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Who really benefits from poverty-targeting in social protection: the poor or the rich?

Stephen Kidd

Asking whether the poor or the rich are the main beneficiaries of poverty-targeting in social protection probably seems like a strange question to many people.  On the face of it, the answer appears obvious: surely logic dictates that it must be the poor? Furthermore, it is often assumed that universal provision delivers no particular advantage for the poor as they only receive the same level of benefit as the rich.

But, as so often happens in social protection, the seemingly obvious answer is the wrong answer. In reality, when comparing the two options of poverty-targeting and universal provision, the main beneficiaries of poverty-targeting are the rich while the poor are the main beneficiaries of universal provision.

How can this be? Well, the answer is found in the magic of taxation. Most national social protection schemes financed from general government revenues are paid from taxes. So, when assessing who benefits from social protection we need to take into account both the transfer itself and the tax that is used to finance the benefit.

A simple thought-experiment can demonstrate why the rich lose out economically much less from poverty-targeted social protection when compared to universal provision.

Imagine a country in which the population comprises five citizens. As in most countries, our imaginary country is highly unequal. The total income of all citizens is 10,000 units and Figure 1 shows the relative incomes of each of our five citizens: while the richest citizen has an income of 7,000 units, the poorest has an income of only 200 units.

Figure 1: Distribution of wealth across the five citizens of our imaginary country

Now, imagine two scenarios:

  • In the first, the country establishes a poor relief (poverty-targeted) programme – let’s call it a conditional cash transfer – for the poorest citizen, so only s/he benefits.
  • In the second scenario, the country establishes a universal scheme offering a transfer of equal value to all citizens.

Obviously, there is a significant difference in the level of investment required for the two scenarios. The poverty-targeted programme is, in our experiment, by far the cheaper of the two, at 0.5 per cent of GDP (i.e. a slightly higher cost than most poor relief schemes currently found in low- and middle-income countries, such as Brazil’s Bolsa Familia, Mexico’s Prospera and the Philippines’ Pantawid programme). The universal scheme, as would be expected, is much more expensive, at five per cent of GDP (a little lower than the cost of Iran’s universal transfer for households – a form of basic income grant – when it was first introduced, and slightly higher than Georgia’s universal old age pension). The higher cost reflects the reality of the political economy of social protection: that universal schemes not only have higher coverage levels but, since everyone benefits, are more popular than poverty-targeted programmes. As a result, they generate both higher expenditures and, very often, higher value transfers.

The analysis makes two simple assumptions: i) everyone in the population is taxed at the same rate; and, ii) the poverty-targeting is perfect, ensuring no leakage to those outside the poorest quintile. Given that perfect targeting is an illusion – since even the most effective poverty-targeted schemes have exclusion errors of around 50 per cent of their intended recipients – we bias the results towards making poverty-targeting more attractive.

Figure 2 shows the change in the incomes of the country’s citizens after both scenarios are implemented. While the poorest citizen does better than all other citizens under the poverty programme, s/he is, in fact, much better off under the universal programme, with an increase in income of 90 units rather than the 49 units received under the poverty-targeted scheme. Further, while, under the poverty programme, citizens 2, 3 and 4 lose out slightly, they are net beneficiaries under the universal programme. This is important in the context of low- and middle-income countries since it is common for over 80 per cent of the population to be living on low incomes (in most countries, the vast majority of the population lives under US$5.00 per day, in purchasing power parity terms, a very low amount).

Figure 2: Net income gains and losses under the poverty-targeted and universal schemes

However, when we examine the richest citizen, it is clear that s/he does best under the poverty-targeted programme. While s/he loses some income under poverty-targeting, it is minimal since the tax paid to finance this relatively small programme is also minimal. His/her net loss under the universal scheme is much larger, despite receiving the same transfer as the other citizens. In fact, the losses of the richest citizen are equal to the gains of the other four citizens.

While this is only a thought-experiment, it mimics real life. It explains why we often find poverty-targeted schemes dominating in countries where democracies are weak: in such contexts, social protection schemes are often designed to respond to the interests of the rich, who want low taxes, rather than the interests of the majority of citizens. A key aim of poverty-targeting is to minimise taxation, which disproportionately hits the wealthy (even when taxation is not progressive): that’s why Trump’s tax cuts in the USA have been strongly advocated – and welcomed – by elites. Austerity measures in Europe have similarly been designed to cut the budgets of welfare programmes for the poor while lowering the overall tax burden. Indeed, as the World Bank (2015) itself has admitted (albeit in a paper it didn’t publish): “The historical … evidence suggests that the forces pushing for better [in other words, poverty] targeting are more regularly motivated by cutting entitlement bills and ensuring financial sustainability than by helping the poor.” By ‘financial sustainability,’ we should understand ‘lower costs and taxes’ since, in reality, universal schemes, despite their higher costs, are more financially sustainable than poverty-targeted programmes, due to their popularity which, as noted above, is derived from the fact that everyone benefits.

