A new paper by Robert Allen, “Absolute Poverty: When Necessity Displaces Desire” (American Economic Review, December 2017), has proposed and implemented a method of measuring global poverty. Allen advocates this as an alternative to the World Bank’s longstanding method using Purchasing Power Parity (PPP) rates across countries in trying to assure that the international poverty line has constant purchasing power globally.
At the core of Allen’s method is the use of Linear Programming (LP) to set a least-cost diet for attaining stipulated nutrients, following George Stigler (“The Cost of Subsistence,” Journal of Farm Economics, 1945). Allen estimates country-specific least-cost diets anchored to globally-constant nutritional requirements with an allowance for spending on his stipulated bundle of non-food goods. Allen does not present his method as a complement to the Bank’s, but as superior. He claims that his method yields substantially high global poverty counts than the World Bank’s $1.90 a day line.
My comment on Allen’s paper, “An interesting step backwards,” argues that his proposed method is the resurrection of a method famously rejected long ago, including by Stigler, because it produces poverty lines of little social relevance. From the point of view of the history of thought on poverty, it is interesting to see what this old method delivers with new data for the developing world.
On a close inspection of his results and on doing some extra calculations, I find that his claim that the global absolute poverty count is much higher than currently thought, based on the Bank’s $1.90 line, is no longer true when one uses nutritional requirements that would seem to accord more closely with practice in low-income countries. This gives a much lower poverty count than the Bank’s $1.90 line. And the trend over time is virtually identical. I also argue that there is an urban bias in the prices Allen uses for valuation, which raises his counts relative to the national lines in low-income countries that have been used to determine the $1.90 line.
The comment argues that Stigler was right, and the method Allen proposes should still be rejected, based on Allen’s own findings. PPP’s remain essential for global poverty measurement.
Partly in response to concerns about chronic undernutrition, there is an expanding effort at social protection in developing countries and this effort is typically focused on transfers targeted to poor families (as discussed in Chapter 10 of The Economics of Poverty). These policies regularly assume that targeting poor households suffices in reaching poor individuals. Is that right?
A new paper, “Are poor individuals mainly found in poor households?“, with Cait Brown and Dominique van de Walle, studies the effectiveness of these household targeting efforts when one is trying to reach poor individuals, as identified by the nutritional status of women and children. Our answers will surprise many readers.
As expected, there is a “wealth gradient” in that poorer families are more likely to include undernourished women and children. But other factors are at work, including intra-household inequality and shared risks from the health environment. In our comprehensive assessment for 30 countries in sub-Saharan Africa we find that undernourished women and children are spread quite widely across the household wealth and consumption distributions.
Strikingly we find that roughly three-quarters of underweight women and undernourished children are not found in the poorest 20% of households, and around half are not found in the poorest 40%. Countries with higher undernutrition tend to have higher shares of undernourished individuals in non-poor households.
It is clear from our results that to have any hope of reaching undernourished women and children in Africa, policy interventions will either require much more individualized intra-household information or they will need to be nearly-universal in coverage.
One often hears that high incomes are simply the reward for greater effort, and poverty reflects laziness. Here, for example, is what Ben Stein has said (In The American Spectator, April 4. 2014): “There is an immense amount of income inequality here [in the US] and everywhere. I am not sure why that is a bad thing. Some people will just be better students, harder working, more clever, more ruthless than other people”. Stein goes on to claim that long-term poverty reflects “poor work habits”.
Is there any truth to the claim that there is less inequality and poverty than we think, once one allows for the differing degrees of work effort that people make? My paper “Inequality and poverty when effort matters,” argues that it is far from obvious that allowing for heterogeneity in effort implies less inequality or poverty.
If one takes seriously the idea that effort comes at a cost to welfare then it is clear that prevailing approaches are not using a valid monetary measure of welfare. While this much is obvious enough, the heterogeneity in effort must also be brought into the picture. Then the distributional outcome is far from obvious. It may be granted that average effort rises with income, but there is also a variance in effort at given income. The implications for measuring inequality and poverty stem from both the vertical differences (in how mean effort varies with income) and the horizontal differences (in how effort varies at given income).
It is unclear on a priori grounds what effect adjusting for effort in a welfare-consistent way will have on standard measures. There are both empirical and conceptual issues. The implications for measurement of taking effort seriously depend crucially on the behavioral responses to unequal opportunities, and not all of those responses are readily observable. Measures with a clearer welfare-economic interpretation call for data on efforts, for which existing surveys are limited to a subset of the dimensions of effort.
The paper provides illustrative calculations for American working adults without disabilities. A positive income gradient in labor supply is evident in the data. This gradient accounts for very little of the income gap between the poorest third (say) and the overall mean. The fact that poorer workers work less appears to contribute rather little to overall inequality in observed incomes. However, the considerable heterogeneity in effort at given incomes imparts a large horizontal element to inequality measures that adjust for effort consistently with behavior.
On calculating distributions of welfare-consistent equivalent incomes to allow for this heterogeneity, I find higher measures of inequality than for observed (unadjusted) incomes. Contrary to the common view, the prevailing practice of ignoring differences in effort understates inequality.
It can be acknowledged, however, that some of the apparent heterogeneity in leisure preferences seen in the data is deceptive given likely rationing and measurement errors. When I use predicted leisure shares based on covariates I find a modest drop in the measured levels of inequality on adjusting for effort. Adjusting for effort does not appear to make much difference in the structure of inequality, as indicated by regressions using a set of circumstances related to gender, age, race and place of birth.
The implications for measures of poverty depend crucially on whether one sets the poverty line consistently with the welfare metric. If one does not do so, then poverty rates are lower using equivalent incomes although this essentially vanishes when one smooths the data. However, these comparisons are arguably deceptive since one is not setting the poverty line consistently with how one is assessing welfare. To correct for this, one needs to include a normative allowance for leisure as a basic need in setting the poverty line.
On introducing even a modest allowance for leisure as a basic need (valued at a low wage rate) I finds higher poverty rates when one adjusts for effort. If half the average amount of leisure taken by American adults is deemed to be a basic need then the poverty rate based on equivalent incomes, adjusted for effort, is nearly twice as high as that based on observed incomes.
In short: allowing for effort in a way that is broadly consistent with behavior does not attenuate the disparities suggested by standard data sources on income inequality or poverty. Indeed, one can reasonably argue the opposite: there is even more inequality and poverty than current measures suggest.
These two graphs are depicting the same information is different ways. Both relate to the distribution of consumption per person in the developing world. Both are from the same data source, using the methods described in my paper with Shaohua Chen, “Developing world is poorer than we thought” (though I have updated the numbers to 2011).
Graph (a) in the left gives the poverty incidence curves (PICs) for 1981 and 2011. Each point on the vertical axis gives the proportion of the population of the developing world living below the point on the horizontal axis. The lower panel in (a) gives the vertical difference between the two (2011-1981). We see a decline in the poverty rate for all possible poverty lines. This also implies that virtually all sensible poverty measures will show a reduction in poverty over this 30 year period. (These claims use well known results from the litertature; see Chapter 5 of EOP).
Graph (b) gives instead the horizontal difference at each percentile. This is the absolute growth incidence curve (GIC). (The concept of the GIC comes from another paper with Shaohua Chen, “Measuring pro-poor growth“). Consistent with graph (a) we see a gain at all levels. But what is also striking in (b) is how much smaller the absolute gain is at the bottom (for the poorest percentile on the left). This is a case of rising absolute inequality.
I have come to realize recently that many people who have learnt that absolute poverty measures are falling in the developing world, and are naturally pleased to know that, are surprised at graph (b), and some are even shocked. But they are just two ways of representing the same information.
Yes, poverty is falling (graph a). But it is coming with rising absolute inequality (graph b).
There is much talk these days about the idea of a basic income. This is an untargeted transfer, set at the same level for all recipients within a domain. It is variously called ‘citizenship income’, ‘universal basic income’ or (my favourite) ‘basic income guarantee’ (BIG). The debate for and against the BIG idea spans the globe. A BIG is often contrasted with a set of targeted transfers that would fill all the poverty gaps.
Without necessarily advocating a BIG, this article points out that some of the arguments we hear against the idea are straw men.
