverty line, however, they must spend above a minimum just to reside in a home that meets the local building codes and meets basic human needs.
“Shelter poverty” analysis provides an alternative to the traditional approach. Shelter poverty is a concept that was first developed by Michael Stone, a professor of community planning, in the 1970s. In this analysis, instead of comparing housing costs to income, housing costs are evaluated in the broader context of the household’s other basic needs, including food, clothing, and transportation. If housing costs are high enough that household’s residents cannot cover these basics from their income, then they are said to be experiencing shelter poverty. The challenge for this method lies in determining how much money must be spent to meet other needs, especially because the federal government no longer publishes such estimates for non-housing necessities.
The Self-Sufficiency Standard, created by University of Washington senior lecturer Diana Pearce in the 1990s, addresses this issue by compiling estimates of basic expenditures from various public and private sources, based on the county of residence, the number of persons in the household, and the age(s) of any children present. This information can be combined with anonymized responses to the American Community Survey, a nationally representative survey conducted annually by the U.S. Census Bureau. The combined data make it possible to determine whether each household in the sample is experiencing shelter poverty. This method also helps determine if, and by how much, households fall short in covering their expenses. That is called the “affordability gap.” Using estimates developed in this way, analysts can extrapolate out to the general U.S. population.
Housing Affordability in Ohio and South Carolina
A shelter poverty analysis was conducted for Ohio renters who responded to the American Community Survey, and for sampled South Carolina renters and homeowners (including both mortgage holders and those who own a home free and clear). In both states, the shelter poverty method generates substantially different results than a basic cost burden analysis. Although overall rates of economic distress are generally similar using the two different measures, the total affordability gap using the shelter poverty measure is substantially larger. Among Ohio renters, it would take over $3 billion annually to address cost burdens using the 30 percent metric, but nearly $15 billion per year to mitigate shelter poverty entirely. The disparity is somewhat narrower in South Carolina, but a similar gap exists.
There are differences in the areas of need as well. In both Ohio and South Carolina, the prevalence of a cost burden measured by the ratio system is higher than the burden of shelter poverty in suburban areas with the highest median household incomes. In economically distressed urban and rural areas in both states, far more households experience shelter poverty than excessive ratio cost burdens. In other words, it appears that current standards of housing affordability overstate the needs of families who are most able to pay and understate burdens for those least able to do so.
Improving Housing Affordability
Overall, experts may not be accurately describing the magnitude and nature of housing affordability challenges in the United States. Those experiencing shelter poverty are found in nearly every community nationwide. In South Carolina, which is not by national standards a particularly expensive state to live in, households experiencing shelter poverty (nearly one-third of all individuals and families statewide) have an average affordability gap of $14,330 per year, or about $275 per week.
Meanwhile, the geographic distribution of shelter poverty suggests that the 30 percent measure distorts the landscape of housing affordability. That distortion happens because there are households that choose to spend more than 30 percent of their income voluntarily and are thus inappropriately categorized as cost burdened. Meanwhile, others spend less than 30 percent on housing costs but still find they do not have enough to make ends meet. Taken together, failure to consider these issues leads decision-makers to understate the level of economic inequality among U.S. households.
It is worth noting that affordability gaps are not only measures of deprivation experienced by less fortunate Americans. These gaps also reflect economic activity that is lost due to the inability of many households to meet basic needs. Ohio renters have about $15 billion less to spend each year as consumers in the state’s economy because they lack access to affordable housing.
Although housing costs have become more politically salient in recent years, the scope and scale of the problem have not been fully articulated. Housing is the single largest expense for most individuals and families, and it is typically regulated at the county and municipal level through zoning codes and related ordinances. Local policymakers must consider whether their policies are harming the welfare of residents and businesses alike by artificially restricting housing supply or preventing construction of subsidized housing.
All Americans have a stake in better measurements of housing affordability – and better solutions to the shortfalls many people face in this vital area. A shortage of affordable homes can have numerous downstream effects. Employers may face high rates of labor turnover if employees cannot find places to live in the vicinity. Longer commuting distances increase the amount of traffic and contribute to urban sprawl, which has a variety of negative environmental, social, and economic consequences.
To find solutions, local officials must engage with homeowners, renters, business owners, and nonprofit groups, as well as housing policy experts in the public and private sectors. To ensure communities across the country have a path toward a prosperous and sustainable future, everyone must be able to find a suitably located and affordable place to call home.
Opinions expressed in this brief are those of the author alone, not the State of South Carolina or any other entity.
Read more in Bryan P. Grady, “Shelter Poverty in Ohio: An Alternative Analysis of Rental Housing Affordability,” Housing Policy Debate 29, no. 6 (November 2019): 977-989.
Report: Home Health Aides Scraping By on Low Wages During Pandemic
On Equal Pay Day, the Rutgers Center for Women and Work highlights the growing number of home health aides in New Jersey and the economic challenges they face
New Jersey’s home health aides are caring for seniors and people with disabilities during the COVID-19 pandemic, while earning an average salary of just $25,000 per year, according to a report released today by the Center for Women and Work at the Rutgers School of Management and Labor Relations. Since home health aides and other domestic workers are predominantly women, their low wages help to explain why the gender wage gap persists in New Jersey and across the U.S.
“With all of the attention rightly focused on our incredible doctors, nurses, and first responders, it’s easy to forget about the thousands of home health aides who are caring for vulnerable New Jerseyans every day,” said Debra Lancaster, executive director of the Rutgers Center for Women and Work. “We’ve seen a growing demand for their services over the last 20 years. Yet, they remain among the lowest-paid workers in our state.”
