Thank you Carlos.It’s a honor to be invited to present on the occasion of the 4th DAC Development Debate with title « What would it take to achieve the MDGs by 2015.I am Jean-Philippe Stijns, Economist with the OECD Development Centre.This morning, I would like to give you the highlights of an OECD Development Study that was published in late April. The title has benefited from the marketing skills of our PAC colleagues.Basically what we do The paper sizes the additional development resources that are needed and that are potentially available to attain the MDG’s in developing countries.We did insist on the subtitle though because we think that attaining anything like the MDGs will be at least as much a matter of political will here and there as well as of policies than of sheer financing…Let me start by telling you a bit more about the motivation behind this study…
Someone legitimately asked me lately: Why bother with the MDGs at this point?Indeed, the 2015 deadline is nearly upon us. But has Carlos has pointed out progress remains to be made and the MDGs are unfinished business. It would be odd, to say the least, to move on to a post-20015 framework, whatever its shape or form, without at least taking stock of what’s left to be done and the means we potentially have to do so.Indeed, we live it to the UN to track in details MDG achievement per se. What we’re interested in is what would it take to close the remaining gaps and where the resources to do so could come from.We’re not writing in a vacuum. The Los Cabos report of the G20 Working Group on Development did welcome the efforts by International Organisations to improve the statistics on tax revenue collection in developing countries.Indeed, the MDGs have for too long been approached in a donor-centric way both in terms of their conception and appropriation (or lack thereof) together with the way accountability to get them achieved was conceived in practice led them to be called by some as Millennium “Donor” Goals.There was thus a strong case to revisit the MDGs and to extend the analysis in the direction of the tax revenue mobilisation that could potentially contribute to achieve them.
Goal 7: Ensure environmental sustainability Target 7A: Integrate the principles of sustainable development into country policies and programs; reverse loss of environmental resources Target 7B: Reduce biodiversity loss, achieving, by 2010, a significant reduction in the rate of loss Target 7C: Halve, by 2015, the proportion of the population without sustainable access to safe drinking water and basic sanitation (for more information see the entry on water supply) Target 7D: By 2020, to have achieved a significant improvement in the lives of at least 100 million slum-dwellersGoal 8: Develop a global partnership for development
The study uses two approaches:i) a bottom-up approach, which assesses the cost of directly addressing poverty, education and health goals through targeted transfers and expenditures;ii) a top-down approach, which measures the amount of development finance required to ensure that there is enough economic growth to meet the MDGs.The top-down approach measures are constructed as time-bound targets to be sustained until 2015,while the bottom-up approach assumes that targeted transfers and expenditure are always paid out each year and indefinitely.To generate the global cost, a choice is made, country-by-country, between the two approaches on a case-by-case basis, according to their relative cost. The characteristics of middle-incomecountries make the bottom-up approach is often the most cost-effective. For low-income countries the top-down approach has generally proven to be a better option. The key assumption to keep in mind is that the top-down approach assumes an unchanged income distribution while the bottom-up approach assumes unchanged quality / inclusiveness of growth. Of course, reality is way more complex, and MDG spending can help towards raising growth and obviously not all types of growth are equally attractive to achieve the MDGs. This is thus highly schematic and obviously hybrid policies aimed at inclusive growth are ideal, the question being more one of degree than a binary one as our schematic approach might suggest.
