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Posts By Robert Lerman
Dr. Robert Lerman, a leading expert on how education, employment, and family structure work together to affect economic well-being, is the Urban Institute's first Institute fellow in labor and social policy. He was director of the Institute's Labor and Social Policy Center from 1995 to 2003.
Dr. Lerman was one of the first scholars to examine the factors leading to unwed fatherhood and the effects of early unwed fatherhood on earnings. His work on youth apprenticeships in the late 1980s encouraged the creation of national school-to-work programs. Dr. Lerman's current research focuses on interactions between job and marital stability, the effects of marriage promotion programs, and youth transitions from school to career.
The author of more than 150 articles, monographs, reports, reviews, and conference papers, Dr. Lerman has held dual appointments with the Urban Institute and the economics department at American University since 1995. He chaired the American University department from 1989 to 1995 and continues to be a professor of economics there. Dr. Lerman has served on a variety of panels and commissions, including the National Academy of Sciences panel looking at the nation's postsecondary education and training system for the workplace and the board of the National Fatherhood Initiative. He has testified before congressional committees on such topics as youth apprenticeship, child support policies, and the information technology labor market.Links: http://www.urban.org/expert.cfm?ID=RobertILerman
| Posted: December 2nd, 2013
This post originally appeared on Family-Studies.org.
Stagnant wages among men without college degrees and rising unmarried parenthood among high school graduates with little or no college education represent two critical challenges facing the United States. Both trends increase income inequality and prevent people from entering into and remaining in the middle class.
One symptom of the problem is the declining labor force participation of men at middle levels of education and at prime working ages. Nearly half of 25- to 49-year-old men are high school graduates (or GED completers) without an associate’s or bachelor’s degree. Long-term trends as well as current economic weakness have been bad news for this group. For men with no more than a high school degree, joblessness doubled from 7.5% in 1979 to 15.5% in 2007 just before the Great Recession. As of early 2013, 22% of these prime-age men were not employed. Over the same period, married fatherhood plummeted among high school graduate men, falling from 65% in 1979 to 38% in 2013. Especially since joblessness is associated with negative family outcomes, helping young people obtain better jobs and earn more are critical tasks for this generation and for the welfare of the next generation.
Expanding apprenticeship can play a key role. Apprenticeships help young people gain mastery in an occupation as well as other workplace skills; they supply employers with workers who achieve strong technical and employability skills. Studies show U.S. apprenticeships are extraordinarily cost-effective. Analyses conducted for Washington State’s Workforce Board show that taxpayers net almost three times their spending on apprenticeships within two and a half years of the program’s completion, and the combined benefits accruing to participants and taxpayers are about five times the costs. By the time former apprentices reach age 65, benefits to taxpayers reach $23 for each dollar spent.
Apprenticeships train people by combining work-based learning with classroom instruction in a unified program that leads to a recognized and valued occupational credential. Young people, especially young men, who hate sitting through classes all day can spend part of their time making something, learning by doing, and seeing an immediate application of their course work. Trainees earn money and contribute to production while they learn. Apprentices graduate with a sense of pride and identity as a member of a community of practice. Mentoring is built into the apprenticeship process, with employers and trainers having a real stake in the young person’s success.
Expanding apprenticeship is feasible in the U.S., as the recent growth in South Carolina’s apprenticeship initiative is proving. The extraordinary expansion in Britain demonstrates how apprenticeships can succeed in relatively free labor markets. Achieving results in the U.S. will require increases in funding that are minuscule in comparison to college subsidies. Even tripling the federal and state funding for apprenticeships would amount to about 2% of the 2013 increase in funding for college loans. Failing to provide even minimal funding for apprenticeships means neglecting the young people who prefer work-based learning.
The key for a successful and widespread program is to attract large numbers of employers to create apprenticeships that meet occupational standards. Today, only about 20,000 U.S. employers offer apprenticeships compared to over 100,000 employers in Britain, with a population about one-fifth that of the U.S.
