Chapter

CHAPTER 7 Progress Toward External Viability

Author(s):
Susan Schadler, and Hugh Bredenkamp
Published Date:
June 1999
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Author(s)
Tsidi Tsikata

Progress toward external viability is a central objective in ESAF-supported programs. To this end, the programs emphasize macroeconomic policies and structural reforms that are designed to strengthen external sector performance and alleviate the severe external debt-service burdens that many ESAF users face. However, despite increasingly concessional terms on both new and old (rescheduled) loans, and continuing positive net transfers from official sources, the debt burdens of many of these countries remain high and in some cases have grown over the past decade. This chapter will review the evidence on the external performance of ESAF users since the mid–1980s, with a view to:

  • assessing the extent of progress toward external viability;
  • examining why some countries have achieved more than others;
  • investigating the extent to which external positions evolved differently under ESAF-supported programs than was envisaged, and the reasons for such divergences; and
  • identifying policy lessons.

The study updates, for a longer period and larger sample, similar analysis reported in the last ESAF review (Schadler and others, 1993). The present study, which will look at the sample as a whole, is complementary to a study commissioned for the external evaluation of the ESAF (IMF, 1998), which looks at persistent debt and balance of payments problems in more detail for a few selected countries.

The first section discusses conceptual and methodological issues that arise in measuring progress toward external viability, distinguishing between two broad aspects: reducing the burden of external debt and debt service on the economy, and lessening the extent of reliance on exceptional financing to meet balance of payments needs. Vulnerability factors that render countries susceptible to shocks, especially from the terms of trade, are also considered. Identified key indicators are then used, in the next section, to examine progress made by ESAF users over the past ten years, in terms of both trends during the decade to 1995 and progress in each country since the period immediately preceding its first SAF/ESAF-supported program. The third section attempts to answer the question of why some countries progressed further than others. This is done by examining the relative contributions of various components of the balance of payments to the evolution of external debt in each country, by investigating the role of adverse terms of trade movements in determining outcomes, and by looking at policy and growth across countries. A fourth section focuses mainly on countries that did not make clear progress toward external viability, compares outcomes with targets for selected external sector variables under SAF/ESAF programs, and reviews the process of external debt accumulation since each country’s first SAF/ESAF arrangement. Conclusions are presented in the final section, followed by two appendices.

Conceptual and Methodological Issues

External Viability, Sustainable External Position, and Debt Sustainability

A purely market-based definition of external viability would require that current account deficits be financed by spontaneous capital inflows.1 For most of the countries that seek financial assistance under the ESAF, viability in this sense can be regarded only as a distant goal because of their limited access to private capital flows.

The ESAF operational guidelines stipulate that, ideally, programs should aim to establish by the end of a three-year program period an external current account deficit that can be financed by “normal” and “sustainable capital inflows.” Abnormal or exceptional financing for these purposes includes accumulation of arrears, debt rescheduling, debt cancellation, and official (or officially sponsored) borrowing to meet a balance of payments need.2 For programs where exceptional financing is judged to be unavoidable, it is expected that every effort will be made to reduce the amount of such financing steadily and, if possible, to eliminate it by the end of the three-year period.

The guidelines also make provision for cases where existing debt obligations may be so onerous that rescheduling and new financing on conventional terms would not significantly improve the medium-term balance of payments outlook. In such a case, the IMF staff are enjoined to assist the authorities in seeking concessional arrangements from creditors to reduce the debt and debt-service burden.

Since 1995, programs for heavily indebted poor countries (HIPCs) are required to contain a “debt-sustainability analysis.” A country is said to have a sustainable debt burden if it is judged able to meet its current and future external obligations without recourse to debt rescheduling, debt cancellation, or the accumulation of external arrears, and without compromising economic growth (Boote and Thugge, 1997). Unlike the traditional notion of a sustainable external position, this definition of sustainability does not require elimination of balance of payments support in the medium term, but projections would be expected to show a reduced reliance on such support and an eventual exit from ESAF arrangements. Although it is less stringent than the ideal in the ESAF guidelines, movement toward debt sustainability is consistent with progress toward a sustainable external position. Both the ESAF guidelines and the notion of debt sustainability that underlies the HIPC Initiative envisage that countries should approach the same first “milestone”—orderly relations with creditors and graduation from debt relief.

Gauging Progress Toward External Viability

For countries with limited access to private capital markets, progress toward external viability has two main components: lowering the burden of debt and debt service and reducing resort to exceptional financing of current account deficits.3 Two sets of indicators are commonly used to gauge progress on the respective components: ratios of debt and debt service to some resource base (typically, exports, government revenue, or GDP); and accumulation of external arrears, debt relief, and borrowing to meet a balance of payments need. In this chapter, the exceptional financing indicator is defined in terms of ratios to exports. Judgment about what constitutes a sustainable external position also depends on factors such as the economy’s susceptibility to—and ability to withstand—shocks, as well as the capacity of the authorities to formulate and implement adjustment measures in a timely manner when confronted with growing imbalances.

Ratios based on the stock of nominal debt do not capture differences in the degree of concessionality and so may be misleading, especially in cross-country comparisons and in a situation where a country is paying off old debt and contracting new debt on more concessional terms. In recognition of this problem, the World Bank now publishes data on the net present value (NPV) of external debt for reporting countries in the annual Global Development Finance;4 however, the time series begin only in 1991. In this study, therefore, the primary emphasis is on the evolution of debt-service obligations.5 While these obligations reflect both the volume and the average terms of debt outstanding, the drawback, relative to using the present value of the debt stock, is that they measure only the contemporaneous burden and do not take account of higher or lower future repayment obligations.

For the denominator of the ratio, it is useful to distinguish between two aspects of the debt-service burden: effecting the foreign exchange payment, and raising the required domestic resources (that is, the internal transfer problem). The first is represented typically by ratios to exports; exports provide a direct yardstick, especially where foreign exchange constraints are paramount. The second, which is most important for countries where the bulk of external debt is public debt, can be represented by ratios to government revenue or to GDP.

Attractive as the ratio of debt service to government revenue is as a measure of the fiscal burden of debt service, there are difficulties with interpreting it as an indicator of external debt sustainability.6 Where the fiscal system is in disarray, and revenues are abnormally low, the debt service/government-revenue ratio may misidentify as a debt-sustainability problem what is really a fiscal problem. Conversely, the ratio would tend to understate the debt burden when the revenue/ GDP ratio is unsustainably high. To the extent that GDP measures the potential revenue base, debt service/GDP ratios may be less problematic; they can be construed as encompassing debt service/revenue and revenue/ GDP ratios. However, there are also measurement and interpretation problems with using GDP, especially during periods of sharp movements in the real exchange rate.7 For example, the 1994 devaluation of the CFA franc produced a drop in the foreign currency value of GDP in these countries and hence a sharp increase in GDP-based external debt ratios, even for several countries where the debt-to-export ratio fell.8

Clearly, there is no perfect yardstick for measuring progress toward external viability. The assessment in this review will be based on a range of indicators that are consistent with key elements of both the 1993 ESAF review (Schadler and others, 1993) and the framework for debt-sustainability analysis being used for the HIPC Initiative. Specifically, progress will be assessed with reference to changes in the ratios of debt service to exports and to GDP, and reliance on exceptional financing. The assessments will be supplemented by reviews of indicators of the fiscal burden of external debt service as well as indicators of external vulnerability. The evolution of debt/export ratios will also be examined, although in the absence of consistent time series for the NPV of debt, the focus will be on changes in nominal debt over time, rather than on levels relative to some threshold of sustainability.9

What Progress Has Been Made?

This section first reviews broad trends in resource flows, and the external debt and debt-service burdens of ESAF users since the mid–1980s. It then examines how positions of individual countries have evolved since the adoption of SAF/ESAF-supported programs. The analysis does not attempt to delineate developments that are directly and solely attributable to SAF/ESAF-supported programs. Instead, it seeks to gauge how far countries have traveled since they embarked on adjustment efforts supported by SAF/ESAF resources. The last subsection complements the historical review of debt burdens with the results of forward-looking debt-sustainability analyses that have been prepared by the IMF staff for individual countries.

Broad Trends

Resource Flows

Aggregate net resource flows to nontransition ESAF countries increased from $8.2 billion a year during 1981–85 to $14.6 billion a year in 1991–95, with official grants and long-term debt accounting for about 90 percent of these flows (Table 7.1).10 The inflow of portfolio equity was negligible for most countries, and foreign direct investment remained modest. In nominal terms, the average flow of grants more than doubled, whereas net debt flows were stagnant. In proportionate terms, official grants increased from 36 percent to 52 percent of aggregate net resource flows, while the contribution of net debt flows fell from 61 percent to 36 percent. The nontransition Asian countries bucked the overall trend: in these countries the share of official grants and net debt flows each fell slightly, and foreign investment rose to almost a fourth of aggregate net flows during 1991–95.

Table 7.1Amounts and Composition of Aggregate Net Resource Flows1
Average Annual Flows

(in billions of U.S. dollars)
Composition (in percent)
1981–851986–901991–951981–851986–901991–95
Nontransition ESAF users (30 countries)
Aggregate net resource flows8.211.914.6100.0100.0100.0
Official grants2.95.67.636.147.352.2
Net flows on long-term debt4.95.85.360.649.136.0
Net foreign investment20.30.41.73.43.611.7
Foreign direct investment0.30.41.03.43.66.9
CFA Africa (8 countries)
Aggregate net resource flows1.72.12.4100.0100.0100.0
Official grants0.51.11.629.652.667.1
Net flows on long-term debt1.10.90.767.043.131.4
Net foreign investment20.10.13.44.21.5
Foreign direct investment0.10.13.44.21.4
Non-CFA Africa (14 countries)
Aggregate net resource flows2.84.86.0100.0100.0100.0
Official grants1.22.73.741.856.461.4
Net flows on long-term debt1.62.01.856.442.129.5
Net foreign investment20.10.10.51.81.59.0
Foreign direct investment0.10.10.41.81.56.0
Nontransition Asia (4 countries)
Aggregate net resource flows2.73.64.7100.0100.0100.0
Official grants1.11.41.440.138.130.2
Net flows on long-term debt1.52.02.255.455.848.0
Net foreign investment20.10.21.04.56.021.8
Foreign direct investment0.10.20.54.56.010.4
Western Hemisphere (4 countries)
Aggregate net resource flows1.01.41.6100.0100.0100.0
Official grants0.20.51.019.433.059.9
Net flows on long-term debt0.70.90.575.963.732.2
Net foreign investment20.14.73.37.9
Foreign direct investment0.14.73.37.9
Memorandum: Low-income countries
Aggregate net resource flows21.937.867.8100.0100.0100.0
Official grants6.612.516.130.433.023.8
Net flows on long-term debt13.420.920.061.355.329.4
Foreign investment21.84.531.78.411.846.8
Foreign direct investment1.84.326.78.411.539.4
China0.82.922.53.67.533.2
Portfolio equity flows0.15.00.37.3
China2.53.7
Source: Debtor Reporting System (World Bank).

Aggregate net resource flows comprise net flows on long-term debt (disbursements less amortization), official grants, net foreign direct investment, and portfolio equity flows.

The sum of net foreign direct investment and portfolio equity flows.

Source: Debtor Reporting System (World Bank).

Aggregate net resource flows comprise net flows on long-term debt (disbursements less amortization), official grants, net foreign direct investment, and portfolio equity flows.

The sum of net foreign direct investment and portfolio equity flows.

For low-income countries as a whole,11 official grants grew at a slightly slower pace than for non-transition ESAF users (140 percent and 160 percent, respectively, between 1981–85 and 1991–95), whereas net debt flows grew 3t a slightly faster pace. After a nearly tenfold increase between the early 1980s and 1990s, foreign direct investment emerged as the most important component of aggregate net resource flows to low-income countries—accounting for nearly 40 percent in 1991–95. However, the bulk of the increase in foreign direct investment over the period has been to China. Excluding China, growth in foreign direct investment to other low-income countries was only slightly higher than for nontransition ESAF users.

Level and Structure of External Debt Among ESAF Users

The stock of external debt (including private debt not guaranteed by the public sector) nearly doubled between 1985 and 1995 for nontransition ESAF users. This rate of increase was less than for low-income countries in general (170 percent) and about the same as for all developing countries (100 percent).12 The concessional element in external debt, as measured by the average grant element in new borrowing and by the share of concessional borrowing in total debt, increased for ESAF users and has been significantly larger for these countries than for low-income countries as a group (Table 7.2).

Table 7.2Concessional Element in External Debt
ESAF Users1Low-Income CountriesAll Developing Countries
198519951985199519851995
Average grant element in new borrowing (percent)250.061.729.929.615.120.2
Concessional debt as share of total (percent)347.265.939.442.016.621.1
Net present value (percent of face value)72.176.185.6
Memorandum
Total external debt (billions of U.S. dollars)81.6161.0198.3534.81,028.32,065.7
Source: Debtor Reporting System (World Bank); and IMF staff calculations.

Excluding transition economies.

The grant element of a loan is the grant equivalent–that is, commitment value minus the discounted present value of its contractual debt service–expressed in percent of amount committed. This information is reported for new borrowing. It is not available on total debt stock prior to 1991.

The Debtor Reporting System defines concessional debt as loans with original grant element of at least 25 percent.

Source: Debtor Reporting System (World Bank); and IMF staff calculations.

Excluding transition economies.

The grant element of a loan is the grant equivalent–that is, commitment value minus the discounted present value of its contractual debt service–expressed in percent of amount committed. This information is reported for new borrowing. It is not available on total debt stock prior to 1991.

The Debtor Reporting System defines concessional debt as loans with original grant element of at least 25 percent.

Public and publicly guaranteed debt dominates the external debt of nontransition ESAF users, accounting for over 80 percent in 1995. Nearly half of such debt is to bilateral creditors. The share of multilateral debt has increased substantially since 1985, whereas the share held by private creditors has shrunk from 21 percent in 1985 to about 7 percent in 1995. By contrast, for low-income countries as a whole, the share of debt to private creditors remained above 25 percent, and it continues to be large (over 40 percent) for all developing countries (Table 7.3). The reduced share of debt to private creditors among ESAF users probably reflects greater wariness on the part of private lenders following the debt crisis of the early 1980s and the limits on nonconcessional borrowing under ESAF arrangements. There are, however, a number of ESAF users for whom private creditors (mostly commercial banks) still hold significant shares of public and publicly guaranteed debt. In Côte d’Ivoire, Nicaragua, and Zimbabwe, private creditors’ share in public and publicly guaranteed debt fell from over half in the late 1970s and early 1980s but was still about 20 percent in 1994. Private creditors also hold more than 20 percent of public and publicly guaranteed debt in Albania and Mongolia. Key features of private lending to ESAF users are highlighted in Box 7.1.

Table 7.3Distribution of Public and Publicly Guaranteed External Debt by Creditor(In percent)
ESAF Users1Low-Income CountriesAll Developing Countries
198519951985199519851995
Bilateral48.843.644.042.928.839.1
Multilateral (excluding IMF)20.244.117.327.89.016.1
IMF10.15.89.93.35.34.2
Private20.96.528.826.056.940.6
Memorandum
Share of public and publicly guaranteed external debt in total77.182.274.781.971.070.1
Source: Calculated from Debtor Reporting System (World Bank).

Excluding transition economies.

Source: Calculated from Debtor Reporting System (World Bank).

Excluding transition economies.

Debt-Service Burdens

Nominal debt—because it does not reflect the degree of concessionality—overstates the debt burden of most ESAF users. During 1985–95, the ratio of scheduled debt service to exports improved (fell) in over 70 percent of ESAF users, although even in 1995 the ratio exceeded 25 percent—the upper end of the benchmark range in the framework for the HIPC debt initiative—in over half of the countries. Moreover, scheduled debt service relative to GDP improved for significantly fewer countries than did the ratio to exports (Figure 7.1).13 Thus, for many countries, including some where the ratio of debt service to exports improved, overall debt-service burdens remained severe. The median ratio of scheduled debt service to exports trended downwards from 43 percent in 1985 to 28 percent in 1995.14 The ratio of scheduled debt service to GDP presents a more static picture: modest improvements in the late 1980s, especially among HIPCs, were halted in the early 1990s (Figure 7.2; a list of HIPCs and non-HIPCs covered in this review is presented in Box 7.2.).15 These differing trends reflect a doubling in the share of GDP exported by nontransition ESAF users (from 14 percent to 27 percent between 1985 and 1995).

