1 The Diversity of MDG Progress
Author: International Monetary Fund
Language:
English
Keywords:
MISC RPT; MISC; biodiversity loss; ecosystem goods; MDG performance; area ecosystem service; policy reform; CPIA index; Global; Sub-Saharan Africa; East Asia; Asia and Pacific; South Asia; IDA country; lagging country; low-income country; country diversity; poverty target; Hunger and malnutrition
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Abstract

With less than five years left to achieve the Millennium Development Goals (MDGs), the international development community is showing renewed urgency to assess the various development efforts, especially in light of the recent global economic crisis and the still-fragile recovery. What are the prospects and challenges for reaching the goals? Answers are clearly linked to the complex tapestry of progress that lies below the global numbers.

With less than five years left to achieve the Millennium Development Goals (MDGs), the international development community is showing renewed urgency to assess the various development efforts, especially in light of the recent global economic crisis and the still-fragile recovery. What are the prospects and challenges for reaching the goals? Answers are clearly linked to the complex tapestry of progress that lies below the global numbers.

The Global Monitoring Report [GMR] 2011 extends the forward-looking analysis started in last year’s report by examining more carefully the diversity of progress and its implications for the remaining gaps and challenges. It complements that report’s analysis of the impact of the global crisis on the MDGs.

A key observation on the progress toward the MDGs is its diversity. At the aggregate and regional levels, low-income countries, particularly fragile states and those in Sub-Saharan Africa, lag because of a combination of low starting points and difficult circumstances. Behind those aggregate numbers, however, the great diversity of performance across indicators, countries, and groups of countries requires further analysis. That is the subject of this chapter.

Several questions demand answers: How many countries are off target, and how far are they from the goals? Why are some countries behind? And what factors are key to improving the odds that off-target countries can reach the goals?

Looking under global progress

The global numbers tell a familiar, mixed story (figure 1.1). The latest information confirms that progress toward the MDGs remains substantial on gender and education, access to safe drinking water, extreme poverty, and hunger, in that order. On current trends and despite the recent global economic crisis, the world is on track to reach the global target of cutting income poverty in half by 2015. Thanks to rapid growth in China, the East Asia and Pacific region has already halved extreme poverty. Developing countries will also likely achieve the MDGs for gender parity in primary and secondary education and for access to safe drinking water, and will be very close on hunger and the primary education completion rate.

Progress continues to lag in health-related development outcomes, such as child and maternal mortality and access to sanitation. New data and methodologies indicate much more progress than previously thought in reducing maternal mortality, but that is still the MDG that lags the most. On current trends, the world will likely miss these three targets by 2015. Most regions are off track, but East Asia and the Pacific, Latin America and the Caribbean, and Europe and Central Asia are doing somewhat better than others.

FIGURE 1.1
FIGURE 1.1

Current global distance to the MDGs is wide ranging

Source: World Bank staff calculations based on data from the World Development Indicators database.Note: Distance to goal achieved in this graph is a weighted average of the latest indicators, using population weights in 2009. In this and other graphs in the chapter, the focus is on MDGs with well-defined targets and time-series data to assess progress.

Poor countries and regions tend to lag in attaining the MDGs. As a group, they lag on all the MDGs and are unlikely to reach a single target by 2015. Generally, fewer low-income than middle-income countries are on target to achieve each MDG (figure 1.2). The number of countries in each income group does not differ greatly, so this is not the result of the distribution of countries. In fact, about 40 countries are currently classified as low income, compared with 54 lower-middle-income and 48 upper-middle-income countries (see appendix 1 for the classification). Nor do the results arise from missing data in low-income countries because the availability of data also shows little variation among income groups (see appendix table A1.1). At the global level, the latest poverty data remain at 2005, and box 1.1 explains why.

FIGURE 1.2
FIGURE 1.2

Fewer low-income countries are on track to achieve the MDGs

Source: World Bank staff calculations based on data from the World Development Indicators database.Note: The number above each bar refers to the number of countries attaining that MDG.

The pattern more likely stems from the starting points—especially incomes, which matter greatly in attaining the MDGs. As several studies show, recent achievements are obscured by poor past performance and by the disproportionate challenges the MDGs pose in many Sub-Saharan African and other poor countries.1 The longer the distance to the 2015 targets, the more ambitious the goals appear and the steeper the path to achieve them. Ravallion and the World Bank and IMF discussed how higher starting poverty rates are generally associated with a lower responsiveness (elasticity) of poverty to economic growth.2 Countries in Sub-Sa-haran Africa implemented reforms later than others and therefore benefited much later from accelerating economic growth. However, after showing no decline for much of the 1990s, Sub-Saharan Africa’s poverty has fallen steeply since 2000.

Poverty data and projections

New poverty projections at the World Bank are the result of several changes—new and more recent household surveys, updates of historical consumption per capita from national accounts, and a new forecast of per capita consumption growth. For this report, the poverty forecast includes 62 new household surveys out of a total of 123 countries, which reflect methodological advances in newer surveys and changes in the underlying distribution of income not measured by changes in mean income or expenditure. The forecast therefore captures changes in income inequality in the new surveys. However, it assumes inequality is unchanged in other countries. Some of the effects of food and fuel price shocks in 2008 are captured in the new surveys.

Based on the economic projections of developing countries at the International Monetary Fund and the World Bank, the world remains on track to reduce by half the number of people living in extreme poverty. The number of people living on less than $1.25 a day is projected to be 882.7 million in 2015, which is lower than the previous estimate of 918 million (see the table on the next page). The decline results mainly from data changes for India, which showed a more rapid growth of per capita consumption than previously reported in the national accounts. This estimate will be updated further when India’s forthcoming household survey for 2008 is completed. That survey will provide a more accurate estimate of household consumption for different income groups. Although the poverty numbers for East Asia and the Pacific remain relatively stable, China’s poverty rate and number (at the poverty level of $1.25 a day) have decreased further, based on the new 2008 household survey and a higher growth rate of its household income. Projections for Sub-Saharan Africa are slightly better than previously estimated: its extreme poverty at $1.25 a day is projected to be 35.8 percent in 2015, lower than the previous forecast of 38.0 percent, because of its higher recent growth performance and growth forecast. However, several of Africa’s household surveys for 2008 still need to be completed (see the discussion of gaps below).

The new household surveys employed in the forecast cover about 43.1 percent of the population in developing countries in 2008 and 7.6 percent in 2009 (see the figure on the next page). However, gaps for 2008-10 household surveys remain at the regional level: South Asia (pending India’s new household survey), 10.8 percent of population is covered; Middle East and North Africa, 19.1 percent; Sub-Saharan Africa, 20.1 percent; Latin America and the Caribbean, 84.1 percent; East Asia and the Pacific, 90.3 percent; and Europe and Central Asia, 94.4 percent. Efforts are already under way at the World Bank to close remaining gaps before the end of 2011 to complete and update the time-series estimate of poverty at the global and regional levels for 2008.

Estimates of poverty reduction on a poverty line of $1.25 and $2.00 a day, by region

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Source: World Bank staff calculations from PovcalNet database.
ch01ufig01

Population coverage of the latest available household surveys is increasing

Source: World Bank staff calculations based on household data from the PovcalNet database.

