In July 2013, the World Bank decided to phase-out lending for new coal-fired power plants in middle-income countries, except in rare circumstances where no financially feasible alternatives to coal exist. This decision was made for a combination of reasons including concerns about local air pollution and global climate change, as well as evidence that these projects have little trouble attracting private capital without World Bank involvement. Now, policymakers are considering whether the World Bank’s policy should also cover projects designed to retrofit existing coal-fired power plants in middle-income countries by adding scrubbers and other technologies that increase efficiency and reduce air pollution. 

There are several fundamental questions underlying this debate: Is financing coal power plant retrofits a good use of World Bank resources? If so, should the World Bank insist on the use of best available technologies when it finances these retrofits? These questions are vitally important, as retrofit technologies are designed to minimize toxic air pollutants, including soot and smog, which are both dangerous for human health and the world’s climate. Older coal plants without retrofit technologies are less efficient, and emit more pollutants per unit of coal burned than those with retrofits applied. Evidence shows that soot and smog can cause respiratory illness and asthma, especially in children and elderly people, and can diminish local agricultural production by reducing sunlight. Furthermore, in many countries coal plants are the single largest source of carbon dioxide emissions driving climate change. 

To help inform the policy debate, this analysis surveys the technologies in use in more than 2,000 coal-fired power plants currently in operation, under construction, or planned in middle-income countries. The findings reveal that roughly 70 percent of these power plants rely on old, inefficient technologies. Retrofitting these plants would reduce pollution, increase efficiency and save lives. In middle-income countries that do not mandate coal retrofits, the World Bank could play a helpful role in financing those improvements, particularly as part of broader policy reforms designed to reduce climate pollution and increase efficiency across the power sector.

Importantly, however, the data also show that important qualifications should be made. First, because coal is a major source of greenhouse gas emissions and retrofits are likely to keep coal plants operating longer, the World Bank should insist that retrofit projects occur within a context of national and local policy reforms designed to abate greenhouse gas pollution. Toward this end, the World Bank should continue to help countries build capacity to adopt and enforce climate pollution controls and other offsetting actions and policies. Second, the World Bank should insist that projects it finances use best available pollution control technologies. Already, the substantial majority of coal retrofits completed to date in middle-income countries have used best available technologies. These retrofits were almost universally financed exclusively by private capital. The World Bank should not use its capital to support inferior retrofit technologies that are below the standards already adopted by the private sector in middle-income countries.

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This presentation by Alan Berube to the Cleveland EITC Forum explains how boosting low-income families' participation in tax credits can help put the city's workers, neighborhoods, and the local economy itself on more solid financial ground.

The metro program hosts and participates in a variety of public forums. To view a complete list of these events, please visit the metro program's Speeches and Events page which provides copies of major speeches, powerpoint presentations, event transcripts, and event summaries.

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Low-Income Boys in Higher Inequality Areas Drop Out of School More Often than Low-Income Boys in Lower Inequality Areas, Limiting Social Mobility, New Brookings Paper Finds
“Economic despair” may contribute if those at the bottom do not believe they have the ability to achieve middle class status

Greater income gaps between those at the bottom and middle of the income distribution lead low-income boys to drop out of high school more often than their counterparts in lower inequality areas, suggesting that there is an important link between income inequality and reduced rates of upward mobility, according to a new paper presented today at the Brookings Panel on Activity. The finding has implications for social policy, implying a need for interventions that focus on bolstering low-income adolescents' perceptions of what they could achieve in life.

In “Income Inequality, Social Mobility, and the Decision to Drop Out Of High School,” Brookings Nonresident Senior Fellow and University of Maryland economics professor Melissa S. Kearney and Wellesley economics professor Phillip B. Levine propose a channel through which income inequality might lead to less upward mobility—often assumed to be the case but not yet fully proven. The conventional thinking among economists is that income inequality provides incentives for individuals to invest more in order to achieve the higher income position in society, but Kearney and Levine observe that if low-income youth view middle-class life as out of reach, they might decide to invest less in their own economic future.

See an interactive map of inequality by state, plus more findings »

The authors focus on income inequality in the lower half of the income distribution, as measured by income gaps between the 10th and 50th percentiles of the income distribution rather than income gaps between the the top and bottom of the income distribution, which has been more of a focus in popular culture. They show this "lower-tail" inequality is more relevant to the lives of poor youth because the middle is a more realistic ambition. Furthermore, their research could reconcile a puzzle: social mobility does not appear to be falling, despite the rise in income inequality. But, as Kearney and Levine point out, U.S. income inequality has been rising because the top of the distribution has been pulling away from the middle, not because the bottom is falling farther behind the middle.

The authors look specifically at high school drop-out rates through a geographic lens, noting the link between highly variable rates of high school completion and income inequality across the country. One-quarter or more of those who start high school in the higher inequality states of Louisiana, Mississippi, Georgia, and the District Columbia fail to graduate in a four-year period, as compared to only around 10 percent in Vermont, Wisconsin, North Dakota, and Nebraska—lower inequality states. Their econometric analysis goes on to show that low-income youth—boys in particular—are 4.1 percentage points more likely to drop out of high school by age 20 if they live in a high-inequality location relative to those who live in a low-inequality location.

Kearney and Levine examine a number of potential explanations for this link, including differences in educational inputs, poverty rates, demographic composition, and other factors. Ultimately, the evidence suggests that there is something specific about areas with greater income gaps that lead low-income boys there to drop out of school at higher rates than low-income boys elsewhere. The authors' research suggests that adolescents make educational decisions based on their perceived returns to investing in their educational development: a greater distance to climb to get to the middle of the income distribution could lead to a sense that economic success is unlikely—what they term “economic despair.”

"Income inequality can negatively affect the perceived returns to investment in education from the perspective of an economically disadvantaged adolescent,” they write. “Perceptions beget perceptions."

Digging into reasons students themselves give for dropping out, they find that low-income students from more unequal places are more likely to give up on their educational pursuits. Surprisingly, survey evidence shows that academic performance does not have as large an impact on low-income students in high inequality states: 51 percent of dropouts in the least unequal states reported that they dropped out because they were performing poorly, as compared to only 21 percent of students who dropped out in the most unequal states.

The finding suggests that economic despair could play an important role: if a student perceives a lower benefit to remaining in school, then he or she will choose to drop out at a lower threshold of academic difficulty. They also note that while the wage premium of completing high school should reduce the dropout rate, household income inequality has an offsetting negative effect.

The choice between staying in school and dropping out may reflect actual or perceived differences from the benefits of graduating. For instance, the authors note their past research showing that youth from low-income households who grow up in high lower-tail inequality states face lifetime incomes that are over 30 percent lower than similar children in lower inequality states. They also highlight other research showing that the overwhelming majority of 9th graders aspire to go to college, but by 11th grade, low-SES students are substantially less likely to expect they will enroll in college, even among those students with high test scores.

"There are important policy implications for what types of programs are needed to improve the economic trajectory of children from low-SES backgrounds," they write. "Successful interventions would focus on giving low income youth reasons to believe they have the opportunity to succeed. Such interventions could focus on expanded opportunities that would improve the actual return to staying in school, but they could also focus on improving perceptions by giving low-income students a reason to believe they can be the "college-going type." For example, interventions might take the form of mentoring programs that connect youth with successful adult mentors and school and community programs that focus on establishing high expectations and providing pathways to graduation. They could also take the form of early-childhood parenting programs that work with parents to create more nurturing home environments to build self-esteem and engender positive behaviors."

Read the full paper from Kearney and Levine here »

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• How “economic despair” affects high school graduation rates for America’s poorest students

The Earned Income Tax Credit (EITC) provides a refundable tax credit to lower-income working families. In 2011, the EITC reached 27.9 million tax filers at a total cost of $62.9 billion. Almost 20 percent of tax filers receive the EITC, and the average credit amount is $2,254 (IRS 2013). After expansions to the EITC in the late 1980s through the late 1990s—under Democrat and Republican administrations—the EITC now occupies a central place in the U.S. safety net. Based on the Census Bureau’s 2012 Supplemental Poverty Measure (SPM), the EITC keeps 6.5 million people, including 3.3 million children, out of poverty (Center on Budget and Policy Priorities [CBPP] 2014a). No other tax or transfer program prevents more children from living a life of poverty, and only Social Security keeps more people above poverty.

Since the EITC is only eligible to tax filers who work, the credit’s impact on poverty takes place through encouraging employment by ensuring greater pay after taxes. The empirical research shows that the tax credit translates into sizable and robust increases in employment (Eissa and Liebman 1996; Meyer and Rosenbaum 2000, 2001). Thus, the credit reduces poverty through two channels: the actual credit, and increases in family earnings. This dual feature gives the EITC a unique place in the U.S. safety net; in contrast, many other programs redistribute income while, at least to some degree, discouraging work. Importantly, transferring income while encouraging work makes the EITC an efficient and cost-effective policy for increasing the after-tax income of low-earning Americans. Yet a program of this size and impact could be more equitable in its reach. Under the current design of the EITC, childless earners and families with only one child, for instance, receive disproportionately lower refunds. 

In 2014, families with two children (three or more children) are eligible for a maximum credit of $5,460 ($6,143) compared to $3,305 for families with one child. Married couples, despite their larger family sizes, receive only modestly more-generous EITC benefits compared to single filers. Childless earners benefit little from the EITC, and have a maximum credit of only $496—less than 10 percent of the two-child credit. 

Prominent proposals seek to mitigate these inequalities. President Obama’s fiscal year 2015 budget includes an expansion of the childless EITC, a concept outlined by John Karl Scholz in 2007 in a proposal for The Hamilton Project. Notably, MDRC is currently evaluating Paycheck Plus, a pilot program for an expanded EITC for workers without dependent children, for the New York City Center for Economic Opportunity (MDRC 2014). The recent Hamilton Project proposal for a secondary-earner tax credit addresses the so-called EITC penalty for married couples (Kearney and Turner 2013). And the more generous EITC credit for three or more children was recently enacted as part of the American Recovery and Reinvestment Act of 2009, and is currently scheduled to sunset in 2017. 