Since the recipients of poverty-targeted schemes are politically weak, the programmes themselves tend to be of low quality, with high exclusion errors and low-value transfers. Consequently, as our thought experiment showed, the impacts of poverty-targeted programmes on poverty are much lower than universal schemes (for example, the impacts of Brazil’s Bolsa Familia scheme on poverty and inequality are a fraction of the impacts of the country’s almost universal pension scheme). Further, they often include conditions and sanctions – the so-called conditional cash transfers – with elites using poverty-targeted transfers as a means of controlling the behaviour of the poor. Sometimes, they are delivered as workfare, often with negative consequences for poor families who are obliged to work long hours for little pay (for example, the Young Lives project has demonstrated that Ethiopia’s Productive Safety Net Scheme has actually made recipients poorer).

Paradoxically, therefore, poverty-targeting has to be understood as pro-rich rather than pro-poor. If progressive social protection policies are to be implemented, it is important that those working on social protection understand that it is universal schemes that are the most pro-poor, a result of their lower exclusion of the poor and higher impacts on the well-being of those living in poverty.

In reality, however, even though the rich lose out economically from universal schemes, they benefit in many other ways. The universal provision of services delivers more equal, happier, peaceful and more prosperous societies. In such societies, the rich don’t have to hide behind high walls and armed guards but can fully benefit from living in safer and more cohesive societies. It’s no coincidence that the countries most committed to universal provision – the Nordic countries – are among the most prosperous, equal and happiest societies. In effect, therefore, universal provision is neither pro-poor nor pro-rich but pro-all.

Does this simple thought-experiment explain why some institutions – such as the World Bank and IMF – promote poverty-targeting while opposing universal schemes? (Of course, they are not alone: bilateral donors usually support and finance poverty-targeted programmes across Africa and Asia, although there are notable exceptions such as the United Kingdom’s and Ireland’s financing of a universal pension in Uganda and the European Union’s financing – through UNICEF – of a pilot universal child benefit in Angola). An interesting question is whether the support for poverty-targeting within these institutions is the result of an ongoing allegiance to a pro-rich neoliberal ideology or because their staff actually do not understand who are the true beneficiaries of poverty-targeting? I suspect that it is a mix of both.

If pro-all inclusive social protection systems are to be established in low- and middle-income countries, it will be necessary for the voices of the majority of the population to be heard, in particular during elections. Developing countries need progressive politicians who can see through the myth that targeting the poor is pro-poor and, instead, outline a vision of an inclusive social protection system benefitting all citizens – including those living in extreme poverty – through the effective and fair redistribution of wealth. Such politicians will be richly rewarded at the polls.

The author Stephen Kidd is a Senior Social Policy Specialist at Development Pathways and has more than 30 years of experience working on social development and social protection across Africa, Asia, the Pacific and Latin America. Prior to joining Pathways, he was Director of Policy and Communications at HelpAge International, a Senior Social Development Adviser at DFID (where he led the Social Protection Policy Team), a lecturer in Social Anthropology at the University of Edinburgh and worked for over 10 years in Paraguay on indigenous land rights.

View his publications by clicking here, and comment on his blog below.


  • Nice. Make it personal and assume/accuse me of being a rich brat who only thinks about his money. I cannot sign the post because I work for one of those places defending targeting, and I don’t want my views to be mistaken for those of my workplace. I do not come from the top 10 percent of my national population. Not even close. But that is completely besides the point. Although to be expected – when the technical arguments are weak, one resorts to personal attacks.