Middle-income countries—both lower and upper—generally exhibit the best performance. For example, 80 percent of countries in the upper-middle-income bracket (23 countries) have achieved or are on track to achieve the extreme poverty target. Similarly, 72 percent of lower-middle-income countries (34 countries) are reaching the target for gender parity in secondary education. In one area, however—gender parity in primary education—progress in both low-income and middle-income countries is substantial.

Latin America and the Caribbean is showing excellent results and leading in several indicators: hunger, primary education completion, gender parity in secondary education, access to safe drinking water, and access to sanitation. Even so, it faces serious challenges on maternal mortality, with just 10 percent of countries (three countries) that have reached or are on track to reach the 2015 target (figure 1.3).

East Asia and Pacific is progressing in many areas, particularly on education, gender parity, and access to safe drinking water. Its performance is particularly good for gender parity in secondary education, where 82 percent of countries (14 countries) are on target.

South Asia is also closing the development gap. Its performance is encouraging for primary education completion, gender parity, maternal mortality, and access to safe drinking water, although performance needs to improve for extreme poverty and hunger.

Eastern Europe shows important progress on extreme poverty (the region’s countries account for 32 percent of countries on target). Advances are also significant for child and maternal mortality. Challenges remain, however—particularly in Central Asia, where progress on extreme poverty, child and maternal mortality, and access to safe drinking water is relatively low. For instance, no Central Asian country is on track to achieve the child mortality goal; but the target is still within reach or close to becoming on target for five countries in the subregion (see below and appendix 1 for a discussion of the concept, close to becoming on target).

The Middle East and North Africa is performing relatively well on gender parity in secondary education and on access to sanitation. However, it needs faster progress on extreme poverty, hunger, and maternal mortality.

FIGURE 1.3
FIGURE 1.3

Countries on target to achieve the MDGs, by region

Source: World Bank staff calculations based on data from the World Development Indicators database.

Sub-Saharan Africa lags the other regions but can point to some encouraging results. Progress is quite good on extreme poverty (9 countries), hunger (8 countries), gender parity in primary education (27 countries), and access to safe drinking water (15 countries). Goals related to child and maternal mortality, access to sanitation, and primary education completion require stepped-up efforts.

Several low-income countries are doing well. A look beneath the aggregate global statistics shows not just middle-income countries doing well, but many low-income countries, too (table 1.1). A recent study by Leo and Barmeier confirmed that progress in individual African and poor countries was surprisingly strong.3

TABLE 1.1

Several low-income countries are achieving the MDGs

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Source: World Development Indicators database (as of March 2011).Note: List of low-income countries is based on the new World Bank classification for fiscal year 2011 (see appendix 1).

Variation behind the aggregates. The typical global and regional summaries amass data for countries of dissimilar development and types—fragile, low-income, and middle-income countries. For example, the Europe and Central Asia region covers such middle-income countries as Albania and Bulgaria and such low-income countries as Tajikistan and Uzbekistan. Among the developing countries in Sub-Saharan Africa, some are middle-income countries (such as Mauritius and South Africa); some lower-middle-income countries (such as Angola and the Democratic Republic of Congo) are resource rich, but their levels of development may be closer to those of low-income countries. Progress has been more heterogeneous than is shown by the aggregate figures.4

Country progress, not just global or regional

Although the MDGs were conceived as global targets to spur development efforts and support to poor countries, it is necessary to measure and describe progress at the country or other level to better understand advances and remaining gaps (see box 1.2). To untangle the aggregate numbers, we introduce alternative ways of analyzing MDG progress with a focus on lagging countries. Our approach characterizes MDG progress by country performance and by different typologies—such as initial income and policy-institutional conditions, subsequent growth and policy-institutional achievement, the poorest countries versus the others, level of fragility, and export sophistication and shipping connectivity (broadly following Collier and O’Connell5). This approach provides some empirical explanations of the links between development’s drivers and different rates of MDG progress.

Where do countries stand?

Several global targets will be missed, but the following questions also matter: How many countries are attaining the goals, and how many are behind? Are lagging countries far from the goals? And how many are already close? Answers from available information are surprisingly hopeful.

To examine them, we distinguish countries that are on target (or on track)—that is, their annual rate of progress between the reference year of MDGs in 1990 (or the closest available) to the latest year of data implies the right trajectory or trend to meet or exceed the goals—and those that are off target (or lagging). We look first at the gaps of off-target countries because they are the countries that need most attention.

First, the variation among lagging countries is large, but the average gap is not (table 1.2). Lagging countries are, on average, only 23 percent away from being on track to achieve all the MDGs. They are especially close to the targets for gender parity in primary education (average gap is 7 percent); gender parity in secondary education (16 percent gap); hunger (19 percent gap); primary education completion (20 percent gap); and, to some extent, under-five mortality (23 percent gap). But for each target there are countries where progress has been scant. For example, several countries are far from halving extreme poverty, even as the global goal will be reached.

Progress is mixed or poor on access to safe drinking water, access to sanitation, maternal mortality, and extreme poverty. Even so, the mean gaps of all lagging countries are less than 50 percent from the targets on access to safe drinking water (25 percent) and access to sanitation (27 percent), and no worse than 40 percent on maternal mortality (32 percent) and extreme poverty (39 percent).

Different starting points will imply a unique trajectory for each country to reach a specific goal. Hence, comparing the slope or growth rate of the historical path with the required one is a good way to assess progress. Leo and Barmeier define lagging countries as close to target if their trajectory is within 50 percent of the required progress to reach the goals, earning half a full score.6 In our methodology, we do not assign numerical scores in this manner or use an arbitrary cutoff point of 50 percent. Although we use the trend deviations or differences in the two growth rates to define the gaps, the actual gaps are retained to classify countries into groups according to their progress, to measure the mean gaps of each group, and to identify countries that are within 10 (or 20) percent of becoming on target. The mean gaps of lagging countries are all less than 50 percent across the MDGs, and they provide data-specific cutoff points to split the off-target countries into two subgroups: above average and below average. Countries in the top half are “close to the target,” whereas countries in the bottom half are “far from the target” (appendix 1 explains the approach in more detail).

More important, among countries that are off track, the top half are, on average, only about 11 percent away from being on target. The mean distance of this subgroup is only 4-9 percent for gender parity in primary and secondary education, child mortality, primary education completion, and hunger. Indeed, countries close to the target need to increase primary education completion only by 9.2 percent (or 1.5 percent a year), on average, to be on track to reach the 2015 target.

However, the rather uneven distribution also points to serious problems for the bottom half of the off-target countries, those far from the target among the lagging coun-tries—they are disproportionately far from the targets, especially for poverty (67 percent) and maternal mortality (51 percent). And the range of variation is considerably large among countries off target. For extreme poverty and primary education completion, the gap between the countries closest to and farthest from being on target is 96 percent, a fact that clearly illustrates the diversity of performance. This is the case for El Salvador and Uzbekistan on extreme poverty reduction and for Bhutan and Djibouti on primary completion rates.