Critics of the BIG idea argue that it costs far too much to be considered seriously. Some BIG proposals have had scary price tags, but that misses the point. Most countries (including many poor countries) already spend public money on poverty reduction. If the same resources would be better spent fighting poverty using a BIG, then that’s what should be done. We can ask this question for any given level of the basic income.
India, for example, has subsidies that benefit the non-poor more than the poor. Cutting these and replacing them with some form of BIG would almost certainly have greater impact on poverty. More remarkably, a BIG might well be more cost-effective against poverty than India’s main programmes targeted to the poor, namely the Public Distribution System (PDS) (for subsidised food) and the Mahatma Gandhi National Rural Employment Guarantee Act (MNREGA), a workfare programme that aims to be self-targeted to poor people. In research with colleagues I have found that a small basic income in Bihar, one of India’s poorest states, would have more impact on local poverty than the labour earnings from MNREGA (Murgai et al. 2016).
A key element of the case for a BIG is how it would be financed. Progressive income taxes are an option in rich countries, and then the BIG is formally equivalent to Friedman’s (1962) negative income tax. When financed by reduced expenditures on other public programmes, the benefits and costs of those programmes should be considered. That could make a BIG proposal look worse if it was introduced at the expense of (say) better quality schooling, or healthcare for poor people. Fine, let’s look at that carefully. But we should not write off a BIG at the outset as too expensive. A BIG should be among the options to be considered by any developing country in a package of anti-poverty policies (Ravallion 2016).
The favourite calculation here is simple. Just measure each poor person’s poverty gap – the distances below the poverty line for all the poor – and make handouts accordingly. Voila, no more poverty! A budget to cover the aggregate poverty gap will almost always be much smaller than the cost of a BIG.
This calculation is deceptive, for three main reasons. The first is about incentives. Perfect targeting like this generates 100% marginal tax rates on poor people because if a poor family’s income increased by US$1, its benefit level would fall by US$1. We would have created a policy-induced poverty trap. If implemented, once everyone realised this was the case, the cost would undoubtedly rise until it was much higher than the initial aggregate poverty gap.
The second reason concerns the information constraints on targeting. These can be severe, especially in poor countries with weak administrative capacity. Policymakers in practice have access to a limited subset of the information needed to reliably establish how poor someone was. The household data that could be reliably used for this purpose are limited, and we know even less about living conditions at the individual level. We are a long way from perfect targeting in practice.
Third, when the budget is free to vary, finer targeting may well undermine public support (notably from the middle class) for anti-poverty policies (Sen 1995). The poor end up with a larger share of a smaller pie, with ambiguous gains.
A simple anti-poverty policy assigns transfers based on observed categories, such as location, household size, or landholding in rural areas. More sophisticated versions use a proxy means test in which a statistical model is calibrated using a limited set of readily observed household characteristics in a sample survey. Data on these characteristics are used to predict who is poor in the population as a whole.
These methods have often disappointed in practice. Even with a fixed budget sufficient to eliminate poverty with perfect information, optimally designed transfers as a function of the information that is available do not come close to eliminating poverty. This has been shown in recent research for countries in Africa (Brown et al. 2016). Even with the aggregate poverty gap as the budget, three-quarters of the poverty would remain.
There are further questions here: what does it mean to target ‘well enough’, and well enough for whom? Experience and research point out the horizontal inequities of targeted social policies in practice. At the community level, these policies may appear opaque or almost random. People can see that equally poor families are being treated differently by these targeting tools. Some get help but others do not. The obvious unfairness of this situation can generate social conflict and undermine well-intentioned social policies. There can be gains from tapping into community-based information, but there are risks there too (Mansuri and Rao 2012).
Whether the information available to policymakers is reliable and sufficient for the task of targeting is an open question. It should be examined carefully in each setting, taking account of the social tensions that can be generated by bad targeting. But we should also not presume that there are large gains for poor people from exploiting the available information in practice.
This one is surprising, because a BIG would probably be the most non-distortionary policy imaginable. Nobody would be able to do anything to change how much they got. Granted, there would probably be a positive income effect on demand for leisure. As with all transfers, however, one must also consider impacts on other relevant constraints facing poor families, including uninsured risk and credit constraints. Transfers can help relax these constraints on employment. There is evidence that South Africa’s ‘older person’s grant’ did this for recipient families (Ardington et al. 2009).
Incentive effects should not be ignored. Some targeted policies create high marginal tax rates for poor people. This is a bad idea. But incentive problems are often exaggerated, and may not be serious in practice (Banerjee et al. 2017).
Undeniably, there are tradeoffs. When thinking about a BIG, however, we could define ‘income’ more broadly than just cash income. A full income concept could include imputed values for services in kind, such as publicly provided health insurance and schooling. A BIG discussion might emphasise these ‘non-cash’ dimensions of welfare.
The composition of the basic (full) income package would then be a policy choice. That choice would be important, and it would never be easy. There are concerns about paternalism that overrides the preferences of poor people. But the key point is that non-cash benefits should be factored into any characterisation of what, exactly, is guaranteed. So this is not a valid case against a BIG.
I doubt if there will ever be a truly universal BIG in which everyone gets a fixed lump-sum. More likely we will see some form of a ‘State-contingent’ basic income, meaning that the transfer would be uniform within some category of households or type of people. It might be defined by where people live, their age, or employment status. This might not achieve the vision of a full citizenship income that advocates have wanted, but it can also help reduce the concerns about fine targeting.
But, wait a minute – a State-contingent basic income is nothing more than a targeted policy based on categorical poverty indicators, and so we have come full circle. In practice, the lines between basic income and targeted assistance are blurred. The core policy issues are how many states or groups we identify for different transfers, with uniform treatment within the group, and how we handle transitions between states, noting the incentive problems this creates.
Whether we see universal BIGs in future or not, the current policy debates will hopefully lead us to be less reliant on finely targeted social policies that focus on avoiding leakage to the ‘non-poor’ yet rarely have the kind of information needed to do this credibly, are often based on an incomplete accounting of the costs incurred (not least by poor people), and end up excluding many who are in real need. In combination with more reliable personal identification systems, a retreat from the fine-targeting fetish we often see today toward more transparent forms of universality promises more socially inclusive, politically effective and more cost-effective anti-poverty policies, not least in poor countries (Ravallion 2017).
A universal basic income at some decent level is not yet feasible in many countries. But more universality in service provision and social protection – and less fine targeting – would create better social policies.
This article first appeared on VoxDev: http://voxdev.org/topic/institutions-political-economy/straw-men-debate-basic-income-versus-targeting.
Ardington, Cally, Anne Case and Victoria Hosegood (2009), “Labor Supply Responses to Large Social Transfers: Longitudinal Evidence from South Africa”, American Economic Journal: Applied Economics, 1(1):22-48. Available here.
Banerjee, A, R Hanna, G Kreindler and B Olken (2017), ‘Debunking the Stereotype of the Lazy Welfare Recipient: Evidence from Cash Transfer Programs Worldwide’, mimeo, Massachusetts Institute of Technology.
Brown, C, M Ravallion and D van de Walle (2016), ‘A Poor Means Test? Econometric Targeting in Africa’, NBER (national Bureau of Economic Research) Working Paper 22919.
Friedman, M (1962), Capital and Freedom, University of Chicago Press, Chicago.
Mansuri, G and V Rao (2012), Localizing Development: Does Participation Work?, World Bank, Washington DC.
Murgai, Rinku, Martin Ravallion and Dominique van de Walle (2016), “Is Workfare Cost Effective against Poverty in a Poor Labor-Surplus Economy?”, World Bank Economic Review, 30(3):413-445.
Ravallion, M (2016), The Economics of Poverty: History, Measurement and Policy, Oxford University Press, Oxford and New York.
Ravallion, M (2017), Interventions against Poverty in Poor Places, World Institute of Development Economics (in press), Helsinki.
Sen, A (1995), “The Political Economy of Targeting”, in D van de Walle and K Nead (eds.), Public Spending and the Poor, Johns Hopkins University Press.
There seems to be much enthusiasm today for efforts to improve access to information about poor people’s rights and entitlements. In a much debated recent example, Facebook’s “Free Basics” platform provides free access to a selected slice of the internet (including, of course, Facebook). In arguing for Free Basics, Mark Zuckerberg says that “everyone … deserves access to the tools and information that can help them to achieve all those other public services, and all their fundamental social and economic rights.” I think we would all agree; less obvious is whether Free Basics will help do that. Critics argue that it is a “walled garden” approach—indeed, a threat to net neutrality. There have been proposals for other options using subsidized internet data packs, as in the proposal for India made recently by Nandan Nilekani and Viral Shah.
