Policy, Planning, and Research WORKING PAPERS Macroeconomic Adjustment and Growth 1 Country Economics Department The World Bank July 1989 WPS 235 Borrowing, Resource Transfers, and External Shocks to Developing Countries Historical and Counterfactual Steven B. Webb and Heidi S. Zia The 16 highly indebted countries received about half the net transfers to developing countries from official and commercial lenders in 1978-82 - and accounted for all the resource flows back to creditors in 1983-86. The Policy, Planning, and Research Complex disuibutes PPR Wodtung Papers to disseminate the findings of work in progress and to enoourage the exchange of ideas among Bank staff and al others interested in development issues. These papers carry the names of the authors, reflect only their views, and should be used and cited accordingly. The findings. intcrpreutions, and conclusions are the authors'own They should not be attributed to the World Bank, its Board of Directors, its management, or any of its member countries. Pollc,Pnnlng, and Research Mcoonomlc Adjustment and Growth If develop;ng countries follow the same paths years of high rep ,ductive rates reaches adult- industrialized countries have followed, saving hood, the proportion of working-age population for retirement will initially become more impor- rises sharply. Then, as baby boomers retire and tant Ps the population growth rate declines. die off, it declines toward the steady-state level. To calculate the potential importance of life- Webb and Zia simulated aggregate rates for cycle saving (saving for retirement), Webb and life-cycle savings for Brazil, China, Korea, Zia set up a simulation model that translates Mexico, Nigeria, Pakistan, and Turkey. demographic projections into savings-rate projections. Modeling explicitly the behavior of The savings rates increase ' *r 6 percentage each cohort of households separates the effects points when the last baby boomers enter the of changing population shares of children and work force and begin to save after their children retirees. These shares behave differently and leave home. The effect on life-cycle saving is have different effects on saving as the popula- dramatic; the effect on total savings rates, which tion growth rate changes. are often three or four times as high, is not. Baseline World Bank population projections Simulated life-cycle savings rates peak at an assume that by the middle of the twenty-first absolute 10 percent or less in all cases. The century, if not sooner, the net reproductive rate pattems in these projections seem robust with of women in every country will decline to 1.0, a regard to assumptions about productivity level that will cventually lead to a stable popula- growth, interest rates, and age-specific participa- tion. As the last cohort of those bom in the tion in the labor forcc. This paper is a product of the Macroeconomic Adjustment and Growth Division, Country Economics Department. Copies are avaiiable free from the World Bank, 1818 H Street NW, Washington DC 20433. Please contact Emily Khine, room N 1 1- 067, extension 61765 (27 pages with chains and tables) The PPR Working Paper Series disseminates the findings of work under way in the Bank's Policy, Planning, and Research I Complex. An objective of the series is to get these findings out quickly, even if presentations are less than fully polished. | I The findings, interpretations, and conclusions in these papers do not necessarily represent official policy of the Bank. Produced at the PPR Dissemination Center TABLE OF CONTENTS I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 II. The Growth of Debt and Net Transfers of Resources: . . . . . . . . 3 III. Resource Transfers And Investment ... . . . . . . . . . . . . . . 8 IV. Capital Flight .... . . . . . . . . . . . . . . . . . . . . . . 10 V. Credit Availability .... . . . . . . . . . . . . . . . . . . . 12 VI. Trade Flows .... . . . . . . . . . . . . . . . . . . . . . . . . 15 V. Counterfactual Stimulation ... . . . . . . . . . . . . . . . . . 16 Interest Rate Shocks .1.9.. . . . . . . . . . . . . . . . . . . 19 Terms of Trade Shocks .... . . . . . . . . . . . . . . . . . . 22 VII. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 LEFERENCES We have benefited from comments by Bela Balassa, Vittorio Corbo, Jaime de Melo, John Holsen, Fred Jaspersen, Miguel Kiguel, Ed Somensatto, John Underwood, and other colleagues in CECMG. Of course, any errors that remain are our own r& -ponsibility. I. Introduction International lending has been a double-bladed axe that cut both ways for economies struggling to develop. When borrowed resources came in, they allowed countries to increase investment without as much reduction of current consumption or simpl, to consume more. But the loans complicated the development process when they had to be repaid, especially if the resources were, by bad luck or bad policy, not invested in ways that provided the means for repayment. This paper gathers some statistical evidence on the magnitude of lending and repayment and on the question of whether the repayment reduced the resources available in the 1980s for development. The evidence largely confirms commonly held beliefs, but the discussion emphasizes what seems new or controversial. Nine findings stand outs 1. Looking only at long-term, public and publicly guaranteed debt understates the volume of commercial lending to the developing countries before 1982 and the size of net transfers out to commercial creditors since 1982. 2 2. For many countries the stocks of short-term debt or long- term non- guaranteed debt built up rapidly before 1982 and declined sharply since then, when those types of debt were rescheduled and reclassified as long-term publicly guaranteed. 3. Most debtor countries have transferred net resources to commercial creditors since 1980, but on average the (middle-income) countries that have not had to reschedule their loans have made much smaller net transfers to creditors than the tountries that have rescheduled. 4. Neither the abs3lute size of a country's debt nor the amount of World Bank adjustment lending has had a discernable positive effect on the net transfers of commercial credit to the countries; indeed, the correlation is weakly negative. 5. There is a significant negative correlation between the change in the resource balance and the change in dome'tic investment from the five years before 1982 to the four years thereafter. 6. The cost of paying unusually high real interest rates in the 1980s usually explains less than a fifth of the debt that countries have built up. 7. Terms of trade changes since 1978 (assuming the real trade flows that actually occurred) generally had dramatic effects on the incomes of developing countries. For most manufacturing exporters and mae, non-energy primary exporters, the effects of terms-of-trade shocks, accumulating with interest from 1979 to 1986, reduced net worth by half or more of a year's GDP. 8. The terms-of-trade effects increased the potential net worth of oil exporters by even larger amounts, however, although most of them did not take the opportunity to pay off their debt and acquire net assets in the rest of the world. 3 9. There is not a close correlation between the extent that a country was hurt by terms-of-trade changes and the extent to which it is today considered a problem debtor. II. The Growth of Debt and Net Transfers of Resources: External borrowing and repayment are the dominant items in the capital accounts of most developing countries. Table 1 shows a statistical survey of the debt buildup in the 70 countries that are included in the Report on Adjustment Lending 1 (RAL1) statistical appendix. (These include all the important developing coumtries except China and India.) The years 1978, 1982, and 1986 were chosen to indicate the debt situation after the first oil shock, after the second oil shock (and at the outbreak of the debt crisis), and after 4 years of attempted adjustment to the debt crisis. From 1978 to 1982 the debt expanded rapidly, almost doubling in nominal terms and growing about 30 percent in real terms. After 1982 the growth slowed, in both nominal and real terms. In the distribution of debt between categories of borrowers, the main changes were that the share of debt owed by Latin American Countries (LAC) and the Highly Indebted Countri4es (HICs) increased between 1978 and 1982, and then by 1986 it drorped back what it had been in 1978. Europe, Middle-East, and North Africa's (EMENA) share in the debt owed has dropped over the eight years; Asia's has risen. Changes in the distribution of debt to commercial and official creditors reflect developments in the political economy of debt. From 1978 to 1982 the middle-income countries, especially the highly indebted countries (HICs), increased their share in the commercial credit to developing countries, but. not in official credit. With credit readily obtainable from 4 commercial sources, some countries did not want to put up with the conditionality of official creditors, even if it could get them loans on slightly more favorable terms. In some countries, the private sector did most of the external borrowing, without explicit government guarantees. From 1982 to 1986, total debt to commercial lenders (from the RALl 70) remained essentially constant in real terms. (Table 1 shcws debt deflated with manufacturing unit value index of developed countries.) After 1982 the share of commercial credit to the HICs fell, but this was partially offset by an increase in their share of the credit from official sources. The low-income countries, which had not borrowed heavily from commercial creditors, suffered a decline in their shares of both official and commercial credit. Commercial credit includes public and publicly guaranteed (PPG) long- term commercial credit, and also short-term and non-guaranteed long-term credit, which was mostly from commercial creditors to private borrowers. Some of the debt that started out as short-term or non-guaranteed (PNG) long-term debt had by 1986 been reclassified as long- term PPG debt in the reschedulings. The oanks found that, because they had not made sure that short-term loans were put to self-liquidating uses, they had to recognize them as long-term obligations, at best. The developing countries found that, when foreign-exchange controls prevented private debtors from servicing non- guaranteed debt, the foreign creditors effectively pressured the debtor governments to assume the debt. In many cases this was the price for keeping open the nation's lines of trade credit. Since a substantial part of the long-term PPG debt in 1986 was originally lent as short-term and private non- guaranteed debt, it seems best to lump all three categories together from the start. 5 Table 1 also shows the debt burdens as a percent of GNP and of exports (Table lb). During the 1978-82 period, the total debt burdens became more similar across categories. Since 1982, however, the burdens have become more different, mainly because of diffi:ent growth experiences. For manufacturing expotters and EMENA countries, debt burdens have increased only moderately since 1982. Manufacturing prices have held up relatively well and volumes have grown. For HICs, for oil and non-oil primary exporters, and for Sub-Saharan Africa, debt burdens have grown much faster than the ability to pay. Many countries devalued their currency in real terms, as part of the adjustment process, which increased their debt/GDP ratio. Net transfers between creditors and debtors offer another perspective on the evolution of the debt problem and countries' efforts to adjust. Calculating net resource transfers from debt data yields a picture of where resources are going to and coming from externally. Net transfers from creditors would differ from the (negative) resource balance by items such as increased reserves, direct foreign investments, and unrequited transfers.1 Resource balances are considered separately later. Net transfers from a creditor would be disbursements minus repayments minus interest paid by the debtor. The estimates of net transfers in the following charts and tables are calculated from the World Debt Tables. The net transfers on commercial long- term debt (PPG and PNG) just sum the estimates of net transfers in the Debt Tables. For total commercial transfers we could not use this method, because there are no data on the net transfers for short-term debt and only incomplete 1 The resources balance equals exports minus imports of goods and non- factor services. It is about the same as the non-interest current account, if interest payments are the bulk of factor services. 