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Lant Pritchett is a senior fellow at the Center for Global Development and professor of the practice of international development at Harvard's Kennedy School of Government, where he taught from 2000 to 2004 and from 2007 onward. Before rejoining the Kennedy School in 2007, he was lead socio-economist in the social development group of the South Asia region of the World Bank. He occupied various other positions at the World Bank during his tenure there, beginning in 1988. Pritchett was a team member on a number of prominent World Bank publications including Economic Growth in the 1990s: Learning from a Decade of Reforms (2005); Making Services Work for Poor People (World Development Report 2004); Assessing Aid: What Works, What Doesn't and Why (with David Dollar, 1998); and Infrastructure for Development (World Development Report 1994). He has published two books with Center for Global Development, Let Their People Come (2006) and The Rebirth of Education (2013). Pritchett has published over a hundred articles and papers (with more than 25 co-authors) on a wide range of topics, including state capability, labor mobility, and education, among many others. Originally from Idaho, Pritchett is the father of three children and now lives in an empty nest with his wife of 31 years.
The "arbiter of value" is a key concept in Mark Moore’s RISE working paper: "Creating Efficient, Effective and Just Educational Systems through Multi-Sector Strategies of Reform." This concept, which he brings to the education sector after decades of experience in a variety of public sector organizations (his 1994 book Creating Public Value is a classic in the field), helps understand the industrial organization of basic schooling and why schooling is mostly publicly managed around the world—and even why a failed political coup affects who can teach school in Turkey.
Moore points out that the standard economic approaches to industrial organization cannot explain why the public sector manages schools at all, much less their scale or scope. In most economic approaches the consumer is, if not king, as least treated as a sovereign and the ultimate arbiter of value. Typically if a policy analyst wants to know whether the market for athletic shoes or sunglasses or haircuts or piano lessons or dentistry is working well or not, they take the preferences/wishes/wants of individuals as the sovereign arbiter of what is valuable for them. That is, no one analyzes the industrial organization of haircuts on the presumption there is a uniformly best haircut and judges the market for haircuts on the basis of whether or not everyone got that same best haircut. There is no such thing as a public or social arbiter of value for haircuts—people get (or try to get) the haircut they want and the result is judged on the basis that each person is the best arbiter of value of their own haircut.
Markets can of course have what economists call "market failures" of various types due to the structure of markets (e.g. markets in products with massive economies of scale can end up with natural monopolies that charge prices that are inefficiently high) and of course markets may fail to produce equality (or equity). But outcomes are still normatively judged relative to the consumer as arbiter of value and, in a market economy, the scale and scope of organizations is ultimately determined by how well these choices of organization structure allow organizations to meet consumer needs.
Professor Moore’s key insight about education systems is that the positive explanation of widespread public management of basic education around the world and of the scale and scope of existing public education systems is not that there are the standard "market failures" or even desires for equality or equity (in the usual sense). But rationales for public engagement in schools "take aim at the core normative idea of market economies which is that individuals are the only appropriate arbiters of value in the society" (pg 12). That is, the state as an actor is deeply engaged as an actor in education because the society, as a social public, plays a direct role as arbiter of value in adjudicating the performance of education systems.
That is, education is, in his view, a "public good" not in the sense of the economists’ definition as a good that is non-rival and non-excludable (like, say, national defense) but in the sense that the arbiter of value of what is "good" is the "public." His Table 1 (below) provides an array of what is more and less "public" in two senses. One, to what extent is the "arbiter of value" purely private versus public. Very few modern societies would think to dictate what haircut a person should have or what style of shirt they should wear simply because "we" have preferences the individual doesn’t—hence this is the least public cell (individual arbiter of value, material welfare).
But few people are willing to adopt the view that the sole arbiter of value of their own (or their child’s) education is the person or parent. Most societies regard formal basic education as fundamentally a process of the creation of public value. Some part of this is the production of cognitive skills and some part of the publicness is a sense of concern for the welfare of others and of duties to others. But what "public value" means in this context is deeper and includes some definition of "the public" as the arbiter of value of the beliefs and attitudes and dispositions that are transmitted through the schooling process.
This combination of the role of "the public" as an arbiter of value and the informational structure of skills versus beliefs explains the industrial organization of schooling and why public management dominates basic schooling around the world (chapter 5 of my book The Rebirth of Education argues that beliefs are not justiciable, so there cannot be third party contracting for instruction in beliefs).
The role of government as the "arbiter of value" in the education system influences the scope of the possible in the construction of a learning performance oriented education system. Governments will be more open to "private" schooling depending on what "private" means and how they stand vis a vis the desired socialization of those private schools. In Indonesia the government financially supports private Islamic schools; in other countries madrasas are seen as a security threat. Even if schools are producing demonstrably superior learning of literacy and numeracy, governments will object to schools promoting ideologies that threaten their legitimacy or stability—as the recent events in Turkey, where the government purged its education system of tens of thousands of ministry workers and teachers, clearly illustrate. National governments will be more open to "community" schools or "local" control in part depending on the political and ideological nature of the communities or local governments that control schools.
One important part of achieving education systems coherent about learning is to produce an arbiter of value that values learning as strongly as it values other dimensions of schooling.
Table by Mark Moore
This is one of a series of blog posts from “RISE"—the large-scale education systems research programme supported by the UK’s Department for International Development (DFID) and Australia’s Department of Foreign Affairs and Trade (DFAT). Experts from the Center for Global Development lead RISE’s research team.
The “just right” approach for the mobility of low-skill labor looks to avoid either “too hard”—expecting countries to make legally binding commitments to a global protocol—or “too soft”—no global mechanisms for reducing restrictions on labor mobility. We propose a “bundled” organization that works with existing bilateral labor agreements and partners as part of an organization capable of analysis and advocacy.
Workers with equal intrinsic productivity make higher wages working in a more productive place.
Last year in Science magazine a collection of luminaries (nine authors, two from MIT, two from Yale, etc.) published what many regard as “gold standard” evidence about the impact of a “gold standard” anti-poverty program. The program is a multifaceted program that has six elements: (1) a productive asset transfer, (2) consumption support, (3) technical skills training, (4) high frequency home visits, (5) a savings program, (6) some health education. The program was evaluated in six country sites and was evaluated using a randomized control trial (RCT).
The program produced substantial gains in households’ annual consumption of nondurables in the third year after the productive asset transfer and one year after the end of the program intervention. Given the litany of income generating programs that have failed to have a sustained impact, this news of a sustained (even if only in year 3) gain in household consumption from a targeted anti-poverty program was widely regarded as very good news (see Table 1, column 1, below).
The paper assumes the gains in year 3 will be sustained forever and calculates the NPV (net present value, the sum of all costs and gains, discounted by how far in the future they occur) of the program (in PPP $) at a five percent discount rate (Table 1, column 2). The total gains are impressively large (partly because NPV at 5 percent discount rate multiplies the annual gain by roughly a factor of 20).
Of course this program, being multifaceted, is not cheap. The NPV of costs varies across countries between $1,500 and $6,000 per household. Averaged across the countries besides Honduras (where incomes fell because the “productive asset” transferred was livestock that died), by year 3 the program had spent $4,545 per household and each household’s nondurables consumption was higher in year 3 by $344.
But, with the assumptions (debatable, but we’ll roll with them)—(a) the gains in year 3 are sustained forever and (b) a low discount rate (5 percent)—then the net benefits are substantial and pass a standard benefit/cost test.
Let’s call this debatably but not unreasonably “the best you can do”—that is, if you were looking to augment the incomes of poor people programmatically in situ this intervention has both rigorous evidence across multiple contexts and that evidence suggests program efficacy on its side. (The advocates for “direct cash transfer” could make a case it doesn’t surpass the “index fund”-like benchmark of just giving the households the program costs in cash ($4,500), and they might be right, but just for my argument’s sake let’s assume this program is the gold standard).
