Event Information

In 2015, 193 countries adopted the Sustainable Development Goals (SDGs), a new global agenda that is more ambitious than the preceding Millennium Development Goals and aims to make progress on some of the most pressing issues of our time. Goal 4, "To ensure inclusive and quality education for all, with relevant and effective learning outcomes," challenges the international education community to meet universal access plus learning by 2030. We know that access to primary schooling has scaled up rapidly over previous decades, but what can be learned from places where transformational changes in learning have occurred? What can governments, civil society, and the private sector do to more actively scale up quality learning?

On April 18-19, the Center for Universal Education (CUE) at Brookings launched "Millions Learning: Scaling Up Quality Education in Developing Countries," a comprehensive study that examines where learning has improved around the world and what factors have contributed to that process. This two-day event included two sessions. Monday, April 18 focused on the role of global actors in accelerating progress to meeting the SDGs. The second session on Tuesday, April 19 included a presentation of the Millions Learning report followed by panel discussions on the role of financing and technology in scaling education in developing countries.

 Join the conversation on Twitter #MillionsLearning

Video

• Getting millions to learn: What will it take to accelerate progress on meeting the Sustainable Development Goals?
• Scaling quality education: The launch of the Millions Learning report
• Do funders help or hinder scaling in education?
• What role can technology play in scaling education?

Audio

• Getting millions to learn: What will it take to accelerate progress on meeting the Sustainable Development Goals?

Transcript

• Uncorrected Transcript - Day 1 (.pdf)
• Uncorrected Transcript - Day 2 (.pdf)

Event Materials

• 20160418_millions_learning_transcript
• 20160419_millions_learning_transcript

How has the Joint Comprehensive Plan of Action (JCPOA)—signed between the P5+1 and Iran one year ago—played out in practice? Several Brookings scholars, many of whom participated prominently in debates last year surrounding official congressional review, offered their views.

Social Security faces a financial shortfall. If Congress does nothing about it, current projections indicate that benefits will be cut automatically by 21 percent in 2034. Congress could close the gap by raising revenues, lowering benefits, or doing some of both. If benefits seem generous, Congress is likely to lean toward benefit cuts more than revenue increases. If they seem stingy, then the reverse.

Given the split between the two parties on whether to cut benefits or to raise them, evidence on the adequacy of benefits is central to this key policy debate. Those perceptions will help determine whether Social Security continues to provide basic retirement income for workers with comparatively low earnings histories and a foundation of retirement income for most others or it will become just a minimal safety-net backstop against extreme destitution?

Down-in-the-weeds disagreements among analysts often seem too arcane for anyone other than specialists. But sometimes they are too important to ignore. A current debate about the adequacy of Social Security benefits is an example.

The not-so-simple question is this: are Social Security benefits ‘generous’ or ‘stingy’? To answer this question, people long looked to the Office of the Social Security Actuary. For many years that office published estimates of something called the ‘replacement rate’—that is, how high are benefits paid to retirees and the disabled relative what they earned during their working years. A 2014 retiree with median earnings had average lifetime earnings of about $46,000. That worker qualified for a benefit at age 66 of about $19,000, a replacement rate of about 41%. Replacement rates vary with earnings. Dollar benefits rise with earnings, but they rise less than proportionately. As a result, replacement rates of low earners are higher than replacement rates of high earners.

As you might suppose, there are many ways in which to compute such ‘replacement rates. Because of analytical disputes on which method is best, the Social Security trustees in 2014 decided to stop including replacement rate estimates in their annual reports.

In December 2015, the Congressional Budget Office (CBO) offered what it considered a better measure of the generosity of Social Security. It estimated that replacement rates for middle income recipients were about 60%–dramatically higher than the 41% that the Social Security Trustees had estimated.