6 data on the amount of short-term debt that was rescheduled or reclassified into long-term. To cover the reclassification problem, we calculate total net transfers from commercial creditors as the change in the total debt (stock of short-term plus long-term (PPG and PNG] debt) minus the interest rate (average rate of commercial long-term PPG) times the average total debt during the year. This method also has some problems, because the change of debt also reflects debt forgiveness, discounts on equity and local-currency swaps, and exchange-rate changes, none of which should count as net transfers. Exchange- rate changes are important for some years, but have tended to cancel each other out over the longer periods.2 Debt swaps have been significant for only a few countries and only very recently. It seems more important to capture the negative transfers on short-term debt, as trade credit lines have shrunk. Total official transfers are t.ie reported transfers on official long-term debt plus an estimate of IMF net transfers -- disbursements minus principal repayments minus an interest rate (average official long-term) times average IMF during the year.3 Official transfers refer to loans only and thus do not include official grants. Total net transfers are the sum of total commercial 2 When the dollar was rising, in 1980-84, debt increases understate net flows. When the dollar fell, since early 1985, debt increases overstated net flows. The period 1978-82 straddles a trough in the dollar values; 1983-86 straddles a hump. Of course, exchange rate changes did not fully cancel out; the yen was much higher in 1986 than in 1978. 3 The IMP has its own terminology, in which disbursement of credit is called a "purchase,' and repayment is a "repurchase." 7 and official net transfers.4 Table 2 shows the results of these calculations, subdivided by period, by debtor-country group, and by type of creditor. From all creditors, the net transfers to all borrowers were strongly positive in 1978-82. In the context of OPEC oil shocks, "Debt was considered a solution rather than a problem."5 With two exceptions, net transfers from every category of creditor to every category of debtor declined sharply after 1982. To low-income countries total net transfers via lending remained positive, but declined by over one-half. To Sub-Saharan Africa net transfers via lending remained barely positive, but one must remember that official grants were important there. For the other categories of middle-income countries the total net transfers became negative, especially for the HICs and Latin-America, which overlap considerably.6 Counting short-term and non- guaranteed debt as part of total debt to commercial creditors makes the net transfers to them from middle-income countries more negative than only counting long-term public debt. As shares of GNP, transfers to commercial creditors in 1983-86 averaged almost 4Z of GNP for upper-middle income countries and HIC's, but were lower for manufacturing exporters and lower- middle-income countries. From official creditors, resource transfers before 1983 were much smaller than from commercial creditors, except to low-income countries. Since 4 If the loan were reclassified from commercial to official (e.g., because of exercising an Export-Import Bank guarantee) this transaction is counted (incorrectly) as a negat'ive transfer. 5 Fishlow, 1988, p. 202. 6 See also Husain, 1988. 8 1983 resource transfers from officia: creditors have remained positive, but to every category they have fallen, except to the HIC's and Latin America, which have received more. Partly the overall decline reflects the interest burden, and for some manufacturing exporters it may reflect a positive decision to borrow less when even official loans were becoming more expeneive in real terms. The decision to increase net transfers to Latin America probably reflects political decisions by creditor governments to use official lending to avert a breakdown of relations with commercial creditors. Note that the net transfers from official creditors to middle-income debtors are far less than what commercial creditors took out. So there has been no global bail out. It was probably more common that the carrot of official lending, small as it was relative to total debt of HICs, helped keep debtors at the negotiating table with commercial creditors, who succeeded there in getting large net resource transfers. III. Resource Transfers and Investment Since 1980 most developing countries have had negative net resource transfers along with lower investment rates, and slower or negative output growth. Some observers argue that the primary chain of causal connections has run from debt crisis to negative transfers to curtailed investment to stagnant output (Sachs, 1986; Husain, 1988). Feedback loops only made matters worse. Did a more positive resource balance (corr-ponding to more negative transfer to creditors) lead to lower investment? The simple cross-sectional correlation between the share of GDP going to investment and the share going to resource balance has the predicted 9 negative sign but is too weak to be significant.7 Perhaps this is because of differences between the structure of economies and the ways of defining the statistics. To hold tz. se constant, we compared the changes in investment share and resource- balance share from the 1979-82 period to the 1983-86 period. Figure 1 shows the results. The points are scattered around a line through the origin with a slope of negative 1.0. The one-to-one average correspondence of changes in resource transfers and investment is consistent with causality in either direction. Diminishing investment opportunities -- perhaps due to the interest rate and terms of trade shocks discussed later and the recessions accompanying the initial phases of adjustment -- would lower desired investment and at the same time reduce the resource transfers that financed it. For countries, however, the change in the financing flow exceeded or preceded the change in investment fundamentals, and it appears that credit constraints caused the reduced investment, especially in infrastructure and social investment. Changes in saving can also be deduced from Figure 1. If a country lies on the line through the origin wich slope of -1.0, then its saving rate did not change. Countries below the line decreased saving by the vertical or horizontal distance from the line. For instance, Argentina reduced investment by 9 per cent of GNP but increased resource transfers by only 4 percent, implying that the share of consumption (although not the absolute value) rose by 5 percent of GNP. Korea, on the other hand, increased resource transfers by 7 percent of GNP, but took only 1 percent out of investment, implying that the other 6 percent came through more saving. 7 The relationship was examined for the averages of 1979-1982 and 1983-86. 10 IV. Capital Flight The capital account is more than just borrowing and repaying external debt. For instance, in 1980 developing countries ran a capital account surplus of only about $68 billion, while their outstanding debt rose by $96 billion. In 1984, debt rose by about $69 billion, while the capital account surplus was only $14 billion.8 The net inflow of direct investment, which would make the capital account more positive, was more than offset by accumulation of official reserves and, more importantly, by private purchases of assets in industrial countries, including capital flight. Since evasion of taxes, unsustainable appreciation of the domestic currency, and exchange controls often motivate capital flight, statistics are sparse and uncertain. But the magnitudes are not trivial. Table 3 shows estimates of capital flight by two authors.9 Argentina, Mexico, and Venezuela account for most of the capital flight from the countries investigated. For those three, capital flight accounted for one-third to two-thirds of their total debt in 1984. For most countries capital flight has at least slowed since 1984, so its share in the total debt has probably not risen much since then. Most of the capital flight occurred when governments could easily borrow foreign exchange to sustain overvalued domestic currencies. More recent capital flight, for instance from Brazil, has mostly had to go through 8 World Bank Debt Tables 1987-88; IMF, IFS. Saudi Arabia, Kuwait, Middle East unspecified, and South Africa were subtracted from the IFS capital account total for developing countries, because the Debt Tables do not include them. 9 The two estimation methods in Khan and Haqu^ 1987 give similar results. 11 the more arduous route of actual (if not fully reported) export surpluses. For the evolution of its debt burden, it makes little difference in the short- run whether their citizens used the foreign exchange to import consumption goods or to buy undeclared foreign assets -- capital flight. In either case the borrowed resources do not generate productive assets to help service the debt. But in the longer-term there is a big difference. If the investment climate improves at home, holders of flight capital can liquidate their foreign assets with interest and bring home the funds for domestic investment.10 Of course, the key caveat is, if the investment climate improves at home. Table 2 also shows the resource balance as a share of GNP for the various categories of countries. The difference, noted earlier, between net transfers from creditors and the negative resource balance of the developing country parallels the distinction between the increase of debt and the negative current account balance (plus reserve changes). For lower-income countries grants may account for much of the difference between net transfers to creditors and the resource balance. For middle-income countries, there is a discrepancy before 1982, which could reflect capital flight, but little difference since then. 10 If domestic investment in a market with serious distortion were the alternative use of funds that went to capital flight, then the country might be better off in the long run if funds were invested abroad in higher-yield projects. But capital flight is pernicious to the extent that its benefits only go to a privileged few and that it increases the need of governments to borrow abroad and reduces the tax base. 12 V. Credit Availability The amount of its scheduled debt service that a country pays with current earnings, rather than finances, depends on the relationship of the debtor country with its commercial banks and official creditors. Let us consider three factors that might influence net resource flows from commercial creditors: past payment record, the threat of default, and World Bank adjustment loans. When a country runs out of ftmds to meet its debt obligations, it typically goes through a rescheduling with its creditors, and then its future borrowing is tightly constrained. Figures 2A and B compare net transfers before and after 1982 for middle-income countries that did and did not go into arrears or require repeated reschedulings in the 1980s. (Appendix I lists the countries in each category.) From commercial creditors the countries that eventually rescheduled got higher net transfers before 1982 but have had much more negative transfers since then. Much of the theoretical analysis of sovereign debtors assumes that they are motivated to pay anything only by the prospects for positive (present value) net transfers in the future, but this could hardly explain the facts at hand (see Eaton, Stiglitz and Gersowitz, 1986 for a survey). No creditors are considering making future positive net transfers large enough to outweigh the negative net transfers of the mid 1980s. Some other motive must be dominant, perhaps the fear of trade reprisals or the high convenience value of access to trade credit and use of international banking services. From official creditors in 1978-82, the problem debtors-to-be were receiving lower net transfers. This is consistent with the hypothesis mentioned earlier that HICs preferred to borrow in the commercial market where they did not have to worry about the policy 13 conditionality required by official lenders. Since 1983 creditworthy and problem debtors (middle-income) have shared about equally