Figure 7.1Scheduled Debt Service

Source: IMF staff estimates.

1Values for Mozambique (1985 = 277.0 and 1995 = 108.2) are not shown because of scale considerations.

2Excludes Guyana.

Figure 7.2Scheduled Debt Service of ESAF Users1

Source: IMF staff estimates.

1Excluding transition economies, Guyana, and Tanzania.

2Heavily indebted poor countries.

Exceptional Financing

There are significant differences in the extent to which various groups of ESAF users relied on exceptional financing (Table 7.4). For the HIPCs, total exceptional financing tended to rise in relation to exports, with debt relief (rescheduling and cancellation) being the dominant form of such financing. Although net accumulation of arrears declined for the HIPCs, this form of financing was still as important as balance of payments support for this group of countries during 1991–95. For the non-HIPCs, arrears accumulated during 1981-85 were reduced in 1986–90, and balance of payments support was the main form of exceptional financing after the mid–1980s. The Asian countries stand out as having made little use of debt relief and accumulation of arrears.

Table 7.4Annual Average Exceptional Financing by ESAF Users1(Annual average; in percent of exports of goods and nonfactor services; group means)
1981–851986–901991–95
HIPCs
Net change in arrears7.710.03.4
Debt relief213.524.436.7
IMF credits and loans2.10.71.6
Other balance of payments support30.81.02.3
Total exceptional financing24.036.144.1
Arrears and debt relief21.134.540.1
Non-HIPCs
Net change in arrears4.7-3.40.0
Debt relief21.31.00.0
IMF credits and loans1.00.40.3
Other balance of payments support31.61.1
Total exceptional financing7.0–0.41.4
Arrears and debt relief6.0-2.40.0
CFA Africa
Net change in arrears0.14.31.1
Debt relief26.416.628.6
IMF credits and loans0.3-0.82.0
Other balance of payments support30.01.01.4
Total exceptional financing6.921.0303.2
Arrears and debt relief6.620.929.8
Non-CFA Africa
Net change in arrears11.32.20.5
Debt relief211.328.124.9
IMF credits and loans2.31.91.2
Other balance of payments support30.01.31.8
Total exceptional financing25.033.528.4
Arrears and debt relief22.730.425.3
Asia
Net change in arrears0.00.00.0
Debt relief20.60.00.0
IMF credits and loans2.50.00.6
Other balance of payments support30.01.81.0
Total exceptional financing3.11.81.6
Arrears and debt relief0.60.00.0
Western Hemisphere
Net change in arrears18.324.115.1
Debt relief220.017.356.0
IMF credits and loans0.60.50.9
Other balance of payments support30.80.44.7
Total exceptional financing39.842.376.8
Arrears and debt relief38.441.471.2
Source: IMF staff estimates.

Excluding transition economies.

Rescheduling and cancellation.

Program and adjustment lending by the World Bank, the African Development Bank, the Asian Development Bank, and the Inter-American Development Bank.

Source: IMF staff estimates.

Excluding transition economies.

Rescheduling and cancellation.

Program and adjustment lending by the World Bank, the African Development Bank, the Asian Development Bank, and the Inter-American Development Bank.

Box 7.1Private Lending to ESAF Users

Significant Source of Financing for a Few Countries

Historically, private creditors (mostly commercial banks) have been an important source of medium-and long-term financing for a few ESAF users. In the mid–1970s, these creditors held more than half of the public external debt of Côte d’Ivoire, Nicaragua, Togo, and Zimbabwe, and between one-third and one-half of the public external debt of Bolivia, Guyana, Senegal, and Sierra Leone.

Sharp Rise in the Late 1970s and Early 1980s

During a short-lived boom in commodity prices in the late 1970s, several countries—for example, Bolivia, Côte d’Ivoire, Kenya, Madagascar, Nicaragua, Niger, Senegal, and Togo—borrowed heavily from commercial banks to sustain expenditure levels that had been boosted during the upturn. Annual disbursements of medium- and long-term loans by private creditors to nontransition ESAF users covered in this review increased from $0.8 billion in 1975 to S3.1 billion in 1980. Disbursements to Côte d’Ivoire, which rose from less than $0.3 billion to nearly $1.2 billion over this period, accounted for a large part of the increase.

Slowdown in New Lending After the Debt Crisis

In the aftermath of the debt crisis in the early 1980s, there was a considerable slowdown in private lending to ESAF users. Annual disbursements fell to under $1 billion in 1985 and have since fluctuated between $0.7 billion and $1.2 billion, with disbursements to Côte d’Ivoire falling to under $0.3 billion in 1983 and to $22 million in 1994. Net transfers (that is, disbursements minus debt-service payments) have been negative since 1983, except for a small positive transfer ($33 million) in 1993.

Restructuring of Commercial Bank Debt

Many of the countries that borrowed heavily from private sources have had difficulty in meeting their debt-service obligations and have sought relief in the form of commercial bank debt- and debt-service-reduction operations. ESAF users that have completed such operations include Albania, Bolivia, Guyana, Mauritania, Mozambique, Nicaragua, Niger, Senegal, Sierra Leone, and Uganda.1 Debt buybacks (usually financed by the World Bank or bilateral donors) have been a popular form of the operation for these countries and have been combined with schemes to reduce debt-service burdens in a couple of cases (Albania and Bolivia). Vietnam and Côte d’Ivoire are at advanced stages in the process of completing similar operations.

1For details, see Dunaway and others (1995) and World Bank (1997).

Debt relief for ESAF users was often obtained in Paris Club debt-restructuring agreements.16 Typically, debt relief is provided in a succession of agreements and linked to performance under IMF-supported programs. To date, 25 ESAF users have restructured official bilateral debt under the umbrella of the Paris Club, mostly on concessional terms.17

Progress During the Adjustment Phase

In this section, the analysis shifts from broad trends, and focuses on the extent to which the countries under review have made progress toward external viability since they embarked on their first SAF/ESAF-supported programs. The approach is to compare developments in the three years prior to the first such program with developments over the most recent three-year period for which data are generally available, 1993–95.

Principal Indicators

Three main indicators are employed to gauge progress toward external viability: the ratios of scheduled debt service to exports,18 scheduled debt service to GDP, and exceptional financing (defined narrowly as arrears and debt relief)19 to exports. Countries that either improved (reduced) all three ratios or maintained them at low levels, are classified as having made “clear progress” toward external viability; countries that regressed on at least two indicators are classified as having made “no progress”; and all others are considered to have made “limited progress” (Table 7.5).20

Table 7.5Principal Indicators of Progress Toward External Viability of ESAF Users1(In percent unless otherwise indicated)
Scheduled Debt-Service Ratios
Exports2GDPExceptional Financing Ratio3
Pre-SAF/ESAF41993–95Percent changePre-SAF/ESAF41993–95Percent changePre-SAF/ESAF41993–95ChangeTime Span (in years)5Program Years6
Clear progress7
Bangladesh30.312.8-57.82.11.3-37.19.06.0
Benin48.630.1-37.96.04.6-22.840.713.0-27.77.05.0
Bolivia80.039.4-50.812.27.6-37.646.414.9-31.69.06.0
Burkina Faso29.021.9-24.63.22.8-13.911.22.3-8.95.03.0
Gambia, The44.925.7-42.87.24.5-37.138.0-0.3-38.210.05.0
Lesotho41.014.9-63.63.52.8-21.48.06.0
Malawi47.527.8-41.413.610.8-20.25.5-2.4-7.98.04.0
Mauritania34.532.7-5.217.515.1-13.813.37.6-5.710.05.0
Nepal6.710.759.90.71.6139.78.04.0
Pakistan35.827.6-22.74.54.50.4-0.47.04.0
Sri Lanka21.312.5-41.15.54.3-21.08.05.0
Uganda67.838.5-43.24.84.2-11.75.20.9-4.39.06.0
Mean40.624.5-30.96.75.4-8.113.43.0-10.48.24.9
Median38.426.7-41.25.24.4-20.65.4-5.08.05.0
Limited progress7
Burundi49.934.3-31.24.94.0-17.62.32.310.04.0
Equatorial Guinea59.635.2-40.918.816.3-13.4-34.128.462.58.02.0
Ghana45.327.1-40.05.06.428.3-14.3-0.713.59.04.0
Guinea32.929.6-10.19.76.2-36.03.614.711.19.04.0
Guyana896.827.7-71.44.58.03.56.04.0
Mali42.037.4-10.87.57.4-0.920.320.70.48.05.0
Mozambique291.7136.4-53.213.333.1149.5278.2197.1-81.09.06.0
Niger44.732.7-26.89.64.9-48.714.923.08.19.03.0
Senegal24.722.9-7.57.26.1-15.611.016.45.59.06.0
Togo44.539.6-11.114.89.0-39.213.334.321.08.04.0
Mean73.242.3-30.310.110.40.729.734.44.78.54.2
Median45.033.5-29.09.66.4-15.67.718.66.89.04.0
No progress7
Honduras37.638.11.511.013.119.213.57.3-6.34.02.0
Kenya25.729.213.75.68.857.11.01.08.03.0
Madagascar79.363.7-19.711.112.714.547.551.33.89.03.0
Sierra Leone51.659.014.35.59.370.421.339.818.59.02.0
Zimbabwe20.724.618.76.39.551.54.02.0
Mean43.042.95.77.910.742.616.519.93.46.82.4
Median37.638.113.76.39.551.513.57.31.08.02.0
Memorandum
Mean (whole sample)53.134.5-23.98.18.14.720.017.8-2.28.04.2
Median (whole sample)44.529.6-26.86.76.3-13.85.57.38.04.0
Source: IMF staff estimates.

Excluding transition economies. Côte d’Ivoire and Nicaragua are excluded because their ESAF programs had been in place for less than three years at end–1995. Tanzania is also excluded because of severe deficiencies in official export data. See Table 7.22 in Appendix 7.1 for results of statistical tests.

Scheduled debt service as a ratio of exports of goods and nonfactor services. For Lesotho, the denominator includes workers remittances because of the dominance of this item in the country’s foreign exchange earnings.

Exceptional financing is defined as the sum of net change in arrears, rescheduling, and debt cancellation (current maturities). The ratio is to exports of goods and nonfactor services.

Annual average for three years preceding first SAF/ESAF program.

Number of years from the first SAF/ESAF program to 1995.

Number of annual arrangements completed since the first SAF/ESAF program.

Countries that made “clear progress” are those that showed improvement in all three indicators or maintained them at low levels. Countries that made “no progress” are those where at least two indicators worsened. All other countries are in the “limited progress” group.

The ratio of debt service to GDP is not computed for Guyana, owing to breaks in the data for nominal GDP.

Source: IMF staff estimates.

Excluding transition economies. Côte d’Ivoire and Nicaragua are excluded because their ESAF programs had been in place for less than three years at end–1995. Tanzania is also excluded because of severe deficiencies in official export data. See Table 7.22 in Appendix 7.1 for results of statistical tests.

Scheduled debt service as a ratio of exports of goods and nonfactor services. For Lesotho, the denominator includes workers remittances because of the dominance of this item in the country’s foreign exchange earnings.

Exceptional financing is defined as the sum of net change in arrears, rescheduling, and debt cancellation (current maturities). The ratio is to exports of goods and nonfactor services.

Annual average for three years preceding first SAF/ESAF program.

Number of years from the first SAF/ESAF program to 1995.

Number of annual arrangements completed since the first SAF/ESAF program.

Countries that made “clear progress” are those that showed improvement in all three indicators or maintained them at low levels. Countries that made “no progress” are those where at least two indicators worsened. All other countries are in the “limited progress” group.

The ratio of debt service to GDP is not computed for Guyana, owing to breaks in the data for nominal GDP.

The requirement that countries in the “clear progress” group show declines in both the scheduled (as opposed to actual) debt-service ratio and in exceptional financing was intended, in part, to minimize the likelihood of including in this group countries whose debt burdens had declined solely, or mainly, on account of debt relief. By definition, debt relief has no effect on scheduled debt service, while heavy reliance on such relief would tend to push up total exceptional financing.21 The stipulation that ratios of debt service to exports and GDP should improve for countries in the “clear progress” group also reduces the risk of including instances where an apparent easing of the debt-service burden is achieved only by diverting a higher share of stagnant or declining GDP to exports (more direct evidence on this point is given in the next section of this chapter).

Box 7.2ESAF Users: HIPCs and Non-HIPCs

For some of the background analysis for this study, the countries under review were classified according to whether they belonged to the group of 41 countries that were identified by the staffs of the World Bank and the IMF in 1995 as heavily indebted poor countries (HIPCs).1 The groupings were as follows:

HIPCsNon-HIPCs
BeninAlbania
BoliviaBangladesh
Burkina FasoCambodia
BurundiGambia, The
Côte d’IvoireKyrgyz Republic
Equatorial GuineaLesotho
GhanaMalawi
GuineaMongolia
GuyanaNepal
HondurasPakistan
KenyaSri Lanka
Lao P.D.R.Zimbabwe
Madagascar
Mali
Mauritania
Mozambique
Nicaragua
Niger
Senegal
Sierra Leone
Tanzania
Togo
Uganda
Vietnam
1HIPCs not covered in this review are Angola, Cameroon, Central African Republic, Chad, Republic of Congo, Democratic Republic of Congo (former Zaïre), Ethiopia, Guinea-Bissau, Liberia, Myanmar, Nigeria, Rwanda, São Tomé and Príncipe, Somalia, Sudan, Yemen, and Zambia.

Country experiences differ for various reasons, including how long and how persistent the adjustment effort has been. A few countries started their ESAF-supported programs relatively recently, and thus the process of external adjustment may be at an early stage. Also, as detailed in Chapter 9, there were frequent gaps and interruptions in ESAF-supported programs in most countries, some of which could be characterized as periods of “nonadjustment.” For reference, these features of country experience are represented (albeit crudely) in the last two columns of Table 7.5.

Excluding two late ESAF users—Côte d’Ivoire and Nicaragua—where programs had been in place for less than three years at end–1995, as well as the transition countries and Tanzania (on data grounds), 12 countries made clear progress since their first SAF/ESAF arrangement, 10 made limited progress, and 5 made no progress.22 In general, the direction of change in the external burden indicator was the same as dial: for the internal burden indicator. However, there were four countries (Ghana, Madagascar, Mozambique, and Sierra Leone) where the ratio of debt service to exports either fell or was broadly stable, but the ratio of debt service to GDP rose; in each, this divergence reflected a sharp increase in the share of exports in GDP.

All except four countries that made clear progress (Bangladesh, Lesotho, Nepal, and Sri Lanka) still had ratios of scheduled debt service to exports above 20 percent by 1993–95; two others (Malawi and Mauritania) continued to have rather high ratios of debt service to GDP (greater than 10 percent:). At the other end of the spectrum, the ratio of debt service to GDP increased for all the countries that made no progress, and all three ratios worsened for two countries in this group (Kenya and Sierra Leone).23 The countries that made limited progress typically increased reliance on exceptional financing but maintained or improved their ratio of debt service to exports and to GDP (Figure 7.3).24 In this group, the very high levels of Mozambique’s debt service and exceptional financing (well over 100 percent of exports) stand out.25

Figure 7.3Principal Indicators of Progress Toward External Viability1

(In percent unless otherwise indicated)

Source: IMF staff estimates.

1Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania. Countries that made “clear progress” are those that showed improvement in all three indicators or maintained them at low levels; countries that made “no progress” are those where at least two indicators worsened; all other countries are in the “limited progress” group.

2Scheduled debt service as a ratio of exports of goods and nonfactor services.

3Scheduled debt service as a ratio of GDP.

4Exceptional financing is defined as the sum of net change in arrears, rescheduling, and debt cancellation. The ratio is to exports of goods and nonfactor services.

5Excluding Mozambique.

