Low-Income Countries: International Financial Institutions Met Many Goals in Response to Financial, Food, and Fuel Crises, but Impact on Spending Difficult to Establish
Released: 2011-10-26T00:00:00

Letter

Background

Since 2007, a series of overlapping food, fuel, and financial crises have negatively affected the world economy, prompting the IFIs to respond. (See fig. 1.)

Between 2007 and 2009, a financial crisis in the U.S. subprime mortgage market gradually extended to other developed countries and became a global financial crisis, which in turn generated a global economic crisis impacting developed and developing countries—including LICs—with varying degrees of intensity. Prior to, and partly in parallel with the financial crisis, global food and fuel prices increased sharply between mid-2007 and mid-2008. In some cases this exacerbated the impact of the financial crisis and some governments banned food exports. Although international food and fuel prices dropped precipitously as the global financial crisis unfolded in late 2008, they have resurged to record highs again in 2011, igniting concerns about a repeat of the 2008 food crisis and its negative impact on poor people in developing countries, particularly LICs.

IFIs and global leaders have launched a coordinated international response to the crises. In March 2009, the World Bank announced a comprehensive crises response framework that could channel additional donor contributions to poor countries to bolster ongoing World Bank activities. To help ensure that IFIs would have sufficient resources to respond to the crises, in April 2009 the Group of Twenty (G-20) world leaders committed to measures designed to increase IFI resources available to LICs, including through voluntary bilateral contributions to the World Bank’s crises response framework. The G-20 also endorsed the IMF’s intention to increase financing for LICs, including from resources derived from proceeds of IMF gold sales.

LICs, the majority of which are in sub-Saharan Africa, comprised a population of about 810 million people at the outset of the crises in 2007. Most LICs depend to some extent upon imports of food and fuel, and about half are classified as fragile states challenged by weak capacity, poor governance, political instability, ongoing violence or the legacy of past conflict, as shown in fig. 2. According to IFIs, these factors can render countries vulnerable to crises driven by fluctuations in international food and fuel prices. ........................................

Instructions:

Online, hover over a country name in the table for more information. For print version, see appendix II, page 53.

In food-importing countries, imports of basic foodstuffs outweighed exports over the past 3 years, according to the UN Food and Agriculture Organization. We define net energy consumers as those countries for which net energy production was less than consumption in 2009. The World Bank uses the term “fragile” to refer to countries with particularly weak policies and institutions, as well as those with the presence of a UN or regional peace-keeping or peace-building mission during the past 3 years.

The World Bank and IMF provide financial and technical assistance to member countries. Two World Bank institutions—IDA and IFC—assist LICs. IDA, the primary World Bank financer to LICs, provides no-interest loans and grants to eligible countries that have limited or no access to international credit markets. IDA funds long-term programs in agriculture, infrastructure, and social services such as health and education, and provides technical assistance for programs in economic and institutional development to strengthen country policies and institutional capacity. Commitments to these programs are disbursed at different rates depending on a number of factors, including recipient country capacity and whether the project is an investment lending project or a development policy lending project. The rate of disbursements is important because committed funds cannot be used by recipient countries until the funds are disbursed. IFC provides investments and advisory services to build the private sector in developing countries, including LICs.

The IMF provides economic surveillance, lending, and technical assistance to its member countries. IMF surveillance involves the monitoring of economic and financial developments and the provision of policy advice. The primary purpose of IMF lending is to assist countries facing balance-of-payments difficulties, and IMF loans to LICs are intended to help foster economic growth and reduce poverty. IMF lending is conditional upon borrowing countries’ implementation of policies. To help countries manage their economies, the IMF provides guidance and training on how to strengthen institutions and design appropriate macroeconomic, financial, and structural policies.

Since 1996 the World Bank and IMF have participated in bilateral and multilateral efforts to relieve the debt burdens of poor countries to help them achieve long-term economic growth and debt sustainability, meaning they can make their future debt payments on time without rescheduling. To assess how a country’s current level of debt and prospective new borrowing affect its ability to service its debt in the future, the World Bank and IMF jointly conduct a DSA. DSAs include an analysis of a country’s projected debt burden over the next 20 years and its vulnerability to shocks. In 2009, we reported that the World Bank and IMF had improved their DSAs, including by considering the strength of a country’s policies and institutions, and that the DSAs identified numerous ambitious actions countries should take in order to avoid future unsustainable debt levels.

Crises Negatively Impacted LICs, but Less Than Experienced by Advanced Economies

The food, fuel, and financial crises negatively impacted LIC economies, but the slowdown in growth was less than experienced by advanced economies. Our analysis shows that during the crises period of 2007 through 2009, key economic indicators slowed or declined for 38 LICs compared to the pre-crises period of 2004 through 2006.

Economic Growth Slowed and Inflation Increased

While the average annual growth rate in real gross domestic product (GDP), or national income, for the 38 LICs remained positive during the crisis period, it declined by an average of about 1 percentage point, dropping from an average of 7.1 percent during the pre-crises period to an average of 6.2 percent during the crises period. The largest decline occurred between 2007 and 2009 when real GDP growth fell nearly 2 percentage points, from 7.1 percent to 5.3 percent. (See fig. 3.) Nine countries experienced an actual decline in their real GDP in 2008 or 2009: Cambodia, Chad, Eritrea, Guinea, Madagascar, Mauritania, Niger, Solomon Islands, and Zimbabwe.

The slowdown in the growth rate of real GDP in LICs was milder than the downturn in real GDP growth experienced by advanced economies during the crises, which declined from 2.7 percent in 2007 to -3.4 percent in 2009. According to the IMF, the LICs’ period of growth prior to the crises provided a cushion, helping many countries weather the food and fuel price increases between 2007 and 2008 and the global financial crisis. However, IFIs have reported that lower growth rates caused by the crises could lead to increases in poverty in LICs.

Moreover, the slowdown in real GDP growth occurred while LICs’ inflation was rising. The average annual inflation rate for 38 LICs increased from 8.6 percent during the pre-crises period to an average of 11.6 percent during the crises, peaking at nearly 14 percent in 2008. (See fig. 4.)

Higher food and fuel prices contributed to rising inflation. World food prices were stable from 2001 to the beginning of 2007, and then climbed steeply during 2007 and 2008. After a brief downturn in the latter part of 2008, world food prices began rising again, resulting in a net increase in prices of about 74 percent between January 2007 and May 2011. (See fig. 5.)

Similarly, world crude oil prices rose sharply during 2007 and 2008 and, after receding through early 2009, rose again through May 2011, resulting in a net price increase of over 99 percent when compared to January 2007. (See fig. 6.)

While the human and social development impacts of higher prices vary by country, the resurgence in prices has triggered renewed concern. Our previous work shows that many LICs were experiencing protracted food emergencies and had severe and widespread malnourishment even prior to the onset of the crises. In April 2011, the IFIs warned that the resurgence of higher food prices was increasing the cost of food imports in LICs, aggravating existing balance-of-payments problems and putting pressure on government budgets. Moreover, in July 2011, the UN World Food Program declared a food crisis in eastern Africa due mainly to low domestic harvests resulting from consecutive droughts.

Trade and Fiscal Deficits Worsened

The average current account (trade) deficit-to-GDP ratio for the 38 LICs increased from 3.6 percent in 2007, to 5.4 percent in 2008, and decreased to 4.2 percent in 2009, as shown in figure 7. Twenty-eight countries experienced a widening of their current account deficit-to-GDP ratio during the crises period compared to the pre-crises period.

Moreover, the fiscal deficit-to-GDP ratio increased from an average of 2.6 percent in 2007 to 3.7 percent in 2009 for 37 LICs, attributable more to rising expenditures than declining revenues. The fiscal deficit-to-GDP ratio for the LICs averaged 1.8 percent between 2004 and 2006 and nearly doubled to 3.2 percent between 2007 and 2009. The IMF reported that most LICs adopted a countercyclical fiscal response, such as preserving or expanding spending to support the economy and protect the poor. The growth rate of real primary expenditures accelerated, leading to a widening of the fiscal deficit-to-GDP ratio. The IMF also reported that LICs could increase spending, in part, because they had established sufficiently strong fiscal positions before the crises began.