Gaps and issues in measuring development outcomes beyond 2015

Measuring broad development outcomes through specific indicators is never precise, so the diversity in MDG performance is partly the result of indicator or measurement issues. Although the purpose of this report is not to focus on these issues, they are important for future deliberations of MDGs beyond 2015. Some of the issues are the following:

  • Outcomes versus outputs. Some MDG indicators (such as under-five mortality and maternal mortality) quantify development outcomes, whereas others (such as the primary education completion rate and ratios of girls to boys in education) are specific intermediate outputs. It is not surprising that the more outcome-based health MDGs often progress more slowly than others. But poverty reduction, a broad development outcome, is progressing rapidly. Because of the inherent and varying difficulty of demonstrating progress and results, choosing between outcomes and outputs may touch on issues of political economy. For example, a target like universal primary school enrollment is easily embraced because it is easier to show progress by getting children through school than it is to make sure they learn something, which may also be harder to measure. By contrast, learning outcomes as an objective are often resisted when the jobs and pay of teachers are at stake, partly because the outcomes also depend on other factors beyond the control of teachers. Take Tanzania as an example. It received an MDG award at the 2010 United Nations summit for its rapid progress on the primary education completion rate, but the ultimate development goal of improving learning outcomes of Tanzanian children remains problematic.a The point is that some meaningful development outcomes rest outside the scope of the MDGs, and it is important to begin to develop the auxiliary indicators and information base to monitor them.

  • Missing targets. Some specific development outcomes are not defined or are missing. Economic growth, particularly inclusive growth, is also excluded from the MDGs, as noted by many commentators. Its centrality as a means to achieve the MDGs is nonetheless monitored in the Global Monitoring Report framework. Missing global public goods include climate change-related goals (such as reducing carbon emissions) and market access for developing countries.

  • Targets versus trends. Although Sub-Saharan countries as a group will find it difficult to meet the poverty goal by 2015, they are progressing far above historical trends. Therefore, deviations from the targets versus deviations from past trends also matter. A related, wider issue is whether the MDGs should be absolute or relative targets.b

  • Data gaps. Poor data availability may fail to convey progress or understate deterioration resulting from shocks and conflicts. Among the MDGs, the collection and dissemination of poverty aggregates seem to lag the most. Conducting and completing household income and expenditure surveys in large countries is difficult, often delaying global or regional poverty updates because of the weights of these countries in the aggregates. There is also spotty information about infectious diseases, such as malaria and tuberculosis. Other data issues include reporting errors that severely compromise the accuracy of the maternal mortality ratio. And hunger is assessed only indirectly, through minimum food intake and its deprivation.

  • Metrics issues in some MDGs. When targets are measured in proportionate amounts, such as reducing by half the proportion of people living on less than $1.25 a day, problems can arise at both extremes. For low-income countries with high initial poverty rates, many of which are in Africa, the greater distance to the goal makes the target harder to reach; for middle-income countries where poverty rates are less than 10 or even 5 percent, reducing the rate further is also difficult and may entail assisting the hard-to-reach populations (chapter 4). The ratios of girls to boys in schools may be stagnant at 97-99 percent in some higher-middle-income countries because of different enrollment ratios between girls and boys. Boys may be lagging in completion rates (for example, at the primary level in Uruguay and at the secondary level in the Russian Federation). In addition, country figures can vary from international ones because of differences between national education systems and the International Standard of Education Classification (ISCED) used in multilateral development agencies—as well as differences in coverage and even population estimates.

  • Averages and weights. Large countries such as China, India, and Nigeria dominate their respective regional averages, especially on measures, such as poverty, where population is the weight. So the pattern would likely change if the reference unit pertained to individual countries, not regional or global aggregates. For example, many poor countries, including Bangladesh, Bolivia, the Lao People’s Democratic Republic, Malawi, Mozambique, Nepal, and Niger are registering major achievements on difficult MDGs such as child mortality.

a. Uwezo Tanzania 2010.b. ODI 2010.
TABLE 1.2

Lagging countries are close to getting on target

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Source: World Bank staff calculations based on data from the World Development Indicators database.Note: A country is “close to the target” if its distance to getting on target (that is, its gap of trajectory) is smaller than the average gap of all lagging countries. Otherwise, it is “far from the target” (that is, its distance is greater than the average gap). Figures in parentheses indicate the range of variation (Maximum value—Minimum value) of countries off target, by MDG. Averages and numbers of countries cover only those with data—and that may vary by MDG. See appendix 1 for more details.
TABLE 1.3

Many countries are within 10–20 percent of being on target

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Source: World Bank staff calculations based on data from the World Development Indicators database.

Indeed, many lagging countries are already within striking distance. From another perspective, table 1.3 provides the proportion of countries within 10 percent or 20 percent of getting on target. A third of off-target countries have, on average, a gap of 10 percent or less from being on target across the MDGs. Countries like Bangladesh (extreme poverty, hunger, and maternal mortality), Indonesia (hunger, child and maternal mortality, access to safe drinking water), and Mali (gender parity in primary education and access to safe drinking water) are in this category. (Table 1.4 lists these countries by MDG.) More than half have a gap of 20 percent or less. Of the countries within 20 percent of target, the best results are for gender parity in primary education, primary education completion, gender parity in secondary education, and hunger. The worst results are for access to sanitation, extreme poverty, and maternal mortality, with access to safe drinking water and under-five mortality in the middle.

TABLE 1.4

Lagging countries within 10 percent of being on target to achieve the MDGs

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Source: World Bank staff calculations based on data from the World Development Indicators database.Note: See also box 1.2, which covers metrics issues concerning some MDG targets.

All told, developing countries have been doing much better than thought until recently. Although many more developing countries are off track than on track to achieve the targets, two thirds or more of developing countries are actually on target or close to being on target, thanks to more than a decade of better policy and growth (figure 1.4). Many countries are making substantial progress in several MDGs: gender parity in primary education (89 of them), gender parity in secondary education (82), access to safe drinking water (66), primary completion rate (55), and extreme poverty (47). For instance, about 70 percent of developing countries have achieved or are on track to achieve the targets for gender parity in primary and secondary education. Although half the monitored countries (57) are off target for the primary education completion goal, two-thirds of them (38) are very close to being on track.

FIGURE 1.4
FIGURE 1.4

More than two-thirds of developing countries are on track or close to being on track

Source: World Bank staff calculations based on data from the World Development Indicators database.Note: A country is “close to the target” if its distance to getting on target (that is, its gap of trajectory) is smaller than the average gap of all lagging countries. Otherwise, it is “far from the target” (that is, its distance is greater than the average gap). The number above each bar indicates the number of countries. See appendix 1 for more details.

Progress is mixed or poor on access to sanitation, maternal mortality, and child mortality (box 1.3). Unfortunately, more than 40 percent of low-income to upper-middle-income countries in the sample (58 countries) are significantly off target for access to sanitation.