    – A pre-transfer and pre-tax Gini of 60 percent cannot be found in many countries in the world. So no, you did not pick a normal countries. Simply stating a fact does not make it true. Pre-transfer and pre-taxes gini coefficients are almost impossible to find for all countries in the world, but the OECD compiles them for quite a few countries, and I see one (South Africa) in their list with a 70% gini coefficient. The UK and the US are at 50. https://stats.oecd.org/Index.aspx?DataSetCode=IDD#
    – An extreme poverty rate of 40 percent (actually your example has a 60 percent) is not normal. The international extreme poverty line is 1.90. 5$ per day PPP is an arbitrary figure and has nothing to do with extreme poverty. What “most people would argue” has no technical bearing in this debate. And by the way, the official poverty line (federal) in the US is 12,000U$ per year for one individuals, 16,000 for 2, and 25,000 for 4. I am not familiar with the food poverty line in the US that you mention, and I could not find a reference for it. The US Department of Agriculture defines food security, not food poverty, and it is more a measure of deprivation. I cannot see any link to monetary figures. Would be glad to see where you find a reference to the 5$ a day being food poverty in the US. Again – facts please, not statements.
    – I happen to know the Tanzania PSSN very well. It has some of the best targeting in the world. Check the baseline report in case you missed it. And maybe pick your examples better because if that is what you call random, you need to take a second look at the definition of random. http://documents.worldbank.org/curated/en/273011479390056768/pdf/110255-WP-P124045-OUO-9-PSSN-IE-Baseline-Report-FINAL-FOR-PUBLISHING.pdf
    – Here we go again and we start confusing people. You were talking about a UBI, and now of course you want to compare it to non-universal benefits to show that they cost roughly the same. So you bring up the Mongolian CMP, which is NOT universal of course, and it is a categorical benefit (it is reserved for families with children). In practice it did reach 90 percent of the population, but have some intellectual clarity and honesty when you argue for a UBI. Compare apples to apples, poverty programs to poverty programs. The objective of the CMP is NOT poverty reduction, which is what you were arguing for when advocating for a UBI. Its objective is fertility. Likewise – nice try on the universal pensions, which of course is for people above a certain age (and hence categorical by definition). So you are saying that a pension which covers, say, 20 percent of the population (see Georgia) and cost 5 percent of GDP is comparable in cost to UBI which would cover 100 percent. I would check that math. When I mentioned Mongolia, I was referring to the actual UBI they had in 2011 and 2012, which cost over 8 percent of GDP, and lasted a year before they had to get the IMF in. At the very least, I would expect this example to be known, as it is one of the very very very few examples in which a universal unconditional benefit to all citizens was tested.
    – Nice speculation on the public. The only example we have where they asked the public about targeting vs universal is Switzerland, where a referendum told the politicians that “the public” did not favor spending 10 percent of GDP on giving away money to all. So, yeah, “the public really only opposes poverty targeting”.
    Anyway – I am kind of glad you attacked me on a personal level and assuming that I am a rich person defending my interests. The counter technical you raise are easily dismissed. So you make assumptions and attack me personally. And you know what you say about he who assumes…..


  • Dear Anonymous (we’d love to know who you are),

    Thank you for your post. Of course, this is – as I stated – a simple thought experiment but its point is to represent reality in a very simple manner. A more complex analysis using a national household survey would come up with the same conclusion: the rich are the main beneficiaries of poverty targeting – due to the lower taxes they pay – while the poor benefit most from universal provision. This is an obvious and self-evident point, but one that is often not understood (even among many so-called social protection experts).

    Unfortunately, you make a number of errors:

    • You state that Gini co-efficients of 0.6 are unusual. Yet, here we are talking about a pre-transfer and pre-tax context. So, Sweden and Norway’s pre-tax and pre-transfer Gini would be 0.57, Denmark’s would be 0.56 and the UK’s 0.63. So, the imaginary country I created seems rather typical
    • You state it would have a poverty rate of 40%. That’s fine and not unusual at all. In most low and middle-income countries the vast majority of the population lives on less than $5 PPP per day, which many would argue would be extreme poverty (it’s the food poverty line in the USA). So, a high poverty rate – in particular in a pre-tax and pre-transfer situation – is not abnormal.
    • You state that the size of the universal benefit is small. But, at 5% of national income per capita, it’s a little higher than Mongolia’s universal Child Money programme (at 4% of GDP per capita).
    • You state that I underbudgeted the benefit, at 5% of GDP. But, a range of countries worldwide have universal pensions at around this value while universal child benefits are usually much lower cost.
    • You claim that no politician could sell a benefit of 10% of GDP to the public. Yet, average investment on social security in high income countries – much of which is on universal coverage benefits – is 12% of GDP and clearly popular with the ‘public’ (the ‘public’ really only oppose poverty targeted schemes, from which they are excluded). And, while you claim the ‘public’ wouldn’t accept 10% of GDP, my point was that it is the rich who would oppose this most. Most of the ‘public’ would be big winners if distribution were universal which is why, in high-income countries, a large proportion of government budgets is spent on universal health, education and social security schemes. Investing 10% of GDP on poverty-targeted schemes is, of course, non-sensical in a real world situation.
    • You seem to misunderstand my point on targeting and equal levels of tax. I was only noting that if I had taken into account realistic targeting errors and progressive taxation, then the rich would be even bigger losers and my argument would be even stronger.
    • Nonetheless, it would be good to find evidence of the “better targeting” that you claim is out there. Perhaps we can find it in high income countries with large formal economies. But, in low and middle-income countries we have only found a couple of examples of programmes with exclusion errors below 50% (and the errors in these countries are not much below that). You say mixed methods would be better. So, Kenya’s HSNP scheme uses community-based targeting and a PMT and has delivered more or less random selection. And, the World Bank has shown that, in Tanzania’s PSSN, which also uses a mixed methods approach, targeting performance in rural Tanzania is, again, little better than random. So, sorry, not much luck there with mixed methods!

    Anyway, we don’t know who you are but I’m guessing that you come from the richest 5% or 10% of your national population. So, it’s not surprising to find a rich person defending poverty-targeting: it’s almost certainly in your self-interest but it is most definitely not in the interests of the vast majority of the population of your country, including the poorest citizens.






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