in the net transfers from official creditors. Another approach to net transfers to commercial creditors is to ask why some credit-constrained debtors get away with weaker efforts to repay than others. One theory takes off from Keynes's observation that a debtor owning a hundred pounds is at the mercy of its creditors, while a debtor owing a million pounds has the creditors at its mercy. Sachs and Huizinga claim that big debtors, whose debt is an important share in banks' portfolios, have used the threat of default to get more generous reschedulings than smaller debtors could obtain (1987). Figure 3 shows a more complex picture. Among the middle income debtors owing less than $50 billion, a larger absolute debt (in 1982) correlates negatively with net transfers from commercial creditorG as a share of GNP, which would suggest less generous reschedulings. Excluding Brazil and Medico the correlation coefficient is negative 0.34 (and is statistically significant at 52 significance level). Maybe for mid-size debtors the banks will put forth more effort to collect than for small debtors. For the two biggest debtors, Mexico and Brazil, there does seem to be some truth to Sach's claim, because their net transfers are less negative than the mid-size debtors. Mexico and Brazil also have, however, prospects for long-term growth that are better than most developing countries; so more generous lending might be economically justified (Webb 1987). Policy-based lending by the World Bank is supposed to have synergistic effects in encouraging more lending by other creditors. There are many reasons why one would not expect more adjustment lending by the Bank to correlate one-to-one with larger net transfers from other creditors. Still, 14 some positive correlation would help vindicate the argument that adjustment lending serves to attract commercial credit. Such a correlation does not show, however, in Figures 4A, B, C, D and E. Indeed, the average net transfers from creditors (not counting Adjustment Lending) to countries getting structural adjustment loans (SALs) and sectoral adjustment loans (SECALs) was less than the average transfers to countries not getting any SALs. For middle-income countries the negative relation between net transfers and having a SAL was stronger for commercial creditors than for official. Surprisingly, the negative relation between net transfers and having a SAL or SECAL was stronger for IDA countries than for Bank borrowers. Presumably there are some selection biases here. Countries which cannot get positive net flows from other creditors turn to the Bank and IDA for SALs. Countries with higher external debt and thus higher scheduled negative resource transfers may be more likely to get adjustment lending. Among countries which (needed and) got SALs, there is no clear positive or negative relationship between the amount of SAL (and SECAL) lending and transfers from the aggregate of other creditors. For official creditors there is a positive relation with a correlation coefficient of .44. With net transfers from commercial creditors to middle-income countries, however, the Bank's adjustment lending seems weakly negatively correlated (with a correlation coefficient of -.15). Overall, if the SALs and SECALs have any synergistic effects in making the recipients attractive targets for other lenders, those effects were too subtle to show up in these charts (see correlation coefficients at bottom of charts). Perhaps one needs more time to see the effects of adjustment policy. 15 VI. Trade Flows The real values of exports and imports, shown as indices in Tables 4A, B and C, indicate the extent and mode of capital flows and real adjustment.* For every aggregation in Table 4A (except India), real exports increased relative to the volume of imports in the 1980s; in most cases the imports fall while exports rose. For HICs, real exports rose by almost one fifth, and 4'ports fell by one fifth. Major countries that raised real export by well over one-half from 1980 to 1986 -- Turkey, Korea, Pakistan, Thailand, Malaysia -- have not had severe debt-servicing difficulties, and have maintained voluntary access to commercial credit. Mexico, the Philippines, and Brazil became HICs, however, despite export growth in the 15 and 40 percent range. Some commodity and oil exporters nad slow growing exports, like Argentina and Cote d'Ivoire, or even saw exports decline, like Indonesia, Jamaica, Nigeria, and Zambia. The countries that maintained strong export growth and avoided debt servicing difficulties have sustained real growth of imports, shown in Table 4C. All the HICs, on the other hand, have reduced real imports. Argentina, Nigeria and Zambia have cut them by over one-half. A study comparing the HICs and 10 major non-HICs found that, while the two groups had nearly identical statistical profiles in 1980-82, the non- HICs had distinguished themselves with much more rapid export growth since the * The real values are calculated as the nominal flows divided by the MUV, which is the World Bank's index of Manufactures Unit Value -- the dollar unit value of G-5 exports of manufactures to developing countries. 16 debt crisis started in 1982. The rapid export growth seems to explain the continued access on the non-HICs to commercial bank credit although a few countries, like Korea, have reduced their total debt. The debt and imports of the non-HICs continued to grow rapidly. (Corbo, 1989.) V. Counterfactual Stimulation Rapid build-up of external debt often signals a country's need for structural adjustment. But to evaluate the success of adjustment and adjustment lending, one cannot look merely at the absolute level of a country's debt or even its ratio to GNP or exports. Since the onset of the debt crisis in 1982 every debtor country has become more indebted, even though they have taken adjustment measures, with varying degrees of success. High real interest rates and adverse movements of the terms of trade account for some of the increase in debt of the developing countries, but these effects vary widely. To estimate the effects of changing real interest rates and terms of trade, one must have some idea of what would have happened without those changes. This section reports the results of counterfactual simulations of the change in country's net worth with the same real trade flows but alternate, historically more "normal" patterns of prices and interest rates on commercial debt. The counterfactuals take into account the compounding of interest on extra borrowing to pay higher interest or finance the losses due to terms-of-trade shifts. The counterfactuals should not be viewed as general equilibrium forecasts of what would have happened with a different path of prices and interest rates.11 Rather, they highlight the nominal effects of 11 See Corbo and de Melo 1987 for such an exercise. 17 price changes (regarding the interest rateralso as a price) while holding the underlying real quantities constant. To compare the cumulative impact of changes in real interest rates and terms of trade over the years 1979-86, we would like to have something like the present value of total lost and gained consumption opportunities. This should be the present value of changes made in current consumption plus the changes in net worth, assets usable for future consumption. To approximate this result, the calculation focuses on net worth, with no change assumed in consumption. The effects of external conditions were treated as changes in debt service paid to commercial creditors, which affected with compounding interest the country's net worth. The calculations assume, in other words, that real trade flows did not react to interest-rate and terms- of-trade changes and therefore that the entire shock was financed externally. Real trade flows did change in response to shocks, of course, which means that there was also some domestic adjustment. We do not model that, but we can tell how it affects our interpretation of results. If investment did all the domestic adjustment -- say, by reduced imports of machinery to compensate for the loss of coffee revenues -- and if the foregone domestic investment would have returned the world interest rate, then we can still say that the external shock altered net worth one-for-one. Evidence in Figure 1 supports the interpretation that the domestic side of adjustment fell predominantly on investment. For the part of domestic adjustment made by changing consumption, we can say that calculating the impact on net worth is equivalent to accumulating the value of foregone consumption, using the world interest rate as the consumers' discount rate. In other words, the net worth changes in the 18 counter factual calculation can be interpreted as the accumulation of the combined changes in foreign debt, domestic capital stock, and consumption. Of course, the composition of the response varied from country to country, and there are some systematic patterns. Commercial long-term (PPG and PNG) and short-term debt are all assumed to carry the same interest rate as was actually paid on long-term PPG debt. For other private debt there are no data on the interest paid. If commercial debt becomes negative in the counterfactual -- the country becomes a creditor with the private financial sector -- the interest rate earned is assumed to be LIBOR. The counterfactuals assume that financing from official sources occurred independently from the debtor's situation vis a vis commercial creditors. Although some debtors received extra official loans to help with commercial debt problems, as suggested earlier, and obviously the amount of new commercial financing depended on the pre-existing stock of debt, these relationships were complex and varied widely across countries. The counterfactual estimates are built up in several simple steps. The actual debt at the end of period t equals the debt at the end of period t-l, plus interest on that debt, minus the resource balance in period t, plus net borrowing for purposes other than financing interest payments on imports. (The last item would cover direct investment, reserve changes, and capital flight. In the World Debt Tables, it also includes exchange-rate effects.) Debtt = Debtt_l + Debtt_1* rt_l - Res Balt + Other Net Borrowingt (1) 19 The counterfactuals simulate the build-up of debt with alternate assumptions about the interest rate r and trade prices, which result in a counterfaetual resource balance. CF Debtt - CF Debtt_l *(l + CF rt) - CF Res Balt + Other Net Borrowingt (2) Since we want to use the actual Other Net Borrowing in the counterfactual, that is obtained by solving for it in equation (1) and plugging the result into equation (2). The results of the counterfactual are measured as a gain in net worth -- as the difference between the simulation of debt with the counterfactual and the simulation of debt with the actual long-term interest rate and actual resource balance. The simulated actual debt was usually very close to the actual, but the comparison of simulations seemed the most accurate way to measure the effects of the counterfactual assumptions and to exclude the effects of the method of simulation. Interest Rate Shocks On interest rates, the counterfactual we are trying to evaluate is that the real rates in international markets stayed around their historic average. Table 5 shows the recent history of world interest rates and inflation. The double-digit nominal interest rates, which were showing inflation in the US, were causing the prices of internationally traded goods to drop, even for industrial countries. This pushed real interest rates up to almost 20 percent. Some developing countries were paying even more. Of course, this was far above historic norms. For 1963-86, LIBOR minus the inflation of the MUV index averaged 2.5 percent per annum. Spreads and fees would make the effective rate to developing-country borrowers somewhat higher. 