To bring the U.S. program to scale, I suggest several initiatives, including:
- national and state leadership and creating a brand (Apprenticeship America?) for apprenticeship,
- developing systems for matching potential apprentices and employers,
- making Pell grants and Trade Adjustment Assistance compatible with apprenticeship training,
- establishing a performance-based, federal-state matching fund to support a business-friendly staff to market and provide technical assistance directly to individual employers. The staff would show the benefits of apprenticeships to firms and assist in the creation of programs at the firm level.
- giving state-level incentives to high schools and community colleges to market apprenticeships and offer the related classroom instruction, and
- building websites to provide reliable information about how to start apprenticeships and where apprenticeship slots are available, and ideally to assist with the process of matching prospective apprentices with apprenticeship openings.
A robust apprenticeship system can generate skill and wage growth for large numbers of young people, especially those who do not obtain a bachelor’s degree. As apprenticeships enhance youth development and employability skills in such areas as communication, problem-solving, and teaching others, the skills required for healthy couple relationships will also improve. With added earnings and the maturation that deepens as people move from apprentice to master, young people will be well-equipped to contribute to the nation’s productivity and, more importantly, to build strong marriages and families.
Apprentice photo from Shutterstock.
Filed under: Economy |Tags: apprenticeships, evidence, families, policy, Urban Institute Add a Comment »
| Posted: August 7th, 2013
The Obama administration recently directed federal agencies to make government more accountable by “applying existing evidence about what works, generating new knowledge, and using experimentation and innovation to test new approaches to program delivery.” So how should this directive apply to the administration’s policies on investing in the earnings capacity of Americans?
Currently, the administration and the Congress are failing to use the best evidence to choose investments that are most cost-effective in increasing people’s skills and thereby strengthening the middle class. Unfortunately, they now spend a tiny amount on apprenticeship—an evidence-based approach that works—while showering massive funding on certain post-secondary education strategies of dubious effectiveness. If the administration truly wants to allocate dollars based on the strongest evidence, it should embark on a major expansion of the apprenticeship system.
Such an initiative would combine work-based and academic learning to sharply increase skills, employment and earnings, production, and access to valuable occupational credentials.
What’s the evidence for apprenticeships?
The international evidence for the cost-effectiveness of apprenticeships is compelling. Countries with robust apprenticeship systems achieve far lower youth unemployment rates than countries without these systems, as documented by the Organization for Economic Cooperation and Development. Its 2010 report “Off to a Good Start: Jobs for Youth (2010)” highlights the role of apprenticeships in smoothing the transition from school to work and in achieving low youth unemployment. Earnings gains from apprenticeships yield high rates of return, often in the range of 15 percent or more.
Along with these monetary benefits comes a sense of pride in mastering an occupation. These are not the only social benefits. Employers gain as well; they recoup most or all of their training costs during the apprenticeship period. The rest is gravy, coming in the form of reduced hiring costs and increased innovation.
Apprenticeships in the United States are highly cost-effective
While apprenticeships in the United States are far less common than in other advanced economies, studies show U.S. apprenticeships are extraordinarily cost-effective. According to analyses conducted for Washington State’s Workforce Board, the government nets almost three times its spending on apprenticeships within two and a half years of the program’s completion. In this short period, benefits to participants and taxpayers are about five times the costs. By the time former apprentices age reach age 65, projections suggest public benefits of $23 for each $1 spent. These gains to apprenticeship far outweigh the net benefits to community college career programs.
Another study of returns to apprenticeship in 10 states documents large earnings gains for participants. Six years after starting a program, average apprenticeship participants earn 1.4 times as much as their peers with similar work histories but who were not apprentices. The estimated apprenticeship returns were nearly $28 in social benefits for every dollar of government and worker costs.
Can U.S. employers be persuaded to expand apprenticeships?
The evidence shows that apprenticeships are cost-effective, but can they actually be expanded? Again, the evidence shows a well-executed marketing effort can help make it happen. For example, in South Carolina, small incentive payments and a low-cost marketing initiative reaching out to individual employers generated a five-fold increase in apprenticeships, even during the latest downturn when employment was plummeting.
