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Legal empowerment of the poor, education, Africa, evaluating aid effectiveness
Justin Sandefur is a senior fellow at the Center for Global Development. Prior to joining CGD, he spent two years as an adviser to Tanzania's national statistics office and worked as a research officer at Oxford University's Centre for the Study of African Economies. His research focuses on a wide range of topics, including education, poverty reduction, legal reform, and democratic governance.
Can short–term unconditional cash transfers (UCT) create longer-term impacts? In a new paper, Berk Özler and co-authors study a group of young women in Malawi, who participated in a two-year cash transfer experiment as adolescents, in order to understand the long-term impacts of these short-term cash transfers. More than two years after the end of transfers, they find that the substantial short-term benefits of the program have largely evaporated. Unconditional cash transfers (UCT) caused short-term reductions in marriage, fertility, and HIV infection, but the cessation of cash transfers is immediately followed by a wave of marriages and pregnancies, accompanied with a catch-up to the control group in HIV prevalence. For those who had already dropped out of school at the outset of the experiment, two years of conditional cash transfers produced a meaningful long-term increase in educational attainment, delays in marriage, declines in fertility, and a more educated pool of husbands; however they see no increase in employment rates, earnings, real-life capabilities, or empowerment, suggesting that schooling itself has not improved the medium-term welfare of young women in this context.
Over the weekend, Angus Deaton won the Nobel Prize in economics. The previous weekend, the World Bank announced that the global poverty rate dipped below 10 percent in 2015, for the first time in history. These two announcements have an interesting connection.
One of Deaton’s many contributions has been to help economists improve how we measure consumption and welfare in developing countries. As Chris Blattman noted earlier this week, graduate students in development economics often venture out into the proverbial “field” for the first time lugging well-worn copies of Deaton’s book The Analysis of Household Surveys: A Microeconometric Approach to Development Policy, like missionaries clutching their bibles. This is part of what people mean when they talk about Deaton promoting “methodological individualism.” He gave development economists the tools to look beyond notoriously unreliable and opaque macroeconomic statistics from poor countries, and dig into micro-level survey data about individuals and households.
No institution has embraced Deaton's methods so enthusiastically as the World Bank. The Bank devotes immense resources to funding and assisting developing countries collect household survey data to make it possible to do the kind of micro analysis Deaton recommended, on health, education, inequality, and not least, the global poverty rate.
Which is why I was a bit surprised when the World Bank released new global poverty numbers last weekend going all the way up to 2015. The hallmark of the Bank’s herculean effort to measure global poverty is that it builds the number from the ground up, collating all the best available micro survey data from around the world. But here’s the catch: in the countries where most poor people live, the surveys stop in about 2012. Everything beyond 2012 is essentially guesswork, taking us back to the pre-Deaton era.
Even worse, not only is the Bank more or less guessing that poverty fell below 10 percent in 2015, the Bank’s own analysis (see chapter 6) shows that its own method of guessing is systematically biased toward optimism.
Figure 1. Projections show the global poverty rate may have fallen but the number of poor remains high
Source: Cruz et al (2015) http://pubdocs.worldbank.org/pubdocs/publicdoc/2015/10/109701443800596288/PRN03-Oct2015-TwinGoals.pdf
The ideologically loaded assumptions behind the World Bank’s 2015 poverty numbers
Suppose you have a survey on household consumption in India in 2004, and you need a poverty estimate for 2010. How do you get there? The methodology the Bank uses is to look at national accounts data to measure growth in household consumption from 2004 to 2010, apply this growth rate to the 2004 survey data, and estimate a new poverty rate.
This method embodies two big assumptions, which become very controversial if you utter them out loud. The first is that “Growth is Good for the Poor.” This is the title of a much-cited World Bank paper, by David Dollar and Aart Kraay. They show that on average, across countries and recent time periods, when average incomes rise, incomes of the bottom quintiles of the income distribution rise proportionally. That result still stands. But bear in mind, while this finding holds on average, individual countries may experience periods of extremely progressive or regressive growth.
The second big assumption in the World Bank’s method is that growth in household consumption in national accounts data is a good prediction of growth in consumption from household survey data. In many developing countries, national accounts estimate household consumption as a residual (what spending is left over after you measure government consumption, investment and international transactions), so there’s little hard data to rely on until household surveys are completed. Interestingly, while the Bank relies on the assumption that national accounts and surveys move together for the 2015 poverty number, it’s own analysis shows that assumption is unwise. Bank researchers found in 2014 that in recent years, national accounts measures of consumption have grown much faster than survey measures. (See Figure 6.3 below, reproduced from the World Bank report.) Using the former to estimate the latter will result in systematic bias toward finding rapid poverty reduction.
Figure 2. Growth rates of survey consumption versus growth rates of national accounts consumption
Source: World Bank (2014) https://openknowledge.worldbank.org/bitstream/handle/10986/20384/9781464803611.pdf
The report concludes that if the World Bank had applied the extrapolation methodology to India — assuming growth was good for the poor, and national accounts growth predicts growth in survey means — it would have underestimated the number of poor people by about 200 million in 2010. Keep in mind the Bank estimates there were about a billion poor people in the entire world that year. That’s not a small error.
It is clear that the researchers deep in the belly of the Bank hold their noses when they do extrapolations to come up with the latest poverty numbers, and would prefer to focus on years where there is survey data. But one can imagine — and note, this is purely speculation — that pressure from somewhere higher up in the bureaucracy to have headlines for 2015 is quite strong. If public relations has gotten ahead of real knowledge, that would be shame.
The first step is admitting you have a problem
There’s a great essay by Paul Krugman, “The Fall and Rise of Development Economics,” that tells the story of how Europeans’ maps of sub-Saharan Africa from the 15th to the 19th century got better and better along the coasts — where Europeans were, ahem, “exploring” — and worse and worse in the interior. The reason is obvious: over time, Europeans learned more, but the standards of map-making also improved. It was no longer acceptable to rely on hearsay. Stories of mythical creatures in the interior gave way to blank space on the map, while the coasts were fleshed out with sextants and compasses.
Krugman notes that the same thing happened in development economics from the 1940s to the 1970s. The deep intuitions of Albert Hirschman and Rosenstein Rodan were abandoned, as modern theorists searched for more rigorous mathematical formulations. While Krugman is concerned with theory, there may be an analogy to empirics, and what we know — or don’t know — about global poverty.
Deaton gave development economists the equivalent of sextants and compasses. The World Bank and the broader discipline have taken up these tools and dramatically improved our knowledge of the map of global poverty. But parts of the map, including everything added from 2012 to 2015, are still basically built on tall tales of mythical creatures. In order to make more progress, we may need to put those stories to rest, and admit how much we don’t know.