Neither the Facebook proposal nor that of Nilekani and Shah includes explicit pro-poor targeting. Is that needed? It might be argued that it is likely to be the poor who are least connected now, so the gains will automatically be greater for them. Against this, those who have the hardware and are currently connected are less likely to be poor and will probably be in the best position to benefit from these initiatives, including enjoying any new subsidies.
Before we decide on Free Basics versus subsidized data packs, or some other option, we should see how well information spreads at present. There is already lots of “public information” out there relevant to poor people in India, and there are various dissemination channels. While there may well be frictions for knowledge diffusion, associated with illiteracy and caste-based social exclusion, how important are they? Are the poor still sufficiently well connected socially to tap into the flow of knowledge, or does poverty come with social exclusion, including exclusion from information about programs designed to help poor people? Is a more explicitly targeted approach called for? An understanding of the sources of current inequality in information access is a pre-condition for thinking seriously about policies.
Using edutainment to learn about knowledge diffusion
The use of entertaining media—“edutainment” as Eliana La Ferrara dubs it in her paper “Mass Media and Social Change”—is attracting attention as a means of both directly informing poor people of their rights and entitlements and changing preferences and how existing communities operate. Such interventions can also provide a lens on existing processes of knowledge diffusion.
In a new paper, “Social Frictions to Knowledge Diffusion,” with Arthur Alik-Lagrange, I have used an edutainment intervention to identify key aspects of how knowledge is shared within villages in rural Bihar (a relatively poor state of about 100 million people in the Northeast of India). We show how an information campaign can throw light on the extent to which information is shared within villages. The campaign we studied used an entertaining fictional movie to teach people their rights under India’s National Rural Employment Guarantee Act (NREGA) (a motivating example used by Nilekani and Shah). NREGA created a justiciable “right-to-work” for all rural households in India. The most direct and obvious way NREGA tries to reduce poverty is by providing extra employment in rural areas on demand. This requires an explicit effort to empower poor people, who must take deliberate unilateral actions to demand work on the scheme from local officials.
In a book I wrote with Puja Dutta, Rinku Murgai and Dominique van de Walle, “Right to Work?” it was found that most men and three-quarters of women had heard about NREGA, but most were unaware of their rights and entitlements under the scheme. Given that about half the adults in rural Bihar are illiterate, a movie made sense as an information intervention. The setting and movie are described in Right to Work? and you can see the movie (audio in Hindi) on my website, economicsandpoverty.com.
The movie was tailored to Bihar’s specific context. Professional actors performed in an entertaining and emotionally engaging story-based plot whose purpose was to provide information on how the scheme works, who can participate and how to go about participating. The story line was centered on a temporary migrant worker returning to his village from the city to see his wife and baby daughter. He learns that there is BREGS work available in the village, even though it is the lean season, so he can stay there with his family and friends rather than return to the city to find work. It was intended that the audience would identify strongly with the central characters.
With the aim of promoting better knowledge about NREGA in this setting, the movie was randomly assigned to sampled villages, with a control group not receiving the movie. Knowledge about NREGA was assessed in both treatment and control villages. Residents were encouraged to watch the movie, but not (of course) compelled to do so. Some watched it and some did not. The new paper studies the impacts on knowledge, and the channel of that impact—notably whether it was purely through the direct effect of watching the movie or whether it was through knowledge sharing within villages.
There is a methodological challenge here, namely how to identify the knowledge gains (if any) for those in the assigned villages who did not actually watch the movie. We postulate that there is a latent process of knowledge diffusion among households within the village. An individual’s knowledge reflects both this process and a latent individual effect representing the individual’s “connectedness.” The latter is assumed to be time invariant, as it depends on long-standing networks of association between people, reflecting how each individual fits within the village social structure including caste positions and the ability of that individual to process the new information. Having two observations within each household allows us to obtain an estimate that is robust to latent heterogeneity in household factors. By exploiting the differences over time, our method is also robust to latent individual effects.
Socially differentiated knowledge spillovers
We find robust evidence of spillover effects, which account for about one third of the average impact of the movie on knowledge about NREGA’s key wage and employment provisions. While knowledge sharing is evident, poorer people, by various criteria, appear to be less well connected, and so benefit less from the spillover effect—relying more on direct exposure to the intervention.
Our key finding is that the knowledge diffusion process is far weaker for disadvantaged groups, defined in terms of caste, landholding, literacy, or consumption poverty. For poor people, it appears that the direct effect of watching the movie is all that really matters to learning about NREGA. There is also some indication of negative spillover effects for illiterate and landless households, suggesting the strategic spread of misinformation.
More effective pro-poor knowledge diffusion does not, of course, assure an effective public response on the service supply side. In another paper, “Empowering Poor People through Public Information?,” it was shown that the (direct and indirect) knowledge gains from the movie did rather little to assure a more responsive program. Right to Work? documents a number of specific, fixable, deficiencies in the responsiveness of NREGA in Bihar to the needs of poor people.
These research findings confirm that efforts are needed to improve the access of poor people to knowledge about public services that can help them, and that edutainment can work. The research also suggests that such efforts need to be directly targeted to poor groups, rather than relying on prevailing processes of knowledge diffusion, which may simply reflect, and reinforce, existing inequities.
(First posted on the World Bank’s Development Impact blog; 1/19/2016.)
The Rusty Radiator Awards for 2015 have been announced, in time for Christmas. These awards have been going for a few years. Not heard about them? From their website: “The Rusty Radiator Award goes to the fundraising video with the worst use of stereotypes. This kind of portrayal is not only unfair to the persons portrayed in the campaign, but also hinders long-term development and the fight against poverty.”
The “winner” this year is Band Aid 30. Apparently this was based on votes. The jury’s report: “Band Aid 30 contributed to the spread of misinformation and stereotypes of Africa as a country filled with misery and diseases. The Ebola outbreak occurred in three countries in West Africa. We resent the idea of a bunch of celebrities joining forces together, giving the impression that they are saving Africa from Ebola. Furthermore, they just make it so much more about themselves! Highly offensive and awful in every way possible. Celebrities cannot stop Ebola.”
Really? In principle I agree that stereotypes about poverty should be avoided. While the aid business has been somewhat prone to them, they do not help the cause of better development knowledge, including more and better aid. But is this particular award justified? The scene at the beginning of the Band Aid 30 clip a poor emaciated Ebola victim in her blood-soaked bed being carried away by health workers in their protective suits is shocking, especially when followed by a slew of cameras taking shots of the celebrity singers arriving for the recording of the clip. Not exactly good taste. But this is not one of those videos of well-healed celebrity musicians handing out food to poor African children, which irk me too (as in the clip for another Rust Radiator award winner). Nor did I get the impression that the Band Aid celebrities were claiming that they were saving Africa from Ebola. They might fairly be accused of bad taste, but I don’t see how they are promoting stereotypes that hinder long-term development and the fight against poverty.
There is a counter-argument. The Ebola crisis awakened many in the rich world to the appalling state of the health systems in West Africa (as in much of the world) AND that this longstanding development problem had spillover effects globally. This needs to be better known, and the Band Aid clip will help. The world is poorly equipped for handling pandemics, and some shock treatments like this may well help mobilize collective action to address the root causes. Showing such a scene at the beginning of the celebrity’s song is a little off-putting, but I think the Rusty Radiator Award is exaggerated in this case, and there is a counter-argument on positive benefits. Excess sensitivity does not help either dear Radiator folk.
In marked contrast, the winner of the Golden Radiator Award is Zalissa’s Choice from Burkina Faso. (From the website: “The Golden Radiator Award goes to the fundraising video using creativity and creating engagement. This kind of charity campaign is stepping outside of the common way with using stereotypes.”) Zalissa’s Choice is an uplifting choice for this award! I recommend it.
This article does not try to summarize the book, but rather to focus on the main lessons that emerge on the challenges in thinking and action about poverty going forward.