Reallocate funds from less effective school-based strategies
The funding required for an expansion of apprenticeship would be modest compared with past and future increases in higher education spending. Pell grants for low-income students to attend college—over half of which go for two-year public and private colleges—tripled in 2011 dollars from $12.7 billion to $37.0 billion in the past 10 years.
Federal spending on loans for higher education is skyrocketing as well; the recently passed reduction in interest rates on student college loans will probably add $5 billion per year to the costs of the program. Meanwhile, federal dollars for the apprenticeship system has declined sharply in real terms and today amount to less than a measly $30 million.
The evidence offers no support for giving priority to added higher education outlays over spending for expanding apprenticeship. A college education yields generally high returns, but the evidence of college effectiveness is weak for the many marginal students who start and never finish two-year colleges. The government’s own What Works Clearinghouse cites a rigorous study showing that added scholarship funding for community college students did not increase enrollment credits or academic achievement, let alone have labor market impacts. For the United States as a whole, college completion rates are dismal, especially for two-year public institutions. Only one in five students entering full-time two-year programs completed them within 150 percent of the expected time.
If the Obama Administration follows its own directive and uses evidence to determine investments in human capital, we should see a shift toward major investments in apprenticeship in the coming years. Let’s hope the message gets through the many layers of government.
Apprentice photo from Shutterstock
Filed under: Economy |Tags: apprenticeships, congress, evidence, Obama, policy, Urban Institute 1 Comment »
| Posted: March 8th, 2013
Point-Counterpoint: The Minimum Wage (part 2) Read Austin Nichols's minimum wage counterpoint.
Photo by Flickr user anthonyzh82, used under a Creative Commons License (cc-by-sa 2.0)
Focusing on the minimum wage ignores the critical distinction between what workers earn for their economic contributions and what families require for basic living standards. Common terms that inappropriately mix the two concepts include “a living wage” or a “family sustaining wage.” Even for a family with a single earner, no social benefits, and no other income (such as child support payments), their living standard will depend not only on the worker’s hourly wage but also on the number of hours worked. For all other situations, the wage rate and living standards are clearly very different concepts.
Clearly, a middle-income family’s ability to buy necessities does not depend on whether their teenage son or daughter earns $7.25 or $8.50 per hour. But what about families with only one low-wage earner? In this case, the earner’s ability to work steadily at a full-time job is more important than the wage rate. Why? Because of the income-related cash and in-kind benefits that go together with work and earned income.
Let’s take the example of a full-time, full-year worker earning the minimum wage ($7.25) and supporting two children. At $7.25 an hour for 2,000 hours, the worker would earn $14,500 per year, far below the 2013 poverty line of $19,530 for a family of three. However, after including what the family qualifies for in tax and food stamp benefits and deducting payroll taxes, the family’s spendable resources jump from $14,500 to over $24,000. While this amount is far from comfortable, it does bring the family’s income 24 percent above the poverty line. It is a noteworthy public accomplishment to have a benefit system that encourages and rewards work enough to move even a minimum-wage worker’s family above the poverty line.
Now, of course, such a family would be even better off if the worker earned $9 per hour, even after losing one-third of the worker’s earnings gain to increased taxes and reduced benefits. But, what if that worker faced a greater risk of unemployment or had to curtail his or her hours because employers decided to hire fewer minimum-wage workers? Then the result is far from clear. Areas where wage rates in various occupations are especially low will be unlikely to absorb a 25 percent increase in the minimum wage without significant job losses or reductions in working time. In other areas, the group most likely to lose jobs is the least advantaged: African American youth. Because families need to earn about $13,500 to qualify for the maximum EITC and child tax credits, reductions in hours worked may limit the potential of low-wage workers to move above poverty. Although ongoing debates suggest that it’s unclear how many the minimum wage would put out of work, do we really want to risk losing jobs when only 40 percent of African American men age 18 to 24 hold jobs of any kind?