Regional patterns vary. The maps in this report show global and regional patterns (see map 1.1). Because the gaps in the top half of lagging countries are small, the ratio of countries close to the target to the total number of off-target countries also provides a relative measure of progress among MDG underachievers (table A1.2 and related tables in appendix 1). Within this group, Sub-Saharan Africa shows encouraging results. For instance, 81 percent of the region’s lagging countries are relatively close to the extreme poverty target. Fifty percent of the region’s countries are very close to the target for gender parity in secondary education, and 53 percent are quite close for hunger. Progress is also evident in access to safe drinking water (69 percent of countries are close to the target).

Many South Asian countries that face difficulties in reaching the 2015 targets are also performing better than average in the off-target group. For instance, all the region’s countries are within reach of the extreme poverty target, and 80 percent are close to the access to sanitation goal. For 67 percent of South Asian countries, the hunger target is within range.

In the Middle East and North Africa, 67 percent of countries are close to the target for gender parity in primary education. Even more encouraging: 80 percent of countries in the region are within reach of the primary education goal.

In Latin America and the Caribbean, Europe and Central Asia, and East Asia and Pacific—the regions with better MDG performance—most off-target countries are close to several goals, such as hunger, primary education completion, and gender parity. Results are less promising for maternal mortality and access to sanitation. Interestingly, for countries that have low poverty rates (that is, less than 10 percent), reducing extreme poverty at $1.25 a day to a much greater extent may not be easy (see box 1.2).

Improving children’s health through sustainable access to food, water, and energy

Sustainable access to food, safe drinking water, basic sanitation, and modern energy sources can decrease child mortality significantly.a Of the estimated 10.5 million child deaths annually, the vast majority are from preventable and treatable diseases and conditions, including low dietary energy consumption (underweight), unsafe drinking water and the lack of basic sanitation (diarrhea), and indoor air pollution related to solid fuel use for cooking and heating (pneumonia).

Based on socioeconomic and environmental trends, we project the population that lacks adequate access to food, water, and energy, and the resulting effect on child mortality. Except for Middle East and North Africa, progress is not enough to reach the MDG target on child mortality; and Sub-Saharan Africa does not even come close by 2030. Accelerated progress significantly improves this situation (see the figure below). This is especially the case in Sub-Saharan Africa, where approximately one-third of the child mortality gap can be achieved by achieving other MDGs.

Rising demand for food, water, and modern energy will put pressure on scarce natural resources (for example, fertile land for food and bioenergy; oil resources for clean fuels, such as kerosene for cooking). This will increase the prices of (especially) food and energy. And it will hurt poor people in importing countries in Sub-Saharan Africa and South Asia whose governments are unable to guarantee affordable prices when global prices increase.b Furthermore, provision of food, water, and energy becomes more difficult when natural resources are not properly managed or degrade as a result of global environmental change.c For example, climate change induces changes in rainfall and temperature patterns, potentially increasing the likelihood of short-term crop failures and long-term production declines as well as deterioration in water quality. The most vulnerable are poor and food-insecure countries at lower latitudes (especially in seasonally dry and tropical regions) that largely depend on rainfed farming—again in Sub-Saharan Africa and South Asia. Many such pressures are slow moving and cannot easily be stopped because of major inertia, including the pressures of fertility transition and greenhouse gas accumulation. They become apparent only in the long term, after 2015 or even after 2030, trapping people in their poverty and reversing progress.

Therefore, to achieve the MDG target on child mortality, accelerated growth in the other MDGs is key—particularly access to food, improved drinking water, basic sanitation, and improved energy sources. Furthermore, policies addressing increased access to food, water, and energy should take global scarcities and global environmental changes into account. This could both help in achieving the MDGs and in making those achievements more sustainable.

ch01ufig02

Projected child mortality results from various causes, 2015 and 2030

Source: PBL 2009a.Note: Because being underweight is usually not a direct cause of a child’s death (although it increases the risks of dying from pneumonia, malaria, and diarrhea), it is reported separately.a. The accelerated progress scenario for 2015 achieves the MDG targets on food, water, malaria, and energy (GISMO model, PBL 2008).
a. PBL 2009b.b. PBL 2011.c. PBL 2009b.

Country diversity generally softens the gloomy global picture. All these statistics are remarkable, revealing progress that is much more diversified and much more hopeful than the recent pessimism about achieving the MDGs. That pessimism was likely colored by the gaps at the global level, the difficult circumstances of poor countries, the potential negative impact of the recent global crisis, and the lack of recent data to assess outcomes. For example, although only 27 percent of low-income countries are on track to achieve or have achieved the extreme poverty target, almost 90 percent of these countries with data are in the top half of the lagging group and, therefore, have the poverty goal within their reach. Similarly, around 40 percent of low-income countries are close to the primary education completion goal, even though only 7 percent of the countries in this income group are on target.

What the data also suggest is that the reference unit matters. Simple country averages that give equal importance to each country qualify the global story, which uses weighted averages that give more importance to countries with large populations. This can work in both directions. For example, the progress in reducing world poverty and in meeting the goal is essentially the result of rapid advances by China and India, with the absolute number of poor people falling rapidly in China. Too many countries, however, still lag on the poverty goal, and their average shortfall of 39 percent to be on target is the biggest among the MDGs. In contrast, the average distance to becoming on target for under-five mortality is only 23 percent for lagging countries, somewhat less daunting than the global distance derived from the population of all under-five children.

Country analysis generally brightens the global picture, but both global and country perspectives are necessary for the complete view. In an unprecedented manner, the MDGs as global targets have galvanized development efforts to help the world’s poor; however, the country unit is relevant because these efforts are still geared to individual countries, given that country-owned strategy and capacity are important aspects of development assistance.

What important lessons therefore emerge from the complex tapestry of progress? Why are some countries on target, but others are not? Of the lagging countries, why are some close to target and others far away? The two main drivers often cited as key to attaining MDG-related development outcomes are economic growth and sound policies and institutions (fundamental to effective service delivery to the poor).7 Although it is easy to cite these two drivers, it is hard to provide empirical substance to their impact on achieving the MDGs.

We pursue this tack in the next section by examining the country pattern against growth and policy accomplishments, continuing the forward-looking analytical work started in the 2010 Global Monitoring Report8. More specifically, we ask whether initial conditions or subsequent growth and policy improve the odds of reaching the goals. The analysis looks at these elements in two ways: using prima facie evidence from graphical associations and patterns, which point to these elements’ likely association with the diverse progress of countries; and using a statistical investigation of their significance in increasing the likelihood of attaining MDG-associated outcomes.

The role of growth and policy

Initial conditions count in MDG performance, but subsequent growth and policy also matter greatly—or more. In most cases, countries that are doing better (those on or close to the target) exhibited favorable starting conditions around 1990 (the reference year). A higher per capita GDP in 1990 is generally associated with better MDG performance (figure 1.5).

Although there is no perfect indicator of the overall quality of policy and institutions in developing countries, the World Bank’s annual Country Policy and Institutional Assessment (CPIA) provides a broadly consistent framework for assessing country performance on 16 items grouped in four clusters: economic management, structural policies, policies for social inclusion and equity, and public sector management and institutions.