Home health aides check vital signs and assist their clients with bathing, dressing, meals, medications, and other daily activities, while providing companionship and emotional support. Some aides live with their clients 24/7. Others work for home health agencies and visit multiple clients daily. The Rutgers Center for Women and Work’s analysis of federal data finds:
- New Jersey has about 36,000 home health aides. That’s more than almost every other state.
- 95 percent are women; 51 percent are immigrants; and 69 percent are Black, Hispanic, or Asian.
- The number of home health aides in New Jersey is on the rise due to an aging population.
- Despite the important services they provide, home health aides are low-wage workers.
- The average home health aide in New Jersey earns between $23,380 and $25,330.
The Center for Women and Work made the announcement on Equal Pay Day, the symbolic date on which women’s earnings catch-up to men’s earnings from the previous year. New Jersey ranks at or near the bottom of all states on pay equity for women of color. Latina women in New Jersey earn 42 cents and black women earn 56 cents for every dollar a white man earns, according to data from the National Women’s Law Center.
“The low wages paid to home health aides and other domestic workers are a major reason why we still have a wage gap in 2020,” said Yana Rodgers, economist and faculty director of the Rutgers Center for Women and Work. “It’s not always a function of overt discrimination. In many cases, the problem is that jobs thought of as ‘women’s work’ do not pay as much as ‘men’s work.’ Until that changes, the wage gap is not going away.”
About the School
The Rutgers School of Management and Labor Relations (SMLR) is the world’s leading source of expertise on managing and representing workers, designing effective organizations, and building strong employment relationships. SMLR’s Center for Women and Work engages in research, education, and programming that promotes economic and social equity for women workers, their families and communities.
Hardship During the Great Recession Linked with Lasting Mental Health Declines
People who suffered a financial, housing-related, or job-related hardship as a result of the Great Recession were more likely to show increases in symptoms of depression, anxiety, and problematic drug use, research shows. The research findings, published in Clinical Psychological Science, a journal of the Association for Psychological Science, reveal declines in mental health that were still evident several years after the official end of the recession, but were obscured when examining trends in population-level data (e.g., the number of people overall with each mental health outcome).
“Our study provides a new perspective on the impact of The Great Recession, showing that population-level analyses likely miss important patterns in the data,” says lead researcher Miriam K. Forbes, who began the research at the University of Minnesota and now works at Macquarie University in Sydney, Australia. “By looking at individuals’ mental health and experiences of the recession, we could see a different picture.”
“Individuals who experienced even a single recession impact still had higher odds of nearly all of the adverse mental health outcomes we examined – including clinically significant symptoms of depression, generalized anxiety, panic, and problems with drug use – three years after the recession,” Forbes explains. “And these odds were higher still in specific sociodemographic groups who suffered marked losses during the recession or without a strong safety net.”
Forbes and University of Minnesota colleague Robert F. Krueger examined data collected as part of the longitudinal Midlife in the United States study of adults aged 25 to 75. To investigate the impacts of the Great Recession, which officially lasted from December 2007 to June 2009, the researchers focused on data collected in the 2003-2004 wave, three years before the recession began, and the 2012-2013 wave, three years after the recession ended.
Forbes and Krueger examined participants’ symptoms of depression, anxiety, and panic disorder and their symptoms of problematic alcohol and drug use. In the 2012-2013 wave, participants also reported whether they had experienced a variety of recession-related impacts, including financial impacts (e.g., missed mortgage or credit card payments, declared bankruptcy), job-related impacts (e.g, took on an additional job, lost a job), and housing impacts (e.g., moved in with family/friends, threatened with foreclosure).
As observed in previous studies, the prevalence of each mental-health outcome in the full sample remained stable or decreased slightly from 2003-2004 to 2012-2013. But when the researchers looked at mental-health outcomes in relation to the hardships individuals experienced as a result of the Great Recession, the analyses told a different story. Specifically, each hardship experienced was associated with an increased likelihood of having symptoms of depression, generalized anxiety, panic, or problems with drug use. This pattern held even when Forbes and Krueger accounted for participants’ previous symptoms and their sociodemographic characteristics.
The researchers also found that individuals who did not have a college education were more likely to show increased anxiety in relation to job-related hardships. And people not living with a spouse or partner were more likely to have problems with drug use associated with housing-related hardships. These associations may reflect the relative lack of safety net available to people in the job market who have fewer qualifications, or who rely on a single income.
The analyses also showed that people with greater financial advantage were particularly affected by some hardships. Compared with their less-advantaged peers, participants who were well off were more likely to have anxiety symptoms associated with housing-related hardships and were also more likely to have drug use problems associated with financial hardships. These associations may reflect that fact that experiences such as “moving in with friends or family to save money” or “selling possessions to make ends meet” likely signal a substantial loss of assets and a considerable level of hardship for people who were previously living comfortably.
The researchers note that the observational nature of the MIDUS data does not allow them to conclude that recession hardships caused an increase in participants’ symptoms. However, the findings do reveal the limited perspective afforded by aggregate-level analyses – understanding people’s actual lived experiences requires analyses that examine individual-level outcomes and changes over time.
The Great Recession of 2007 to 2009 resulted in huge losses to employment, earnings, assets, and income in the United States and this research shows that those losses were associated with lasting negative mental health outcomes for many individuals.
“These findings suggest the adverse effects of the Great Recession on individuals’ mental health likely compounded and prolonged its economic costs, highlighting that government-funded mental health support following financial recessions may not only ease individuals’ burdens, but could be a sound financial investment that may act to stimulate faster economic recovery following future recessions,” says Forbes.
“These findings may be particularly pertinent given some indications that the next period of economic contraction might begin as early as 2020,” she adds.
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