More broadly, raising the minimum wage diverts attention from policies that can raise earnings by increasing the productivity of workers. Instead of debating the best ways to achieve these gains, we are mired in a less productive debate over how much to mandate higher pay through an arbitrary government wage policy framed inaccurately as a family income solution.
Filed under: Economy Add a Comment »
| Posted: February 1st, 2013
Bad terminology can create bad policy. Nowhere is this more evident than in housing policy. The best example is the use of the term “low-income housing.” Though widely used, there is no such thing as low-income housing in the sense that a physical place is inextricably linked only to residents with low incomes. Of course, some housing is commonly rented or bought by low-income families. But just because low-income families commonly purchase certain cars and buy meals at certain restaurants, we do not call those things “low-income cars” or “low-income restaurants.” Rather, it is the low price of housing, cars, and other goods that attracts low-income families.
So what, you might ask? Low price, low income, what’s the difference? Importantly, this semantic error affects the thinking and actions of policy advocates and government officials. Instead of providing low-income families with more purchasing power to obtain housing, too often policymakers attempt to subsidize and wall off certain houses and apartments for the poor and near poor. Public housing is one example. The government provides subsidies for building and maintaining specific places limited to people with low incomes. Other programs also subsidize particular homes and apartments and restrict them for use only by low-income or lower-middle-income households.
This approach is problematic. First, subsidies tied to specific “low-income” homes substantially restrict where recipients can live, and what’s available may be a poor choice for their families. Second, the cost of subsidizing construction programs is higher than the cost of boosting people’s purchasing power to rent or buy their own dwellings, even assuming the construction units last at least 30 years. For both reasons, the government’s cost is often far higher than the recipient’s benefit.
Even the much-vaunted low-income housing tax credit, endorsed strongly by the New York Times editorial board, is costly and does little to expand housing supply. The tax credit aims to encourage developers to invest in affordable housing. They sell the credits to investors, lowering the amount they need to borrow to build or fix up property. But developers generally sell their tax credits at a discount, leaving them with only about 70-75 percent of the government subsidy. To advocates of these programs, the subsidies add to the stock of “affordable” housing. But, as research has shown, the added housing financed by government is largely or completely offset by less private-financed housing.
Further, the families benefiting from the low-income housing tax credit often have incomes well above the poverty line, while many families with far lower incomes receive no subsidy. It is not even clear that significant rent savings accrue because the rents charged for reserved “low-income” housing are often well in the range of market rents.
In unusual situations, stimulating production of low-cost housing may be worthwhile because it benefits the neighborhood or gets around regulations that restrict low-priced units. But pushing for more subsidized “low-income housing” on grounds of too few affordable places can be inefficient, particularly when home prices have fallen dramatically and large numbers of existing homes are vacant. Instead, raising the purchasing power of low-income families offers a better deal for them and for the government than encouraging new construction through tax credits.
The issue is hardly academic—today, 30 percent or fewer households eligible for housing subsidies actually receive one. So any savings can be critical in extending benefits to more low-income families.
By shifting from construction incentives to rent vouchers, the government can save 20 percent or more on its current housing outlays, meaning it could offer vouchers to many more low-income families at the same costs. Moreover, as shown elsewhere, if the new vouchers emphasized homeownership instead of renting, the government’s costs would be even lower—which could mean even more available vouchers and more families covered by subsidized housing. That’s quite a benefit from thinking more clearly about the housing of low-income families!
Filed under: Built Environment 2 Comments »
| Posted: December 6th, 2012
Debates about income inequality and the shrinking middle class have largely focused on globalization, the declining share of middle-wage jobs, the eroding role of unions, technological change that benefits more educated workers, tax policies, and the share of income going to the top 1 percent. Often ignored is the question of whether we’re really measuring inequality accurately. Do standard measures of money income really capture inequalities in living standards? Not really. Because of differences in living costs across communities, higher incomes don’t necessarily translate into higher living standards. Housing costs reduce purchasing power in some communities more than in others. At the same time, income gaps can become more pronounced when low-wage workers are discouraged from moving to areas with high housing costs. Where people live, it turns out, matters a lot in measuring and accounting for the inequality of living standards.