20 The counterfactual interest-rate calculation assumes that the real interest rate stayed at 4 percent, and thus that the nominal rate equalled inflation of the MUV plus 4 percent. Varying the counterfactual real rate up or down by a point does not make a dramatic difference. Pour percent is above the ex post real rate that prevailed during the debt build-up, prior to 1982, but we want to highlight what the exceptionally high structure of real rates in the 1980s contributed to the debt build-up for developing countries. We want to avoid the criticism that the results are driven by an assumption that commercial banks would give away money at below-market rates in the counterfactual. Assuming a 4 percent real interest rate since 1978 would rais'a the net worth of most countries by 1986, compared with actual rates. (A few countries would have been worse off in the counterfactual, because they actually did not pay much of the intetest owed.) As one would expect, the countries and regions that relied most on commercial financing were hardest hit by interest rate shocks. Tables 6A, B and C show results by region and country. The 4 percent real rate on commercial credit would have made most countries worse off in the late 1970s but would have helped them in the 1980s. This result is sensitive to the price numeraire. In earlier calculations with the US GNP deflator, which only slowed its inflation rate, the net worth gains in the interest rate counterfactuals were less over the whole period. With the US GDP deflator, usually more gain showed up in the terms of trade counterfactual. On the other hand, with the industrial-country trade prices as numeraire, more gains showed up with the interest rate counterfactual and 21 less in the terms of trade counterfactual.12 This happened because the industrial trade prices dropped sharply in the early 1980s, pushing actual real rates to 20 percent or more. Another counterfactual scenario, in which all countries who paid their interest do better, starts with the actual debt at the end of 1980 and assumes the constant 4 percent re.l rate from 1981 through 1986. We can think of this as the soft-landing counterfactual -- Paul Volcker stops inflation but restarts money growth in time to keep real interest rates from going up high as they did. The right-hand parts of Tables 6A, B and C show that by 1986 the accumulated impact high interest rates since 1980 had lowered net worth of HICs and LAC countries by about 152. For other groups the impact was smaller. We can also evaluate this gain by asking how much lower would their debt be if countries had not borrowed to pay higher interest rates associated with the hard landing. Venezuela, Ecuador, Yugoslavia, and Mexico were hardest hit; real rates above 42 in the 1980s accounted to over 30 percent of their debt by 1986. Other major Latin debtors would have had 20-30 percent less debt with the soft landing. Anecdotal evidence suggests that if real interest rates had not sunk so abnormally low in the late seventies countries would nit have borrowed as heavily, but modelling prudence in primary borrowing as a function of the current real interest rate lies beyond the scope of the paper. It might be difficult to construct a plausible model of rational decision making that would replicate the borrowing patterns of the 1970s and early 1980s. 12 These trade prices are the average of the dollar unit value of exports and dollar unit value of imports for industrial countries, as reported in the IMF, IFS. 22 Figures 5A, B, C, and D show the change of investment and resource balance (1983-86 compared to 1979-82) compared with the networth gain in the interest-rate counterfactual (plus means real interest rates in 1979-86 were higher than 1969-78). As the correlation coefficients at the bottom of the charts show, there are no significant correlations for middle or low-income countries. Terms of Trade Shocks Table 7 shows terms of trade relative to the base period 1969-78, which is 1.00. The typical manufacturing exportex started with terms of trade in 1978 at or below the average of the previous decade; terms of trade then worsened, because of oil price movement, with some recovery in 1985-86.13 Most oil exporters had a reciprocal and more dramatic experience, with terms of trade peaking in 1980-82, then falling.14 Primary exporters (all others) had a mixed experience with terms of trade since 1978, which was generally more negative than positive. The second set of counterfactual scenarios focuses on the impact of changes in the debtor country's terms of trade. The counterfactual scenario assumes that the country's export and import prices moved with the MUV (manufactured unit value) index, at the same ratio as in 1969-78, but that the volume of exports and imports followed their actual paths. Thus the counterfactual trade flows incorporate the effects on real trade flows of the 13 Tunisia is an exception, because it also exports oil. 14 Egypt and especially Cameroon had the misfortune to get their exports of oil booming when its price was coming down. 23 changes in incomes, real exchange rates, trade taxes and subsidies, and other policies that actually occurred. The formulas for the counterfactual values (in current dollars) of exports of goods and non-factor services are: Exportst (lcu) CF Exports t (S) pexports, (lcu)* e t 1980 1978 pexports (lcu) * 1 E i *MUV 10 i-1969 M4Vi *ei t where e is the exchange rate. LCU means local currency unit. The first term is the real value of exports in 1980 dollars. The second term is the average price of exports relative to the unit-value index of manufactured imports.15 The product of the first two terms is the counterfactual value of exports in 1980 dollars, discussed earlier and shown in Table 4b. The final term reflates the value up to current dollars, which is necessary to make it comparable with debt data. Counterfactual imports are calculated in the same way. The improvement in the resource balance (exports minus imports of goods and non-factor services) that would have taken place each year if 1969-1978 terms of trade had continued is presented in Tables 8A and B. It is the resource balance in the counterfactual scenario minus the actual resource balance. A positive CF Gain shows how much greater country's resource balance would have been if 1969-1978 relative prices had continued, and therefore how much its balance worsened as a result of the terms-of-trade changes that 15 The 1980 exchange rate appears again in order to index the exchange rate to 1980, like the other prices in the summation. 24 actually occurred. A negative CF Gain means that the country (typically an oil exporter) would have had a lower or more negative resource balance with 1969-1978 relative prices and that it benefited from the terms-of-trade that actually prevailed. The CF Networth Gains in Tables 9A, and 9B are positive for majority of the developing countries, which were hurt by the second oil shock in 1979 and have only in the late 1980s faced terms of trade again that are as favorable as in the decade leading up to 1978. Many countries gained, however, from the post 1978 terms of trade. Indeed, the total of their gains was larger than the losses by the majority. Clearly, the export composition is decisive. The decline in non-oil primary product prices importantly contributed to the deterioration of the terms of trade of many developing countries. Copper exporters especially suffered from terms-of-trade changes, relative to the counterfactual, and oil exporters especially benefitted. Table 9B shows the counterfactual gains of individual countries, grouped by export category. Chile, Brazil, Jamaica, Kenya, Malawi, Madagascar, Philippines, Zaire and Zambia -- countries with problematic levels of debt -- would have had net worth higher by 25 percent or more of GNP (1986) if the 1969-1978 terms of trade had continued. In all these countries, except Zaire and Jamaica, the investment shares declined from 1979-82 to 1983-86 by at least 4 percent of GNP and as much as 12 percent. (See Figure 1.) Resource transfers to foreigners rose about the same amount as investment declined. In other words, there was substantial domestic adjustment in these countries, and most of it took place on the investment side. Consumption stagnated or declined only proportionally with GNP. 25 In other countries that have not become ptoblem debtors -- Korea, Hungary, Pakistan, Portugal, Thailand, and Turkey -- terms of trade changes can also account for net worth being lower by over 25 percent of GNP. In these countries, however the investment shares of GNP declined by less than 3 percent from 1977-82 to 1983-86 or even rose slightly, as in the case of Turkey. Strong growth has continued through the 1980s, partly as a cause and partly as an effect of sustained investment shares. Korea was the most highly indebted of these countries in 1982, relative to GNP, but the strong increase of its saving effort and especially its rapid export growth convinced commercial creditors to keep open the lines of credit, which are now being paid off. Turkey and Hungary started the decade with relatively closed economies and low debt to GDP ratio, and their reforms to open up trade made them attractive borrowers on international markets. Hungary has become a problem debtor. Turkey and Pakistan have also had a lot of official lending. In the counterfactual scenarios, several of the countries become net creditors to the international commercial financial sector. This does not, of course, imply that we think Turkey and Kenya would now be big net cieditors if the 1978 terms of trade had continued. With more favorable terms of trade, the countries might have borrowed less and what they borrowed could have financed greater real inflows of resources for investment. The oil exporters, such as Mexico, and Venezuela, Nigeria, and Indonesia, benefitted greatly from the path of relative prices since 1978, but they became problem debtors anyway. So did a few non-oil exporters, such as Argentina. If they had saved the windfall gains from the second oil shock, they would have quickly become net creditors and would have benefited from the high real interest rates of the 1980s. When the terms of trade improved for 26 oil exporters, they adjusted mainly by increasing domestic investment in the oil sector. There was negative adjustment externally, as the high oil prices improved the access of oil exporters to commercial financing. (Here is where Indonesia and Colombia, not to mention Saudi Arabia and Kuwait, differ from the oil exporters that became problem debtors.) It seems that some oil importers and their creditors treated the post-1978 terms-of-trade changes as temporary and advisable to finance. This was only partially true and evidently less true than was assumed for the countries that have gotten into debt difficult. es. Even the most rational bankers and finance ministers could make such mistakes in forecasting prices. But it was not rationally consistent to lend heavily at the same time to oil- exporting countries that were benefiting from the relative price changes in 1979-82, as if these changes were permanent. There does not seem to be any clear correlation between terms-of- trade shocks and the changes of resource balance or of investment from the 1978-82 to 1983-86. Figures 6A, B, C, and D show the scatter plots for middle and low-income countries and the correlation coefficients which range from 0.00 to 0.21 indicating little or no relationship. We have also looked at the combined impact on net worth of terms-of- trade and interest-rate shocks (Tables 10A, B, and C). The results reflect the same general trends as in each of the separate counterfactual simulations reported in tables 6A and 9A. Counter-factual networth gains are positive for most of the developing countries. Groups of countries that gained from the combination of terms of trade and interest-rate shock are the oil exporters, Africa (including Nigeria), and Asia (excluding India). 27 VIZ. Conclusions Terms of trade shocks have had massive effects on demand for and usage of international financing. It is rational to finance some negative terms of trade shocks, partially offsetting the temporary ones and perhaps showing some impacts of the permanent ones. The counterpart, however, to financing negative shocks is for the international finance community to require countries with positive terms of trade shocks to borrow less or to repay. If Mexico and Venezuela had been reducing their debt ratios after 1979, Mexico would not have started the crisis in 1982. And commercial banks would have had the more leeway to maintain a longer term perspective with other debtors. For middle-income countries, net transfers to and from commercial creditors dwarf the resource transfers from official creditors. Thus, until 1982 many big debtors could ignore official conditionality without serious financial consequences. Since 1983, resource transfers from official lenders to HICs have increased and have effectively recycled to pay net transfers out to commercial creditors, rather than to finance the investment necessary to complement reformed policies. At least for the middle-income countries, it seems that official adjustment lending can meet its objectives only if coordinated with commercial lending. External shocks have seriously hurt some economies and have helped others. But the strength and direction of the shocks do not explain which middle-income countries now have difficulties servicing their commercial debt. One cannot argue from the evidence here that the HICs and their commercial creditors deserve a bailout because they were especially hard hit by external circumstances beyond their control. 