Foreign Direct Investment Declined in 2009

Net foreign direct investment inflows for 39 LICs declined by 17 percent during 2009, ending a generally steady increase since 2000, as shown in fig. 8. Twenty-three of the 39 countries, or nearly 60 percent, had lower net foreign direct investment inflows in 2009 compared to 2007.

IFIs Increased Funding and Met Many Disbursement Goals, but the Impact of Their Actions on LIC Government Spending Has Been Difficult to Establish

In response to the crises, we found that IDA met its goal to increase the amount of financial assistance and partly met its goal to increase the speed of disbursements to LICs, but the impact of IDA’s actions on LIC government spending has been difficult to establish. The IFC increased assistance to LICs but its response was limited by capacity constraints and is difficult to measure. The IMF significantly boosted financial assistance to LICs, but its contribution to LIC government spending increases during the crises has been difficult to establish.

IDA Increased Financial Assistance and Met Many Disbursement Goals, but Impact on Government Spending Has Been Difficult to Establish

IDA met its goal to increase the amount of financial assistance and partly met its goal to increase the speed of disbursements to LICs. In addition, IDA reported that its crises response initiatives supported LIC government spending but we found that the impact has been difficult to establish.

The World Bank responded to crises in LICs through regular IDA lending and by establishing initiatives. The World Bank committed a total of $18.1 billion in IDA funds to LICs during the crises response period between 2008 and 2010 through both regular IDA lending and crisis response initiatives. This represented an increase in new commitments of approximately $5 billion, or 39 percent, as compared to commitments made between 2005 and 2007. These resources were part of a fixed 3- year allocation, replenished in 2008 prior to the onset of the global economic crisis. This allocation represented an increase of 12.8 percent as compared to the 2005-2008 IDA allocation and was intended in part to help countries achieve the Millennium Development Goals (MDGs). To respond to the crises within the context of this fixed set of resources, IDA could choose to shift its priorities toward crisis response, accelerate disbursements of existing IDA funds, or provide additional funds from donors or internal resources.

To complement regular IDA lending during the crises, the World Bank established a crisis response framework comprised of five initiatives that committed $12.2 billion in financial assistance to LICs between 2008 and 2010. These commitments included $10.8 billion in existing IDA funds and $1.4 billion in new financial assistance. The five initiatives are: the Global Food Crisis Response Program (food program), established in May 2008 to help countries reduce the impact of high food prices on the poor by providing rapid financial assistance, policy advice, and social protection services such as food stamps and school feeding programs for the most vulnerable; the IDA Fast Track Facility, established in December 2008 to help countries offset the impacts of the financial crisis on governments’ budget expenditures, including social and infrastructure programs; the Rapid Social Response Program (social protection program), established in April 2009 to help countries mitigate the impacts of crises by promoting social protection programs through rapid financing of immediate interventions in safety nets and other areas, and by improving capacity needed to establish and implement effective safety net systems; the Infrastructure Recovery and Assets Platform (infrastructure program), established in March 2009 to help countries mitigate the impacts of the crises by supporting critical infrastructure investments and new project development and implementation, and; the Pilot Crisis Response Window, established in November 2009 to help reduce the need for countries to make tradeoffs between financing crises response efforts or long-term development programs by providing new financing that was additional to countries’ existing IDA funds.

In response to the crises, IDA committed $1.4 billion in new financial assistance to 36 LICs between 2008 and 2010. Four of the five initiatives—the food, social protection, and infrastructure programs and the Pilot Crisis Response Window—aimed to increase the amount of financial assistance available to LICs using additional donor contributions and internal World Bank resources. We found that IDA committed $1.1 billion in new financial assistance to LICs through the Pilot Crisis Response Window and $288 million in new grant assistance to LICs through the food and social protection programs. The World Bank reported that governments’ requests for social protection grants to establish and enhance safety net systems provided by the social protection program significantly exceeded the availability of new resources. By April 2011, LICs had submitted 133 project proposals totaling $161 million against available funding of about $58.5 million. These projects were to establish or enhance social protection activities and safety net systems benefiting the poorest, as well as to improve the data and institutional capacity necessary for effective implementation. The World Bank further reported that it has established a permanent Crisis Response Window effective July 2011 that could be used to continue to fund activities supporting both crises response and preparedness in IDA-eligible countries, including LICs. Finally, donors did not provide additional funding to the infrastructure initiative, which was originally designed to provide up to $3 billion to help offset the impact of soaring energy prices.

Four of the five IDA initiatives—the Fast Track Facility, food program, social protection program, and Pilot Crisis Response Window—were designed to increase the disbursement speed of commitments made from existing IDA funds. While disbursement rates are a useful metric for capturing the World Bank’s response to the immediate needs of recipient countries through the crises response initiatives, we recognize that there are other less quantifiable considerations for assessing the impacts and effectiveness of development assistance. These initiatives were also designed to increase the speed of project preparation and processing, which occurs prior to project approval. According to the World Bank, preparation time was reduced during the crisis for both investment lending and development policy lending programs. To determine whether the disbursement speed of commitments made through the crises response initiatives had increased, we compared the first year disbursement rates for each initiative to the first year disbursement rate of projects approved from 2008 through 2010 that did not fall under any initiative. The World Bank uses a different methodology to report disbursement rates. We did not use the World Bank’s standard disbursement rate methodology because our analysis sought to isolate those activities which were explicitly undertaken in response to the crises.

These initiatives committed approximately $3.9 billion to 32 LICs from existing IDA funds. Three of four initiatives increased the speed of disbursements. The infrastructure program, which committed $6.9 billion in existing IDA funds in addition to the $3.9 billion, did not have a goal to increase the speed of disbursements. More specifically:  The first year disbursement rate was 69.1 percent for the Fast Track Facility, compared to a first year disbursement rate of 33.5 percent for projects that were not funded through an initiative.  The first year disbursement rate was 64.5 percent for the food program, compared to a first year disbursement rate of 33.5 percent for projects that were not funded through an initiative. However, we found that almost half of the commitments made through existing IDA funds, about $405 million, went to three projects in Ethiopia and Bangladesh. When these projects are excluded from the analysis, the disbursement rate for this initiative declines to 39 percent.  The first year disbursement rate for the social protection program was 34.1 percent, slightly higher than the first year disbursement rate of 33.5 percent for projects that were not funded through an initiative. However, the social protection program did not increase the speed of disbursements when compared to social protection projects approved during the pre-crises period, which had a first year disbursement rate of 47.8 percent. According to the World Bank, increasing the speed of disbursements for social protection programs in LICs has been challenging due to a lack of existing social protection programs and recipient countries’ capacity to effectively implement them. To address this challenge and facilitate crises preparedness in LICs, the World Bank intends to continue to finance the development of social protection programs. In early 2011 donors emphasized the importance of a continued focus on capacity building and improved data collection in LICs, to help overcome these constraints.  The Pilot Crisis Response Window did not increase the disbursement speed of commitments, with a first year disbursement rate of 27.5 percent, compared to a first year disbursement rate of 33.5 percent for projects that were not funded through an initiative (see fig. 9).

In 2009, the Development Committee, an advisory group to the World Bank and IMF, also urged the acceleration of the delivery of financial assistance to recipient countries. However, we found that the World Bank did not accelerate disbursements for both investment lending projects or development policy lending projects for the group of LICs on average as a whole even though a majority of countries received disbursements faster during the crises response period. Specifically, the average first year disbursement rate to LICs was 16.8 percent for all investment lending projects approved between 2008 through 2010, as compared to an average first year disbursement rate of 17.3 percent for all investment lending projects approved between 2005 through 2007. Similarly, the average first year disbursement rate to LICs was 90.7 percent for all development policy lending projects approved between 2008 through 2010, as compared to an average first year disbursement rate of 96.9 percent for all development policy lending projects approved between 2005 through 2007. Overall, the average first year disbursement rate to LICs was 31.1 percent for all projects approved between 2008 and 2010, as compared to an average first year disbursement rate of 39.3 percent for all projects approved between 2005 and 2007, a difference of about 8 percentage points. According to U.S. Treasury, this decline in part reflects the World Bank’s need to ensure that recipient country capacity and governance controls were sufficiently robust to absorb the additional resources provided during the crisis period.