Analysts of poverty trends have long recognized that cash income does not tell the whole story, since it ignores the importance of noncash public benefits, such as food stamps, housing assistance, and health coverage. Indeed, the Census Bureau is now taking into account noncash benefits and differences in housing costs when measuring poverty. Recently, researchers have begun analyzing geographic differences to explain trends in income inequality.
Several mechanisms are potentially at work, as Enrico Moretti of the University of California, Berkeley points out. Living costs may increase faster in areas where high-income, highly educated people are concentrated. The rise in living costs may come from more rapid growth in housing prices and in the prices of other goods and services linked to rising land values. High-income people may have moved to metropolitan areas where housing costs are especially high. By contrast, low-wage, less-educated workers have been less likely to move to areas where they would earn higher wages but not higher living standards. Moretti finds all of these factors at work, showing that the rising inequality in money income didn’t completely translate into rising inequality in purchasing power. According to Moretti, more than 20 percent of the rising money advantage of college graduates over high school graduates between 1980 and 2000 did not represent an advantage in living standards.
Locational differences can make income inequality appear worse than the actual inequality of living standards. Economists have long viewed local zoning requirements as harmful to low-income families by limiting their access to attractive suburban neighborhoods. By requiring large lot sizes, towns have priced low-income families out of their housing markets. Now, as highlighted by the New York Times Economix blog, Peter Ganong and Daniel Shoag of Harvard University have demonstrated that differential housing regulations are a major culprit in slowing the convergence of regional income gaps, thereby lessening the migration into high cash income, high cost areas communities and adding to the inequality in money incomes. High-wage areas used to attract all types of workers. As the supply of workers, including low-skill workers, went up in high-wage metro areas and fell in low-wage metros, wage differences between metro areas declined. In recent years, because high housing costs have increasingly offset higher wages, fewer workers have chosen to migrate within the United States. Thus, low-income families lose in two ways from restrictive regulations—those in highly regulated areas face higher prices because of limitations on supplies and those in other locations lose access to better paying jobs because they cannot afford the high-priced housing. Housing subsidies can shield some low-income families from increased housing costs in high-priced areas, but most low- and middle-income families receive no housing benefits at all.
To see how money income fails to capture purchasing power differences, compare the ability of low- and middle-skill workers and of median-income families to buy homes in four high-priced and four low-priced metropolitan areas. To simplify, let’s look only at the burden of a 30-year mortgage at a 4 percent interest rate. As the table shows, workers at moderate education levels face enormous mortgage burdens trying to buy homes in the four high-priced metro areas. But, homes in low-priced areas are quite affordable even among workers without a college degree. The gaps in affordability are far less in the case of family income. Still, a median-income family would have to spend more than double their share of income on the median-priced home in the Los Angeles or San Francisco metro areas than in the four low-priced metro areas. As a result, family income inequality across cities looks far higher when we don’t account for differences in housing costs. Median family incomes are 40 percent higher in San Francisco than in Oklahoma City, but the gap in income after mortgage payments falls to 9 percent. Since other living costs are higher in San Francisco, the differences in purchasing power are even smaller. The figures illustrate how inequality in purchasing power is often lower than inequality in money incomes.