Considering this broad set of EITC reforms, and recognizing the demonstrated effectiveness of the program as an antipoverty program with numerous benefits, this policy memo proposes an expansion for the largest group of  EITC recipients: families with one child. In particular, I propose to expand the one-child schedule to be on par with the two-child schedule, in equivalence scale-adjusted terms. An equivalence scale captures the cost of living for a household of a given size (and demographic composition) relative to the cost of living for a reference household of a single adult, and is a standard component in defining poverty thresholds. The proposal expands the maximum credit for one-child families to $4,641, from $3,305 under current law, an increase of about 40 percent. The expansion will lead to a roughly $1,000 increase in after-tax income for taxpayers in the bottom 40 percent of the income distribution receiving the higher credit. As this paper outlines, the expansion is justified on equity and efficiency grounds. This expansion is anchored in the equity principle in that the generosity of the credit should be proportional to the needs of families of differing sizes; I use the equivalence scale implicit in the poverty thresholds of the Census SPM as a guide for household needs. This proposal is also supported by efficiency principles given the EITC’s demonstrated success at raising labor supply among single mothers. 

The target population for the proposal is low-income working families with children. Implementing this proposal requires legislative action by the federal government; it is important to note that altering the EITC schedule requires a simple amendment to the tax code, and not a massive overhaul of our nation’s tax system. The revenue cost of the proposal derives from additional federal costs of the EITC, less the additional payroll and ordinary federal income taxes. The private benefits include increases in after-tax income and reductions in poverty. The proposal would also generate social benefits through the spillover effects that the increase in income plays in improving health and children’s cognitive skills (Dahl and Lochner 2012; Evans and Garthwaite 2014; Hoynes, Miller, and Simon forthcoming).

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In his state of the union and his budget, the President spoke of the stagnation of middle class incomes. Whatever growth we have had has not been broadly shared.  More than 78% of the growth in GDP between 1979 and 2013 has gone to the top one percent. Even Republicans are beginning to worry about this issue although they have yet to develop concrete proposals to address it.

Slow Growth in Incomes

Middle class incomes were growing slowly before the recession and have actually declined over the past decade.   In addition, according to the New York Times, the proportion of the population with incomes between $35,000 and $100,000 in inflation-adjusted terms fell from 53% in 1967 to 43% in 2013.  During the first four decades this was primarily because more people were moving into higher income groups, but more recently it was because they have moved down the ladder, not up.  One can define the middle class in many different ways or torture the data in various ways, but there is plenty of evidence that we have a problem.

What to Do

The most promising approach is what I call “the second earner solution.”  For many decades now, the labor force participation rate of prime age men has been falling while that of women has been rising.  The entry of so many women into the labor force was the major force propelling whatever growth in middle class incomes occurred up until about 2000. That growth in women’s work has now levelled off.  Getting it back on an upward track would do more than any policy I can think of to help the middle class.

Imagine a household with one earner making the average wage of today’s worker and spending full-time in the job market.  That household will have an income of around $34,000. But if he (or she) has a spouse making a similar amount, the household’s income will double to $68,000. That is why the President’s focus on a second-earner credit of $500, a tripling of the child care tax credit, expanding the Earned Income Tax Credit, and providing paid leave are so important. These policies are all pro-work and research shows they would increase employment.

No Marriage = No Second Earner

One problem, of course, is that fewer and fewer households contain two potential workers.  So it would also help to bring back marriage or at least its first cousin, a stable cohabiting relationship.  My ideas on this front are spelled out in my new book, Generation Unbound. In a nutshell, we need to empower women to not have children before they have found a committed partner with whom to raise children in a stable, two-parent family. Whatever the other benefits of two parents, they have twice as much time and potentially twice as much income.    

Other Needed Responses

Shouldn’t we also worry about the wages or the employment of men?  Of course.  But an increase in, say, the minimum wage or a better collective bargaining environment or more job training will have far smaller effects than “the second earner solution.”  In addition, the decline in male employment is related to still more difficult problems such as high rates of incarceration and the failure of men to take advantage of postsecondary education as much as women have. 

Still the two-earner solution should not be pursued in isolation. In the short-term, a stronger recovery from the recession is needed and in the longer-term, more effective investments in education, research, infrastructure, and in labor market institutions that produce more widely-shared growth, as argued by the Commission on Inclusive Prosperity. But do we really expect families to wait for these long-term policies to pay off?  It could be decades. 

In the meantime, the President’s proposals to make work more appealing to existing or potential second earners deserves more attention.  

April 15 is tax day, but not many Americans will be lining up at the post office or logging onto TurboTax as midnight approaches. Taxpayers who receive refunds often file well ahead of the April 15 deadline. And according to new research, many of those refund dollars are already spent or spoken for.

Early filing is particularly common among taxpayers who claim the Earned Income Tax Credit (EITC), which supplements earnings for low-income workers and their families. EITC recipients often receive substantial refunds, especially in relation to their income. According to new data available through our EITC Interactive, nationwide 26.8 million taxpayers benefited from the EITC for the 2013 tax year, and they claimed a total of $64.7 billion from the credit. Combined with other credits and over-withholding these families received, the average refund for EITC filers topped $4,100 that year. As the accompanying map shows, that amount approached $4,500 or more in many southern states.

I thought of those large refunds while reading a fascinating new book by sociologist Kathryn Edin and her colleagues, titled, It’s Not Like I’m Poor: How Working Families Make Ends Meet in a Post-Welfare World. The book provides insights from in-depth interviews with 115 families with children in the Boston area who claimed the EITC. It examines their household budgets and how the families view and use the credit. The authors find that these families rely greatly on their tax refunds to close the gap between the wages they earn and the daily costs of living in an expensive region like Greater Boston. For some, a large tax refund also enabled them to purchase something normally confined to middle-class families, such as a special birthday present for a child or dinner out at a restaurant.

One of the authors’ central findings, however, was that EITC recipients bear a considerable amount of debt—95 percent of the families studied had debt of some kind. The most common (66%) was credit card debt, with the typical family owing nearly $2,000. Considerable shares of families also had utility, car, or student loan debt.

Their indebtedness was not surprising given that wages covered on average only about two-thirds of monthly expenditures. The authors classified one-quarter of families’ refund spending as dedicated to debt/bills, but other ways families  spend the money—such as repairing a car or paying ahead on bills—point to the lack of financial cushion EITC recipients endure throughout the year.

For the families Edin and colleagues studied, the average tax refund represented a staggering three months of earnings. Despite that, the authors report that many families expressed that they preferred the "windfall" versus receipt of payments over several months, partly because the lump sum held out the prospect of helping them save. But one has to wonder if the EITC, now routinely referred to as the nation's most effective anti-poverty policy, best supports families' financial security in this form, as its recipients fall further behind each month.

We should experiment with new ways of delivering EITC recipients' tax refunds that preserve some of its windfall aspect while also periodically delivering portions of the credit throughout the year. A small periodic payment pilot is underway in Chicago, and early findings suggest that advance payments of taxpayers' anticipated EITC helped them meet basic needs, pay off debt, and reduce financial stress relative to similar families not receiving such payments. It’s time to try making the EITC more than an annual boom in a bust-filled financial cycle for low-income families. 

This originally appeared in “Insight,” a publication of Grantmakers for Children, Youth, and Families.

For many in the United States, American poverty conjures images of urban blight or remote Appalachian hardship that motivated the War on Poverty in the 1960s. But the geography of poverty in the U.S. has shifted well beyond its historical confines (Kneebone and Berube, 2013). During the first decade of the 2000s, the poor population living in suburbs of the nation’s largest metropolitan areas for the first time outstripped the poor population living in central cities, and poverty continues to grow faster today in the suburbs.¹ This trend has been even more pronounced for those living below twice the federal poverty line—equivalent to $48,500 for a family of four in 2015—which roughly mirrors the population eligible to receive the federal Earned Income Tax Credit (EITC).

Although it was not originally billed as an antipoverty program, in its 40 years, the EITC has become one of the nation’s most effective tools for lifting low-income workers and their families above the poverty line. In 2013 alone, Brookings estimates that the EITC lifted 6.2 million people, including 3.1 million children, out of poverty (Kneebone and Holmes, 2014). What follows is a discussion of the EITC’s growing importance to recipients in light of the new geography of poverty, its role in boosting local economies, and how expanding participation in the program and paying the credit differently could enhance its effectiveness as a local economic stabilizer.

The shifting geography of poverty challenges traditional approaches to combat poverty through investments in place.

When President Johnson declared a War on Poverty in 1964, poverty in the U.S. was primarily urban or rural. This was also the case in 1975 when the EITC was created: Nearly a million more low-income individuals at that time lived in rural areas or big cities than in the suburbs of major metropolitan areas.² Place-based antipoverty interventions dating to the War on Poverty were thus designed with these two geographies—especially cities—in mind. Brookings estimates that today, the federal government spends about $82 billion per year across more than 80 place-focused antipoverty programs, spread across 10 agencies (Kneebone and Berube, 2013). Many are not well-suited to suburban contexts, for several reasons.

First, suburban poverty is more geographically diffuse than urban poverty. Suburban communities tend to be less densely populated than cities and larger in size, and cover more total area. Whereas centralized services might be appropriate in an urban context because they are easily accessible to many in need, it is more difficult to achieve those economies of scale in the suburbs, where residents live farther apart and have limited access to transit. Many competitive federal grant programs allocate points based on population served and population density, implicitly favoring large central cities.

Second, suburban municipalities may lack the experience and administrative capacity needed to sustain services for low-income families and communities. Cities have dealt with poverty longer, and have had more time to develop strategies and structures to support their poor populations. Some of this capacity stemmed explicitly from Community Action Agencies, one of the original War on Poverty programs, which was intended to spur local innovation. Small suburban communities by and large did not have this same experience. Because of their relatively small size, suburban governments may not be able to achieve the administrative scale needed to deliver effective safety-net programs.

Third, many suburban communities lack the economic scale and fiscal structure needed to fund services for low-income residents. Because many small municipalities are limited in how they are permitted to raise revenues—typically through a combination of property and sales taxes—they are especially prone to financial instability caused by the very economic conditions that also generate greater need for services. As poverty suburbanizes, small suburban communities simultaneously face rising demand and falling tax revenues to support those services. Moreover, tax “competition” among many small suburbs within a metro area can further erode the fiscal capacity and political will for these jurisdictions to support people in need.