Table 1. Rigorous evidence about an anti-poverty program shows (mostly) sustained positive gains—but the total lifetime magnitude is about a third of a year working in the USA versus their own country for a low skill worker.
Year 3 nondurable consumption ITT treatment effect (line 6 of Table 4).
NPV of total benefits per household (line 8 of table 4)
NPV of total costs (line 2 of table 4)
NPV of benefits less costs of multifaceted poverty program
Lower bound of the estimate of the annual wage gain of low-skilled male worker (correcting for selection), PPP
Average (excluding Honduras)
Source: Banerjee et al (Table 4) and Clemens, Montenegro and Pritchett 2016 (column 5).
Now, what is the least “you” (as a rich country citizen) could do for the world’s poor? The least you could do is “let their people come” (at least some of their people and in some modality). This is the least that you can do, as it costs you, the typical rich country citizen, nothing. Since these newly-arrived workers would willingly work at jobs that employers would willingly pay them to do at the prevailing wage, a program could easily be designed that produced positive job possibilities for existing American-born workers and hence zero wage loss for those people already here. (Even the existing migration has near zero loss for almost all ‘indigenous’ workers (Ottavio and Peri) so a program aimed to minimize wage impact could likely do even better). And the public finance implications of labor mobility are roughly whatever the program wants them to be as this is a feature of program design. Rather than costing $4500 per beneficiary this has cost zero to you.
The free lunch is available because of the different place-specific productivities (or TFP if you will) so that workers with equal intrinsic productivity (or “human capital”) make higher wages working in a more productive place even without reducing the TFP available to all other workers. Hence the additional product of the poor person working in a rich country is a net gain in output. The least you can do at the margin for the global poor is to just let them (and only of course those who want to) work in your high productivity environment instead of using the coercion of your nation-state to keep them trapped in the low productivity place they happened to be born in (imagine what you would want if you were born there and they were born here).
Turns out for these six countries the least you can do of letting a worker work in the USA for one year is almost forty times better than the annual gain of the best you can do. The average annual household gain from the “best you can do” is $344 per year. The average wage differential from the “least you can do” is $13,119—38 times higher. Even under the doubly optimistic scenario that these programmatic gains last forever and are discounted at 5 percent, the total lifetime value of the best you can do is less than a fourth the gain from just letting a worker work in a high productivity environment for one year.
Figure 1. The annual gain from a gold standard poverty program is roughly 1/40th the wage differential of low skill workers from these countries working in their country versus the USA
So, I am all for searching for evidence and discovering and then doing the best we can do in terms of in situ poverty programs, but why not also do some of the least we can do and let more of their people come to work in high productivity places?
The Social Progress Index is an effort of the Social Progress Imperative to create a new and better way to compare the human and social development performance of countries. High on their agenda is to not use GDP per capita or other measures of national development, but rather focus on direct measures of human well-being. And it turns out to be a useful measure of the importance of national development. Let me explain.
The Social Progress Index (SPI) has three components:
1. basic human needs,
2. foundations of wellbeing, and
Each of these three components are built of four sub-indicators which are each themselves built up from raw data. For instance, 1) basic human needs has four sub-components:
1.1 nutrition and basic medical care,
1.2 water and sanitation,
1.4 personal safety.
The sub-component 1.2 water and sanitation is based on data on:
1.2.a access to piped water,
1.2.b rural access to improved water source, and
1.2.c access to improved sanitation.
In apparent contrast to the SPI approach, in earlier papers with Michael Woolcock and Matt Andrews, I have argued one definition of national development is a four-fold transformation of nation-states towards (1) a more productive economy, (2) a more responsive polity, (3) a more capable administration, and (4) more equality of treatment of all citizens. With Charles Kenny I argued that high levels of national development were highly correlated with nearly every proposed normative measure of human development and hence drive towards greater national development was typically a powerful source of gains in human development.This new SPI is a fresh chance to assess how strong the connection is between national development and direct measures of human well-being.
Turns out, this new Social Progress Index (SPI) is almost perfectly correlated with national development. If one predicts the Social Progress Index using just three measures: (ln) GDP per capita (productive economy), the POLITY index of autocracy/democracy (responsive polity) and World Governance Indicator of Government Effectiveness (capable administration) the correlation across 128 countries of the actual values of SPI with the predicted values is .961 (an R-Squared of .924). A correlation of .96 in cross-section data is amazingly, astoundingly high. Most people would feel that two measures correlated at .96 are measuring the same thing, not even highly correlated measures of different things. (In fact, often two measures of the same thing—like “years of schooling of the adult population”—don’t have cross-national correlations as high as.96 due to pure measurement error.)
Figure 1 shows the scatter-plot of the actual values of the Social Progress Index and the predicted values (the predicted values are the National Development Index which best predicts SPI).
The boxes are drawn in the graph to emphasize the white space. White space in this graph means something—it is the combination of country experiences in social progress-national development that just don’t happen. The northwest section is white space because no country in the bottom third of national development (the west on NDI) is anywhere near the top third of social progress (north on SPI). Similarly the southeast section is white space because there is no country in the top third of national development (east on NDI) anywhere near the bottom third of social progress (south on SPI). And pretty much all the countries in the middle third by national development are at or near the middle third on social progress.
One can imagine two “pure” development strategies. ‘Due North’ means doing as well as possible on Social Progress while holding national development fixed. ‘Due East’ means going after national development while acquiring only the Social Progress gains expected from the north-east sloping relationship.
It is obvious that for countries with low national development (the bottom third) the Due North strategy of focusing on increasing Social Progress while holding national development fixed has sharply limited prospects. A typical country in the bottom third, like Mozambique, has an actual and predicted SPI of about 46. The regression residuals have a standard error of about 4 so that if Madagascar had SPI performance one standard error better than predicted for its NDI its SPI would be 50. That would move it to ahead of Pakistan and Zimbabwe (at 49) to about the level of Tanzania or Uganda. Alternatively, the 90th percentile of the residuals is 5.75. So if Madagascar were among the 10 percent best SPI performers for its level of NDI it would be at 51.75, reaching Rwanda, but would not achieve the Social Progress of Laos or Bangladesh. Even if Madagascar were the best performer of SPI for its level of national development it would still be in the world’s bottom third on Social Progress.
In contrast, the predicted gains from national development progress are both powerful and unlimited on the upside. So, for instance, if Madagascar improved its GDP per capita, government effectiveness and polity scores by one standard deviation each, its predicted Social Progress would rise to 61.6—ahead of Egypt (60.74) and approaching Morocco (61.9) or China (62.1). And if Madagascar had experienced the growth performance of Korea and had Korea’s GDP per capita that alone would raise the predicted SPI to 68.4—ahead of Thailand or Turkey.
Of course, there is no reason why a country could not have both national development progress and improve its SPI relative to NDI as the same time. For instance, moving ahead in NDI by one standard deviation and having SPI higher for NDI, Madagascar reaches 65.6.
Figure 2: Illustrating various scenarios for Madagascar (a lower third SPI country)
Technical Points: One Big and Two Small
The big point is that correlation is not causation. I am not using statistical procedures (either OLS or other) to resolve whether NDI causes SPI or vice versa. Causality is resolved by theory. The basic theory of the consumer tells us an expansion in consumption possibilities (the budget set) causes higher consumption of all normal goods (budget expansion paths are upward sloping). Higher consumption does not, per se, cause higher income or expand the budget set. Many of the SPI items are consumption items (e.g. piped water) and no one has a causal theory that suggests these are causes (much less the predominant causes) of higher output per worker, GDP or better government. Hence there is a well worked out and empirically validated causal theory of how NDI causes SPI but not (for many/most items in SPI) vice versa. (That said, some SPI items could be argued and we’ll argue that out another day).