Filed under: Built Environment, Other 3 Comments »
||Median Wage High School Graduate Buys at the 25th Percentile of Home Values
||Median Wage Worker with Some College Buys Median Priced Home
||Median Income Family Buys Median Priced Home
||Value of Median Priced Home
|Percent of Income Needed to Buy Home
|Los Angeles, CA
|San Francisco, CA
|Kansas City, MO
|Oklahoma City, OK
|South Bend, Indiana
| Posted: December 7th, 2011
Journalists and commentators parsing the U.S. Census Bureau’s new Supplemental Poverty Measure (SPM) when it debuted about a month ago missed one surprising result of what happens when the new measure is applied. As most news stories correctly pointed out, the SPM counts as income certain public benefits that the official measure didn’t. Chief among them are the Earned Income Tax Credit (EITC), food stamps (now Supplemental Nutrition Assistance Program-SNAP), and low-income housing assistance. Under the official measure, the roughly $170 billion spent on these programs was totally under the radar, even though these three benefits amount to about $3,700 per low-income person. (That’s over $15,000 annually for a family of four). Under the SPM, these and some other benefits are counted as income, though not fully because people report less in benefits than the government has paid out.
Several headlines highlighted the higher estimated poverty rate yielded by the SPM than by the official measure. The Washington Post’s Michael Fletcher, for instance, claims that the new Census measure “…painted a more dismal picture of the nation’s economic landscape than the official measure from September.”
So how can poverty go up if the new measure raises collective incomes by over $170 billion? As some journalists and experts noted, children fared better when public benefits are counted. But why should extra spending on kids result in higher poverty among the elderly and other groups?
Let me oversimplify a bit to explain. The official measure was set up as an absolute measure—the income needed to achieve a specific unchanging living standard. The threshold set was three times the cost of an economy food budget. Over time, that threshold has risen only to keep pace with inflation, not with rising living standards. In contrast, the SPM threshold is a relative concept. It equals what a family with two children at the 33rd percentile of spending devote to food, clothing, housing, and utilities plus another 20% of this amount. This threshold is then adjusted for family size and local housing costs.
The percentile used to calculate the SPM threshold is somewhat arbitrary. Choose a relatively high percentile (say 50%) and you get a high poverty threshold and higher level of measured poverty. Choose a lower one (say, 25%) and both drop. By selecting 32-34%, the Census Bureau raised the income threshold so now it’s about 10% higher than under the official measure. That statistical move doesn’t mean that the poor’s living standards have dropped, so the SPM doesn’t really “…paint a more dismal picture ” so much as it creates a new benchmark based on a higher standard of living.
A second conceptual shift is that the SPM deducts from income what the Census Bureau terms “necessary expenses.” These include taxes, work expenses, and the amount of child support individuals pay, all of which lower net income. Also deducted are spending on child care and out-of-pocket health expenses. Child care is usually a work expense, but people still have discretion over what quality they buy. Health spending is clearly consumption and differs from income or expenses necessary to generate income. Health services are valuable—sensible uses of income—and more spending presumably raises an individual’s living standards.
Like the official measure, the SPM doesn’t count government-paid health services, even though they can greatly enhance living standards and life itself. So, yes, older Americans spend more out-of-pocket on healthcare, which pushes up their poverty rate. But, the presumed improvements in living standards financed by significant Medicare and Medicaid benefits go uncounted. This approach raises the same concern that led to the SPM—the distorted picture you get when you don’t count government benefits aimed at alleviating hardship.
Certainly, health spending poses a quandary for counting poverty. For an individual, paying more health expenses may reflect poorer health. When unhealthy people must spend more of their own money to achieve the same health status as healthier individuals, they have fewer dollars to spend on everything else and thus have (non-health) living standards as low as individuals who have income levels below the poverty line. On the other hand, when rising Medicaid and Medicare spending makes a population better off over time, they are surely enhancing living standards and should be counted. Moreover, if the improvements from added health spending are not worth the costs, then policymakers should shift spending toward cash or other supports that would benefit recipients more.
Filed under: Assets and debts, Government, Health Care, Urban Culture 1 Comment »
| Posted: December 6th, 2011
Mississippi and other parts of the deep South have long held the unwanted distinction of home to America’s deepest poverty. Footage and newspaper photos of New Orleans during Hurricane Katrina captured Southern state deprivation for all to see. Even after decades of progress, Mississippi’s income per capita is still the country’s lowest—fully 23% below the national average. But now the Census Bureau’s new improved Supplemental Poverty Measure (SPM) shows that the poverty rate is lower in Mississippi than in much richer New York and California.