However, at the individual country level, total commitments in 22 of 36 LICs, including commitments made to both investment lending projects and development policy lending projects, were disbursed faster during the crises period than during the pre-crises period. Disbursement rates, which vary over time, depend on a number of factors, including recipient country capacity, need, and governance, and the type of lending. For example, commitments to Burundi, a fragile state with limited capacity, increased by 114 percent while disbursements increased by 46 percent, which results in a lower disbursement rate during the crises response period. (See fig.10.) LIC governments reported mixed experiences relating to the timeliness of the World Bank’s response to crises. Some governments said they received financial support very rapidly, while others noted that World Bank support had been sluggish. For a more detailed analysis of World Bank commitments and disbursement rates to individual countries, see appendix III.

The World Bank reported that speed was facilitated by the Bank’s new rapid response policy and increased use of development policy lending where circumstances permitted. In addition, World Bank and U.S. Treasury officials reported that the restructuring of existing lending portfolios facilitated an expedient response in some countries.

Two initiatives were designed to support domestic spending in recipient countries during the crises, in areas including social services, education, and infrastructure. In 2010, the World Bank reported that both initiatives— the Fast Track Facility and the infrastructure program—met this goal. For example, the World Bank reported that the Fast Track Facility operation in the Democratic Republic of Congo prevented the government from having to cut essential social spending or resort to inflationary spending. Similarly, the World Bank reported that the infrastructure program supported domestic spending and helped to mitigate the direct impacts of the crisis.

However, as we previously reported, IFIs do not independently track developing countries’ poverty-reducing expenditures and instead rely upon developing countries’ governments to provide such data, even though the accuracy of these data and country capacity to provide this information is questionable. Additionally, for the infrastructure program, the World Bank developed a rapid diagnostic tool to identify at-risk countries and provide a detailed assessment of crises impacts and associated country infrastructure spending needs, but conducted the diagnostic in only one LIC, Bangladesh. Therefore, we found that the degree to which World Bank actions impacted government spending has been difficult to establish.

IFC Increased Assistance to LICs, but Its Response Was Limited by Capacity Constraints

The IFC responded to the food and fuel crises through lending in the agriculture and energy sectors and responded to the financial crisis through existing and new initiatives and by enhancing coordination with donors, but its response was limited by capacity constraints. Between 2008 and 2010, IFC increased its new lending commitments in LICs while new IFC commitments overall declined and foreign direct investment in LICs declined by 17 percent between 2008 and 2009. As a result, IFC’s investments during the crises in LICs increased as a percentage of net foreign direct investment. Annual IFC commitments in LICs in fiscal years 2009 and 2010 exceeded $900 million each year, while commitments in fiscal year 2008 were about $460 million. IFC also committed a total of $1.1 billion to LICs through two crisis response initiatives, the pre- existing Global Trade Finance Program and the new Global Trade Liquidity Program, which supported $3.4 billion in trade through credit guarantees and risk sharing.

According to officials, IFC also developed new approaches for coordinating with other multilateral institutions in LICs at the regional level. The Joint Action Plan for Africa, established in 2009, for example, developed a method for IFC to collaborate more closely with other lenders in support of development activities in Africa. Similarly, officials said that agreements with donors, made to enhance the response to the financial crisis, will allow IFC to quickly coordinate with donors in response to a future crisis.

According to IFC officials, IFC’s response was limited by internal and external constraints. Internally, under its Articles of Agreement IFC must undertake its financing on terms and conditions which it considers appropriate, taking into account, among other things, the terms and conditions normally obtained by private investors for similar financing. In addition, IFC has relatively limited resources as compared to other IFIs. Officials told us that because of these constraints, much of its crisis response relied on donor governments to provide additional funds. In some cases, this dependence negatively affected the speed of IFC’s response because IFC could not respond until donor governments fulfilled their commitments. IFC also faced external capacity constraints in recipient countries. For example, officials explained that in Ethiopia, foreign investors, including IFC, are often subject to additional scrutiny by the government, which has limited IFC’s ability to do business there. Overall, IFC officials said that the actions they took to respond to the crises sent a positive signal to the market, but officials noted that this is difficult to measure and did not provide quantitative evidence of this effect.

IMF Significantly Boosted Financial Assistance to LICs, but Its Contribution to Government Spending Increases Has Been Difficult to Establish

During the crises response period between 2008 and 2010, the IMF response included committing approximately $4.9 billion in new lending to 28 LICs, temporarily lowering interest rates on its loans, and doubling the limit individual countries could borrow against. In addition, the IMF provided $250 billion to support all of its members, including LICs, which collectively received the equivalent of $5.8 billion. Governments could use these funds to boost international reserves, cushion against shocks, or meet balance-of-payment needs. Moreover, the IMF changed its lending instruments to address crisis impacts, aiming to make them more flexible and tailored to specific country needs. For example, according to the IMF, the newly created Rapid Credit Facility provides low-access, rapid, and below-market-rate financial assistance to LICs facing an urgent balance-of-payments need, without requiring program-based conditions. According to IMF officials, these efforts were supplemented by technical support and surveillance activities, which also played a role in assisting LICs through the crises. In addition, the IMF reported that its policy advice and programs in LICs were supportive of a countercyclical policy response and higher government spending during the crisis. For example, according to the IMF, government spending increased in almost 90 percent of LICs with IMF programs in 2009.

We found that IMF loans to LICs increased more than sixfold from approximately $748 million between 2005 and 2007 to about $4.9 billion between 2008 and 2010. In the three countries we reviewed—Burundi, Ethiopia, and Tanzania—the IMF reported that country-specific program goals were achieved. However, circumstances may change quickly, and in one case, inflation resurged soon after the program ended. While conclusions from this sample are not generalizable to all LICs, these examples illustrate how IMF-supported programs operated in these three countries.

In July 2008, Burundi started a 3-year $76 million arrangement with goals to support poverty reduction and macroeconomic stability. Approximately 3 years later, a June 2011 IMF review stated that performance under the program has been broadly satisfactory, despite the impact of the food and fuel shocks. At the same time, however, the IMF also lowered Burundi’s 2011 economic growth projection to 4.2 percent, due in part to the expectation that higher food and fuel prices will continue.  Ethiopia requested a $240 million arrangement in August 2009 to help steer the economy through the global financial crisis, with the goals of reducing inflation and building international reserves. In October 2010, an IMF review concluded that the program was on track and that government policies to reduce inflation and increase reserves had been successfully implemented. According to IMF officials, the program ended in November 2010 and inflation rose to about 30 percent in May 2011, mainly because the government did not implement agreed-to reforms.  Tanzania began a $328 million 12-month arrangement in May 2009 with the goal of mitigating the adverse impact of the global financial crisis and addressing a projected deterioration in balance of payments stemming from a decline in exports and foreign direct investment. The IMF’s subsequent review determined that country program goals were met, and the program was concluded on schedule a year after inception.