A transition in thinking: In reviewing the history of thought on poverty I was struck by how much mainstream thinking has changed over the last 200 years. We see a transition in the literature and policy debates between two radically different views of poverty. Early on, there was little reason to think that poor people had the potential to be anything other than poor; poverty would inevitably persist. Prominent thinkers even argued that poverty was necessary for economic advancement, since without it, who would farm the land, work the factories and staff the armies? Avoiding hunger was the necessary incentive for doing work.
This way of thinking still left a role for policy in providing a degree of protection from shocks, which helped assure social stability in the wake of crises. The protection motive for antipoverty policy goes back well over 2,000 years in both Western and Eastern thought. While the need for social protection was well understood in principle among the elites, their support tended to fade in normal times, and often needed to be re-established in new crises. However, mass poverty was largely taken for granted. Beyond short-term palliatives to address shocks, there was little or no perceived scope for public effort to permanently reduce poverty. Promotional antipoverty policies made little sense to those in power.
In the second, modern, view, poverty is not only seen as a social ill that can be avoided through public action, but doing so is seen as perfectly consistent with a robust growing economy. Indeed, the right antipoverty policies are expected to contribute to that growth by removing material constraints on the freedom of individuals to pursue their own economic interests. Poverty was no longer seen as some inevitable, even natural, condition, but as something that could and should be eliminated.
The state came to be given a prominent role in helping to assure that all individuals have access to the essential material conditions for their own personal fulfillment—arguably the most important requirement for equity, but also the key to breaking out of poverty traps. Antipoverty policy came to be seen as a matter of both promotion and protection. Along with rising real wages and (hence) savings by poor people, public education systems, sound health systems and reasonably well functioning financial markets were deemed to be crucial elements for the next generation to escape poverty, for good.
This transition in thinking came with much struggle. Many people came to protest, join community or religious groups, labor and civil-rights movements, or political coalitions of one sort or another to lobby for governmental action to help fight chronic poverty in multiple dimensions. The resistance to their efforts was often strong, and a great many brave people sacrificed their liberty and even their lives in those struggles over centuries.
Successful promotion policies took time to evolve, and were invariably mediated by politics. However, in due course, a self-reinforcing cycle emerged in the successful countries to help assure a sustained and (over time) more rapid escape from absolute poverty. Success in implementing partial antipoverty policies often fostered success in securing broader coverage and implementing new initiatives.
Progress has been slow in some periods and the cycle has been broken at times, with many setbacks. The history of thinking and action on poverty provides ample illustrations of the fragility of the progress that has been seen. Each major step forward was followed by a backlash in thinking and policymaking. We still see this today, with poor people being blamed for their poverty and even criminalized. But, as we strive to support efforts against poverty going forward, it is important to acknowledge the progress that has been made.
Progress against poverty: The new millennium still has roughly one billion people in the world living in poverty by the standards of what “poverty” typically means in the poorest countries. While the data are far from ideal, as best can be determined, there were also about one billion people in the world living in such poverty 200 years ago. The difference is that then they accounted for about four out of five people in the world, while today they account for one in five.
Since 2000 the developing world has been reducing the extreme poverty rate at about one percentage point per year—over three times the long term annual rate for the world as a whole over the last 200 years. If this progress can be maintained then the developing world will eliminate at least the most extreme forms of absolute poverty in a much shorter timespan than did today’s rich world. We should not, however, presume that the developing world’s new pace of progress against poverty will automatically be sustained. That will require good policies, and a measure of good luck.
Challenges to eliminating extreme poverty: There are two distinct paths going forward. The low-case, “pessimistic,” trajectory entails that the developing world outside China regresses back to the relatively slow progress of the 1980s and 1990s. On this path, it would take another 50 years or more to lift one billion people out of poverty. This would surely be judged a poor performance. By contrast, an “optimistic path” would be to maintain the higher growth rate for the developing world as a whole seen since 2000 without a rise in overall inequality. If that could be achieved then we can be reasonably confident of lifting that one billion people out of extreme poverty by sometime around 2030 (Ravallion, 2013).
What are the principle challenges in assuring that the second path is followed? Among the list of threats one can identify to attaining that goal, inequality stands out as a major concern today. Rising inequality can mean that growth largely by-passes poor people. This has been happening in some countries of the rich world, including the U.S.. Experience among developing countries has been varied. Inequality falls about as often as it rises in growing developing countries, although absolute poverty measures tend to fall with growth. High-inequality countries have a harder time reducing poverty in that they typically need higher growth rates than low-inequality countries to attain the same pace of progress against poverty and their high inequality often makes that growth even harder to attain.
In thinking about the implications for policy it is important to un-pack inequality—to identify the specific dimensions most relevant to progress against poverty. Inequalities in access to good quality schooling and health care stand out in many developing countries today. In many rural economies, inequalities in access to land (including insecurity of rights over land) also remain an impediment to pro-poor growth. Gender inequalities stand out everywhere, though not just in terms of command over material goods.
More pro-poor policies call for better quality public institutions and services that are inclusive of the needs of poor people. With the required political will there is much that can be done to improve health and education services in poor places and in making legal systems more inclusive. These are high priorities for antipoverty policy everywhere. While the “heavy-lifting” against poverty will probably continue to come from pro-poor growth processes, there is also an important supportive role for redistribution and insurance using state-contingent transfers, ideally financed primarily by domestic taxation. And that role is unlikely to be temporary; all countries need a permanent safety net. In thinking about the (many) options, policy makers in developing countries should be more open to the idea of only broadly targeted and largely unconditional transfers (as distinct from finely targeted conditional transfers). Improving tax systems in poor countries to expand the revenue for domestic antipoverty policies must also be a high priority.
External development assistance should continue to play a role. This is ethically compelling in its own right but also as compensation for the costs rich countries impose on poor ones (such as through past contributions to the stock of greenhouse gases and the past injustices of colonial exploitation and trade restrictions). Aid has two important roles. First there will be emergency aid—short-term assistance to deal with crises. There will be concerns about moral hazard, which have to be taken seriously, but wealthier countries should be called upon to help poor countries deal with agro-climatic and other shocks. Second, development assistance should help foster the conditions for sustainable poverty reduction in the longer-term, including institutional development and building better public administrations (such as for domestic resource mobilization).
It must be acknowledged, however, that the record of development aid has been uneven, and not always well-considered in the light of what we have learned about the economics of poverty. For example, a common view among aid donors is that they need to incentivize better policies—to use a carrot and stick approach, rewarding good efforts and punishing bad ones. This is a risky strategy and may well push fragile states into a poor-institutions trap (Ravallion, 2016, Chapter 9).
Market failures are an important reason why inequality matters to progress against poverty. Credit market failures have been a prominent concern. The policy responses entail some combination of efforts to make markets and institutions work better for poor people and efforts to compensate for market failures through other means, including redistribution. Inequality can also undermine the potential for making such policies happen. Those who benefit from their ability to capture new opportunities will often resist reforms that try to assure broader access to those opportunities, also given that poor people on their own have little current capacity to compensate the non-poor losers from pro-poor reforms. History is full of examples. English industrialists in the 19th century lobbied against compulsory schooling and against bans on child labor, and helped stall those reforms for a long period. Indian industrialists in the post-Independence decades lobbied for trade protection that diminished the scope for poverty reduction through labor absorbing export-led manufacturing growth. Powerful landholders in both these countries (and elsewhere) effectively undermined the potential for land reforms and other redistributive policies. And in many countries, insiders in urban formal-sector labor markets (on both sides of the market) act to effectively restrict competition from outsiders.
“Inequality” is not a single idea, but takes many forms, and can be seen very differently by different people. This fact creates much debate—though sometimes this seems like a debate between ships passing in the dead of night, not seeing or understanding each other’s perspective. The differences in how inequality is perceived can also stall pro-poor economic policies. A good example is the reaction that some people (understandably) have to rising absolute inequality. The once widely-held “stylized fact” of development that higher relative inequality is the unavoidable “price” for growth and (hence) poverty reduction, has been overturned in the light of new theories and evidence. Poor growing economies can and have avoided rising relative inequality, but they will have a much harder time avoiding rising absolute inequality—a rising absolute gap between the rich and the poor. And many citizens view inequality in absolute rather than relative terms. They are justified in taking that view; the concept of (relative) inequality held by most economists derives from an axiom that need not be accepted, and (indeed) appears to be rejected by many people. Those who view inequality as absolute and value it independently of poverty will see a trade-off between poverty and inequality. Ameliorating concerns about rising absolute inequality will almost certainly entail less progress against poverty.
