By Pippa Norris (Harvard University)
This year sees the official end of the Millennium Development Goals (MDGs), which have been the heart of the development agenda, as agreed by the world’s governments in the United Nations at the beginning of the century. This begs the question: What will succeed the MDGs and how will progress be monitored?
The MDGs’ eight goals are measured through 21 targets and 60 indicators. Data assessing progress in achieving the MDGs suggest a mixed bag: some targets have been met, with progress since 1990 in child survival, literacy, and access to basic sanitation. Still, profound social disparities exist; so too does extreme poverty.[i] Proponents like Jeffrey Sachs press the case that technical know-how and learning can and has designed highly effective aid programs that save lives and strengthen development.[ii] By contrast, skeptics such as William Easterly claim that most large-scale aid projects are doomed to fail.[iii] Reductions in global poverty can also be attributed primarily to the remarkable economic growth improving the lives and security of millions living in China, rather than development aid per se. Most debate about aid effectiveness has focused on examining tangible local results attributable to specific projects, such as initiatives promoting girl’s schooling in Afghanistan, child immunizations against measles in Nepal, or the distribution of anti-malarial drugs and insecticide treated bed-nets in South Sudan. An extensive literature has sought to determine the broader impact of aid using national indicators, such as trends in poverty, child mortality, primary school completion rates, and the proportion of the population with access to clean water.
Members of the World Values Survey executive committee organised an expert meeting
at the United Nations on Monday. Ronald Inglehart is speaking. (Photo by Pippa Norris)
The MDGs’ eight goals are measured through 21 targets and 60 indicators. Data assessing progress in achieving the MDGs suggest a mixed bag: some targets have been met, with progress since 1990 in child survival, literacy, and access to basic sanitation. Still, profound social disparities exist; so too does extreme poverty.[i] Proponents like Jeffrey Sachs press the case that technical know-how and learning can and has designed highly effective aid programs that save lives and strengthen development.[ii] By contrast, skeptics such as William Easterly claim that most large-scale aid projects are doomed to fail.[iii] Reductions in global poverty can also be attributed primarily to the remarkable economic growth improving the lives and security of millions living in China, rather than development aid per se. Most debate about aid effectiveness has focused on examining tangible local results attributable to specific projects, such as initiatives promoting girl’s schooling in Afghanistan, child immunizations against measles in Nepal, or the distribution of anti-malarial drugs and insecticide treated bed-nets in South Sudan. An extensive literature has sought to determine the broader impact of aid using national indicators, such as trends in poverty, child mortality, primary school completion rates, and the proportion of the population with access to clean water.
As the era of the MDGs draws to an end, the international community is debating their replacement in 2016 by the Sustainable Development Goals (SDGs). It is proposed to expand the number of goals, and also the statistical indicators and specific targets adopted to monitor progress. The plan has been criticized as a ‘Christmas tree’ where there are so many indicators that monitoring will be a nightmare, overwhelming the capacity of national statistical offices to generate reliable data in many developing countries.[iv] Statistics on many of the standard indicators used by the MDGs are incomplete, even concerning basic matters, such as conventional measures of poverty assessed by the proportion of the population living below US$1 a day. There is often a substantial time-lag between data collection and policy analysis needs. Moreover, poverty and human development are increasingly understood as multidimensional phenomena, where household access to cash income provides a poor proxy indicator of social deprivation, such as access to essential medicines, feelings of neighborhood security, or experience of lived poverty. Official agencies in many fragile states with displaced populations and least developed economies have limited or no access to reliable decennial Census data, Labor Force or multi-topic Household Surveys providing estimates of multidimensional aspects of poverty. There remain cross-national inconsistencies in harmonizing the definitions, sources, time-periods, and methods used to estimate progress towards the MDGs.[v]
In response, several UN bodies have suggested that the international community should supplement official statistics by incorporating various innovative data sources associated with the ‘Big Data’ revolution. Hence the report, A World that Counts, recommends: “Better data and statistics will help governments track progress and make sure their decisions are evidence-based; they can also strengthen accountability. This is not just about governments. International agencies, CSOs and the private sector should be involved. A true data revolution would draw on existing and new sources of data to fully integrate statistics into decision making, promote open access to, and use of, data and ensure increased support for statistical systems.”[vi]
As one important aspect of this data revolution, many of the long-established cross-national social surveys can play a vital role by generating robust and reliable data useful for monitoring the SDGs. This includes studies such as the World Values Survey, founded in 1981 and now covering around 100 societies, and thus the grand-daddy of comparative social and attitudinal surveys by non-profit international organizations. It can also engage the Global-barometers covering several major world regions, such as the Afro-Barometer, and commercial surveys, such as the Gallup World Poll.
In response, several UN bodies have suggested that the international community should supplement official statistics by incorporating various innovative data sources associated with the ‘Big Data’ revolution. Hence the report, A World that Counts, recommends: “Better data and statistics will help governments track progress and make sure their decisions are evidence-based; they can also strengthen accountability. This is not just about governments. International agencies, CSOs and the private sector should be involved. A true data revolution would draw on existing and new sources of data to fully integrate statistics into decision making, promote open access to, and use of, data and ensure increased support for statistical systems.”[vi]
As one important aspect of this data revolution, many of the long-established cross-national social surveys can play a vital role by generating robust and reliable data useful for monitoring the SDGs. This includes studies such as the World Values Survey, founded in 1981 and now covering around 100 societies, and thus the grand-daddy of comparative social and attitudinal surveys by non-profit international organizations. It can also engage the Global-barometers covering several major world regions, such as the Afro-Barometer, and commercial surveys, such as the Gallup World Poll.