Nations frequently help migrants fleeing crisis. They help out of generosity—generosity that quickly wears thin. What would they do if they acted instead from stark self-interest? Consider András Gróf, a refugee who arrived illegally in Austria after crossing the Hungarian border with a smuggler and then running through a swampy field under cover of darkness. He came without his family, without a college degree, without assets beyond 20 dollars. Back home, he had watched soldiers arrive, first to rape his mother, later to conscript young men like him. So András fled for the same reason that so many others leave the Middle East and Africa; whether or not there was an imminent threat to his life, the future in his country looked hellish.
András didn’t arrive in Austria in 2015. He fled Hungary with 200,000 other refugees in 1956. But the global response to that earlier wave of (many non-Christian, mostly unskilled) refugees pouring into Western Europe shows a way forward for the international community today.
In an act of apparent generosity, 37 countries—from Venezuela to New Zealand—came together to resettle almost all of the refugees that resulted from the Hungarian Revolution of 1956. András went to the United States. Ten years later, under the new name of Andy Grove, he became a co-creator of Intel Corporation. Later Time magazine’s Person of the Year as Intel’s path-breaking CEO, he helped create an American industry of immeasurable economic and strategic importance. Other Hungarians in the same wave, who likewise arrived as unaccomplished young men, became artists (the great cinematographer László Kóvacs) and captains of industry (Steve Házy). More than 40,000 others became less-visible colleagues, neighbors, and spouses of Americans, strengthening and enriching the country vastly more than the assistance they got.
Grove’s story reveals some larger truths. Recent research overturns the standard narrative: that addressing migration crises mainly means curtailing the conflict and poverty that “push” migrants away from home, and slashing the excessive generosity that “pull” them into other countries. Instead, pragmatic and self-interested policymakers should consider that they often waste resources when trying to reduce push factors, and they can spark an inhumane and inefficient race to the bottom by acting individually to reduce pull factors. Through broad international cooperation to get people out of camps and into the labor force, though, they can transform refugees from a burden into an investment.
Waste and Worse
Politicians indulge in remarkable hubris when they speak of fixing the root causes of migration crises. Other countries can do little in the short run to end many crises once they are underway. The root causes of the Hungarian upheaval lasted a generation. Military intervention by the West would likely have led to chaos and much greater human flight. Today’s Middle East is no different. In a review of the entire history of refugee movements, the great political scientist Myron Weiner concluded that outside interventions can exacerbate and rarely halt mass departures from zones of conflict, particularly revolutions.
The lesson extends beyond sudden crises. Successful development assistance will typically increase emigration from low-income countries in the medium and long term. Officials commonly claim the opposite: that assisting economic development in poor countries, such as Yemen and Ethiopia, will reduce migration pressure from there in years to come. But research by one of us (Clemens) finds exactly the reverse pattern. Emigrants leave middle-income countries, such as Algeria and Albania, at about triple the rate that they leave the poorest countries. With greater earnings, they acquire the means, education, and contacts to depart. Only when countries surpass middle-income status, with further increases in prosperity at home, does migration pressure typically start to lessen.
What each rich country can do is alter what pulls people to that country specifically, once they have decided to flee their own land. To be sure, donor-countries can sometimes affect push factors to some degree. They can reduce forced migration after natural disasters through humanitarian aid inside the origin country. And for those displaced by conflict, donors can provide emergency assistance to nearby countries, in today’s case, Lebanon and Jordan, which are taking in the majority of migrants from Syria. Economists Ryan Bubb, Michael Kremer, and David Levine have proposed that rich countries could reduce onward flows by compensating third countries—elsewhere in the region or even far away—for the upfront costs of permanently resettling and integrating them. But in many crises, assistance in the original country of origin largely cannot deter departure.
A Race to the Bottom
What each rich country can do is alter what pulls people to that country specifically, once they have decided to flee their own land. Germany has shown willingness to consider large numbers of asylum applications from Syria this year, possibly attracting more of those already in flight. Conversely, countries can deter entry with draconian physical barriers and tight rationing of asylum. Tony Abbott’s Australia reduced unauthorized seaborne arrivals from about 20,000 in 2013 to almost zero in 2014, by instructing patrol ships to turn back migrant boats even if they appeared at risk of sinking.
These policies can effectively shunt migrants and asylum-seekers from one destination to another. But they create the pernicious incentive for other destination countries to do the same. If Slovakia and Hungary can divert fleeing Syrians to Germany, Slovakians and Hungarians can still free ride on the benefits of Germany’s assistance: all share in the relief of watching fewer migrant deaths. But if numerous other countries follow suit, the stress on Germany can surge. This raises pressure for Germany to likewise try to divert migrants elsewhere.
Such a race-to-the-bottom does not deter desperate people from leaving places where hope has succumbed to violence and destitution. In surveys conducted by economist Linguère Mously Mbaye, half of irregular migrants from Senegal said that they would be undeterred by a 25 percent chance of death on their way to Europe. So long as Europe is prosperous and free, the region as a whole will “pull” desperate people to its shores in times of crisis, despite roughly 20,000 deaths in the Mediterranean over the past decade.
The obvious solution is a cooperative mechanism to share responsibility for assistance.
Existing instruments of cooperation are terribly inadequate. The United Nations 1951 Convention Relating to the Status of Refugees enshrines the principle of “non-refoulement”—that people cannot be forcibly repatriated into persecution. But its obligations are national obligations, for the specific country in which a refugee arrives and seeks asylum. It only strengthens the incentives for each signatory to free-ride, physically diverting asylum seekers to transit countries and raising the standards of proof to grant asylum.
Asylum seekers and other crisis migrants can be apportioned by some more rational rule—rather than leaving cash-strapped southern Europe to cope with the crisis alone. This is the textbook solution to free-riding, and all participants can benefit. Coordination can serve each state’s self-interest.
The current proposal for refugee quotas voted by the EU on September 22 is a step in this direction, but it is much too modest. It accepts the notion that this is a European problem rather than a global one. This has two consequences. First, the plan only addresses the needs of 120,000 refugees, although 400,000 already require resettlement from Syria alone. Second, it leaves refugee camps in the Middle East drastically underfunded, which is likely to produce more forced displacement next year. A broader global solution is needed to cope with the full scale of this crisis.
The 1956 agreement that brought Andy Grove to America was built on this principle of cooperation for long-term self-interest. Austria was swamped with a flood of desperate Hungarians amounting to two percent of Hungary’s population. By accepting a refugee influx equivalent to just 0.02 percent of the American population, the United States absorbed almost a quarter of the total flow out of Hungary. In so doing, it helped turn what could have been a burden into a benefit. It made assisting the Hungarians an investment with a positive return.