Urban poverty is another challenge. The urbanization of poverty—whereby poverty rates fall more slowly in urban areas than in rural areas—is to be expected in almost any developing country that is successful in reducing poverty overall. Urban economies create new opportunities that poor people in rural areas have often sought out to improve their lives. Distorted urban labor markets can readily create excessive urbanization, as can the lack of effective public efforts to promote agriculture and rural development; indeed, many developing countries have gone even further in (explicitly or otherwise) taxing the rural economy to support the urban economy. Removing long-standing policy biases in both taxation and public spending remains a high priority for pro-poor growth. No less misguided are restrictions on migration and urban policies that under-supply services to poor urban residents, including rural migrants. Poor people are often trapped as the victims of policies that simultaneously repress agriculture while making life difficult for rural migrants. Development policymaking needs to be more neutral to these two sectors of economic activity. That will probably still entail an urbanization of poverty, but that should not be a cause for alarm as long as poverty is falling overall.
The sustainability of poverty-reduction efforts poses a further set of challenges in assuring that we can reach the optimistic path. We do not want to reach the poverty-reduction target only to fall back in subsequent years. On an encouraging note, research has suggested that lower initial levels of absolute poverty at a given mean consumption foster higher subsequent rates of growth in average living standards in developing countries and help to ensure that economic growth itself is poverty reducing (Ravallion, 2012). Thus, a “virtuous cycle” can be anticipated that would help to ensure the sustainability of the reduction in poverty.
Relative poverty: The other side of the coin to falling absolute poverty is rising relative poverty. Economic growth has generally meant lower absolute poverty rates, but over time relative considerations have become more important. Such relative poverty is still poverty. Welfare concerns about relative deprivation and costs of social inclusion demand higher real poverty lines as average incomes grow (though it makes little sense for this to be a constant proportion of average income in developing countries). But progress against relative poverty will be slower. Even the optimistic path will leave another one billion or so people in the world who live above the frugal poverty lines typical of the poorest countries but are still poor by the standards of the countries they live in. This type of poverty can also be eliminated but it will almost certainly require much stronger redistributive efforts than we have seen to date in most countries.
The policies are available. The bigger challenges ahead are in assuring the political will and administrative capabilities to implement and enforce sound antipoverty policies, and in adapting them to differing circumstances and evolving knowledge about their efficacy.
Ravallion, Martin, 2012, “Why Don’t we See Poverty Convergence?” American Economic Review, 102(1): 504-523.
____________,2013, “How Long Will It Take To Lift One Billion People Out Of Poverty?” World Bank Research Observer 28(2): 139-158.
____________, 2016, The Economics of Poverty: History, Measurement and Policy, New York: Oxford University Press.
The decade or two after WW2 saw many of the world’s poorest countries gain their independence from Colonial rule, and they were hoping to rapidly become less poor. Economics taught policy makers in those countries that a higher investment rate is crucial to assuring faster economic growth. Being a poor country makes it harder to finance the required investments from domestic savings. Yet rich countries should have ample savings available that might be profitably diverted to this task. In an ideal world, global capital markets could be expected to bridge the gap. But 70 years ago those markets were thin and/or not trusted as a source of finance.
In response, the United Nations Monetary and Financial Conference, held at Bretton Woods in 1944, created the International Bank for Reconstruction and Development (IBRD)—a core component of what came to be known as the World Bank. (The International Monetary Fund was created at the same time.) The essential idea was that the IBRD would borrow money on global markets to lend to developing countries. The Bank’s AAA credit rating (stemming from conservative lending policies relative to its capital) allowed it to lend on favorable terms. An aid-facility (with a large grant component), the International Development Association (IDA), was added in 1960.
Much has changed in the 70 years since the famous Bretton Woods conference. World Bank lending (IBRD+IDA) now represents only about 5% of the aggregate private capital flows to developing countries. In the last 10 years or so there have been prominent calls for radically reforming, or even closing, the institution on the grounds that international capital markets have developed greatly over those 70 years. It is also claimed by some that the Bank’s efforts are wasted due to poor governance in developing countries.
Does the Bank still have an important role? If so, does it fulfill that role, and if not, how might it do better? In a new paper I argue that the Bank’s development role today overlaps only partially with its original role, as conceived at the Bretton Woods Conference 70 years ago (Ravallion, 2015). Its role today is complementary to (rather than competing with) the private financial sector, other development banks, and academia. Knowledge-generation is central to that role. Development knowledge has properties of a public good, which the Bank can generate in the process of actually doing development on the ground.
Threats to the Bank’s effectiveness: There is still much appeal to the bundling of knowledge with lending that has been the distinctive feature of the Bank’s operations. But there are a number of threats to the efficacy of this model.
There have been some longstanding concerns that the Bank’s “lending culture” rewards operational staff for the volume of their lending, with only weak incentives for assuring that knowledge is both applied and generated in the lending operations. The pressure to lend influences the Bank’s ability to deliver objective policy advice to client countries, even when it is not welcome politically. Too often the Bank’s “country strategy” essentially mirrors that of the government, which may or may not serve broader long-term development goals.
Another threat is the perception that the Bank’s most powerful shareholders have excessive influence on its operations and policy advice. The U.S. has long been identified in this role, though some other countries have also been keen to have their say. Some critics are concerned (rightly or wrongly) about conflicts of interest when the Bank gives advice to developing countries.
These are threats to the Bank’s effectiveness as a knowledge leader in both the public and private sectors. All parties—both clients in developing countries and private investors—must have confidence that the institution is not pushing lending for its own sake or beholden to a few powerful owners. Only then can the Bank be accepted as the source of the objective policy advice and information that is needed.
Recent organizational changes have made some effort to put knowledge in the driver’s seat by organizing the Bank around a set of sectorally-defined “practices.” In the end the organogram has changed rather little. However, the threats to the Bank’s effectiveness are unlikely to be solved by changing the Bank’s organogram. The incentives of managers and staff also need to change, to assure a better alignment with development goals. (See Ravallion, 20105, for some examples of specific proposals for reform from past Bank staff.)
Knowledge Bank? There has been much rhetoric about the “Knowledge Bank” over the last 15 years, but I am not alone in believing that the reality has fallen short of the rhetoric. There is a chronic and growing underinvestment in the kind of rigorous research that is needed to identify and address pressing development issues—both the constraints on rapid poverty reduction at country level and the global public bads that threaten us collectively (ranging from climate change to pandemics). Research has been under-valued and under-funded.
Granted we still see some high-quality research at the Bank, though not always on high-priority topics. We see more ex-post evaluations today than 20 years ago. However, much does not get evaluated, and what gets evaluated is a non-random subset of all projects, casting doubt on what we learn about the whole. Too often, methodological preferences drive what gets evaluated rather than the knowledge gaps facing policy makers. Alongside this, we see fewer and less rigorous ex ante evaluations, which make explicit a project’s economic rationale—why the project is expected to have a social value justifying its cost.
Three changes are needed: Echoing the observations of others within and outside the Bank, three things need to change:
Further reading: Martin Ravallion, “The World Bank: Why it is Still Needed and Why it Still Disappoints,” Journal of Economic Perspectives, Winter 2016.
(This was first posted on the World Bank’s Let’s Talk Development blog.)
More thought has been given to the validity of the conclusions drawn from development impact evaluations than to the ethical validity of how the evaluations were done. This is not an issue for all evaluations. Sometimes an impact evaluation is built into an existing program such that nothing changes about how the program works. The evaluation takes as given the way the program assigns its benefits. So if the program is deemed to be ethically acceptable then this can be presumed to also hold for the method of evaluation. (I leave aside ethical issues in how evaluations are reported and publication biases.) We can dub these “ethically benign evaluations.”
Another type of evaluation deliberately alters the program’s (known or likely) assignment mechanism—who gets the program and who does not—for the purpose of the evaluation. Then the ethical acceptability of the intervention does not imply that the evaluation is ethically acceptable. Call these “ethically contestable evaluations.” The main examples in practice are randomized control trials (RCTs). Scaled-up programs almost never use randomized assignment, so the RCT has a different assignment mechanism, and this may be contested ethically even when the full program is fine.