The new geography of poverty makes direct investments in low-income individuals and families—like the EITC—even more important.

The mismatch between existing place-based antipoverty strategies and the places where poverty is growing fastest heightens the importance of investing directly and effectively in low-income individuals and families through programs such as the EITC. Following its expansion in the mid-1990s, the EITC became the most significant cash transfer program available to low-income working families. The Internal Revenue Service (IRS, 2014) estimates that approximately 79 percent of EITC-eligible taxpayers nationally claim the credit each year—a remarkably strong participation rate among federal safety-net programs.

The high program participation rate and growth over time in EITC expenditures reflects both increases in the credit’s generosity and growing need. In 2000, according to our analysis of IRS Stakeholder Partnerships, Education and Communities (IRS-SPEC) data, total EITC expenditures topped $42 billion (in 2013 dollars). In 2013, they approached $65 billion, equivalent to approximately 80 percent of the amount spent by the federal government on place-based poverty interventions.³

Analysis of IRS-SPEC data further suggests that the EITC’s geographic incidence closely tracks the shifting geography of need. From 2000 to 2013, the number of suburban filers claiming the EITC rose by 62 percent, compared to 33 percent in cities. Changes in the distribution of EITC claims mirrored changes in the location of poor and near-poor populations, particularly growth in the suburbs.⁴ And because lower-income suburban communities (where at least 40 percent of residents are poor or near-poor) are becoming more diverse, too—60 percent of their residents are non-white or Hispanic—the EITC also effectively reduces growing race-based income gaps in suburbs.⁵

EITC dollars support local economies.

The EITC benefits not only low-income families, but also the wider communities in which they live. Although it is widely regarded today as one of the country’s most successful antipoverty programs, the EITC was originally designed to be a temporary economic stimulus measure, in the Tax Reduction Act of 1975 (Nichols and Rothstein, 2015). During the 2000s, more local and state governments made a concerted push to expand participation in the EITC among eligible filers, in part to inject more federal dollars into their local economies (Berube, 2006a).

There are several mechanisms through which the EITC could benefit local economies. California State University researchers categorize the local economic impact of EITC refunds as the sum of direct effects (EITC recipients spending their refunds), indirect effects (business spending in response to EITC recipient spending), and induced effects (changes in household income and spending patterns caused by direct and indirect effects). Together, these effects represent the local “multiplier” effect (Avalos and Alley, 2010). Their estimates for California counties suggest that, in many cases, the credit creates local economic impacts equivalent to at least twice the amount of EITC dollars received.

Direct economic effects result from EITC recipients spending a portion of their refund locally, supporting local businesses and jobs. Consumer surveys show that low-income families spend a relatively large share of their income on groceries and other necessities, which tend to be purchased locally. Analysis of those surveys links tax refund season to increased likelihood of consumer activity as well as larger purchases (Adams, Einav, and Levin, 2009). People spend more, and more frequently, during tax refund season.

The EITC also supports local communities in less obvious ways. The concept of “tax incidence” reflects that the party being taxed, or receiving a tax credit, may not bear its full costs (or reap its benefits) because others shift their behavior in response to the tax. Along these lines, Jesse Rothstein estimates that as much as 36 cents of every dollar of EITC received flows to employers, because by enabling workers to better make ends meet on low wages, the credit effectively lowers the cost of labor. Those lower labor costs may, in turn, allow local employers to hire more local workers (Nichols and Rothstein, 2015).

Finally, emerging evidence suggests that progressive tax expenditures like the EITC can enhance intergenerational income mobility for local children, possibly by counteracting credit constraints that many low-income families face (Chetty, Hendren, Kline, and Saez, 2015). In areas with larger state EITCs, low-income children are more likely to move up the income ladder over time.

The local impact of the EITC depends on how, and how many, eligible filers claim the credit.

The local impact of the EITC also depends on whether eligible workers and families file tax returns and claim the credit. As noted above, the IRS estimates that 79 percent of those eligible to receive the EITC nationally claim it. Given local variation in characteristics associated with uptake, there is likely also considerable local variation in EITC participation (Berube, 2005). Efforts to increase participation locally can thus increase the level of investment communities receive from the program.

Research has identified several factors associated with EITC participation rates among the eligible population. Eligible filers less likely to claim the credit include those who live in rural areas, are self-employed, do not have qualifying children, do not speak English well, are grandparents, or recently changed their filing status (IRS, 2015). One study suggests that communities with moderately sized immigrant populations may exhibit lower EITC participation rates, due perhaps to less robust social networks or more dispersed/heterogeneous populations that may limit awareness of the credit (Berube, 2006b).

Recent research also suggests that EITC participation is higher in areas with more tax preparers, who may promote greater local awareness of the credit (Chetty, Friedman, and Saez, 2012). While individuals who enlist the help of tax preparers are more likely to receive the EITC, they may face significant fees that blunt the credit’s overall impact (Berube, 2006a). Expanding access to volunteer tax preparation services or simple, free online filing could help preserve more of the credit’s value for low-income families and their communities.

To maximize the EITC’s role as a local economic stabilizer, we should consider periodic payment options.

 The EITC already functions as an important antipoverty tool for low-income workers and families, and a boon to local economic stability. Communities should nonetheless be interested in efforts to connect taxpayers to a portion of their EITC throughout the year, rather than only as a lump-sum refund at tax time.

Debt features significantly on the balance sheets of EITC recipients. Recent research finds that about 95 percent of EITC recipients have debt of some kind, and that large shares of refunds are dedicated to debt payments or deferred expenses (such as car repair). Recipients do not use the majority of EITC refunds to pay for monthly expenses, despite the fact that their wages typically cover only two-thirds of those expenses (Halpern-Meekin, Edin, Tach, and Sykes, 2015).

Paying a portion of filers’ anticipated EITC periodically (and directly, rather than through employers like the defunct Advance EITC program) in smaller amounts over the course of a year could help them cope with these spending constraints and avoid taking on debt (Holt, 2008). By enabling families to better keep up with spending on regular items most often purchased locally—rent, food, vehicle maintenance—periodic payments could also support local economies. And by improving families’ liquidity, such payments could reduce reliance on high-cost financial products such as payday loans.

The EITC continues to gain importance as place-based strategies lag behind poverty’s suburbanization, and communities seek ways to maximize public investment in the face of budget constraints at all levels. The program lifts millions of working individuals and families out of poverty each year regardless of their location, and in doing so also supports community financial stability. An expanded EITC—at the federal, state, or local level—with options for periodic payment and better alternatives to high-cost tax preparation could provide even stronger support to low-income families and the places where they live.

References

Adams, W., Einav, L., and Levin, J. (2009). Liquidity constraints and imperfect information in subprime lending. American Economic Review. 99(1), 49–84. Retrieved from http://web.stanford.edu/~jdlevin/Papers/Liquidity.pdf

Avalos, A., and Alley, S. (2010). The economic impact of the Earned Income Tax Credit (EITC) in California. California Journal of Politics and Policy. 2(1). Retrieved from http://escholarship.org/uc/item/2jj0s1dn

Berube, A. (2005). Earned income credit participation—What we (don’t) know. Washington, DC: Brookings Institution. Retrieved from http://www.brookings.edu/metro/eitcparticipation.pdf

Berube, A. (2006a). Using the Earned Income Tax Credit to stimulate local economies. Washington, DC: Brookings Institution. Retrieved from http://www.brookings.edu/~/media/research/files/reports/2006/11/childrenfamilies-berube/berube20061101eitc.pdf

Berube, A. (2006b). ¿Tienes EITC? A study of the Earned Income Tax Credit in immigrant communities, Washington, DC: Brookings Institution. Retrieved from  http://www.brookings.edu/~/media/research/files/reports/2005/4/childrenfamilies-berube02/20050412_tieneseitc.pdf

Chetty, R., Friedman, J., and Saez, E. (2012). Using differences in knowledge across neighborhoods to uncover the impacts of the EITC on earnings (NBER Working Paper Series no. 18232). Retrieved from http://eml.berkeley.edu/~saez/chetty-friedman-saezNBER13EITC.pdf

Chetty, R., Hendren, N., Kline, P., and Saez, E. (2015). The economic impacts of tax expenditures: Evidence from spatial variation across the U.S. Retrieved from http://www.irs.gov/pub/irs-soi/14rptaxexpenditures.pdf

Halpern-Meekin, S., Edin, K., Tach, L., and Sykes, J. (2015). It’s not like I’m poor: How working families make ends meet in a post-welfare world, Oakland, CA: University of California Press.

Holt, S. D. (2008). Periodic payment of the Earned Income Tax Credit. Washington, DC: Brookings Institution. Retrieved from http://www.brookings.edu/research/papers/2008/06/0505-metroraise-supplement-holt

Internal Revenue Service. (2014). Statistics for tax returns with EITC. Retrieved from http://www.eitc.irs.gov/EITC-Central/eitcstats

Internal Revenue Service. (2015). About EITC. Retrieved from http://www.eitc.irs.gov/EITC-Central/abouteitc

Kneebone, E., and Berube, A. (2013). Confronting suburban poverty in America. Washington, DC: Brookings Institution Press.

Kneebone, E., and Holmes, N. Fighting poverty at tax time through the EITC. Retrieved from http://www.brookings.edu/blogs/the-avenue/posts/2014/12/16-poverty-tax-eitc-kneebone-holmes

Nichols, A., and Rothstein, J. (2015). The Earned Income Tax Credit (EITC) (NBER Working Paper Series no. 21211). Retrieved from http://www.nber.org/papers/w21211.pdf

From its modest beginnings in 1975, the Earned Income Tax Credit has grown into one of the nation’s most effective anti-poverty programs. Each year, the EITC supplements low-income workers’ earnings, encouraging work and lifting millions of people out of poverty.¹ It has positive lasting effects for parents, who have shown longer-run earnings increases and better health outcomes. At the same time, their children exhibit a host of benefits, from better school performance and higher rates of college enrollment to more hours worked and higher incomes in adulthood.² 

Moreover, the EITC supports economic stability in communities throughout the country where filers collectively receive millions of dollars in earnings supplements annually.³ These successes stem from a series of targeted expansions—supported by both Republicans and Democrats—over the EITC’s 40-year history, transforming it from a small credit into a significant income supplement for low-income working families.⁴

Yet more can be done to preserve and build on the effectiveness of the EITC, and a growing number of elected officials and policy experts have proposed  strengthening the credit. Three main recommendations have emerged from these proposals.