The distribution of relatively early and late SAF/ESAF users was fairly even across groups. The average time span since the first SAF/ESAF arrangement ranged from 8.5 years for the countries that made limited progress to 6.8 years for the “no progress” group. One area in which differences between the groups was significant was the relative amount of time spent under completed annual arrangements—60 percent for the “clear progress” group, compared with 49 percent and 35 percent for the “limited progress” and “no progress” groups, respectively.

The 1993 ESAF review concluded that 11 of 19 countries covered either made significant progress toward external viability or maintained relatively favorable positions. The remaining eight countries were judged to have made little progress in relieving external pressures on their economies. Although the present review employs a slightly different methodology and classification scheme, some comparison can be made between its results and those of the 1993 ESAF review (Table 7.6):

  • Eighty-one percent of the countries reported on in this review made some progress toward external viability, compared with 58 percent in the 1993 review (Schadler and others, 1993).
  • More than half of the poorer performers in the 1993 review (specifically, Burundi, Guinea, Mauritania, Niger, and Uganda) are now classified as having made some progress.
  • Two countries covered by the last review—Kenya and Madagascar—remain classified as having made little or no progress toward external viability.26
  • All of the 11 countries that made progress in the 1993 review are once again judged, in this review, to have made some progress.
Table 7.6Comparison with Results of 1993 ESAF Review
1993 ESAF Review1Current Review
Progress
BangladeshBangladesh
BoliviaBenin
Gambia, TheBolivia
GhanaBurkina Faso
GuyanaBurundi
LesothoEquatorial Guinea
MalawiGambia, The
MozambiqueGhana
SenegalGuinea
Sri LankaGuyana
TogoLesotho
Malawi
Mali
Mauritania
Mozambique
Nepal
Niger
Pakistan
Senegal
Sri Lanka
Togo
Uganda
No progress
BurundiHonduras
GuineaKenya
KenyaMadagascar
MadagascarSierra Leone
MauritaniaZimbabwe
Niger
Tanzania
Uganda

Schadler and others (1993). The 1993 review measured progress toward external viability by the evolution of ratios of debt and debt-service to exports, and by the extent of reliance on exceptional financing. Countries that made progress were those in which the indicators declined or remained stable at relatively favorable starting positions over the course of their SAF/ESAF-supported programs.

Schadler and others (1993). The 1993 review measured progress toward external viability by the evolution of ratios of debt and debt-service to exports, and by the extent of reliance on exceptional financing. Countries that made progress were those in which the indicators declined or remained stable at relatively favorable starting positions over the course of their SAF/ESAF-supported programs.

Fiscal Burden of Debt Service

The ratio of scheduled debt service to government revenue declined for most of the countries that made some measure of progress toward external viability and rose for nearly all the countries in the “no progress” group (Table 7.7). The ratio in the most recent three-year period remained very high (over 50 percent) for more than 40 percent of the sample covered in Table 7.7, including for two of the countries that made clear progress (Malawi and Mauritania).27 However, in several of these cases with high ratios of debt service to government revenue—Guinea, Madagascar, Niger, Sierra Leone, and Togo—government revenue relative to GDP of 7–13 percent suggests a weak government revenue effort.

Table 7.7External Debt Service: Fiscal Burden Ratios1(In percent)
Debt Service/GDPDebt Service/Government Revenue2Government Revenue/GDP2
Pre-SAF/ESAF31993–95ChangePre-SAF/ESAF31993–95ChangePre-SAF/ESAF31993–95Change
Clear progress4
Bangladesh2.11.3-0.823.911.7-12.28.711.22.5
Benin6.04.6-1.446.335.2-11.112.913.30.3
Bolivia12.27.6-4.6132.330.6-101.711.224.913.7
Burkina Faso3.22.8-0.454.223.7-30.511.311.80.5
Gambia, The7.24.5-2.750.922.9-28.019.721.01.3
Lesotho3.52.8-0.816.78.9-7.821.131.09.8
Malawi13.610.8-2.764.262.2-2.021.217.4-3.8
Mauritania17.515.1-2.480.261.6-18.621.724.32.6
Nepal0.71.60.97.315.68.39.110.31.2
Pakistan4.54.50.024.726.41.618.317.2-1.1
Sri Lanka5.54.3-1.225.621.5-4.121.520.2-1.3
Uganda4.84.2-0.663.442.5-20.98.010.52.5
Mean6.75.4-1.449.130.2-18.915.417.82.3
Median5.24.4-1.048.625.0-11.715.617.31.3
Limited progress4
Burundi4.94.0-0.936.622.5-14.013.317.84.5
Equatorial Guinea18.816.3-2.594.494.50.120.317.5-2.8
Ghana5.06.41.446.830.8-16.012.521.38.8
Guinea9.76.2-3.573.856.9-17.013.111.0-2.1
Guyana204.384.6-119.7
Mali7.57.4-0.130.153.623.516.013.9-2.1
Mozambique13.333.119.885.7178.092.415.718.62.9
Niger9.64.9-4.785.771.7-14.011.27.0-4.2
Senegal7.26.1-1.138.740.72.018.615.1-3.5
Togo14.89.0-5.853.770.116.427.513.1-14.4
Mean10.110.40.375.070.3-4.616.515.0-1.4
Mean (excluding Guyana)10.110.40.360.668.88.216.515.0-1.4
Median9.66.4-1.163.863.5-6.915.715.1-2.1
No progress4
Honduras11.013.12.169.877.77.915.516.91.4
Kenya5.68.83.224.831.26.422.728.45.7
Madagascar11.112.71.679.0143.264.214.08.9-5.0
Sierra Leone5.59.33.992.282.2-10.06.311.65.3
Zimbabwe6.39.53.217.932.614.734.629.1-5.5
Mean7.910.72.856.873.416.618.619.00.4
Median6.39.53.269.877.77.915.516.91.4
Memorandum
Mean (whole sample)8.18.10.060.153.1-7.016.417.00.7
Source: IMF staff estimates.

Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania. See Table 7.22 in Appendix 7.1 for results of statistical tests.

Government revenue excluding grants.

Annual average for three years preceding first SAF/ESAF program.

See footnote 7 in Table 7.5 for description of categories.

Source: IMF staff estimates.

Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania. See Table 7.22 in Appendix 7.1 for results of statistical tests.

Government revenue excluding grants.

Annual average for three years preceding first SAF/ESAF program.

See footnote 7 in Table 7.5 for description of categories.

Progress on Vulnerability Indicators

The vulnerability of the external positions of ESAF users is judged by indicators of export concentration, holdings of international reserves, and variability in export earnings (Table 7.8).28 As would be expected, on average, the group with more concentrated exports held more reserves and also increased the level of reserves as export concentration rose. Also as expected, countries in the group with more diversified export bases generally had more stable export earnings.

Table 7.8ESAF Users: Vulnerability Indicators1
Export Variability
Percent Share of Three Top Exports in TotalReserves in Months of Imports2Coefficient of variation3Around linear trend4
UserMain Export(s)1985199519851995Change1981–851991–95Change1985–95
Decreasing or moderate and stable export concentration5
BangladeshJute goods/ready-made garments65.765.52.05.33.310.225.515.312.9
Bolivia6Gas/soya products94.7*34.06.25.6-0.712.418.25.812.5
Côte d’IvoireCocoa75.553.60.00.50.58.915.56.611.3
Equatorial
GuineaCocoa/petroleum70.5*50.50.40.1-0.327.917.6
Gambia, The6Groundnut and products88.6*61.5*0.35.95.528.719.8-8.921.9
Guinea7Bauxite83.3*69.70.62.41.95.39.13.812.7
GuyanaBauxite/sugar84.059.70.26.46.121.219.5-1.717.1
HondurasCoffee/bananas62.748.80.91.70.87.316.69.39.4
KenyaCoffee/tea67.237.73.52.4-1.010.214.54.38.3
MadagascarCoffee57.946.92.21.8-0.45.419.914.510.4
MozambiquePrawns65.563.92.16.64.544.413.3-31.08.6
NicaraguaCoffee66.749.16.92.4-4.517.232.114.922.4
Pakistan6Cotton products72.0*41.21.32.71.48.121.313.211.4
TanzaniaCoffee55.949.60.32.62.325.532.56.919.8
ZimbabweTobacco41.246.02.13.31.212.915.93.09.3
Mean70.151.81.93.31.415.620.14.013.7
Increasing or very high export concentration5
BeninCrude oil/cotton products75.5*85.8**0.14.03.945.215.9-29.214.7
Burkina FasoCotton39.181.93.77.63.99.911.71.817.5
BurundiCoffee88.7**90.1**1.712.310.612.919.86.917.6
GhanaCocoa/gold83.9*85.82.44.21.939.916.1-23.88.0
LesothoLabor93.4**77.3**2.04.12.244.329.3-15.017.2
MalawiTobacco75.375.7*2.40.8-1.612.615.73.117.6
MaliCotton72.390.5*0.76.45.76.212.86.610.5
MauritaniaFish99.4*96.7*2.81.5-1.39.711.11.58.5
NepalReady-made garments/ carpets53.570.63.96.02.111.46.9-4.59.8
NigerUranium96.8**79.8*3.111.18.023.016.6-6.417.7
SenegalFish44.552.80.10.20.216.79.2-7.513.8
Sierra Leone6Rutile62.686.30.93.62.710.425.515.218.0
Sri LankaTea/garments & textiles58.067.63.24.71.513.022.29.212.4
TogoPhosphate rock/cotton58.676.18.33.6-4.712.923.210.318.2
Uganda6Coffee98.2**75.5*2.44.01.616.956.739.843.5
Mean73.379.52.54.92.419.019.50.516.3
Source: IMF staff estimates.

Main export accounts for over 50 percent of total; ** main export accounts for over 75 percent of total.

Excluding transition economies.

The reserves reported for individual CFA African countries (Benin, Burkina Faso, Côte d’Ivoire, Equatorial Guinea, Mali, Niger, Senegal, and Togo) are not as meaningful as for the other countries because of the pooling arrangements in the CFA franc zone.

The ratio of the standard deviation to the mean of exports of goods and nonfactor services over the period (in percent).

The standard error of a linear trend regression (with a constant term), in percent of average exports of goods and nonfactor services during 1985–95.

Countries where the 1995 share of the top three exports in the total was more than 10 percent higher than the 1985 ratio, or where the top three exports accounted for over 75 percent of total exports in 1995, are classified as “increasing or very high export concentration.” The others are grouped under “decreasing or moderate and stable export concentration.”

Export data for 1994-the latest for which a reliable commodity breakdown is available-were used to calculate the share of the three top exports in total shown under the 1995 column.

1986 export data and 1987 reserves data used for 1985.

Source: IMF staff estimates.

Main export accounts for over 50 percent of total; ** main export accounts for over 75 percent of total.

Excluding transition economies.

The reserves reported for individual CFA African countries (Benin, Burkina Faso, Côte d’Ivoire, Equatorial Guinea, Mali, Niger, Senegal, and Togo) are not as meaningful as for the other countries because of the pooling arrangements in the CFA franc zone.

The ratio of the standard deviation to the mean of exports of goods and nonfactor services over the period (in percent).

The standard error of a linear trend regression (with a constant term), in percent of average exports of goods and nonfactor services during 1985–95.

Countries where the 1995 share of the top three exports in the total was more than 10 percent higher than the 1985 ratio, or where the top three exports accounted for over 75 percent of total exports in 1995, are classified as “increasing or very high export concentration.” The others are grouped under “decreasing or moderate and stable export concentration.”

Export data for 1994-the latest for which a reliable commodity breakdown is available-were used to calculate the share of the three top exports in total shown under the 1995 column.

1986 export data and 1987 reserves data used for 1985.

Overall, there appears to have been some reduction in vulnerability. Nearly half of the countries considered reduced their levels of export concentration, and about two-thirds increased their holdings of international reserves (Table 7.9). There was no clear pattern, however, among countries grouped according to the degree of progress toward external viability.

Table 7.9ESAF Users: Progress on Vulnerability Indicators1
Export ConcentrationReserve Coverage
FellUnchangedRoseRoseUnchangedFell
Clear progress
Bangladesh
Benin
Bolivia
Burkina Faso
Gambia, The
Lesotho
Malawi
Mauritania
Nepal
Pakistan
Sri Lanka
Uganda
Proportion (percent)242253375817
Limited progress
Burundi
Equatorial Guinea
Ghana
Guinea
Guyana
Mali
Mozambique
Niger
Senegal
Togo
Proportion (percent)2403030702010
No progress
Honduras
Kenya
Madagascar
Sierra Leone
Zimbabwe
Proportion (percent)2602020602020
Whole sample proportion
(percent)442630701515
Source: IMF staff estimates.

Based on data in Table 7.8.

Refers to the proportion of countries within each group for which the specified indicator moved as marked.

Source: IMF staff estimates.

Based on data in Table 7.8.

Refers to the proportion of countries within each group for which the specified indicator moved as marked.

Debt Sustainability

Discussion of the extent to which countries have made progress toward external viability thus far has relied on historical trends. The focus in the debt-sustainability analysis used for the HIPC Initiative is, instead, on the future time path of key indebtedness indicators, derived from country-specific macroeconomic scenarios. These scenarios, geared toward assessing the sustainability of countries’ debt, depend on assumptions about commodity prices, net resource flows (including debt relief), and macroeconomic policies. Two key thresholds of sustainability have been established to serve as benchmarks for the analyses: a range of 200–250 percent for the NPV debt-to-export ratio; and 20–25 percent for the debt-service-to-export ratio.29 The levels judged to be sustainable for a particular country take account of the fiscal burden of debt service and other vulnerability factors, including susceptibility to trade shocks, official reserve positions, and the extent of reliance on foreign transfers.

A summary of the main debt and debt-service indicators from debt-sustainability analyses that have been prepared by IMF staff for 25 ESAF users is presented in Table 7.10. Seventeen out of the 25 countries are projected to maintain or attain ratios below the threshold levels by 2000. However, five of these countries would continue to have rather high ratios of debt service to government revenue (above 25 percent) in 2000.

Table 7.10HIPC ESAF Users: Indicators of Debt Sustainability1
Ratios (percent)
Net present value debt/exportDebt service/exportDebt service/ government revenue
199520001995200019952000
Clear progress
Benin2211329.710.715.619.1
Bolivia22317227.621.813.6
Burkina Faso21515211.612.717.913.6
Malawi26515922.121.736.426.9
Mauritania24318718.419.313.2
Uganda27123427.519.328.614.6
Limited progress
Burundi46643242.036.127.730.1
Equatorial Guinea2072427.82.693.78.9
Ghana21912940.015.440.621.7
Guinea18419.911.919.0
Guyana16627.413.077.541.1
Mali14512814.214.222.021.0
Mozambique98949127.241.841.246.4
Niger34623336.117.475.922.0
Senegal14110211.514.824.127.1
Togo2121069.610.620.5
No progress
Honduras19611633.714.466.434.7
Kenya1489724.815.827.916.7
Madagascar48525854.217.9151.632.0
Sierra Leone49917084.319.233.2
Others
Côte d’Ivoire34015423.113.945.826.5
Lao, P.D.R.184975.210.89.37.0
Nicaragua1,358332140.443.053.934.9
Tanzania52519543.517.279.025.9
Vietnam824612.25.618.812.2
Source: IMF staff estimates.

Excluding transition economies. For Burundi, based on preliminary data.

Source: IMF staff estimates.

Excluding transition economies. For Burundi, based on preliminary data.

Of the 22 countries classified in Table 7.5 as having made some progress toward external viability, several (Bolivia, Burundi, Malawi, Mozambique, Niger, and Uganda) are projected to have at least one debt-burden indicator that remains above the low end of the sustainable threshold range. In contrast, one country (Kenya) classified in the present study as having made no progress toward external viability nonetheless is projected to have its indicators well below the sustainable threshold.30

Why Have Some Countries Progressed Further Than Others?