The IMF also noted that LICs supported by an IMF program increased government spending during the crises, including on health and education services, more than countries that were not supported by an IMF program, and implied that this was attributable to the IMF programs “as Fund financing reduced liquidity constraints and helped catalyze donors’ support.” However, we found that this causal link has been difficult to establish because the comparison groups differ in important ways. In order to conclude that differences in government spending are driven by IMF programs, the groups of countries being compared need to be as similar as possible. Our analysis of the data underlying the IMF’s assertion found that non-program LICs consistently differed from program LICs across certain measures of institutional quality and macroeconomic policy. Furthermore, the finding that program LICs increased spending more than non-program LICs is highly sensitive to the inclusion of a few countries in the group of non-program LICs, which either did not need a program or could not obtain one. Non-program LICs had lower scores on a variety of measures of institutional quality, such as political stability, government effectiveness, and rule of law. Countries with institutional weaknesses in these categories may overlap with the fragile states, as shown in fig. 2. In addition, non-program LICs had higher inflation rates and larger budget deficits prior to the crises than LICs with IMF-supported programs, which may indicate that non-program countries had less capacity to use fiscal and monetary policy to respond to the crises.

We conducted several analyses to determine if the IMF’s results were sensitive to small changes in the underlying sample of countries designed to make the set of non-program LICs more like LICs with IMF programs. In one analysis, we omitted the countries with the two lowest scores on political stability in 2009 (Sudan and Yemen) from the set of non-program LICs, thereby making the sample more similar to program LICs. Based on the new sample, program LICs no longer increased spending more than non-program LICs. In another analysis, we omitted the countries with the two largest budget deficits prior to the crisis (Eritrea and Guyana) from the set of non-program LICs and similarly found that program LICs no longer increased spending more than non-program LICs. Importantly, it does not necessarily follow from these sensitivity analyses that IMF- supported programs were ineffective at increasing spending. A reasonable estimate of what might have happened in the absence of an IMF-supported program is necessary to assess the impact of programs on spending, which the IMF analysis implicitly assumes is the experience of non-program LICs. A more rigorous analytical approach would be needed to conclude that IMF-supported programs resulted in increased government spending during the crises. Analytical approaches that systematically account for differences between program and non-program countries would be necessary to credibly conclude whether or not an IMF- supported program led to greater public spending.

IFIs Did Not Lower Debt Distress Ratings Due to the Crises, but If Underlying Projections Prove Too Optimistic Then Grants Could Be Increased

The IMF and World Bank prepare annual debt distress ratings, which assess countries’ ability to repay their debt. The IMF and World Bank did not lower any LICs’ debt distress rating as a result of the food, fuel, and financial crises. However, we found that some of the underlying macroeconomic projections might prove too optimistic based on current risks to the global economic recovery and rising commodity prices, as well as on our review of the debt sustainability analysis (DSAs) for three countries. If these projections ultimately prove too optimistic and countries’ ability to repay their debt declines significantly, some multilateral institutions could subsequently choose to provide more grants than loans to help lower the risk of debt problems reemerging. Our review of these DSAs is nongeneralizable and meant to be illustrative, not representative.

Debt Distress Ratings Assess Countries’ Ability to Repay Debt

The debt distress rating is the IMF and World Bank’s assessment of the risk that a country will not be able to repay its future debt. In assessing risk and determining a sustainable debt level, the DSA considers the strength of the country’s policies and institutions based on the World Bank’s Country Policy and Institutional Assessment index (CPIA). The index classifies LICs as weak, medium, or strong performers, with debt burden thresholds associated with each performance category, as shown in figure 11. For example, Ethiopia is in the “medium” performer category, which means that its performance will be judged against the debt burden threshold indicators for that category. The threshold indicator for the present value debt-to-export ratio is 150 percent. Exports are an important source of funding for repaying debt. The IMF and World Bank have determined that debt-to-export levels in excess of 150 percent put LICs ability to repay debt at risk. According to Ethiopia’s 2010 DSA, Ethiopia’s debt-to-export ratio is projected to reach a high of 133 percent in 2011 and then decline. Burundi, which is classified as a “weak” performer, faces a lower, more constraining threshold of 100 percent. According to its 2010 DSA, Burundi’s debt-to-export ratio exceeded this limit throughout the projection period by a wide margin. For example, from 2011 through 2013, that ratio was projected to be at or above 200 percent. The IMF and World Bank use the extent and duration of the threshold breaches to determine the country’s debt distress risk rating, as discussed below.

The assessment of the country’s risk of debt distress—meaning the country cannot service its debt without resorting to exceptional finance (such as debt relief) or a major correction in balancing its income and expenditures—depends on how the country’s debt indicators compare with these debt burden threshold indicators under the DSA’s “baseline” scenario, as well as under alternative scenarios and stress tests. The baseline is the main macroeconomic scenario which describes the evolution of the debt and the macroeconomic variables based on realistic assumptions and projections of key macroeconomic variables such as GDP, inflation, exports, imports, and government revenues. Countries are classified into four categories—low, moderate, high risk, or in debt distress—according to their likelihood of debt distress, based on the extent and duration of breaches in their threshold indicators. (See fig. 12.) Debt burden thresholds are not rigid ceilings, and, according to the IMF and World Bank, the debt distress rating seeks to strike a balance between a mechanistic use of the categories and a judgmental approach.

Countries classified as “in debt distress” or “high risk of debt distress” receive 100 percent grant financing from IDA, while countries at moderate risk receive 50 percent grants and 50 percent concessional loans, and countries at low risk continue to receive 100 percent concessional loan financing. As shown in figure 12, 13 of the LICs are “in” or at “high” risk of debt distress and 24 are either at “moderate” or “low” risk.

The DSA uses a 3-year moving average CPIA score in determining a country’s policy performance in order to reduce variations in the risk of debt distress rating stemming from small annual fluctuations in the CPIA that do not represent a material change in countries’ capacity to service their debt. If following the release of the new annual CPIA score, the updated 3-year moving average CPIA rating breaches the applicable CPIA boundary, the country’s performance category would change only if the size of the breach exceeds 0.05; if below 0.05, the country’s performance category would change only if the breach is sustained for 2 consecutive years.

IMF and World Bank Did Not Lower Debt Distress Ratings Due to Crises

Although the crises adversely impacted LICs’ economies, the IMF and World Bank did not change any country’s debt distress rating as a result of the crises, indicating that they did not expect the crises to adversely impact LIC economies enough to significantly impair their ability to repay debt. The IMF forecasted a rebound in LIC growth in line with the forecast of a quick recovery for the global economy. The global recovery, which the IMF subsequently reported is subject to risks, is expected to boost demand for LIC exports and improve access to foreign capital, both of which are expected to facilitate private sector growth. According to the IMF, the LICs’ period of growth prior to the crises provided a cushion, helping countries weather the food and fuel price increases between 2007 and 2008 and the global financial crises. As a result, LICs were able to implement countercyclical policies, such as preserving or expanding spending to support the economy and protect the poor, and expanding public investment.

For reasons other than the crises, the IMF and World Bank changed 10 LICs’ debt distress ratings from 2007 through 2010. (See fig. 13.) Nine ratings improved for the following reasons:  Six countries received full and irrevocable debt relief from government and multilateral creditors.  Two countries, Chad and Niger, had higher projected GDP growth stemming from growth in mineral sectors. Chad achieved higher GDP growth due to oil sector growth. Niger is implementing large uranium and oil projects, which are expected to boost exports and government revenues significantly.  Ethiopia’s rating changed due to the inclusion of workers’ remittances as an important source of debt service financing and resilience of the Ethiopian economy to the global economic crisis.

Only one rating worsened. Burkina Faso’s debt distress rating changed from moderate in 2007 to high in 2008 because the country was reclassified from a strong to medium performer and therefore exceeded the new, lower debt burden indicators.

The implication of a change in a country’s debt distress rating is that a country whose rating improves will generally receive a larger proportion of concessional loans, and if it worsens, it will receive a greater proportion of grants, as shown in figure 13.

According to the IMF and World Bank, the DSA’s quality depends to a large extent on the realism of the projections under the baseline scenario. As explained in their policy paper, realistic means that the scenario takes account of a country’s growth potential as well as its capacity constraints, including the risk that governments do not implement desired policy reforms. Further, historical averages for the key macroeconomic variables for the past 10 years may provide some guidance about the extent of realism in the baseline scenario projections. The IMF has indicated that explicit justification is required if sustainable debt ratios are driven by DSA assumptions that deviate sharply from historical norms.