Now to the small points. First, the fit is amazingly good given how much measurement error people think there is in measuring concepts like “social progress” or “national development.” Suppose the true relationship was that national development and social progress were perfectly correlated and hence national development predicted social progress exactly, but that each was a concept measured relative to the true concept with a small amount of measurement error—a noise to noise plus signal of 4 percent. Then the observed R-Square would be .924 just from measurement error alone. Second, I did all this empirical work in a few hours and hence have had no time to data mine or functional form mine or goodness of fit mine in any way (for instance, the observation for El Salvador (SLV) on GDPPC just looks way too low to me and hence it looks like a good SPI performer for is level of national development, and if I am right then fixing this would raise the R2; similarly India appears to underperform in part because the WGI measure thinks India has a more effective government than Indonesia, Vietnam or Argentina (which I have my doubts about), and a lower number for India would improve the R2. I just put natural log of PWT8.0 GDPPC (for which the latest data is 2011), the WDI number for Government Effectiveness (and maybe some other “state capability” indicator would give better fit), and the raw POLITY score. With any effort I could crank the R-Squared (a bit) higher but that this is just the “slap in the standard data in the standard way and see what happens” goodness of fit which makes .96 even more amazing.
One of the big debates about efforts like the MDGs or SDGs that drive donor agendas is how much progress can be achieved “programmatically”—by the application of specific projects, programs or policies at existing levels of national development—and how much of progress on human development will require national development (in its multiple dimensions of the four-fold transformation). The very tight association of national development and measures of human development or social progress is an important fact that should inform this debate.
Last week the World Bank announced the process for choosing the next president of the organization. Minutes after midnight on the first day nominations were to be accepted, the US formally nominated the incumbent Jim Kim. Other nominations are possible in what is, allegedly, an “open, merit-based, and transparent” process (criteria agreed upon by the World Bank’s Board in April 2011 and promoted by CGD in 2012 through support for multiple candidates and open meetings with, and questions for, nominated candidates), but which will only be “open” for three weeks.
Here are five women who could ably lead the World Bank.
Sheryl Sandberg. American. COO at Facebook, Vice President of Global Online Sales and Operations at Google, Chief of Staff for the US Treasury Secretary. Sheryl’s first job was at the World Bank, where she went to India on project missions. She has since been engaged in policy in the US, serving as the Chief of Staff to the Secretary of the Treasury, and in the private sector with two successful companies, as a Vice President at Google (and key to Google.org’s engagement in development) and as Chief Operating Officer at Facebook. She is also the founder of LeanIn.org, a non-profit organization to help women succeed. She would bring to the table knowledge of the private sector, legendary management skills, political savvy and deep concern about development and social issues. Although she is American, any other country member of the World Bank could nominate her.
Ngozi Okonjo-Iweala. Nigerian. Minister of Finance of Nigeria, Managing Director of the World Bank. Ngozi has long and deep experience in the World Bank, having been a Managing Director. She has also been Minister of Finance in Nigeria on two occasions (2003-2006, 2011-2015). Given her experience, she understands the issues facing the Bank’s clients—developing country governments—intimately, and the issues facing the World Bank’s ability to deliver to those clients. (Ngozi is currently a CGD Board member and distinguished visiting fellow).
Kristalina Georgieva. Bulgarian. Vice President and Commissioner for Humanitarian Aid and Civil Protection for the European Commission, Vice President and Corporate Secretary for the World Bank. Kristalina was a fantastic manager at the World Bank and rose to the position of Vice President and Corporate Secretary, the position that handles the relationship between the Bank’s management and the Board. She then served in the European Commission and is now Commissioner for Budget and Human Resources. She has proven she can successfully manage in multinational organizations of different types, and was touted as a candidate to be Secretary General of the UN.
Isabel Guerrero. Chilean. Vice President for the South Asia Region at the World Bank, Lecturer at Harvard and MIT. Isabel was consistently an innovative and reform-minded manager at the World Bank as a country director for key clients like Mexico and India. She ended her Bank career as Vice President for South Asia, responsible for a $39 billion portfolio. Since leaving the Bank, she has been teaching at MIT and Harvard Kennedy School and has founded a non-profit, IMAGO, to help grassroots development organizations scale up.
Any one of them would bring fresh perspectives and management skills to a World Bank currently beleaguered with challenges both internal (e.g. see the views of the Staff Association, former World Bank chief spokesperson Tim Callen's letter in the Financial Times, and CNN on the World Bank’s “crisis of leadership”) and external (e.g. the rise of the AIIB, institutional drift, financial viability).
I know all five personally. And I am an introvert. If I can name five female candidates just from my personal acquaintances, imagine how many more qualified and exciting candidates might emerge if there were a search. I don’t know Caroline Anstey, a previous Managing Director of the World Bank, or Indra Nooyi, the PepsiCo CEO from India, for instance, but both have been mentioned. I am confident that soliciting the views of people, groups, communities and governments would produce dozens of qualified women candidates, maybe even better than the five I happen to know.
Or, although all World Bank presidents so far have been male and the organization might benefit from a bit of the gender diversity that it preaches, it might just be that a male is the best candidate this time, too.
But this search and recruitment for the next leader of the World Bank apparently isn’t going to happen. The US Treasury, the largest shareholder, seems anxious to push Jim Kim through a truncated and accelerated reappointment rather than an “open, merit-based, and transparent” global search. It would be good for the World Bank and good for the world—and even good for Jim Kim too, if he prevails—if other countries nominated strong candidates for this important position in development.
Historically the World Bank’s President was nominated by the USA and that person was then approved by the World Bank’s Board (and in a reciprocal agreement Europe nominated the head of the IMF). Now, discussions have begun “over how and whether to reappoint” Jim Yong Kim, when his first term ends next June. I agree with the World Bank Staff Association that we need to be able to have confidence in this process.
In April 2011, in part still smarting from the disastrous experience with Paul Wolfowitz, the World Bank’s Board of Governors unanimously committed to an “open, merit-based and transparent” process for the selection of the President.
In the selection process of 2012 there were for the first time multiple nominees including an African woman, Ngozi Okonjo-Iweala, who many argued was more qualified to be head of a development bank than the American nominee. Just compare the relevant training and work experience of having been an economist, Minister of Finance, and Managing Director of the World Bank (Okonjo-Iweala) to having been a medical doctor, one part of a small NGO, and briefly the president of a small liberal arts college (Kim). But to the disappointment of many, and the surprise of no cynic, the key actual qualification was American nationality and Dr. Kim was appointed to a five year term. (For full transparency, Ngozi Okonjo-Iweala became a CGD distinguished visiting fellow in 2015 and has been a CGD Board member since 2007).
What I heard from many US officials at the time was that the American election in November of 2012 meant Obama could not afford to either “lose” or “give away” a traditionally American position (especially to an African). A common position, privately expressed, was an acknowledgement that this was a weak appointment but the suggestion that “next time” it might be possible to consider American support for a truly “open, merit-based, and transparent” process, one that might even result in the appointment of a non-American.
This time is last time’s next time. To accept the “next time” rationale this time would be to accept that “next time” will never come.
First, this time is a time. There has never been any expectation that World Bank Presidents would be reappointed. Only two of twelve presidents have been reappointed for a second five year term: Robert McNamara and James Wolfensohn. Reappointment, then, is the exception rather than the rule. The argument that the selection process for a reappointment should be different and isn’t a “time” is a non-starter, as it thwarts the very idea of having limited five year terms. Every President would love to declare that a re-election doesn’t need a full blown election, which is precisely why democracy requires that re-elections are just the same as elections.