LEGITIMATE BUT MISPLACED: If you take away South Asia, and particularly China, there has been little progress at the global level. Can we be happy with goals that are met in one country / region and essentially unmet elsewhere?LEGITIMATE BUT OUTSIDE OUR SCOPE: Our study takes the MDGs as they are. The point that one should not equate too readily MDGs and development is well taken though.THE STUDY EMBRACES THIS CONCLUSION: our favourite analogy is that if I tell you that your smoking will cost an expected 1 million EUR to you and the rest of society, your optimal reaction should not be to save a million away. Similarly, we think that aid effectiveness is unfinished business and that much is to be said about improving the quality of expenditure in developing countriesFAIR ENOUGH: Our estimates are quite crude although they are the most up-to-date and an improvement upon what others have done including the WB. We don’t want to be fetishist about our estimates. Our figures are helpful to get an idea about the order of magnitude of the policy challenges the MDGs represent in different types of countries. One does not need to know the temperature down to the tenth of the degree to decide whether to put a tee-shirt or a pull-over on…
What is the annual financial size of the challenge of development?Now, one question that can be asked is how much ODA alone would have to grow to meet this USD 120 billion challenge? One then needs to estimate how much of ODA does actually help to meet the MDGs. One possible rule of thumb that our DCD colleagues suggested was to consider country programmable aid from DAC countries, including the EU but excluding multilateral agencies. This figure was close to 60 billion in 2009, and thus would have to be tripled from its current level to generate an incremental USD billion 120, in other words 180 billion in total. If we stretched our assumption to assume that all ODA, at almost USD 120 billion in 2009 helps with the MDGs, then aid would ‘only’ have to double.Keeping the above-mentionned caveats about MDG overlaps and capacity bottlenecks in mind, it’s anyone’s guess by exactly how many times aid would have to multiply to achieve the MDGs let alone a more profound definition of development. Whatmore, aid is not the only game in town, fortunately, and there is no reason to expect ODA to do all the work. And in any case, it is clear that the overall estimate depends a lot on the quality of international cooperation and domestic policies that we assume. If we were able deliver on improving those, the bill could probably be reduced substantially.What we do learn with this figure is that meeting the MDGs everywhere with ODA alone does not look like a very realistic prospect in the current day and age.
This graph shows estimates for the bottom-up and top-down costs of acheiving the MDGs in different income groups:LICS: <1000 USD pc paLMICS: 1-4000 USD pc paUMICS: 4000-12000 USD pc pa in UMICSthe tab for achieving the MDGs top-down, i.e. by boosting development financing enough to grow unequal countries out of poverty is extremely high at USD 140 billion.the main reason for this is a combination of highly unequal income distributions with a historical record of reactivity to flows of development financein contrast, the bottom-up costs of achieving the MDGs are very low at USD 6 billionthe reason is that the absolute size of poverty in UMICs lagging behind on MDGs is not that bigThis is why this study opts for bottom-up to estimates to find out at the other extreme in LICs,the bottom-up costs of achieving the MDGs are much higherwhile the top-down costs are lowerThe top:down – bottom:up ratio is such that in many cases the discounted cost of the top-down approach is lower than that of bottom-up
Whenwetake a look at the same question acrossregionsratherthanincomelevels, Latin Americaischaracteric of the situtation of UMICSWhilesub-saharanAfricanis more characteristic of LICsNearly USD 5 billion would be the cost of targeted welfare programmes to halve the number of people living in absolute poverty (Figure 3). Much will be concentrated in sub-Saharan Africa. MDG 1, fighting extreme poverty and hunger, will be achieved globally by 2015 as rapid poverty reduction in a few large countries will have reduced global poverty to less than half of its 1990 level. However, without action, about 35 countries will fall short of the goal of halving the number of people living in absolute poverty. Slightly under USD 9 billion would be needed to achieve universal primary education (UPE) by 2015, MDG 2 (Figure 4). School attendance has increased markedly over the past decade. But, to offer schooling to all primary age children, overall education spending should increase by more than 7% in developing countries that still need to achieve UPE. In sub-Saharan Africa, education spending needs to rise by more than 20%. Yet, USD 1.1 billion would suffice to offer primary schooling to all children in countries where income per capita is lower than about USD 1 000 per year (low-income countries)USD 60 billion would be needed to cut mortality among children under five by two thirds, reduce the maternal mortality ratio by three quarters and to combat AIDS, malaria and other major diseases, MDGs 4-6 (Figure 5). About USD 35 billion will be needed for health in South Asia and USD 20 billion in Sub-Saharan Africa. Upper-middle income countries—where per capita income is roughly between USD 4-12 000 per year—already spend enough on average to meet the MDGs but the distribution and quality of health expenditure is a key issue.