28 Lower-income countries rely more on official financing (and grants) as external sources of resources for investment. Since 1983 these countries have seen net transfers from official creditors (not counting grants) fall, although often their financing needs have grown and their policies improved. Furthermore, investment may be more sensitive to the resource balance in low income countries than in middle income countries. A less developed country has a less efficient domestic financial structure and weaker links from its own private sector to international capital markets. Good investment projects are unlikely to get financing unless there is official lending. One could argue, therefore, that increased official lending would have a more favorable impact on the resource balance and domestic investment for lower income countries than for middle-income countries with high commercial debts. 29 REFERENCES CORBO, Vittouio and de MELO Jaime (1987), NExternal Shocks and Policy Reforms in the Southern Cone: A Reassessment," DRD Report, No. 241., Washington, D.C., February 1987. CORBO, Vittorio (1988), 'Stylized Facts about the Adjustment Process," Xerox, World Bank, October 1988. CUDDINGTON, John T. (1986), 'The Economic Determinants of Capital Flight: A Econometric Investigation," Conference at the Institute for International Economics on Capital Flight and Third World Debt, Washington, D.C., October 2-4, 1986. DOOLEY, Michael P. (1988), 'Capital Flight: A Response to Differences in Financial Risks," July 1986. EATON, Jonathan and GERSOVITZ, Mark and STIGLITZ, Joseph (1986), 'The Pure Theory of Country Risk," European Economic Review 30: 481-514. HUSAIN, Ishrat (1988), 'The Adequacy of Resource Flows to Developing Countries,' Report to World Bank Development Committee, February 1988. KHAN, Mohsin S. and HAQUE, Nadeem U. (1987), 'Capital Flight from Developing Countries,' Finance and Development, 24 (March), No. 1: 2-5. SACHS, Jeffrey (1986), 'Managing the LDC Debt Crisis,' Brooking Papers on Economic Activity, 2: 397-440. SACHS, Jeffrey and HUIZINGA, Harry (1987), 'U.S. Commercial Bank and the Developing Country Debt Crisis," for Brookings Panel on Economic Activity, September 10-11, 1987. WEBB, Steven B. (1987), 'Can Developing Countries Outgrow Their Debt?," U.S. Dept. of State, PAS Working Paper Series, No. 2 (September). 30 TABLE IA ODt Ratia in Key Yuri for RALI Countris RALI Noinal Debt (Ia11 19'u 192 19 Total Dbt $335,676 86U,948 $846,119 - Comercial LT (PPO) 1117,112 8229,524 1381,M - Comweial LT I ST I PU $234,09 847,408 $54,707 - Official & IIF $100,780 7170,539 8297,52 RALI Real Dbt - 190 dollars ISM Total Debt U416,90 852,823 $746,199 - Comrcial LT (PP8) 6145,481 8231,411 8336,237 - Comercial LT L ST I PN *291,795 *8uo,m 483,898 - Official I IIF $125,193 5172,088 8262,374 as=== as,sts s saa : : : w a a s s Shire of Total RALI Debt Total Debt as Percent of WP FroD All Creditors 1978 1982 1986 1979 1982 1996 Total RALI 1001 100? 100? 33? 452 612 Low Incom 11? 9? 102 401 491 651 Riddle Income 892 912 902 331 45? 601 Highly Indebted 572 601 572 311 45? 63? Nanufacturing Exporters 421 40? 40? 292 42? 511 Prieary Goods Exporters 26? 29? 29? 381 582 75? Oil Exporters 32? 32? 312 35? 421 65? LAC 472 51t 47? 341 49? 632 Asia 18? 192 21? 332 44? 602 ENEMA 24? 201 21? 3.62 45? 51 SSAF 10? 102 11% 26: 36? 702 Share of Comercial k ST I PNG Debt Courcial LT S ST S PN6 Debt 7o RALI Comercial S ST I PN6 hebt as Percent of 6NP 1978 1992 1986 1978 1982 1986 Total RALI 100? 1002 100? 2? 33? 39 Los Incose 52 3? 2? 12? 12? 10? Middle Income 951 971 9"? 24? 351 43? Highly Indebted 67? 701 66? 261 39? 4n Manufacturing Exporters 43? 402 41? 21? 312 34? Primary 60ods Exporters 22? 25? 24? 23? 892 401 Oil Exporters 35? 352 35? 27? 4? 482 LAC 57? 602 56? 292 42? 491 Asia 16? 189 20? :ox 307 37% EIENA 19? 152 !8? 20! 26? 30? SSAF 9? n 6? 142 17? 252 Share of Official Debt I IMF Credit Official Dbt S IlF Credit to RALi Official & IMF Credit as Percent of GNP 1978 1982 1996 1979 1982 1986 Total RALI 100? 1002 1007 :02 12? 21? Low Incoue t26 27? 24t 2I? 372 542 Middil Income 74? 732 7t 8? 10? 182 Highly Indebted 32? !22 40' 52 6? 16I Manufacturing Exporters 39? 40? t39 8? 112 17? Primary Goods Exporters 34? 362 38? 152 201 :.2 Oil Exporters 27? 232 232 92 92 17% LAC 25? 24? 30? 52 6t !42 Asia 24? 242 23? 132 14? 23? ENEMA 351 313 27? 162 201 24? SSAF 162 192 20? 122 19? 452 31 TAKLE 13 Debt Ratios in Key Years Total Debt As Percent of Exports 1978 1982 1986 Low Incose 2601 333Z 4261 Niddle Incose 183% 219Z 284Z Highly Indebted 222% 2871 3d9% Manufacturing Exporters 201% 2242 239Z Primary Goods Exporters 170% 2711 343% Oil Exporters 191% 200% 352Z LAC 257X 319% 4321 Asia 128Z 156% 1871 EHENA 2001 1812 241Z SSAF 126X 205% 343X 32 TAKE 2 Not Transfer% From Creditors to Developing Countries failliom dollus per year) (prcnt of WIP) (percent of WI) Negtive of All Creditws All Creditors Resource llmuce 1971-82 1913-h 1978-l 82 13-U 1970-82 1983-86 Lwlncme 84,67! 82,064 4.21 1.71 10.02 3.7n Middle Incoe 126,34 (526,7821 2.41 -2.2t 2.7n -1.61 Oil Exporters ",17I (11,2021 2.12 -2.5! 0.6 -3.01 Manufacturing Exporterc S11,565 tl10,0531 2.01 -1.71 4.8! 0.1t Prieary Bcode Exporters 512,697 (l3,:02) 4.41 -1.01 4.5 l 12. Highly Indeted 516,826 (525, 989 2.11 -3.41 2.0! -3.71 LAC 813,194 521,872) 2.1t -3.61 1.3! -4.51 ASIA 59,346 (S1,9971 3.41 -0.71 2.n 0.41 EIEI 56,406 (81,3841 2.41 -0.51 7.9! 5.32 SSW, 55,133 $532 3.0! 0.3! 4.4! 1.41 Official and IIF Official and IPF 1978-82 1993-86 1978-82 1983-96 Lor-Incem 54,283 83,012 3.8! 2.4! Riddle Incon s9,389 54,999 0.7n 0.41 Oil Experters 2,377 51,798 0.5! 0.4? Manufacturing Exportew 54,947 5926 0.9! 0.2! Primary 6oads Exporters $5,325 55,246 1.9! i.7t Highly Indebted 52,921 53,334 J.41 0.4! LAC $1,847 $3,645 0.3! 0.61 ASIA 53,335 Sl, 78 1.41 0.5t EIEIA 54,061 5339 1.5! 0.1! SSAF $3,421 52,404 2.0! 1.5! Coeercial Creditors Comercial Creditors Long-Term (PPS4PNB) & Short-Tere Long-Tore (PP6SPN1) I Short-Tore 1978-92 1983-86 1979-82 1993-96 Lo-Incone 5391 (5948) 0);2 -0.9! M;ddle locoel $19,995 (J31,77) 11.72 -2.6! Oil Exporters 56,801 J1l3,000) 1.1 -2.8a anufacturi g Exporters 56,619 (JlO,979) 12.1 -1.9! Primary goods Exporters $7,371 058,4471 2.6S -2.7! Highly Indebted $13,905 '529,3221 :1.7 -3.97 LAC 511,:46 (525,5171 1.8: -4.21 ASIA 55,010 (53,565) 2.02 -1.21 EIENA 52,339 51l,124) ^ 92 -0.1 SSAF S1,712 (1,872) 1.0! - t.2 Craerc:al Long-ter Credtors Comrcial Long-Term Creditcrs (PPG+PNG) IPPG.PNS) S9?-9-8 1993-86 1978-92 1983-86 Lou-Income S753 (8425) 0.7! -0.3! Riddle Income 814,209 (J22,527) 1.21 -1.9! - ' . 33 TABLE 3 CAPITAL FLIGHT 1974-84 (S billion) Accumulated Value of Flight Capital up through 1984 Gross External Estimates of: Country Debt 1984 Dooley Cuddington Argentina $468 $31.0 $15.8 Brazil 105.2 11.6 0.4 Chile 20.1 0.2 -2.0 Korea, Rep. of 43.2 9.0 Mexico 96.4 42.8 38.8 Peru 13.1 3.0 1.3 Phillipines 24.6 4.8 1.4 Venezuela 36.2 28.0 13.7 Total 69.3 Sources: World Debt Tables 1987-88; Dooley 1986; Cuddington 1986. 34 T-ble 4a Trade volume Indices 198X) -1.:a: 1978 1979 1930 19031 1932 19:3 1984 1798'5 198 Ex:ports Volume Index Africa 0.92 1.02 1.0 O.69 0).64 0.62 0.65 0.69 (:. 6i5 Asia o0.69 0.94 1.0 0 .t: 1.02 1.11 1.21 1.20 1.44 India 0.67 0.92 1.00 1.02 1.02 1. 08 1.19 1.15 1.29 EMENA 0.91 0.98 1.04) 1.03 1.07 1.14 1.23 1.30 1.34 LAC 0.90 0.97 1. 00 1.05 1.05 1.10 1.21 1. 24 1.20 Low Income 0.92 0.91 1.00 0.99 0.99 1.01 1.01 0.99 1.00 Middle Income 0.89 0.98 1.00 0.97 0.98 1.04 1.13 1.17 1.22 Oil Exporters 0.91 1.03 1.00 0.84 0.84 0.89 0.92 0.92 0.98 Manufacturers 0.85 0.91 1.00 1.12 1.14 1.25 1.41 1.48 1.55 Primary 0.90 0.96 1.00 0.99 1.01 1.00 1.07 1.10 1.12 HICs 0.87 0.98 1.00 0.94 0.92 0.96 1.05 1.08 1.07 Imports Volume Index Africa 1.00 0.86 1.00 1.06 0.95 0.80 0.74 0.69 0.58 Asia 0.84 0.96 1.00 1.09 1.11 1.22 1.18 1.14 1.26 rndia 1.02 1.07 1.00 1.04 1.03 1.16 1.15 1.27 1.30 EMENA 0.93 0.99 1.00 1.00 0.99 1.01 1.06 1.05 1.06 LAC 0.82 0.90 1.00 1.01 0.84 0.62 0.66 0.65 0.66 Low Income 0.85 0.87 1.00 0.93 0.90 0.86 0.86 0.87 0.81 Middle Income 0.88 0.94 1.00 1.05 0.97 0.90 0.91 0.88 0.90 Oil Exporters 0.90 0.88 1.00 1.14 1.01 0.83 0.80 0.78 0.71 Manufacturers 0.92 1.01 1.00 0.98 0.96 0.98 1.01 1.00 1.11 Primary 0.79 0.86 1.00 0.99 0.90 0.84 0.86 0.81 0.79 HICs 0.88 0.92 1.00 1.02 0.87 0.69 0.67 0.65 0.65 Note: Asia Excludes India and China 35 TABLE 40 Export Voluse Index 1979 1979 1900 1991 1982 1983 1984 1985 1986 exports volindex Turkey 1.06 0.96 1.00 1.85 2.59 2.95 3.53 3.97 3.91 Burundi 1.40 1.56 1.00 1.75 1.89 1.59 1.94 2.16 2.10 Korea 0.92 0.91 1.00 1.15 1.23 1.41 1.56 1.59 2.01 Pakistan 0.74 0.84 1.00 1.13 1.05 1.39 1.33 1.33 1.82 Thailand 0.85 0.94 1.00 1.13 1.24 1.20 1.42 1.52 1.73 Malaysia 0.82 0.97 1.00 0.99 1.10 1.23 1.40 1.41 1.66 Portugal 0.74 0.94 1.00 0.98 1.04 1.21 1.38 1.54 1.64 Mauritius 0.95 0.98 1.00 0.93 1.03 1.04 1.09 1.22 1.60 Mauritania 0.83 0.95 1.00 1.23 1.13 1.47 1.37 1.51 1.59 Mexico 0.84 0.94 1.00 1.06 1.21 1.35 1.49 1.45 1.52 Cameroon 0.67 0.80 1.00 1.22 1.17 1.40 1.56 1.65 1.51 Sri Lanka 0.85 0.97 1.00 1.10 1.15 1.13 1.27 1.40 1.40 Bangladesh 0.98 0.97 1.00 1.15 1.24 1.29 1.30 1.19 1.40 Ecuador 0.98 1.02 1.00 1.05 1.00 1.02 1.15 1.32 1.39 Uruguay 0.91 0.97 1.00 1.06 0.95 1.10 1.10 1.16 1.33 Philippines 0.83 0.89 1.00 1.01 1.00 1.09 1.18 1.09 1.33 India 0.87 0.92 1.00 1.02 1.02 1.08 1.19 1.15 1.29 Brazil 0.75 0.82 1.00 1.21 1.10 1.26 1.54 1.64 1.29 Jordan 0.67 0.86 1.00 1.17 1.13 1.19 1.27 1.37 1.29 Papua New 6uinea 1.01 1.00 1.00 1.05 1.04 1.05 1.05 1.22 1.29 Zaire 0.98 0.82 1.00 0.87 0.95 1.05 1.09 1.11 1.28 Hungary 0.89 0.99 1.00 1.05 1.09 1.16 1.24 1.31 1.28 Coloebia 0.87 0.87 1.00 0.90 0.92 0.81 0.91 0.99 1.25 Mali 0.72 0.80 1.00 0.95 0.95 1.05 1.12 1.19 1.24 Morocco 0.96 0.96 1.00 1.00 1.05 1.14 1.17 1.22 1.24 Chile 0.77 0.87 1.00 0.91 0.95 0.96 1.02 1.10 1.20 Egypt 0.90 0.87 1.00 0.90 0.99 1.05 1.10 1.10 1.17 Senegal 0.93 1.05 1.00 1.09 1.14 1.25 1.16 1.02 1.16 Kenya 0.99 0.95 1.00 0.96 0.95 0.97 0.99 1.05 1.15 Togo 0.99 0.68 1.00 1.27 1.25 1.07 1.09 1.10 1.15 Paraguay 0.93 1.66 1.00 1.03 1.14 0.82 0.90 1.07 1.09 Tunisia 0.82 1.00 1.00 1.03 0.96 0.97 1.00 1.03 1.09 Algeria 1.07 1.15 1.00 0.94 0.94 0.97 1.00 1S.02 1.07 Dominican Republ 0.99 1.22 1.00 1.06 0.89 1.00 1.04 1.05 1.07 Panama 0.70 0.70 1.00 0.97 1.05 1.04 0.97 1.04 1.06 Argentina 1.00 1.01 1.00 1.11 1.05 1.02 1.07 1.20 1.06 Ivory Coast 0.87 0.89 1.00 1.07 1.08 1.00 1.10 1.09 1.05 Venezuela 1.10 1.15 1.00 0.97 0.99 0.99 0.99 0.93 1.03 Costa Rica 1.01 1.05 1.00 1.16 1.04 1.04 1.14 1.07 1.01 Yugoslavia 0.91 0.93 1.00 0.95 0.90 0.84 0.90 0.95 0.72 Peru 0.98 1.10 1.10 0.97 1.03 0.93 1.01 1.05 0.91 Benin 0.66 0.90 1.00 1.09 1.30 1.04 1.07 1.04 0.91 Ethiopia 0.86 0.85 1.00 0.99 0.95 1.03 1.20 0.96 0.90 Malawi 0.68 0.75 1.00 0.82 0.74 0.76 1.00 0-96 0.89 Jamaica 0.99 1.02 1.00 1.04 1.02 0.98 1.00 0.85 0.89 Indonesia 0.93 0.95 1.00 0.82 0.75 0.78 0.79 0.72 0.83 36 TABLE 48 (con't.) 1979 1979 1980 1991 1982 1983 1984 1985 1996 Central Afr. Rep 0.81 0.83 1.00 1.04 0.83 0.85 0.86 0.89 0.78 Sierra Leone 0.99 0.75 1.00 0.95 0.81 0.65 0.69 0.72 0.76 Zambia 1.16 1.03 1.00 0.87 1.01 0.91 0.85 0.80 0.74 6uyana 1.08 0.97 1.00 0.94 0.72 0.67 0.75 0.77 0.72 Rwanda 0.79 1.07 1.00 1.01 1.03 0.79 0.65 0.77 0.71 Tanzania 0.97 0.99 1.00 1.19 0.97 0.79 0.68 0.76 0.69 Madagascar 0.94 1.02 1.00 0.74 0.68 0.60 0.63 0.66 0.68 El Salvador 0.86 1.17 1.00 0.85 0.75 0.83 0.79 0.82 0.67 Guinea Bissau 0.81 0.81 1.00 0.72 0.64 0.59 0.81 0.59 0.65 Sudan 0.73 0.59 1.00 0.85 0.61 0.79 1.12 0.58 0.63 Niger 1.23 0.94 1.00 0.98 0.76 0.80 0.73 0.66 0.63 6uatemala 0.86 0.95 1.00 0.86 0.78 0.70 0.69 0.70 0.60 Haiti 0.54 0.60 1.00 0.58 0.71 0.64 0.69 0.64 0.58 Nigeria 0.74 1.10 1.00 0.45 0.36 0.34 0.35 0.43 0.42 Burkina Faso 0.98 0.95 1.00 1.13 0.95 0.85 0.89 0.93 Burma 0.59 0.90 1.00 1.00 1.00 1.11 Honduras 0.89 1.05 1.00 1.01 0.90 0.96 0.99 1.05 Ghana 1.18 1.16 1.00 0.91 1.05 0.57 0.62 0.66 Somalia 1.07 0.90 1.00 0.90 1.20 0.97 0.55 0.76 Chad 1.18 1.11 1.00 0.90 0.88 0.77 0.73 0.76 6uinea 0.87 0.89 1.00 0.92 0.99 1.01 1.12 1.06 37 TABLE 4C Imports Voluse Index 1978 197n 1980 1991 1992 1983 1964 1983 1986 isports volindex Turkey 1.05 0.98 1.00 1.15 1.24 1.45 1.85 2.00 2.23 Ethiopia 0.80 0.85 1.00 1.07 1.19 1.25 1.37 1.36 1.33 Korea 0.95 1.06 1.00 1.04 1.07 1.18 t.30 1.28 1. Rwanda 0.80 0.85 1.00 0.98 1.20 1.19 1.31 1.19 1. Buinea Bissau 1.02 1.04 1.00 0.93 1.29 1.24 1.44 1.49 1. Jordan 0.80 1.06 1.00 1.19 1.27 1.31 1.30 1.32 1. Nauritius 1.10 1.10 1.00 0.89 0.80 0.82 0.90 0.99 1. Mauritania 1.06 0.99 1.00 1.23 1.47 1.43 1.35 1.36 1. Ind!a 1.02 1.07 1.00 1.04 1.03 1.16 1.15 1.27 1. Sri Lanka 0.71 0.84 g.l0 0.93 1.07 1.11 1.12 1.25 1. Mali 0.85 M.91 1.00 0.96 0.95 1.08 1.17 1.35 S. Indonesia 0.82 0.91 1.00 1.34 1.36 1.43 1.1! 