A debate has emerged about the ethical validity of RCTs. This has been brewing for some time but there has been a recent flurry of attention to the issue, stimulated by a New York Times post last week by Casey Mulligan and various comments including an extended reply by Jessica Goldberg. Mulligan essentially dismisses RCTs as ethically unacceptable on the grounds that some of those to which a program is assigned for the purpose of evaluation—the “treatment group”—will almost certainly not need it, or benefit little, while some in the control group will. As an example, he endorses Jeff Sachs’s arguments as to why the Millennium Villages project was not set up as an RCT. Goldberg defends the ethical validity of RCTs against Mulligan’s critique. On the one hand she argues that randomization can be defended as ethically fair given limited resources, while (on the other hand) even if one still objects, the gains from new knowledge can outweigh the objections.
I have worried about the ethical validity of some RCTs, and I don’t think development specialists have given the ethical issues enough attention. But nor do I think the issues are straightforward. So this post is my effort to make sense of the debate.
Ethics is a poor excuse for lack of evaluative effort. For one thing, there are ethically benign evaluations. But even focusing on RCTs, I doubt if there are many “deontological purists” out there who would argue that good ends can never justify bad means and so side with Mulligan, Sachs and others in rejecting all RCTs on ethical grounds. That is surely a rather extreme position (and not one often associated with economists). It is ethically defensible to judge processes in part by their outcomes; indeed, there is a long tradition of doing so in moral philosophy, with utilitarianism as the leading example. It is not inherently “unethical” to do a pilot intervention that knowingly withholds a treatment from some people in genuine need, and gives it to some people who are not, as long as this is deemed to be justified by the expected welfare benefits from new knowledge.
Far more problematic is either of the following:
The latter situation is clearly objectionable if it is seen to hold. But it is often hard to verify in development settings. Ethics has been much discussed in medical research. In that context, the principle of equipoise requires that there should be no decisive prior case for believing that the treatment has impact sufficient to justify its cost. (This is David McKenzie’s sensible modification to clinical equipoise to fit the types of programs in discussion here.) By this reasoning, only if we are sufficiently ignorant about the likely gains relative to costs should we evaluate further. Implementation of such an ethical principle may not be easy, however. In the context of antipoverty or other public programs, a priori (theoretical and/or empirical) arguments can often be made both for and against believing ex ante that impact is likely. A clever researcher can often create a convincing straw man to suggest that some form of equipoise holds and that the evaluation is worth doing. While this cannot be prevented, we should at least demand that the case is made, and it stands up to scholarly public scrutiny. That is clearly not the norm at present.
It has often been argued that whenever rationing is required—when there is not enough money to cover everyone—randomized assignment is a fair solution. (Goldberg makes this claim, though I have heard it often. Indeed, I have made this argument a few times with government counterparts in attempting to convince them on the merits of randomization.) In practice, this is clearly not the main reason that randomistas randomize. But should it convince the un-believers? It can be accepted when information is very poor, or allocative processes are skewed against those in need. In some development applications we may know very little ex ante about how best to assign participation to maximize impact. But when alternative allocations are feasible (and if randomization is possible then that condition is evidently met) and one does have information about who is likely to benefit, then surely it is fairer to use that information, and not randomize, at least unconditionally.
Conditional randomization can help relieve ethically concerns. One first selects eligible types of participants based on prior knowledge about likely gains, and only then randomly assigns the intervention, given that not all can be covered. For example, if one is evaluating a training program or a program that requires skills for maximum impact one would reasonably assume (backed up by some evidence) that prior education and/or experience will enhance impact and design the evaluation accordingly. This has ethical advantages over simple randomization when there are priors about likely impacts.
But there is a catch. The set of things observable to the evaluator is typically only a subset of what is observable on the ground (such information asymmetry is, after all, the reason for randomizing in the first place). At local level, there will typically be more information—revealing that the program is being assigned to some who do not need it, and withheld from some who do. The RCT may be ethically unacceptable at (say) village level. But then whose information should decide the matter? It may be seen as quite lame for the evaluator to plead, “I did not know” when others do in fact know very well who is in need and who is not.
Goldberg reminds us of another defense often heard, namely that RCTs can use what are called “encouragement designs.” The idea here is that nobody is prevented accessing the primary service of interest (such as schooling) but the experiment instead randomizes access to some form of incentive or information. This may help relieve ethical concerns for some observers, but it clearly does not remove them—it merely displaces them from the primary service of interest to a secondary space. Ethical validity still looms as a concern when any “encouragement” is being deliberately withheld from some people who would benefit and given to some who would not.
While ethical validity is a legitimate concern in its own right, it also holds implications for other aspects of evaluation validity. There is heterogeneity in the ethical acceptability of RCTs. That will vary from one setting to another. One can get away with an RCT more easily with NGOs than governments, and with small interventions, preferably in out-of-the-way places. (By contrast, imagine a government trying to justify why some of its under-served rural citizens were randomly chosen to not get new roads or grid connections on the grounds that this will allow it to figure out the benefits to those that do get them.) An exclusive reliance on randomization for identifying impacts will likely create a bias in our knowledge in favor of the settings and types of interventions for which randomization is feasible; we will know nothing about a wide range of development interventions for which randomization is not an option. (I discuss this bias for inferences about development impact further in “Should the Randomistas Rule?”.) Given that evaluations are supposed to fill our knowledge gaps, this must be a concern even for those who think that consequences trump concerns about processes.
If evaluators take ethical validity seriously there will be implications for RCTs. Some RCTs may have to be ruled out as simply unacceptable. For example, I surely cannot be the only person who is troubled on ethical grounds by the (innovative) study done in Delhi India by Marianne Bertrand et al. that randomized an encouragement to obtain a driver’s license quickly, on the explicit presumption that this would entail the payment of a bribe to obtain a license without knowing how to drive. (This study was conducted and funded by the World Bank’s International Finance Corporation. And it was published in a prestigious economics journal.) The study confirmed that the process of testing and licensing was not working well even for the control group. But the RCT put even more drivers on Delhi roads who did not know how to drive, adding to the risk of accidents. The gain from doing so was a clean verification of the claim that corruption is possible in India and has real effects, though I was not aware of any prior doubt about the truth of that claim.
There may well be design changes to many RCTs that could assure their ethical validity, such as judged by review boards. One might randomly withhold the option of treatment for some period of time, after which it would become available, but this would need to be known by all in advance, and one might reasonably argue that some form of compensation would be justified by the delay. Adaptive randomizations are getting serious attention in biomedical research; for example, one might adapt the assignment to treatment of new arrivals along the way, in the light of evidence collected on covariates of impact. (The U.S. Food and Drug Administration issued guidelines a few years ago.)
The experiment might not then be as clean as in the classic RCT—the prized internal validity of the RCT in large samples may be compromised. But if that is always judged to be too high a price then the evaluator is probably not taking ethical validity seriously.
(First posted on the World Bank’s Development Impact blog.)
In 2013 the World Bank announced that one of its two goals is to “share prosperity,” which is to be measured by the growth rate in mean consumption (or income) for the poorest 40% of the population. (Its other goal is eliminating absolute poverty.)
The growth rate in the mean for the poorest 40% has the appeal of simplicity. But that comes with a cost. An important concern is that it does not tell us anything at all about how much rising prosperity is being shared amongst the poorest 40%, or how the losses from economic contraction are being spread. For example, the mean of the poorest 40% could rise without any gain to the poorest.
That limitation is important in the light of recent research. While the developing world as a whole has made huge progress in reducing the numbers of people living in poverty, much less progress has been made in raising the developing world’s consumption floor—the level of living of the poorest. (I show this here.) If we are really committed to sharing prosperity then we should surely not be leaving the poorest behind.
There is a remarkably simple fix for the Bank’s measure of success in sharing prosperity: Instead of measuring the growth rate of the mean for the poorest 40% the Bank should measure the mean growth rate of the poorest 40%. This may sound like some nerdy quibble, but it does matter. This subtle difference in the measure makes a big difference in its properties. With this change, the measure of “shared prosperity” reflects how equitably aggregate gains have been shared amongst the poorest 40%. If inequality falls (rises) among the poorest 40% then the mean growth rate will be higher (lower) than the growth rate of the mean. The mean growth rate of the poorest 40% is also quite easy to calculate from any two standard household surveys. (They do not need to be panel data.)