It is relatively easier for upper-middle income countries to finance their MDG needs: compared to bottom-up costs at least, only a marginal increase in existing flows of development resources is needed. This average picture does hide the mismatch there is been the UMICS that could improve tax collection significantly and those with the highest MDG neeeds.It is still challenging in average for low- and lower-middle income countries to finance their needs. Both top-down and bottom-up costs are difficult to finance with a reasonable increase in the existing flows of development resources.The situation of lower middle income countries typically looks more like that of low-income countries than that of upper-middle income countries. At least, with respect to those countries within these groups that have not met yet the MDGs.More generally, LICS and LMICS, the cost of achieving the MDGs is on the order of exististingdevelopment resources , implying that these will need to more or less double in these countries.However, the picture is not as demanding when the bottom-up costs.
Concessionary and Private Capital Flows from DAC Member Countries to Developing CountriesBoth ODA and private capital flows from DAC member countries to developing countries have grown considerably over the last four decades and particularly since over the last ten years:After increasing by more than 63% during the last decade, official development assistance (ODA) decreased by nearly 3% in 2011. The pressure put on public budgets by the financial crisis is such that this trend is likely to continue in the coming years. -Private capital flows to developing countries have reached their peak in 2007, at above USD 330 billion,billion, only to sink below USD 130 billion in 2008 – just under their 1978 level in real terms. The amount and the trend for private capital flows are such that the prospect of filling the financing gap in low-income countries at least partly through increased private capital flows is a real option. However the very high volatility of these flows is notable and needs to be addressed. The spillovers of these flows in terms of social development also need to be boosted through the right type of policies from and partnerships with the public sector.-Grants by private voluntary organisations have also grown although, at USD 22 billion, they are still in a smaller order of magnitude than ODA and private capital.
- The amount of domestic resources that developing countries are estimated to be able to raise through increased tax revenues is about half the size of the USD 120 billion amount in additional resources annually. On average the corresponding increases in the tax revenues : gdp ratio look reasonable, between 2.5-5%, especially starting from typically low collection ratios in developing countries.Difference between low-income and middle-income countries in the potentially availabletax resources is striking: Additional tax resources available in middle income countries cancover the cost of MDG-related service needs. However, note that there is a mismatch between countries where taxes can be raised in principle and countries where MDGs are located. This raises the issue of what scope there is for international cooperation between emerging economies to help with development. Low-incomecountries however do not have the same capacity. There is no way their tax potential can cover either the top-down or bottom-up costs of their MDGs.
Some countries can make sizable gains, including some countries include some with significant financing gaps.In upper-middle-income countries and in much of Latin America, poverty could be considerably reduced through redistributive fiscal policy. We cannot expected that of other parts of the world.
Upper middle-income countries can be expected to mobilize enough DR to meet the MDGs, by bottom-up approach.In contrast, neither low-income nor lower middle-income countries can be expected to mobilize enough DR to meet their needs, either from a bottom-up or top-down approach.Policy options to address the MDG needs for low- and lower-middle income countries cannot be of the ‘either-or’ type but rather will take the form of ‘this-and-that’. We will need ODA, we will need the cooperation activities of emerging partners, we will also need FDI and remittances, as well as private donations. What one type of development financing flow cannot do on its own, 5 or more can, especially if the right type of policy reforms are pursued in developing and in advanced countries to improve the quality of public expenditure and of aid.
