Europe’s social polarisation and the generational struggle

This post, written by Bruegel's Olga Tschekassin, discusses the latest results on Europe's poverty rates, unemployment rates and income inequalities. The post is a part of the Wikiprogress Series on Jobs and Earnings.

According to the latest Eurobarometer survey on the social impact of the crisis, 80% of respondents believe that poverty has increased in their country over the past 12 months. Over 30% of respondents in Greece, Latvia, Lithuania, Bulgaria, Romania and Hungary reported that their household ran out of money to pay for ordinary bills, food and other daily consumer items at some point during the previous 12 months. These alarming numbers are reflecting the perception of European citizens. But what do indicators measuring different dimensions of poverty and inequality actually show?

The best publically available indicator to assess poverty is the ”Severe Material Deprivation Rate” (SMDR). It is an absolute measure of poverty and represents the proportion of people who cannot afford at least four out of nine basic needs, like utilities, regular hot meals or heating to keep the home adequately warm. As you can see in the interactive map below, there is a strong dispersion across Europe. While Bulgaria has the highest rate (44.1%), in Luxembourg only 1.3% of people are severely affected by a lack of resources. The average rate in EU27 countries increased from 9% percent in 2007 to 9.9% in 2012. Even though this increase does not seem to be as dramatic as the survey implies, it is worth highlighting that a share of almost 10% is unacceptable and against the objective of promoting the well-being of EU citizens.

(To view an interactive version of this map, see the original post here.)
 

There were opposite developments for young and old people in the EU: the SMDR stood at 11.7% for those under 18 at the end of 2012, while the rate for the elderly (over 65) reached 7.5%. The evolution of these rates since 2007 is divergent: Between 2007 and 2012, in 20 out of 28 EU countries the elderly SMDR declined on average by 4.5 percentage points (pp). At the same time, however, in 16 out of 28 countries the children SMDR has increased on average by 4.4 pp. Therefore, a generational divide is emerging: while the fall in severely materially deprived elderly people is a welcomed development, the adverse development for children is worrying.

Looking at the unemployment rate, we observe an increase in all EU countries in the period 2007–2012 with the exception of Germany, while the rate remained practically unchanged in Austria, Malta, Finland and Poland. The EU28 average unemployment rate stood at 7.2 % of active population in 2007. By the third quarter of 2013, this rate had increased to 10.9%. The countries with the lowest unemployment rates are Austria, Germany and Luxembourg, as opposed to Greece, Spain, Croatia, Cyprus and Portugal, where the rate is very high. Overall we note that there was an increase in the South-North divide in terms of unemployment, which has reached unacceptably high levels in several south European countries and leads to more polarisation across Europe.

Directly related to this indicator is the share of people living in jobless households, which has increased significantly throughout the crisis. The situation is especially alarming in Ireland, where every fifth child lived in 2012 in a household where no one worked. The share of such children was also higher than 15 % in Bulgaria, the UK and Hungary. Besides, the share of young people not in employment and not in any education and training (NEET) more than doubled in seven countries. The reality for young people aged between 15 and 24 years is worst in Greece, Spain and Croatia.

Using the Gini coefficient as an indicator for inequality, we observe the highest levels of inequality in 2012 in Latvia, Spain, Greece and Portugal, while the lowest rates are reported in Slovenia, Czech Republic and Sweden. As Zsolt Darvas and Guntram Wolff outline in their Policy Brief published on the 1st of April 2014, inequality in most advanced economies has been rising since about 1980 and could have been a reason for the pre-crisis increase in household debt and the consequent consumption squeeze during the crisis.

Therefore, developments of various social indicators show a gloomy picture. Social pain has already undermined the citizens’ trust in the EU and their own governments. This could devitalize the acceptability of painful structural reforms and fiscal consolidation measures and, in turn, diminish the reform momentum or even lead to political instability.

- Olga Tschekassin

This blog first appeared here at Bruegel.org on 1 April, 2014.
 

See Also:

European Network on Measuring Progress

Quality of life in Europe: Subjective well-being

Progress Initiatives in Europe

The European Centre for Social Welfare Policy and Research

 

Ending chronic poverty: Breaking down a policy no-man’s land

This post by Marie-Claire Tuzeneu, Production Manager of the Development Co-operation Report at the OECD, provides a first look at Andrew Shepherd’s piece for the OECD Development Co-operation Report 2013.