Let’s take a simple example. Suppose that there are four representative people comprising the poorest 40%, with incomes (in $s per day) of $0.75, $0.75, $1 and $1. After some economic shock or policy change their incomes are $0.50, $0.75, $1 and $1.25, i.e., there is a gain of $0.25 for the least poor, at the expense of the poorest. The growth rate in the mean of the poorest 40% is zero, while their mean growth rate is -2% (the average of -33%, 0%, 0%, 25%).
This change may still not be considered enough. There are other measures, although they often lose the advantage of simplicity. In more careful monitoring, a broader dashboard of measures will clearly be needed in assessing how well prosperity is being shared. For example, if one really cares about not leaving the poorest behind then one should also focus directly on that; there are now operational measures for that purpose, which are also easy to implement, as I show in this paper.
However, my point here is that one can improve the Bank’s measure with only a small change in wording. And the alternative measure can be implemented at virtually no extra cost in monitoring.
(In the interests of full disclosure, I participated in the internal discussions at the Bank in 2012 about its goals. I am writing this post two years after leaving the Bank, and in the light of research since then.)
In an OPED last year, “Reading Piketty in India,” I noted how poor the U.S. was in the mid-19th century. As best I can determine from the data available, the proportion of America’s population living below India’s poverty line was roughly as high then as it is in India today. The period 1850-1929 saw the poverty rate fall by some 20 percentage points. The U.S. saw great progress against extreme poverty in this period. A few people have asked me for more details. Here they are, also extending the calculations to other rich countries.
We already know that the categories “developed” and “developing world,” were much less relevant around 1800 than they are today (and they will undoubtedly become less relevant in the future). Of course, there were disparities in average levels of living across the countries of the world, but less so than today—indeed, quite possibly less than one finds amongst many developing countries today. Average living standards in 18th century Europe were higher than in Asia or Africa, but the proportionate difference was less than we see today.
Francois Bourguignon and Christian Morrisson assembled distributional data back to the early 19th century, to match up with Angus Maddison’s estimates of national income. Bourguignon and Morrisson only calculated poverty measures for the world as a whole. Using their data base (which they kindly provided) I calculated what % of the population of the countries in their study that are considered rich countries today lived below the Bourguignon-Morrisson “extreme poverty” line back to 1820. That line was chosen to synchronize with the poverty rate for 1990 implied by the Chen-Ravallion “$1 a day” line. Figure 1 summarizes the results.
These numbers should only be considered as broadly indicative, especially given the paucity of good data for the 19th and early 20th centuries. Nonetheless, they suggest that today’s rich countries had poverty rates in the early and mid-19th century that are comparable to those found in even relatively poor developing countries today. The countries of today’s rich world started out in the early 19th century with poverty rates below the global average at the time, but not that much below. In most cases, their poverty rates fell dramatically in the 19th century (Japan was a late starter but caught up in the 20th century). Yet today there is virtually no extreme poverty left in today’s rich world, when judged by the standards of poor countries today.
Figure 1: Past poverty rates for today’s “rich countries”
Key: ACN: Australia-Canada-New-Zealand; ACH: Austria-Czechoslovakia-Hungary; BSM: Benelux-Switzerland-Micro-European States; PS: Portugal-Spain; UKI: United Kingdom and Ireland
Notes: Author’s estimates using parameterized Lorenz curves calibrated to the data set developed by Bourguignon and Morrisson (2002), which was kindly provide by the authors. Bourguignon and Morrisson used a poverty line based on that used by Chen and Ravallion (2001) for measuring poverty in developing countries. The estimates allow for the fact that Bourguignon and Morrisson anchored their measures to GDP per capita (from Maddison, 1995) rather than the survey-based means used by Chen and Ravallion. Bourguignon and Morrisson determined that the poverty line corresponding to the line of $1.08 per day used by Chen and Ravallion on survey-based distributions was $2.38 per day ($870 per year) when applied to GDP per capita.
A couple of remarks can be made on the current relevance of these numbers. First, understanding the past success of today’s rich world against extreme poverty should be high on the list of research issues for development economics. (I explore the topic further in Ravallion, forthcoming.)
Second, when progress against poverty is measured as a % point per year it slowed down a lot toward the end (as can be seen in Figure 1). More surprisingly, when measured in proportionate terms, experiences differed greatly, as can be seen from Figure 2. Some countries (the US, the UK, Japan) saw steady progress in proportionate terms, while others saw more erratic changes in rates of progress at low poverty rates. While we often assume that it will be a long hard slog to get the last few percentiles out of extreme poverty, some rich countries maintained steady progress to the end, and some even accelerated.
Figure 2: Annualized proportionate rates of change in the poverty rate from Figure 1
Bourguignon, Francois and Christian Morrisson, 2002, “Inequality among World Citizens: 1820-1992,” American Economic Review 92(4): 727-744.
Maddison, Angus, 1995, Monitoring the World Economy. Paris: OECD.
(This was first posted on the Center for Global Development’s Policy Blog.)
There is growing support in the rich world for a basic-income guarantee (BIG), in which the government would provide a fixed cash transfer to every adult, poor or not. In 2015, for example, the Swiss will vote on a referendum to introduce a BIG. We have not yet seen a national BIG rolled out, although there are policies in place with similar features. (For example, the US earned-income tax credit, while not strictly a BIG, contains some similarities.) Proponents say it’s an easy way to reduce poverty and inequality; if that’s so, it’s time to think BIG in the developing world, too.
Support for the BIG idea (also known as a poll transfer, guaranteed income, citizenship income, or an unmodified social dividend) has spanned the political spectrum. Some supporters see it as a “right of citizenship,” or a foundation for economic freedom to relax the material constraint on peoples’ choices in life. Others have pointed out that a BIG is an administratively easy way to reduce poverty and inequality, with modest distortionary effect on the economy as a whole. There are no substitution effects of a BIG on its own (there’s no action anyone can take to change their transfer receipts). Supporters also note there’s no stigma associated with a BIG, since it’s not targeted only to poor people. And a BIG may well be more politically sustainable than finely targeted options that may have a narrow base of support.
Opponents, on the other hand, echo longstanding concerns that the welfare state undermines work incentives. There may well be income effects of a BIG on demand, including for leisure. The effect on employment is unclear, however. The BIG could ease constraints on work opportunities, such as those that hinder self-employment or migration. On balance, work may even increase.
As with any social policy, a complete assessment of the implications for efficiency and equity of a BIG must also take all costs and how it is financed into account. The administrative cost would likely be low, though certainly not zero given some form of personal registration system would be needed to avoid “double dipping” and to ensure larger households receive proportionately more. One low-cost way of doing this would be to establish a personal identification system, such as the Aadhaar in India.
Further, a BIG could be a feasible budget-neutral way of reforming social policies. There could be ample scope for financing it by cutting poorly targeted transfer schemes and subsidies heavily favoring the non-poor. A BIG scheme would easily replace many policies found in practice today. For example, it would clearly do better in reaching the poor than the subsidies on the consumption of normal goods (such as fuel) that are still found in a number of countries.
The un-targeted nature of a BIG runs against the prevailing view in some circles that finer targeting is always better. But that view is questionable. For example, recent research has shown that once one accounts for all the costs involved in India’s National Rural Employment Guarantee Scheme, including the forgone earnings of participants, a BIG with the same budgetary cost would have greater impact on poverty than the labor earnings from the existing scheme. The work requirements of the employment scheme ensure that it is very well-targeted. Even so, it is likely to be a less cost-effective way to reduce poverty than an untargeted BIG with the same budgetary cost. There may well be other advantages to India’s current scheme; for example, asset creation, risk mitigation, and empowerment. But it is not clear whether these benefits would tilt the balance relative to a far simpler BIG.
The BIG idea should be put on the menu of social policy options for developing countries.
(This was first posted on the Center for Global Development’s Policy Blog.)
The challenges of measuring and monitoring global poverty have received a lot of attention in recent times. There have been debates about the Sustainable Development Goals, as well as some more technical debates. Assessments of progress against poverty at the country level, and most decisions about how best to fight poverty within countries, do not require global poverty measures. Nonetheless, such measures are important to public knowledge about the world as a whole, and they help inform the work of development agencies, including in setting targets for overall progress.
In a new working paper I discuss three current issues that are specific to global poverty monitoring, and proposes some solutions.