Countries struggle to absorb refugee flows when those flows are sudden and concentrated in a limited area. Their beds and other facilities are quickly swamped, and all they can do is build camps—usually hived off from the economy and life around them. This is what Lebanon and Jordan have been forced to do, with too little international assistance. Moreover, encamped people can give back little in economic terms, as the camp serving their immediate needs also isolates them from any contribution they could make.
But the problem is the encampment, not the refugees themselves. Indefinite camp life could have wasted Grove’s talents; integration unleashed them. Refugees that can integrate and work generally perform well. Turkey’s recent efforts to integrate Syrian arrivals have caused them to have a net positive effect on Turkish workers’ wages, as economists Ximena del Carpio and Mathis Wagner have shown. Likewise refugees to the United States, after several years to get on their feet, economically outperform non-refugee migrants. Indeed, refugees in this country earn 20 percent more than other immigrants, work more hours, and speak better English, as economist Kalena Cortes has shown. They benefited the economy rather than burdening it.
Refugees to Europe likewise benefit the countries they go to, in the medium and long term. From 1994 to 2008, Denmark responded to successive international crises—in Yugoslavia and Somalia, and later in Iraq and Afghanistan—by admitting over 80,000 refugees, tripling the share of its population born outside the EU. Drawing on social security records covering all Danish workers, economists Mette Foged and Giovanni Peri have found that refugees raised the wages, employment, and occupational mobility of low-skill Danes. They did this by pushing Danes into more complex tasks and jobs, complementing many refugees’ more basic skills.
People who flee crises are seeds, scattered by a storm. These benefits are not automatic. They arise when migrant flows to any particular country are moderate. In major crises, this means that a coordinated group work to spread out the migrants and then integrate them. The United Nations High Commission for Refugees (UNHCR) estimates that the cost to host a Syrian refugee at Zaatari camp in Jordan can exceed $10,000 after a few years, without foreseeable economic benefits to UNHCR’s donors. But Germany reaps tens to hundreds of thousands of dollars in lifetime added-value from each Syrian that is successfully integrated into its labor force, an incredible bargain for the one-off $14,000 per person resettlement cost. These benefits depend, however, on other countries’ cooperation with Germany to mitigate the shock to the German system. And those other countries that cooperate can reap the same, positive long-term returns.
Seeds, Not Swarms
We will make better policy when we think more pragmatically and less fearfully about what a migration crisis is. To many newspapers, migrants fleeing violence are a “flood,” to extremists, they are an “invasion.” To the British Prime Minister—in a comment he later withdrew—they are a “swarm.”
History and reflection suggest a rather better metaphor: People who flee crises are seeds, scattered by a storm. When too many seeds are stuffed into one farm’s soil, few germinate and everyone loses. If farmers fear this outcome enough, those fears can become self-fulfilling. As each farmer pushes the seeds downhill onto someone else’s land, they pile up and become a burden. Alternatively, farmers can share the seeds and all reap a rich harvest.
These benefits are not immediate or automatic. But neither are they hypothetical. The world turned 200,000 desperate Hungarians into a gift. But only the world, not a country or two fulfilling its treaty obligations, could have done that: it took 37 nations working together. A global agreement with binding but equitable quotas could likewise resolve today’s crisis—and beyond that, turn it from an act of generosity into a historic investment with worldwide payoff.
Rigorous evaluations show giving poor people cash is a very effective policy. But polls show poor Tanzanians would rather have government services.
This is part II in our blog series about poll results from Tanzania on managing the country’s newfound natural gas wealth. Read part I on fuel subsidies and stay tuned for part III on transparency.
Cash transfers are all the rage among international development experts, and for good reason. In Tanzania, which is our focus here, randomized controlled trial (RCT) results show that the government’s pilot cash transfer program led to increased savings and livestock investment, reduced child illness, and improved education outcomes, with no increase in tobacco or alcohol expenditure. Myriad studies in other contexts reach similar findings.
There are also good reasons for Tanzanians to doubt the efficacy of spending natural gas revenues though regular government channels. Rakesh Rajani, former director of Tanzanian civil society organization Twaweza, remarked that after years of lobbying the government to spend more on education, he finally got what he wanted, and learned to stop asking. Tanzania dramatically increased its primary education over the past decade, but Twaweza research found enormous leakage between what was allocated to schools and what actually reached them. Worse, many children who are enrolled in government primary schools can’t read or do basic math. In this context, you might expect citizens to prefer cash in their pockets over bigger budgets for the ministry of education.
You’d be wrong. Results from our recent poll show that about two-thirds of Tanzanian voters would rather spend gas revenues on government services than cash transfers. That’s an even stronger rejection of cash than in earlier polling by Twaweza, which found voters preferred government spending on health, education and security services over direct distribution of natural gas revenues, 43 percent to 38 percent.
It’s not that people hate cash. When we asked respondents about the idea of using gas revenue for cash transfers without specifying any other policy options, they were more enthusiastic. A majority of Tanzanians supported direct distribution in general (62 percent) — more so if transfers were targeted to children and the elderly (68 percent), and even more so if targeted to child savings accounts (77 percent). But that support fell dramatically once the question was posed as a tradeoff between direct distribution and the alternative of the government spending the revenues.
If question phrasing matters so much, perhaps voters just need to stop and think this issue through. So what happened to support for cash transfers when we subjected respondents to our RCT in deliberative democracy?
After intensive deliberation — watching videos that presented experiences ranging from Tanzania’s own cash transfer experience to the Alaskan model, debating with each other, and asking questions of policymakers and researchers — people’s views about cash transfers were significantly different. They became even more convinced that government should spend the money itself. The share of Tanzanians who prefer direct distribution over government spending fell from 28 percent to 18 percent after deliberation. In short, the more people heard and talked about cash transfers, the less they liked the idea.
Figure 1. Cash transfers vs. government spending
Some people think that the money should be given directly to households... Other people think that the money should be spent by the government for what the public needs... Where would you place yourself?
Control group:Cash, 28%Gov’t, 66%
Information only:Cash, 24%Gov’t, 69%
Info and deliberation:Cash, 18%Gov’t, 77%
Explanations: Who doesn’t like money?
To explain the low level of support for cash transfers, we spliced the data a variety of ways: by wealth, education, gender, and a measure of trust in government.
Based on conversations with opposition politicians in Dar es Salaam, we speculated that people who trust the current government less would be more supportive of cash. What we found is the opposite: more trust in government yields more support for direct distribution, although this correlation is not statistically significant. We can only speculate after the fact as to why. Perhaps respondents preferred the known to the unknown: schools and health clinics have, after all, been built in most villages in rural Tanzania in the last 30 years. During deliberation, participants questioned the mechanisms required to channel cash directly to households. Who would be in charge of accounting for that transfer?
Anecdotally, one reason respondents cited for favoring government spending over direct distribution during the discussion was that social services encourage a collective voice that helps increase accountability, while cash transfers would focus people on private interests and leave room for corruption.