Preserve two key provisions of the EITC that are set to expire in 2017;

Expand the credit for workers without qualifying children; and

Offer filers options to receive a portion of the credit outside of tax time.

In this brief, we consider the first two recommendations, using our MetroTax model and detailed microdata from the 2014 American Community Survey to estimate the impact of these potential changes on workers and on the metropolitan areas and states where they live.⁵ A new analysis by Steve Holt will take an in-depth look at the issue of periodic payment.

If two key EITC provisions expire in 2017, 7.4 million filers would lose part or all of their EITC.

In 2009, Congress and the Obama administration enacted two targeted, but temporary, expansions to the EITC. The legislation reduced the “penalty” for married couples filing jointly by extending their eligibility for the credit $5,000 beyond that for unmarried filers, and it boosted the credit for families with three or more children (who are more likely to be low-income even when working).

If those provisions expire in 2017, the EITC would shrink for 6.7 million taxpayers, while a little under 700,000 filers would lose eligibility altogether. Two-thirds of filers who would be affected are married couples, 1.8 million of whom are also raising more than two kids (meaning they would be subject to both cuts). The remaining third are unmarried workers with at least three children. Most of these taxpayers (58 percent) have a high school diploma or less, and they are most likely to work in manufacturing, construction, and retail. The typical adjusted gross income of these filers is $28,000 a year, just above the poverty line for a family of four (roughly $24,000 in 2014).

States and metro areas in the Midwest and West would see the steepest cuts if these provisions expire. 

Every state stands to lose millions of dollars if these EITC provisions are not made permanent. States and metro areas with higher-than-average shares of married couples and larger families would be hardest hit. In the Intermountain West, Idaho and Utah could see a 10 percent drop in federal EITC dollars coming into the state (Table 1). The major population centers in those states—including metropolitan Provo and Ogden in Utah and Boise, Idaho—top the list of major metro areas that would experience the biggest cuts if these provisions expire.

While larger states like California and Texas would see their EITC claims drop by smaller percentages, the size of the EITC-eligible population in these states mean that the expiration of these two provisions would translate into a loss of more than half a billion dollars in California ($538 million) and over $400 million in Texas. Taxpayers in the Los Angeles metro area stand to lose an estimated $185 million in EITC receipts, while those in Dallas would forfeit nearly $100 million. (For detailed state and metro data see the appendix.)

Expanding the credit for workers without qualifying children would benefit more than 14.4 million filers. 

The EITC for childless workers is significantly smaller than the credit for families with children. In tax year 2013 (the most recent year for which detailed data are available), workers with qualifying dependents received $2,794 on average through the EITC, compared to the meager $281 claimed by the average childless worker.⁶ In fact, low-wage earning childless adults are the only group of taxpayers actually taxed into (or deeper into) poverty by the federal tax system.⁷

Both President Obama and House Speaker Paul Ryan have proposed expanding the EITC for these workers, as have legislators—including Sen. Patty Murray (D-Wash.), Rep. Richard Neal (D-Mass.), and Rep. Barbara Lee (D-Calif.)—and Republican presidential candidate Jeb Bush.⁸ (Republican presidential candidates Ted Cruz and John Kasich have also called for the EITC to be expanded but have not specified whom that expansion would target.⁹)

The proposals put forward by Obama, Ryan, Lee, and Bush are strikingly similar (although they differ considerably in how they would pay for it). These expansions would double the size of the credit for childless workers and the pace at which the credit phases in and out (Figure 1). They would also lower the minimum age of eligibility from 25 to 21.¹⁰

Together, these changes would boost the value of the credit for 8 million filers and extend eligibility to 6.4 million more taxpayers, increasing EITC dollars for these workers by $6.9 billion.¹¹

The filers who would benefit from these changes are largely unmarried workers (87 percent) who are most likely to be employed in service industries (retail, accommodation and food service, administrative services), health care, and construction. Half of these workers have a high school diploma or less. The typical adjusted gross income for these workers is just $8,300, well below the poverty threshold for individuals and married couples without children (e.g., $12,316 and $15,853, respectively, in 2014).

Several states and large metro areas in the Midwest and Northeast would see the number of childless workers eligible for the EITC more than double if the credit were expanded. 

The District of Columbia and Utah, each of which has above-average shares of the population between 21 and 24, would experience the largest percentage growth in the number of childless workers eligible for the EITC (135 and 134 percent, respectively). However, the bulk of states that would double their pool of eligible filers without qualifying children fall in the Midwest (North Dakota, Iowa, Nebraska, and Wisconsin) and Northeast (Rhode Island, Massachusetts, and Vermont), and tend have higher-than-average shares of one-person households and households without children.

Similarly, while the number of EITC-eligible childless workers in the Provo metro area would more than triple if the credit were expanded, most of the major metro areas that would at least double the number of eligible workers without qualifying children are in the Midwest (e.g., Grand Rapids, Milwaukee, and Toledo) and Northeast (e.g., Bridgeport, Boston, and Springfield) (Map 1).

In this era of partisan gridlock in Washington, it is rare to find a policy with the kind of bipartisan support the EITC has received—a testament to its effectiveness in encouraging work, alleviating poverty, and improving outcomes for workers and their children. By preserving key provisions of the EITC for working families and by making the EITC work better for workers without qualifying children, millions of Americans across the country stand to benefit.

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Each year, one in five households filing a federal income tax return claims the Earned Income Tax Credit (EITC). Targeted primarily to lower-income workers with children, it is one of many credits and deductions filers take each year on their federal income tax forms. However, unlike typical credits and deductions, the EITC is a refundable credit, meaning that after offsetting what is owed to the government filers receive the remainder of the benefit as a refund.

By supplementing earnings for low- and moderate-income households, the EITC helps bridge the gap between what the labor market provides and what it takes to support a family. It encourages and rewards work and has become one of the nation’s largest and most effective anti-poverty programs. In contrast to other work support and poverty alleviation programs, it achieves this with very little bureaucracy beyond what otherwise exists to administer the tax code.

Although the EITC began in 1975 as a small credit (no more than $400), a number of targeted expansions in subsequent years mean that today the EITC’s assistance can be considerable. In 2015, a single parent with three children working full-time all year at the federal minimum wage ($7.25 an hour) is eligible for a credit of $6,242, a boost of more than 40 percent above her earnings of $15,080 (though combined it still leaves her 12 percent below the federal poverty level).

However, the only way to obtain these substantial benefits is to claim the EITC on the annual federal income tax return. While lump-sum payments have perceived benefits (such as being able to pay off debts, make larger purchases, or force savings), the EITC’s single annual disbursement can present a challenge for the working parent trying to make ends meet throughout the year. It can also be problematic for households wanting to stretch out their refund as an emergency savings reserve.

My 2008 paper, “Periodic Payment of the Earned Income Tax Credit,” proposed an option that would allow a family to receive a portion of the EITC outside of tax time, striking a balance between lump-sum delivery and the need for resources throughout the year. Specifically, half of the credit could be claimed in four payments spread out during the year, while the remaining credit would continue to be paid as part of the tax refund.

Since then, several significant developments have occurred. A little-used option for receiving some of the EITC in each paycheck ended in 2010. In 2014, the federal government initiated a new tax credit advance payment process to subsidize health insurance premiums through monthly disbursement of the Affordable Care Act’s Premium Tax Credit. Other countries providing assistance similar to the EITC have continued to innovate and offer access to benefits during the year. Finally, members of Congress and think tanks have proposed alternatives to a single lump-sum disbursement of the EITC, and others have begun to explore and experiment with alternatives, most notably in Chicago, where a 2014 pilot program made quarterly payments to 343 households.

In light of these developments, this paper reviews the author’s original EITC periodic payment proposal, examines emerging alternatives, and addresses the following key questions:

• What is the demand for periodic payment alternatives?
  
  
• What benefits will accrue from the availability of periodic payment?
  
  
• What risks are associated with periodic payment and how can they be managed?
  
  
• What is the administrative feasibility of periodic payment?

The emerging answers point a way forward for identifying different distribution options that would enhance the EITC’s value to low- and moderate-income working families.

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The Earned Income Tax Credit (EITC) supports millions of single parents and their children each year. Although the majority of these are single moms, Father’s Day provides a good reminder that single dads are also a significant part of the equation.

Using Brookings’ MetroTax model, we estimate that roughly half (49 percent) of all EITC-eligible tax filers in 2014 filed as head of household—a group that includes many single custodial parents. Of these estimated 13.1 million filers, 8.9 million were women, and 4.2 million were men. These female-headed households included an estimated 14.7 million qualifying children, while their male counterparts included 6 million qualifying children.

Although women head of household filers were more likely to be EITC-eligible (69 percent), male heads of household were not far behind, with an estimated 61 percent eligible to receive the EITC in 2014.

To learn more about the EITC-eligible population, visit Brookings’ EITC data interactive.

EXECUTIVE SUMMARY

Parents, educators, government ministers and policymakers in all contexts and countries around the world are concerned with learning and how to improve it. There are many reasons for this, but none is more important than the fact that learning is at the heart of success at the individual, community and global levels. Learning First is the title of this report, with the strong implication that learning should be the foremost goal of education policies worldwide.

The present review seeks not only to explain why this is the case but also focuses on what we need to know—that is, what research is needed—in order to improve learning in the decades to come, particularly among those children most in need. This question is addressed in the following six sections.

1. Learning Goals and Research. The first section begins with a historical synopsis of international education goals put forward in 1990 at the World Conference on Education for All in Jomtien (Thailand), in 2000 at the Education for All conference in Dakar, and later in 2000 as a part of the UN Millennium Development Goals for 2015. In 2011, the Center for Universal Education at the Brookings Institution published A Global Compact on Learning: Taking Action on Education in Developing Countries, which stated that there is a “global learning crisis—which affects children and youth who are out of school with limited learning opportunities and those who are in school but not learning the skills they need for their futures.” The present review of learning research in low-income countries follows from that report. The overall purpose is to explore the most pressing learning issues today that require further research attention in the years to come.
    