The first relates to one of the main sources of dissatisfaction with prevailing poverty measures that use a constant real line, namely that they do not take account of the concerns people everywhere face about relative deprivation, shame and social exclusion; these can be termed social effects on welfare. To some extent the fact that higher national lines are found in richer countries reflects these social effects on welfare. But the differences in national lines also reflect to some extent more generous welfare standards for defining poverty in richer countries.
Yet we can all agree that we need to use a consistent welfare standard in measuring poverty globally. We need to be reasonably confident that people we judge to have the same level of welfare—the same capabilities for example—are being treated the same way wherever they live. Amartya Sen put the point nicely: that “…an absolute approach in the space of capabilities translates into a relative approach in the space of commodities.” But when we think about how best to do that, we run into the problem that we do not know whether the higher lines in richer countries reflect differences in the incomes needed to attain the same level of welfare, or (instead) that they reflect higher welfare standards in richer countries.
The paper argues that two global poverty lines are needed—a familiar lower line with fixed purchasing power across countries and a new upper line given by the poverty line that one would expect given the country’s level of average income, based on how national poverty lines vary across countries. The true welfare-consistent absolute line lies somewhere between the two bounds. By this approach, to be judged “not poor” one needs to be neither absolutely poor (independently of where and when one lives) nor relatively poor (depending on where and when one lives).
The second problem is an evident disconnect between how poverty is measured in practice and the emphasis given in social policy and moral philosophy to leaving none behind. For example, a 2013 report initiated by the U.N. on setting the new SDGs argued that: “The indicators that track them should be disaggregated to ensure no one is left behind and targets should only be considered ‘achieved’ if they are met for all relevant income and social groups.” But how do we know of none are being left behind? To assess whether the poorest are being left behind one needs a measure of the consumption floor. Here there is a severe data constraint, namely that a low observed consumption or income in a survey could be purely transient, and so unrepresentative of permanent consumption.
However, I have shown that a more reliable estimate of the consumption floor can be derived from existing measures of poverty under certain assumptions. This can be readily implemented from existing poverty data, and it provides a rather different vantage point on progress against poverty. While the developing world has made much progress in reducing the number of poor, there has been very little progress in raising the consumption floor above its biological level. In that sense, the poorest have been left behind. Progress against poverty should not be judged solely by the level of the consumption floor, but it should not be ignored.
Finally, the paper reviews the ongoing concerns about the current Purchasing Power Parity (PPP) exchange rates from the International Comparison Program (ICP). (See, for example, the CGD blog post here, and the comments on that post; my new paper addresses this debate.) The days are (thankfully) gone when the community of users simply accepts without question the aggregate statistics produced by publicly-funded statistical organizations like the ICP. Recurrent debates about the ICP’s results have been fueled in part by poorly-understood methodological changes and in part by the ICP’s longstanding lack of openness, notably in access to primary data.
Calculating PPPs that are appropriate for global poverty measurement using ICP price data is not exactly easy, but nor is it the hardest task imaginable as long as researchers have access to the data. There are also options to using ICP prices, although further testing is needed on their performance. Even staying with the ICP, adjustments will be called for, such as to deal with urban bias in the price surveys. Going forward, better price-level comparisons for the purpose of measuring poverty, including sub-national analysis, require re-estimating the PPPs from the primary data. If the ICP is to continue to be a valuable resource, it needs to make public the primary data to facilitate such calculations.
Each of the paper’s proposals for addressing these problems could undoubtedly be improved upon and refined if there is enough agreement that effort is needed to develop better global poverty measures along these lines. That effort is justified if our global measures are to continue to have relevance in global public knowledge, and to international policy making and poverty monitoring.
This week saw the release of the World Bank’s updated global poverty counts. There is new country-level data on poverty and inequality underlying these revisions. But the big change is that the numbers are now anchored to the 2011 Purchasing Power Parity (PPP) rates for consumption from the International Comparisons Program (ICP). Previously the numbers were based on the prior ICP round for 2005. The Bank published a reasonably clear Press Release explaining that the new international poverty line is $1.90 per person per day at 2011 prices; also see this blog post by Bank researchers.
Some observers have said that $1.90 entails a large upward revision to the Bank’s global poverty line. An article in the Financial Times ran the headline that “The Earth’s poor set to swell as World Bank shifts poverty line.” Similarly, ’in this Vox piece, CGD’s Charles Kenny and Justin Sandefur claim that this is “the biggest upward revision of the poverty line in 25 years.”
The FT article went further to suggest why this has happened, quoting Angus Deaton, a Professor at Princeton, as claiming that the Bank has an “institutional bias towards finding more poverty rather than less.” By this view, there is a motive to the Bank’s seemingly large upward revision to its poverty line—to keep itself in business as the leading institution fighting global poverty. But this conspiracy theory makes little sense on closer inspection.
We must first understand that the $1.90 is in 2011 prices while $1.25 was in 2005 prices. Everyone knows about inflation. But how should one deal with inflation for this purpose? If one simply updates the $1.25 line for inflation in the U.S. one gets $1.44 a day in 2011. This was done in some calculations soon after the release of the 2011 ICP results, such as those by CGD researchers reported here. Updating the line for U.S. inflation 2005-11 greatly reduces the global poverty rate for 2011 when compared to the old PPPs.
However, fixing the U.S. purchasing power of the international line over time is very hard to defend given the generally higher inflation rates in developing countries than the U.S. Thus, while $1.44 a day in 2011 has the same purchasing power in the US as $1.25 in 2005, when $1.44 is expressed in local currencies of developing countries using the 2011 PPPs it has lower purchasing power in most of those countries than when the prior $1.25 line in local currency is adjusted for inflation in those countries. In that sense, using $1.44 in 2011 lowers the poverty line, and that is why one gets less poverty.
Instead, the Bank’s researchers went back to the national poverty lines for low-income countries that were used to derive the $1.25 a day line, as described here. They then updated those national lines to 2011 prices using the best available country-specific Consumer Price Indices. On then converting to PPP for 2011 and taking an average they got $1.90. This is not the only way one could have updated the $1.25 a day line. One could instead have asked what the average national line is amongst the poorest “x” countries in 2011, which would have been more consistent with past methods used by the Bank. But the method they have used to get to $1.90 is defensible, and it has the appeal that the underlying national lines for low-income countries have constant purchasing power over time.
This is surely a strange way for the Bank to reflect the claimed bias toward overstating the extent of poverty. More plausibly, in my view, there is no such bias since the real value of the line is being held constant in poor countries.
Furthermore, none of this makes much difference to the pace of progress against extreme absolute poverty over time. As the Bank announced in its Press Release, that progress remains largely unchanged from the old PPPs. Indeed, the PR is quite upbeat on the pace of progress. This hardly sounds like a bias toward exaggerating the extent of global poverty!
There are, nonetheless, changes in the composition of the world’s poor, as the new ICP round has revised the PPPs for many countries. Those changes are not yet well understood. (See, for example, my comments here on India’s new PPP.) As I noted in a recent blog post, “We need better global poverty measures,” the ICP has not been as open as one would like about their price data. And the raw PPPs are not well suited to poverty measurement. The Bank’s researchers have done some “patch-ups” (such as adjusting for the evident urban bias in the ICP’s price surveys), but a more fundamental ICP overhaul is needed if the PPPs are to continue to be used in global poverty measurement.
I also argued in the same blog post that the absolute line of $1.25 a day in 2005 prices (or $1.90 a day in 2011 prices) is inadequate today. Two global poverty lines are now needed—a lower line with fixed purchasing power across countries and a new upper line given by the poverty line that one would expect given the country’s level of average income, based on how national poverty lines vary across countries. The true welfare-consistent absolute line—whereby one judges poverty by a common absolute standard of welfare, which may well require differing commodities in different settings—lies somewhere between the two bounds. By this approach, to be judged “not poor” one needs to be neither absolutely poor (independently of where and when one lives) nor relatively poor (depending on where and when one lives). Global poverty estimates for both bounds can be found here; the upper bound suggests less progress against poverty, but still progress. If anything, the World Bank is overestimating the pace of that progress.
My advocacy of this new “upper bound” is not some bias toward over-estimating poverty for some conspiratorial reason. Rather it recognizes the differing social realities of what is needed to not be considered poor in today’s world. The World Bank, and its critics, also needs to recognize those realities.
(This was first posted on the Center for Global Development’s Policy Blog.)