MAP 1.1
MAP 1.1

The world is still on track to meet the poverty reduction target

Source: World Bank staff calculations based on data from the World Development Indicators database.
FIGURE 1.5
FIGURE 1.5

MDG performance is stronger in countries with good initial conditions

Source: World Bank staff calculations based on data from the World Development Indicators database.Note: A country is “close to the target” if its distance to getting on target (that is, its gap of trajectory) is smaller than the average gap of all lagging countries. Otherwise, it is “far from the target” (that is, its distance is greater than the average gap).

The score is from 1 (low) to 6 (high) for each policy that covers a wide range of issues.9 The index focuses on policies and institutional arrangements—the key elements that are within the country’s control—rather than on actual outcomes (for example, growth rates) that are influenced by elements outside the country’s control. Over time, good policies and institutions are expected to lead to favorable growth and poverty reduction outcomes, notwithstanding possible yearly fluctuations caused by external factors.10 Using the 1996 CPIA, the earliest index with comparable scale and criteria available,11 suggests that countries starting with good policies and institutions tend to do better in the MDGs.

Starting points—inherited initial conditions—explain why middle-income countries generally do better than low-income countries. Having grown earlier, they also tend to have implemented earlier a better set of policies and institutions. But there are variations. For extreme poverty and gender parity in primary education, countries making the fastest progress are those that experienced medium poverty and female-to-male primary enrollment ratios in the 1990s (see table A1.5 in the appendix). The latter results draw attention to the challenges of poverty reduction in the proportionate way that MDGs are defined at low-income and middle-income levels—for poor countries, the distance to the goal is long; for middle-income countries, halving already low poverty rates is not easy.

FIGURE 1.6
FIGURE 1.6

Subsequent economic growth and policy seem to matter more

Source: World Bank staff calculations based on data from the World Development Indicators database.Note: A country is “close to the target” if its distance to getting on target (that is, its gap of trajectory) is smaller than the average gap of all lagging countries. Otherwise, it is “far from the target” (that is, its distance is greater than the average gap).

So, although starting points (given their inherited nature) do not say much about what countries can or should do, they need not preordain outcomes. The good news is that economic growth and policy performance after the initial year appear to count greatly, if not more than the starting points (figure 1.6). On average, countries that have reached or are on track to reach the targets (excluding gender parity in primary education) show the fastest per capita GDP growth over 1990-2009. In the same way, countries close to the target tend to have grown faster, in per capita terms, than countries far from the target. Likewise, a strong policy and institutional framework in the most recent year, 2009, tends to facilitate service delivery to the poor and to improve MDG performance (table 1.5).

Both factors—initial conditions and subsequent growth and policy—also point to why the MDGs are such big challenges for the poorest and most fragile countries. The world’s 79 poorest countries serviced by the World Bank’s International Development Association (IDA) have a threshold per capita gross national income of $1,165 for fiscal year 2011, with average per capita growth and recent institutional performances well below average.12 Half the IDA countries are in Sub-Saharan Africa. With lower incomes and a late start in policy reforms and growth, IDA countries’ MDG performance tends to lag that of middle-income and non-IDA countries (figure 1.7a). Despite the greater distance to the MDGs set by low starting points, the poverty target is within reach for more than 70 percent of IDA countries as a result of more recent economic growth and policy improvement. That is also true of the hunger target for 58 percent of IDA countries. Results are also good for gender parity in primary education.

TABLE 1.5

Growth and CPIA scores are higher in countries on track or close to being on track

Average values across MDGs (weighted by the number of countries in each MDG category)

article image
Source: World Bank staff calculations based on data from the World Development Indicators database.Note: The pairwise correlation between average GDP per capita growth and the CPIA index is 0.32 (significant at 0.01 level). GDP per capita, purchasing power parity constant 2005 international dollars. A country is “close to the target” if its distance to getting on target (that is, its gap of trajectory) is smaller than the average gap of all lagging countries. Otherwise, it is “far from the target” (that is, its distance is greater than the average gap).

Fragile conditions in conflict-affected countries are also associated with very poor MDG performance because these countries may experience growth collapses and disastrous policy and institutional environments (see box 1.4).13 In broad terms, the proportion of on-target countries tends to rise with declining state fragility (figure 1.7b). Fragility in the graph is the index from the Center for Global Policy, which ranges from 0 (no fragility) to 25 (high fragility), divided into four categories ranging from little to extreme fragility (for more information on fragile states and the policy toolbox, see box 5.4).14

Export sophistication and shipping connectivity also have positive associations with MDG performance. In a period of rapid globalization and trade expansion, these two trade dimensions tend to be related to MDG performance in developing countries. Countries with a higher level of export sophistication are generally more on track to achieve the targets (figure 1.8a). Likewise, countries more integrated into global shipping networks are more likely to be on or close to the target (figure 1.8b).

We also looked at simpler dimensions of trade—commodity versus noncommodity exporters as well as landlocked versus other countries—but the associations tend to be less defined than those shown in figure 1.8. In any case, export sophistication, shipping connectivity, and state fragility are likely to be correlated with a country’s level of development, growth performance, infrastructure, and with its policies and institutions for trade, private sector development, and doing business.15

Assessing the odds of achieving the MDGs

Is it possible to link and simulate the impact of growth and policy to the likelihood of achieving the MDGs in a manner more rigorous and statistical than with graphical associations? Although formal econometric analysis, in principle, can isolate partial effects that are not apparent from the simple correlations in the previous section, there are caveats: the direction of impact between development outcomes as measured by the MDGs and the two basic drivers (growth and policy) can go both ways; the two drivers themselves are likely to be correlated; and some factors that affect the progress of MDGs are not readily measurable and available. Data constraints are also problematic. For these reasons, the findings in this section are preliminary; they are specific to the approach and presentation of data taken; and they may not apply when using other approaches or treatment of the MDG variables.

FIGURE 1.7
FIGURE 1.7

MDG performance lags in IDA and fragile countries

Source: World Bank staff calculations based on data from the World Development Indicators database and Marshall and Cole 2010.Note: The number above each bar indicates the number of countries. See appendix 1 for more details.

With these caveats and building on the empirical patterns, previously defined measures of MDG progress, and the basic drivers of progress in the GMR framework,16 we introduce a simple and intuitive model that is suited to assessing the probability of a country falling into one of the three defined categories, linking performance to the two drivers. For a given development indicator associated with each MDG, the likelihood of a country being on target, close to the target, or far from the target is expressed as a function of

  • economic growth (annual per capita GDP growth, 1990-2009);

  • recent quality of the policy and institutional framework approximated by the current CPIA, which assesses recent changes in policies and institutions and, by design, does not correlate with recent growth17;

  • initial conditions (per capita GDP in 1990 and CPIA index in 1996); and

  • controls (specific development indicators around 1990).

The impact of violence on the MDGs

The World Development Report 2011: Conflict, Security, and Development depicts the arrested social development in countries affected by violence. Development in these countries is lagging on nearly every MDG (top figure below).