2. Learning Definitions and Contexts. This section reviews how the field of education has defined learning over the years. Here, learning is defined as a modification of behavior due to experience—such as in knowledge, skills, attitudes and values. Three main principles of effective learning are suggested: individual active involvement, social participation, and meaningful engagement. As a way to emphasize the importance of learning contexts, three individual stories—Illa, a four-year-old Quechua-speaking girl in Peru; Pawan, an eight-year-old primary school student in urban India; and Rachida, a young illiterate woman in rural Morocco—are provided in order to better explain the importance of learning as a culturally specific phenomenon. These stories help to illustrate a more general learning framework, encompassing the relationship between two dimensions of learning—its processes and contexts. A discussion follows concerning the need to disaggregate learners and their learning contexts—between countries and within countries—as a way to overcome frequent and simplistic generalizations about how the “average” child learns.
    
3. Global Change and the Contexts of Learning. This section considers the issue of global change on how learning and learning contexts are being transformed around the world. For example, researchers need to pay more attention to the impact of migration on children’s learning and on educational systems more broadly. In each instance of translocation, children confront the challenges of adapting to a new environment that may include different languages, dialects or cultures within the nonformal learning contexts of daily life. Similarly, in formal education contexts, student migrants have to cope with contrasts in culture, lifestyle and language of schooling, and demonstrate skills and achievement that may vary dramatically with their culture of origin. Other changes due to globalization include increased multilingualism in schools, growing overcrowding in classrooms, inability to keep up with teacher training, changes in intergenerational learning, and the growing importance of 21st-century skills. Based on these observations, it is suggested that learning contexts and needs should be understood as a shifting target.

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The confluence of the agreement on 17 Sustainable Development Goals (SDGs, or Global Goals) in 2015, and the increased attention being paid to the role of non-traditional actors in contributing to shared prosperity, provide a unique opportunity to focus attention on attempts to identify promising new solutions to the barriers that impede the full development of the world’s youngest citizens. Current estimates indicate that 200 million children globally under the age of 5 are at risk of not reaching their development potential. With these goals, the global community has a tremendous opportunity to change the course of history. There is evidence that certain early childhood development (ECD) interventions—spanning the nutrition, health, water and sanitation, education, social protection, and governance sectors from conception to age 5—have high potential to help to achieve the SDGs related to child development. Furthermore, early childhood interventions have been found to improve adult health and education levels, reduce crime, and raise employment rates, which will be paramount to achieving global economic, climate, and physical security.

Impact bonds have the potential to address some of the main financing and delivery constraints faced in ECD. By providing upfront private capital, impact bonds could help to address service provider liquidity constraints and leverage public capital by allowing the government to connect preventive programs with future benefits to individuals, society, and the economy. Impact bonds also have the potential to drive performance management, support monitoring and evaluation, and create accountability, which all help to address quality and capacity constraints. By fostering innovation, experimentation and adaptive learning in service delivery, cost-effective solutions could be identified through impact bonds. By producing evidence of outcome achievement, impact bonds could shift the focus toward effective ECD programs. Finally, collaboration across stakeholders—a necessary component of impact bonds—has the potential to allow for alignment of interests and a win-win situation for investors, outcome funders, and program beneficiaries alike.

The high participation of non-state actors and potentially significant returns in ECD make it a promising sector for impact bonds. Unlike other services that may have entrenched interests, the multitude of agencies and non-state entities financing and providing ECD services potentially allows for more experimentation. The preventive nature of ECD programs also fits well with the core feature of SIBs, which is that preventive investments will result in valuable short- and potentially long-term outcomes. There is evidence that ECD interventions can have immense effects on later-life outcomes. For example, a longitudinal study of a program in Jamaica, in which participants received weekly visits from community health workers over a 2-year period, was found to increase the earnings of participants by 25 percent, 20 years later.

There may, however, be some particular challenges associated with applying impact bonds in the ECD sector. Impact bonds (and other Payment by Results mechanisms tied to outcomes) require meaningful outcomes that are measureable within a timeframe that is reasonable to the outcome funder (and investors in the case of an impact bond). Meaningful outcomes are outcomes that are intrinsically or extrinsically valuable. Intrinsically valuable outcomes that are measureable within a reasonable timeframe could be extrinsically valuable if they are proxies for long-term benefits to individuals, society, or the economy. The delay between ECD interventions and later-life results may prove an impediment in some cases. By identifying appropriate interim measures such as language development, socioemotional development, and schooling outcomes that may proxy for desirable longer-term outcomes, the issue of delay could be mitigated. For example, there is evidence that early stimulation and health programs can have statistically significant effects on schooling outcomes in the short-run. An increase in focus on the intrinsic value of short-term outcomes that result from ECD interventions, such as child survival, is also important.

As the global community moves beyond the Millennium Development Goals to a set of Global Goals and associated targets linked to measurable outcomes, there is an opportunity to demonstrate a commitment to invest in future generations. Leveraging upfront funding, focusing on outcomes through adaptive learning and testing new ways to deliver early childhood interventions more effectively are all means of achieving the ECD-related goals. Despite the hype around all of the new financing mechanisms, the keys to creating high-quality, locally appropriate programs remains simple—real-time collection of outcome data, the freedom to fail, and the flexibility to course-adjust. In some circumstances social service provision based on outcomes and adaptive learning may require mechanisms like impact bonds or other Payment by Results mechanisms. In other circumstances it may not. As this very nascent field continues to grow, more research will be needed to capture lessons learned, contextualize them within the larger landscape of ECD financing and service provision, and apply them to real-world social challenges with the world’s youngest and most disadvantaged populations at the forefront of the conversation. 

Read the previous report on the landscape of impact bonds across sectors and geography »

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March 18 was an historic day for early childhood development (ECD) financing—the Departments of Social Development and Health of the Western Cape province of South Africa committed 25 million rand ($1.62 million) in outcome funding for three social impact bonds (SIBs) for maternal and early childhood outcomes. This is the first ever funding committed by a middle-income government for a SIB—to date no low-income country governments have participated in a SIB either—making South Africa’s choice to pioneer this new path especially exciting.

A SIB is a financing mechanism for social outcomes where investors provide upfront capital for services and a government agency repays investors contingent on outcome achievement. There are currently two active development impact bonds or DIBs (where a donor provides outcome funding rather than a government agency) in middle-income countries, one for coffee production in Peru and one for girls’ education in India. The South African SIBs, whose implementation was facilitated by the Bertha Centre for Social Innovation and Entrepreneurship at the University of Cape Town and Social Finance U.K. as well as other organizations, will be the first impact bonds in Africa.

We have been following closely the development of these SIBs over the last two years through our research on the potential applications of impact bonds for ECD outcomes, and recently hosted a discussion on the topic at Brookings. There are currently nine other impact bonds worldwide that include outcomes for children ages 0 to 5, including two recently announced impact bonds in the U.S. for nurse home-visiting in South Carolina and support for families struggling with substance abuse in Connecticut.

Impact bonds are well suited to fund interventions that have high potential returns to society; that require learning, adaptability, and combinations of services to achieve those returns; and that are not core government-funded services (often resulting in a relative proliferation of non-state providers). In our recent report, we find that a majority of evaluations show ECD can have unparalleled returns, but there are also a number of evaluations that show no significant impact or where impact fades out. Overall however, there are few evaluations relative to the number of service providers and interventions, an indication of how little we know about the effectiveness of the majority of service providers. For example, there are only 15 studies examining the effects of ECD interventions in low- and middle-income countries on later-life socioemotional development, which has been shown to be a critical determinant of success in school and life.

The case for government investment is strong, but continuous learning and adaptation is needed to ensure the high potential impacts are achieved. Tying payments to outcomes could help the ECD sector in three ways: it could encourage new government investment in ECD, it could encourage performance management and adaptability, and, crucially, it could help develop the knowledge base of what works in ECD. Unlike some other sectors where providers are able to finance their own operations to participate in a results-based (performance-based) contract through fees or other cash flows, ECD providers will almost always require upfront capital in order to reach the most vulnerable. Consequently, we find that, despite some significant challenges, ECD interventions are particularly well suited to impact bonds.

For this reason, there are three things we find particularly exciting about these new SIBs for early childhood development in South Africa:

1. Collaboration of two departments to ensure a continuity of outcome measurement and, hopefully, achievement. Given their different mandates, the Department of Health will fund outcomes for pregnant mothers and children in their first 1,000 days and the Department of Social Development will fund outcomes for children ages 2 to 5. The Bertha Centre writes that “the funding will be made available to three community based organizations working with pregnant women and children up to five years of age with outcomes including improved antenatal care, prevention of mother to child transmission of HIV, exclusive breastfeeding, a reduction in growth stunting, and improved cognitive, language and motor development.” 

The continuity of quality services is essential to sustaining the impacts of early childhood services, and this is the first set of impact bonds to address outcomes across the development spectrum from age 0 to 5. Selecting outcomes however, particularly for more complex learning outcomes for children ages 3 to 5, can be one of the greatest challenges for impact bonds in the ECD sector.

A full list of recommended outcome metrics for ECD impact bonds is available in our report.

2. Outcome fund structure. The SIBs in South Africa have been designed as impact bond funds, where the outcome funder issues a rate card of prices it is willing to pay for certain outcomes and multiple service providers are awarded contracts to provide those outcomes. This structure, which has been implemented in four instances in the U.K., could help facilitate impact bonds at greater scale than what we have seen thus far.

At the Brookings event on impact bonds, Louise Savell of Social Finance U.K., explained that scale was critical in the South African case because there are few providers that work across the entire province. While the discussion around pricing outcomes in the U.K. was more focused on future value to the economy, the discussion in South Africa had to be more attuned to the price of providing services. These delivery prices differ greatly by township, which may result in different outcome payment prices by township. The impact bond designers also had to ensure the outcome price allowed for providers to serve the hardest to reach.

3. Matching of private-sector outcome funds. This is the first impact bond to date where private-sector actors will augment outcome funds, in addition to serving as investors. Impact bonds take a great deal of work for a government agency to establish—though it will likely drop over time—and additional or matching of outcome funds will be critical to making this effort worthwhile for low- and middle-income country governments.