We assessed the realism of the 2010 DSA projections for three countries—Burundi, Ethiopia, and Tanzania—and found that a too optimistic tone potentially prevailed. While conclusions from this sample are not generalizable to all LICs, these examples are illustrative of how DSAs are conducted. For the sample we reviewed, we based our conclusion on our analysis of the divergence between the DSA projections and their historic values, as well as on the reasonableness of the DSAs’ underlying assumptions that countries (1) would realize growth-enhancing investments; (2) would implement agreed-to reforms, such as tax reforms that would boost government revenues; and (3) would not be subject to adverse country-specific factors, such as recurring droughts, floods, and political instability. For the three countries we reviewed, we found that macroeconomic projections did not adequately consider the country’s vulnerabilities, such as failure to implement reforms, inability to make planned investments, or recurrence of adverse weather or political instability.

The 2010 DSA for Burundi projects that real GDP growth rate will increase from its 10-year historical average of 2.7 percent to an average of 4.7 percent over the medium-term. This projected strong GDP growth depends on several factors, including an increase in anticipated export earnings from privatization of the coffee sector, which accounts for about two-thirds of total exports, and integration into the East Africa Community, which could give Burundi access to a broad market of about 120 million people and attract more investment. However, Burundi might not meet the GDP projection if it does not realize the higher export earnings from reform of the coffee sector. Privatization of the coffee sector is occurring more slowly than expected, with only 13 of 117 coffee processing facilities sold because there were few interested buyers. While the government plans to accelerate the sale of the remaining stations beginning in 2011, it is not clear whether investors will buy them. In June 2011, the IMF lowered Burundi’s 2011 growth projection from 4.5 percent to 4.2 percent, noting that higher food and fuel prices were likely to continue to increase throughout the year.

The IMF reported that risks to Burundi’s macroeconomic outlook are significant and include higher food and fuel prices and a worsening of the political, social, and security situation, which would endanger donor support and could further worsen debt indicators. Nonetheless, the 2010 DSA assumes Burundi’s security and political situation will continue to improve. Moreover, Burundi’s 2010 DSA projected a large decrease in the fiscal deficit-to-GDP ratio, from a 5 percent average during 2007 through 2009, to 1.3 percent in 2015, based on a widening of the tax base as a result of continued tax reforms as well as reductions in spending. The IMF said that mobilizing domestic revenue is critical for Burundi’s fiscal sustainability. However, the fiscal deficit projections assume that Burundi will control government wages and reduce defense and security spending.

In 2010, the IMF and World Bank changed Ethiopia’s risk of debt distress from “moderate” to “low” based on the inclusion of workers’ remittances, which means that Ethiopia now receives 100 percent concessional loan financing instead of 50 percent grants and 50 percent concessional loans. In addition, Ethiopia’s 2010 DSA projected that Ethiopia would achieve strong export growth and implement key reforms. Ethiopia’s 2010 DSA projected exports as a percent of GDP to rise to 19.1 percent by 2015, compared to the 10-year average of 13.5 percent, and to further increase to a 31 percent average during 2016 through 2030. However, in April 2011 IMF staff expressed concern that Ethiopia’s failure to implement monetary reforms, including removing the government- imposed bank credit ceilings, as well as highly negative real interest rates, were hindering the commercial banks’ financing role, which is fundamental to higher growth. In May 2011, IMF staff lowered estimates for Ethiopia’s real GDP growth rate from the 7.7 percent forecasted in Ethopia’s 2011 DSA to 6 percent for 2011 through 2012 due to high inflation, restrictions on private bank lending, and a more difficult business environment.

The projected large increase in growth in the 2010 DSA depended on anticipated growth in service exports resulting from an expected increase in electricity exports based on current energy investments, greater investment in the national airline, and continued good harvests supporting agriculture. The DSA notes Ethiopia’s debt profile is very sensitive to export growth assumptions.

The inclusion of workers’ remittances as a source of debt repayment was a main reason for the improvement in Ethiopia’s debt distress rating in 2010. While the DSA projects workers’ remittances to remain large and stable at 8.5 percent of GDP, it did not provide historical data or additional information upon which to base this conclusion. Moreover, IMF staff reported that Ethiopia’s risk of external shocks, such as droughts and high international commodity prices, is high. Ethiopia depends on rain-fed agriculture, which accounts for nearly half of GDP and 85 percent of employment. For the last 30 years, Ethiopia has been hit by droughts every 5 to 7 years, as well as frequent increases in international prices. However, staff told us that country-specific factors, such as weather- related shocks, were not specifically incorporated in the baseline scenario as such.

Tanzania’s 2010 DSA projects higher export and GDP growth. The 2010 DSA projects a 6.5 percent real GDP growth rate in 2011, rising to 7.5 percent in 2015. The growth in real GDP is based on expected returns from the increase in infrastructure investment, including a rise in agricultural productivity and improved food distribution through investment in rural roads and markets, which is to be financed by additional domestic and external borrowing on less concessional terms. Also, Tanzania’s DSA projects an increase in the export-to-GDP ratio from 24.1 percent in the medium term to 28.5 percent in the long-term based on the country’s potential to substantially increase commodity and manufacturing exports.

Following discussions with Tanzanian government officials, in Tanzania’s 2011 DSA the IMF projected a slowdown in real GDP growth for fiscal year 2011/12 (July through June), from the earlier projected rate of 7.1 percent to 6.6 percent. This revision was based on adverse weather, rising fuel prices, and lagging investment. The poor rainfall disrupted electricity generation and lagging investment coupled with higher demand for electricity led to power rationing, which adversely impacted growth. The rising cost of fuel increased the replacement cost of power generation. In addition, the ongoing drought could adversely affect the 2011 food harvest.

If Projections Prove Too Optimistic, Creditors Could Provide More Grants

To the extent that DSA projections prove too optimistic, debt problems may reemerge. This could become evident in the projections in future DSAs, and, if the deviations from the prior projections are significant enough, the country’s debt distress rating could change, meaning the country could receive more grants than loans. IMF and World Bank staff advise that the quality of the DSA hinges critically on the projections and assumptions underlying the baseline scenario, since alternative assumptions can lead to substantially different debt dynamics.

The causes of optimism in the DSAs could be at the global macroeconomic level as well as at the country level. According to the IMF, there are increased risks to global economic recovery, including slower growth and extreme volatility in commodity prices. At the country level, our assessment of three countries’ DSAs illustrates how projections and assumptions can change over a relatively short period of time, potentially affecting a country’s risk of debt distress. For example, Burundi’s present value of debt-to-exports ratio already exceeds the country-specific threshold by a wide margin throughout the projection period. Burundi faces challenges in generating higher government revenue through tax reform and increasing export earnings due to slower than anticipated coffee sector reforms. Lower fiscal revenues or declining GDP growth would lead to a considerable deterioration of its debt ratios, according to its 2010 DSA. This could lead to Burundi being classified as “in debt distress.” However, since Burundi is already to receive only grants from creditors, options to assist the country financially might be limited.

Similarly, if Ethiopia does not achieve the export growth projections in its DSAs, its debt ratios and performance ratings could worsen, and, if significant enough, could lead to a worsening of its debt distress rating. If this occurs, the terms of Ethiopia’s financing from certain lenders could change. Ethiopia now receives its financial assistance as all concessional loans, but a change in risk rating could lead to financing with a larger grant component.

Regarding Tanzania, IMF staff reported in 2011 that revenue collection had fallen short of ambitious targets, and that the rapidly increasing fiscal deficit was being financed by increasingly expensive resources due to a shift from mostly grants to loans. Though Tanzania’s current risk of debt distress is low, maintaining current spending policies could widen the fiscal deficit, leading to rising debt servicing costs, with an adverse impact on the debt indicators. In May 2011, IMF reported that Tanzania faces formidable challenges given widespread poverty, high population growth, and tremendous dependence on foreign aid, and the near-term economic outlook is subject to considerable uncertainty with a rising risk of donor aid shortfalls and higher international fuel prices.