By identity, there are only a few direct influences on the evolution of debt-service ratios (see Appendix 7.2): (1) changes in average payment terms owing to changes in market interest rates or, even more important for low-income countries, changes in the degree of concessional icy on new borrowing;31 (2) the rate of accumulation of debt, which in turn is influenced by the current account deficit, non-debt-creating inflows, and changes in official reserves; (3) debt write-offs;32 and (4) the growth of exports or GDP, whichever is the denominator. Of course, each of these direct influences is itself affected by policies and exogenous factors. This section examines the evolution of these influences and tries to assess the degree to which each accounted for differences in the evolution of debt-service ratios.

Degree of Concessionality in External Borrowing

On average, at end–1995 the countries that had made clear progress toward external viability- had a higher concessional element in their total debt stock than the countries that had made no progress (Table 7.11, page 142).33 However, there was no statistically significant difference between groups in the average level of the grant element received over the entire period since the first SAF/ESAF arrangement. Thus, access to concessional borrowing does not appear to be an important factor that distinguishes the countries that made clear progress from the rest.

Table 7.11ESAF Users: Average Grant Element in New Borrowing and Net Present Value of Debt1(In percent)
Average Grant Element in New BorrowingRatio of NPV to Nominal Value of Debt, 1995
Pre-SAF/ESAF21993–953t to 19954
Clear progress
Bangladesh70.171.672.655.9
Benin60.776.073.755.9
Bolivia34.651.247.474.0
Burkina Faso60.176.277.151.0
Gambia, The45.482.074.350.2
Lesotho51.840.339.458.4
Malawi64.977.175.347.6
Mauritania48.666.761.768.3
Nepal71.369.673.249.2
Pakistan36.240.937.777.6
Sri Lanka57.659.960.967.7
Uganda42.875.264.952.4
Mean53.765.663.259.0
Mean (excluding Lesotho)53.867.965.459.1
Standard deviation (excluding Lesotho)13.012.512.710.8
Limited progress
Burundi57.273.674.045.2
Equatorial Guinea71.278.666.474.1
Ghana52.052.057.464.3
Guinea49.058.560.164.9
Guyana22.868.268.075.2
Mali64.476.373.358.9
Mozambique34.475.969.776.6
Niger50.969.766.562.2
Senegal40.772.464.165.3
Togo70.2
Mean51.369.566.665.2
Standard deviation15.58.85.59.7
No progress
Honduras31.244.443.781.2
Kenya32.054.752.874.1
Madagascar49.677.070.474.1
Sierra Leone77.872.070.562.6
Zimbabwe20.230.633.182.2
Mean42.255.754.174.8
Standard deviation22.519.216.57.8
Source: Debtor Reporting System (World Bank).

See Table 7.22 in Appendix 7.1 for results of statistical tests.

Annual average for the three years preceding the first SAF/ESAF arrangement.

Annual average between 1993 and 1995.

Annual average since the first annual SAF/ESAF program.

Source: Debtor Reporting System (World Bank).

See Table 7.22 in Appendix 7.1 for results of statistical tests.

Annual average for the three years preceding the first SAF/ESAF arrangement.

Annual average between 1993 and 1995.

Annual average since the first annual SAF/ESAF program.

The Flows Underlying Changes in Debt-to-Export Ratios

The average debt-to-export ratio fell for the groups that made “clear” and “limited” progress toward external viability and increased for the “no progress” group (Table 7.12, page 143).34 In contrast to a common concern that IMF-supported programs address excessive debt burdens by squeezing imports and shifting resources to export production, countries that made the most progress toward external viability had noninterest current account deficits similar in size to those that made limited progress and significantly larger than those that made no progress.35 Moreover, the countries that made “clear” progress also built reserves more strongly than the other groups. Export growth was significantly higher in the groups that made some progress toward external viability than in the “no progress” group. However, its direct effect on debt accumulation in the former groups was partly offset by higher imports.

Table 7.12Summary Analysis of Change in Ratio of External Debt to Exports1,2
Influences on External Debt

(annual averages; in percent of beginning-period debt stock)
External Debt to Export Ratio

(in percent)
Current account deficit excluding interest
Prior to first SAF/ESAF21995Percent change3Interest paymentsOfficial transfersIncrease in gross reservesForeign direct investmentOther4Export growth (percent)5Time span (years)6
Clear progress7
Mean405.2357.8-1.430.13.9-16.34.6-1.3-11.710.78.5
Mean (excluding Lesotho)418.6373.5-1.118.13.8-9.72.7-0.9-5.39.98.5
Median340.1383.6-3.214.84.2-9.13.5-0.4-4.411.78.0
Limited progress
Mean572.7520.4-0.416.13.7-12.61.5-1.5-1.36.28.5
Median354.2419.7-1.115.43.9-13.21.8-0.4-0.87.49.0
No progress
Mean368.2418.2-0.36.95.6-4.51.0-0.5-3.75.16.8
Median338.8278.2-2.95.04.8-4.50.7-0.4-3.07.28.0
Source: IMF staff estimates.

Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania. See footnote 1 in Table 7.5; also see Table 7.22 in Appendix 7.1 for results of statistical tests and Table 7.25 in Appendix 7.2 for country-specific data.

Year preceding the first annual SAF/ESAF arrangement.

Annual average calculated as geometric mean. The reported mean for each group is calculated as the average of percent changes for countries in the group.

Includes mainly debt cancellation, portfolio capital flows, errors and omissions, and valuation changes (see Appendix 7.2).

Exports of goods and nonfactor services. Annual average calculated as geometric mean.

Number of years from first SAF/ESAF arrangement to most recent year for which complete data (for all relevant variables) were available.

Burkina Faso is excluded because of gaps in its debt-stock data for the late 1980s.

Source: IMF staff estimates.

Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania. See footnote 1 in Table 7.5; also see Table 7.22 in Appendix 7.1 for results of statistical tests and Table 7.25 in Appendix 7.2 for country-specific data.

Year preceding the first annual SAF/ESAF arrangement.

Annual average calculated as geometric mean. The reported mean for each group is calculated as the average of percent changes for countries in the group.

Includes mainly debt cancellation, portfolio capital flows, errors and omissions, and valuation changes (see Appendix 7.2).

Exports of goods and nonfactor services. Annual average calculated as geometric mean.

Number of years from first SAF/ESAF arrangement to most recent year for which complete data (for all relevant variables) were available.

Burkina Faso is excluded because of gaps in its debt-stock data for the late 1980s.

Another area of substantial difference between the groups that made some progress and the group that did not was in the size of official transfers (grants). Relative to initial debt stocks, grants were on average more than twice as large in the former group. One possible explanation is that, because the group that made no progress spent significantly less time under completed IMF-supported programs, donors that linked disbursements to program performance may have disbursed fewer grants to the “no progress” group.

Flows of direct foreign investment were relatively small and similar across groups. Several authors have noted that the surge in private capital flows to developing countries in recent years has bypassed most low-income countries, especially those in sub-Saharan Africa (Box 7.3).

Shocks, Policies, and Growth

What were the relative roles of favorable terms of trade, and adjustment policies, in determining progress toward external viability? Did progress depend on countries compressing imports or sacrificing growth through financial austerity programs? These questions have an important bearing not only on the determinants of relative progress toward viability but also on the durability of such progress.

The terms of trade deteriorated for most ESAF users in the period since their first SAF/ESAF-supported program. On average, the deterioration was somewhat more severe for the countries that made “limited” progress toward external viability than for those that made “clear” or “no” progress (Table 7.13). This evidence is consistent with the notion that adverse terms of trade movements may have hampered some countries’ efforts to improve their external positions—and, in particular, may help to explain why some made “limited” rather than “clear” progress. But terms of trade developments do not appear to be the factor that delineates the “clear” from the “no” progress group.

Table 7.13Summary Terms of Trade and Real Effective Exchange Rate Indices1
Terms of Trade

(1985= 100)
Real Effective Exchange Rate Indices2

(1985= 100)
Pre-SAF/ ESAF31993–95Percent changePre-SAF/ESAF31993–95Percent change
Clear progress
Mean104.996.5-8.092.366.6-27.8
Median103.693.7-5.694.670.7-26.3
Limited progress
Mean100.978.3-22.489.442.3-52.7
Median98.981.9-23.398.448.8-51.2
No progress
Mean103.689.8-13.490.756.3-38.0
Median102.592.0-10.092.253.9-39.2
Sources: IMF, World Economic Outlook and Information Notice System databases.

Excluding transition economics, Côte d’Ivoire, Nicaragua, and Tanzania. See footnote 1 in Table 7.5; see also Table 7.22 in Appendix 7.1 for results of statistical tests and Table 7.26 in Appendix 7.2 for country-specific data.

Increases signify real appreciation, decreases real depreciation.

Annual average for three years preceding first SAF/ESAF arrangement.

Sources: IMF, World Economic Outlook and Information Notice System databases.

Excluding transition economics, Côte d’Ivoire, Nicaragua, and Tanzania. See footnote 1 in Table 7.5; see also Table 7.22 in Appendix 7.1 for results of statistical tests and Table 7.26 in Appendix 7.2 for country-specific data.

Increases signify real appreciation, decreases real depreciation.

Annual average for three years preceding first SAF/ESAF arrangement.

Exchange rate policy and liberalization of the exchange and trade systems are especially relevant for progress toward external viability, insofar as they directly enhance the competitiveness of the export sector. The real effective exchange rate, on average, has tended to depreciate for most ESAF users since their first SAF/ESAF-supported programs. The depreciation was slightly higher for the countries that made limited progress toward external viability than for the “clear” and “no progress” groups.36

Box 7.3Macroeconomic Determinants of Private Capital Flows

In the 1990s, private capital flows have emerged as a major source of financing for a growing number of developing countries in Asia and Latin America. However, this phenomenon has largely bypassed most of sub-Saharan Africa. The private capital flows that do go to sub-Saharan Africa are mainly in the form of loans and foreign direct investment; portfolio equity flows are minuscule. A recent study, (Bhattacharya, Montiel, and Sharma, 1997) notes that, unlike Latin America which also saw a sharp drop in private loans in the aftermath of the debt crisis, sub-Saharan African countries have not been able to reestablish their credit-worthiness. Most countries in sub-Saharan Africa receive only modest amounts of foreign direct investment, in spite of rates of return on foreign direct investment estimated to have been higher than in other regions.1 This suggests that perceived risks and impediments to foreign investment may be higher in Africa than elsewhere.

The study’s findings on the macroeconomic determinants of private capital flows can be summarized as follows.2

  • Foreign direct investment has been attracted to growing open economies with relatively stable real effective exchange rates. A rapidly or steadily growing economy is likely to offer higher rates of return than one that is not growing, and a highly variable real effective exchange rate (typically the result of high and variable inflation) is likely to adversely affect the traded-goods sector and make returns to foreign investors more uncertain.
  • Private loans tend to go to countries with low levels of external debt in relation to GDP, and higher rates of investment (interpreted as signaling appropriate utilization of resources in previous years).
  • Movements in international interest rates were not found to be important for the flow of foreign direct investment and private loans. However, the authors expect that, as countries become creditworthy and begin to attract larger volumes of equity capital, movements in international interest rates may begin to exert greater influence.
1The authors estimate that rates of return on foreign direct investment averaged 24–30 percent in Africa during 1990–94, compared with 16–18 percent for all developing countries.2Based on a set of regressions using panel data for 31 sub-Saharan African countries (including 21 countries covered by this ESAF review) over the period 1980–95. Domestic factors considered were the growth rate, rate of investment, level of consumption (or saving), openness of the economy, ratio of external debt to GDP, and fluctuations in the real effective exchange rate. The key external factor considered was international interest rates (as a proxy for the opportunity cost of investing funds in developing countries).

Chapter 4 of this review examined progress in structural reforms—including in the areas of exchange and trade systems—by employing indices designed to capture how close countries have moved toward “best practices.” All ESAF countries had made progress in exchange and trade reform by 1991–95 compared with 1981–85, although, on average, the countries that made some progress toward external viability scored higher than the “no progress” group in the 1980s (Table 7.14). During 1991–95, however, differences in average scores among countries grouped by degree of progress were not statistically significant.

Table 7.14Indicators of External Sector Reform1
Exchange System Scores2Trade System Scores3
1981–851986–901991–951981–851986–901991–95
Clear progress
Mean4.25.05.53.13.64.8
Median5.05.06.03.04.05.0
Limited progress
Mean4.24.95.73.04.15.1
Median5.05.06.03.04.05.0
No progress
Mean3.33.55.32.33.54.5
Median3.53.55.02.04.04.5
Memorandum
Mean (whole sample)4.04.65.52.93.74.9
Median (whole sample)4.05.06.03.04.05.0
Source: Chapter 4.

The extent of reform is classified as low (score of 1–2), moderate (3–4), or high (5–6) relative to a specified notion of “best practices” (score of 5–6). See Table 7.27 in Appendix 7.2 for country-specific data.

Based on the level of parallel market exchange rate premiums and on the extent of surrender requirements and nonmarket foreign exchange allocation.

Based on the extent of quantitative restrictions, levels and dispersion of tariffs, and the extent of import exemptions.

Source: Chapter 4.

The extent of reform is classified as low (score of 1–2), moderate (3–4), or high (5–6) relative to a specified notion of “best practices” (score of 5–6). See Table 7.27 in Appendix 7.2 for country-specific data.

Based on the level of parallel market exchange rate premiums and on the extent of surrender requirements and nonmarket foreign exchange allocation.

Based on the extent of quantitative restrictions, levels and dispersion of tariffs, and the extent of import exemptions.

By contrast, one area of policy where significant differences emerged among groups was fiscal adjustment. There was significant reduction in the primary fiscal deficit in the “clear progress” group, and a tendency toward larger fiscal imbalances in the “limited progress” group (Table 7.15).37 Fiscal balances improved in 9 of the 12 countries that made “clear” progress, whereas of the 10 countries in which the fiscal balance deteriorated, only 3 made “clear” progress toward external viability (Figure 7.4).38 However, even for the “clear progress” group there was no tendency for the current account deficit to decline as a share of GDP. For the sample as a whole, changes in the fiscal balance tended to be offset, at least partially, by an opposite change in the nongovernment sector’s saving-investment balance. This suggests that the beneficial effects on external viability from cutting public sector deficits might operate indirectly by “crowding in” private sector activities and stimulating exports and growth in the group of countries that made the most progress toward external viability.

Table 7.15Sectoral Financial Balances

(In percent of GDP)1

Primary Fiscal Balance2Nongovernment Sector Balance3Noninterest Current Account4
Pre-SAF/ESAF51993–95ChangePre-SAF/ESAF51993–95ChangePre-SAF/ESAF51993–95Change
Clear progress
Mean-8.3-3.44.90.7-7.4-8.1-7.5-10.7-3.2
Median-7.6-3.33.61.2-3.3-4.2-6.4-7.8-1.7
Limited progress
Mean-6.6-7.2-0.6-5.1-5.3-0.2-11.6-12.5-0.9
Median-5.6-7.7-1.1-2.0-3.60.6-12.2-8.0-0.4
No progress
Mean-4.0-2.11.90.4-2.3-2.8-3.5-4.5-0.9
Median-2.8-2.70.9-0.3-1.9-1.6-3.5-5.1-1.6
Source: IMF staff estimates.

See Table 7.22 in Appendix 7.1 for results of statistical tests and Table 7.28 in Appendix 7.2 for country-specific data.

Excluding grants.

Calculated as current account balance minus fiscal balance.

Noninterest current account balance excluding official transfers.

Annual average for three years preceding first SAF/ESAF program.

Source: IMF staff estimates.

See Table 7.22 in Appendix 7.1 for results of statistical tests and Table 7.28 in Appendix 7.2 for country-specific data.

Excluding grants.

Calculated as current account balance minus fiscal balance.

Noninterest current account balance excluding official transfers.

Annual average for three years preceding first SAF/ESAF program.

Figure 7.4Sectoral Financial Balances1

(In percent of GDP)

Source: IMF staff estimates.

1 Points on the downward-sloping 45-degree line indicate countries where the current account was unchanged. Points above (below) this line indicate improvement (deterioration) in the current account. Excludes Guyana and Mozambique.