1.14 :. Nalaysia 0.69 0.83 1.00 1.06 1.20 1.31 1.39 1.26 1. Burundi 0.98 1.16 1.0O 0.94 1.16 1.27 1.37 1.22 *. Portugal 0.81 0.90 I.Q0 1.06 1.12 1.02 0.99 1.01 Thailand 0.84 1.01 1.00 1.00 0.85 1.08 1.11 1.07 1. PaMistan 0.74 0.96 1.00 0.92 0.80 0.91 0.98 1.03 1. Hungary 1.06 1.01 1.0C 1.02 0.98 0.99 1.00 1.07 Togo 1.32 1.12 1.00 1.15 1.10 0.87 0.95 0.93 1. Paraguay 9.63 0.68 1.00 0.99 0.93 0.64 0.76 0.76 :.07 Bangladesh 0.77 0.75 1.00 0.96 0.94 0.92 1.02 1.21 1.05 ;orocco 15.07 1.11 1.00 1.02 1.05 0.93 0.97 0.97 1.04 Coloebia 0.85 0.84 1.00 1.08 1.26 1.14 1.11 1.08 1.03 Senegal 0.93 0.93 1.00 1.15 1.!0 1.14 1.04 0.97 1.02 Tunisia 0.83 0.96 1.00 1.13 1.14 1.11 1.19 1.02 1.00 Ca roon 0.81 0.90 1.00 1.15 1.04 0.99 1.08 0.75 I. Tanzania 0.73 0.59 1.00 0.9t 0.79 0.61 0.68 P. 7 O.97 Panama 0.83 0.85 1.00 1.00 1.0C 0.91 0.98 0.99 0X95 Papua Mew 8uine 0.85 0.91 1.00 1.00 0.9? 0.98 0.97 0.93 0.9; 'amaica 1.09 1.00 1.00 1.06 !.09 1.03 0.98 0.90 e.9; Costa Rica 1.01 1.04 1.00 0.76 0.60 0.70 0.78 0.84 X.9: Philippines 0.83 0.97 1.00 0.97 1.0 1.12 0.94 0.72 0.90 Central Afr. Re 0.84 0.79 1.00 0.86 0.B1 0.79 0.82 0.85 0.88 Algeria 1.05 0.97 1.00 1.11 1.12 1.12 1.14 1.07 0.24 El Salvador 1.39 1.30 1.00 0.89 0.77 0.76 0.91 0.83 0.89 Niger 0.84 0.94 1.00 1.03 1.05 1.01 0.95 0.98 0. S Dominican Repub 0.72 0.85 1.00 0.90 0.77 0.75 0.69 0.71 . 7? Ecuador 0.91 0.92 1.00 0.91 0.97 0.73 0.71 0.76 07 Egypt 0.76 0.98 1.00 0.87 0.89 1.01 1.04 0.91 0.76 Uruguay. 0.76 0.93 1.00 1.01 0.87 0.70 0.59 0.60 0. C Zaire 0.78 0.79 1.00 0.89 0.80 0.76 0.73 0.74 0.'4 Sudan r 0.78 0.64 1.00 1.18 1.29 1.13 1.22 0.82 G.72 Venezuela 1.24 1.07 1.00 1.01 1.09 0.55 0.68 0.71 O., Yugoslavia 0.98 1.10 1.00 0.97 0.75 0.69 0.68 0.68 0').7 Chile 0.69 0.84 1.00 1.16 0.74 0.63 0.73 0.65 0.2! Kenya 1.12 0.91 1.00 0.79 0.66 0.54 0.64 0.bq M.70 37 TABLE 4C Imports Voluwu Index 1978 1979 1990 1991 1982 1983 1984 1985 19 imports volindex Turkey 1.05 0.98 1.00 1.15 1.24 1.45 1.85 2.00 2. Ethiopia 0.88 0.85 1.00 1.07 1.19 1.25 1.37 1.36 I. Korea 0.95 1.06 1.00 1.04 1.07 1.18 1.30 1.28 1. Ruanda 0.80 0.85 1.00 0.98 1.20 1.19 1.31 1.19 1. 6uinea Bissau 1.02 1.04 1.00 0.93 1.29 1.24 1.44 1.48 1. Jordan 0.80 1.06 1.00 1.19 1.27 1.31 1.30 1.32 1.39 Nauritius 1.10 1.10 1.00 0.89 0.80 0.82 0.90 0.99 1.8 Mauritania 1.06 0.99 1.00 1.23 1.47 1.43 1.35 1.36 1.33 India 1.02 1.07 1.00 1.04 1.03 1.16 1.15 1.27 1.30 Sri Lanka 0.71 0.84 l.J0 0.9,3 1.07 1.11 1.12 1.25 1.29 Mali 0.85 0.91 1.00 0.96 0.95 1.08 1.17 1.35 1.29 Indonesia 0.82 0.91 1.00 1. 4 1.36 1.43 1.11 1.14 1 .6 Nalaysia 0.69 0.83 1.00 1.06 1.20 1.31 1.39 1.26 1.^^ Burundi 0.98 1.16 .00 0.94 1.16 1.27 1.37 1.22 .:2 Portugal 0.81 0.90 1.Q0 1.06 1.12 1.02 0.98 1.01 .1 Thailand 0.84 1.01 1.00 1.00 0.85 1.03 1.11 1.07 Pakistan 0.74 0.96 1.00 0.32 0.80 0.91 0.98 1.03 1.12 Hungary 1.06 1.01 I.OC 1.02 0.98 0.99 1.00 1.07 ;10 Togao 1.32 1.12 1.00 1.15 1.10 0.87 0.95 0.93 1.09 Paraguay 0.63 0.68 1.00 0.99 0.93 0.64 0.76 0.76 -.07 Bangladesh 0.77 0.75 1.00 0.96 0.94 0.92 1.02 1.21 1.05 oarocco 1.07 1.11 1.00 1.02 1.05 0.93 0.97 0.97 1.04 Colombia 0.95 0.84 1.00 :.08 1.26 1.14 1.11 1.08 1.0 Senegal 0.93 0.93 1.00 1.15 1.!0 1.14 1.04 0.97 1.0^ Tunisia 0.83 0.96 1.00 1.13 1.14 1.11 1.18 1.02 1.00 Cameroon 0.81 0.90 1.00 1.15 1.04 0.99 1.08 0.75 1.JC Tanzania 0.73 0.59 1.00 0.93 0.79 0.61 0.68 0.77 0.97 Panama 0.83 0.85 1.00 1.00 1.0C 0.91 0.98 0.99 .9 Papua Nev 8uine 0.85 0.91 1.00 1.00 0.99 0.98 0.97 0.93 0.93 aaaica 1.09 1.00 1.00 1.06 1.08 1.03 0.98 0.90 MI, Costa Rica 1.01 1.04 1.00 0.76 0.60 0.70 0.78 0.84 J.9. Philippines 0.83 0.97 1.00 0.97 1.01 1.12 0.94 0.72 0.90 Central Afr. Re 0.84 0.79 1.00 0.86 0.01 0.79 0.82 0.95 0.8e Algeria 1.05 0.97 1.00 1.11 1.12 1.12 1.14 1.07 0.24 El Salvador 1.39 1.30 1.00 0.89 0.77 0.76 0.81 ).%3 .83 Niger 0.84 0.94 1.00 1.03 1.05 1.01 0.85 0.98 0.'^ Dominican Repub 0.72 0.85 1.00 0.90 0.77 0.75 0.69 0.71 0.7 Ecuador 0.91 0.91 1.00 0.91 0.97 0.73 0.71 0.76 0. Egypt 0.76 0.98 1.00 0.87 0.88 1.01 1.04 0.91 3.76 Uruguay 0.76 O.q9 1.00 1.01 0.87 9.70 0.59 0.60 O. Zaire 0.78 0.79 1.00 0.89 0.90 0.76 0.73 0.74 02.4 Sudan 0.78 0.64 1.00 1.18 1.29 1.13 1.22 0.82 0.72 Venezuela 1.24 1.07 1.00 1.01 1.09 0.55 0.68 0.71 C. Yugoslavia 0.98 1.10 1.00 0.87 0.75 0.69 0.68 0.68 C.? Chile 0.69 0.94 1.00 1.16 0.74 0.63 0.73 0.65 C. Kenya 1.12 0.91 1.00 0.79 0.66 0.54 0.64 0.60 0.7 39 TABLE 5 MOULD INTEREST RATES AND PRICES 1978 1979 1980 1981 1982 1983 1994 1985 1986 LIBOR 6 o. 9.22 12.2S 14.0! 16.7% 13.6U 9.9? 11.3! 8.61 6.92 Inflation Nanufacturing Uiit Value 5.7n 12.3N 9.n9 1.02 -2.01 -2.0! -2.11 1.1 17.7! LIN real Ianufacturing Unit Value -6.5$ -0.2! 4.1! 15.7J 15.61 12.01 13.41 7.62 -10.92 Inflatice US 7.42 8.83 9.12 9.61 6.5! 3.X9 4.11 3.3! 2.61 LIBOR real US 1.82 3.42 4.91 7.1! 7.1! 6.1! 7.22 5.3! 4.32 Inflatio Trade Pricn 1l.3! 17.3? 17.6! -3.1! -4.5! -4.1 -2.6? -1.0 9.12 LIBOR real Trade Prices -2.1? -5.2! -3.52 19.8! 18.1T 14.01 13.92 9.7n -2.3Z Srces: INF, IFS. 40 TABLE 6A Gains of Debtors with Counteriactual Interest Ratn (four percent above inflation of mufacturing unit value) 19SB 1956 1996 Interest Rate Interest Rate CF Networth gatn is million) CFI Netnorth gain Africa $835 1 1,503 Africa 15,079 Asia 55,608 516,796 Asia 121,477 India $177 $5B9 Indta $797 EIENA 15,613 $15,235 ENENA $10,493 LAC $36,951 592,799 LAC iS9,686 Los Incoe (1$1,673) ($3,056) Lou Income i217 Niddle Intcoe $50,083 *12S,359 liddle Incom 5136,517 Non Oil Exporting $20,924 $71,395 Non Oil Exporting $74,591 Oil Exporters 821,159 $59,004 Oil Erporters $61,926 Kanufacturers $19,932 145,&fl Ianufacturers 845,390 Prieary 17,320 822,706 Primary $29,420 HICa 540,957 $103,379 HICs 8113,40 SAL Countr ns 840,976 $105,551 SIIL Ceuntries $110,192 Non SAL Countries 87,534 $20,782 Non SAL Countrin $26,542 CF Netuorth gain SOPhire (share of GDP) CFBI lNtvorth gain lDhhare Africa 0.2. 1.21 Africa 3.91 Asia 1.92 5.51 Asia 7.01 India 0.11 0.32 India 0.31 EDEIU 1.92 4.52 EllEA 3.12 LAC 5.22 14.11 LAC 15.22 Lon Income -1.4% -2.42 Low Incomo 0.21 Niddle Incom 3.7 9.91 Niddle Income 10.5t Non Oil Exporting 3.42 9.1t Non Oil Exporting 9.42 oil Exportrs 4.12 13.91 Oil Exporters 14.n lInufacturers 3.11 6.n Manufacturers 6.61 Primary 2.42 7.02 Primry 9.11 RICS 4.62 13.02 HICt 14.32 SAL Countries 3.42 9.32 SAL Countries 9.n mon SAL Countrin 2.n 6.92 Ion SAL Coontries 9.92 CF Nteorth gain DdtShare (slhe of ddtl CFBI Netortwh gain kbtShare Africa 0.62 1.62 Africa 5.62 Asia 4.52 9.5 Asia 12.12 India 0.72 1.41 India 1.92 EaEIU 4.3 9.62 ElE 5.92 LAC 11.41 23.92 LIC 25.5t Lou Intom -2.92 -3.62 Lou lacen 0.3 Kiddle Income 8.62 17.22 Kiddle Incom 111.12 lon Oil Exporting 7.72 14.5 Non Oil Exporting 15.21 Oil Experters 10.22 22.21 Oil Exporters 23.72 Kanufacturers 7.71 13.42 Ianufcturers 13.32 Primay 4.22 9.72 Primary 12.51 HICS 10.62 21.19 HIC, 23.91 SAL Countries 6.12 15.92 SAL Coumtrin .62 No Sk Costrin 5.62 12.1t Nbn SM Countrin 15.41 (cotsterfactual since I1971 lsince IS11I lotex kia Ecludsn India and China 41 TAOLE 68 Increase of Netmorth (reduction of Debt) From A Constant Real Interest Rate of Four Percent: Share of ODP 1982 1986 1986 Counterfactual since 1978 Counterfactual since 1981 Interest Rate Interest Rate CF Networth gi:i GDPshare CF8I Networth gain 6DPshare Chile 8.32 37.01 Chile 36.12 Ecuador 8.7Z 27.02 Ecuador 27.7? Mexico 7.6? 26.2? Nexico 25.82 Panaua 12.02 25.5 Panaua 26.5Z Venezuela 6.32 24.0? Venezuela 25.0? Costa Rica -1.02 21.41 Costa Rica 23.4? Jamaica 1.42 13.92 Jamaica 17.2% Argentina 5.7? 13.3? Argentina 14.62 Ivory Coast 4.8? 1228Z Ivory Coast 17.51 Dominican Republic 4.21 12.71 Dominican Republic 12.0? Uruguay 2.4? 12.32 Uruguay 12.9? Papua Nec Guinea 3.3? !2.2? Papua New 6uinea 15.32 Portugal 5.2% 11.5' Portugal 13.82 Yugoslavia 4.0? 9.3Z Yugoslavia 11.1? Niger 5.1? p.2Z Niger :1.32 Nigeria 2.0? 8.1% Nigeria 7.82 lauritius 5.42 8.1? Mauritius 8.1% Horocco 4.5? 7.9? Morocco 10.1I Brazil 38.9 7.3? Brazil 9.42 Colaobia 2.9? 7.7X Colombia 11 Korea 4.11 7.71 Korea 8.6? Malawi 3.6? 6.8% Malami 7.98 El Salvador 3.3? 6.8? El Salvador 8.8? Malaysia 1.4? 6.2? 1'alaysia 8.M2 Thailand 3.1% 5.72 Thailand 5.82 Guatemala 2.98 5.52 5uateuala 7.52 Sri Lanka 2.4? 5.4% Sri Lanka 5.42 Indonesia 1.1 4.7? Indonesia 6.42 Honduras 5.0% 4.5% Honduras 4.11 Philippines -'.2? 3.0: Philippines 8.5? Algeria -0.2? 2.9? Algeria 6.62 Turkey 0.0? 2.4? Turkey 6.7% Tunisia 0.7Z 1.9Z Tunisia 4.12 Hungarv 3.0? 1.8Z Hungary -49.62 Kenya 0.0? 1.5% Kenya 4.9% Burkina Faso 1.9Z 1.32 Burkina Fasc 1.5? Pakistan 0.6? 1.1' Pakistan 1.2 Egypt 0.% 19.1% Egypt 1.7l Caeeroon 0.30 0.9% Cameroon 2.2? Paraguay 0.3? 0.3Z Paraguay 0.9? India 0. 1 0.32 India 0.'? Burma 0.1? 0.2% Burma 0.62 Bangladesh -0.1% 0.0Z Bangladesh 0. 2 Ethiopia 0.0? -0.1? Ethiopia 0.2? 42 TABLE 6B (Ckn't.) 1982 1986 1986 Jordan 0.5Z -0.1 Jordan 0.01 Burundi -0.2X -0.32 Burundi 0.0O Rwanda -0.6Z -0.9X Rwanda -0.32 Madagascar 0.22 -1.02 Madagascar -1.92 Senegal -1.3Z -1.52 Senegal 0 22 Haiti 0.0 -1.72 Haiti -1.72 Peru 2.4Z -1.92 Peru 1.52 Mali -1.42 -3.02 Mali -1.82 6hana -3.02 -4.02 Ghana -1.22 Central Afr. Rep -3.52 -4.72 Central Afr. Rep -1.52 Chad -4.8% -5.92 Chad -2.1% Siarra Leone -2.11 -6.5% Sierra Leone -3.52 6uyana -1.52 -7.22 Suyana 4.62 Suinea -4.32 -10.22 Guinea -4.92 Benin -5.1% -10.92 Benin -7.12 Sudan -5.92 -12.42 Sudan -4.82 Tanzania -3.1% -13.52 Tanzania -9.82 Mauritania -8.3% -15.0% .1auritania -5.89 Zaire -8.27 -15.32 Zaire 1.62 Zambia -3.2% -21.12 Zambia -5.02 Guinea Bissau -3.22 -21.72 Suinea Bissau -18.12 Togao -21.22 -23.8X Togo -0.92 43 TABLE 6C Gains of Net Vorth (Reduction of Debts From A Constant Real Interest Rate of Four Percent: Ratio To Debt 1982 1986 1996 Counterfactual since 1978 Counterfactual since 1901 Interest Rate Interest Rate CF Networth gain DebtShare CF8I Networth gain DebtShare Venezuela 13.32 35.5% Venezuela '6.92 Ecuador 13.72 33.32 Ecuador 34.22 Mexico 14.8Z 32.3% Mexico 31.92 Chile 11.62 29.8Z Chile 29.02 Yugoslavia 13.02 29.0X Yugoslavia 33.4% Panaua 13.1% 26.72 Panama 27.98 Argentina 7.41 21.3% Argentina 23&4% Uruguay 8.3X 20.62 Uruguay 21.7l Costa Rica -0.82 20.3X Costa Rica 22.3% Dominican Republic 11.62 20.2% Dominican Republic 19.11 Portugal 8.9Z 19.9% Portugal 23.9% Brazil 11.21 18.72 Brazil 22.5Z Nigeria 14.52 17.3% Nigeria :6.5% Mauritius 10.1% 16.6b Mauritius 16.7% Colombia 11.12 16.62 Colombia 17.52 Korea 7.81 16.52 Korea 18.42 El Salvador 8.1% 15.9X El Salvador 20.6% Guatemala 15.67 14.82 Guatemala 20.5% Papua New Guinea 4.8% 13.32 Papua NeN Guinea 16.82 Niger 10.52 13.12 Niger 16.1Z Thailand 9.3- 12.83 Thailand 13.12 Ivory Coast 4.6% 10.92 Ivory Coast 14.82 Algeria -0.41 10.2X tigeria 23.2% Sri Lanka 4.02 8.6Z Sri Lanka 8.5% Jamaica 1.5% 8.5% Jamaica :.4X Indonesia 4.0Q 8.22 :ndonesia 11.12 Malaysia 2.72 7.'Z Malaysia 10.3X Malawi 4.2% 7.5% Xalawi 8.5% Morocco 5.9% 6.4% -rocco 9.2% Honduras 7.7% 5.5% Honduras 5.0% Turkey 0.1% 4.22 Turkey :1.9X Phil.ppines -0.32 3.2: Philippines 9.1% Pakistan 2.92 '.7% Pakistan 2.82 Tunisia 1.5% 2.