Moreover, the effectiveness of the debt distress rating and associated financing requirements in keeping countries’ debt at sustainable levels depends on their broader use by borrowers and creditors. Some other multilateral institutions—including the African Development Bank, Asian Development Bank, Inter-American Development Bank and International Fund for Agricultural Development—and developed countries use the debt distress rating system to make decisions about their terms of financing. If projections ultimately prove too optimistic and countries’ ability to repay their debt declines significantly, some multilateral institutions could subsequently choose to provide more grants than loans to help lower the risk of debt problems reemerging.

Concluding Observations

The food, fuel, and financial crises resulted in slower economic growth, higher deficits, and increased inflation for LICs. While the overall impact of the crises on LICs may have been milder than in the advanced economies, the high rate of poverty in these countries increases their overall vulnerability. For example, our previous work shows that many LICs were experiencing protracted food emergencies and had severe and widespread malnourishment even prior to the onset of the crises. The IFIs responded to the crises by increasing the amount of resources made available to the LICs. The IMF increased lending to LICs more than sixfold to almost $5 billion. The World Bank committed $18.1 billion through regular lending and five new crises response initiatives that committed $12.2 billion in financial assistance to LICs, including $1.4 billion in new funding. The World Bank provided funding as a mix of loans and grants, depending on the performance and debt vulnerability of each country. The World Bank was able to meet its goal of increasing the speed of disbursement for several initiatives, but the overall picture is mixed, especially when compared to the pre-crises period. Furthermore, in the case of both institutions, the impact of these new resources on LIC government spending during the crises has been difficult to establish. According to the World Bank and IMF, the crises did not significantly impair the countries’ ability to repay their future debt, because they expected the world economy to reestablish its pre-crises growth levels and the LICs to implement reforms necessary to achieve projected future growth levels. However, the increased risk to the global recovery and the extreme volatility of commodity prices may undermine the realization of these expectations. To date, the mix of loans and grants provided by the multilateral development banks have been largely unaffected by the crises. We found that the projections for our case study countries may prove too optimistic, which could contribute to debt problems re-emerging as the amount of loans countries receive could be greater than what would be considered sustainable. However, given that the IFIs update the DSAs on a regular basis, any excessive optimism should become evident over time, and the World Bank and other lenders could then increase the amount of grants they provide which would help mitigate potential debt problems.

Agency Comments and Our Evaluation

The U.S. Treasury, World Bank, and IMF provided written comments on a draft of this report, which are reprinted in appendixes IV, V, and VI, respectively.

The U.S. Treasury commented that the IFIs appropriately responded to the crisis and effectively managed the trade-offs associated with quickly disbursing funds in an environment of limited capacity to absorb aid and that the United States strongly advocated for increased IFI engagement in LICs during the crises. The Treasury letter also stated that we provided a good overview of how the IMF responded forcefully to the crisis. In our discussion on the impact of IMF programs on government spending, they suggested we should have examined the impact of IMF programs on social spending. However, we would emphasize that accounting for the differences between program and non-program countries is critical to estimating the impact of IMF programs on spending during the crisis, which the IMF did not do in their 2010 report. The U.S. Treasury also noted that speed of disbursements is just one measure of effective crisis response and that it is important to consider trade-offs between speed of disbursements and the need to ensure adequate governance structures and fiduciary controls are in place. We included this information in our report. In addition, the Treasury stated that by working closely with the World Bank and other multilateral development banks (MDBs) to put in place the right fiduciary arrangements and strengthen country capacity to absorb and manage MDB assistance, the Treasury can improve the quality of the World Bank’s and other MDBs’ interventions and improve the monitoring and reporting of development results.

The World Bank stated that it welcomes and agrees with our overall conclusion that IFIs, including IDA and IFC, met many goals in response to the crises in LICs. The World Bank also stated that it achieved a significant increase in both its commitments and its disbursements to LICs. We acknowledge that the World Bank responded to crises in LICs by increasing its commitments and disbursements through regular IDA lending and by establishing initiatives. Our analysis focused on the initiatives because these were specifically designed to respond to the crises. Our calculations for the overall commitments and disbursements, as well as the disbursement rates, differed from the World Bank’s because our methodology sought to isolate those activities which were explicitly undertaken in response to the crises. The World Bank said that IDA accelerated assistance delivery without compromising attention to governance and aid effectiveness. We acknowledge that disbursement rates, which vary over time, depend on a number of factors, including recipient country capacity, need, and governance, and the type of lending. The World Bank said there is growing evidence that IDA- supported public spending for essential services increased. As we previously reported, IFIs do not independently track developing countries’ poverty-reducing expenditures and instead rely upon developing countries’ governments to provide such data, even though the accuracy of these data and country capacity to provide this information is questionable. Finally, regarding debt sustainability, the World Bank noted that our analysis is based on a sample of just three countries and thus cannot assess the realism of the 2010 DSA projections. We based our conclusions on our assessment of the realism of the 2010 DSA projections for three countries as well as on the current risks to global economic recovery, reported by the IMF in August 2011.

The IMF indicated broad agreement with the findings of our report, including the overview of the impact of the crisis on LICs. While the IMF suggested that our assessment is narrow, we paid sufficient attention to a range of response efforts, mentioning the IMF’s call for countercyclical policy responses, improved macroeconomic conditions in LICs, doubling of access levels, and modifications to lending instruments. The IMF acknowledged that comparing program with non-program countries does not prove a causal link from program engagement to higher spending and notes a recent related study. We include a reference to the study entitled “What Happens to Social Spending in IMF-Supported Programs” but also note that it does not necessarily reflect the results during the crises response period. The IMF also stated that growth assumptions underlying LIC DSAs have been borne out so far and that DSAs have built-in methods for addressing risks. We described the IMF’s use of alternative scenarios and stress tests to arrive at a country’s debt distress rating. However, we noted that these tests are very general and do not adequately reflect country-specific risks including political instability, adverse weather, global economic crises, and failure to implement reforms or make planned investment. Our analysis of the three countries’ DSAs is intended to be illustrative and not generalizable. Our conclusion, that projections which might be too optimistic could be mitigated by future DSAs and additional grants, is not dependent on these three countries.

As agreed with your offices, unless you publicly announce the contents of this report earlier, we plan no further distribution until 30 days from the report date. At that time, we will send copies to Members of Congress; U.S. Treasury, the IMF, and the World Bank. In addition, the report will be available at no charge on the GAO Web site at http://www.gao.gov.

If you or your staffs have any questions about this report, please contact me at (202) 512-9601 or melitot@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. GAO staff who made major contributions to this report are listed in appendix VII.

Appendix I: Objectives, Scope, and Methodology

Our objectives were to examine (1) the economic impact of the crises on low-income countries (LIC), (2) international financial institutions’ (IFI) responses and reported results, and (3) IFIs’ assessment of the impact of the crises on LICs’ ability to repay their debt.

Economic Impact of Crises To examine the impact of the crises on LICs’ economic performance, we collected and analyzed key macroeconomic data from 1990 through 2010 for 38 of the 40 LICs for which data were available, except as where noted. We analyzed variables including real gross domestic product (GDP), current account, fiscal deficit, government expenditures and revenue, consumer price index measure of inflation, and foreign direct investment. We obtained these data series from the widely used IMF and World Bank databases—World Economic Outlook, International Financial Statistics, and World Development Indicators. We computed LICs’ average economic performance with respect to each of the key economic variables, including current account and fiscal deficits and inflation, using a real GDP weighted average based on purchasing power parity (PPP) GDP, so that the resulting weighted average reflects each country’s size in terms of their share in total GDP of the entire group of LICs. We used the PPP GDP weights to construct weighted averages for the other variables, including fiscal and current account deficits, government revenue and expenditures, and the consumer price index measure of inflation.