The previous two blog posts on the Development Co-operation Report (DCR) 2013 – which discussed key points from Andy Sumner and Li Xiaoyun’s chapters – focused on what is needed to help people get out of extreme poverty (defined as an income of USD 1.25 per day). In his chapter “How do we get to zero on poverty – and stay there?”, Andrew Shepherd (Chronic Poverty Advisory Network, Overseas Development Institute) emphasises the importance of also developing policies to support those that have escaped extreme poverty and are just above the poverty line, thereby ensuring that that they don’t fall back into extreme poverty. To achieve this, he calls for a post-2015 framework that directly addresses and includes targets for ending chronic poverty.

Who are the chronically poor? Within his chapter, Shepherd defines chronic poverty as “extreme poverty experienced over many years, a lifetime, or perpetuated from generation to generation”. Chronic poverty is often multidimensional in nature and, therefore, cannot be fully captured by measures of income poverty alone. Using a measure combining income and consumption, the 2008-09 Chronic Poverty Report estimated that there are currently between 320 and 443 million chronically poor people.

What policies could help end chronic poverty? The local context – as well as related economic, societal, political or institutional factors - plays an important role in whether or not a household is able to escape extreme poverty over the long term. These factors may create barriers that make it more difficult to end chronic poverty. These barriers cannot be removed through “Business as usual” policies and programmes. Shepherd calls for a root-and-branch re-orientation and reprioritisation of policies and programmes under the following four categories:

1.   Social protection: Solid systems of social protection must be backed by national political commitment. For example, employment guarantees must be extended to jobs within the informal economy so that all employment is an avenue out of poverty, not just a survival option.
2.  Growth that reaches the poorest: Within the agricultural sector, policies should focus not only on crop productivity, but also on building the asset bases of poor farmer households. Policies and programmes must be put in place that help increase access to electricity by reducing the upfront costs for families to connect to electrical grids.
3.    Human development for the hard to reach: For this category, policies in a wide variety of areas – ranging from health to gender equality – must be revisited. Taking the example of education, current development programmes, which focus on increasing attendance rates for primary education, should be expanded to also include pre-school and post-primary education.
4.   Transformative social change: Regardless of the specific model chosen to support the chronically poor, a country must have “far-sighted political leadership with a strong nation-building plan” in order for its programmes and policies to be effective.

What targets and goals should be included in the post-2015 framework? Shepherd calls for a post-2015 framework that focuses on eradicating extreme poverty, arguing that “If the factors keeping people poor over long periods of time (or in chronic poverty) are not explicitly addressed, there is no chance of getting to or near zero.” To that end, the post-2015 goals and targets should not just focus on USD 1.25 per day income poverty, but should also look at the poverty lines just above that threshold. Under the current system, those households that have escaped USD 1.25 per day income poverty and are living on USD 2 or USD 4 per day fall within a “policy no-man’s land”. If programmes and policies are not also developed to support those just above the extreme poverty line, they risk falling back into extreme poverty. To address these concerns, Shepherd would propose a series of three targets that are illustrated in the figure below. While this specific set of targets only addresses income poverty, it could also be adapted and applied to the other dimensions of poverty.

Ending chronic poverty and other topics explored in the Development Co-operation Report 2013: Ending Poverty will be discussed in a live panel debate, which will be held in London on 5 December and will be viewable via live-streaming. For more information, visit the Intelligence Squared event page or follow the discussion on Twitter using #povertydebate.

A dynamic post-2015 goal: Eradicate extreme poverty

Note: Target 1 should be combined with Target 2 for each country, since some countries need to do more of 1 and less of 2, and vice versa.

Source: This figure is taken from Chapter 4 of the DCR, “How do we get to zero on poverty – and stay there?”, by Andrew Shepherd.

- Marie-Claire Tuzeneu

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The New Geography of Poverty - OECD Development Cooperation Report 2013

This post by Valentin Lang, Policy Analyst at the OECD provides a first look on Andy Sumner’s piece for the OECD’s Development Cooperation Report 2013. This blog is part of the Wikiprogress series on post-2015.