The gap between the estimates of CBO and those of Social Security is even larger than it seems. To see why, one needs to recognize that to sustain living standards retirees on average need only about 75% to 80% as much income as they did when working. Retirees need less income because they are spared some work-related expenses, such as transportation to and from work. Those are only average of course; some need more, some less.

If one believed the SSA actuaries, Social Security provides median earners barely more than half of what they need to be as well off as they were when working. Benefit cuts from that modest level would threaten the well-being for the majority of retirees who are entirely or mostly dependent on Social Security benefits—and especially for those with large medical expenses uncovered by Medicare.

On the other hand, if one accepted CBO’s estimates, Social Security provids more than three-quarters of the retirement income target. Against that baseline, benefit cuts would still sting, but they would pose less of a threat, and not much of a threat at all for most retirees who have some income from private pensions or personal savings.

When the CBO estimates came out, conservative commentators welcomed the findings and cited CBO’s well-established and well-earned reputation for objectivity. They correctly noted that many retirees have additional income from private pensions, 401ks, or other personal savings, and asserted that there was no general retirement income shortage. By inference, cutting benefits a bit to help close the long-term funding gap would be no big deal. Social Security advocates were put on the defensive, hard-pressed to challenge the estimates of the widely-respected Congressional Budget Office.

But earlier this year, CBO acknowledged that it had made mistakes in its Decameter estimates and revised them. The new CBO estimate put the replacement rate for middle-level earners at around 42%, almost the same as the estimate of the Social Security actuaries, not the much higher level that had sent ripples through the policy community. One conservative analyst, Andrew Biggs, who had trumpeted the initial CBO finding in The Wall Street Journal, promptly and honorably retracted his article.

Two aspects of this green-eyeshade kerfuffle stand out. The first is that policy debates often depend on obscure technical analyses that are, in turn, remarkably sensitive to ‘black-box’ methods to which few or no outsiders have ready access. The second is that CBO burnished its reputation for honesty by owning up to its own mistakes — in this case, a whopping overestimate of a key number. Such candor is all too rare; it merits notice and praise.

But there is a broader lesson as well. Technical issues of comparable complexity surround numerous current political disputes. Is Bernie Sanders’ single-payer plan affordable? Will Marco Rubio’s tax plan cause deficits to balloon? To vote rationally, people must struggle to see through the rhetorical chaff that surrounds candidates’ favorite claims. There is, alas, no substitute for paying close attention to the data, even if they are ‘down in the weeds.’

Editor's note: This piece originally appeared in Fortune.

As a rhetorical ideal, greater opportunity is hard to beat. Just about all candidates for high elected office declare their commitments to promoting opportunity – who, after all, could be against it? But opportunity is, to borrow a term from the philosopher and political theorist Isaiah Berlin, a "protean" word, with different meanings for different people at different times.

Typically, opportunity is closely entwined with an idea of upward mobility, especially between generations. The American Dream is couched in terms of a daughter or son of bartenders or farm workers becoming a lawyer, or perhaps even a U.S. senator. But even here, there are competing definitions of upward mobility.

It might mean being better off than your parents were at a similar age. This is what researchers call "absolute mobility," and largely relies on economic growth – the proverbial rising tide that raises most boats.

Or it could mean moving to a higher rung of the ladder within society, and so ending up in a better relative position than one's parents.

Scholars label this movement "relative mobility." And while there are many ways to think about status or standard of living – education, wealth, health, occupation – the most common yardstick is household income at or near middle age (which, somewhat depressingly, tends to be defined as 40).

As a basic principle, we ought to care about both kinds of mobility as proxies for opportunity. We want children to have the chance to do absolutely and relatively well in comparison to their parents.

On the One Hand…

So how are we doing? The good news is that economic standards of living have improved over time. Most children are therefore better off than their parents. Among children born in the 1970s and 1980s, 84 percent had higher incomes (even after adjusting for inflation) than their parents did at a similar age, according to a Pew study. Absolute upward income mobility, then, has been strong, and has helped children from every income class, especially those nearer the bottom of the ladder. More than 9 in 10 of those born into families in the bottom fifth of the income distribution have been upwardly mobile in this absolute sense.