Let me nowconlude by highlighting some of the policy implications we think we can derive from our numbers. If I had made this presentation in French I might have used the expression, « pistes de réflexion » as what follows are based, once again, on what can only be considered orders of magnitude, not precise estimates and there are many methodological limitations to the exercise.With these caveats in mind, one thing that has emerged again and again from consulting stake-holders is that political will is paramount. Taking on the challenge of eradicating poverty, including in MICs, is not going to happen if it does not become the priority of policy-makers. And just collecting and pouring more public money at the problem is hardly going to be the solution if the constrain is the administrative capacity and the quality of public expenditure.Therefore, given the order of the magnitude of the resources needed, and the current circumstances, time has come for OECD countries to deliver on policy coherence and aid effectiveness and for developing countries to deliver (further) on improving tax collection, public expenditure and investment climate
There is a stark contrast between the relative with which upper middle income countries should be able to meet all their MDGs and the challenge while this still represents for lower-income countries.Partners can therefore help by providing dialogue spaces created to share knowledge and good practices regarding what works and how to make reform happen.So, saying that the core of development financing can come from within in UMICS is not tantamount to saying that OECD countries should disengage from them, to the contraryIn low-income countries, the financing gap is such that the case for a big push in development financing is still measurable even if it’s become a bit of a rude word in erudite circles over the years. The key point is that the size of extreme poverty in its multiple dimensions is such that it’s worth doing what it will take to grow the entire income distribution in those countries out of poverty. This said, tax revenues already represent 10 times more resources than aid in Africa. Some of this is explained by high oil revenues in a few MICs but not all. So it is clear where the future of development financing lies for Africa as well although this is not for tomorrow for all countries, obviously.
Clearly the size of the challenge, particularly in LMICS and LICS is such that we will need all development resources to play their role, hopefully with my synergies than at the moment, as a result of the global partnership for development and of a more inclusive dialogue amongst all stakeholders.Finally, the size of the challenge is also such that we will need more value for money. There is way to cut corners going forward regarding the quality of policies in both developed and developing countries. The quality of aid and cooperation will need to improve given that ODA is forecast to stagnate at best for the years to come. And in developing countries, the quality of public expenditure will have to improve in line with collected tax revenues. In any case, it’s close to impossible to increase tax collection if tax-payers are not convinced their taxes are reasonably well spent.
Let me end by throwing at the audience a few questions that the study does not ambition to answer but hopes to put on the table…
Using the Poverty Gap to Calculate Transfers to the Poor (MDG 1)The poverty gap index (Foster et al., 1984) measures the mean proportionate shortfall from the poverty line for a given population. We use the poverty gap approach to measure the total transfer required to eradicate poverty in a given country for a given income distribution. The poverty gap is easily computable from the parameters of the Lorenz curve, the poverty headcount, mean income, and the poverty line, following Datt (1998).The poverty gap associated with the mean income and poverty headcount obtained under a “business as usual” growth scenario through 2015 -based on the most recent World Economic Outlook projections from the IMF-can be compared to the poverty gap of a distribution associated with the target growth scenario calculated for the financing gap calculation of Chapter One. The difference between the predicted and the targeted poverty gaps in 2015 can then be used to calculate the aggregate transfer that will be needed every year to keep sufficient numbers of poor people out of poverty to assure that the poverty headcount is half its 1990 levels.
Calculating Expenditure to Meet Education-related Goals (MDGs 2 & 3)The cost of achieving universal primary education is estimated using the method proposed by Delamonica et al. (2001). Based on country-specific unit cost estimation of primary education, this study projected the annual additional cost of reaching a net enrolment ratio equal to 100% for primary education by 2015. According to the definition of the United Nations’ Statistics Division, the net enrolment rate (NER) in primary education is the number of children of official primary school age who are enrolled in primary education as a percentage of the total children of the official school age population. The NER data available for years 1999-2009 and data for public expenditure on primary education come from UNESCO and the World Bank. Population census and projections are taken from the United Nations’ World Population Prospects, the 2010 Revision (United Nations, Population Division). GDP per capita is taken from the IMF World Economic Outlook data, April 2011 Edition. Public expenditure per student is the current public spending on education divided by the total number of students by level, as a percentage of GDP per capita. Public expenditure (current and capital) includes government spending on educational institutions (both public and private), education administration as well as subsidies for private entities (students/households and other private entities), (World Bank Data).Under the baseline projection, which assumes NERs remain constant, the projected additional expenditure can be considered an upper bound estimate of the cost that could be incurred in 2015.