Notwithstanding the evidence of greater fiscal restraint in the “clear progress” group than in the “limited progress” group, there is no sign of import or growth compression contributing to better progress toward external viability. The countries that made progress toward external viability performed better than the “no progress” group on both real GDP and export volume growth, while average import volumes increased more for the groups that made “clear” and “no” progress than for the groups that made “limited” progress (Table 7.16 and figure 7.5).39 These findings do not lend support to the view drat growth and external viability are conflicting objectives. On the contrary, they suggest a positive association between the two goals, which may reflect causal effects in both directions (export-led growth helps to promote external viability and vice versa), as well as the common influence of strong financial and structural policies.

Table 7.16Growth and Trade Indices1
Average Annual GDP Growth

(in percent)
Export Volume Index

(1985 = 100)
Import Volume Index

(1985 = 100)
Pre-SAF/ESAF21993–95t to 19953Pre-SAF/ESAF21993–95t to 19954Pre-SAF/ESAF31993–95t to 19954
Clear progress
Mean2.14.97.7108.1197.97.3106.6163.95.8
Median2.04.84.2104.9187.66.9103.3162.48.2
Limited progress
Mean1.73.73.2103.7153.25.593.5121.31.8
Median0.93.63.6103.3153.15.7101.2126.53.2
No progress
Mean2.31.41.299.6118.02.8108.1133.75.6
Median2.52.11.2105.4108.53.5106.4138.44.4
Sources: World Bank and IMF staff estimates.

Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania. See footnote 1 in Table 7.5; see also Table 7.22 in Appendix 7.1 for results of statistical tests and Table 7.29 in Appendix 7.2 for country-specific data.

Annual average for three years preceding first SAF/ESAF arrangement.

Annual average since the first annual SAF/ESAF program.

Average annual change in the index from the year preceding the first SAF/ESAF arrangement to 1995; calculated as a geometric mean.

Sources: World Bank and IMF staff estimates.

Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania. See footnote 1 in Table 7.5; see also Table 7.22 in Appendix 7.1 for results of statistical tests and Table 7.29 in Appendix 7.2 for country-specific data.

Annual average for three years preceding first SAF/ESAF arrangement.

Annual average since the first annual SAF/ESAF program.

Average annual change in the index from the year preceding the first SAF/ESAF arrangement to 1995; calculated as a geometric mean.

Figure 7.5Growth of Real GDP, Export Volume, and Import Volume1

(Average annual percent change)

Sources: World Bank and IMF staff estimates.

1Average annual change in the index from the year preceding the first SAF/ESAF arrangement to 1995, calculated as a geometric mean. Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania.

Targets Versus Outcomes: Explaining the Shortfalls

This section examines why some countries with SAF/ESAF-supported adjustment programs for a number of years have made limited or no progress toward external viability. Three questions are addressed. Did countries borrow more than had been anticipated in programs? Was debt management based on excessively optimistic assumptions—for instance, regarding prospective export growth?40 Or was there excessive debt accumulation during periods between ESAF-supported programs, or when such programs had broken down? Most of the discussion concerns countries that did not make clear progress toward external viability, although the experience of other countries is brought in where comparisons are needed.

Did Countries Borrow More Than Anticipated in Programs?

A comparison (Table 7.17) of the projected ratios of debt service to exports, debt to exports, and debt to GDP with outturns shows the following.41

  • Ratios of debt service to exports were usually programmed to fall, but they fell by less than planned.
  • Debt-to-export ratios also were usually programmed to fall, but they tended to increase.
  • In the cases where they were programmed to increase, debt-to-GDP ratios tended to increase more than programmed.
Table 7.17Debt and Debt-Service Ratios: Projections Versus Outturns1
Debt Service/ExportsDebt/ExportsDebt/GDP
tt + 1t + 2tt + 1t + 2tt + 1t + 2
Projections2
Burundi (SAF 1986)16.319.619.349.555.257.3
Equatorial Guinea (ESAF 1993)31.029.228.2229232235121.6112.1107.1
Ghana (ESAF 1988)44.542.935.336838336564.370.574.3
Guinea (ESAF 1991)352.047.243.874.373.671.3
Guyana (ESAF 1990)4116.057.052.0836746718
Honduras (ESAF 1992)41.934.731.632229828161.559.557.2
Kenya (ESAF 1989)24.624.123.723923722758.362.462.4
Madagascar (ESAF 1989)109.298.581.0174.8163.9154.0
Mali (ESAF 1992)44.540.940.6
Mozambique (SAF 1987)5237.0239.7192.3
Mozambique (ESAF 1990)190.5153.8127.3370.8380.2386.9
Niger (ESAF 1989)34.032.831.831031732449.448.948.3
Senegal (ESAF 1988)30.429.126.873.972.569.6
Sierra Leone (SAF 1986)482.051.245.8556528517
Togo (ESAF 1989)37.631.725.923722822280.779.176.9
Zimbabwe (ESAF 1992)25.025.327.278.585.986.2
Mean69.859.952.0387.2371.2361.2104.8105.3104.3
Mean (excluding Mozambique)49.240.336.6387.2371.2361.280.680.378.6
Outturns6
Burundi (SAF 1986)26.142.934.739867959445.866.374.7
Equatorial Guinea (ESAF 1993)43.933.927.8428371257159.1202.9129.5
Ghana (ESAF 1988)37.837.225.331432733558.055.452.9
Guinea (ESAF 1991)29.928.926.128334439770.569.583.9
Guyana (ESAF 1990)98.145.433.0792539426
Honduras (ESAF 1992)42.839.038.6337348336101.6109.4118.5
Kenya (ESAF 1989)25.738.736.031629531460.161.972.2
Madagascar (ESAF 1989)87.673.6103.6611583707117.099.7128.4
Mali (ESAF 1992)41.139.642.158961971791.198.4155.6
Mozambique (SAF 1987)303.0263.0242.02,2722,2342,198275.0335.0339.0
Mozambique (ESAF 1990)212.1158.3171.72,2011,6561,673349.9357.6409.2
Niger (ESAF 1989)38.034.133.428130533652.251.757.1
Senegal (ESAF 1988)35.332.227.632625821171.160.252.8
Sierra Leone (SAF 1986)60.064.258.045550164466.291.464.8
Togo (ESAF 1989)30.533.826.526533729274.769.170.6
Zimbabwe (ESAF 1992)27.629.225.721521519274.977.376.3
Mean71.262.159.5630.3600.6601.7111.1120.4125.7
Mean (excluding Mozambique)44.640.938.5400.8408.6411.280.285.687.5
Source: IMF staff estimates.

Coverage is for countries that did not make “clear” progress toward external viability.

There was a wide variety in the definition of “exports” used to calculate ratios reported in program documents. The majority of cases used exports of goods and nonfactor services. A few used goods and receipts from all services, and others included private transfers. It was not always possible to reconstruct the exact ratios for the outturn data.

The ratio of debt service to exports is based on “net exports” (gross exports less mixed mining companies’ imports, service payments, and transfers).

Export ratios are based on merchandise exports.

Ratio of debt service to exports is based on exports of goods and services including workers remittances.

Export ratios are based on exports of goods and nonfactor services. Reexports are excluded for Madagascar and Togo.

Source: IMF staff estimates.

Coverage is for countries that did not make “clear” progress toward external viability.

There was a wide variety in the definition of “exports” used to calculate ratios reported in program documents. The majority of cases used exports of goods and nonfactor services. A few used goods and receipts from all services, and others included private transfers. It was not always possible to reconstruct the exact ratios for the outturn data.

The ratio of debt service to exports is based on “net exports” (gross exports less mixed mining companies’ imports, service payments, and transfers).

Export ratios are based on merchandise exports.

Ratio of debt service to exports is based on exports of goods and services including workers remittances.

Export ratios are based on exports of goods and nonfactor services. Reexports are excluded for Madagascar and Togo.

Formal limits on external borrowing during IMF arrangements are usually placed only on “nonconcessional” debt.42 IMF-supported programs in the countries that did not make clear progress toward external viability often had zero limits on such debt, and these limits were universally observed (Table 7.18). There was also a high degree of compliance with nonzero limits, with excesses only in Honduras (twice). In general, the amounts of nonconcessional borrowing allowed under the programs reviewed were modest, and actual borrowing was usually well within established limits. Thus, to the extent that these countries continue to have severe debt and debt-service burdens, a closer look must be taken at the broader pattern of debt accumulation envisaged under programs, including the buildup of concessional debt.

Table 7.18ESAF Users: Limits on Nonconcessional Public Borrowing or Guarantees1
Maturity Limited (in years)Amounts, Beginning with First Annual Arrangement2
tt + 1t + 2
Country and ProgramCurrency UnitLimitOutturnLimitOutturnLimitOutturn
Burundi (SAF 1986)SDR millions0–12
Equatorial Guinea (ESAF 1993)30–12
Ghana (ESAF 1988)US$ millions1–1285.085.085.073.5
Guinea (ESAF 1991)US$ millions1–1220.0
Guyana (ESAF 1990)US$ millions0–1210.010.05.0
Honduras (ESAF 1992)4US$ millions1–1215.014.225.027.0*20.020.8*
Kenya (ESAF 1989)US$ millions1–12100.069.5155.0155.079.560.1
Madagascar (ESAF 1989)SDR millions1–1220.03.05.02.6
Mali (ESAF 1992)1–12
Mozambique (SAF 1987)US$ millions1–1220.014.025.03.920.0
Mozambique (ESAF 1990)US$ millions1–1215.00.115.07.01.0
Niger (ESAF 1989)0–12
Senegal (ESAF 1988)SDR millions1–1224.00.524.01.424.0
Sierra Leone (SAF 1986)
Togo (ESAF 1989)
Zimbabwe (ESAF 1992)US$ millions1–15220.021.0170.043.0210.0135.0
Source: IMF staff estimates.

Coverage is for countries that did not make “clear progress” toward external viability; cases where limit was exceeded are indicated with asterisks (*).

The initial annual arrangement is denoted by t. Because of program interruptions, the subsequent two years (t + 1 and t + 2) do not necessarily correspond to the second and third annual arrangements. In many cases the reported limits are from “shadow” programs.

The range of maturities was changed to 0–15 years in year t + 1.

The range of maturities was changed to 1–14 years in year t + 2.

Source: IMF staff estimates.

Coverage is for countries that did not make “clear progress” toward external viability; cases where limit was exceeded are indicated with asterisks (*).

The initial annual arrangement is denoted by t. Because of program interruptions, the subsequent two years (t + 1 and t + 2) do not necessarily correspond to the second and third annual arrangements. In many cases the reported limits are from “shadow” programs.

The range of maturities was changed to 0–15 years in year t + 1.

The range of maturities was changed to 1–14 years in year t + 2.

Were countries borrowing more than expected, or did exports and GDP fall short? For the countries that made limited or no progress toward external viability, there was a clear tendency for projections of official borrowing to exceed outturns (Table 7.19). This tendency may reflect weaknesses in policy implementation; indeed, slippages with respect to conditions for the release of adjustment lending from the World Bank and other multilateral financial institutions were sometimes cited in staff reports to explain delays in programmed disbursements. To investigate this possibility, the experience of countries that made “limited” or “no” progress toward external viability was compared with that of the ten multiyear arrangements in the whole sample that ran the full course without significant interruption—the presumption being that policy implementation in these cases was broadly in line with the original program. The pattern of deviations from projected external borrowing in this subsample was more evenly distributed, although it still showed some tendency to overestimate official borrowing.

Table 7.19Official Borrowing: Targets Versus Outturns1(O = overestimate; U = underestimate; E = on target)
tt + 1t + 2
Limited or no progress2
Burundi (SAF 1986)OEO
Equatorial Guinea (ESAF 1993)UOO
Ghana (ESAF 1988)OOO
Guinea (ESAF 1991)OOO
Guyana (ESAF 1990)OUO
Honduras (ESAF 1992)OUE
Kenya (ESAF 1989)UUE
Madagascar (ESAF 1989)OOO
Mali (ESAF 1992)OOU
Mozambique (SAF 1987)OOO
Mozambique (ESAF 1990)OOO
Niger (ESAF 1989)OOO
Senegal (ESAF 1988)OOO
Sierra Leone (SAF 1986)
Togo (ESAF 1989)OOU
Zimbabwe (ESAF 1992)
Summary frequency distribution
Overestimates121010
On target12
Underestimates232
Uninterrupted programs3
Bangladesh (ESAF 1990/91)4
Benin (ESAF 1993)OOO
Gambia, The
(ESAF 1988/89)OOO
Ghana (ESAF 1988)OOO
Lesotho (SAF 1988/89)UUU
Lesotho (ESAF 1991/92)UUU
Mozambique (SAF 1987)OOO
Nepal (SAF 1987/88)3
Tanzania (SAF 1987/88)3
Uganda (ESAF 1989/90)UUO
Summary frequency distribution
Overestimates445
On target
Underestimates332
Source: IMF staff estimates.

“Targets” are the projections contained in the IMF staff report for the first annual arrangement. Outturns that fall within 5 percent of the projection are classified as being “on target” (E); projections that exceed the outturn by more than 5 percent are classified as “overestimate” (O); and those below outturns by more than 5 percent are classified as “underestimate” (U).

Coverage is for countries that did not make “clear progress” toward external viability.

Coverage is for multiyear arrangements that ran their full course without major interruption (see Chapter 9).

Gross official borrowing not reported in IMF staff report.

Source: IMF staff estimates.

“Targets” are the projections contained in the IMF staff report for the first annual arrangement. Outturns that fall within 5 percent of the projection are classified as being “on target” (E); projections that exceed the outturn by more than 5 percent are classified as “overestimate” (O); and those below outturns by more than 5 percent are classified as “underestimate” (U).

Coverage is for countries that did not make “clear progress” toward external viability.

Coverage is for multiyear arrangements that ran their full course without major interruption (see Chapter 9).

Gross official borrowing not reported in IMF staff report.

As a check on the robustness of this pattern of deviations, the sample was broadened to include all annual SAF/ESAF arrangements for which data were available. Results of formal tests for systematic errors in projections of official borrowing indicate that projections tended to be biased upward in uninterrupted arrangements but not in interrupted arrangements. Outturns for interrupted programs were broadly in line with projections. (The results of the statistical tests and a frequency distribution for the full sample are presented in Table 7.23 in Appendix 7.1 and in Figure 7.6; see Appendix 7.1 for a description of the testing methodology.)

Figure 7.6Official Borrowing: Deviations of Outturns from Projections

(Full sample)

Source: IMF staff estimates.

Two conclusions may be drawn from this evidence. First, it was not the case that borrowing in excess of programmed levels lay behind weak progress toward external viability. Second, the evidence of no significant deviation from targeted official borrowing for interrupted arrangements suggests—contrary to what would be expected, if the IMF plays a catalytic role—that access to foreign borrowing may not have been impeded significantly by weak policy implementation.

Export Projections

Similar comparisons were made of projections and outturns for export earnings. Here, too, there is evidence of a tendency for projections to exceed outturns in the group of countries that did not make clear progress. In contrast, for the ten uninterrupted arrangements, off-target projections for exports were nearly as likely to be overestimates as underestimates, especially in the first two program years (Table 7.20). The evidence is consistent with the hypothesis that weak policy implementation was a factor in countries where “no” progress was made toward external viability.

Table 7.20Merchandise Exports: Targets Versus Outturns1(O = overestimate; U = underestimate; E = on target)
tt + 1t + 2
Limited or no progress2
Burundi (SAF 1986)OOO
Equatorial Guinea (ESAF 1993)OOO
Ghana (ESAF 1988)UEE
Guinea (ESAF 1991)EOO
Guyana (ESAF 1990)OOU
Honduras (ESAF 1992)OOO
Kenya (ESAF 1989)OOO
Madagascar (ESAF 1989)UOO
Mali (ESAF 1992)EOO
Mozambique (SAF 1987)UEO
Mozambique (ESAF 1990)EUO
Niger (ESAF 1989)OOO
Senegal (ESAF 1988)OOO
Sierra Leone (SAF 1986)OOO
Togo (ESAF 1989)UEO
Zimbabwe (ESAF 1992)OOO
Summary frequency distribution
Overestimates91214
On target331
Underestimates411
Uninterrupted arrangements3
Bangladesh (ESAF 1990/91)EUU
Benin (ESAF 1993)OOO
Gambia, The (ESAF 1988/89)EEU
Ghana (ESAF 1988)UEO
Lesotho (ESAF 1988/89)UUO
Lesotho (ESAF 1991/92)EUU
Mozambique (SAF 1987)UEO
Nepal (SAF 1987/88)U
Tanzania (SAF 1987/88)OOO
Uganda (ESAF 1989/90)OOO
Summary frequency distribution
Overestimates336
On target33
Underestimates433
Source: IMF staff estimates.