Second, I am not (now) arguing that Jim Kim should not be reappointed because of poor performance. I am just arguing that the context within which his performance should be assessed is an “open, merit-based and transparent” process for considering who should lead the World Bank this time. Certainly it is possible that one of the candidates to be the next president will be Jim Kim. Assessing his strengths and weaknesses in his current term will be important factors in deciding whether he or some other nominee should be the World Bank’s next leader.
But even if, counter-factually, there were broad and deep consensus among all stakeholders that Jim Kim had done a fantastic job in his first term, this time would still be last time’s next time and it still would be necessary to go through a full-blown selection process in order to ensure the legitimacy of the selection, even if the result of that process is a re-appointment. Given the World Bank Staff Association’s recent open letter, it is clear there is not a broad and deep consensus on Jim Kim’s performance, which makes the legitimacy of the process even more important.
Third, this is not saying that the USA should not take its responsibility as major shareholder seriously. But as a major shareholder, it should honor its April 2011 commitment to an open, merit-based and transparent process. Announcing (privately or publicly) support for the re-appointment of Jim Kim even before the process has gotten underway is a trifecta: it undermines "open," undermines "merit-based" and undermines "transparent."
There have been many voices out there for many years saying that reserving the leadership of the World Bank exclusively for an American increasingly undermines the legitimacy of the leader and the organization (see Raghuram Rajan here in 2008 and Michaels Clemens and Kremer here in 2016). This doesn’t mean that an American might not emerge as the best candidate, but that this choice would only have legitimacy if it emerges from a process all agree was a vigorous and open global search for the best leader that considered more than the history of only American males.
This time is next time, so this time of selection of the leader of the World Bank should be the best time.
New data from Round 2 of the OECD PIAAC (Organisation for Economic Co-operation and Development Programme for International Assessment of Adult Competencies) show the typical Indonesian adult (25-65 years old) living in Jakarta, who has completed tertiary education, has lower literacy proficiency than the typical Greek or Dane who completed only lower secondary school. Additionally, the Jakartan with tertiary education had lower literacy proficiency than adults in every other OECD country who only completed upper secondary schooling.
Figure 1: Jakartans with tertiary education have the same literacy proficiency on the OECD PIAAC assessment as Danes who have less than upper secondary schooling.
The results from Jakarta are shocking and reinforce all of the empirical premises behind RISE.
This is the kind of finding about education in the developing world that drives the RISE research agenda. The RISE focus on getting systems of basic education to pivot to learning is based on empirical observations about the current status of schooling.
Learning in many developing countries is very far behind the rich countries. The assessment of literacy in proficiency was based on a six level scale from “below level 1” to “level 5”. A person at level 1 (who would score between 176 and 226 points) should have the following skills:
Most of the tasks at this level require the respondent to read relatively short digital or print continuous, non-continuous, or mixed texts to locate a single piece of information that is identical to or synonymous with the information given in the question or directive. Some tasks, such as those involving non-continuous texts, may require the respondent to enter personal information onto a document. Little, if any, competing information is present. Some tasks may require simple cycling through more than one piece of information. Knowledge and skill in recognising basic vocabulary determining the meaning of sentences, and reading paragraphs of text is expected.
In Jakarta, 69 percent are at or below level 1 in literacy—32 percent below level 1 and 37 percent just at level 1. In contrast, only 4.5 percent of the OECD population is below level 1. In numeracy, 60.4 percent of the Jakartan population is at or below level 1. Even more shockingly, 42.3 percent of Jakartans who had tertiary education were at level 1 or below on literacy proficiency (compared to only 7 percent of those with tertiary in the OECD).
In literacy, the typical (median) Jakartan scored 200.5. In the USA, not known for high performance schooling and with wide social inequalities, the person at the 10th percentile scored 204.2. In high performing, low inequality countries like Finland, Japan, Slovak Republic, and Korea, the 5th percentile adult did almost as well as the typical Jakartan.
There are social inequalities within country, but even the highly schooled in Indonesia are far behind global standards. There is, rightly, a great deal of attention paid to the fact that marginalized and disadvantaged groups (first generation learners, ethnic minorities, women) are lagging behind. And this is true in Indonesia, but in thinking about the education system, it is important to keep in mind this doesn’t mean the disadvantaged are getting a bad education and the advantaged in Jakarta a good education—it means the disadvantaged are getting a terrible education (essentially none at all) and the advantaged a bad (or mediocre at best) education.
For instance, adults who had at least one parent who completed tertiary schooling scored 63 points higher than another adult who had neither parent complete upper secondary schooling. Existing social inequalities are definitely perpetuated by the current system. But the “advantaged” in Jakarta (those with a highly educated parent) scored 258 which is lower than the “disadvantaged” adult (those with neither parent having attained upper secondary education) in 9 of the 28 OECD countries.
Hence, reducing inequality by bringing everyone in Jakarta up to the Jakarta mean would leave all Jakartans massively disadvantaged globally.
The “high performing” adults in Indonesia—the 90th percentile—score at 263 which is lower than the OECD median adult (271) and, strikingly, is lower than the average OECD adult with just an upper secondary education (264).
While societies want the average level of education for all to be high, they also need highly skilled leaders in their politics, social and civic life, and their economy. The problem with learning performance is not just that 69 percent in Jakarta are at level 1, but also that there is essentially no one at level 5 and only .5 percent at level 4. Level 4 or 5 literacy proficiency is attained by about 1 in 10 adults in the OECD, but only 1 in 200 in Jakarta. Even among those with tertiary education, only 2 percent are at level 4 or 5 (compared to 21 percent of those in OECD with tertiary).
The ability of expansion in enrollment/attainment to close the gap is small. Indonesia, like most countries, has made massive progress in expanding enrollment. Comparing the older to younger adults shows that 57.2 percent of older adults 55-65 (yikes, my age!) had less than upper secondary schooling, but that has fallen to only 29.6 percent today. This progress in expanding attainment in schooling, combined with the low levels of learning, imply that little aggregate progress can be made just by expanding access.
A simple counter-factual: Suppose everyone in Jakarta had upper secondary education—instead of 29 percent of the cohort (25-34) that ended with just lower secondary—but the average learning level of those with secondary remained the same. Then the typical adult score would increase from 201 to 211—up by just 10 points. That is great; but the gap between Jakarta and the median OECD is 70 points—201 to 271—so bringing universal completion of upper secondary would eliminate only 1/7th of the gap.
This is where it gets shocking. Even if everyone in Jakarta had tertiary education this would only eliminate half the skills gap with the OECD. This is because the average adult with tertiary education scores only 234 and the typical (median) adult in the OECD is at 271. Put another way, even the totally unrealistic proposal of universal tertiary schooling (even in the OECD only 41 percent of adults have tertiary) would only get Indonesia half way to the OECD at current levels of learning.
More of the same expansion of only schooling attainment cannot get countries like Indonesia to global competencies. There needs to be more learning at each level of schooling.
The pace of progress is frustratingly slow. While we cannot track progress over time, a survey of adults can compare performance by age. Not surprisingly, given the massive increases in attainment and the potential deterioration of skills with age, the youth (25-34) in the OECD score much better in literacy than do the older cohorts—a gap of 29 points. What is striking is that the difference between older and younger cohorts is smaller in Indonesia—only 17.3 points separate the older cohort (55-65) and those 30 years younger (25-34), in spite of the massive progress in expanding schooling attainment.
Figure 2: There is progress between the older and younger generations in Jakarta—but this progress is slow—slower than in the OECD (the gap is bigger for the young).