We analyzed the LIC group’s macroeconomic performance over the 2007 through 2009 crises period, and compared this to the group’s performance during the pre-crisis period from 2004 through 2006 to determine whether economic performance improved or deteriorated. We also disaggregated the results to determine which countries experienced improvements and deteriorations in each of the key macroeconomic variables. We corroborated our results with data from the economic and financial forecasting firm, IHS Global Insight. We also examined and assessed the DSA’s incorporation of World Economic Outlook assumptions concerning the global pace of recovery, including those of the country’s key trading partners. We also compiled information on international food and oil price data from the UN Food and Agriculture Organization’s Food Price Index and the U.S. Department of Energy. Additionally, we reviewed IMF country reports and World Bank Country Assistance Strategies, which also contain limited historical information on the key macroeconomic variables. Some IMF data is based on developing country government data with greatly varying statistical capacity across countries, and we discussed these limitations with IMF officials. We determined that the data were sufficiently reliable for summarizing countries’ past macroeconomic performance.

Crises Response

To examine IFIs’ responses to the crises and reported results, we analyzed documents and data from the World Bank and the IMF. For the World Bank, these documents include proposals and framework documents for the crisis response initiatives; Country Assistance Strategies and Interim Strategy Notes; Project Information Documents and Implementation Completion Reports; and Independent Evaluation Group reports and approach papers. For the IMF, we reviewed IMF country reports; countries’ letters of intent; research papers; and the Independent Evaluation Office reports. We also reviewed joint World Bank-IMF publications. We interviewed officials from these institutions, as well as from the Department of State and the U.S. Agency for International Development.

To evaluate whether the World Bank’s crisis response was consistent with the institution’s stated goals of increasing the speed of disbursements, we analyzed World Bank data on financial commitments and disbursements made to LICs between 2005 and 2010. To do this, we determined the first year disbursement rate for all projects approved during the crises response period (2008 through 2010); all projects approved during the pre-crises period (2005 through 2007); and all projects approved during the crises response period under each initiative, as well as those approved during the crises response period outside of any initiative. We did not use the World Bank’s standard disbursement rate methodology because our analysis sought to isolate those activities which were explicitly undertaken in response to the crises. For our analysis, this included only projects approved after the World Bank first stated its intention to respond to any of the three crises. This occurred in early 2008, with the establishment of the Global Food Crisis Response Program. We also identified the total number of projects and the amount of funding committed in association with any of the World Bank’s crisis response initiatives.

To measure the speed of disbursements, we first calculated the total disbursements for each project that took place during the first four quarters following project approval. We then determined the average disbursement rate by using a weighted average, which is computed as the ratio between the sum of first year disbursements and the sum of the commitments. One type of project, “additional financing” projects, tracks disbursements under the “parent” project, though commitment amounts are recorded under the “additional financing” project. In our dataset, there were 160 of these projects, out of a total of 622. To ensure that disbursements from “additional financing” projects were captured in our analysis, we developed a methodology that calculated the remaining commitment balance of the “parent” project as of the quarter in which the additional financing project is approved. We then added the balance to the new commitment from the additional financing project to form the denominator of the disbursement ratio. We then calculated the first year disbursement rate by determining the first four quarters of disbursements under the “parent” project following the approval date of the “additional financing” project. We used disbursement data through June 2011, the latest available, to ensure as many projects as possible (97 percent of all projects) had 4 quarters of disbursements. Eighteen projects approved in the fourth quarter of 2010 had only 3 quarters of disbursement data. We used disbursement data through June 2008 for the pre-crisis period to make our analysis comparable. We then compared various disbursement rates to one another to reach our conclusions. We assessed the reliability of the data we used in our analysis by comparing the consistency of the data among the various sources, and discussing the data with World Bank and IMF officials. For the data used to determine World Bank disbursement rates, we interviewed World Bank officials to understand their database and correct errors in the data. We determined that the data used in our analysis were sufficiently reliable for our purposes.

To determine U.S. dollar values associated with the IMF’s response to the crises, we used information on IMF program and funding levels. To calculate the portion of the $250 billion in support that the LICs received, we totaled the amount each country received in Special Drawing Rights, the IMF’s unit of account, and multiplied that by the August 28, 2009 conversion rate to arrive at a U.S. dollar value. To calculate that IMF loans to LICs increased more than sixfold from approximately $748 million between 2005 and 2007 to about $4.9 billion between 2008 and 2010, we used data from the “IMF Lending Arrangements” online tool. For each year, we totaled new lending to LICs in Special Drawing Rights, then converted that total to dollars using the year-end exchange rate. We also assessed the sensitivity of the results of an IMF analysis of government spending in LICs in 2009 using data from the IMF and the Worldwide Governance Indicators. We compared program LICs and non- program LICs using measures of institutional quality from the World Governance Indicators and indicators of macroeconomic policy from the IMF’s World Economic Outlook database. We conducted sensitivity analyses by omitting countries with the lowest scores on certain measures of institutional quality or the least favorable pre-crisis macroeconomic policies from the sample of non-program LICs. We assessed the reliability of data used in our sensitivity analyses and found them to be sufficiently reliable for summarizing and ranking countries’ institutional quality and macroeconomic policy.

Debt Sustainability Analyses

To examine the extent to which IFI’s assessments of LICs’ ability to repay their debt was impacted by the crises, we reviewed the changes in each of the 40 LIC’s Country Policy and Institutional Assessments (CPIA) and debt distress ratings over the period 2007 through 2010 to determine if the crises led to a change in a country’s rating. We used CPIA data from the World Bank’s online database and the debt distress ratings from each of the LIC’s debt sustainability analyses (DSA) over the period.

To illustrate how the DSAs are conducted and how macroeconomic projections affect the reliability of the debt distress rating, we focused on three case study countries: Burundi, Ethiopia, and Tanzania. We selected these countries based on criteria that include the number of IFI projects, amount of IFI financial support, and country conditions. For example, between fiscal years 2008 and 2010, Ethiopia and Tanzania were in the top three recipients of IDA assistance by dollar value, receiving approximately $4.8 billion, while Burundi is a post-conflict fragile state. For each of our three case-study countries, we analyzed the country’s 2010 World Bank-IMF Bank DSAs, as well as the associated IMF program reviews and Article IV consultations, and World Bank Country Assistance Strategies. We also reviewed prior and subsequent DSAs to make comparisons and check for data consistency. In addition, we met with IMF staff responsible for the DSA preparation for preparing each of the case-study countries.

We based our assessment of the DSA’s ability to accurately reflect the country’s debt vulnerabilities on our analysis of the DSA’s macroeconomic projections and the underlying assumptions, which form the basis of the country’s risk of debt distress. These include the DSA’s projections and assumptions regarding key macroeconomic variables, such as real GDP and export growth, and the divergence of the growth rates of these variables from their historic values; assumptions regarding the LIC’s implementation of reforms and productivity-increasing investment; and assumptions concerning the country’s vulnerability to external shocks, including adverse weather, political or regional instability, and rising food and fuel prices.

To determine economic performance over the study period for our three case study countries, and to calculate historical growth rates for key macroeconomic variables, we relied primarily on IMF and World Bank databases—World Economic Outlook, International Financial Statistics, World Development Indicators, and Balance of Payments Statistics. We also utilized data from IMF Article IV consultations and country program reviews. We compared GAO-calculated 10-year historical averages for the most important macroeconomic variables with the DSA’s historical averages for these variables, which form the basis for the DSA’s projections and debt ratios. We evaluated the IFIs’ determination of a country’s risk of debt distress partly based on the extent to which the values of historical key macroeconomic variables diverge from their projected values; and, if so, whether the DSA provides reasonable justification for this divergence. In making this assessment, we also considered additional information available in the Article IVs, World Bank Country Assistance Strategies, and Global Insight Country Intelligence Reports. We also based our assessment of the IFIs’ determination of the country’s risk of debt distress on the DSA’s consideration of country- specific factors, such as the country’s susceptibility to weather-related shocks; political instability; and implementation of institutional reforms that would enhance a country’s growth prospects, particularly in the economic and debt management areas. We discussed our approach and preliminary findings with officials from the IMF. We assessed the reliability of data used in our country analysis based on the consistency of data across various sources and determined them to be sufficiently reliable to make nongeneralizable assessments of the DSAs for the three case study countries.