We found a bit more support for the idea that poorer, less educated people are more in favor of cash. This gap is not huge, though. If we disaggregate Figure 1 between the wealthier half and the poorer half of the deliberation treatment group, there’s about a 5 percent difference in support for cash. (In Tanzania, the bottom half of our national sample would be almost entirely below the international poverty line of $1.25 per day in PPP terms.)
Statistically, the strongest explanation of cash preferences is gender — and in particular, the interaction between gender and deliberation.
In the control group (not shown) men and women reported nearly identical views about cash transfers. Two days of information and deliberation did nothing to change women’s minds. But men, on the other hand, saw a fairly large decline in support for cash. If you look at the results in Figure 2, showing people’s opinions after deliberation, you’ll see men are notably less enthusiastic about distributing money in general, as well as to households with children and elderly members specifically. None of these gender differences existed before deliberation.
In sum, cash transfers appeal to poorer people and, once they’ve thought hard about it, women more than men. But all demographic groups (rich, poor, men, women, etc.) prefer government spending to cash.
Figure 2. People like cash transfers in principle, especially women and especially when targeted to vulnerable groups or for savings, but both men and women prefer government services
After deliberation, percent of respondents who supported distributing gas revenue through cash transfers...
... to all households:Women, 54%Men, 38%
... to all households with children, elderly:Women, 56%Men, 47%
... to retirement accounts:Women, 66%Men, 67%
... to child savings accounts:Women, 71%Men, 65%
... vs explicit trade-off with gov’t services:Women, 21%Men, 14%
Try it, you’ll like it
How much should these poll results matter to economists advocating cash transfer programs in the developing world?
Cash transfers might bring systemic benefits that aren’t immediately obvious to individual citizens responding to a poll. For instance, in a low-income country, sovereign rents from big oil or gas discoveries may seriously distort the relationship between government and citizens. Colleagues here at CGD argue that direct distribution of natural resource rents can help maintain the link between government revenue and citizen accountability. Their argument (known as “oil-to-cash,” or in Tanzanian’s case, gas-to-cash) is that if a government like Tanzania’s commits to distribute at least some of the windfall revenues directly to its own citizens, they’ll be more likely to have the information (about total gas revenue for example) and expectations (about future transfers) that will discourage misappropriation.
By this argument, democracy depends on cash transfers, rather than vice versa.
Another response to these poll results is that people might prefer cash transfers once exposed to them. James Ferguson’s recent book, Give a Man a Fish, documents the mass politics behind widespread social transfers in South Africa and neighboring countries. We suspect poll numbers would look different in these countries where a significant share of the population already depends on government transfers for a large share of their livelihood.
But the idea that people don’t know what’s best for them is hard to square with the finding that support for cash fell significantly when respondents in the RCT learned more about direct distribution proposals. You would have expected the opposite effect.
For now, it is interesting that in a low-income democracy like Tanzania, cash transfers remain a fairly technocratic fad, rather than a movement with popular, grassroots support. In Tanzania, people appear to trust their government more than economists do.
Last week, Gavi, the Vaccine Alliance, completed a $7.5 billion replenishment to fund its work on immunization in the world’s poorest countries between now and 2020. Gavi’s next step is to ensure that the money is used as effectively as possible to save lives and improve health.
Today, we’re launching a working paper and policy brief that we hope will be a helpful input to that discussion. We find that many of the vaccines provided by Gavi went to people who would have been vaccinated anyway, leading to little increase in overall vaccination rates — especially for the cheapest vaccines, and particularly in middle-income countries. Paradoxically, this is partially good news. Our results imply that if it's possible to save lives with a vaccine that costs a few cents, most middle-income countries will do it with or without aid. But that doesn't mean there's no place for aid. First, the poorest countries in the world still struggle to roll out basic vaccines. Second, for newer vaccines that countries have not widely adopted on their own, we find signs of a positive impact of Gavi aid on vaccination rates.
A natural experiment at a global level
Measuring the impact of Gavi is difficult. Alas, Gavi did not conduct a global RCT, randomly selecting program countries to receive aid. But they did something almost as useful from an analyst’s point of view: Gavi focused on countries whose initial gross national income (GNI) was below a strict threshold, originally set at $1,000 per capita. That means Gavi countries were poorer and had lower initial vaccination levels than non-Gavi countries. But the strict cut-off allows us to compare countries on either side of the threshold that should be fairly similar, and check for a jump in outcomes at $1,000.
As shown in the graph below, Gavi’s abrupt eligibility cut-off was fairly well enforced: the probability a given country received aid from Gavi in a given year jumped from about 20 percent if they had a per capita GNI just above $1,000 to over 80 percent if they were below the line. Lower-middle-income countries (i.e., countries in the vicinity of the cut-off, which is where our analysis is relevant) received roughly one-quarter of Gavi’s programmatic funding, while low-income countries, those further away from the threshold, received the remaining three-quarters.
So aid levels clearly jumped at the arbitrary $1,000 income threshold. Did outcomes jump as well, signaling a positive impact of Gavi aid? In short: for cheap vaccines they didn’t; for more expensive vaccines, results are more promising.
The results suggest that the impact of Gavi support depends on the vaccines it is buying. Approximately 40 percent of Gavi’s programmatic funding has been used to buy pentavalent vaccines — a combination shot covering diphtheria, pertussis, and tetanus (DPT) alongside Haemophilus influenza type B (Hib) and hepatitis B (hep B). In 2000, DPT coverage in threshold countries was already high, and the cost of the vaccine was low. Hib and hep B were more expensive, but prices for hep B fell fast and many non-eligible countries adopted the vaccine as part of their schedule. Today, DPT is available for $0.17 a dose, and hepatitis B for $0.19 a dose. Gavi’s provision of pentavalent vaccines effectively crowded out domestic spending on DPT and hep B.
But many countries above the threshold for Gavi support did not roll out Hib vaccinations, suggesting that element of the Gavi-purchased pentavalent vaccine was providing additional immunizations that would not have happened absent Gavi support. Similarly, Gavi purchases of the rotavirus vaccine (at $5 a dose), increased coverage among eligible countries as compared to ineligible countries.
The graph below shows hep B vaccination rates for countries on either side of the Gavi eligibility cut-off. While aid deliveries jump sharply at the eligibility line, there’s no sign of a similar jump in vaccinations — suggesting limited or no impact for countries near the threshold.
The picture looks more compelling for Hib. Though still far from conclusive, there’s a statistically significant jump up in Hib coverage as you cross the threshold into Gavi eligibility.