There's a catch, though. Strong absolute mobility goes hand in hand with strong economic growth. So it is quite likely that these rates of generational progress will slow, since the potential growth rate of the economy has probably diminished. This risk is heightened by an increasingly unequal division of the proceeds of growth in recent years. Today's parents are certainly worried. Surveys show that they are far less certain than earlier cohorts that their children will be better off than they are.

If the story on absolute mobility may be about to turn for the worse, the picture for relative mobility is already pretty bad. The basic message here: pick your parents carefully. If you are born to parents in the poorest fifth of the income distribution, your chance of remaining stuck in that income group is around 35 to 40 percent. If you manage to be born into a higher-income family, the chances are similarly good that you will remain there in adulthood.

It would be wrong, however, to say that class positions are fixed. There is still a fair amount of fluidity or social mobility in America – just not as much as most people seem to believe or want. Relative mobility is especially sticky in the tails at the high and low end of the distribution. Mobility is also considerably lower for blacks than for whites, with blacks much less likely to escape from the bottom rungs of the ladder. Equally ominously, they are much more likely to fall down from the middle quintile.

Relative mobility rates in the United States are lower than the rhetoric about equal opportunity might suggest and lower than people believe. But are they getting worse? Current evidence suggests not. In fact, the trend line for relative mobility has been quite flat for the past few decades, according to work by Raj Chetty of Stanford and his co-researchers. It is simply not the case that the amount of intergenerational relative mobility has declined over time.

Whether this will remain the case as the generations of children exposed to growing income inequality mature is not yet clear, though. As one of us (Sawhill) has noted, when the rungs on the ladder of opportunity grow further apart, it becomes more difficult to climb the ladder. To the same point, in his latest book, Our Kids – The American Dream in Crisis, Robert Putnam of Harvard argues that the growing gaps not just in income but also in neighborhood conditions, family structure, parenting styles and educational opportunities will almost inevitably lead to less social mobility in the future. Indeed, these multiple disadvantages or advantages are increasingly clustered, making it harder for children growing up in disadvantaged circumstances to achieve the dream of becoming middle class.

The Geography of Opportunity

Another way to assess the amount of mobility in the United States is to compare it to that found in other high-income nations. Mobility rates are highest in Scandinavia and lowest in the United States, Britain and Italy, with Australia, Western Europe and Canada lying somewhere in between, according to analyses by Jo Blanden, of the University of Surrey and Miles Corak of the University of Ottawa. Interestingly, the most recent research suggests that the United States stands out most for its lack of downward mobility from the top. Or, to paraphrase Billie Holiday, God blesses the child that's got his own.

Any differences among countries, while notable, are more than matched by differences within Pioneering work (again by Raj Chetty and his colleagues) shows that some cities have much higher rates of upward mobility than others. From a mobility perspective, it is better to grow up in San Francisco, Seattle or Boston than in Atlanta, Baltimore or Detroit. Families that move to these high-mobility communities when their children are still relatively young enhance the chances that the children will have more education and higher incomes in early adulthood. Greater mobility can be found in places with better schools, fewer single parents, greater social capital, lower income inequality and less residential segregation. However, the extent to which these factors are causes rather than simply correlates of higher or lower mobility is not yet known. Scholarly efforts to establish why it is that some children move up the ladder and others don't are still in their infancy.

Models of Mobility

What is it about their families, their communities and their own characteristics that determine why they do or do not achieve some measure of success later in life?