“Targets” are the projections contained in the IMF staff report for the first annual arrangement. Outturns that fall within 5 percent of the projection are classified as being “on target” (E); projections that exceed the outturn by more than 5 percent are classified as “overestimate” (O); and those below outturns by more than 5 percent are classified as “underestimate” (U).

Coverage is for countries that did not make “clear progress” toward external viability. Equatorial Guinea is excluded because of recent discovery of oil, which has vastly improved its medium-term balance of payments outlook.

Coverage is for multiyear arrangements that ran their full course without major interruption (see Chapter 9).

Source: IMF staff estimates.

“Targets” are the projections contained in the IMF staff report for the first annual arrangement. Outturns that fall within 5 percent of the projection are classified as being “on target” (E); projections that exceed the outturn by more than 5 percent are classified as “overestimate” (O); and those below outturns by more than 5 percent are classified as “underestimate” (U).

Coverage is for countries that did not make “clear progress” toward external viability. Equatorial Guinea is excluded because of recent discovery of oil, which has vastly improved its medium-term balance of payments outlook.

Coverage is for multiyear arrangements that ran their full course without major interruption (see Chapter 9).

In formal tests for systematic errors in export projections, the sample of all annual arrangements exhibited a tendency towards overshooting in export projections. However, there was a marked difference between uninterrupted and interrupted arrangements: outturns tended to exceed projections in the uninterrupted arrangements and to fall short in the interrupted ones. (The results of the statistical tests and a frequency distribution for the full sample are presented in Table 7.24 in Appendix 7.1 and in Figure 7.7.) This suggests that underperformance of exports relative to projections may be related to weaker-than-programmed policies. If so, the projections, which implicitly assume full implementation of the agreed policies, should not be interpreted as biased.

Figure 7.7Merchandise Exports: Deviations of Outturns from Projections

(Full sample)

Source: IMF staff estimates.

Evolution of Debt During and Outside Programs

The last of the questions posed at the beginning of this section was whether heavy borrowing during program interruptions might be a factor in the cases where there had been a lack of significant progress toward external viability. To address this question, the sample was reduced to the 14 cases where either program interruptions lasted for a year or more or an incomplete program had not been replaced by another arrangement (thus yielding a “nonprogram” period) for at least a year.43 Eight of these countries were classified above as having made “limited” or “no” progress toward external viability.

Overall, the evidence suggests that the average pace of debt accumulation was similar for “program” and “interruption” periods (Table 7.21). However, in half of the cases debt accumulation during the interruption periods exceeded the pace when the program was on track. Thus, in general, borrowing appears not to have been curtailed significantly when programs (policy implementation) faltered, and in some instances a perverse relationship is apparent (higher borrowing associated with program interruptions).44 This finding suggests some ambiguity in the link between aid disbursements and policy implementation, in contrast to the earlier suggestion of a positive link between disbursements of official transfers and policies.

Table 7.21Debt Accumulation During and Outside Program Years1
Average Growth in Debt Stock2 (in percent a year)Time Span
Program years“Interruption” yearsProgram years“Interruption” years
Countries that did not make clear progress3
Burundi14.14.554
Equatorial Guinea5.6-2.743
Ghana5.08.453
Guinea3.510.454
Honduras0.78.822
Mali6.02.552
Senegal2.72.572
Sierra Leone5.28.126
Mean5.45.34.43.3
Standard deviation4.04.41.71.4
Other countries with at least one year of program interruption4
Benin10.821.461
Bolivia1.211.771
Burkina Faso24.315.641
Mauritania5.60.663
Nepal15.512.334
Tanzania3.84.353
Mean10.211.05.22.2
Mean (excluding Tanzania)11.512.35.22.0
Standard deviation8.67.51.51.3
All countries in subsample
Mean7.47.74.72.8
Standard deviation6.66.41.61.4
Source: IMF staff estimates.

Coverage is for nontransition ESAF users where program interruption lasted at least one year.

Simple average.

Subset of the countries that made “limited” or “no progress” toward external viability (see Table 7.5).

Tanzania and a subset of the countries that made “clear progress” toward external viability (see Table 7.5).

Source: IMF staff estimates.

Coverage is for nontransition ESAF users where program interruption lasted at least one year.

Simple average.

Subset of the countries that made “limited” or “no progress” toward external viability (see Table 7.5).

Tanzania and a subset of the countries that made “clear progress” toward external viability (see Table 7.5).

Conclusions

Since the mid–1980s, the structure of public and publicly guaranteed external debt of ESAF users has shifted toward more concessional bilateral and multilateral debt, and away from private commercial debt. Also, the proportion of official grants in aggregate net resource flows to most of these countries has increased while the share of net debt flows has declined. However, several countries continue to be saddled with heavy debt and debt-service burdens. This chapter has reviewed evidence on the external sector performance of a broad sample of ESAF users with a view to assessing the extent to which they had made progress toward external viability since the inception of SAF/ESAF-supported programs. It has also sought to identify policy lessons for improving performance under programs by comparing the experiences of the relatively more successful countries with the rest.

Twelve out of the 27 countries for which there was sufficiently complete and reliable data were judged to have made “clear” progress toward external viability, 10 to have made “limited” progress, and the remaining 5 to have made “no” progress. All the 11 countries that were judged to have made some progress in the 1993 ESAF review (Schadler and others, 1993) remained in the same category in this review, and more than half of the poorer performers in the 1993 review are now classified as having made some progress. Notwithstanding the progress that many countries have made, several still have heavy debt-service burdens.

Contrary to a common concern that IMF-supported programs achieve progress toward external viability by squeezing imports and promoting exports to curtail current account deficits, the analysis found that the countries that made progress maintained larger current account deficits than those that made no progress. These larger deficits were financed by higher levels of official transfers. The group that made “no” progress spent significantly less time under completed annual arrangements than the groups that made “clear” or “limited” progress, suggesting that the pattern of official grants may partly reflect donors’ responses to performance under IMF-supported programs.

Far from being conflicting objectives, it appears that strong export-led growth and progress toward external viability are complementary. The countries making most progress achieved significantly greater real GDP and export volume growth than those that made no progress. The study found positive associations between fiscal tightening, export growth, and real GDP growth on the one hand and progress toward external viability on the other. While the relative performances of the various groups were influenced to some extent by differences in the impact of terms of trade shocks, significantly stronger fiscal adjustment in the group that made “clear” progress suggests that policies were important to the outcomes.

Terms of borrowing do not appear to be an important factor in the extent to which countries made progress toward external viability. In particular, there was no significant difference between groups in the average grant element received in new borrowing since countries embarked on their SAF/ESAF-supported programs.

Why did debt management policies not succeed in containing debt pressures, especially in countries that made “no” progress toward external viability? The evidence indicates that program limits on nonconcessional borrowing were almost universally respected, and that there was no tendency for total official borrowing (including concessional resources) to exceed programmed levels. The study also found no evidence that borrowing plans incorporated in these programs were based on systematically unrealistic export projections, once account is taken of broad policy implementation.

What does seem to have contributed to persistent debt problems in a number of the countries under review is an apparent tendency for borrowing to have continued even when policy implementation faltered and programs were interrupted. This suggests a possible disconnection between loan disbursements and policies (in contrast to the earlier suggestion that disbursements of grants may have been positively related to policy implementation).

Appendix 7.1. Statistical Tests of Differences Between Group Averages

A substantial part of the analysis in this chapter revolves around the grouping of countries according to the degree of progress toward external viability. In view of large dispersions of data values within groups, differences in group averages were tested for statistical significance. For each variable of interest, a first step was to establish whether the distribution of data within each group could be said to have come from a normally distributed population. This was done using standard normality tests based on skewness and excess kurtosis.

If the data passed the normality test for each group, a t-test was applied for small sample inferences concerning two means (“clear progress” versus “limited progress,” and “clear progress” versus “no progress”), the null hypothesis being that the two means are equal. The calculated t and corresponding degrees of freedom are obtained (see, for example, Blaisdell, 1993) from

where x¯i is the mean of group i,si2 is the variance for group i, and ni is the number of observations in group i.

If for any particular variable the tests rejected the null hypothesis of normality for one group or more, the nonparametric Mann -Whitney [i-test of differences between pairs of medians was used. This test entails ranking all the observations from the lowest to the highest value, calculating the rank sum for each group and using this in a s-rest where the calculated z (see, for example, Blaisdell, 1993) is

where n1 is the number of observations in sample 1, n2 is the number of observations in sample 2, and

where R2 is the rank sum for sample 2.

Because it is recommended that for this test each group have at least ten observations, the tests involving the “no progress” group—which has only five members—were supplemented by tests of equality between the medians for the “clear” and “limited” or “no progress” groups.

Summary test statistics for checking differences in group averages in this chapter are reported in Table 7.22 (see also Tables 7.23 and 7.24).

Table 7.22Statistical Tests of Differences in Group Averages
Table Number and VariableNull Hypothesis1t-Statistic2z-Statistic2
Table 7.5Percent change in ratio of scheduled debt service to exportsMedian 1 = Median2-0.79
Medianl = Median3-2.53**
Medianl = Median4-1.76*
Percent change in ratio of scheduled debt service to GDPMedianl = Median2-0.36
Medianl = Median3-2.64**
Medianl = Median4-1.54
Change in ratio of exceptional financing to exportsMedianl =Median2-3.43**
Medianl = Median4-1.79*
Medianl = Median3-3.37**
Table 7.7Change in ratio of scheduled debt service to GDPMedianl =Median20.28
Medianl = Median3-3.16**
Medianl = Median4-1.34
Change in ratio of scheduled debt service to government revenueMedianl = Median2-1.63
Medianl = Median3-2.42**
Medianl =Median4-2.37**
Change in ratio of government revenue to GDPMeanl =Mean21.54
Meanl = Mean30.78
Table 7.11Average grant element in new borrowing (Pre-SAF/ESAF)Meanl = Mean20.77
Meanl = Mean31.19
Average grant element in new borrowing (1993–95)Meanl = Mean2-0.81
Meanl =Mean31.13
Average grant element in new borrowing (t to 1995)Medianl = Median20.14
Medianl =Median31.37
Medianl = Median40.77
Ratio of NPV to nominal debt (1995)Meanl = Mean2-1.47
Meanl = Mean3-3.74**
Table 7.12Percent change in ratio of external debt to exportsMeanl = Mean2-0.43
Meanl =Mean3-0.31
Noninterest current account deficitMedianl = Median20.25
Medianl = Median32.44**
Medianl = Median41.30
Interest paymentsMeanl = Mean20.35
Meanl = Mean3-2.07*
Official transfersMedian 1 = Median20.25
Medianl = Median3-2.04**
Median 1 =Median4-0.75
Increase in gross reservesMedianl = Median21.65
Medianl = Median31.53
Medianl = Median41.92*
Export growthMeanl =Mean21.92*
Meanl =Mean31.92*
Table 7.13Percent change in terms of tradeMeanl =Mean21.66
Meanl =Mean30.76
Percent change in real effective exchange rateMeanl = Mean22.71**
Meanl =Mean31.02
Table 7.15Change in primary fiscal balanceMeanl =Mean21.84*
Meanl = Mean31.21
Change in nongovernment sector balanceMedianl = Median2-1.71*
Medianl = Median3-1.42
Medianl = Median4-1.93*
Change in noninterest current accountMeanl =Mean2-0.51
Meanl =Mean3-0.65
Table 7.16Average annual GDP growthMedianl = Median21.25
Medianl = Median32.32**
Medianl = Median42.00**
Average annual export volume growthMeanl = Mean20.96
Meanl = Mean31.89*
Average annual import volume growthMeanl =Mean21.39
Meanl = Mean30.25

For the series that passed the normality test, the null hypotheses test for equality between the mean of the clear progress group (Meanl) and the means of the “limited” and “no progress” groups (Mean2 and Mean3, respectively). For the nonnormal series, the nonparametric tests were used to test null hypotheses of equality between medians-Median 1, Median2, and Median3, for the “clear,” “limited,” and “no progress” groups, respectively. In addition, because of the small size of the “no progress” group, the median for the “clear progress” group was also compared with the median for the combined “limited” and “no progress” groups (Median4).

Single (*) and double (**) asterisks indicate the cases where the null hypothesis is rejected at the 10 percent and 5 percent significance levels, respectively.

For the series that passed the normality test, the null hypotheses test for equality between the mean of the clear progress group (Meanl) and the means of the “limited” and “no progress” groups (Mean2 and Mean3, respectively). For the nonnormal series, the nonparametric tests were used to test null hypotheses of equality between medians-Median 1, Median2, and Median3, for the “clear,” “limited,” and “no progress” groups, respectively. In addition, because of the small size of the “no progress” group, the median for the “clear progress” group was also compared with the median for the combined “limited” and “no progress” groups (Median4).

Single (*) and double (**) asterisks indicate the cases where the null hypothesis is rejected at the 10 percent and 5 percent significance levels, respectively.

Table 7.23Systematic Errors in Projections of Official Borrowing
Uninterrupted ArrangementsInterrupted ArrangementsAll Arrangements
Full samplett+ 1t + 2Full samplett+ 1t + 2Full samplett+ 1t + 2
Means
Projected163.88157.83164.07169.75228.21252.84239.26180.59220.06241.88230.24178.97
Actual169.76168.70157.33183.24215.80238.09232.39164.19209.97230.08223.38167.05
Correlation coefficient
Between actual and projected values0.900.930.880.900.970.980.970.920.970.980.960.90
Root = mean = square error80.0761.0587.0589.0573.4667.0291.3352.9874.3366.3690.8359.79
Decomposition of mean-square error into:1
Proportion due to bias0.010.030.010.020.030.050.010.100.020.030.010.04
Proportion due to difference of regression coefficient from unity0.480.280.570.570.010.020.010.040.010.15
Proportion due to residual variance0.510.690.420.410.960.930.980.860.980.960.990.81
Regression of actual on projected values2
Constant term58.5042.2355.8075.40-17.64-21.12-14.53-0.06-11.09-15.69-10.7318.43
t-statistic32.63**1.021.321.73-2.27**-1.77*-0.77-0.01-1.25-1.24-0.531.38
Slope coefficient0.680.800.620.641.021.031.030.911.001.021.020.83
t-statistic3,4-4.64**-1.68-2.60**-2.59**0.670.530.37-1.190.110.300.17-2.58**
Mean deviation regression5
Constant term5.8710.87-6.7313.49-12.41-14.75-6.87-16.40-10.09-11.79-6.86-11.92
t-statistic30.300.40-0.170.34-1.90*-1.51-0.50-1.87-1.63-1.29-0.53-1.27
Number of observations18666124464434142525040

Based on the regression of actual (A) on projected (P) values: A(t) = a + bP(t) + e(t). Proportion due to bias = 0 when a = 0; proportion due to difference of regression coefficient from unity = 0 when b = 1; the remaining proportion is due to variance of e. See Maddala (1977).

Statistical significance at the 10 percent and 5 percent level is indicated by * and **, respectively.

Based on heteroscedastic-consistent standard errors.

Null hypothesis: slope coefficient equals unity.

Estimates of the constant parameter based on a regression restricting the slope coefficient to unity.

Based on the regression of actual (A) on projected (P) values: A(t) = a + bP(t) + e(t). Proportion due to bias = 0 when a = 0; proportion due to difference of regression coefficient from unity = 0 when b = 1; the remaining proportion is due to variance of e. See Maddala (1977).

Statistical significance at the 10 percent and 5 percent level is indicated by * and **, respectively.

Based on heteroscedastic-consistent standard errors.

Null hypothesis: slope coefficient equals unity.

Estimates of the constant parameter based on a regression restricting the slope coefficient to unity.