The results suggest that Gavi’s model of providing aid “in kind” (vaccines rather than cash) does not make it immune from the phenomenon of fungibility, where aid crowds out a recipient’s own spending. In this case, Gavi support for cheap vaccines in threshold countries displaced vaccine spending that governments would likely have made regardless. And the governments used the savings elsewhere. For vaccines that would not have been purchased absent Gavi support, fungibility was much less of an issue since there was no existing spending to displace.
It is important to note that these findings apply to countries near the threshold of Gavi eligibility. Across Gavi-eligible countries as a whole, hepatitis B coverage increased from 17 percent in 2000 to 80 percent in 2013 while Haemophilus influenza coverage increased from 4 percent to 77 percent. This very rapid adoption is consistent with a story that Gavi facilitated rollout of coverage through the provision of a combination vaccine covering those diseases as well as diphtheria, pertussis, and tetanus, especially in the poorest countries.
Vaccines save lives, and we find some evidence Gavi has significantly increased vaccine rollout. But our research suggests Gavi might have had an even bigger impact if it had steered resources away from buying cheap vaccines and associated expenditure in threshold countries. The good news is that Gavi has already started making reforms in this direction, introducing phased cofinancing at the threshold. We hope our paper will help in the design of the next round of adjustments.
Last summer, the Liberian government delegated management of 93 public elementary schools to eight different private contractors. Given the intense controversy around the program, the government—with some encouragement from our colleagues at Ark Education Partnership Group, who helped manage the program—agreed to randomize the allocation of schools during the pilot, and the three of us partnered with Innovations for Poverty Action (IPA) to evaluate its impacts. One year later, we have the first preliminary results from the randomized control trial, which we presented to President Ellen Johnson Sirleaf and her cabinet last week.
To save you a click, here's the lede from the joint CGD and IPA policy brief:
After one year, public schools managed by private operators raised student learning by 60 percent compared to standard public schools. But costs were high, performance varied across operators, and contracts authorized the largest operator to push excess pupils and under-performing teachers into other government schools.
We look forward to feedback on the paper, and please stay tuned for a more academic write-up of these results in the coming months—covering what we think they mean for the broader debate on aid in fragile states, school management, and charter schools.
In the meantime, Liberia is holding presidential elections next month. President Sirleaf and Education Minister George K. Werner championed both this project and the idea of a rigorous, independent evaluation. But it will fall in part to a new government to weigh the pros and cons highlighted in the evaluation their predecessors started. If the program continues, we hope to follow these schools and students through the full three years of the pilot, ending in the summer of 2019.
A commission led by the UN's special envoy for education, Gordon Brown, is calling for a doubling of global aid for education, without any clear reform agenda to raise learning levels in the world's failing school systems. That might be ok: bad schools in poor countries still seem to produce big benefits.
Last week the Center for Global Development hosted a panel with three heads of state vying to raise money for three rival education funds. Former UK prime minister Gordon Brown and former Tanzanian President Jakaya Kikwete were there to pitch a new entity they want to set up called the International Finance Facility for Education, aka IFFed, which they're billing as an analog to the widely celebrated Global Fund in health.
Awkwardly, something "like the Global Fund but for education" already exists, and its board chair was also on stage in the person of Julia Gillard, former Prime Minister of Australia, representing the Global Partnership for Education (GPE), which is also looking for money to replenish its coffers. Luckily, they seem to have agreed on a way to carve up the education landscape:
Brown's proposed fund, the IFFed, would serve lower middle-income countries, allowing them to borrow for education at concessional rates.
Gillard and GPE will continue to focus on low income countries with grant money. (Though, awkwardly again, the IFFed's list of "pioneer countries" also includes a number of low-income countries from the GPE's list, like Chad, Congo, Ethiopia, Malawi, Mozambique, and Tanzania. Why do we need a new organization again?)
And lastly, UNICEF's new "Education Cannot Wait" fund—represented on the panel last week by Tony Lake, UNICEF's Executive Director—will serve the true bottom of the pyramid, so to speak: refugees and displaced people.
Now, if only there was any money to divide. Aid budgets are tight these days. All the panelists were members of the U.N. Commission that Brown chaired on financing the U.N.'s Sustainable Development Goals for education. And the one thing all the panelists agreed on was that much more money was needed, both in aid and in domestic spending in developing countries.
Money probably won't improve school quality
Nobody on the panel had any appetite to talk about politically difficult education reforms that might turn money into learning.
Indeed, rather than focusing on the UN's new global learning goals, Gordon Brown and colleagues have shifted their focus to global spending goals. That's a very different conversation: in the unlikely event large amounts of new aid money are forthcoming in today's political climate, they're far from guaranteed to produce learning outcomes.
This is something of a departure from the text of Brown's Education Commission report, which dives deep into data and current literature on how to achieve learning for all. It bemoans the 'learning crisis' in many developing countries, reviews effective interventions to overcome the crisis, the need for more and better learning assessment, and notes that more spending often isn't the answer (see Figure 1 which shows Vietnam's high performance and low spending, and the inverse spending-performance relationship in a sample of Pakistani districts). Even as it turns to the question of finance, the report focuses on innovative mechanisms to incentivize reform and a stronger focus on learning.
That was the bait, now comes the switch. In the very last chapter the report turns to its "ask", tallying up why the world needs to raise education spending by $200 billion a year. And in the public discussion of the Commission's work, it's those spending goals—not all the careful analysis of reforming school systems—which now dominate the conversation.
Throwing money at failing school systems is welcome, but unlikely to work. A vast body of research questions the link between education spending and learning outcomes, and some of the best micro research on interventions to improve learning focuses on things that cost zero money, or even reduce education budgets.
In a review of programs to raise learning in the developing world in the journal Science, Michael Kremer, Conner Brannen, and Rachel Glennerster reach a conclusion broadly at odds with the push for money first:
[A]mong those in school, test scores are remarkably low and unresponsive to more-of-the-same inputs, such as hiring additional teachers, buying more textbooks, or providing flexible grants. In contrast, pedagogical reforms that match teaching to students’ learning levels are highly cost effective at increasing learning, as are reforms that improve accountability and incentives, such as local hiring of teachers on short-term contracts.
The things that Kremer et al say don't work are precisely the things the Education Commission is budgeting an extra $200 billion in global spending to expand. In contrast, the promising reforms that the authors describe here tend to have two things in common: first, they're often quite cheap, or even free; and second they're politically difficult.
But bad schools still seem to produce good outcomes
While the research literature shows a weak link from money to learning gains, it also shows that education in the developing world has amazingly high returns. This is paradoxical. We know that learning levels in poor countries are abysmally low. In an earlier post, I showed that in half of the fifty or so developing countries where we have data, fewer than 50 percent of women who left school after fifth grade could read a single sentence.
Sending kids to school has huge social returns, particularly for girls. Not only are the wage returns to a year of schooling generally estimated at around 10 percent per annum, but more educated women have fewer children and their children are less likely to die. This is somewhat puzzling if school isn't even teaching them to read.