Looking forward, it will be interesting to compare and contrast the structure and design of these SIBs with the impact bonds for ECD outcomes in Cameroon, India, and potentially other countries as they launch in the coming years. Each impact bond must be designed taking into consideration the particular issues and challenges in a given context. However, sharing learnings from one impact bond to the next will likely improve both efficiency and quality of the impact bond implementation. 

Many scholars have argued that once “basic needs” have been met, higher income is no longer associated with higher in subjective well-being. We assess the validity of this claim in comparisons of both rich and poor countries, and also of rich and poor people within a country. Analyzing multiple datasets, multiple definitions of “basic needs” and multiple questions about well-being, we find no support for this claim. The relationship between well-being and income is roughly linear-log and does not diminish as incomes rise. If there is a satiation point, we are yet to reach it.

Introduction

In 1974 Richard Easterlin famously posited that increasing average income did not raise average well-being, a claim that became known as the Easterlin Paradox. However, in recent years new and more comprehensive data has allowed for greater testing of Easterlin’s claim. Studies by us and others have pointed to a robust positive relationship between well-being and income across countries and over time (Deaton, 2008; Stevenson and Wolfers, 2008; Sacks, Stevenson, and Wolfers, 2013). Yet, some researchers have argued for a modified version of Easterlin’s hypothesis, acknowledging the existence of a link between income and well-being among those whose basic needs have not been met, but claiming that beyond a certain income threshold, further income is unrelated to well-being.

The existence of such a satiation point is claimed widely, although there has been no formal statistical evidence presented to support this view. For example Diener and Seligman (2004, p. 5) state that “there are only small increases in well-being” above some threshold. While Clark, Frijters and Shields (2008, p. 123) state more starkly that “greater economic prosperity at some point ceases to buy more happiness,” a similar claim is made by Di Tella and MacCulloch (2008, p. 17): “once basic needs have been satisfied, there is full adaptation to further economic growth.” The income level beyond which further income no longer yields greater well-being is typically said to be somewhere between $8,000 and $25,000. Layard (2003, p. 17) argues that “once a country has over $15,000 per head, its level of happiness appears to be independent of its income;” while in subsequent work he argued for a $20,000 threshold (Layard, 2005 p. 32-33). Frey and Stutzer (2002, p. 416) claim that “income provides happiness at low levels of development but once a threshold (around $10,000) is reached, the average income level in a country has little effect on average subjective well-being.”

Many of these claims, of a critical level of GDP beyond which happiness and GDP are no longer linked, come from cursorily examining plots of well-being against the level of per capita GDP. Such graphs show clearly that increasing income yields diminishing marginal gains in subjective well-being. However this relationship need not reach a point of nirvana beyond which further gains in well-being are absent. For instance Deaton (2008) and Stevenson and Wolfers (2008) find that the well-being–income relationship is roughly a linear-log relationship, such that, while each additional dollar of income yields a greater increment to measured happiness for the poor than for the rich, there is no satiation point.

In this paper we provide a sustained examination of whether there is a critical income level beyond which the well-being–income relationship is qualitatively different, a claim referred to as the modified-Easterlin hypothesis. As a statistical claim, we shall test two versions of the hypothesis. The first, a stronger version, is that beyond some level of basic needs, income is uncorrelated with subjective well-being; the second, a weaker version, is that the well-being–income link estimated among the poor differs from that found among the rich.

Claims of satiation have been made for comparisons between rich and poor people within a country, comparisons between rich and poor countries, and comparisons of average well-being in countries over time, as they grow. The time series analysis is complicated by the challenges of compiling comparable data over time and thus we focus in this short paper on the cross-sectional relationships seen within and between countries. Recent work by Sacks, Stevenson, and Wolfers (2013) provide evidence on the time series relationship that is consistent with the findings presented here.

To preview, we find no evidence of a satiation point. The income–well-being link that one finds when examining only the poor, is similar to that found when examining only the rich. We show that this finding is robust across a variety of datasets, for various measures of subjective well-being, at various thresholds, and that it holds in roughly equal measure when making cross-national comparisons between rich and poor countries as when making comparisons between rich and poor people within a country.

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Editor’s note: The following remarks were prepared and delivered by Gary Burtless at a roundtable sponsored by the American Tax Policy Institute on January 7, 2016. Video of Burtless’ remarks are also available on the Institute’s website. Download the related slides at the right. 

To eliminate suspense from the start: Nothing I am about to say undermines the popular narrative about recent inequality trends.  For the past 35 years, U.S. inequality has increased.  Inequality has increased noticeably, no matter what income definition you care to use.  A couple of things you read in the newspaper are untrue under some income definitions. For example, under a comprehensive income definition it is false to claim that all the income gains of the past 2 or 3 decades have gone to the top 1 percent, or the top 5 percent, or the top 10 percent of income recipients.  Middle- and low-income Americans have managed to achieve income gains, too, as we shall see.

Tax policy certainly affects overall inequality, but I shall leave it for Scott, David, and Tracy to take that up. Let me turn to my main job, which is to distinguish between different reasonable income measures.

The crucial thing to know is that contradictory statements can be made about some income trends because of differences in the definition of income.  In general, the most pessimistic statements about trends rely on an income definition that is restrictive in some way.  The definition may exclude important income items, items, for example, that tend to equalize or boost family incomes.  The definition may leave out adjustments to income … adjustments that tend to boost the rate of income gain for low- or middle-income recipients, but not for top-income recipients.

The narrowest income definition commonly used to evaluate income trends is Definition #1 in my slide, “pretax private, cash income.”  Columnists and news reporters are unknowingly using this income definition when they make pronouncements about the income share of the “top 1 percent.”  The data about income under this definition are almost always based on IRS income tax returns, supplemented with a bit of information from the Commerce Department’s National Income and Product Account (NIPA) data file.

The single most common income definition used to assess income trends and inequality is the Census Bureau’s “money income” definition, Definition #2 on the slide.  It is just the same as the first definition I mentioned, except this income concept also includes government cash transfer payments – Social Security, unemployment insurance, cash public assistance, Veterans’ benefits, etc.

A slightly more expansive definition (#3) also adds food stamp (or SNAP) benefits plus other government benefits that are straightforward to evaluate. Items of this kind include the implicit rent subsidy low-income families receive in publicly-subsidized housing, school lunch subsides, and means-tested home heating subsidies.

Now we come to subtractions from income. These typically reflect families’ tax obligations.  The Census Bureau makes estimates of state and federal income tax liabilities as well as payroll taxes owed by workers (though not by their employers).  Since income and payroll taxes subtract from the income available to pay for other stuff families want to buy, it seems logical to also subtract them from countable income. This is done under income Definition #4.  Some tax obligations – notably the Earned Income Credit (EIC) – are in fact subtractions from taxes owed, which would not be a problem in the case of families that still owe positive taxes to the government.  However, the EIC is refundable to taxpayers, meaning that some families have negative tax liabilities:  The government owes them money.  In this case, if you do not take taxes into account you understate low-income families’ incomes, even as you’re overstating the net incomes available to middle- and high-income families.

Now let’s get a bit more complicated.  Forget what I said about taxes, because our next income definition (#5) also ignores them.  It is an even-more-comprehensive definition of gross or pretax income.  In addition to all those cash and near-cash items I mentioned in Definition #3, Definition #5 includes imputed income items, such as: 

• The value of your employer’s premium contribution to your employee health plan;
• The value of the government’s subsidy to your public health plan – Medicare, Medicaid, state CHIP plans, etc.
• Realized taxable gains from the sale of assets; and
• Corporate income that is earned by companies in which you own a share even though it is not income that is paid directly to you.

This is the most comprehensive income definition of which I am aware that refers to gross or pre-tax income.

Finally we have Definition #6, which subtracts your direct and indirect tax payments.  The only agency that uses this income definition is principally interested in the Federal budget, so the subtractions are limited to Federal income and payroll taxes, Federal corporate income taxes, and excise taxes.

Before we go into why you should care about any of these definitions, let me mention a somewhat less important issue, namely, how we define the income-sharing group over which we estimate inequality.  The most common assessment unit for income included under Definition #1 (“Pre-tax private cash income”) is the Federal income tax filing unit.  Sometimes this unit has one person; sometimes 2 (a married couple); and sometimes more than 2, including dependents.

The Census Bureau (and, consequently, most users of Census-published statistics) mainly uses “households” as reference units, without any adjustment for variations in the size of different households.  The Bureau’s median income estimate, for example, is estimated using the annual “money income” of households, some of which contain 1 person, some contain 2, some contain 3, and so on.

Many economists and sociologists find this unsatisfactory because they think a $20,000 annual income goes a lot farther if it is supporting just one person rather than 12.  Therefore, a number of organizations—notably, the Luxembourg Income Study (LIS), the Organisation of Economic Cooperation and Development (OECD), and the Congressional Budget Office (CBO)—assume household income is equally shared within each household, but that household “needs” increase with the square root of the number of people in the household.  That is, a household containing 9 members is assumed to require 1½ times as much income to enjoy the same standard of living as a family containing 4 members.  After an adjustment is made to account for the impact of household size, these organizations then calculate inequality among persons rather than among households.

How are these alternative income definitions estimated?  Who uses them?  What do the estimates show?  I’ll only consider a two or three basic cases.

First, pretax, private, cash income. By far the most famous users of this definition are Professors Thomas Piketty and Emmanuel Saez.  Their most celebrated product is an annual estimate of the share of total U.S. income (under this restricted definition) that is received by the top 1 percent of tax filing units.

Here is their most famous chart, showing the income share of the top 1 percent going back to 1913. (I use the Piketty-Saez estimates that exclude realized capital gains in the calculation of taxpayers’ incomes.) The notable feature of the chart is the huge rise in the top income share between 1970—when it was 8 percent of all pretax private cash income—and last year—when the comparable share was 18 percent.  