Source: OECD Skills Matter: Further Results, 2016. Table A3.5
Suppose we take 17.3 points every 30 years as the crude rate of progress. For the young cohort of Jakarta (205) to reach the current level of the young cohort of the OECD (279), it will take roughly:
This post is not critical of Indonesia, in fact, Indonesia is to be applauded for its participation in PIAAC (and other international assessments like PISA) whereas many other countries shy away from creating the data that allows these comparisons. Indonesia’s scores on learning assessments of students are actually pretty typical of developing countries, if anything, actually slightly above average. If other countries around Indonesia’s (Jakarta’s) student performance level on international assessments (like PISA or TIMSS) were to participate in this adult survey, one suspects the results would be similar to those of Jakarta. For instance, Chile, an OECD country with five times Indonesia’s per capita income in PPP averaged only 220.1. This new data from Jakarta, while strictly only about Jakarta, is almost certainly illustrating a widespread problem.
The new PIAAC results about adult literacy and numeracy skills are another strong piece of evidence revealing the need for developing country education systems to pivot to learning. Indonesia cannot wait 128 years to close the skill gap. It needs to accelerate learning progress now.
This is one of a series of blog posts from “RISE"–the large-scale education systems research programme supported by the UK’s Department for International Development (DFID) and Australia’s Department of Foreign Affairs and Trade (DFAT). Experts from the Center for Global Development lead RISE’s research team.
Motivated by our experience in designing a particular social program, skill set signaling for new entrants to the labor market in Peru, we articulate the need for, and explore the empirical consequences of, alternative learning approaches to the design of development projects. We suggest that project, program, and policy design must depend on more robust learning strategies than the attempt to directly apply results from ”systematic reviews” or move prematurely to an RCT.
Lant Pritchett and Amanda Beatty argue that many education systems are attempting to push children through curricular material faster than their teachers can teach it and their students can learn it. Students fall behind and eventually stop learning. The authors provide a formal model of this phenomenon and provide empirical evidence on its implications.
A savvy and prominent Indian policy maker once said to me (roughly):;
You guys from the World Bank say you want to help the government of India with our development agenda but then all you want to talk about is poverty, poverty, poverty. Let me point out two things. First, India is a democracy and hence to be the government at all we have to have 51 percent of the votes and we don’t have that many poor voters. Second, once we are the government of India we are the government of all Indians, not just the poor ones, so our agenda has to reflect the aspirations of all Indians. So either you are really helping us with our development agenda or you are just pushing yours.
The World Bank has decided to make this problem – the divergence of the organization’s rhetoric on “extreme poverty” and their clients’ desire for support in their national development agendas – even worse. They have announced that their goal is to “eradicate extreme poverty” (while only “monitoring” the income of the poorest 40 percent in each country—but with no goal). This new goal is meant to sound like a bold and ambitious target but is exactly the opposite. This is a dramatic retreat by the World Bank, a shift from an organization that supports national development agendas towards an organization that just promotes cost-effective charity work. This new focus is wildly at odds with what leaders of developing countries and their citizens want, care about, and want global support in accomplishing. This new goal is like a World Series champion team announcing their goal for the next seasion is not scoring runs or winning games but just bunting well.
The problem is that the exceptionally penurious definition of “extreme” poverty concocted by international elites as a global target includes too few people to be the basis for a development agenda for most of the world. Table 1 shows the 20 most populous countries in the world (which includes all developing countries with more than 60 million people). This includes 4.9 billion of the world’s 7 billion people. If your agenda isn’t relevant in these places, it just isn’t really a global development agenda.
Ask: “in how many of these places does ‘extreme poverty’ include the median voter?” More concretely, in how many of these places is the headcount poverty rate above 50 percent of the population? The answer is just two: the Democratic Republic of Congo (ex-Zaire) and Nigeria.
Now ask: “how many of these places have substantial development agendas for which they might legitimately expect some support (if not grants ) from a global organization like the World Bank?” To answer this we look at the ratio of each country to the best country in the world on three indicators of national development: output per capita, democratic performance, and governance (e.g. control of corruption, rule of law, government effectiveness). To make the comparison easier we scale each so that the best is 100 and the worst zero. A National Development Index (NDI) is the (geometric) mean of these three (Kenny and Pritchett 2013)
Certainly Pakistan is a country that no one would characterize as adequately developed. It scores just 18 on the National Development Index (NDI). Yet the poverty head count measure shows only 21 percent of the population in extreme poverty. So in democratic Pakistan “eradicating extreme poverty” is an agenda that includes only 1 in 5 voters. Ethiopia has extremely low development in every respect and yet less than one in three Ethiopians is poor enough included in the World Bank’s new goal. While Indonesia, Vietnam, and the Philippines have been doing well in some regards, they are far from free of development challenges, and yet less than one in five of their citizens is in “extreme poverty.”
As my friend in India points out, while India does well on measures of democracy, it has only 6 percent of the output per person of the world’s highest, and faces significant challenges with governance. Yet the headcount poverty is less than a third of the population. Is the median voter in India really so well off that helping them improve their lives and livelihoods cannot be included in the World Bank’s goal?
China’s economic performance has been staggering over the last few decades so its “extreme poverty” rate is only 11.8 percent. That certainly means China needs no financial support from development agencies but is China—with only 16 percent of the per capita income of the world’s highest and substantial challenges in governance – now completely off the development agenda except for its bottom-most 11 percent?
In some countries at the top of the world’s priorities there are severe development issues and yet almost no extreme poverty. Certainly Egypt has massive challenges in development—yet its “extreme poverty” head count is only 1.7 percent. Despite Iran’s high income from oil, its development index score is only on a par with Indonesia and India—but extreme poverty cannot anchor a development agenda there as only 1.5 percent are in extreme poverty.
Obviously, countries like the USA (86), Germany (82) and Japan (74) are developed, and a development agenda need not apply to them to be globally relevant. But countries like Mexico (42) and Turkey (45), which have have not been recipients of “aid” for many years, still maintain a productive engagement with the World Bank but their “extreme poverty” is already lower than the 2030 target of “eradication.”
Eradicating extreme poverty has to be just one among many development goals. It cannot be the sole or primary goal of a development organization that wishes to remain engaged productively with national governments. You cannot set organizational goals that ignore the more than half the population of of all but two of the world’s 20 most populated countries and still remain a global force for progress in development.
The unfolding of “thesis, antithesis, synthesis” about the use of randomized control trials (RCTs) as a tool in improving development policies and practices has reached the “synthesis” stage. A new paper in the 3ie working paper series “Evaluations with Impact” by Shah, Wang, Fraker and Gastfriend (hereafter IDinsight team and, full disclosure, three of which were students of mine) (2015) does an excellent job both in laying out the debate and in articulating a newly emerging conventional wisdom in which quite similar new approaches to the use of randomization have been proposed by a number of actors.
In this debate the “thesis” was that the increased use of randomized controlled trials (RCTs) as a technique in impact evaluation (usually promoted as “independent” impact evaluation) would make important contributions to human well-being in the field of development. Variants of this thesis were promoted by academics at newly formed research hubs like JPAL and IPA, by practitioners at newly formed organizations like 3ie, and in at least parts of major multi-lateral and bi-lateral organizations (DIME in the World Bank, DIV in USAID, DFID, IDB, etc.), and a few governments (e.g. Mexico’s unit in the Social group).
In 1996 circumstances led me to be the World Bank “task manager” of record of an early RCT by Michael Kremer and Paul Glewwe. Hence I was an early non-adopter of this new technique because I could see it was leading research away from, not towards, key needed insights about the process of improving development projects and programs. For about 20 years I have been part of the antithesis. I have always maintained that RCTs got one claim right—using randomization in assignment was the best way to identify the causal impacts of particular interventions—but got everything else about the use and impact of RCTs on development policy and practice wrong. I will just list (with links to various papers and blogs) the four claims in the “causal chain” or “theory of change” or “logframe” from doing more RCTs to better development practice to increased human well-being that I argue against.