In a background paper for the Education Commission, my colleagues Mari Oye, Lant Pritchett and I show the relationship between girls' schooling and outcomes like women's fertility and their children's survival is significantly higher where schools produce more learning. The correlation between a year of schooling and child survival is roughly two-thirds higher in countries with the highest versus lowest level of school quality.
Looking at the individual level data, women who completed six years of primary schooling had roughly 0.6 fewer children than women with no schooling, and those children were about 5 percent more likely to be alive. But if you focus only on women who went to school and didn't even learn to read—i.e., women seemingly failed by bad schools—they still had about 0.25 fewer children and their kids were still about 2 percent more likely to be alive.
To be clear, these are nothing more than correlations. You can think of lots of reasons more schooling might be correlated with lower child mortality absent any causal mechanism. But there's growing evidence to suggest the return to schooling is indeed causal, based on natural experiments and policy reforms in places where enrollment has expanded in systems that produce fairly dire learning outcomes.
So maybe pouring more money into business-as-usual and low quality education isn't such a bad investment after all.
Counterfactuals: if we spend more on education, what do we give up?
Fine, perhaps the world needs more bad schools. The world needs lots of things. Is bad education a better bet than, say, HIV drugs or famine relief?
The most intriguing part of Gordon Brown and co.'s pitch is the claim that they can create "new money." The plan is a bit of financial engineering to stretch aid dollars further:
Start with a couple billion dollars of good old-fashioned aid money
Add a couple billion more dollars of loan guarantees from rich countries to Brown's new IFFed fund.
Use that money as collateral to borrow on international capital markets at low rates, thanks to the backing from major donor countries.
Re-lend to poor countries so long as they promise to spend on education.
The basic idea, which is a good one, is to as rich countries unwilling to part with much cash during an age of austerity, to lend their credit rating instead. The problem is, it's not an idea unique to education advocates.
Recently, my colleagues Nancy Birdsall and Ngozi Okonjo-Iweala proposed a new, "Big Bond for Africa" in which rich countries would use their aid budgets to borrow at low rates and lend onward to African countries on concessional terms to pursue whatever development needs they want to prioritize—education or other. And my colleague Michele de Nevers and colleagues, including the former treasurer of the World Bank, Kenneth Lay, have proposed a Tropical Forest Finance Facility (TFFF) that would borrow from rich countries to create essentially a large endowment whose returns would fund forest conservation. There's no escaping the fact these are rival initiatives.
As that old bumper sticker used to say: "It'll be a great day when the schools have all the money they need, and the Air Force has to hold a bake sale to buy a new bomber." If the Trump administration is seriously weighing a new MOAB bomb versus a global fund for education, I'm all for the latter. Sadly, that's not the actual trade-off faced in foreign aid spending conversations in the era of Trump and Brexit.
When aid budgets are tight, advocating for one specific sector like education isn't a question of generosity or a moral crusade, it's essentially just a zero-sum game of earmarking a fixed budget. If that's the game we're playing, education advocates can't duck the conversation about how to generate the biggest learning gains at the lowest cost.
But they will still try. As moderator, my colleague Amanda Glassman opened last week's event with a brief statement about the need for improved efficiency and quality in global education. The panel was unimpressed. When her turn came to comment, Julia Gillard of GPE confessed, "while you were giving your speech about efficiency, Gordon leaned over to me and whispered, 'Yes, but we need more money too.'"
This blog post has been updated to include a correction. The International Commission on Financing Education is led by the UN’s special envoy for education, but it is not a UN commission, as originally stated.
Experts worry letting ordinary citizens manage resource windfalls will lead to populism. We ran a randomized trial in deliberative democracy in Tanzania to find out.
This is the first of a three-part blog series and has a related podcast. Part II will look at cash transfers, and part III at transparency.
Are low-income democracies doomed to squander their natural resource wealth?
Tanzania is one of the poorest democracies in the world. Elections this October will mark 20 years of multiparty democracy, and yet three-fourths of the population still lives under $2 a day.
But recently Tanzania discovered natural gas reserves that are projected to yield anywhere from $15 to about $75 per capita in government revenue each year, depending on global commodity prices and a complex set of policy and investment decisions still pending. While $75 might sound paltry, it’s roughly equal to the median Tanzanian’s total food consumption in a year.
A few months back, we blogged here about an ongoing public opinion poll we were running with REPOA, a Dar es Salaam think tank, asking Tanzanians what they expect from natural gas, and what they would do with this windfall if and when it arrives.
In private conversations, many experts were skeptical that Tanzania’s poor, rural electorate could provide useful input into an often technical policy debate about natural gas. (“Populism!”) We decided to embrace that challenge. We teamed up with Jim Fishkin and co. of Stanford University, who specialize in a process they call “deliberative polling.” We started by running a standard, nationally representative poll. Then we brought together 400 respondents from our sample of 2,000 for a two-day extravaganza in deliberative democracy, including educational videos, small group discussions, and Q&A with experts in economics and in the gas sector.
After everybody went home, we polled them again — along with a control group that wasn’t invited. In sum, we ran a nationally representative, randomized experiment in deliberative democracy. Here’s a snapshot of what we found in terms of (a) what Tanzanians think, and (b) how those views changed as they got more information and spent time deliberating.
Timeline for the experiment:
February 2015: We surveyed 2,000 randomly selected Tanzanians about their knowledge and opinions of natural gas policy.
March 2015: We invited 700 of those respondents (chosen at random again) to “information sessions” where they watched educational videos about natural gas policy and other countries’ experiences.
April 2015: We invited a random 400 of the 700 to a two-day deliberative event, where they debated gas policy in small groups, and asked questions to gas researchers, politicians, and bureaucrats.
May 2015: We polled all 2,000 people again, to see how their opinions had evolved.
Details of the experimental design are available at the American Economic Association’s RCT registry.
Result #1: Tanzanians are responsive to arguments against fuel subsidies
Tanzanians are more market friendly and, well, neoliberal than we expected from a formerly (and still nominally) socialist country. Take the example of fuel subsidies.
Many developing countries spend huge amounts of money on fuel subsidies that are highly regressive and distortionary, benefitting rich people with cars and generators, and encouraging use of dirty fossil fuels. Economists at the IMF and elsewhere have been trying to wean countries off these subsidies for years, but attempts to dismantle them have led to massive protests, as in Nigeria last year. The problem is that where median consumption is as low as in Tanzania, the “right” price for electricity and fuel is likely to hit the poor hard; a progressive solution is cash transfers targeted to the poor to offset higher energy prices — but see the results forthcoming in part II of this post on that.