A critical time for the future of global development has begun. In September, the international community gathered at the United Nations General Assembly in New York to launch the final phase of the international process that will lead to a new global development framework for post2015. The development community has started vigorous work on new approaches to end poverty. A much awaited publication in this regard is the OECD’s Development Cooperation Report 2013: Ending Poverty, the subject of a live panel debate in London on 5 December 2013. 

In his contribution to the report, Andy Sumner, Co-Director of King’s International Development Institute, shows that the global patterns of poverty have changed fundamentally over the past few years. He argues that we won’t be successful in tackling this new pattern of poverty with our current approach to international development. The world economy has changed and so has poverty. The next development framework has to account for this and has to initiate new forms of development cooperation. According to Sumner, a “new bottom billion” lives in middle-income countries. Whereas in 1990, most extremely poor persons lived in a low-income country, today more than 70% of them live in middle-income countries. In the next few years, some of these countries could even develop into high-income countries if they meet IMF growth forecasts.

In short, we see the geography of poverty shifting radically

This new world of poverty consists primarily of countries whose gross national income per capita gives them middle income status but whose “nothing magically happens when a country crosses an arbitrary line into a new classification based on per capita income” population comprises large numbers of extremely poor. Apparently, mere economic growth does not guarantee progress in poverty reduction. Today, the poverty problem is inextricably linked to the inequality problem.

Sumner draws some important conclusions from these remarkable findings. He argues that if we want to eradicate poverty in the future, the traditional approach of “development aid” that flows from OECD countries to the least developed countries is by far not enough. Development cooperation has to realise that. Development cooperation with countries whose populations suffer from poverty should therefore not be less intense only because of their middle-income status – but it should be different:

Development cooperation with middle-income countries can draw on a wider range of resources and policy options than low-income countries. Middle-income countries have a larger tax base and have more domestic resources available for work in poverty reduction. The credit ratings of middle-income countries allow them to borrow capital from financial markets. Therefore, development cooperation can and must take new forms beyond ODA.

For instance, Sumner points to the possibility that providers of development cooperation could shift from grants to concessional loans and to the co-financing of global and regional initiatives. Knowledge sharing and joint policy-related research will also have to become more important. Another central challenge for providers of development cooperation is to focus more on policy coherence for development. They must better co-ordinate development and non-development policies and ensure that the latter do not undermine the former.

At the same time, a focus on inequality has to be a key feature of future development cooperation. Combating global poverty means combating inequality inside countries. Mere economic growth will not suffice. It must be inclusive and must be connected to socio-economic policies that tackle inequalities: “Growth with redistribution is the way forward.” Sumner’s analysis, thus, points to the fact that it seems inevitable to address inequalities in the post-2015 development framework.

The new geography of poverty requires new policies to fight it and Andy Sumner’s contribution to the OECD’s Development Cooperation Report 2013 leads the way ahead.

Could Big Data provide alternative measures of poverty and welfare?

This is the fifth in a series of ODI Development Progress blogs that debate how a post-2015 framework ought to measure poverty - find out more.

’Google knows more, or is in a position to know more, about France thanINSEE [National Institute of Statistics and Economic Studies]’, two French scientists wrote in an op-ed published in Le Monde in January. In the context of developing countries, the question raised by this bold claim is: could Big Data help us know more about poverty and welfare, including, or perhaps especially, in places where the dearth of traditional data is often turning poverty monitoring and forecasting into an exercise in guesstimation? Could the Big Data revolution contribute to fixing part of the ‘statistical tragedy’?

The underlying argument is that these new kinds of data, stemming from individuals and communities as they go about their daily lives, contain insights into their experiences that we can mine to help them in return. This idea can be traced back to a much-cited 2009 paper, which found that light emissions picked up by satellites could track GDP growth.

Since then, widely cited evidence that Internet-based data could be used to monitor inflation in real-time and allow digital disease detection, as well as construct economic indicators to forecast the present, and build a’real-time growth index’, among many other applications, have given weight to the promise. Cell-phone Call Detail Records (CDRs), which capture the time, location, recipients’ location etc. of each call, have also helped model malaria spread, unveil reciprocity giving in the aftermath of disasters, and study internal migration.

So it seems only logical, and very appealing, to claim that the same data and tools could be deployed tomonitor poverty, and may even be conducive to a leap-frogging of statistical systems. Although the term Big Data is absent from the report of the High-Level Panel on the post-2015 framework, it is hard not to read it between the lines of the development data revolution it sketches.