Claims that RCTs of impact evaluation could (even in principle) produce useful codifiable knowledge with external validity about development policies and practices were wrong (paper and paper).
Claims about the political economy of policy adoption and scaling were wrong (paper).
Claims about how organizations learn and change practices on the basis of evidence were wrong (paper and paper).
The claim that RCTs would or could address issues of first order importance in development was wrong (blog).
I will be the first to admit that my arguments (and even those of other more senior and respected development economists like Agnus Deaton (paper and paper)) had the effectiveness of a pea-shooter against a tank. Apparently nothing could prevent a hype cycle in RCTs. One reason critics had no impact was that a very effective rejoinder to early critiques was not counter-argument per se but the Alka-Seltzer commercial refrain: “Try it, you’ll like it.” Initially there were so few RCTs the argument that we couldn’t possibly know their impacts until we tried them was persuasive.
Another reason critics had little impact was that agnostics rarely alter the course of faith based movements; heretics do.
The importance of the IDinsight team paper is that neither of these powerful counter-objections apply.
The IDinsight team (2015) points to 2,500 RCTs in development (the latest version of Eva Vivalt’s meta-analysis paper draws on 647 papers). OK, so we’ve tried it, for going on two decades now, and at massive scale. Where are we, and now what?
Perhaps even more importantly, the IDinsight team authors are children of the revolution, not older agnostics who saw the rise of RCTs from the outside (and can be accused of “not getting it” or defensiveness about the past).
On my reading, a key insight of the IDinsight team is to distinguish Knowledge Focused Evaluation from Decision Focused Evaluation – two uses of the technique of randomization (the first three columns of Table 1 are from their paper). That is, rather than a mostly pointless debate about the value of “randomization” as a technique per se, the interesting questions are the who, what, how, and why of randomization. Their point is that “knowledge focused” evaluations were seen as an arm of research and about building a generalizable (and hence externally valid) body of knowledge about “what works.” In contrast, “decision focused” evaluations are the use of randomization to make decisions relevant to the implementing organization.
Table 1: Characteristics of Knowledge-Focused, Decision-Focused, and Accountability-Focused Evaluations
Knowledge Focused Evaluation
Decision Focused Evaluation
Evaluator (with input from implementer)
Implementer (with input from evaluator)
Funder (e.g. MoF, donor)
Outside technical support
Embedded policy advisor
Time to release findings
Depends on funder
? (Properly only incremental cost vs other evaluation methods)
Lower diversity with emphasis on more robust methods and downstream outcomes
Higher diversity with greater emphasis on proximate outcomes and practical considerations
Emphasis on impact/outcome on beneficiary justification
Significant concerns due to intention to apply findings across contexts
Reduced concern since action is intended to occur in implementer’s context
Definition of success
Contribution to development theory, contribution to high level policy debates, scale-up of generalizable interventions
Informed decision and at-scale action, or program discontinuation, in implementer’s context.
Does evaluation provider funder with assessment of impact of implementer.
Source: IDinsight team (2015), table 5 for first two columns (Knowledge Focused Evaluation and Decision Focused Evaluation), my own for AFE.
IDinsight team assess (based on evidence and interviews with key actors) the “weak links in the Knowledge Focused Evaluation theory of change” and examine why there is now a general perception the randomista revolution has had rather more impact on PhD training and journal articles than on development practice.
They argue a better approach is not to give up on randomization per se but rather to move to a strategic mix of Knowledge Focused Evaluations and Decision Focused Evaluations. The IDinsight team argue that Decision Focused Evaluations should be (pg 22):
Demand driven—conducted only when an implementer desires evidence to inform future action
Tailored—generating decision-relevant evidence within the temporal, budgetary, operational, and political constraints of the implementer,
Embedded—within the implementer’s operation and decision making structures; and
Cost-effective—aiming for a positive social return on investment (with the evaluation considered as the ‘investment’).
To their distinction of Knowledge Focused Evaluation and Decision Focused Evaluation I would add a third type (in the fourth column of Table 1), the Accountability Focused Evaluation, which is building randomization into the ex post evaluations that are routinely required of donor funded projects and programs (and which are done in some government programs). The World Bank (as one example of a multi-lateral organization I have some knowledge of) has always, as a matter of policy, done an ex-post evaluation of every project that rated the success or failure of the project. That evaluation was reviewed by a quasi-autonomous arm of the organization (in that it answered only to the Board, not Management) which also rated the project. This department (the once Operations Evaluation Department now the Independent Evaluation Group) also did/does both more in-depth evaluations of selected projects and thematic evaluations (e.g. of all “directed credit” or “integrated rural development” projects). Part of the rhetoric around the advent of RCTs was that the existing project and program evaluation mechanisms were too weak as an accountability device both because they were not truly “independent” of the implementer/funder organization and that, without a valid counter-factual the causal impact could not be rigorously assessed. Hence it was “win-win” as doing evaluation with RCTs could be both better at accountability (AFE) and knowledge (Knowledge Focused Evaluation).
It is easy to see (even without my paper on the topic) that one cannot have Knowledge Focused Evaluation, Decision Focused Evaluation and Accountability Focused Evaluation all at the same time as one cannot both be embedded in the implementing organization and providing real time feedback on how to do what the organization wants to do better and an “independent” evaluator of whether what the organization does is worth doing and hence at risk of losing funding. It is also easy to see (again, without my paper) that organizations will generally resist Accountability Focused Evaluation if they can and hence will resist Knowledge Focused Evaluation if bundled with AFE. On the other hand, organizations are more likely to want to use Decision Focused Evaluation.
The IDinsight team (2015) are articulating an emerging new “synthesis” based on the “lessons of experience” of the new evaluation organizations. Because the arguments for it are roughly right, something like the shift from Knowledge Focused Evaluation to Decision Focused Evaluation and the rise of organizations like IDinsight itself working directly with development organizations is, with different names and different acronyms, happening nearly everywhere.
The “It’s all about MeE” is an organizational learning approach that combines monitoring (M), experiential learning (“little e”-like Decision Focused Evaluation) to “crawl the design space” and (at some stage), impact Evaluation (like Knowledge Focused Evaluation). This is an integral part of the Problem Driven Iterative Adaptation (PDIA) approach to building state capability (BSC) at CID, of which I am a participant, and the broader Doing Development Differently (DDD) network.
The Evidence for Policy Design (EPoD) group, also at CID at Harvard proposes SMART policy design that emphasizes embeddedness with the implementing organization and rapid, evidence-based feedback loops.
Howard White (until recently the executive director of 3ie) at a recent conference on evaluation in Berlin discussed the difference between “Accountability” evaluations and “Learning” evaluations. He made something very much Accountability vs Knowledge Focused Evaluation vs Decision Focused Evaluation distinction saying: “Second generation questions don’t ask ‘does it work’ but design questions about ‘how can it work better?’ He noted that the biggest uptake in the use of randomization was by the private sector where organizations like Yahoo! do “impact evaluations” that take one hour. These are clearly Decision Focused Evaluation not Knowledge Focused Evaluation uses of randomization.
The new Global Innovation Fund has an approach of “pilot, test, scale” which recognizes that a “pilot” phase in which there is “field testing” of innovations (the Decision Focused Evaluation stage) that must precede the “test” (or Knowledge Focused Evaluation stage). And perhaps the “pilot” and “test” needs to be adapted for each context as “pilot-test” in one context and “scale” in another is demonstrably poor practice.
The IDinsight team points in a useful and productive direction to take techniques of randomization into the fabric of the detailed decision making and tacit learning that organizations need to do in the course of responding to problems and scaling up robust approaches to solving those problems.
It is love not science that means never having to say you are sorry.