Calculating Expenditure to Meet Health-related Goals (MDGs 4, 5, & 6)Health-related MDGs include reducing child mortality (MDG 4), improving maternal health (MDG 5), and combating HIV/AIDS, malaria, and other pandemic diseases (MDG 6). According to the World Health Organization (2010), ensuring access to the types of interventions and treatments needed to address MDGs 4, 5 and 6 requires on average “little more than USD 60 per capita [annually] by 2015”.It is legitimate to wonder how realistic it is to assume that USD 60 per capita would be the amount of health expenditure required to meet health-related MDGs in all developing countries. This study, however, sticks to WHO’s USD 60 per capita estimate not only because the virtue of its simplicity and transparency but also because it is questionable whether health-related MDGs are as meaningful in middle-income countries as in lower-income countries. With the USD 60 per capita target maintained, to calculate how much additional expenditure will be required globally to meet this threshold, baseline spending on health first needs to be estimated under reasonable assumptions about future spending.The current level of government spending on health is projected up to 2015 for 128 developing countries for which data is available. Data for per capita total expenditure on health come from the WHO. IMF World Economic Outlook data, April 2011 edition forecasts are used for GDP growth projections between 2011 and 2015. These costs per inhabitant are multiplied by population projections coming from the United Nations’ World Population Prospects, the 2010 Revision (United Nations, Population Division). Our baseline is a constant scenario, where initial per capita expenditure for health in 2009 remains constant.
Estimating the Scope for Scaling-up Domestic Resources MobilisationThe degree to which countries can scale-up the mobilisation of their own domestic resources to finance the local achievement of the MDG’s is explained by an adoption from the techniques used by Piancastelli (2001) and Bird et al. (2004; 2008) to calculate “tax effort” in developing countries. Their tax effort index is calculated to compare predicted tax revenues to actual tax revenues and to estimate how much extra tax revenue may be collected if a country improves tax collection. Empirically, taxes as a share of GDP can be shown to depend on the economy’s level of development, on the share of the economy that is formal or industrialised and on the openness of the economy to trade. Generally, higher levels of development and higher levels of openness coincide with higher levels of tax collection. Predicted tax revenue is estimated using a regression framework (pooled OLS and fixed effects) for the period 2000-2010 for all countries for which data for tax revenues, agricultural share, trade openness and GNI per capita were available. The ratio of predicted tax revenues to actual tax revenues is called “tax effort”: Countries with tax effort below 1 are collecting fewer taxes than they are expected to given their structural characteristics, while countries with tax effort above 1 are collecting more than they are expected to.
Aid flows have doubled between the early 2000s and the end of the decade.Budget pressures on many DAC member governments are such that expecting ODA to remain constant in nominal terms is probably already an optimistic scenario.There is a need to re-examine the focus on the often cited goal of increasing ODA flows to 0.7% of DAC member GDP.
DDD "what would it take to achieve the #MDGs by 2015?"
4th DAC Development Debate What would it take to achieve the MDGs by 2015?Can we still Achievethe Millennium Development Goals?FROM COSTS TO POLICIES An OECD Development Centre study Jean Philippe Stijns, Ph.D., Economist OECD Development Centre
Motivation The paper sizes the additional development resources • that are needed •And that are potentially available to attain the MDG’s in developing countries 2015 deadline is rapidly approaching, and progress remains to be made Growing demand for data on domestic resources available for development, and how they compare to other flows (See AEO 2010- 2011). Cf. Los Cabos report of the G20 working group on development. MDG’s too often thought of as Millennium “Donor” Goals. Revisit MDG costing exercises from early 2000s & extend to scope for domestic tax collection.