But conceptual clarity, practical guidance, ethical considerations and innovative foresight have too often been lacking, leaving an open field for sceptics who have long stressed the risks and challenges of Big Dataor insisted that the real revolution is small data (or long data). Findings that Google got flu wrong this year in the US have cast additional doubt on Internet-based data’s reliability, representativeness, and thus relevance, to inform policy decisions, while the revelations about PRISM have raised concerns over privacy to a whole new level. But recent publications and debates have shed direct light on some of the specific promise, challenges and requirements of leveraging Big Data to improve current, and perhaps develop alternative, measures of poverty and welfare.

In particular, a paper showed that cell-phone records from a major city in Latin America could help predict socioeconomic levels, poverty’s first cousins. This was done by matching CDR-inferred behavioural data and official statistics on socio-economic levels, using supervised machine learning techniques to unveil how differences in socioeconomic levels typically ‘showed’ in cell-phone data, and back. This example illustrates a key and seemingly purpose-defeating requirement for developing models and algorithms able to translate digital data into indicators of the social world: the availability of ‘ground truth’ indicators of the social world (such as survey data) used to build and validate the models.

But this does not mean that Big Data is useless, or rather superfluous, in such contexts: indeed, assuming a sufficiently high and time-resistant level of accuracy (internal validity), CDR data would then provide some sense of changes in socio-economic levels that would not get captured until the next official survey.

The problem is evidently more acute in places where no such data exist, ie precisely where alternative indicators are most needed. One avenue would be to apply ‘matching’ rules developed elsewhere to local CDRs. But the resulting ‘alternative’ indicators will be highly conjectural because the underlying algorithm may not pass the test of external validity: applying a model matching CDRs and socio-economic levels developed using CDRs and Demographic and Health Surveys (DHS) data from Côte d’Ivoire to a neighbouring country, may yield misleading values because of cross-country differences. In such a case, the question is: is any data better than no data at all? 

Another recent paper studying the impact of biases in mobile-phone ownership on estimates of human mobility inferred from CDRs is also worth mentioning for two reasons. One is its key finding: that CDR-based estimates of mobility appeared to be surprisingly robust to substantial biases in phone ownership, which may turn out to be equally true for measures of welfare. The other is its research question and method: asking how accurate a picture of the social world some Big Data streams may paint, given, or in spite of, their inherent biases, drawing (again) on survey data as ’ground truth data’.

Noteworthy investment and progress are also visible in the critical strand of research (and advocacy) on privacy-preserving analysis. In particular, researchers, using CDRs for mobility analysis too, have developed an algorithm that uses an emerging technique known as ‘differential privacy’ that injects ‘noise’ into the model at points in order to reduce the likelihood of individual re-identification.

Although not directly concerned with poverty these papers are important because they point specifically to the methodological avenues and leads that need to be explored to develop privacy-preserving Big Data capacities that may, in time, help monitor poverty.

It is also crucial to note that Big Data is not only about data production (and analysis), but also about data consumption (and exchange). If we care about adequately monitoring human welfare, we should account for the consumption of free data. Think of the hours spent on social media in cyber-cafés, and increasingly on cellphones, around the world, that provide a ‘consumer surplus’ not captured in any official statistics. The caveat may not apply to the poorest of the poor, but there is no reason to consider that a problem receiving increasing attention in developed countries is irrelevant to developing countries where Internet penetration is growing much faster. In other words: Big Data do not stand apart from the quantities and phenomena to be measured but add to the measurement problem.

The related, and perhaps even more critical, point here is that the rise of data-driven activities is deemed to render GDP (and GDP per capita) less and less relevant over time as the measure of human welfare it was never intended to be. The argument that monetary poverty and GDP per capita are very crude indicators of human progress is not new, but Big Data may prove instrumental in devising true alternative measures.

In particular, the growing availability of such rich individual data about people’s behaviors and desires will offer new options for communities to capture, monitor and improve their own welfare in ways that mayincrease local empowerment through Big Data—very far from the misleading notion that Big Data is about offering a 30,000 foot view of the world.