To help get at this vital question, the Brookings Institution has created a life-cycle model of children's trajectories, using data from the National Longitudinal Survey of Youth on about 5,000 children from birth to age 40. (The resulting Social Genome Model is now a partnership among three institutions: Brookings, the Urban Institute and Child Trends). Our model tracks children's progress through multiple life stages with a corresponding set of success measures at the end of each. For example, children are considered successful at the end of elementary school if they have mastered basic reading and math skills and have acquired the behavioral or non-cognitive competencies that have been shown to predict later success. At the end of adolescence, success is measured by whether the young person has completed high school with a GPA average of 2.5 or better and has not been convicted of a crime or had a baby as a teenager.

These metrics capture common-sense intuition about what drives success. But they are also aligned with the empirical evidence on life trajectories. Educational achievement, for example, has a strong effect on later earnings and income, and this well-known linkage is reflected in the model. We have worked hard to adjust for confounding variables but cannot be sure that all such effects are truly causal. We do know that the model does a good job of predicting or projecting later outcomes.

Three findings from the model stand out. First, it's clear that success is a cumulative process. According to our measures, a child who is ready for school at age 5 is almost twice as likely to be successful at the end of elementary school as one who is not.

This doesn't mean that a life course is set in stone this early, however.

Children who get off track at an early age frequently get back on track at a later age; it's just that their chances are not nearly as good. So this is a powerful argument for intervening early in life. But it is not an argument for giving up on older youth.

Second, the chances of clearing our last hurdle – being middle class by middle age (specifically, having an income of around $68,000 for a family of four by age 40) – vary quite significantly. A little over half of all children born in the 1980s and 1990s achieved this goal. But those who are black or born into low-income families were very much less likely than others to achieve this benchmark.

Third, the effect of a child's circumstances at birth is strong. We use a multidimensional measure here, including not just the family's income but also the mother's education, the marital status of the parents and the birth weight of the child. Together, these factors have substantial effects on a child's subsequent success. Maternal education seems especially important.

The Social Genome Model, then, is a useful tool for looking under the hood at why some children succeed and others don't. But it can also be used to assess the likely impact of a variety of interventions designed to improve upward mobility. For one illustrative simulation, we hand-picked a battery of programs shown to be effective at different life stages – a parenting program, a high-quality early-edcation program, a reading and socio-emotional learning program in elementary school, a comprehensive high school reform model – and assessed the possible impact for low-income children benefiting from each of them, or all of them.

No single program does very much to close the gap between children from lower- and higher-income families. But the combined effects of multiple programs – that is, from intervening early and often in a child's life – has a surprisingly big impact. The gap of almost 20 percentage points in the chances of low-income and high-income children reaching the middle class shrinks to six percentage points. In other words, we are able to close about two-thirds of the initial gap in the life chances of these two groups of children. The black-white gap narrows, too.

Looking at the cumulative impact on adult incomes over a working life (all appropriately discounted with time) and comparing these lifetime income benefits to the costs of the programs, we believe that such investments would pass a cost-benefit test from the perspective of society as a whole and even from the narrower prospective of the taxpayers who fund the programs.

What Now?

Understanding the processes that lie beneath the patterns of social mobility is critical. It is not enough to know how good the odds of escaping are for a child born into poverty. We want to know why. We can never eliminate the effects of family background on an individual's life chances. But the wide variation among countries and among cities in the U.S. suggests that we could do better – and that public policy may have an important role to play. Models like the Social Genome are intended to assist in that endeavor, in part by allowing policymakers to bench- test competing initiatives based on the statistical evidence.

America's presumed exceptionalism is rooted in part on a belief that class-based distinctions are less important than in Western Europe. From this perspective, it is distressing to learn that American children do not have exceptional opportunities to get ahead – and that the consequences of gaps in children's initial circumstances might embed themselves in the social fabric over time, leading to even less social mobility in the future.

But there is also some cause for optimism. Programs that compensate at least to some degree for disadvantages earlier in life really can close opportunity gaps and increase rates of social mobility. Moreover, by most any reasonable reckoning, the return on the public investment is high.

Editor's note: This piece originally appeared in the Milken Institute Review.

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.