-7 Tunisia 5.92 Cameroon 0.92 2.6% Caseroon 6.2% Burkina Faso !.,Z '.62 Burkina Faso 3.1Z Hungary 7.7% 2.4Z Hungary -68.02 Kenya 0.0% 2.22 Kenya 7.22 India 0.'7 1.4t India 1.92 Egypt :.1% 1.42 Egypt '.1: Paraguay 1.22 0.5: Paraguay .7 Burma 0.42 0.4: Burma 1.42 Bangladesh -0.32 0.1% Bangladesh 0.52 Jordan 0.32 -0.1: Jordan 0.02 44 TABLE 6C (con't.) 1982 1986 1986 Ethiopia 0.0 -0.2l Ethiopia 0.5% Burundi -1.1 -0.7? Burundi 0.01 Madagascar 0.2Z -1.0 Madagascar -1.7Z Senegal -2.11 -1.92 Senegal 0.3% Mali -2.01 -2.7% Mali -1.6% Peru 5.01 -3.2X Peru 2.4Z Guyana -0.8% -3.32 Guyana 2.1% Soealia -1.0% -3.3Z Somalia -2.6X Ruanda -4.1Z -3.9% Rwanda -1.42 Haiti 0.1% -5.3X Haiti -5.12 Zambia -3.4% -7.0% Zambia -1.7Z Mauritania -5.4% -7.1 Mauritania -2.8Z 6hana -9.0% -9.41 Ghana -2.8X Central fr. Pep -10.9% -10.0% Central Afr. Rep -3.1l Sudan -7.1% -11.01 Sudan -4.3t Guinea -5.7Z -11.1% Guinea -5.3Z Guinea Bissau -3.31 -11.8% Guinea Bissau -9.9% Sierra Leone -5.5Z -13.5% Sierra Leone -7.3Z Zaire -15.7% -14.1l Zaire 1.5% Tanzania -6.6% -15.4X Tanzania -10.0% Benin -e.1 -17.0X Benin -11.1% Togao -19.0 -22.51 Togo -0.8l Chad -17.7% -25.6% Chad -9.2Z 45 Table 7 Actual Terms of Trade With Average of 1969 to 1978 As Base Line: 1.00 1970 1979 1980 1981 1982 1983 1984 1985 1986 s of Trade tual over 1969 to 1978 Manufacturing Exporters ordan 1.05 1.02 0.97 0.92 0.99 0.99 1.03 1.02 1.17 Yugoslavia 1.01 0.99 0.99 0.98 1.01 0.99 0.94 0.92 1.02 hilippines 0.98 0.95 0.87 0.84 0.80 0.86 0.88 0.86 1.02 Morocco 0.90 0.97 0.92 0.87 0.84 0.86 0.85 0.86 0.95 Korea 1.02 1.00 0.88 0.86 0.88 0.88 0.90 0.89 0.95 Tunisia 0.98 1.OB 1.12 1.15 1.17 1.17 1.'1 1.06 0.95 Portugal 1.00 1.00 0.96 0.91 0.89 0.E9 0.88 0.88 0.94 Thailand 0.91 0.93 0.89 0.81 0.75 0.80 0.79 0.75 0.8: Hungary 0.91 0.89 0.89 0.f8 0.86 0.84 0.82 0.82 0.78 Uruguay 0.78' 0.79 0.76 0.?8 0.79 0.71 0.68 0.65 0.75 ndia 1.00 0.90 0.65 0.69 0.70 0.79 0.72 0.73 0.75 Brazil 1.0 0.99 0.75 0.65 0.65 0.61 0.69 0.65 0.72 Turkey 0.84 0.83 0.64 0.59 0.56 0.55 0.62 0.63 %,70 Pakistan 0.96 1.04 1.00 0.74 0.66 0.66 0.70 0.69 0.6t Primary Exporters Niger 1.03 1.44 1.18 1.32 1.72 1.98 1.92 1.84 1.88 Rwanda 1.00 1.16 0.87 0.70 0.80 1.20 1.80 1.19 1.84 Tanzania 0.99 0.85 1.36 1.25 '.24 1.23 1.28 1.17 Costa Rica 1.09 1.01 1.01 0.83 0.86 0.93 0.96 1.05 1.': Ethiopia 0.91 0.91 0.91 0.91 0.91 0.91 0.82 0.95 1.28 Sudan 1.08 1.13 1.01 1.14 1.38 1.31 1.24 1.61 1.'9 Guinea Bissau 0.83 0.78 0.53 1.13 1.06 1.08 1.29 1.31 I.:S Dominican Republic 0.79 0.81 1.01 I.06 0.91 0.96 0.97 0.92 1.10 Sri Lanka 1.26 1.10 1.01 0.95 0.94 1.0' 1.26 1.06 1.07 Mauritania 0.95 0.84 0.80 0.88 0.90 0.85 0.90 1.02 !06 Uamaira 1.12 0.95 0.96 0.83 0.81 0.78 0.87 0.90 1.0' Ivory Coast 1.29 1.1 1.00 0.87 0.85 0.86 0.99 0.97 1.! Senegal 1.05 0.99 0.94 1.02 0.99 0.97 1.02 1.00 1.0: Central Afr. Rep 1.08 0.98 0.94 0.90 0.93 0.92 0.96 0.93 l.0( Colombia 1.18 1.17 1.07 0.94 0.96 0.97 1.03 1.05 ^.99 Paraguay 1.19 0.65 1.13 1.02 0.96 1.09 1.09 0.94 0.98 Haiti 1.14 0.95 0.98 0.95 0.86 0.9t 0.99 0.90 3.93 lalaysia 1.09 1.17 1.21 1.10 1.08 1.11 1.'9 1.14 A.;6 Mali 0.93 0.93 0.93 0.93 0.94 1.02 1.14 1.04 Q.;: Togo 0.99 1.!1 0.94 0.90 0.91 0.91 0.95 0.95 0.91 Panama 0.93 0.89 0.82 0.81 0.77 0.78 0.85 0.86 0.83 El Salvador 1.07 0.96 0.89 0.74 0.7' 0.67 0.67 0.67 0.;' Guyana 0.92 0.85 0.91 0.83 0.79 0.74 0.71 0.72 O.S: Gua'eeala 0.98 0.87 0.81 0.74 0.70 0.71 0.75 0.68 0^.8: 4adagas:ar 0.81 0.70 0.66 0.65 0.72 0.78 0.94 0.75 0.29 Burundi 0.91 0.06 0.88 0.53 0.55 0.68 0.72 0.66 0.7' Bangladesh 0.69 0.67 0.76 0.66 0.53 0.59 0.69 0.95 0.72 Papua New Buinea 0.90 1.05 0.94 0.72 0.67 0.73 0.79 0.72 0.70 Kenya 0.99 0.91 0.84 Q.71 0.68 0.64 0.72 0.64 0.'0 46 TABLE 7 (con't.) 1979 1979 1980 1981 1982 1984 1985 1986 Peru 0.86 1.19 1.16 1.01 0.90 0.99 0.95 0.76 0.64 enin 0.95 0.95 0.84 0.72 0.11 0.71 0.70 0.70 0.61 Chile 0.65 0.72 0.71 0.65 0.59 0.62 0.57 0.53 0.57 Argentina 0.62 0.68 0.78 0.84 0.64 0.63 0.69 0.61 0.56 Nalawi 0.97 0.71 0.72 0.85 0.86 0.79 0.79 0.53 0.54 Zaire 0.77 0.95 0.89 0.73 0.63 0.61 0.66 0.65 0.54 Zaebia 0.52 0.73 0.63 0.46 0.34 0.40 0.49 0.55 0.44 Sierra Leone 1.15 1.59 1.10 1.10 0.79 0.62 0.44 0.40 0.37 Burkina Faso 0.79 0.84 0.87 0.85 0.97 0.9J 1.01 0.86 Burma 0.99 1.04 1.11 1.15 0.90 0.96 Chad 0.85 0.81 0.74 0.76 0.70 0.85 0.89 0.89 Ghana 1.13 1.13 1.31 1.20 0.81 0.79 1.10 1.10 Guinea 1.24 1.19 1.17 1.41 1.29 1.27 1.38 1.42 Honduras 1.24 1.11 1.13 1.01 0.91 0.84 0.83 0.95 Somalia 1.35 1.41 1.39 1.40 1.23 1.21 1.22 1.21 Oil Exporters Indonesia 1.29 1.63 2.11 2.46 2.39 2.27 2.26 2.23 2.00 Venezuela 1.37 1.87 2.49 2.39 1.85 1.61 1.98 1.84 1.36 Algeria 1.11 1.41 2.00 2.35 2.27 2.22 2.22 2.16 1.21 Nigeria 1.37 1.08 1.40 2.53 2.19 2.03 2.29 1.9 0.89 Ecuador 0.99 1.20 1.32 1.21 1.17 1.15 1.10 1.02 0.75 Mexico 1.01 1.11 1.42 1.52 1.49 1.04 1.00 0.93 0.70 Egypt 0.86 1.09 1.20 1.09 1.08 1.05 1.03 0.89 0.66 Cameroon 0.92 0.76 0.80 0.78 0.80 0.76 0.83 0.81 0.66 47 Table Ba lIprovements in Resource Balance (as 2 of GDP) With 1969 to 1978 Average Terms of Trade 1978 1979 180 1981 1982 1983 1984 1985 1926 Resource ga1 CFI gain 6DP Share Oil Exporters -2.91 -5.4% -9.6% -9.8% -8.71 -7.2% -7.2% -5.72 -0.4% Manufacturers 0.5% 0.92 3.0% 4.2% 4.1% 4.8% 4.72 5.3l .SX Prisary -0.7% -0.1% 1.5% 2.3% 2.0% 1.52 ).0. 0.3% Lao Income 1.0% 0.5% 1.1% 3.0% 3.9% 4.82 2.3% 2. 22 2.:. Middle Income -1.0% -1.52 -2.1% -1.8% -1.2% -0.72 -1.02 00% :.n2 Non Oil Exporting 0.0% 0.6% 2.77. 3.7% 3.4X. 3.4% 3.1% 3.32 3.4', Africa -2.6% -0.1% -2.8% -4.9% -2.32 -0.3% -3.3% -2.5% l2 Asia -1.6% -7.6% -4.4 -3.2% -2.2% -2.5% -3.0% -2.12 -1.52 India 0.0% 1.02 3.5% 3.0% 2.6% 1.81 2.5% 2.4% 2.1 ENENA 1.2% -0.5% -0.6% 0.47 0.8% 1.3% 1.7% 2.3% 3T'. LAC -0.9% -1.1% -1.11 -0.7% -0.5% 0.32 0.0% 1.0% 3. 1 HICS -1.4% -1.1 -1.5% -1.50 -0.4% -0.8% 0.Z . SAL Countries -0.6% -0.3% -0.4% -0.4% 0.0% 0.8% 9.42 1.12. Non SAL Countr:es -1.b6 -6.2% -8.6% -6.5% -4.3% -4.02 - .12 -3.6X .dote: Asia excludes .ndia and China 48 TABLE 83 laprovunnts in Resource alance (as 2 of 6DPI Kith 1969 to 1978 Average Terns of Trade 1978 1979 1980 1981 1982 1983 1914 1995 1986 Resource Bal CFI gain 60P Share Manufuturing Exporters Hungary 42 5S 52 52 72 92 112 12Z 132 Uruguay 52 42 5l 42 42 9X 92 11Z 10X Turkey 12 it 52 72 92 1O0 102 10X 8l Thailand 22 22 32 61 62 52 62 72 72 Pakistan 1I -12 1 6% 92 81 72 72 6X Bratil 02 12 3l 42 41 42 42 52 42 Korea -12 0 5X 62 51 S 42 42 32 Philippines 22 12 32 42 42 32 32 32 32 Portugal 0 02 32 52 42 42 a2 52 2l India 02 12 42 32 32 22 32 22 22 Tunisia 12 -32 -32 -5 -62 -72 -52 -32 02 Foroco 22 12 32 52 52 42 52 42 02 Yugoslavia 02 12 12 12 02 02 12 12 -1t Jordan -52 -92 22 102 52 -1Z -22 -52 -252 Prisary Exporters Zambia 292 122 192 262 352 292 262 241 482 Zaire 42 12 32 7X 102 142 172 192 282 Chile 112 92 92 92 122 13S 172 232 27X Papua Nel Guinea 5S -22 32 162 192 152 122 172 19Z Malawi 22 13! 112 52 42 62 62 16X 15t Kenya 12 32 72 10X 102 0OX 8X 112 101 Guyana 52 1I1 72 152 142 162 192 192 "O Sierra Leone -22 -82 12 22 62 52 72 6X C2 Benin 32 52 52 010 92 102 102 102 9 Panama 32 52 102 107 122 112 62 62 Paraguay -32 92 O0 12 22 1Z 2' 72 A Peru 32 -42 -32 02 12 02 12 42 Malaysia -42 -82 -102 -42 -32 -52 -82 -72 El Salvador -32 22 41 92 82 112 112 142 42 Burundi 12 22 42 92 11X 77 62 7Z 42 Nadagascar 52 102 112 92 62 42 32 2; Guatemala 12 32 52 62 62 42 4% 52 IX Colombia -32 -2l -12 10 02 -12 2. Haiti -42 O0 -32 12 4 32 34 3' Central Afr. Rep -22 12 3X 22 2 22 07o 32 Ivory Coast -82 -42 12 52 62 62 1 1X - Guinea -5X -4l -42 -92 -72 -62 -82 -92 Bangladesh 02 12 -12 22 52 42 12 -32 Jamaica -5X 2X 22 10 112 127 82 72 % Argentina -62 02 62 12 -32 -42 -42 -7X -2: Togo -62 -62 02 12 02 1 12 -2 - :2 49 TABLE 83 (con't.) 1978 1979 1980 1991 1982 1983 1984 1915 1986 Senegal -5X -12 -12 -62 -52 -42 -52 -42 -42 "Ali 21 31 32 -12 -22 -62 -102 -102 -42 Sudan -12 -22 -22 -52 -112 -8l -72 -82 -4% Dominican Republic 42 52 -3X -22 12 2X 42 32 -42 Rwanda 22 -22 42 5% 42 -I1 -52 02 -6, Ethiopia It 1 12 02 02 02 21 -12 -7X Mauritania -3X 42 92 42 02 52 2% -52 -71 Costa Rica -42 -22 O0 91 7% 32 12 -21 -102 Sri Lanka -122 -82 -52 -I% -32 -72 -10% -62 -10% 6uinea uissau 42 102 132 02 -72 -132 -122 -72 -11% Niger 0% -52 22 -42 -127. -162 -192 -192 -131 Tanvania 12 32 -112 -8% -52 -62 -62 -202 Honduras -92 -52 -52 -12 3X 52 62 5% Ghana -2% -32 -52 -32 31 39n -12 -I1 Burma 02 0% -1% -22 -22 02 Burkina FasD 5S 6% 6% 32 32 1% -1% 32 Chad 6% 10% 142 102 11% 52 4% 3% Somalia -32 -42 -32 -32 O -32 02 102 Oil Exporters Egypt 11X -3X -5l 1X 12 322 .15 Caneroon 3X 71 6% 7% 6% 8X 62 52 10% Ecuador 1% -4% -52 -32 -22 -42 -t4 -42 7X Mexico 02 -12 -4% -47. -61 -22 -22 0% 7% Nigeria -7% -'2 -7? -!22 -72 -62 -31 -72 12 Algeria -1% -9X -162 -192 -17% -152 -142 -13% -32 Venezuela -9% -161 -1T17 -182 -102 -9% -152 -132 -7% Indonesia -5% -122 -182 -182 -15 -16% -152 -142 -1'7 50 TAILE 9A Gains of Debtors sith Counterfattual Torn of TraCe (Sas, export and import prices relative to the manufacturing unit value as in 1969.731 Situlated since 1978S 1982 1984 1986 Teros of Trade CF Networth gain (in current dollars) Africa ($27,0791 1140,135) (146,454) Asia (146,493) t174,1911) 1101,5121 India $20,551 o34,082 149,919 EHENA *6,109 $116,65 S17,374 LAC (134,3111 14z,19)1 (127,0O4) Ln* Income *12,621 124,660 134,510 middle Income IS114,4011 ($165,7301 (1172,1571 Non oil Exporting *101,453 $177,254 8270,067 Oil Exporters ($215,65I4 ($342,94) (1$442,224) Hnufactuerrs 895,257 t171,819 $261,513 Primary S1),S16 $30,096 143,064 ilCs (167,770) (897,772) ($94,7361 Hics Oil Comtries 1$126,477) (1194,2071 (1237,423) Hics Non Oil Countrie 158,706 S96,435 $142,637 Sk Countries (121,662) (11461l) 122,3SS Non SAL Cotmtries ($90,118) ($126,409) ($160,046) CF Networth gain GDP%hare (as percent of SOP) Africa -15.5? -24.52 -35.3l Asia -15n.7 -24.21 -33.12 India 11.1I 17.62 21.32 ENENA 2.12 6.12 11.12 LAC -4.8U -6.02 -4.11 Lov Incou 10.52 21.22 27.11 Middle Incone -6.4 -13.02 -13.2t Non Oil Exporting 12.11 23.02 30.6? Oil Exporters -41.9? -63.3? -105.22 Nanufacturers 14.72 30.4: 38.12 Priarvy 6.0 9.3? 13.32 HICS -7.62 -12.3? -11.9? Hics Oil Countries -37.12 -60.2S -100.86 Hics Non Oil Couwtries 10.62 20.42 25.5? SAL Countries -1.32 -1.3? 2.0? Non SAL Countries -20.72 -46.2n -53.42 CF Nletorth gain DetShare (as percent of total debt) Africa -44.21 -56.42 -50.i2 Asia -37.02 -50.9? -57.42 India 80.22 109.0S 120.13 EnIIIDI 4.71 12.3? 21.0? LAC -10.62 -12.02 -6.9? Lo Intome 21.51 33.2? 41.1? Kiddl Intoe -19.7? -25.4? -22.9n Non oil Exporting 27.0? 42.11 55.02 11 Exporters -104.52 -147.n -168.9? Manufacturwrs 36.7n 59.S 76.32 Priwy 10.I2 15.22 18.3? NiCs -17.5t -22.7? -20.02 Nice Oil Countries -91.12 -122.0? -141.22 Hics Non oil Coustrsn 23.7n 3S.5 4.n SAL Contries -4.32 -2.6 3.4? No SAL Cmntries -60.02 -U4.3? -93.02 Note: Asia eicldes India and China 51 TABLE 99 Increase of Net Worth (Reduction of Debt) From Accumulated Value of Resource Balance 6ains Fran The Teras of Trade Effects 1982 1966 1982 1986 Share of Debt Share of GDP Terms of Trade Terms of Trade CF Networth gain CF Networth gain MFG. Exporters MF6. Exporters Uruguay 889.9 158.6. Uruguay 25.4% 94.6% Turkey 74.7% 135.2% Turkey 27.72 76.3X Hungary 84.67 124.72 Hungary 32.9% 90.8% Thailand 65.81 124.4% Thailand 21.8% 55.2X India 80.2% 120.8% India 11.12 21.8% Pakistan 40.6% 117.6% Pakistan 14.96 48,3% Brazil 36.9% e0.9% Brazil 12t.6 33.6Z Korea 29.5% 70.0% Korea 15.4Z 32.8% Portugal 26.5X 56.9% Portugal 15.4I '3.0% Philippines 24.3X 44.0% Philippines 14.92 40.9% Morocco 24.8% 31.8. Morocco 18.92 39.42 Yugoslavia 10.6% 18.9% Yugoslav4a 3.2% 6.3% Jordan 7.9% -31.0% Jordan 5.1% -28.21 Tunisia -39.0% -57.9% Tunisia -19.2% -40.2% Primary Exporters Pritary Exporters Chad 270. 1Z 349.9% Chad 72.5% 30.2% Zambia 139.5% 195.1X Zambia 131.3% 591.9% Chile 85.1% 183.12 Chile S).7X 227.9% Guatemala 145. 3Z 178.9% Guatemala 25.6% 65.92 -l Salvador 58.8X 174.7% E: Salvador 24.0Z 74.91 Papua New 6uinea 64.3% 39. 4% Papua NJew Suinea 44.3% 127.4% Burundi 13. OX0.03 Burundi 23.?7 98.2% Zaire 2.7% ?28X Zaire 27.5 1539.52 Kenya 66.4% 126.2% Kenya ' '2 86.0O Ma'awi 59 :14.5% Sa awi 46.3% 104.2% Benin 51.7% 94.3% 8enin ;2.BX 60.3% Panama 45.3% 89.5% Panama 41.51% 6.6% 8..rkina Faso 100.8& 94X7% Burkina Faso ;4.6% 41.62 Madagascar 73.8% 60.4% Madagascar 48.6% 87.5% Guyana 35.42 6Z.7Z 3uyana 7.1%X 144.9% Sierra Leone 3 1Z 6 4.3 Sierra Leone 1.2% 30.9% Paraguay 37.3% 59.5% Paraguay B.?% 33.7X 6hana -32.3% 54.3% Ghana -10.7% 22.8% Jamaica 19.4% 44.92 lamaica 18.8% 73.8% Dominican Repubi 17.5% 29.8X Dominican Republ 6.3Z 18.89 Central Afr. Rep 21.2% 22.6% Central Afr. Rep 6.9% 10.7% Haiti -4.0% 22.2% 4a; i -1.5% 7. 