When we asked Tanzanians point blank whether the recent natural gas discovery should be used to make fuel and electricity cheaper, a strong majority said “yes.” But when this question was posed as a trade-off between selling gas to generate revenue for other purposes, versus using it to make electricity cheaper, a majority chose the former.
That result was true of the entire sample. But the deliberative poll tells us there was more to the change than an appreciation of opportunity costs the tradeoff question evoked. It was also the case that the more people learned, and the more they thought about the issues, the stronger their support was for extracting natural gas, selling it, and using the revenue to pay for Tanzanians’ needs.
The poll shows that 62 percent of Tanzanians in the control group supported selling gas for revenue over electricity subsidies (figure 1); once they had watched the informational video, 65 percent voted for more revenue. The big change came in the group that participated in two days of discussion and deliberation, in which 76 percent supported monetizing the gas, which implies a highly significant treatment effect from deliberation.
So are Tanzanian voters all orthodox economists at heart? Not quite.
Figure 1. Sell gas for revenue vs. use for electricity
Some people think that Tanzanians should pay full price for energy so that the earnings from selling natural gas can be used for roads, schools, clinics, and electricity lines. Other people think the gas should be used mostly to produce electricity so that electricity would be very cheap for all Tanzanians. Where would you place yourself?
Control group:Revenue, 62%Electricity, 33%
Information only:Revenue, 65%Electricity, 30%
Info and deliberation:Revenue, 76%Electricity, 22%
Result #2: Even after deliberation, voters have little interest in saving gas revenues for the long term
The average Tanzanian voter is probably not quite ready to hand over the economic reins to the orthodox solution of saving via a sovereign wealth fund (long viewed as the favored approach by the IMF and the typical central banker in both developing and developed countries). On the one hand, the orthodox solution is far too stingy, especially in poor countries that are growing, where future generations are likely to be richer than the current one anyway. On the other hand, it’s risky too: even a sovereign wealth fund can go astray. Most Tanzanians support the impulse to spend typically associated with natural resource booms. Contrary to “IMF orthodoxy” that enough revenue be saved to cope with volatility of export prices and allow for smooth consumption over time, 72 percent of Tanzanians prefer to spend natural gas revenues sooner rather than later.
That preference for spending didn’t decline at all when confronted with information about boom and bust cycles in other countries, or given the chance to deliberate.
When probed for what they want to spend the gas money on, 61 percent voted for social services such as health and education over the alternative of roads, power, and infrastructure. This preference strengthened with deliberation, rising to a 71 percent majority. This is not to say Tanzania doesn’t need infrastructure investment; the preference for social services probably reflects demand for services that address Tanzanians’ very basic unmet needs for health and education.
Result #3: But there’s a limit to Tanzanians’ appetite for spending: they oppose leveraging gas to borrow overseas
Since 2013, Tanzania has been flirting with the idea of entering the sovereign bond market, with a debut offering of up to $2 billion in new debt currently planned for later this year or 2016. The timing is notable. Regardless of whether Tanzania makes any deliberate attempt to use gas as collateral (which is less likely than it might have been, given Ghana’s recent experience), bond markets will likely build the new gas reserves into their calculus of Tanzania’s credit worthiness.
Interestingly, although Tanzanians are eager for government to raise spending on education and health, a slim majority are unwilling to support using gas as collateral to borrow and spend before the gas revenues arrive. Deliberation did little to change people’s views on debt. In the control group, 51 percent opposed borrowing (compared to 45 percent in favor), while 53 percent of those who participated in deliberation opposed borrowing, compared to just 42 percent in favor.
Process lessons: Letting people talk beats talking at them
One of the broader “meta-” questions we wanted to address in this study was whether deliberation per se really matters. Perhaps voters are just uninformed, and a simple, cheap information campaign could set them straight without the chaotic (and costly) process of facilitating public deliberation.
Results suggest otherwise.
Deliberation had significant impacts on five of the six broad outcomes we measured (figure 2). Participants’ knowledge of natural gas went up, which is not surprising but a little reassuring. They shifted in favor of extracting and selling the gas, rather than using it to subsidize domestic energy, but didn’t change their mind about saving. In addition, deliberation participants became significantly (in statistical terms) more skeptical of cash transfers, and their enthusiasm for transparency and oversight measures increased significantly. (In future posts, we’ll delve deeper into these last two topics.)
In contrast, people who only watched the informational video but weren’t invited to participate in deliberation showed no significant opinion changes. Their objective knowledge increased, but that’s all. From commercialization to saving to transparency issues, learning more about gas didn’t affect their views.
Figure 2. Summary of experimental treatment effects on Tanzanians' knowledge and policy preferences regarding natural gas
Spend on services
Information and deliberation
Note: Each cell shows the impact of information alone or information plus deliberation on the outcome listed in the top row. The symbol (+) denotes a significant positive effect, (–) a significant negative effects, and “x” no significant effect.
Score a point for deliberative democracy, and a strike against the idea of running information campaigns to simply “educate” voters.
In a democracy like Tanzania, choosing how to use natural resources shouldn’t be reserved for technocrats. The fact that people’s carefully considered opinions on gas policy differ significantly from their naïve first reactions demonstrates that ordinary Tanzanians — mostly rural, many illiterate and poor — have the capacity to wrestle with complex policy issues.
Ensuring good governance in the face of a potential resource windfall will require broad public understanding of difficult policy choices to help shield citizens from opportunistic political arguments. This deliberative poll provides some evidence that building that understanding is possible, and a hint about how to get there.
Thanks to our generous funders for this project: the Bill and Melinda Gates Foundation, the International Initiative for Impact Evaluation (3ie), and the International Growth Centre (IGC), as well as the International Development Research Council (IDRC) who supported Mujobu Moyo’s fellowship at CGD. Thanks also to Jennifer Richmond and Faraz Haqqi for help with the analysis here.
One of the best ways to keep up to speed with the research frontier in development is to follow what new PhDs are doing. But who has time to read all those papers? So, for the busy development professional, here’s a list of some of the PhDs that caught our eye in 2015, summarized for your snackable enjoyment in tweet-length format.
Note that this list is not quite random, but very incomplete—gleaned through word of mouth, the excellent series of posts by job market candidates over at the Development Impact blog, and meetings at the AEA conference in Boston this weekend.
My impression is 2015 has yielded a stronger-than-usual crop of job market candidates in development.
One of the mysteries of development economics is why more people in subsistence agriculture don't migrate to cities where incomes are much, much higher. New data suggests one answer: when they move, their incomes may not go up as much as we thought.
Poverty in poor countries is largely a rural phenomenon. The original engine of development in Arthur Lewis's Nobel-winning work in the 1950s was the movement of people out of farming in pursuit of higher urban incomes, and this same movement away from agriculture remains a focus in work on structural transformation today (see CGD work by Peter Timmer and Selvyn Alkus, and others like Margaret MacMillan and Dani Rodrik's here).