I would like to point out that it is love not science that means never having to say you are sorry. What was “learned from experience” that leads to a shift in emphasis from Accountability Focused Evaluation and Knowledge Focused Evaluation to Decision Focused Evaluation (or its similar variants like MeE or SMART policy design or many others) was that (a) there were few development problems for which there was a logistically implementable solution based on codifiable knowledge for which an RCT (or even a small set of RCTs) could generate external valid results, so, for instance, the medicine analogy often appealed to in support of the value of RCTs was almost wholly misleading, (b) the model that organizational learning could effectively happen through Knowledge Focused Evaluation and Accountability Focused Evaluation was deeply flawed and (c) the political economy of policy change and program design that assumed that effectiveness was primarily limited by availability of rigorous evidence was also misguided. Hmm.
The momentum seems to be building for a goal to “eradicate poverty by 2030.” Reducing poverty is a noble goal, one to which I fully subscribe. But the “eradicate poverty” campaign is actually only focused on “extreme” poverty which is an absurdly low and completely arbitrary definition of the poverty. I am for eradicating poverty, but real poverty, as experienced by billions of people in the world, not on the extremist vision of “dollar a day” poverty. There is no poverty line at a dollar a day (now really $1.25 in purchasing power parity currency units). A dollar a day global poverty line exists nowhere except in the minds of elite technocrats, advocates, and donors.
What would a “line” look like? There is line at 0 degrees Celsius. Below that line water is solid and above that line water is liquid. As water crosses the freezing point it changes states—it freezes. Similarly a person can be said to “have a fever” because we know that the normal, healthy human temperature is 37 degrees Celsius (98.6 F) and temperatures much above that are a reliable symptom of certain infections.
In contrast, as people cross the “dollar a day” poverty line…absolutely nothing special happens to anyone anywhere.
There is no line at dollar a day in objective indicators of well-being. The wide availability of multi-module household data sets allows us to construct graphs showing the relationship between non-money indicators of household and child well-being--like malnutrition or health or child enrollment or access to sanitation or access to electricity--and household economic status for dozens and dozens of countries. As people get more prosperous they are nearly always better off by nearly every indicator—but there is no line. There is no discontinuity or sharp non-linearity around a dollar a day poverty line in any country for any indicator.
There is no line at dollar a day subjectively assessed well-being. In the entire research on subjective well-being or happiness no one has ever argued people are happier or feel better about life because they are “not poor” by the dollar a day standard (any more than any other gain in income). No person in history has ever celebrated crossing the dollar a day threshold—any more than any other income gain—there is no line.
There is no line at dollar a day in income dynamics. One might think a poverty line exists that demarcates a “poverty trap” and that people “in poverty” have a hard time escaping poverty—except that it doesn’t. All of the available evidence that tracks households over time finds enormous fluidity across the dollar a day threshold--and no evidence that it is harder to increase incomes from just below than just above—there is no line.
The epigraph to Marshall’s Principle of Economics was natura non facit saltum—nature doesn’t jump. The idea that people in a state or condition called “poverty” below dollar a day and are discontinuously not in poverty above that line--and that this matters in any way to the reality of people’s lives--belies this common sense and beggars belief. And rightly so, it is demonstrably false.
There is now a polite phrase for “just making stuff up”—it is called “social construction.” All will agree that the dollar a day line doesn’t exist in any objective sense--like the freezing point of water or having a fever-- but rather that poverty itself and the dollar a day construal of poverty are a “social construct.”
But what is the “society” in which a dollar a day poverty line is a “construct”? Poverty as a social construct varies widely across people (not surprisingly, richer people think it takes more money to not be poor), across communities (which when allowed to construct poverty definitions do not converge either on per capita income or consumption expenditures as the exclusive standard nor on dollar a day as a line), and across countries (only very few countries have adopted anything like “dollar a day” as their own national poverty standard). Dollar a day is not a social construct that people commonly have that is being described by outside experts, dollar a day was invented by technocrats.
Dollar a day as a global poverty line is a recent, dating only from the 1990s, created and propagated and treated as a relevant reality only by a narrow group of technocrats, mostly working in and around donor agencies. The “society” of which dollar a day global poverty is a construct is the tiny cosmopolitan “thousand dollar a day” crowd of elites.
No developed country accepts a standard of poverty for their citizens of less than ten dollars a day—and most have poverty definitions much higher than that. Work in Latin America by Nora Lustig and Nancy Birdsall and others suggest the “new poor” in Latin America are those below ten dollars a day as well. So why does the thousand dollar a day crowd try to project an imaginary (and extreme) poverty line into a world in which it doesn’t exist—even as a social construct? The supposedly benign rationale is that this “increases focus on poverty” is completely circular. “Focusing” on reducing dollar a day poverty is only good if focus on those below the line is good which is good if there is a line—but there is no line.
By definition “focus” on one thing blurs another. There are roughly 5 billion people on the planet who are poor by any OECD standard of poverty—and, as I have argued elsewhere--by a reasonable global standard of poverty--but who, the dollar a day definition of poverty says at not poor. An increased “focus” on the dollar a day poor reduces attention to the legitimate and pressing need to improve the lives of these 5 billion. A goal for “eradicating extreme poverty” that excludes the concerns and needs of 5 billion people from the development agenda in favor of the elitist agenda of dollar a day is not progress.
With the rich countries feeling burdened by their own economic problems and fiscally strapped, re-defining development down to a lower, less ambitious, standard will certainly find powerful allies. But the one-two punch of redefining “development” as “poverty reduction” and then redefining “poverty” as “dollar a day” completely changes the historical nature of development as goals for the creation of prosperous, democratic, capable and equal nation-states into the limited and penurious concept of development as just cost-effective charity work.
In the surrealistic Mulholland Drive the director David Lynch plays with our sense of reality. In the ironically named Club Silencio an emcee loudly insists “No hay banda, There is no band” even as a band is heard—and then seen--playing music—but these are then revealed as an illusion. No matter how much rhetoric you hear about “eradicating extreme poverty by 2030” remember: No hay linea, there is no line.
Are your wages determined by what you know, or where you are? This paper estimates how the wages of workers in 42 developing countries would change if the same people could work in the United States. It uses a rich new database on over two million workers around the world. A worker from the median country would earn about 2.7 times as much in the US as at home. This means that (1) for many countries, the wage gaps caused by barriers to movement across international borders are among the largest known forms of wage discrimination; (2) these gaps represent one of the largest remaining price distortions in any global market; and (3) simply allowing labor mobility can reduce a given household’s poverty to a much greater degree than most known antipoverty interventions inside developing countries.
Large international differences in the price of labor can be sustained by differences between workers, or by natural and policy barriers to worker mobility. We use migrant selection theory and evidence to place lower bounds on the ad valorem equivalent of labor mobility barriers to the United States. Natural and policy barriers may each create annual global losses of trillions of dollars.
“Change blindness” is a phenomenon well documented by psychologists and brain scientists. Due to some very deep, hard wired, features about how our vision works we often fail to see even large changes. See how many viewings it takes before you to see the change in this video of a merry-go-round (you’ll need to click on ‘change blindness demos’ and open the .avi file).
The source of change blindness (including in the merry-go-round video) is that the change often happens slowly and in the background. Our neural apparatus for vision is deeply hard-wired to see changes that happen fast and to the foreground (what we are focusing on). So too is our political apparatus.
Europe is experiencing not one, but three population related crises. Two are fast and one is slow.
Europe’s “refugee crisis” and, in the aftermath of the tragic events in Paris, the “terrorism crisis” are fast moving and in the foreground and hence getting lots of attention. However Europe’s slow moving and inexorable ageing crisis is not getting attention. All three are related, as Europe actually needs millions of migrants a year to mitigate its ageing crisis (a fact documented below). As Jack Goldstone puts it, Europe thinks it has an immigration problem but what it really has is an integration problem.