Table 7.24Systematic Errors in Projections of Export Earnings
Uninterrupted ArrangementsInterrupted ArrangementsAll Arrangements
Full samplett + 1t + 2Full samplett + 1t + 2Full samplett + 1t + 2
Means
Projected469.78402.18477.52537.14774.93760.61865.34683.54726.10704.61807.17657.70
Actual447.48390.90447.92509.89744.60735.93850.28627.41697.06682.02789.92606.67
Correlation coefficient
Between actual and projected values0.990.990.990.990.991.000.990.990.990.990.990.99
Root = mean = square error101.3656.3492.96140.70204.48186.26257.85144.91191.74172.54240.44144.18
Decomposition of mean = square error into:1
Proportion due to bias0.050.040.100.040.020.020.000.150.020.020.010.13
Proportion due to difference of regression coefficient from unity0.180.090.120.300.270.600.180.120.240.560.160.06
Proportion due to residual variance0.770.870.780.660.710.380.820.730.740.420.830.81
Regression of actual on projected values2
Constant term-58.62-25.42-57.61-94.6732.4558.7546.09-20.9525.7251.6836.66-25.92
t-statistic3-2.60**-1.27-1.36-1.561.96*2.12**1.29-1.001.611.95*1.09-1.64
Slope coefficient1.081.041.061.130.920.890.930.950.920.890.930.96
t-statistic3,41.79*1.400.691.05-2.79**-2.20**-1.22-1.82*-2.57**-2.06**1.14-1.82*
Mean deviation regression5
Constant term-22.30-11.28-29.60-27.25-30.33-24.69-15.06-56.13-29.05-22.59-17.24-51.03
t-statistic3-1.17-0.61-0.950.56-1.81*-0.97-0.41-2.69**-2.02**-1.05-0.55-2.68**
Number of observations281099147545442175646051

Based on the regression of actual (A) on projected (P) values: A(t) = a + bP(t) + e(t). Proportion due to bias = 0 when a = 0; proportion due to difference of regression coefficient from unity = 0 when b = 1; the remaining proportion is due to variance of e. See Maddala (1977).

Statistical significance at the 10 percent and 5 percent level is indicated by * and **, respectively.

Based on heteroscedastic-consistent standard errors.

Null hypothesis: slope coefficient equals unity.

Estimates of the constant parameter based on a regression restricting the slope coefficient to unity.

Based on the regression of actual (A) on projected (P) values: A(t) = a + bP(t) + e(t). Proportion due to bias = 0 when a = 0; proportion due to difference of regression coefficient from unity = 0 when b = 1; the remaining proportion is due to variance of e. See Maddala (1977).

Statistical significance at the 10 percent and 5 percent level is indicated by * and **, respectively.

Based on heteroscedastic-consistent standard errors.

Null hypothesis: slope coefficient equals unity.

Estimates of the constant parameter based on a regression restricting the slope coefficient to unity.

Appendix 7.2. Decomposition of Changes in Debt-to-Export Ratios

Changes in the ratio of external debt to exports may be due, algebraically, to changes in the debt stock, changes in exports, or a combination of the two. Changes in the debt stock may arise from contracting new debt, amortization, debt cancellation, or valuation changes.

In general, net debt-creating flows in the balance of payments should account for the bulk of changes in the debt stock over a specified period. However, there are two elements that are not captured by these flows: valuation changes and cancellation of debt that has not fallen due. The total change in debt stock can be expressed as in equation (1):

where Dt is debt stock at the end of period t; DBt is net debt-creating flows in the balance of payments during period t; Vt is valuation changes; and Ct is cancellation of debt that has not fallen due. Incorporation of the balance of payments identity into equation (1) and some straightforward algebraic manipulation yields the principal influences on the evolution of debt-to-export ratios.

Balance of payments identity

where ΔR is change in international reserves; NICA is noninterest current account balance, defined to include private transfers but exclude official transfers; i is the effective interest rate, calculated from net interest payments and “average” levels of external debt (D) and reserves (R); OT is official transfers; Fl is foreign investment (direct and portfolio); and Z is net other flows. Recast equation (2):

Debt-export ratio

where Xt is exports of goods and services in period t.

Proportionate change in debt-export ratio

Combining equations (1), (3), and (5) yields

Because of data limitations, the decomposition exercise in Table 7.12 in the text and in Table 7.25 combined some of the elements of equation (6) as follows:

  • The “noninterest” current account balance was redefined to include interest earnings on international reserves.
  • The effective interest rate was calculated from interest payments only (rather than as interest payments net of interest receipts).
  • Foreign direct investment (rather than total foreign investment) is identified separately.
  • Foreign portfolio investment, debt cancellation, valuation changes, and nee other flows (including errors and omissions) are combined under “other.” This term also includes, by residual, a cross-product term (d^X^) omitted in the approximation contained in equation (5).
Table 7.25Analysis of Change in Ratios of External Debt to Exports1
Influences on External Debt (annual average; in percent of beginning-period debt stock)
External Debt/Exports (in percent)Current account deficit excluding interest
Prior to first SAF/ESAF21995Percent change3Interest paymentsOfficial transfersIncrease in gross reservesForeign direct investmentOther4Export growth (percent)5Time span (years)6
Clear progress7
Bangladesh663.9380.2-6.027.32.7-12.52.5-0.1-8.217.79.0
Benin491.4480.4-0.310.32.3-15.24.3-0.810.411.77.0
Bolivia523.0383.6-3.48.13.4-4.80.7-0.4-3.86.69.0
Gambia, The664.8421.4-4.514.82.7-16.23.7-2.51.68.510.0
Lesotho271.6200.1-3.7150.35.4-82.322.6-5.7-75.418.68.0
Malawi383.7498.33.316.94.4-9.00.1--3.04.68.0
Mauritania334.8433.82.68.34.3-6.40.2-0.3-4.43.010.0
Nepal266.0281.00.748.43.2-9.16.2-0.4-1.312.38.0
Pakistan287.8219.0-3.89.95.7-3.21.5-1.9-0.513.97.0
Sri Lanka230.1177.3-3.212.05.0-4.24.7-2.1-13.28.0
Uganda340.1460.13.424.74.2-16.33.5-0.10.37.59.0
Mean405.2357.8-1.430.13.9-16.34.6-1.3-7.710.78.5
Mean (excluding Lesotho)418.6373.5-1.118.13.8-9.72.7-0.9-0.99.98.5
Median340.1383.6-3.214.84.2-9.13.5-0.4-1.311.78.0
Limited progress
Burundi351.6871.69.539.03.6-33.64.3-0.2-3.00.710.0
Equatorial Guinea399.3257.3-5.327.15.1-16.3-0.1-9.7-2.29.38.0
Ghana331.2307.6-0.812.34.2-7.82.6-2.1-2.47.89.0
Guinea305.3416.83.510.83.5-6.1-1.1-1.00.32.99.0
Guyana737.6325.5-12.7-1.82.2-0.42.3-1.116.06.0
Mali565.8507.9-1.316.10.1-12.93.9-0.2-1.37.08.0
Mozambique2,131.71,356.9-4.918.90.8-13.81.5-0.50.312.09.0
Niger262.5489.07.215.74.7-15.40.1-0.7-0.4-3.09.0
Senegal356.9248.5-3.915.18.2-13.52.1--5.99.99.0
Togo285.2422.55.08.14.2-6.2-1.1-0.3-0.1-0.48.0
Mean572.7520.4-0.416.13.7-12.61.5-1.5-1.36.28.5
Median354.2419.7-1.115.43.9-13.21.8-0.4-0.87.49.0
No progress
Honduras340.6278.2-4.95.04.8-4.20.7-1.50.29.94.0
Kenya330.6261.3-2.93.24.8-3.60.4-0.4-0.66.88.0
Madagascar663.7341.6-7.14.83.7-4.6-0.4-0.4-3.07.29.0
Sierra Leone338.81,042.313.313.18.3-4.50.80.6-10.9-5.99.0
Zimbabwe167.1167.60.18.26.0-5.53.7-0.8-4.07.64.0
Mean368.2418.2-0.36.95.6-4.51.0-0.5-3.75.16.8
Median338.8278.2-2.95.04.8-4.50.7-0.4-3.07.28.0

Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania. See footnote 1 in Table 7.5.

Year preceding the first annual SAF/ESAF arrangement.

Annual average calculated as geometric mean. The reported mean for each group is calculated as the average of percent changes for countries in the group.

Includes debt cancellation, portfolio capital flows, errors and omissions, valuation changes, and cross-product terms (see Appendix 7.2).

Exports of goods and nonfactor services. Annual average calculated as geometric mean.

Number of years from first SAF/ESAF arrangement to most recent year for which complete data (for all relevant variables) was available.

Burkina Faso is excluded from this analysis because of gaps in its debt-stock data for the late 1980s.

Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania. See footnote 1 in Table 7.5.

Year preceding the first annual SAF/ESAF arrangement.

Annual average calculated as geometric mean. The reported mean for each group is calculated as the average of percent changes for countries in the group.

Includes debt cancellation, portfolio capital flows, errors and omissions, valuation changes, and cross-product terms (see Appendix 7.2).

Exports of goods and nonfactor services. Annual average calculated as geometric mean.

Number of years from first SAF/ESAF arrangement to most recent year for which complete data (for all relevant variables) was available.

Burkina Faso is excluded from this analysis because of gaps in its debt-stock data for the late 1980s.

See also Tables 7.267.29 for further results of the calculations.

Table 7.26Terms of Trade and Real Effective Exchange Rate Indices1
Terms of Trade (1985 = 100)Real Effective Exchange Rate Indices2 (1985 = 100)
Pre-SAF/ESAF31993–95Percent changePre-SAF/ESAF31993–95Percent change
Clear progress
Bangladesh111.8115.33.295.173.4-22.8
Benin55.559.57.3100.879.8-20.8
Bolivia93.246.2-50.462.620.0-68.1
Burkina Faso137.8144.85.191.661.9-32.4
Gambia, The139.497.6-30.097.375.0-22.9
Lesotho119.1169.242.097.495.2-2.2
Malawi100.295.0-5.291.173.4-19.4
Mauritania90.886.5-4.8106.759.6-44.2
Nepal98.492.4-6.196.768.0-29.7
Pakistan107.0100.1-6.585.259.7-30.0
Sri Lanka97.992.0-6.089.580.4-10.1
Uganda107.358.9-45.194.053.1-43.5
Mean104.996.5-8.092.366.6-27.8
Median103.693.7-5.694.670.7-26.3
Limited progress
Burundi97.663.6-34.8101.249.1-51.5
Equatorial Guinea97.391.6-5.985.854.0-37.1
Ghana105.787.5-17.398.429.6-69.9
Guinea97.358.5-39.969.05.7-91.7
Guyana117.490.1-23.353.035.9-32.3
Mozambique102.787.8-14.598.519.5-80.2
Niger99.571.7-28.0100.048.8-51.2
Senegal91.881.9-10.893.764.7-30.9
Togo98.972.3-27.0105.073.4-30.1
Mean100.978.3-22.489.442.3-52.7
Median98.981.9-23.398.448.8-51.2
No progress
Honduras97.891.4-6.691.558.3-36.3
Kenya101.7101.5-0.189.572.5-18.9
Madagascar105.466.0-37.499.951.8-48.1
Mali85.972.1-16.092.953.9-42.0
Sierra Leone103.392.5-10.4101.347.1-53.6
Zimbabwe127.5115.2-9.668.954.0-21.7
Mean103.689.8-13.490.756.3-38.0
Median102.592.0-10.092.253.9-39.2
Sources: IMF, World Economic Outlook and Information Notice System databases.

Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania. See footnote 1 in Table 7.5.

Increases signify real appreciation, decreases real depreciation.

Annual average for three years preceding first SAF/ESAF arrangement.

Sources: IMF, World Economic Outlook and Information Notice System databases.

Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania. See footnote 1 in Table 7.5.

Increases signify real appreciation, decreases real depreciation.

Annual average for three years preceding first SAF/ESAF arrangement.

Table 7.27Indicators of External Sector Reforms

(Six-point scale)1

Exchange System Scores2Trade System Scores3
1981–851986–901991–951981–851986–901991–95
Clear progress
Bangladesh2.02.04.02.02.04.0
Benin6.06.06.03.04.06.0
Bolivia2.06.06.05.06.06.0
Burkina Faso6.06.06.03.03.05.0
Gambia, The5.05.06.03.04.05.0
Lesotho6.06.06.05.05.05.0
Malawi3.05.05.02.04.05.0
Mauritania3.04.04.03.04.05.0
Nepal3.04.05.03.03.05.0
Pakistan5.06.06.02.02.03.0
Sri Lanka5.05.06.03.03.04.0
Uganda2.02.05.02.03.04.0
Mean4.25.05.53.13.64.8
Median5.05.06.03.04.05.0
Limited progress
Burundi5.05.05.02.04.04.0
Equatorial Guinea6.06.06.04.04.05.0
Ghana2.04.06.02.04.06.0
Guinea3.05.06.02.06.06.0
Guyana3.03.05.04.05.06.0
Mali6.06.06.03.03.05.0
Mozambique2.03.05.02.02.04.0
Niger5.06.06.05.06.06.0
Senegal6.06.06.03.03.04.0
Togo6.06.06.04.04.05.0
Mean4.24.95.73.04.15.1
Median5.05.06.03.04.05.0
No progress
Honduras4.03.06.02.02.06.0
Kenya4.05.05.02.02.06.0
Madagascar3.04.05.02.04.04.0
Sierra Leone4.03.06.02.04.05.0
Zimbabwe2.02.05.03.04.03.0
Mean3.33.55.32.33.54.5
Median3.53.55.02.04.04.5
Memorandum
Mean (whole sample)4.04.65.52.93.74.9
Median (whole sample)4.05.06.03.04.05.0
Source: Chapter 4.

The extent of reform is classified as low (score of 1–2), moderate (3–4), or high (5–6) relative to a specified notion of “best practices” (score of 5–6).

Based on the level of parallel market exchange rate premiums and the extent of surrender requirements and nonmarket foreign exchange allocation.

Based on the extent of quantitative restrictions, levels and dispersion of tariffs, and the extent of import exemptions.

Source: Chapter 4.

The extent of reform is classified as low (score of 1–2), moderate (3–4), or high (5–6) relative to a specified notion of “best practices” (score of 5–6).

Based on the level of parallel market exchange rate premiums and the extent of surrender requirements and nonmarket foreign exchange allocation.

Based on the extent of quantitative restrictions, levels and dispersion of tariffs, and the extent of import exemptions.