Outline1 Why revisit the cost of achieving the MDGs?2 How much would it cost?3 How to pay for the MDGs?4 What policy implications can we derive?
1. Basis of cost estimates 6 out of 8 goals Poverty reduction target Halve the proportion of people living on <$1.25/day Education target(s) Achieved if net enrolment ratio reaches 100% Health related target(s) WHO : Multiple health related targets are met if a level of total expenditure for health exceeds 60 USD per capita
1. Costing MDGs Direct transfers addressing MDG’s Top-Down assuming unchanged quality of growth Growth Dev’t Poverty Poverty Health Educ. Health Educ. Poverty, Education and Health Bottom-UP are addressed through economic growth assuming unchanged income distribution. Source: Atisophon et al. (2011) – OECD DEV WP #306
1. Limitations(real & imagined)1. MDGs were conceived to be met at the global level. Is it unfair to benchmark all countries the same way? Or is it good to apply some gently pressure? But what is the accountability and ownership dynamic?2. The causal MDG achievement & development is questionable Some goals are outputs: e.g. school enrolment; but how about quality? Some goals are impacts: e.g. mortality / prevalence but how enabling is the environment?3. Development financing is not the same as ODA Yet, some countries are still highly dependent on aid (30-50% of revenues); Yet (more) efficient taxes don’t always translate in (more) efficient expenditure. Cf. Global Forum on Development.4. How reliable are the estimates? There are intersections between the MDGs. Conversely, there are serious capacity bottleneck issues. Even the bottom-up approach assumes constant quality of growth…
2. The Big Number 2009 USD billion 20 Low-income countries with financing gap Total 62.1 59.2 121.3 79 Low-and middle income countries with service provision expenditures* But nothing in the making of these numbers imply that this gap necessarily needs to be completely addressed by ODA…Source: Authors’ calculations
2. Top-Down vs. Bottom-Up 160 2009 USD billion 140 140 120 Bottom Up 100 79 80 62 60 Top Down 40 33 34 20 6 0 Upper-middle income Lower-middle income Low incomeSource: Authors’ calculations
2. Top-Down vs. Bottom-Up 180 170 2009 USD billion 160 140 120 100 89 80 60 36 40 26 20 6 9 10 2 0.5 1 4 0.1 0 East Asia & South Asia* Middle East & Europe & Sub-Saharan Latin America Pacific North Africa Central Asia Africa & Caribbean Bottom Up Top DownSource: Authors’ calculations
3. Needs vs. Means160 2009 USD billion140120100 80 60 40 20 0 Low income Lower middle income Upper middle income Financing Gap Existing Development Resources Bottom-Up CostsSource: Authors’ calculations
3. Development Resources 500 2008 USD billion 450 400 350 300 250 200 150 100 50 0 Private capital flows Net grants by private voluntary organisations Other official flows ODANote: Net OOF flows were negative in 2000-01, 2004 and 2006-07.Source: Authors’ calculations based on DOEC-DAC figures
3. Potential Tax Increases 5.0% % of 2009 USD 70 GDP billion 4.5% 60 4.0% 3.5% 50 Total Potential Tax Increase 3.0% 40 2.5% 2.0% 30 Average Potential 1.5% 20 Tax Increase as a 1.0% Share of GDP 10 0.5% 0.0% 0 Low-income Lower Upper middle- middle- income incomeSource: Authors’ calculations
3. Potential Tax Revenues (2)40 36353025 23201510 5 2 2 0 1 0 East Asia & Pacific & Central Asia Middle East & North South Asia Europe Latin America & Caribbean Africa Sub-Saharan AfricaSource: Authors’ calculations
4.Putting it all together160 Top-Down Costs140 Bottom-Up Costs120 FDI100 Remittances 80 ODA 60 Tax revenues 40 Additional Tax 20 Potential 0 Low income Lower middle income Upper middle incomeSource: Authors’ calculations
4.Policy Implications • It’s at least as much about political will and policies than about financing. • Need for a major upgrade in the quality of public policies and institutions: • Policy coherence and aid effectiveness; • Tax collection, public expenditure and investment climate.