People in fragile and conflict-affected states are more liable to be impoverished and malnourished and to lack access to basic health services and safe drinking water. Children born in these countries also tend to miss out on schooling; they are twice as likely to be undernourished and nearly twice as likely to die before age 5 (bottom figure below).

ch01ufig03

Violence poses a major challenge to meeting the MDGs

ch01ufig04

Countries affected by violence account for:

FIGURE 1.8
FIGURE 1.8

MDG performance is better in countries with greater export sophistication and shipping connectivity

Source: World Bank staff calculations based on data from the World Development Indicators database, Lall 2000 for export sophistication, and UNCTAD 2010 for liner shipping connectivity.Note: The index of export sophistication measures the technological content of exports from developing countries, standardized and distributed into four export groups. The shipping connectivity index has a base year of 2004. The number above each bar indicates the number of countries. A country is “close to the target” if its distance to getting on target (that is, its gap of trajectory) is smaller than the average gap of all lagging countries. Otherwise, it is “far from the target” (that is, its distance is greater than the average gap). See appendix 1 for more details.

The probability function across the different states of MDG performance is estimated using the multinomial logit model. Estimations are performed for each of the nine development targets under consideration using “far from the target” as the reference group or base category (see appendix 1 for a technical discussion). The statistical analysis therefore pools all country information and focuses on the probability of a country being in one of the three states of MDG performance.

Most of the literature on the determinants of MDGs, at country or regional level, focuses on demand-side factors (such as income and growth, demographic characteristics, and cultural values and preferences) and on supply-side interventions (such as public social expenditures, infrastructure, institutional quality, and civil service performance). Accordingly, empirical cross-country analyses usually relate supply and demand factors to development indicators in levels.18 In the 2010 Global Monitoring Report, the scenarios of the impact of the recent crisis on the MDGs also used such an approach, and those scenarios remain generally valid. For this report, the emphasis is shedding light on the likelihood of countries attaining the development goals.

The statistical probability of achieving the MDGs is positively correlated with growth and improved policy. The correlation is significant at a 10 percent or better level of statistical significance (see figure A1.1 and marginal probabilities in the appendix). As expected, growth and policy effectiveness are positively related with the predicted probabilities of achieving or being on track for achieving the MDGs.

Both development drivers count, but growth has an all-encompassing bearing on progress toward the MDGs. A closer look at estimation results (table A1.6 in appendix 1) reveals that economic growth has a pervasively significant and positive impact on the odds of achieving all MDGs under consideration, apart from gender parity in primary education. The quality of policy and institutions also has a positive and statistically significant relation with MDGs for hunger reduction, gender parity, and child and maternal health.

Consequently, based on the average pattern thus far and at the aggregate level, growth might have a broader impact on attaining MDGs than the quality of policy and institutions. This is likely because growth has a more immediate effect and can be generated from several sources, including better policy as well as beneficial exogenous shocks and flows in the global economic environment. By contrast, policy improvements as defined by the CPIA cover myriad areas and interventions that need a longer time to come through. In any case, given the short time left until 2015, the statistical results confirm the centrality of growth in improving countries’ odds of achieving the MDGs. (In addition to growth, reducing inequality also helps decrease poverty in the case of Brazil [box 1.5]).

Improving the odds of achieving the MDGs

How much will higher growth and better policy improve these odds? We consider an increase of one standard deviation in growth and in the quality of policy institutional assessment to be equivalent to about 1.8 percentage points in added growth and to the CPIA index rising by 0.5 points.

Economic growth can jump-start countries particularly far from the goals. For countries that are far from the target (starting from a low base), the effects of a one-standard-deviation simulated increase in per capita growth on the probabilities of reaching some MDGs tend to be distinct and large (figure 1.9b). It would raise 12-fold the probability of reaching the targets for primary completion and gender parity in secondary education, more than double it for under-five child mortality and sanitation, almost double it for extreme poverty and hunger, and increase it by more than half for access to safe drinking water.

For countries close to the target, higher growth rates still appear to have a significant impact on primary education completion and gender parity, but not to the same extent as for countries far from the target (note the scale of the y-axis in figure 1.9a). This is doubtless because growth is already higher in this group (see table 1.5), which likely needs better policy to move to a higher plane.

Good policies and institutions are vital for outcome-based MDGs For lagging countries far from the target, this seems true for several health-related MDGs—under-five mortality, maternal mortality, and hunger—as well as for gender parity in primary education. A one-standard-deviation simulated improvement in the quality of policies and institutions would increase the probability of achieving the hunger target nearly fourfold. For the remaining targets, the impact ranges from 152 percent to 67 percent.

For lagging countries close to the target, effective policies and stronger institutions also appear important to the progress on health-related MDGs. For instance, the odds of reaching targets such as maternal mortality and access to safe drinking water improve by more than 30 percent after a one-standard-deviation increase in the CPIA index.

Why do policies and institutions seem to play a greater role in the chances of reaching health-related MDGs in both groups of off-target countries? The reason is likely because the targets are outcome-based measures that depend not only on growth and resources but also on myriad factors in the system: the flow of budgets to localities where resources are needed, accountability and transparency, incentives of service providers and clients, and other institutions for service delivery. If the goals for education and gender parity were also outcome based (for example, based on learning outcomes or equal pay for workers of similar characteristics), the results could be similar. The lack of data and defined goals in these areas makes it hard to test this more systematically. (See appendix 1 for more discussion.)

Reducing inequality and poverty in Brazil

In addition to faster growth and better policies, more inclusive growth and equality within countries will benefit people in the bottom quintiles and lift more people out of poverty. However, despite reduced inequality across countries over the last 25 years, within-country inequality has generally increased in most developing countries since 1980.a Brazil is a notable exception.

At the end of the 1980s, Brazil was one of the most unequal countries in Latin America and the developing world. According to the World Development Indicators database, Brazil’s Gini coefficient of income inequality peaked at 63.0 in 1989—the highest among 70 countries with data, just above Sierra Leone’s 62.9 and Zambia’s 60.5. Since then, Brazil has experienced extraordinary progress in reducing both poverty and inequality—in fact, the country’s Gini coefficient has fallen 10 points, while gross domestic product and real household consumption have grown steadily since 2003, after earlier stagnation.

ch01ufig05

Reduction of income inequality has significant effects on poverty in Brazil

Source: World Bank staff calculations based on PovcalNet database.a. Brazil 1989 is a projection of the structure of income distribution in 1989 with the average income in 2007.

The 1990s marked the expansion of social safety nets in Brazil. Public social expenditure, including conditional cash transfers such as the Bolsa Família, targeted to poor families rose from 17.6 percent of GDP in 1990 to 26.0 percent of GDP in 2008—an increase of almost 50 percent in education, health, housing, and social security. Recent evidence suggests that this increase in social spending and better targeting contributed much to reducing poverty and inequality.b From 1994 to 2004, sound macroeco-nomic policies also lowered inflation from high levels and improved economic growth in more recent years.