Table 7.28Sectoral Financial Balances(In percent of GDP)
Primary Fiscal Balance1Nongovernment Sector Balance2Noninterest Current Account3
Pre-SAF/ESAF41993–955ChangePre-SAF/ESAF41993–955ChangePre-SAF/ESAF41993–955Change
Clear progress
Bangladesh-7.2-4.82.40.6-0.9-1.5-6.6-5.70.9
Benin-8.2-3.44.83.4-1.3-4.7-4.8-4.70.1
Bolivia-14.3-3.011.314.4-3.8-18.20.1-6.8-6.9
Burkina Faso-6.6-8.7-2.2-1.9-0.11.8-8.5-8.8-0.3
Gambia, The-8.36.715.0-3.0-21.7-18.7-11.3-15.1-3.7
Lesotho-8.21.29.3-7.1-35.0-27.9-15.3-33.8-18.5
Malawi-4.7-11.0-6.32.3-10.3-12.5-2.4-21.3-18.8
Mauritania-19.5-1.817.6-6.9-7.3-0.4-26.3-9.117.2
Nepal-8.0-4.33.61.8-4.7-6.5-6.2-9.1-2.9
Pakistan-4.0-0.63.32.4-1.4-3.8-1.6-2.1-0.5
Sri Lanka-6.8-3.23.6-0.1-2.7-2.6-6.9-5.91.0
Uganda-3.6-7.4-3.83.20.9-2.3-0.4-6.5-6.1
Mean-8.3-3.44.90.7-7.4-8.1-7.5-10.7-3.2
Mean (excl. Lesotho)-8.3-3.84.51.5-4.9-6.3-6.8-8.6-1.8
Median-7.6-3.33.61.2-3.3-4.2-6.4-7.8-1.7
Limited progress
Burundi-12.9-7.55.4-1.7-9.2-7.5-14.6-16.7-2.1
Equatorial Guinea2.5-10.4-12.9-26.5-14.611.9-24.0-24.9-0.9
Ghana-3.0-4.4-1.40.9-3.2-4.1-2.1-7.6-5.5
Guinea-4.8-5.7-0.93.8-1.9-5.7-1.0-7.6-6.6
Guyana-10.54.715.23.12.5-0.6-7.47.214.6
Mali-11.1-9.51.6-10.1-4.06.1-21.2-13.57.7
Mozambique-15.5-21.6-6.13.4-22.3-25.7-12.1-43.9-31.8
Niger-6.3-8.0-1.6-2.2-0.31.9-8.5-8.30.2
Senegal-1.0-1.6-0.6-12.0-4.47.6-13.0-6.07.0
Togo-2.8-7.9-5.1-9.54.313.8-12.3-3.78.7
Mean-6.6-7.2-0.6-5.1-5.3-0.2-11.6-12.5-0.9
Median-5.6-7.7-1.1-2.0-3.60.6-12.2-8.0-0.4
No progress
Honduras-3.2-2.70.5-0.3-2.4-2.0-3.5-5.1-1.6
Kenya-1.75.37.0-3.1-1.91.2-4.83.48.3
Madagascar-2.8-5.6-2.8-1.3-0.21.1-4.1-5.8-1.7
Sierra Leone-9.7-6.03.76.4-6.1-12.5-3.3-12.1-8.8
Zimbabwe-2.5-1.60.90.6-1.0-1.6-1.9-2.7-0.7
Mean-4.0-2.11.90.4-2.3-2.8-3.5-4.5-0.9
Median-2.8-2.70.9-0.3-1.9-1.6-3.5-5.1-1.6

Excluding grants.

Calculated as current account balance minus fiscal balance.

Noninterest current account balance excluding official transfers.

Annual average for three years preceding first SAF/ESAF program.

Annual average of most recent three years for which data are available.

Excluding grants.

Calculated as current account balance minus fiscal balance.

Noninterest current account balance excluding official transfers.

Annual average for three years preceding first SAF/ESAF program.

Annual average of most recent three years for which data are available.

Table 7.29Growth and Trade Indices1
Average Annual GDP Growth (in percent)Export Volume Index (1985 = 100)Import Volume Index (1985 = 100)
Pre-SAF/ESAF21993–95t–19953Pre-SAF/ESAF21993–95t–19954Pre-SAF/ESAF21993–95t–19954
Clear progress
Bangladesh4.64.716.1103.8282.712.388.0192.98.6
Benin0.94.13.171.7218.622.2102.4163.38.6
Bolivia-1.04.03.7106.5198.16.6104.5139.65.1
Burkina Faso2.01.43.3114.0107.3-5.9114.9113.7-1.0
Gambia, The-0.8-0.22.2165.4125.13.6155.2137.50.9
Lesotho4.012.49.9126.6540.719.099.6191.38.6
Malawi2.03.02.695.4108.42.889.7161.611.1
Mauritania1.04.93.193.388.0-1.2113.371.0-4.5
Nepal3.15.65.185.1177.29.498.0170.27.8
Pakistan5.75.05.0126.2235.37.299.8126.33.8
Sri Lanka3.66.04.8102.9204.110.4104.1186.59.2
Uganda0.58.133.9105.989.11.6109.5313.611.1
Mean2.14.97.7108.1197.97.3106.6163.95.8
Mean (excluding Lesotho)2.04.27.5106.4166.76.3107.2161.55.5
Median2.04.84.2104.9187.66.9103.3162.48.2
Limited progress
Burundi5.2-5.40.994.7146.13.996.8136.33.4
Equatorial Guinea1.19.65.799.8206.412.2100.9121.05.1
Ghana6.34.44.6102.9230.28.696.6176.34.4
Guinea4.44.0107.0125.70.90.0123.13.1
Guyana-1.77.34.987.1160.011.782.8130.09.6
Mali6.42.13.1103.8173.17.7108.6132.93.3
Mozambique-1.78.65.2116.4168.97.5116.8165.8-0.3
Niger-1.82.80.9110.2103.70.8114.053.1-6.7
Senegal0.71.62.3101.0132.23.6101.5104.30.5
Togo2.41.60.8113.786.0-2.3117.270.6-4.7
Mean1.93.73.2103.7153.25.593.5121.31.8
Median1.13.63.6103.3153.15.7101.2126.53.2
No progress
Honduras2.52.83.4109.7129.33.597.6138.411.6
Kenya5.82.73.1109.0164.95.8114.2164.76.0
Madagascar1.61.41.2105.4106.82.0103.190.42.9
Sierra Leone-1.3-2.1-1.285.080.4-5.4106.4132.52.9
Zimbabwe3.12.1-0.389.0108.58.0119.0142.44.4
Mean2.31.41.299.6118.02.8108.1133.75.6
Median2.52.11.2105.4108.53.5106.4138.44.4
Sources: World Bank; and IMF staff estimates.

Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania. See footnote 1 in Table 7.5.

Annual average for three years preceding first SAF/ESAF arrangement.

Annual average since the first annual SAF/ESAF program.

Average annual change in the index from the year preceding the first SAF/ESAF arrangement to 1995; calculated as a geometric mean.

Sources: World Bank; and IMF staff estimates.

Excluding transition economies, Côte d’Ivoire, Nicaragua, and Tanzania. See footnote 1 in Table 7.5.

Annual average for three years preceding first SAF/ESAF arrangement.

Annual average since the first annual SAF/ESAF program.

Average annual change in the index from the year preceding the first SAF/ESAF arrangement to 1995; calculated as a geometric mean.

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1For a discussion of current account sustainability in the context of market-based capital flows, with applications to selected east Asian and Latin American countries, see Milesi-Ferreti and Razin (1996).
2The determination of “balance of payments need” requires a distinction between transactions undertaken for their own sake (that is, “autonomous” or “above-the-line” transactions that contribute to the overall balance) and financing items (see IMF, 1993). Borrowing from the IMF is always in support of a balance of payments need. Some lending by multilateral and bilateral agencies is also balance of payments support. In this review, balance of payments lending is defined to include IMF credits and loans. World Bank adjustment lending, and adjustment or program loans by the regional development banks (Asian Development Bank, African Development Bank, and Inter-American Development Bank). Bilateral donors, many of whom have become important providers of balance of payments support, are not covered because of lack of comprehensive data.
3A judgment on progress toward external viability might also be based on market tests such as the evolution of discounts in the secondary market price of sovereign debt; such tests are not used in this study because there are no data on these prices for most of the countries under review.
4World Bank (1997); formerly World Debt Tables.
5Some authors (for example, Cline, 1995) argue that interest costs represent the true economic cost of foreign borrowing. In a situation where principal is routinely rolled over, a case can be made for using interest payments to measure the burden of external debt service. However, an argument for a broader measure (interest plus amortization of principal) for low-income countries is their limited access to capital markets (that is, there should be no presumption that new loans will be available to “replace” amortized debt).
6The related issue of fiscal sustainability is not addressed in this chapter. While external debt sustainability focuses on the burden of external debt, fiscal sustainability encompasses all sources of financing for the government (seigniorage, domestic borrowing, and foreign borrowing).
7Ratios based on government revenues are also affected by exchange rate changes. However, to the extent that the government revenue base has a smaller “nontraded” component than GDP, the impact should be less than for the GDP-based ratios.
8One approach to overcoming distortions to relative size of economies that arise from exchange rate changes is to employ GDP series adjusted for purchasing power parity (PPP). Such series are not used to calculate debt and debt-service ratios in this study because they introduce a distortion of their own: the external transfer burden of debt service depends on prevailing exchange rates (not on PPP-adjusted rates).
9Thresholds established under the HIPC Initiative are discussed below.
10This section is based on data from the World Bank’s Debtor Reporting System (DRS). “Aggregate net resource flows” comprise net flows on long-term debt (disbursements minus repayments), official grants, net foreign direct investment, and portfolio equity flows. Borrowing from the IMF is excluded from net flows on long-term debt. For a description of terms, methodology, and sources used in the DRS, see World Bank (1997).
11All ESAF users in this review, except Bolivia, also belong to the group of “low-income” countries in the DRS. The DRS classifies Bolivia as a middle-income country.
12“Developing countries” comprise low-income and middle-income countries in the DRS. For details on the composition of these country groups, see World Bank (1997).
13Figure 7.1 is based on data for 31 of the 36 countries covered in this review. They are the 30 nontransition countries and Lao P.D.R. Five transition countries—Albania, Cambodia, Kyrgyz Republic, Mongolia, and Vietnam—do not have full data.
14The median is used to reduce upward bias from very high ratios for a few countries (for example, Mozambique and Nicaragua). The actual debt-service ratio was much lower than the scheduled debt-service ratio, fluctuating in the 23–29 percent range over the period.
15Tanzania is excluded from Figure 7.2 because of serious deficiencies in export data that could distort the calculation of sample medians over time. Nord and others (1993) have made a convincing case that official statistics severely underestimate exports during 1985–90, when the import regime was liberalized for importers with “own funds.” The authors argued that a sharp drop in reported export earnings merely reflected a diversion of export proceeds into “own funds.”
16The evolution of Paris Club rescheduling terms is described in Kuhn and others (1994) and Boote and others (1995), which also contain summaries of Paris Club operations since the mid- 1970s.
17ESAF users covered in this review that have not had Paris Club reschedulings are Albania, Bangladesh, Burundi, Kyrgyz Republic, Lao P.D.R., Lesotho, Mongolia, Nepal, Pakistan, Sri Lanka, and Zimbabwe. Restructurings for Ghana (1996) and Kenya (1994) were on nonconcessional terms.
18“Exports” generally refer to exports of goods and nonfactor services, following the dominant practice in program documents. However, a variety of other definitions are used in some documents: for example, a broader definition including workers’ remittances (where those are important), or on occasion some notion of “net” exports to highlight significant differences between the gross value of exports and the foreign exchange earnings that accrue to a country. In this chapter, workers’ remittances are included for Lesotho because of the dominance of this item in foreign exchange earnings. Reexports are excluded for Benin. The Gambia, Madagascar, and Togo.
19Lack of comprehensive data on balance of payments loans from bilateral donors was the main reason for employing the narrower definition of exceptional financing relative to that in Table 7.4. Including available data on balance of payments financing from the IMF, World Bank, and the regional development banks made little difference to country assessments.
20For the exceptional financing indicator, zero or negative positions were interpreted as signifying “improvement” regardless of the prearrangement position.
21To the extent that some donors are substituting grants (earmarked for debt relief) for direct debt relief, the exceptional financing indicator employed here may indicate greater progress for some countries than warranted.
22Formal statistical tests were undertaken to investigate differences between group averages of the changes in each of the three principal indicators (see Appendix 7.1). For the ratio of debt service to exports, there was no significant difference between the “clear progress” and “limited progress” groups, but there was significant difference between the “clear progress” and the “no progress” groups. For the ratio of debt service to GDP, there was a significant difference between the group that made “clear progress” and the “no progress” group. With respect to exceptional financing, there was a statistically significant difference between the group that made “clear progress” and each of the other two groups.
23Failure to make progress does not necessarily mean that a country faces an unsustainable debt burden. For example, Kenya (a HIPC) and Zimbabwe (a non-HIPC) have relatively moderate debt burdens.
24The only exceptions to this were Ghana and Mozambique, which reduced their reliance on exceptional financing but saw one of their debt-service ratios rise. Tanzania is excluded from Figure 7.3 for reasons given in footnote 15, above.
25To present a more representative picture of average levels of the various ratios for the groups, Mozambique is excluded from the averages used for Figure 7.3.
26Tanzania was one of the poorer-performing countries in the 1993 review. If its official export and GDP data were accepted on face value, Tanzania would be classified in this review’s “no progress” group.
27The somewhat arbitrary figure of 50 percent was derived from “threshold” ratios of 10 percent for debt service to GDP, and 20 percent for government revenue to GDP.
28The more diversified exports are, the less likely it is that adverse developments in one item will cause large swings in total export earnings. Holdings of international reserves provide some indication of the capacity to withstand temporary adverse shocks. Two measures of export variability are presented: one, the coefficient of variation, compares the extent of variability during 1991-95 with that of a decade earlier (1981-85); the second, variability around a linear trend, is intended to take account of trend growth in export earnings, which the coefficient of variation may misrepresent as increased variability.
29To address concerns about the fiscal burden of debt in very open economies, the guidelines for implementation of the HIPC Initiative allow exceptionally for an NPV of debt-to-exports threshold below 200 percent for HIPCs that are both open (that is, with an exports-to-GDP ratio of at least 40 percent) and making a sufficient effort to generate revenues (that is, with a fiscal revenue-to-GDP ratio of at least 20 percent).
30This favorable outlook reflects, in part, the expected impact of a significant improvement in the composition of external debt. Over the next five years, Kenya is expected to replace most of its nonconcessional public external debt with loans on concessional terms.
31This influence can work through changes in interest rates or in maturities on concessional borrowing.
32There is an important distinction between debt write-offs and even highly concessional debt rescheduling. If accounts are correctly recorded, scheduled debt service is unaffected by rescheduling—concessional or otherwise. In contrast, a debt write-off reduces current and future amortization and interest payments. Because of data constraints, the impact of debt write-offs is not explicitly considered here.
33The concessional dement is measured as the difference between nominal and NPV debt. The difference between the “clear” and “limited progress” groups was not statistically significant.
34In contrast to the previous section, where the “pre-SAF/ESAF” and “latest” periods were defined as three-year averages to smooth year-to-year fluctuations in debt-service ratios, this section looks at changes from the immediate pre-SAF/ESAF year to 1995. Here, the intent is to explain the change in the stock of debt relative to exports since countries embarked on their first SAF/ESAF program.
35For these intergroup comparisons, Lesotho is excluded from the “clear progress” group because large flows of official transfers (from the Southern Africa Customs Union) permitted unusually large current account deficits.
36The “limited progress” group, on average, also experienced more adverse terms of trade developments than the other groups.
37Data limitations dictated a split in the domestic sectors into “government” (rather than “public”) and “nongovernment” in the sectoral saving-investment balances in Table 7.15, differences between the “clear” and “no progress” groups were not statistically significant.
38This positive association between fiscal adjustment and progress toward external viability is consistent with Brooks and others (1998). Their study of the experiences often HIPCs since the 1970s concluded that lack of sustained adjustment policies, particularly in the face of exogenous shocks, contributed to the increase in external debt burdens. Countries with the least diversified export bases (including Uganda and Niger) were found to be the hardest hit by adverse terms of trade shocks.
39Killick (1995) examined the role of import squeezes in current account improvements under IMF-supported programs and concluded that fears that the programs would lead to sustained import strangulation were not justified.
40Brooks and others (1998) found that optimistic forecasts regarding export prospects in the 1970s and early 1980s were partly responsible for heavy borrowing by some HIPCs (for example, Niger and Zambia). The 1993 ESAF review (Schadler and others, 1993) also concluded that there was a tendency to overpredict export values, resulting in downward revisions in program targets and outcomes below targets.
41It was not always possible to reconstruct the precise ratios reported in program documents because of data limitations (see footnotes to Table 7.17). However, focusing on the trends should provide a reasonable indication of divergences between projections and outturns.
42For most of the period under review, concessionality for establishing debt limits was based on the DAC definition—a grant element of at least 25 percent, using a uniform discount rate of 10 percent. Under current IMF guidelines, concessional loans are those with a minimum grant element of 35 percent, using a discount rate based on the commercial interest reference rate (CIRR), published by the OECD, for the currency in which the loan is denominated.
43The list of program interruptions in Chapter 9 was the starting point for this exercise. However, the subsample to be examined here was reduced to programs with interruptions that lasted at least a year, on the assumption that shorter interruptions would probably not allow time for a significant buildup of debt.
44It is possible that exclusion of interest capitalization from new borrowing may temper this conclusion. It was not possible to pursue this in this study because of insufficient data.

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