I have circled one part of the line—between 1986 and 1988—to show you how sensitive their income definition is to changes in the income tax code.  In 1986 Congress passed the Tax Reform Act of 1986 (TRA86). By 1988 the reform was fully implemented.  Wealthy taxpayers noticed that TRA86 sharply reduced the payoff to holding corporate earnings inside a separately taxed corporate entity. Rich business owners or shareholders could increase their after-tax income by arranging things so their business income was taxed only once, at the individual level.  The result was that a lot of income, once earned by and held within corporations, was now passed through to the tax returns of rich individual taxpayers. These taxpayers appeared to enjoy a sudden surge in their taxable incomes between 1986 and 1988.  No one seriously believes rich people failed to get the benefits of this income before 1987.  Before 1987 the same income simply showed up on corporate rather than on individual income tax returns.

A final point:  The chart displayed in SLIDE #6 is the source of the widely believed claim that U.S. inequality is nowadays about the same as it was at the end of the Roaring 1920s, before the Great Depression.  That is close to being true – under this income definition.

Census “money income”: This income definition is very similar to the one just discussed, except that it includes cash government transfer payments.  The producer of the series is the Census Bureau, and its most famous uses are to measure trends in real median household income and the official U.S. poverty rate. Furthermore, the Census Bureau uses the income definition to compile estimates of the Gini coefficient of household income inequality and the income shares received by each one-fifth of households, ranked from lowest to highest income, and received by the top 5 percent of households.

Here is a famous graph based on the Bureau’s “median household income” series.  I have normalized the historical series using the 1999 real median income level (1999 and 2000 were the peak income years according to Census data).  Since 1999 and 2000, median income has fallen about 10 percent.  If we accept this estimate without qualification, it certainly represents bad news for living standards of the nation’s middle class. The conclusion is contradicted by other government income statistics that use a broader, more inclusive income definition, however.

And here is the Bureau’s most widely cited distributional statistic (after its “official poverty rate” estimate).  Since 1979, the Gini coefficient has increased 17 percent under this income definition. (It is worth noting, however, that the portion of the increase that occurred between 1992 and 1993 is mainly the result of methodological changes in the way the Census Bureau ascertained incomes in its 1994 income survey.)

When you hear U.S. inequality compared with that in other rich countries, the numbers are most likely based on calculations of the LIS or OECD.  Their income definition is basically “Cash and Near-cash Public and Private income minus Income and Payroll taxes owed by households.”  Under this income definition, the U.S. looks relatively very unequal and America appears to have an exceptionally high poverty rate.  U.S. inequality has been rising under this income definition, as indeed has also been the case in most other rich countries. The increase in the United States has been above average, however, helping us to retain our leadership position, both in income inequality and in relative poverty.

We turn last to the most expansive income definition:  CBO’s measure of net after-tax income.  I will use CBO’s tabulations using this income definition to shed light on some of the inequality and living standard trends implied by the narrower income definitions discussed above.

Let’s consider some potential limitations of a couple of those definitions.  The limitations do not necessarily make them flawed or uninteresting.  They do mean the narrower income measures cannot tell us some of the things that users claim they tell us.

An obvious shortcoming of the “cash pretax private income” definition is that it excludes virtually everything the government does to equalize Americans’ incomes.  Believe it or not, the Federal tax system is mildly progressive.  It claims a bigger percentage of the (declared) incomes of the rich than it does of middle-income families’ and especially the poor.  Any pretax income measure will miss that redistribution.

More seriously, it excludes all government transfer payments.  You may think the rich get a bigger percentage of their income from government handouts compared with middle class and poorer households.  That is simply wrong.  The rich get a lot less.  And the percentage of total personal income that Americans derive from government transfer payments has gone way up over the years.  In the Roaring 1920s, Americans received almost nothing in the form of government transfers. Less than 1 percent of Americans’ incomes were received as transfer payments.  By 1970—near the low point of inequality according to the Piketty-Saez measure—8.3 percent of Americans’ personal income was derived from government transfers.  Last year, the share was 17 percent. None of the increase in government transfers is reflected in Piketty and Saez’s estimates of the trend in inequality.  Inequality is nowadays lower than it was in the late 1920s, mainly because the government does more redistribution through taxes and transfers.

Both the Piketty-Saez and the Census “money income” statistics are affected by the exclusion of government- and employer-provided health benefits from the income definition. This slide contains numbers, starting in 1960, that show the share of total U.S. personal consumption consisting of personal health care consumption.  I have divided the total into two parts. The first is the share that is paid for out of our own cash incomes (the blue part at the bottom).  This includes our out-of-pocket spending for doctors’ charges, hospital fees, pharmaceutical purchases, and other provider charges as well as our out-of-pocket spending on health insurance premiums. The second is the share of our personal health consumption that is paid out of government subsidies to Medicare, Medicaid, CHIP, etc., or out of employer subsidies to employee health plans (the red part). 

As everyone knows, the share of total consumption that consists of health consumption has gone way up.  What few people recognize is that the share that is directly paid by consumers—through payments to doctors, hospitals, and household health insurance premium payments—has remained unchanged.  All of the increase in the health consumption share since 1960 has been financed through government and employer subsidies to health insurance plans. None of those government or employer contributions is counted as “income” under the Piketty-Saez and Census “money income” definitions.  You would have to be quite a cynic to claim the subsidies have brought households no living standard improvements since 1960, yet that is how they are counted under the Piketty-Saez and Census “money income” definitions.

Final slide: How much has inequality gone up under income definitions that count all income sources and subtract the Federal income, payroll, corporation, and excise taxes we pay?  CBO gives us the numbers, though unfortunately its numbers end in 2011.

Here are CBO’s estimates of real income gains between 1979 and 2011.  These numbers show that real net incomes increased in every income category, from the very bottom to the very top.  They also show that real incomes per person have increased much faster at the top—over on the right—than in the middle or at the bottom—over on the left.  Still, contrary to a common complaint that all the income gains in recent years have been received by folks at the top, the CBO numbers suggest net income gains have been nontrivial among the poor and middle class as well as among top income recipients.

Suppose we look at trends in the more recent past, say, between 2000 and 2011.  That lower panel in this slide presents a very different picture from the one implied by the Census Bureau’s “money income” statistics.  Unlike the “money income numbers” [SLIDE #9], these show that inequality has declined since 2000.  Unlike the “money income numbers” [SLIDE #8], these show that incomes of middle-income families have improved since 2000.  There are a variety of explanations for the marked contrast between the Census Bureau and CBO numbers.  But a big one is the differing income definitions the two conclusions are based on.  The more inclusive measure of income shows faster real income gains among middle-income and poorer households, and it suggests a somewhat different trend in inequality.

Alert voters everywhere realize the economy is neither as strong as claimed by the party in power nor the disaster described by the opposition. The election season will bring many passionate but dubious claims about economic trends. People running for office know that voters rank the economy near the top of their concerns. Of course, perceptions of the economy differ from one voter to the next. A few of us are soaring, more are treading water, and too many are struggling just to stay afloat.

Since reaching a low point in 2009, total U.S. output—as measured by real GDP—has climbed 15 percent, or about 2.1 percent a year. The recovery has been long-lived and steady, a tribute to the stewardship of the Administration and Federal Reserve. The economic rebound has also been disappointingly slow in view of the depth of the recession. GOP office seekers will mention this fact a number of times before November.

Compared with the worst months of the Great Recession, the unemployment rate has dropped by half. It now stands at a respectable 4.9 percent, almost 3 points lower than the rate when President Obama took office and far below the rate in fall 2009 when it reached 10 percent. Payroll employment has increased for 77 consecutive months. Since hitting a low in January 2010, the number of workers on employer payrolls has surged 14.6 million, or about 190,000 a month. While the job gains are encouraging, they have not been fast enough to bring the employment-to-population ratio back to its pre-recession level. June’s job numbers showed that slightly less than 80 percent of adults between 25 and 54 were employed. That’s almost 2 percentage points below the employment-to-population rate on the eve of the Great Recession.

One of the most disappointing numbers from the recovery has been the growth rate of wages. In the first 5 years of the recovery, hourly wages edged up just 2 percent a year. After factoring in the effect of consumer price inflation, this translates into a gain of exactly 0 percent. The pace of wage gain has recently improved. Workers saw their real hourly pay climb 1.7 percent a year in the two years ending in June.

The economic bottom line for most of us is the rate of improvement in our family income after accounting for changes in consumer prices. No matter how household income is measured, income gains have been slower since 2007 than they were in earlier decades. The main reason is that incomes produced in the market—in the form of wages, self-employment income, interest, dividends, rental income, and realized capital gains—fell sharply in the Great Recession and have recovered very slowly since then. That a steep recession would cause a big drop in income is hardly a surprise. Employment, company profits, interest rates, and rents plunged in 2008 and 2009, pushing down the incomes Americans earn in the market. The bigger surprise has been the slow recovery of market income once the recession was behind us.

Some critics of the recovery argue that the income gains in the recovery have been highly skewed, with a disproportionate share obtained by Americans at the top of the income ladder. Economist Emmanuel Saez tabulates U.S. income tax statistics to track market income gains at the top of the distribution. His latest estimates show that between 2009 and 2015 income recipients in the top 1 percent enjoyed real income gains of 24 percent. Among Americans in the bottom nine-tenths of the income distribution, average market incomes climbed only 4 percent.

However, Saez’s estimates also show that top income recipients experienced much bigger income losses in the Great Recession. Between 2007 and 2009 they saw their inflation-adjusted incomes drop 36 percent (see Chart 1). In comparison, the average market income of Americans in the bottom nine-tenths of the distribution fell just 12 percent. These numbers mean that top income recipients have not yet recovered the income losses they suffered in the Great Recession. In 2015 their average market income was still 13 percent below its pre-recession level. For families in the bottom nine-tenths of the distribution, market income was “only” 8 percent below its level in 2007.

Only about half of households rely solely on market income to support themselves. The other half receives income from government transfers. What is more, this fraction tends to increase in bad times. Many retirees rely mainly on Social Security to pay their bills; they depend on Medicare or Medicaid to pay for health care. Low-income Americans often have little income from the market, and they may rely heavily on public assistance, food stamps, or government-provided health insurance. When joblessness soars the percentage of families receiving government benefits rises, largely because of increases in the number of workers who collect unemployment insurance.

Government benefits, which are not counted in Saez’s calculations, replace part of the market income losses families experience in a weak economy. As a result, the net income losses of most families are much smaller than their market income losses. The Congressional Budget Office (CBO) recently published statistics on market income and before-tax and after-tax income that shed light on the size and distribution of household income losses in the Great Recession and ensuing recovery. The tabulations show that, except for households at the top of the distribution, net income losses were far smaller than the losses indicated in Saez’s income tax data.