More specifically, under the official poverty rate, 23.2% of Mississippi’s population was poor in 2009, when 15.9% of New Yorkers and 15.5% of Californians were. But, by the new SPM, the poverty rate falls to 17% in Mississippi and jumps to 17.6% in New York and to 22.4% in California. And keep in mind here that New York’s income per capita is more than 1.5 times Mississippi’s.
So, what’s going on? Is there really less deprivation in Mississippi than in New York or California? This and similar reversals of fortune in other states reflect differences in housing costs. Since spending on housing can eat up as much as half of all household income for those at the poverty threshold, geographic adjustments for housing costs—in the Census Bureau’s calculations, rent for a two-bedroom apartment—can dramatically change both that threshold and poverty rates.
A problem with this approach is that housing quality isn’t taken into account. A two-bedroom apartment in New York or California might be a lot sturdier and more attractive than one in Mississippi. And it might be located in dicier or more isolated neighborhoods with fewer amenities. Sure, housing costs less (and thus drives poverty rates down under the new measure) in rural than in metropolitan areas. That means that some rent differences can reflect differences in living standards, not simply price variations.
To put the SPM measure on the stand for a minute, let’s look at how the official and SPM measures relate to material hardship. Census Bureau economist Trudi Renwick reports that the official measure is more highly correlated with food insecurity, health, and education while the SPM measure is more reflective of such shelter issues as rent burdens, crowding, homelessness, and foreclosures.
To further complicate this comparison, housing costs and poverty rates can vary within states too. In fact, housing prices vary at least as much within as between states. The SPM factors these within- state housing cost adjustments into poverty rates, but, for example, low rents in outer-ring suburbs can be offset by less access to cultural opportunities and high transport costs or unmanageably long commutes. Again, in housing you probably don’t get what you don’t pay for.
The SPM’s geographic adjustments for poverty may illustrate a variant of H. L. Mencken’s dictum that “for every complex problem there is [a metric] that is clear, simple, and wrong.” At any rate, trying to summarize poverty in one number is at best awkward and, however resistant to sound bites and quick takes, multidimensional indicators probably serve us better.
Filed under: Built Environment 4 Comments »
| Posted: November 23rd, 2011
The nation faces an economic paradox. On one hand, a weak housing market is still perpetuating the nation’s economic woes, with millions of families owing more on their mortgage than their home is worth. By some forecasts, the impending foreclosures will keep home prices low for several years, worsen personal and bank balance sheets, and slow economic recovery. On the other hand, homes are increasingly affordable even without sizable income gains. Today, a family earning the median income can buy a medium-value home and spend only 16% of its income on mortgage payments (assuming a 5% down payment and a 4.5% interest rate).
Yet, avoiding foreclosures roundly trumps affordability in policy proposals. The Obama Administration is pushing Fannie Mae and Freddie Mac to allow underwater homeowners who have kept their mortgages current to refinance their debt at today’s low interest rates. Alternatively, opinion pieces in the Nation and the Weekly Standard propose to require banks and others mortgage-holders to cut homeowners’ mortgage debt to levels closer to their homes’ market value. The New York Times’ Joe Nocera recently touted this approach, noting that we’ll have an estimated 6 million unneeded homes within six years. Economist Martin Feldstein concurs, calling for spending up to $350 billion on “principal reduction” in return for homeowners waiving their right to walk away from their loans.
Moves like these can increase current homeowners’ net worth or disposable income, but their impacts on the housing market are uncertain. Lowering interest rates eases monthly housing costs and can boost aggregate housing demand without government subsidies. But, while government-backed principal reduction will alter the balance sheets of households and lenders, they won’t necessarily increase housing demand or reduce housing supply. If a family with a $200,000 mortgage on a house now worth $140,000 can’t or won’t pay its mortgage and then gets evicted or leaves voluntarily, housing supply and demand don’t change, even though the number of units readily available for purchase rises and one more family most likely enters the rental market. Marking down this hypothetical mortgage debt to $150,000 wouldn’t necessarily change supply or demand either: the family might still move and become a renter or might stay put, leaving vacancy levels unchanged.