The agricultural productivity gap—or the ratio of value-added per worker in other sectors compared to agriculture—is huge. A couple years ago, Doug Gollin, David Lagakos, and Michael Waugh published a paper in the Quarterly Journal of Economics systematically documenting these gaps across a sample of 151 developing countries, and found that on average, value-added per worker in other sectors was roughly three times higher than in agriculture.
Click on citations in the legend to view the cited paper.
Economists see income gaps and begin to tear up at the inefficiencies and arbitrage opportunities. As Gollin et al. wrote, if we take these gaps at face value they suggest that “by reallocating workers out of agriculture, where the value of their marginal product is low, and into other activities, aggregate output would increase even without increasing the amount of inputs employed in production.”
Maybe farmers are just different
Perhaps the most obvious explanation for income differences between farmers and non-farmers is the difference in human capital between workers in each sector. And it's true, education differences are big. But when Gollin et al. try to adjust for these schooling differences—allowing not just for differences in years of schooling, but also for actual learning measured by literacy—the agricultural productivity gap only falls from about 300 percent to about 200 percent. It's still huge.
If the potential income gains are so big, why doesn't everyone move to the city?
Enter a new paper, presented at the American Economic Association conference in Philadelphia last weekend, by Joan Hicks, Marieke Kleemans, Nicholas Li, and Ted Miguel, which attempts to resolve this mystery.
Hicks et al.’s data allows them to go a couple steps further. They measure cognitive ability more carefully than most economic surveys, and find higher-skill farmers select into migration. But perhaps more interestingly, they focus on two long-term longitudinal data sets that track migrants over many years as they move jobs between sectors. This allows them to compare the same worker—with the same education, cognitive skills, and other possibly unmeasurable attributes—in different sectors to estimate the agricultural productivity gap.
What they find is, essentially, nothing.
In Indonesia they find individuals earn about 8 percent more working outside agriculture than from farming, and in Kenya about 6 percent more. When they focus on the rural-urban divide rather than farming versus non-farming, the gap is almost precisely zero in Indonesia and about 17 percent in Kenya. Perhaps 17 percent is not trivial, but it's a very far cry from 200 to 300 percent.
Ruminating on the intellection implications for economists, Dietz Vollrath has an insightful blog post discussing the Hicks et al. paper and the broader literature, provocatively titled “The Return of Peasant Mentality.” As he notes, the modern assumption in development economics is that rural farmers are just like everyone else, i.e., rational maximizing agents, just stuck in a more challenging context. The Hicks et al. evidence suggests instead that they self-selected on measures of cognitive skills. Would we find the same if we measured risk aversion and other psychological attributes? Maybe, as Vollrath speculates, peasants really are different, as an earlier era of development scholars assumed.
So should policymakers turn away from rural-urban migration as an anti-poverty tool? (No.)
The “No Lean Season” initiative in Bangladesh has garnered a lot of attention recently for showing the large welfare benefits from encouraging rural-urban migration. A randomized trial by Gharad Bryan, Shyamal Chowdhury, and Mushfiq Mobarak offered individuals in rural Bangladesh an incentive of about $8.50 to migrate to the city for work during the hungry season. That relatively small incentive induced about 22 percent of people to move temporarily. The result is that family members who stay behind increase consumption by 30 to 35 percent, and eat 550 to 700 more calories per day.
There's a lot of space between 300 percent and zero. Even if the agricultural productivity gap overestimates the gains from moving out of agriculture, the returns to rural-urban migration may still be significant—and well worth promoting through public policy.
Bryan et al.’s RCT in Bangladesh also provides interesting answers to why more people don't migrate spontaneously: they document important roles for risk, subsistence constraints, and for learning about the returns to migration—which induced remigration for years after the treatment incentives are removed once people have gone and seen what they can earn.
Reproduced from Bryan, Chowdhury, and Mobarak (Econometrica 2014)
There's also some evidence that the returns to more permanent (as opposed to the seasonal migration in the Bangladesh study) may be higher in other places.
While Hicks et al. find very little in Kenya and Indonesia, an earlier study in Tanzania by Kathleen Beegle, Joachim De Weerdt, and Stefan Dercon find that rural-urban migrants experience consumption gains of around 30 percent (still a far cry from 300 percent). And while the results are slightly less clean for a variety of data reasons, Alan De Brauw, Valerie Mueller, and Tassew Woldehanna find much, much bigger gains from movement when tracking rural-urban migrants in Ethiopia over many years.
At a bare minimum though, this new evidence from Kenya and Indonesia suggests policymakers should be reluctant to assume that leaving the farm is better for people than they realize, and attempt to coerce movement. Here Hicks et al. invoke Tanzania's disastrous forced villagization policy of the 1970s—hopefully not a policy with many contemporary analogs, but still worth ruling out. And they also highlight that positive selection into migration (i.e., movement of higher skilled people, even on unobservable dimensions) reinforces the tendency for this ladder out of poverty to leave the least fortunate behind, which could be read as a plea not to forget rural development and social protection programs during the structural transformation process.
Should this dampen your enthusiasm for international migration? (Also no.)
While poor farmers in many developing countries are “free,” in the narrowest legal sense, to migrate to urban areas and search for a non-farming job, that's not true for international migrants, who face walls and fences and police demanding papers. With those “frictions,” it makes sense that international income gaps are larger and somewhat more robust.
In one of my favorite CGD papers, my colleagues Michael Clemens and Lant Pritchett together with Claudio Montenegro from the World Bank compare immigrants in the US to observationally identical workers (i.e., same education, age, etc.) in their home countries, and find a lower-bound estimate of an earnings increase of over $13,000 per year in PPP dollars from living and working in America.
The same biases that Hicks et al. identify in rural-urban migration apply internationally—higher-earners select into migration—but once that's accounted for, the returns remain large. Using a lottery of Tongans admitted to New Zealand, David McKenzie, Steven Stillman, and John Gibson show that naive non-experimental estimates of the income gains from international migration overstate the truth by twofold. Nevertheless, they show that randomly selected migrants still experience a 263 percent increase in income (!) one year after migrating.
In sum, there is a risk that “why don’t they just move” becomes the “let them eat cake” of 21st-century development economists. The Hicks et al. paper is perhaps a good reminder to focus on removing the barriers to people’s movement, rather than thinking we know what’s best for them. While the gains to migrants in Kenya and Indonesia appear disappointing, the centrality of structural transformation to poverty reduction in history remains uncontested. It’s not always a simple story though, and more research like this will help us understand that messy process better.
Thanks to Doug Gollin for long and patient answers to my questions, to Michael Clemens for helpful suggestions, and to Divyanshi Wadhwa for research assistance.