For example, among households in the middle fifth of the before-tax income distribution, average market income fell more than 10 percent in the Great Recession (see Chart 2). If we include government transfers in the income definition, average income fell 4.4 percent. If we account for the federal taxes families pay, average net income fell just 1 percent. In contrast, among households in the top 1 percent of the distribution, average market income fell 36 percent, average income including government transfers fell 36 percent, and average income net of federal taxes fell 37 percent. Government transfers provided little if any protection to top-income households.

The CBO income statistics end in 2013, so they do not tell us how net income gains have been distributed in the last couple of years. Nonetheless, based on Saez’s income tax tabulations it is very unlikely top income recipients have recovered the net income losses they experienced in the Great Recession. All the available statistics show household income gains since 2007 have been negligible or small, and this is true across the income distribution.

It is popular to say slow income gains in the middle and at the bottom of the distribution are due to outsize income gains among families at the top. While this story is at least partly true for the three decades ending in 2007, it does not fit the facts for the years since 2007. CBO’s latest net income tabulations show that inequality was almost 5 percent lower in 2013 than it was in 2007. The Great Recession hurt the incomes of Americans up and down the income distribution, but the biggest proportional income losses were at the very top. To be sure, income gains in the recovery after 2009 have been concentrated among top income recipients. Even so, their income losses over the recession and recovery have been proportionately bigger than the losses suffered by middle- and low-income families.

Editor's note: This piece originally appeared in Real Clear Markets.

When Franklin Roosevelt delivered his second inaugural address on January 20, 1936 he lamented the “one-third of a nation ill-housed, ill-clad, ill-nourished.” He challenged Americans to measure their collective progress not by “whether we add more to the abundance of those who have much; [but rather] whether we provide enough for those who have too little.” In our new paper, One third of a nation: Strategies for helping working families, we ask a simple question: How are we doing?

In brief, we find that:

• The gulf in labor market income between the haves and have-nots remains wide. The median income of households in the bottom third in 2014 was $24,000, just a little more than a quarter of the median of $90,000 for the top two-thirds.
• The bottom-third households are disproportionately made up of minority adults, adults with limited educational attainment, and single parents.  
• The most important reason for the low incomes of the bottom third is a “work gap”: the fact that many are not employed at all, or work limited hours. 

The work gap

The decline in labor force participation rates has been widely documented, but the growing gulf in the work gap between the bottom third and the rest of the population is truly striking:

While the share of men who are employed in the top two-thirds has been quite stable since 1980, lower-income men’s work rates have declined by 11 percentage points. What about women?

Middle- and upper-income women have increased their work rates by 13 percentage points. This has helped maintain or even increase their family’s income. But employment rates among lower-income women have been flat, despite reforms of the welfare system and safety net designed to encourage work.

Many on the left point to problems like low pay and lack of access to affordable childcare, and so favor a higher minimum wage and more subsidies for daycare. For many conservatives, the problem is rooted in family breakdown and a dependency-inducing safety net. They therefore champion proposals like marriage promotion programs and strict work requirements for public benefits. Most agree about the importance of education.

Time to debate some more radical solutions 

It may be that the standard solutions to the problems of the bottom third, while helpful, are no longer sufficient. A debate about whether to make safety net programs such as Food Stamps and housing assistance conditional on work or training is underway. So are other solutions such as subsidized jobs (created by some states during the Great Recession as a natural complement to a work-conditioned safety net), more work sharing (used in Germany during the recession), or even a universal basic income (being considered by Swiss voters in June).

The idea of a universal basic income (UBI) is certainly an intriguing one, and has been gaining traction. Swiss voters just turned it down. But it is still alive in Finland, in the Netherlands, in Alaska, in Oakland, CA, and in parts of Canada. 

Advocates of a UBI include Charles Murray on the right and Anthony Atkinson on the left. This surprising alliance alone makes it interesting, and it is a reasonable response to a growing pool of Americans made jobless by the march of technology and a safety net that is overly complex and bureaucratic. A comprehensive and excellent analysis in The Economist points out that while fears about technological unemployment have previously proved misleading, “the past is not always a good guide to the future.”

Robert Greenstein argues, however, that a UBI would actually hurt the poor by reallocating support up the income scale. His logic is inescapable: either we have to spend additional trillions providing income grants to all Americans or we have to limit assistance to those who need it most. 

One option is to provide unconditional payments along the lines of a UBI, but to phase it out as income rises. Libertarians like this approach since it gets rid of bureaucracies and leaves the poor free to spend the money on whatever they choose, rather than providing specific funds for particular needs. Liberals fear that such unconditional assistance would be unpopular and would be an easy target for elimination in the face of budget pressures. Right now most of our social programs are conditional. With the exception of the aged and the disabled, assistance is tied to work or to the consumption of necessities such as food, housing, or medical care, and our two largest means-tested programs are Food Stamps and the Earned Income Tax Credit.

Liberals have been less willing to openly acknowledge that a little paternalism in social policy may not be such a bad thing. In fact, progressives and libertarians alike are loath to admit that many of the poor and jobless are lacking more than just cash. They may be addicted to drugs or alcohol, suffer from mental health issues, have criminal records, or have difficulty functioning in a complex society. Money may be needed but money by itself does not cure such ills. 

A humane and wealthy society should provide the disadvantaged with adequate services and support. But there is nothing wrong with making assistance conditional on individuals fulfilling some obligation whether it is work, training, getting treatment, or living in a supportive but supervised environment.

In the end, the biggest problem with a universal basic income may not be its costs or its distributive implications, but the flawed assumption that money cures all ills.  

The narratives on U.S. development aid to Pakistan—as well as Pakistan’s own development policy discussion—frequently invoke the conventional wisdom that more education and better economic opportunities result in lower extremism. In the debate surrounding the Kerry-Lugar-Berman bill in 2009, for instance, the late Ambassador Richard Holbrooke urged Congress to “target the economic and social roots of extremism in western Pakistan with more economic aid.”

But evidence across various contexts, including in Pakistan, has not supported this notion (see Alan Kreuger’s What Makes a Terrorist for a good overview of this evidence). We know that many terrorists are educated. And lack of education and economic opportunities do not appear to drive support for terrorism and terrorist groups. I have argued that we need to focus on the quality and content of the educational curricula—in Pakistan’s case, they are rife with biases and intolerance, and designed to foster an exclusionary identity—to understand the relationship between education and attitudes toward extremism.

My latest analysis with data from the March 2013 Pew Global Attitudes poll conducted in Pakistan sheds new light on the relationship between years of education and Pakistanis’ views of the Taliban, and lends supports to the conventional wisdom. The survey sampled 1,201 respondents throughout Pakistan, except the most insecure areas of Khyber Pakhtunkhwa and Baluchistan. This was a time of mounting terror attacks by the Pakistani Taliban (a few months after their attack on Malala), and came at the tail end of the Pakistan People's Party’s term in power, before the May 2013 general elections.

On attitudes toward the Pakistani Taliban, or Tehrik-e-Taliban Pakistan (TTP), 3 percent of respondents to the Pew poll said they had a very favorable view, 13 percent reported somewhat favorable views, while nearly 17 percent and 39 percent answered that they had somewhat unfavorable and very unfavorable views, respectively. A large percentage of respondents (28 percent) chose not to answer the question or said they did not know their views. This is typical with a sensitive survey question such as this one, in a context as insecure as Pakistan.

So overall levels of support for the TTP are low, and the majority of respondents report having unfavorable views. The non-responses could reflect those who have unfavorable views but choose not to respond because of fear, or those who may simply not have an opinion on the Pakistani Taliban.

The first part of my analysis cross-tabulates attitudes toward the TTP with education and income respectively. I look at the distribution of attitudes for each education and income category (with very and somewhat favorable views lumped together as favorable; similarly for unfavorable attitudes).

Figure 1. Pakistani views on the Pakistani Taliban, by education level, 2013

Figure 1 shows that an increasing percentage of respondents report unfavorable views of the Taliban as education levels rise; and there is a decreasing percentage of non-responses at higher education levels (suggesting that more educated people have more confidence in their views, stronger views, or less fear). However, the percentage of respondents with favorable views of the Taliban, hovering between 10-20 percent, is not that different across education levels, and does not vary monotonically with education. 

Figure 2. Pakistani views on the Pakistani Taliban, by income level, 2013

Figure 2 shows views on the Pakistani Taliban by income level. While the percentage of non-responses is highest for the lowest income category, the percentages responding favorably and unfavorably do not change monotonically with income. We see broadly similar distributions of attitudes across the four income levels.

But these cross-tabulations do not account for other factors that may affect attitudes: age, gender, and geographical location. Regressions (not shown here) accounting for these factors in addition to income and education show interesting results: relative to no education, higher education levels are associated with less favorable opinions of the Pakistani Taliban; these results are strongest for those with some university education, which is heartening. This confirms findings from focus groups I conducted with university students in Pakistan in May 2015. Students at public universities engaged in wide ranging political and social debates with each other on Pakistan and its identity, quoted Rousseau and Chomsky, and had more nuanced views on terrorism and the rest of the world relative to high school students I interviewed. This must at least partly be a result of the superior curriculum and variety of materials to which they are exposed at the college level.

My regressions also show that older people have more unfavorable opinions toward the Taliban, relative to younger people; this is concerning and is consistent with the trend toward rising extremist views in Pakistan’s younger population. The problems in Pakistan’s curriculum that began in the 1980s are likely to be at least partly responsible for this trend. Urban respondents seem to have more favorable opinions toward the Taliban than rural respondents; respondents from Punjab and Baluchistan have more favorable opinions toward the Taliban relative to those from Khyber Pakhtunkhwa, which as a province has had a closer and more direct experience with terror. The regression shows no relationship of income with attitudes, as was suggested by Figure 2.

Overall, the Pew 2013 data show evidence of a positive relationship between more education and lack of support for the Taliban, suggesting that the persisting but increasingly discredited conventional wisdom on these issues may hold some truth after all. These results should be complemented with additional years of data. That is what I will work on next.