Without the reduction in income equality from 1989 to 2007, the $1.25-a-day poverty rate would have been 14.5 percent, instead of the 5.2 percent attained. An additional 17.5 million Brazilians would have remained in extreme poverty. Using regression decomposition methods, Ferreira, Leite, and Raval-lion calculate that without the social transfer policies and programs, the poverty head count index in Brazil would have been about 5 percentage points higher in 2004.c

Brazil’s encouraging results illustrate the importance of inclusive economic growth and reduction of inequality in the fight against poverty and social exclusion. Ravallion identifies two main lessons from the Brazilian experience: “First, reforms to social policies to make them more pro-poor [if fiscally possible] can play an important role in sustaining poverty reduction, even during a period of economic stagnation. Second, sensible macroeconomic and trade policies need not hurt the poor and, in the specific case of taming hyperinflation, are likely to make a significant contribution in the fight against poverty, even when that is not the primary objective.”d

Brazil is also taking steps to reach its indigenous peoples. Between 2002 and 2007, the number of indigenous schools rose by about 45 percent, and school enrollment among indigenous populations increased by 50.7 percent. The “Indigenous Portfolio” (Carteira Indígena) Initiative implemented in 2004 has approved over 250 projects to support economically and environmentally sustainable productive activities for the benefit of 12,000 indigenous families and 60 ethnic groups across 18 Brazilian states; the participation rate by indigenous organizations and communities is more than 80 percent.e Within-country variation and inequality being important, chapter 4 of this report examines one segment of the population—indigenous and socially excluded groups of people—that is lagging behind even in countries that are already on track to achieve the poverty goal.

a. See World Bank (2007, ch. 3) for a more detailed discussion of the trends and issues of global and within-country inequality.b. Ferreira, Leite, and Litchfield 2008.c. Ferreira, Leite, and Ravallion 2010.d. Ravallion 2011, p. 17.e. Government of Brazil 2009.

The simulation results generally show that economic growth and policy effectiveness can contribute significantly to achieving the MDGs. Although per capita GDP growth tends to have a broader impact on development targets, sound policies and institutions—basic dimensions of effective service delivery to the poor—appear crucial for achieving health-related MDGs.

Many more developing countries can get on track. A one-standard-deviation rise in both growth and the CPIA would mean that as many as 32 more developing countries can get on track for the MDGs—an average increase of 44 percent in the number of on-track countries (figure 1.10). This forecast is based on a greater than 50 percent probability of each country getting on track. Statistically, the probability of lagging countries can only reach 100 percent as an upper (asymptotic) limit, but a 95 percent confidence interval of a 50 percent increase will generally cover that upper limit. The percentage increase in the number of countries getting on track generally rises most for the targets farthest behind—targets such as under-five mortality (89 percent), hunger (64 percent), access to sanitation (54 percent), maternal mortality (37 percent), and access to safe drinking water (36 percent). For the other MDGs (such as poverty, primary education completion, and gender equality in primary and secondary education), the increase in the number of countries is about 30 percent, still substantial. Individual countries that are good candidates to get on track are those currently very close—that is, within 10 percent of getting on track (table 1.4).

FIGURE 1.9
FIGURE 1.9

The odds of getting on target rise substantially with faster growth and better policy

Effects of a one-standard-deviation increase in selected development drivers from the multinomial logit estimates

Source: World Bank staff calculations. See appendix 1 for details.Note: For simplicity of presentation, only those countries with significant percentage changes at the 0.10 level or better are shown. Marginal probabilities and odds ratios are presented in appendix 1. Percentage variations are not comparable across indicators. Average standard deviation increase in GDP per capita growth ≈ 1.8. Average standard deviation increase in CPIA index ≈ 0.5. GDP per capita, purchasing power parity constant 2005 international dollars.
FIGURE 1.10
FIGURE 1.10

Growth and policy reforms will put many countries on track

Source: World Bank staff calculations based on a one-standard-deviation increase or improvement in growth and policy. See appendix 1 for details.

How achievable are these gains? Recent history suggests they may be. Achieving the growth assumption for developing countries appears possible. To put the one-standard-deviation growth increase in context, per capita GDP growth will need to double from its historical rate of 1.9 percent a year. Even so, the historical rate is an average covering all types of developing countries and the uneven subperiods during 1990-2009, including the recent global crisis years (2008-09). The increase, in fact, is very much within the realm of actual performance for Sub-Saharan African countries during periods of growth acceleration (3.9 percent), including the high-growth period 2000-07.19

For the two off-target groups, growth during the recent global crisis did not fall below the rates in the reference period (1990-2009), corroborating other economic assessments that low-income countries did relatively well (table 1.6). Three factors explain why the recent crisis was different for low-income countries. First, policies and institutions improved before the crisis, and economic growth accelerated after the mid-1990s—particularly after 2000. Second, unlike previous crises, the recent one was not caused by domestic policy failure, which would have severe impacts on human development out-comes—particularly on child and maternal mortality. Third, spending on social safety nets was protected by governments with the assistance of international financial institutions and the donor community.20 Even during the peak in 2009, their average growth stayed in positive territory. Their recovery is now expected to be strong, with growth prospects for 2010-15 similar to the growth assumption (which is higher than in the reference period, but as good as the recent growth accelerations, variously defined).

TABLE 1.6

A one-standard-deviation increase in growth is definitely achievable

article image
Sources: World Development Indicators database. Growth prospects are from the IMF’s World Economic Outlook. World Economic Outlook.Note: The growth assumption is growth during reference period plus one standard deviation, or 1.8. Growth rates are all simple averages, giving equal weight to each country GDP per capita, purchasing power parity constant 2005 international dollars. n.a. = not applicable.
MAP 1.2
MAP 1.2

Sub-Saharan Africa and Southern Asia are home to the vast majority of children out of school

Source: World Bank staff calculations based on data from the World Development Indicators database.

The global crisis struck the on-track developing countries much harder. At its peak, growth in this group was negative. However, many of the countries are higher-middle-income ones—particularly in Eastern Europe, where the MDGs were less of a challenge. The growth forecast for 2010-15 is still higher than the record in the reference period or the recent trend-break (1995-2007).

Where a problem may surface is in improving policy and institutions, given the few years left until 2015. A one-standard-deviation improvement in the CPIA is equivalent to a 0.5-point increase, or about the difference between the CPIA for on-target countries and for countries far from the target (see table 1.5). A 0.5-point increase in a CPIA rating is the normal award for an improvement in any policy area in a country. But to do this consistently for all the 16 questions in the CPIA is much harder. In any given year, a 0.1-point increase in the overall score represents a significant policy improvement for a country; a 0.2- or 0.3-point increase represents a substantial policy shift or regime change—rare for any country.

But it is certainly conceivable over time. The World Bank’s CPIA has undergone changes to improve its assessment and is only broadly consistent over time. For instance, from 1998 to 2003, 32 countries (24 percent of developing countries for which scores are available) experienced an improvement of 0.5 points or better, especially countries in Eastern Europe. More recently, during the period 2004-09 when the new system has been stable, countries that have achieved an improvement of 0.5 include Georgia, Nigeria, and Seychelles. As one of the few broad measures available for policy and institutions, it is a proxy for the point that significant policy reforms are needed, especially for outcome-based or system-oriented MDGs. Because policy reforms can take time to implement and bear fruit, it is also important to undertake significant reforms sooner than later.