The mark-down policy, if financed by government subsidies, would be highly inequitable. Suppose the Wilson and Brown families each bought properties for $130,000 and each took out a $120,000 mortgage. When the value of the homes hit $230,000, the Wilsons took out a new mortgage for $200,000 to pay off the original mortgage, buy a new car, and pay private school tuition while the Browns continued paying their mortgage. When the home values fell to $140,000, the Browns still had positive equity in the home and no reason to abandon the property, while the Wilsons owed $60,000 more than their home was worth. Is it fair to the Browns of the world to provide a $60,000 subsidy to the Wilsons to keep them in their home? Beyond that, big subsidies to families with both high mortgage debt and high family incomes may not be fair either—a point few mark-down proposals address.
Paying down the negative equity of homeowners would also mainly help four states. About 63 percent of the dollars would flow to homeowners in Arizona, California, Florida, and Nevada, where foreclosures are highest. Yet, these four foreclosure-wracked states account for only 21 percent of the nation’s personal income.
So if government-backed principal reduction raises thorny equity issues without necessarily reducing the supply-demand imbalance, what’s a wiser alternative? My recommendation is to increase demand by helping low-income and young people currently renting or living doubled-up. In our stagnant economy, fewer households are being formed, so demand languishes. With better information on their housing options, greater access to mortgages, and home ownership vouchers, many Americans could buy dwellings with very affordable monthly costs and help stabilize housing markets equitably. Watch for more detail on these alternatives in my next post.
Filed under: Built Environment 1 Comment »
| Posted: October 4th, 2011
The latest word on President Obama’s $448 billion proposal to create up to 2.1 million jobs is that it won’t pass Congress in one piece. One reason may be the high price tag per job. To reduce unemployment, we need a comprehensive attack that’s cost-effective, well-targeted, well-implemented, and well-administered -- and that works both sooner and later.
Here’s a five-part strategy that fits that bill. My proposal would create 4 million new jobs for less than $60 billion net, and it’s far more affordable and effective than President Obama’s.
1. Expand energy development that improves the environment. Speeding up permits for extraction and distribution would allow the U.S. to substitute natural gas for dirtier coal and oil, create hundreds of thousands of high-wage and high-value jobs, reduce foreign oil imports, and lower oil prices and world demand for oil. Converting truck and car fleets from gasoline to natural gas looks increasingly cost-effective and can cut smog and other emissions too.
2. Increase demand for owner-occupied housing. One way to jumpstart housing construction is to create 1 million homeownership vouchers patterned after the rent voucher system, while phasing out the Low-Income Housing Tax Credit, an inefficient subsidy that simply expands supply. Another zero-cost housing-related proposal is to make today’s low mortgage rates available to homeowners whose mortgages are current but who can’t get refinancing because their home value or their income has declined.
3. Provide a generous tax credit for expanding employment. The federal government gives employers a 15% subsidy for increases in the employer’s wage bill (the part subject to social security taxes) above the prior year’s level in the first year and 10% in the second year.
4. Expand apprenticeship training. Apprenticeship combines serious, work-based learning with classroom instruction so novices master core occupational skills and earn valued credentials documenting that mastery. Government could offer a $6,000 subsidy per apprentice for increases in registered apprenticeship beyond 80% of last year’s level and beef up the Labor Department Office of Apprenticeship’s marketing and technical assistance programs.
5. Fund direct job creation. Years ago, Canada managed to create relatively low-wage jobs by requiring nonprofit sponsors to compete for funding—specifying the “public goods” they promise to produce, whether bike paths, repairs and weatherization for low-income housing, recreational centers, child care, or home care assistance for the elderly and disabled.
Together, these five actions would likely stimulate enough jobs to pull the unemployment rate from 9.1% to 5.5%.
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