We conducted this performance audit from September 2010 to September 2011 in accordance with generally accepted government auditing standards. Those standards require that we plan and perform the audit to obtain sufficient, appropriate evidence to provide a reasonable basis for our findings and conclusions based on our audit objectives. We believe that the evidence obtained provides a reasonable basis for our findings and conclusions based on our audit objectives.

Appendix II: Economic, Demographic, and Financial Assistance Data for LICs

Afghanistan

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (15%) assistance (85%)

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (50%) assistance (50%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (52%) assistance (48%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (54%) assistance (46%)

Burma (Myanmar)

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (24%) assistance (76%)

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (68%) assistance (32%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (37%) assistance (63%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (77%) assistance (23%)

Chad

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (42%) assistance (58%)

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (47%) assistance (53%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (54%) assistance (46%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (60%) assistance (40%)

Ethiopia

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (48%)

All bilateral assistance (52%)

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (85%) assistance (15%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (45%) assistance (55%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (37%) assistance (63%)

Guinea-Bissau

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (66%) assistance (34%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (56%) assistance (44%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (32%) assistance (68%)

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (47%) assistance (53%)

Laos

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (38%) assistance (62%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (30%) assistance (70%)

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (59%) assistance (41%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (48%) assistance (52%)

Mali

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (43%)

All bilateral assistance (57%)

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (48%) assistance (52%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (35%) assistance (65%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (43%) assistance (57%)

Niger

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (51%)

All bilateral assistance (49%)

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2009)

All multilateral assistance (19%) assistance (81%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (48%) assistance (52%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (54%) assistance (46%)

Note: Average Annual Official Development Assistance (ODA), for which the main objective is economic development and welfare, was calculated using data from 2008 and 2009 and does not include funding for 2010. ODA excludes certain items such as military aid and antiterrorism activities.

Solomon Islands

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (4%) assistance (96%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2009)

All multilateral assistance (24%) assistance (76%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (60%) assistance (40%)

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (47%) assistance (53%)

Note: Average Annual Official Development Assistance (ODA), for which the main objective is economic development and welfare, was calculated using data from 2008 and 2009 and does not include funding for 2010. ODA excludes certain items such as military aid and antiterrorism activities.

Togo

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (45%) assistance (55%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (41%) assistance (59%)

Assistance (ODA) (Dollars in millions)

Population (nearest million; 2009)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (41%) assistance (59%)

Population (nearest million; 2009)

Assistance (ODA) (Dollars in millions)

Life Expectancy (2008, years)

GNI per capita ($USD; 2008)

All multilateral assistance (15%) assistance (85%)

Appendix III: World Bank Commitments and Disbursements to LICs through Crisis Response Initiatives

Between 2008 and 2010, the World Bank committed $12.2 billion in financial assistance to 38 LICs through five crisis response initiatives, including $10.8 billion from existing International Development Association (IDA) funds, and $1.4 billion from new financial assistance. Figure 14 shows World Bank commitments to 38 LICs between 2008 and 2010.

Within the four crisis response initiatives that sought to increase the speed of disbursements of commitments from existing IDA funds, first year disbursement rates varied by country, as shown in figures 15 through 18.

Appendix IV: Comments from the U.S. Department of the Treasury

GAO Comments

1. We emphasized that accounting for the differences between program and non-program countries is critical to estimating the impact of IMF programs on spending during the crisis, which the IMF did not do in their 2010 report. 2. We acknowledged that the speed of disbursements is one measure, among others, of effective crisis response. We acknowledged the Treasury’s statement that the need to ensure that recipient country capacity and governance controls were sufficiently robust to absorb the additional resources provided during the crisis period played a role in the speed of disbursements.

Appendix V: Comments from the World Bank

GAO Comments

1. We included information about commitments and disbursements in our report, although our figures differ from the Bank’s because we used different methodologies. Our methodology isolated those activities which were explicitly undertaken in response to the crises. 2. We acknowledged that the World Bank responded to crises in LICs through regular IDA lending and by establishing initiatives. Our analysis focused on the initiatives because these were specifically designed to respond to the crises. 3. Our analysis sought to isolate those activities which were explicitly undertaken in response to the crises. We did not assess the World Bank’s standard approach to calculating disbursements. To measure the speed of disbursements, we first calculated the total disbursements for each project that took place during the first four quarters, including the quarter of project approval. We then determined the average disbursement rates for different groups of projects by using a weighted average, which is computed as the ratio between the sum of first year disbursements and the sum of the commitments for all projects that belonged to a group. 4. We acknowledged that disbursement rates, which vary over time, depend on a number of factors, including recipient country capacity, need, and governance, and the type of lending. 5. As we previously reported, IFIs do not independently track developing countries’ poverty-reducing expenditures and instead rely upon developing countries’ governments to provide such data, even though the accuracy of these data and country capacity to provide this information is questionable. We focused on the Fast Track Facility and the infrastructure program because these two initiatives were explicitly designed to support domestic spending in recipient countries during the crises. 6. We based our conclusion that the underlying macroeconomic projections might prove too optimistic on the realism of the 2010 DSA projections for three countries—Burundi, Ethiopia, and Tanzania—as well as on the current risks to the global economic recovery and rising commodity prices, reported by the IMF in August 2011. Our analysis of the three countries’ DSAs is intended to be illustrative and not generalizable. Our conclusion, that projections which might be too optimistic could be mitigated by future DSAs and additional grants, is not dependent on these three countries.

Appendix VI: Comments from the International Monetary Fund

GAO Comments

1. We reported on a wide range of IMF responses, including the IMF’s call for countercyclical policy responses, improved macroeconomic conditions in LICs, doubling of access levels, and modifications to lending instruments. 2. We believe that comparisons of program and non-program country performance can be misleading without appropriate context or analysis. The IMF acknowledged that comparing program with non- program countries does not prove a causal link from program engagement to higher spending and notes a recent related study. The study found that IMF-supported programs were associated with increased spending on education and health as percentage of GDP or a percentage of spending in LICs, based on data from 1985 through 2009. We include a reference to the study, entitled “What Happens to Social Spending in IMF-Supported Programs”—which was released after our audit work had concluded—and we described its conclusions and relevance in a footnote. In particular, the study’s results represent the average effect of an IMF-supported program over the time period, and therefore do not necessarily reflect the results during the crises response period. 3. We discussed the DSAs’ assumption for “quick recovery” in relation to both LICs and the global economy. The IMF forecasted LICs’ recovery in line with the forecast of a quick recovery for the global economy, which was expected to boost demand for LICs’ exports. In August 2011, the IMF reported renewed risks to the global recovery, which means that projections for future export growth could be too optimistic. However, in commenting on this report, IMF noted that the “quick recovery” assumption had been borne out so far. Our report described the IMF’s use of alternative scenarios and stress tests to arrive at a country’s debt distress rating. However, we noted that these tests are very general and do not adequately reflect country- specific risks including political instability, adverse weather, global economic crises, and failure to implement reforms or make planned investment.

Appendix VII: GAO Contact and Staff Acknowledgments

GAO Contact

Staff Acknowledgments

Cheryl Goodman, Assistant Director; Marc Castellano; RG Steinman; Michael Hoffman; Elizabeth Kowalewski; and Arian Terrill made key contributions to this report. The team benefited from the expert advice and assistance of Adam Vogt, Etana Finkler, Bruce Kutnick, Fang He, Shirley Min, Leah DeWolf, Kathryn Buldoc, Martin de Alteriis, Tom McCool, Heneng Yu, Mary Moutsos, Mae Liles, and Holly Dye.