A few take-away messages emerge. First, for the purposes of poverty monitoring or development more broadly, “Big Data” is not about size, but about the qualitative nature of these data trails—what some refer to as “digital breadcrumbs”. Second, Big Data is not even primarily about the data but about the carefulness of their analysis, which requires even more, not less, contextual and ethnographic grounding. Third, Big Data is also about data consumption, not just production. Lastly, much more conceptual, empirical and methodological work is needed before Big Data can be leveraged concretely and safely for poverty monitoring; but Big Data may in time fundamentally change how we measure, and perhaps even fight, poverty.

Other contributions to the ODI Development Progress debate on measuing poverty come from Martin Ravallion on two goals for fighting poverty, Lant Pritchett on the case for a high global poverty line, Stephan Klasen's argument for internationally coordinated national poverty measurement, Sabina Alkire's proposal for a multidimensional poverty index post-2015 and Amanda Lenhardt on the need for disaggregated poverty measurement.


Emmanuel Letouzé is a PhD Candidate at UC Berkeley and a regular consultant for the UN and the OECD, currently serving as a Non-Resident Adviser at the International Peace Institute and an adviser on Big Data for the OECD-Paris 21 initiative. He previously worked as senior development economist on the UN Global Pulse team where he wrote 'Big Data for Development: Challenges and Opportunities'

Measuring poverty below the averages

This is the fifth in a series of blogs from the ODI that debate how a post-2015 framework ought to measure poverty - find out more.

Among the achievements of the Millennium Development Goals (MDGs), the halving of extreme poverty has been celebrated as the great success. The target of reducing the number of people living on less than $1.25 a day is expected to be reached globally, if not surpassed, by 2015. We cannot take this figure at face value though: this progress has not been evenly distributed, and China’s success boosts the average of overall global poverty reduction. But these discrepancies aside, it is reasonably accepted that income poverty is declining, at least to some degree, in all major regions of the world.

At the national level - the standard focal point for most measures of poverty - the picture is slightly less clear, but overall we tend to see a positive trend. The classic conception of nationally distributed poverty is distorted however by the fact that it is no longer concentrated in low-income countries, the class of countries conventionally singled out for high rates of impoverishment. A number of high-poverty countries have graduated to middle-income status, which means it is less easy to capture poverty by measures of average income or consumption.

The changing dynamics of inequality, both across and within countries (see Milanovic, 2012 for an overview), further complicates our view of poverty. Aggregate measures of poverty such as average consumption rates and poverty head-count statistics, while instructive of absolute poverty levels, fail to capture uneven distributions of income or uneven progress on non-income dimensions of poverty.

The distortions caused by aggregate measures of poverty have led us back to the drawing-board, asking: what exactly do we want to measure with poverty statistics? But a more important question is: what will we use these poverty statistics for? If intended as a tool for national policy-makers to make informed decisions about strategies to reduce poverty within their societies, then it makes sense to look beyond national averages towards poverty rates among particular groups and at different income levels.

Narrowing the lens of poverty measurement to the sub-national-level is challenging, not least because the data is often lacking to do so, but if we wish to address the barriers facing the remaining 50 per cent of the world’s poor who have not yet been raised out of extreme poverty, then this is where the measurement of poverty can be most effective.

There are three useful ways to look below the averages, two of which are reasonably straightforward and can be achieved with the statistics already at hand, and one of which will require more effort to measure given its context-specificity. These measures are presented here as complements to, rather than replacements for, existing aggregate measures of absolute poverty, since both types of measures are instructive for the setting of national and international priorities.

1. The share of the poorest quintile in national consumption. This measure can be found in the MDG framework already, though it has not been used. An extension of this would be to look further below the poorest quintile, to consider the bottom 10 per cent and 5 per cent’s share of national consumption. These measures capture two important elements of poverty.

• They draw out the distributional aspects of income at a national level, thereby highlighting inequalities in income shares held by different segments of the population. We might consider this a measure of relative poverty. Poverty and inequality are not mutually exclusive, and the added appeal of this simple measure is that it can be used to examine both.

• They allow for a disaggregation of the population into income groups relevant for policy-makersin their design of strategies to address the structures that keep people impoverished.

In a recent blog focusing on the inequality dimensions of these poverty measures, we drew upon the case of Brazil to show how aggregation can distort our view of poverty and inequality trends. Poverty and inequality have both declined over the past 20 years by most accounts, but the income share held by the bottom decile in Brazil has increased only marginally and from a very low point.