What is in the rest of this report

Developing countries are doing better when looking at country-level figures than at global figures. Lagging countries, on average, are very close to the targets, and their odds of getting on track can improve dramatically with stronger growth and sounder policy. Economic growth has a pervasive effect on all the MDGs and can jump-start countries far from the target. The implications are clear. With 2015 only a few years away, growth in developing countries needs to be taken quickly to a higher plane, the fastest way to lift more countries to the MDGs. Chapter 2 examines the prospects and challenges for economic growth in developing countries, how they are recovering from the recent global economic crisis, and what they need to do to boost growth further.

The quality of policies and institutions is more crucial for MDGs that are health related or are lagging the most, as well as for countries close to the target. What constitutes good policies and institutions in developing countries is complex, however, covering a wide range of areas.

Interventions can be broad and wide ranging or specific to local circumstances and problems. Much has been written about the broad issues, but less about microeconomic interventions, precisely because of specificity and local context. But thanks to the World Bank’s Development Impact Evaluation Initiative and similar efforts, more documentation has emerged in recent years. To help untangle the difficult challenge of improving policies and institutions in developing countries, chapter 3 presents findings and lessons from impact evaluations in health and education, where several of the studies have already been completed.

Chapter 4 examines what countries can do to help the bottom 10 percent of society, usually indigenous and socially excluded groups.

Because a beneficial global environment (Goal 8) also helps support MDG progress in developing countries, chapter 5 reviews global trade, aid, and the actions of international financial institutions for developing countries. Goal 7 on environmental sustain-ability and biodiversity has no well-defined targets but it affects other MDGs, such as child health and human development more generally. Appendix 2 describes some aspects based on contributions from the Netherlands Environmental Assessment Agency.

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2.

Ravallion 2009; World Bank 2010.

3.

Leo and Barmeier 2010.

4.

See, for example, Bourguignon et al. (2008),Leo and Barmeier (2010), and ODI (2010).

6.

Leo and Barmeier 2010.

7.

See, for example, the first Global Monitoring Report (World Bank 2004).

8.

World Bank 2010.

9.

Issues include macroeconomic and fiscal policy, debt policy, trade, human development policy in education and health, gender equality, social protection, budgetary and financial management, and corruption in the public sector.

10.

See World Bank (2009) and footnote 17.

11.

An earlier version of the CPIA goes back to 1970s but uses a different scale and criteria. For example, the assessment of governance issues was not included in the earlier CPIA.

12.

Average GDP per capita growth in IDA countries (1990-2009) is 1.36, a point below average growth in non-IDA countries (2.38). The CPIA index in 2009 is, on average, 3.26 in IDA countries versus 3.69 in non-IDA countries. Fragile or conflict-affected countries (one or more years, 2006-09) exhibit average per capita GDP growth (19902009) close to 1.03 percent and a CPIA index of 3.00 in 2009. However, nonfragile states have grown, in per capita terms, at an average rate of 2.27 percent since 1990. The CPIA index for these countries is 3.68 in 2009.

13.

World Bank 2010. Harttgen and Klasen (2010) show that fragile countries perform worse on MDG levels, but that their MDG progress is not necessarily slower.

14.

Marshall and Cole 2010.

15.

It is important to point out that these simple graphical patterns can be driven by more fundamental development factors, such as growth and institutions. The next section tackles some of these issues.

16.

World Bank 2004.

17.

A study (IDA/DECVP 2007) found the correlation between contemporaneous CPIA and growth to be weak and the correlation between CPIA and future growth to be strong. The CPIA measures the level of policies, not the change; and it focuses on actual implementation, not just introduction or announcement. It is therefore backward looking. The inclusion of the 1996 CPIA is an attempt to capture the policy achievements close to the reference year in 1990, and the 2009 index will include the more recent record. See appendix 1 for a discussion of the use of the CPIA index and other alternatives. See also the guide for CPIA in World Bank (2009).

18.

A review of the determinants of MDGs is in chapter 3. See also Lay (2010) and Lofgren (2010) for extensive reviews on the determinants of education-related and health-related MDG indicators.

19.

See, for example, Arbache, Go, and Page (2008).

20.

See World Bank (2010).

Within Same Series

Other IMF Content

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Cover Global Monitoring Report, 2011
Global Monitoring Report, 2011
Improving the Odds of Achieving the MDGs
Author: International Monetary Fund
ISBN:
9780821387009
ISSN:
0258-7440
Publication Date:
03 May 2011
Publisher:
The World Bank
DOI:
https://doi.org/10.5089/9780821387009.083
Pages:
198
  • View in gallery

    Current global distance to the MDGs is wide ranging

  • View in gallery

    Fewer low-income countries are on track to achieve the MDGs

  • View in gallery

    Population coverage of the latest available household surveys is increasing

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    Countries on target to achieve the MDGs, by region

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    More than two-thirds of developing countries are on track or close to being on track

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    Projected child mortality results from various causes, 2015 and 2030

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    The world is still on track to meet the poverty reduction target

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    MDG performance is stronger in countries with good initial conditions

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    Subsequent economic growth and policy seem to matter more

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    MDG performance lags in IDA and fragile countries

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    Violence poses a major challenge to meeting the MDGs

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    Countries affected by violence account for:

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    MDG performance is better in countries with greater export sophistication and shipping connectivity

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    Reduction of income inequality has significant effects on poverty in Brazil

  • View in gallery

    The odds of getting on target rise substantially with faster growth and better policy

    Effects of a one-standard-deviation increase in selected development drivers from the multinomial logit estimates

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    Growth and policy reforms will put many countries on track

  • View in gallery

    Sub-Saharan Africa and Southern Asia are home to the vast majority of children out of school

Current global distance to the MDGs is wide ranging

Fewer low-income countries are on track to achieve the MDGs

Population coverage of the latest available household surveys is increasing

Countries on target to achieve the MDGs, by region

More than two-thirds of developing countries are on track or close to being on track

Projected child mortality results from various causes, 2015 and 2030

The world is still on track to meet the poverty reduction target

MDG performance is stronger in countries with good initial conditions

Subsequent economic growth and policy seem to matter more

MDG performance lags in IDA and fragile countries

Violence poses a major challenge to meeting the MDGs

Countries affected by violence account for:

MDG performance is better in countries with greater export sophistication and shipping connectivity

Reduction of income inequality has significant effects on poverty in Brazil

The odds of getting on target rise substantially with faster growth and better policy

Effects of a one-standard-deviation increase in selected development drivers from the multinomial logit estimates

Growth and policy reforms will put many countries on track

Sub-Saharan Africa and Southern Asia are home to the vast majority of children out of school

  • CBD (Convention on Biological Diversity). 2010. “Linking Biodiversity Conservation and Poverty Alleviation: A State of Knowledge Review.” Technical Series No. 55, Montreal, Canada.

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  • Kok, M. T. J., S. Tyler, A. G. Prins, L. Pintér, H. Baumüller, J. Bernstein, E. Tsioumani, H. David Venema, and R. Grosshans. 2010. “Prospects for Mainstreaming Ecosystem Goods and Services in International Policies.” Biodiversity 1 (1–2): 45–51.

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  • PBL (Netherlands Environmental Assessment Agency). 2010. Rethinking Global BiodiversityStrategies: Exploring Structural Changesin Production and Consumption to ReduceBiodiversity Loss. Bilthoven, Netherlands.

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