4.Policy Implications • In upper middle-income countries: the goals are affordable (with political will and smart policy design) but: • Political will and policy reforms will be needed • And thus space for policy dialogue and capacity building • In low-income countries: donor countries should deliver on their aid commitments while the momentum for tax reforms is sustained.
4.Policy Implications • More than ever, private capital, development co- operation among countries of the South, remittances from migrants and private donations will need to complement aid. • Ensure that all these resources and domestic policies contribute to sustainable, inclusive growth and to social development.
4. So what’s next? Post-2015 Do the high costs of MDG achievement offer any guidance on what monitoring of international development objectives should be like after 2015? Is development “achieved” after overcoming the extreme poverty embodied in the eight MDG’s? What is the balance between country-relevant objectives and internationally comparable goals? Should enabling a growth environment be prioritized? Should tackling inequality or improving the quality of public expenditure instead be the main focus of reform? Should instead it be aid effectiveness and capacity building?
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Background: the MDGs UN Millennium Declaration (8 Sept 2000):adopts 8 goals to measure development progress 1990 – 2015. Goals are the broad objectives envisioned by member states in theMillennium declaration.Targets quantify how the goal can be achieved. Indicators allow the monitoring of progress towards reaching the targetsand achieving the goals. The paper sizes the additional development resources that are needed in developing countries to attain the MDG’s
5.Methodological Annex Incomes Categories (annual income per habitant – 2010) Upper-middle income: USD 3 976 – 12 275 Lower-middle income: USD 1 006 – 3 975 Low income: USD 1 005 or lessSource: OECD Development Centre based on World Bank data
5.Methodological Annex Reducing poverty through growth: Top-Down for MDG 1 We calculate growth in mean income needed to halve the 1990 headcount ratio. Poor Headcount ratio = f( mean income, poverty line, Lorenz0.25 curve parameters) 1990 2015 Since the per capita growth rate y = I/Y*1/ICOR – p 0.2 target and I =sY + additional resources + OF we can solve for additional resources as shown on the slide, using the y derived from the first step.0.15 Where I is investment, Y is GDP, p is population growth, s is the savings rate, OF is other flows, and 0.1 ICOR is the incremental capital output ratio (which we calculate as the sum of all investment 1990-2015 divided by the change in output between 2016 and 1990).0.05 ICOR is the inverse of the marginal productivity of capital– the higher it is the less productive investment is. 0 $0.00 Source: Authors’ calculations Additional resources = (y + p) * Y * ICOR – s*Y - OF
5.Methodological Annex Reducing poverty through redistribution: Bottom-Up for MDG 1 We can use the Poverty Gap (mean proportionate shortfall of the poor’s income from the poverty line) For those countries which aren’t on track to achieve the target growth rates: we calculate the poverty gap for 2015 using growth as predicted by the IMF WEO as a baseline. This is compared to the Poverty Gap that would obtain if the target growth rates are achieved instead. The difference between these two ratios multiplied times the poverty line (1.25 USD day, or 38 USD per month, or $456 per year) and then times the population of the entire country gives the aggregate transfer to the poor needed to eliminate poverty.