This perspective draws our attention to situations of poverty that are likely to persist amidst wider gains in income growth. The case of Brazil points to the need for retaining absolute measures of poverty, as these are still useful in explaining the country’s laudable achievements in overall poverty reduction over the past 20 years, but also the need to include measures accounting for the distribution of progress alongside them.

Disaggregated income distributions in Brazil 1981-2009

(Lenhardt & Shepherd, 2013)

2.  A comparison of the outcomes of these disaggregated income groups on indicators of human development such as education, health, hunger and employment. We have shown that recent gains in education access, another highly celebrated outcome of the MDGs, have not been evenly distributed within countries when comparing across different income levels. This research showed that the poorest women were indeed reporting more years of education in the 2000s than in the 1990s, but their progress lagged behind gains made by the median income group. Progress was also slower in indicators of early marriage, women’s empowerment and child mortality.

Tracking gains across the multiple dimensions of poverty among different income groups will allow policy-makers to ensure that the policies and programmes they have introduced to tackle these issues are indeed reaching the people in greatest need of them.

3. The horizontal dimensions of inequality which result in higher rates of impoverishment among particular segments of society including ethnic minorities, spatially disadvantaged communities and disempowered women. Marginalised groups, as identified within country contexts, could be disaggregated from national poverty statistics and their group averages on income and human-development outcomes compared to the national average or median for those indicators.

In combination with absolute measures, these three simple disaggregations would highlight those segments of a given society that are most disadvantaged and would allow policy-makers to track progress on poverty reduction among those more likely to face social, political and institutional barriers to broader poverty-reduction efforts.

Other contributions to our debate on measuing poverty come from Martin Ravallion on two goals for fighting poverty, Lant Pritchett on the case for a high global poverty line, Stephan Klasen's argument for internationally coordinated national poverty measurement and Sabina Alkire's proposal for a multidimensional poverty index post-2015.

Amanda Lendardt is Development Progress' new Research Officer. Her research focuseses include intersecting inequalities and discourses surrouding the inclusion of inequality on the post-2015 agenda.  Prior to joining ODI, she conducted research on smallholder farmer market access in Indonesia.

Week in Review

Hello Wikiprogress followers and welcome to this Week in Review! This week’s highlights include a UN report on human rights in the context of the post-2015 agenda, an update from UNICEF on global progress on sanitation and drinking water and an Oxfam report on risk and poverty reduction.

Released this week, the UN’s Who will be Accountable? – Human Rights and the Post-2015 Development Agenda – calls on countries to ensure that the post-2015 development agenda focuses on equality, social protection and accountability, noting that one billion people around the world are still living in poverty. 

“The rise of inequality has severely undermined the achievements of the Millennium Development Goals, or MDGs,” UN Spokesman, 21^st May 2013

Public sector innovation and e-government Egypt

The “OECD E-Government Review of Egypt” assesses Egyptian e-government policies and implementation, and makes recommendations for future actions. The report highlights Egypt’s progress and proposes that to enhance the use of ICTs in the public sector Egypt should undertake a number of measures. Find out more!

No Accident - Resilience and the Inequality of Risk – This report from Oxfam stipulates that governing bodies and aid agencies must challenge the politics and power at the heart of the increasing effects of climate change, growing inequality and people’s vulnerability to disasters. Oxfam highlights the increasing threat of various major external risks and points out that the majority of these are actively dumped on poor people, with women bearing the brunt because of their social, political and economic status. 

Progress on Sanitation and Drinking Water - 2013 Update – UNICEF’s annual report card presents country, regional and global estimates on improvements (or lack of them) in access to drinking water and sanitation. According to the publication, the world will not meet the MDG sanitation target of 75% and if current trends continue, it is set to miss the target by more than half a billion. To find out more about sanitation inequality, read our recent Progblog article on the subject.  

The right poverty measure for post-2015 – is part of a series of blogs that debate how a post-2015 framework ought to measure poverty. This article by Stephan Klasen, Professor of development economics and empirical economic research at the University of Göttingen, puts forward a proposal for internationally coordinated national poverty measurement. 

Thanks for checking in - we are pleased to inform you that our theme of the month in June will be Environment so we look forward to bringing you articles, blogs and Week in Reviews related to the subject in the coming weeks!

The Wikiprogress Team