There are many advantages for the international community in tapping into reliable and well-established social surveys involving a representative sample of ordinary people living in each society. One is that these can furnish data on multidimensional experiences of lived poverty, such as self-reported access to clean water, to food security, and to medicine. Household access to cash income (such as living below US$1 a day) is an inadequate proxy for human development, especially in rural economies and exchange markets. Survey data can thereby enrich our understanding of the different types of severe challenges commonly facing poor households. Surveys are also well-designed to measure public perceptions of ordinary people, which is essential to monitor subjective feelings of security, attitudes towards social deprivation, or satisfaction with public services. In addition, reliable social survey data can also be disaggregated to examine inequalities among major social sectors, such as between women and men, young and old, as well as rural and low-income households. Concern about growing inequality within nations, even while GDP has risen, has pushed concern about this issue to the forefront of the development agenda.
At the same time official national statistical offices may be wary about using social surveys for several reasons. The size of the national samples used in most standard social surveys is far more limited than in official Household Surveys, or population estimates based on the official national Census. Nevertheless the sample size of 1,000 or more people in each society, used in social surveys, is widely accepted as standard in many public opinion polls and it is appropriate so long as the sampling method and fieldwork procedures are well-designed and the results are published along with transparent technical information about confidence intervals. Surveys also need to be careful in harmonizing demographic and social characteristics, so that standardized procedures are implemented across diverse societies. Moreover data should be freely disseminated in user-friendly format without cost as a public resource for the international community, with transparent technical details about sampling methods and questionnaire design, so that national statistical offices, local experts, NGOs, and scholars can access, scrutinize and analyze the data to reflect local priorities. By expanding the use of social survey resources in developing countries, this also strengthens local market research and statistical capacities, as well as potentially providing a voice for ordinary people in shaping development priorities.
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How could this data be used? Table 1 illustrates the potential for generating a Development Dashboard and applying the results from selected items contained in the 6th wave of the World Values Survey (WVS-6) as benchmarks to monitor progress towards the Sustainable Development Goals. WVS-6 covers sixty societies and the case of Ghana was chosen to illustrate some of the results. Thus, for example, the first SDG is to end poverty. To monitor this, the WVS asks: “In the last 12 months, how often have you or your family…Gone without a cash income?” One in ten Ghanaians reported going without a cash income in 2012, but the number rose to one fifth of the older population and one quarter of the lowest income households. Similarly, to monitor food security, the WVS asks: “How often have you or your family gone without enough food to eat in the last 12 months?” While one fifth of people living in Ghana reported going without food, the proportion rose to 30% among the older population and 43 percent of lowest income households. Similar social disparities can be observed across the range of indicators. Moreover concern about subjective security risks were far higher than the reported experiential risks in Ghana, for example there are widespread worries about losing a job or not being able to give children a good quality education. The Development Dashboard gives all actors – bilateral donors, local policymakers, civil society monitoring organizations, and ordinary citizens – the capacity to see transparently how far developmental goals and targets are being met – and where we are falling short of our aspirations.
How could this data be used? Table 1 illustrates the potential for generating a Development Dashboard and applying the results from selected items contained in the 6th wave of the World Values Survey (WVS-6) as benchmarks to monitor progress towards the Sustainable Development Goals. WVS-6 covers sixty societies and the case of Ghana was chosen to illustrate some of the results. Thus, for example, the first SDG is to end poverty. To monitor this, the WVS asks: “In the last 12 months, how often have you or your family…Gone without a cash income?” One in ten Ghanaians reported going without a cash income in 2012, but the number rose to one fifth of the older population and one quarter of the lowest income households. Similarly, to monitor food security, the WVS asks: “How often have you or your family gone without enough food to eat in the last 12 months?” While one fifth of people living in Ghana reported going without food, the proportion rose to 30% among the older population and 43 percent of lowest income households. Similar social disparities can be observed across the range of indicators. Moreover concern about subjective security risks were far higher than the reported experiential risks in Ghana, for example there are widespread worries about losing a job or not being able to give children a good quality education. The Development Dashboard gives all actors – bilateral donors, local policymakers, civil society monitoring organizations, and ordinary citizens – the capacity to see transparently how far developmental goals and targets are being met – and where we are falling short of our aspirations.
Thus post-Rio, the world is facing multiple challenges in meeting developmental goals. One of the lessons from the MDGs is that setting specific goals and concrete targets can be a useful stimulus to focus attention on several critical problems facing the world’s poorest societies, encouraging the delivery of results and thereby holding governments to account for their investment of development aid. But the results-based approach is data intensive. Better monitoring requires taking advantage of the leaps in data availability, which have become widely available through the information revolution in recent decades, including drawing upon social surveys as one important source of evidence in the international community’s toolkit.
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[ii] See Jeffrey Sachs. 2005. The End of Poverty New York: Penguin.
[iii] William Easterly. 2001. The Elusive Quest for Growth. Cambridge, MA: MIT Press. William Easterly. 2006. The White Man’s Burden. NY: Penguin; Dambisa Moyo. 2010. Dead Aid: Why Aid Is Not Working and How There Is a Better Way for Africa. NY: Farrar, Straus and Giroux. For current debates on the topic in the international community, see OECD DAC.
[iv] The Economist. 29 March 2015. ‘Proposed sustainable Development Goals.’
[v] United Nations Inter Agency and Expert Group (IEGA). 2013. ‘Lessons Learned from MDG Monitoring From A Statistical Perspective.’
[vi] United Nations Inter Agency and Expert Group (IEGA). 2014. A World That Counts (http://www.undatarevolution.org/report)
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