The short-run refugee crisis is the result of tragic, unmitigated disaster for Syria, but actually could be a boon to Europe if leaders and populations come to grips with the long-run ageing crisis. Europe needs to either find a way to accept massive flows of migrants in ways that are socially, politically and culturally acceptable or resign itself to chronic fiscal and economic weakness and falling living standards.
That won’t be easy, but if Europe is not going to take these migrants now, then when? If not these people, who?
Europe is ageing out.
In the UN “zero migration” variant population projections by 2050, the labor force aged (15-64) population shrinks by 62 million in core Europe (consisting of the UN’s regions of Western, Northern, and Southern Europe but excluding Eastern). This is a massive fall—like losing roughly all of present day Italy or France, or losing the metropolitan areas of Dallas, Houston, Philadelphia, Washington DC, Miami, Atlanta, Boston, San Francisco, Phoenix, Detroit, Seattle, and Minneapolis-St. Paul combined.
The labor force decline—which is the result of voluntary choices about reproduction—is not, in and of itself, a crisis. There is not a population crisis but an ageing crisis: while the labor force aged population shrinks by 62 million, the population of Europe aged 65 and above rises by 45 million. Never has the combination of fertility changes and improvements in longevity produced such dramatic inversions of the demographic pyramid so that the aged so dramatically exceed the young. For example, in Italy today there are 5.7 million young people (aged 15-24) and about 6.8 million over 75. By 2050 the forecast is 4.4 million youth and 12.6 million over 75—that is 2.8 people older than 75 for every one youth.
While the issues of ageing get really complex with tax rates, replacement ratios, retirement ages, health care costs, labor force participation rates of men and women and more in the mix, the initial arithmetic is pretty simple. The current ratio of labor force aged to retirement aged (LF/R) is 3.3 to 1—there are only 3.3 work aged people (not all of whom are in the labor force) to sustain the pensions, health insurance, and elder care of every single retiree. Even at that ratio the combined social protection programs that Europe is justly famous for—generous pensions, universal health care—require very high tax rates on workers to sustain.
Europe is going to be 212 million people short.
In the UN “zero migration” scenario, the LF/R ratio falls to 1.7 (shown below). It is hard to imagine sustaining anything like Europe’s current social programs with that ratio of potential workers to retirees.
To keep the LF/R (labor force to retiree ratio) constant, each one million new retirement aged people requires 3.3 million new people of labor force age. So at constant labor force participation rates, 45 million more retired aged would require about 150 million additional people of labor force age.
But there aren’t going to be 150 million more workforce aged people, there are going to be 62 million fewer, a gap of 212 million people. The projected labor force aged population in 2050 is 227 million, but would have to be 439 million to sustain the projected 132 million Europeans over 65 at the current ratios.
As recently as 1980, when European social programs were reaching their current structure, the European ratio was 5.3. At 3.3, the LF/R ratio is already far lower than had ever been observed in the world before these recent declines in Europe and Japan. Outside of Europe and Japan, the lowest current ratio is Canada’s at 4.21. It is not even clear that a ratio as low as 3.3 is “sustainable,” as countries have only reached these levels very recently. So perhaps something like current social protection schemes might be possible at ratios lower than 3.3, but that is not obviously so. The lowest in Europe today is Italy at 2.85, with Greece close behind (not exactly inspiring confidence that these are fiscally sustainable. Meanwhile, Japan, hardly a model of recent economic success or coping with ageing, fell from 3.3 just ten years ago to 2.3 today, so this has not been sustained and hence cannot be taken as “sustainable”).
Some simple hypothetical calculations (not “predictions” or “forecasts”) illustrate the magnitude of the next increase in the labor force aged population from migration to maintain LF/R ratios. To keep ratios constant (at their current historic lows) would require 6 million additional labor force aged population a year. Even if one assumes Japan’s current LF/R ratio of 2.3, roughly the lowest ever observed in modern human history, could sustain anything like Europe’s current social programs, Europe would still need 2.2 million more labor force aged people per year.
‘Fear itself is politically fearsome.’
The UNHCR estimated that 800,000 potential refugees would reach Europe via the Mediterranean in 2015 and 2016. That this comes in a huge spurt driven by conflict has made the “refugee crisis” massively visible and led to widespread discussions of how to “solve” it. On top of this is the added challenge of addressing the crisis with the rising fear in Europe and the USA that the refugee and security challenges are linked. And, whether these fears are rationally grounded or not, fear itself is politically fearsome.
It is worth keeping in mind that 800,000 a year is less than a fifth of the total that would be needed not to solve, but just to mitigate the ageing crisis. The question for Europe is how to accommodate the flows it needs while maintaining the other conditions it wants as well.
Like all of us, Europeans want lots of different things. They want people to be able to decide how many children to have, they want to retire at a reasonable age, they want quality health care, they want to have something left over after their tax bill and they want to preserve their national and sub-national identities and cultures. But, as the LSE trained Mick Jagger put it: “You can’t always get what you want.” European democracies want freedom of child bearing and fertility, generous social protection, reasonable taxes and low rates of migration. But even in a democracy, you cannot vote yourself a cake and vote you get to eat it, too.
The ageing problem is so severe it will take a little bit of everything: people will be encouraged to have more children with fiscal and non-fiscal inducements, retirement will be postponed (“live longer, work longer”), benefits will get squeezed, taxes will go up—and after all that Europe will likely still need substantial flows of migrants to maintain its citizens’ way of life. To paraphrase Mick Jagger again, let’s hope Europe gets what it needs.
So, while the refugee crisis is sudden, it is, like many crises, also an opportunity in disguise. If Europe doesn’t want to accept people now, then when? If not these people, then who? If not as refugees, then how? Now is the time for Europe to learn to let their people come not just because it is the right thing to do, but because they need them. Whether or not Europe can recognize and solve its integration crisis is crucial to solving both the fast-moving and attention-getting short run challenges of refugees and security but also the longer run, much bigger, ageing crisis.
The UN Millennium Development Goals (MDGs) seek to ensure that all children complete primary school by 2015. But school completion rates don't tell us how much--or how little--the kids actually learn. This new working paper co-authored by CGD non-resident fellow Lant Pritchett shows that even in countries that meet the primary school completion goal, most students fall short of minimum competency in reading, writing and arithmetic. The answer, the authors argue, is a Millennium Learning Goal that measures how much students actually know. Learn more
The welfare of the poor turns in large measure not only on technocratic development "policies", but the effective delivery of key public services, core elements of which require thousands of face-to-face discretionary transactions ("practices") by service providers. This paper presents eight current proposals for improving service delivery, on the basis of a principal-agent model of incentives that explores how these various proposals change flows of resources, information, decision-making, delivery mechanisms, and accountability.
Poverty reduction is now, and quite properly should remain, the primary objective of the World Bank. But, when the World Bank dreams of a world free of poverty—what should it be dreaming? I argue in this essay that the dream should be a bold one, that treats citizens of all nations equally in defining poverty, and that sets a high standard for what eliminating poverty will mean for human well-being.
Ghost towns dot the West of the United States. These cities boomed for a period and then, for various reasons, fell into a process of decline and have shrunk to a small fraction of their former population. Are there ghost countries—countries that, if there were population mobility, would only have a very small fraction of their current population? This paper carries out four empirical illustrations of the potential magnitude of the "ghost country" problem by showing that the "desired population" of any given geographic region varies substantially.
This paper is part of the Copenhagen Consensus process, which aims to assess and evaluate the opportunities available to address the ten largest challenges facing the world. One of these ten challenges is the “lack of education.” This paper provides an analytical framework to evaluate the various options that can be used to address this issue.