5.Methodological Annex Calculating Expenditure to Meet Education-related Goals (MDGs 2 & 3) NER Pessimistic 100 Universal completion of primary education can be restated as reaching a NER equal to 100%. 90 For the funding gap, we first estimate the baseline spending on education. 80 We estimate the spending that is needed to be spent to achieve the universal enrolment in primary 70 education. The funding gap, which is equal to the difference 60 between the two estimates, is calculated. 2009 2010 2011 2012 2013 2014 2015 100 For the baseline scenarios: 2 assumptions are Optimistic assumed. 90 NERs remain constant at their 2009 level. 80 (pessimistic) 70 NERs grow linearly following the preceding decade trend. (optimistic) 60 2009 2010 2011 2012 2013 2014 2015Source: Authors’ calculations Baseline
5.Methodological Annex Achieve health related MDGs Estimation strategy: According to WHO study, “the money needed to reach the health related MDGs in 49 low-income countries, suggest that, on average (un-weighted), these countries will need to spend a little more than USD 60 per capita by 2015. Projected per capita expenditure for health based on historical data and estimated the yearly financial gap between the required linear trends to reach per capita 60 USD expenditure by 2015. These costs per inhabitant are multiplied by population projections coming from the United Nations’ World Population Prospects, the 2010 Revision (United Nations, Population Division). Our baseline is a constant scenario, where initial per capita expenditure for health in 2009 remains constant.
5.Methodological Annex Estimating the Scope for Scaling-up Domestic Resources Mobilisation The scale-up of domestic resource mobilisation is explained by an adoption from the techniques used by Piancastelli (2001) and Bird et al. (2004; 2008). To calculate “tax effort” in developing countries, we use this index to compare predicted tax revenues to actual tax revenues and to estimate how much extra tax revenue may be collected if a country improves tax collection. Empirically, taxes as a share of GDP can be shown to depend on the economy’s level of development, on the share of the economy that is formal or industrialised and on the openness of the economy to trade. Generally, higher levels of development and higher levels of openness coincide with higher levels of tax collection.
ODA vs. Private Capital Flows0.9% ODA, other official flows and net grants by % GDP of DAC0.8% private voluntary organisations member Countries0.7% Private capital flows0.6%0.5%0.4%0.3%0.2%0.1%0.0%Source: Authors’ calculations based on OECD-DAC
How Much for poverty? 0.2 Middle East & Upper-middle 0.1 North Africa income 0.6 Europe & Central Lower-middle Asia 2.4 2.3 income Latin America & 4.2 Caribbean Low income Sub-Saharan Africa 62 130 170 140 78 1.9 8.5 10 89
How Much for Health? Health needs (MDGs 4-6) measures by Income Group The Big Picture and Region (2009 USD bn) 0 Most of the extra spending on health will be needed in sub-Saharan Africa and South Asia. in order to cut child Upper-middle income mortality by two thirds, reduce the 28.8 Lower-middle income maternal mortality ratio by three 30.1 Low income quarters and halt AIDS, malaria and other major diseases. The highest costs are associated with health (MDGs 4-6) in low- and lower- 0.2 Middle East & North middle 0 Africa countries, USD 59 billion, and, in terms 0.2 Europe & Central Asia of regions in South 4.3 Asia, USD 35 billion, and in sub- 19.5 East Asia & Pacific Saharan Africa, USD 20 billion. Latin America & Caribbean South Asia 34.8 Sub-Saharan Africa
How Much for Education? Education needs (MDGs 2-3) measures by The Big Picture Income Group and Region (2009 USD bn) Upper-middle 1.1 income Although overall school attendance has increased over the past decade, it will still Lower-middle income cost up to USD 8.8 billion to achieve 2.2 universal primary education by 2015. Low income 5.5 The region which requires the highest increase in spending compared to baseline expenditure is Latin America and the Caribbean because of the high cost per Middle East & North 0.4 student in the region. Africa Europe & Central Asia 1 The most challenging rate of increase in 2.3 East Asia & Pacific baseline expenditure that is required is with Sub-Saharan Africa, 22.3%, while middle- 1.3 Latin America & income countries have the largest Caribbean expenditure shortfall, USD 7.7 billion in 1 South Asia total. 2.9 Sub-Saharan AfricaSource: Authors’ calculations