2 Bangladesh 20.0% 19.0G Bangladesh 7.7% ?.7% Peru -5.9% 9.8% Peru -2.8X 6a O Rwanda 82.8% 9.6% Rwanda 12.7% 2.32 Mauritania 8.9% 4.1% Mauritania 13.6% 8.5% 52 TABLE 99 Icon't.i 1962 1986 1982 1986 Ivory Coast -2.1% 3.0% Ivory Coast -2.3% 3.5% Somalia -15.4% -0.31 Soaalia -8.4% Costa Rica 4.4% -1.7% Costa Rica 5.8Z -1.7% Ethiopia 12.1% -2.8% Ethiopia 3.4X -1.21 Honduras -30.9% -5.8% Honduras -19.9% -4.8% Surma -16.8% -12.9% Burma -5.8% -5.9% Guinea Bissau 14.2% -14.6% 6uinea Bissau 13.6% -26.71 Mali 8.6% -14.8% Mali 6.1% -16.6% Togo -10.8% -14.9% Togo -12.1% -15.8% Colombia -19.0 -19.9% Colombia -5.0% -9.3% Argentina -2.1% -31.q% Argentina -1.6% -19.9% Senegal -32.6% -40.5% Senegal -20.7% -32.5% Sudan -26.7X -47.1% Sudan -22.2% -52.9% Guinea -39.6X -67.6% juinea -29.8% -61.9% Tanzania -43.8% -80.0% Tanzania -20.5'h -70.1% Malaysia -62.1 -SI.1% Malaysia -30.9% -65.4% Sri Lanka -46.8% -305.'2 Sri Lanka -28.2% -66.6% Niger -34.8% -118.1% Niger -17.0h -82.86 Oil Exporters Oil Exporters Cameroon 91.5Z 1622.4% Cameroon 29.2% 57.3% Egypt 4.47 4197. Egypt 3.4% 33.5% Ecuador -26.9% -47.0% Ecuador -17.0% -38.1% Nexico -37.9X -48.3% Mexico -19.5% -39.1% VeneZuela -.66.4% -318.1% Venezuela -78.3% -215.72 Nigeria -299.2X -339.3% Nigeria -41.1' -159.9% indonesia -240.3% -35s.5% Indone2Sia -67.2% -201.2% Algeria -173.2Z -394.9% Algeria -63.9% -112.9% 53 TABLE 10-A Increase of Netuorth lReduction of Debt) uith Resource Dalince Sein Fron CF Taros Of Trade and Mith A Four Percent Real Internst: 1982 1984 1986 CF Netvorth gain Coelbngo Africa $19e,379) ($22,045) ($34,518) Asia ($32,239) ($36,024) f$b7,476) India C$1,332 $28,115 845,613 EMENA $5,134 $23,825 S45,0 5 LAC $31,906 bS,5025 689,930 Lox Incone $8,586 i18,048 $26,336 liddle Income ($42,163) $12,733 $6,634 Non oil Exporting 1117,509 $216,797 $317,699 Oil Exporters (159,672) (1204,064) (311,065) Manufacturers $100,557 $186,742 $284,243 Priary $25,539 $48,103 $59,792 HICs ($7,381) $40,989 S48,015 Hcts Oil Countrin (181,001) ($90,591) (8134,754) Hics Non Oil Countries $73,620 $131,578 *182,769 CF NItnotth gain Coebined (Share of SDP) Africa -10.52 -13! -27m Asia -10.9! -11.71 -22.01 India 9.91 14.61 19.9! IENEA 1.7X 89.6 13.31 LAC 1.7! 10.12 13.72 Los Incom 7.11 15.5! 20.71 Riddle Iccoo -3.1 1.02 0.5! Non oil Exporting 14.0N 28.12 36.0! Oil Expurtirs -30.9S -40.6 -74.0N Manufacturers j5.5! 33.1! 41.41 Priory 8.21 14.91 18.41 HICs -0.8! 5.1! 6.0! Hics Oil Countries -23.7! -28.1! -57.21 ;;cs Non Oil Countrin 13.12 27.81 32.7! SAL Countries 2.3! 9.3! 12.9! Mon SAL Countries -22.01 -26.89 -3! p CF Netmorth gain Coabined (Share of Debt) Mrica -302 -31! -39! Alia -25.6! -24.7! -38.1! India 71.5! 8.9! 110.4! ENEMA 4.0! 17.4! 25.3! LAC 3.71 17.8! 23.0! Lou lncom 14.6! 28.0! 31.4! Riddle Iacom -7.22 1.9! 0.9! Non oil Exporting 31.3! 51.52 64.7n Oil Exportsrs -77.3! -87.9? -111.81 NanufacturrS 38.71 64.3! 33.5? Pri w 14.6! 24.3! 25.5? HICs -1.9! 9.5! 10.3! Hics Oil Countries -58.41 -56.9! -80.21 Hics Non Oil Countries 29.7! 4.4! 5 9.3 SAL Countries 5.57 118.3 21.9? io SAL Contries -46.0! -48.3! -65.42 Notet Asia Escludes India and China 54 TABLE 10 increase of Net llorth (Reduction of Debt) Nith resource balance gains from CF terms of trade and vith a four percent real interest: share of GOP 1979 1980 1981 1992 1993 1984 1985 1986 *CF Nettorth gain Combined GDPshare 1ambia 8.41 25.32 52.31 91.1 137.32 195.4l 237.62 456.01 Chile 7.02 14.22 23.89 S1.9S 85.71 116.89 174.72 217.62 Guyana 6.11 10.22 29.4l 54.12 75.7! 109.5! 126.72 132.52 Papua HIe Guinea -3.71 -1.2! 16.0! 40.1! 60.3! 79.1! 106.5! 126.6! Zaire -2.9! -3.0! 3.3! 13.72 31.3! 66.2! 91.4! 113.9! nalaIi 11.9! 22.1! 31.12 38.9! 45.1! 53.6! 73.9S 98.2t Panama 2.3! 12.3! 27.6! 45.9! 62.98 74.1! 82.2! 95.98 Jamaica 0.6! 2.7! 14.3! 26.7! 39.3! 67.3X 93.7! 89.2X Uruguay 3.7! 7.82 12.31 21.1! 50.5! 67.02 85.17 98.2! Hauritius 5.2! 14.9! 29.6! 47.6% 59.5! 76.5! 99.7! 82.6! Kenya 1.0! 7.5! 19.3! 33.0! 48.2! 57.7! 71.9! 81.4l El Salvador 0.9! 4.9! 16.1! 27.il 39.22 47.9! 67.2! 80.3X Hungary 5.3! 12.5! 18.61 25.1! 36.0! 47.0! 59.1! 76.8! Hadagascar 9.7! 19.6! 31.9! 39.9! 45.51 59.1! 67.57 72.7X Turkey 0.4! 4.6! 12.2! 23.8! 36.6! 49.8! 60.3! 71.6! Guatmeala 2.7! 6.72 15.4! 22.5! 27.2! 30.82 36.6?. 58.5! Chad 8.7! 22.4! 37.0! 51.5! 55.6! 68.4! 57.6! 56.0! Benin 4.32 6.6! 16.9! 26.4! 39.5! 51.0! 59.1! 55.1! Thailand 1.6! 4.6! 11.7! 20.3! 26.1! 32.9! 46.0! 54.7! Cauroon 6.1! 10.8! 17.6! 25.3! 34.0! 39.4! 46.89 !.S Burundi 2.1! 6.1! 15.0! 25.3! 31.3 40.9! 46.2! 52.12 Pakistan -1.12 -0.3! 6.3! 14.1! 23.5! 29.1! 36.5! 47.37. forocco -0.2! 2.6! 10.8! 19.12 29.21 40.9Z 47.9! 42.0! Portugal -1.1! 1.4! 9.6! 18.9% 30.4! 44.1! 51.5! 41.4! Philippines -1.82 -0.3! 5.2! 11.8! 20.5! 28.9! 35.0! S9.6! Brazil -0.3! 2.2! 8.0! 14.89 27.6! 34.1! 39.32 39.4! korea -1.3! 2.61 10.9! 18.89 25.4! 30.7! 37.62 Paraguay 7.9! 6.61 7.0! 10.5! 11.5! 17.5! 33.1! :8.! Sierra Leone -V.8! -9.4! -7.0! -0.12 5.3! 14.62 17.7: I^.O Ivory Coast -6.0! -6.1! 0.3! 13.6! 27.4! 36.6! 41.2! 28.4. Egypt -4.3! -9.0! -6.6! -3.89 1.4% 6.7! 14.3! :7.9! Burkina Faso 7.11 13.42 18.0! 23.52 27.9! 30.89 32.4! 7.1! Costa Rica -3.4! -4.1! 3.9! 11.5! 34.6! 37.1! 40.7! 22.5% Ghana -4.3Z -10.4! -14.3! -12.2! 27.2! 24.2! 23.4! 21.!% Indi4 0.9! 4.3! 7.3! 9.9! 11.2! 14.6! 16.2! 19.9% Dominican Republic 3.82 1.7! 1.4! 5.02 9.3! 18.0% 25.4! :9.92 Yugoslavia -0.4! -0.4! 2.9! 6.4! 11.5! 16.7! 19.9S :4.:: Honduras -5.6! -10.7! -9.1! -2.8! 4.0! 10.5! 15.7! .72 Haiti 0.3! -2.5! -1.62 2.1! 4.7! 7.6! 10.3! 1.3: Central Afr. Rep -0.32 1.12 3.1! 5.0! 9.0! 8.4! 10.6! 9.: Bangladesh 1.0! -0.12 2.3! 7.41 12.1! 11.7! 7.9: 9.4! Colombia -2.7! -3.9! -1.5! 1.3X 3.1! 4.32 5.5% 4.47 Peru -6.5l -9.0! -5.6! -1.9! 0.1! 1.52 4.3! 2.! Mauritania -0.9! 4.5! 8.4L 8.62 13.9! 17.3! 12.5!2 .72 Argentina -2.4! 2.4! 6.3! 9.42 8.7! 6.3!b 6.9! 55 TALE 103 (ten't.l 1979 1980 1991 1982 1983 1994 1995 1986 banda -2.51 1.1? 6.2 9.7? 6.98 3.4? 3.5? -2.21 Ethiopia 0.71 1.6t 2.11 2.2? 2.21 4.91 4.7Z -2.89 Ekudor -5. b2 -10. 82 -9. 52 -6. Bl -6 .82 -3 .22 -3. 32 -3.9n Moaica -2.31 -5. 7 -6.42 -9.6? -7.8? -. 92 -1.31 -4.0O Burma -0.62 -2.22 -4.6? -5.82 -5.89 -5.5? -5.12 -5.97. fali 2.11 4.92 5.02 3.21 -2.4? -11.92 -22.6? -24.1% Jordan -10.0? -7.1? 4.1? 9.3? 9.9? 7.32 4.31 -25.1? Senegal -2.3? -4.62 -11.5? -16.02 -21.1% -27.02 -29.4? -29.7% Togo -14.4? -19.6? -23.1% -26.9? -29.0% -30.3? -31.98 -33. 2? Tutisia -3.9? -7.6? -12.6? -19.2? -23.9? -28.22 -30.7% -37.82 Sri Lanka -9.0? -12.4? -11.9? -12.2? -16.6? -22.61 -29.3? -45.1? Malaysia -9.71 -19.9? -23.7? -23.6? -233.9 -26.52 -34.2? -50.4? suinea Iissau 9.07 22.6? 15.6? 7.62 -5.3? -19.4? -26.62 -55.4% Sudan -4.01 -10.9? -14.6? -27.01 -36.7? -47.3? -56.12 -74.4X Niger -6.32 -4.42 -6.3? -15.62 -31.3? -57.8% -74.5? -79.8? 6uinma -6.12 -12.02 -22.4? -30.1? -34.41 -42.32 -53.61 -51.61 Tauzania 1.5? -10.7? -28.1? -24.31 -30.2? -40.4? -43.4? -9W.6% Algeria -10.9? -27.21 -44.9? -59.32 -69.1% -78.32 -86.2% -100.6! Nigeria -1.82 -9.6? -20.9? -27.7? -35.0? -40.9? -49.6? -119.8% Venezuela -18.32 -38.62 -51.3? -56.11 -60.9? -93.42 -108.89 -146.0% Indonesia -13.3? -29.0? -42.4? -55.62 -81.1? -92,12 -109.1% -170.41 Soelia -4.41 -7.82 -9.1% -7.8? -10.9? -7.2? -0.72 56 TABLE IOC Intreae of Nht lorth (Reduction of Debt) vith resource balance gains froe CF tares of trade asd with a four percent real interest: ratio to debt 1979 1980 1981 1982 1993 1994 1995 1996 CF Networth gain coebined kbtshare Chad 27.62 81.6! 124.82 192.01 211.92 249.5 250.62 U44.02 El Salvador 3.62 19.1! 49.21 66.5! 86.1! 115.0! 147.3! 187.2! Chile 15.51 32.2! 49.52 72.9! 93.12 112.4! 136.6! 174.9! Iauritius 17.2! 36.9! 60.5! 98.6! 115.1! 145.7! 156.12 170.2! 6uatteala 18.12 45.0! 105.0! 127.3! 136.9! 124.6! 137.7! 159.89 Camroon 16.1! 30.1! 53.5% 70.7! 96.22 119.2! 130.9! 151.5: Zaaiba 9.3! 30.3! 58.41 96.92 121.4! 141.0! 139.3% 150.3! Uruguay 20.4! 47.N! 63.8! 73.69 82.11 107.4! 113.1! 147.9! Papua New Guinea -13.72 -4.41 33.89 58.2! 76.7! 93.1! 108.5! 138.5! Turkey 1..! 13.6! 36.7! 64.0! 92.5! 114.7! 122.6% 126.9% Thailand 6.5! 1&.98 39.01 61.3! 75.6! 91.6! 100.71 123.3! Kenya 2.3! 15.4! 39.3! 59.8! 73.89 91.0! 96.0! 119.5! Burundi 13.6! 35.42 83.0! 113.5! 110.1! 117.7! 111.5! 116.7! Pakistan -2.5! -0.89 16.9! 38.3! 57.5! 77.3! 90.0! 115.0% India 6.92 39.1! 61.92 71.5! 78.31 89.9! 94.82 110.4% flalawi 18.3! 33.9! 47.2! 52.62 62.1! 73.2! 85.52 C7.9% Hungary 356.52 26.9! 42.21 64.5! 78.62 94.89 93.5t 105.42 Zaire -6.02 -6.32 6.1% 26.2! 45.92 65.3! 75.1! 104.8% Panau 2.4t 14.7! 31.82 50.1! 62.6! 77.5! 94.4 :00.3t Brazil -1.2! 7.32 26.5% 43.5! 57.6! 68.4! 93.32 94.82 Jenin 10.5! 18.3! 37.0! 41.82 54.32 74.89 76.0! 96.6! Korea -3.72 5.4! 22.5! 36.0X 48.9X 61.41 68.4! 83.37. Portugal -2.92 3.9! 19.82 32.5X 43.41 57.2! 63.8t 71.5! Paraguay 33.6! 31.5! 35.3% 45.02 46.4! 53.7! 59.0! 68.21% Hadagascar 34.4! 51.3! 57.5! 60.5! 62.3! 66.3! 63.22 56.82 Sierra Leone -23.51 -24.62 -17.89 -0.2! 15.1! 36.5! 46.2% 62.4? 6uyana 5.1! 7.9! 20.1! 28.5! 38.82 50.7! 55.4U s.:2 Burkina Faso 27.7! 51.3! 61.02 68.4! 66.11 64.7! 59.0% .3l Janaica 0.8! 3.98 17.0! 27.6! 38.52 46.1! 48.89 t4., Bhana -13.92 -36.5! -42.6! -37.0! 73.6! 60.4! 49.l7% Philippines -3.9! -0.62 9.61 19.42 29.5! 39.5! 43.72 42.61 Egypt -6.1! -11.7! -8.82 -4.92 1.92 9.5! 18.6! 34.9t Morocco -0.4! 5.4! 16.0! 25.1! 30.9! 38.0! 35.6% 23.92 Haiti 1.32 -12.1! -5.72 5.8! 13.5! 21.2! 28.3! 31.6! Dooinican Republic 12.2! 5.4! 4.1! 14.0! 20.4! 29.3! 34.2l 31.6! Ivory Coast -11.42 -10.89 0.4! 12.9! 24.0! 29.4! 29.2! 2S.9% Costa Rica -6.52 -7.2! 3.2% 9.7! 25.7! 34.0! 34.91 2!.42 Central Afr. Rep -1.89 4.71 9.6! 15.5! 20.89 20.7! 22.2! :9.0% Honduras -10.32 -19.1! -14.32 -4.3! 5.7! 14.5! 19.32 16.7! Bangladesh 3.89 -0.3! 7.2! 19.4! 26.72 29.2! 19.32 16.52 Colombia -13.0! -18.6! -6.4! 4.89 10.6! 13.6! 13.3! 9.5% Peru -11.0! -19.6! -13.71 -4.0! 0.1% 2.3! 5.3! .72 lauritania -0.89 3.9! 6.42 5.7! 8.5! 9.7! 6.1! ) 2 Somalia -9.0! -14.9! -17.02 -14.3! -17.1! -16.2! -1.2! -2.7! Prgentina -5.9! 5.1! 10.22 12.3! 12.6! 10.6! 9.32 -;.32 57 TlALE IO (can't.) 1979 1980 1991 1982 1983 1984 1985 1986 Ecuador -11.62 -21.21 -17.02 -10.91 -9.61 -3.91 -4.72 -4.9l lexica -7.2l -18.62 -19.62 -18.72 -12.02 -6.92 -2.32 -5.02 Ethiopia 3.6 9.32 8.0l 7.82 7.62 14.9l 11.9l -6.6l Rwanda -16.52 6.92 41.62 63.42 52.82 19.1l 16.61 -9.32 Burm -2.62 -8.71 -15.52 -16.91 -15.22 -14.62 -11.32 -12.92 Mali 5.7n 11.12 9.32 4.52 -2.62 -9.92 -16.22 -21.6l Jordan -18.61 -13.42 7.02 14.42 12.22 9.62 4.62 -27.62 6uinea Bissau 15.82 18.32 17.72 8.02 -4.62 -11.32 -14.52 -30.22 Togo -12.62 -20.42 -23.52 -24.12 -23.12 -25.89 -24.42 -31.32 Senegal -5.92 -10.72 -20.32 -25.22 -27.42 -31.42 -30.92 -37.02 Tunisia -8.32 -18.12 -28.22 -36.92 -45.31 -50.82 -49.32 -54.62 Malaysia -42.12 -74.52 -64.62 -47.42 -39.82 -47.92 -51.22 -62.5% Sudan -9.51 -15.72 -20.02 -32.52 -39.92 -45.62 -50.71 -6b.3l Sri Lanka -17.32 -25.92 -21.52 -20.32 -28.31 -44.52 -49.32 -71.3% Guinea -8.92 -19.52 -29.72 -40.02 -49.92 -67.52 -75.89 -19.02 Tanzania 3.72 -21.62 -40.32 -52.02 -57.42 -69.32 -74.82 -1:.61 Niger -21.12 -12.92 -13.32 -31.89 -60.82 -94.12 -91.92 -113.72 Venezuela -37.12 -77.72 -106.42 -119.12 -110.42 -127.62 -155.52 -7 5. 3t Nigeria -23.22 -99.62 -165.98 -201.72 -167.12 -200.98 -227.22 .252.Il1 Indonesia -39.52 -108.32 -172.72 -198.92 -218.02 -244.62 -257.92 -296.98. Algeria -20.22 -61.62 -113.12 -160.98 -226.52 -293.92 -318.12 -352. 2: 1T(:I1P.F 1 Changes of Investment and Resource Bal. 1979-82 to 1983-86 (Shore of GOP) 0.05 - 0.04 - 0.03 - Guinea issou _ bropica 0.02 - i Cameroon ffi 0.01 E ll Ethiopia 0 0- *pa~~~~~E[!rkey -0.01 - 1ol Pakistan 0 m0 E Koreo o ~~~~~0 0 Uoim * -0.02 - *hoilon 2 -0.03 U n Unisia ° Thailand -0.04 * AJgeri aii KenD y i -0.05 - ° 13OE MExhil,* -0.06 0 -0.07 o 0 U U Magascor V - -0.08 UruguGyU* l Malowi 0 % -0.09 IEI Argentina 2,) -0.112U Nigeria 3 0 O -0.12 I0 -0.13 El Philippines 0 Ivory 4ost -0.14 1 Jorda -0.15 a -0.1 6- _______________ _ * 1I4 ger I I IIIr -0.06 -0.02 0.02 0.06 0.1 0.14 0.18 Change of Resource Balance Share of GDP Correlation Coefficient: -.63 * - ~~at 52' ~ 59 FIGlURE 2a NET TRANSFERS 1978-1982 ($B) OUNrAY ra:Ess vs. PIMMt OEw9s 17 is VNAYFClso R la 14 TW%TE NEr 1ROM 11 10 9 17 CTrAL NET a TarAL NET OFMiCIAL \x A,xFEFt 4 2 0' vQ.LuNTARV AccE PpOsMz OsTom NET TRANSFERS 198,3-1986 ($8) VOLAmY AVCCM VS. PROBLC wrEnMS 2 -lo-16 -18 -n6 -1n -204 -26 -.n ZZVOLUNTRY ~aC P PROBLEM OSMtWS 60 FIGURE 2b NET TRANSFERS SHARE OF GNP (1978-1982) VOUNr ACCES VS. PM~ma. S ::a A 0024 OLNEr TRANW 1CSNP 0.0=F 0.02 0.016 0.016 TAL PEr PR%91E T 0.014 TRANSFERSALN P L 1983-198 /) 0.012- 0.01 0.0065 0.0065 0.004 - 0.002* = V.LINTM AC£SS PROlEM OETOUR! NET TRANSFERS SHARE OF ONP (198,3-1985) o.a)15 V~'OLLi4AMY AOES VS. PFVMMJ DraWs 0- -0.005 ALPET P%TlE T -0.01 -0.015 -0.02- -0.025 -0.0.3- -0.04- vauLNrARf? ACcEES wiotruZ CriwF FIGURE 3 CREDIT CONTSTR,.iNED COUNTRIES: PRIVATE NET TRANSFERS AND ACTUAL DEBT 10 BOLIVIA 0.01 - 0 - 0oiu; -0.01 - 0 NIGERIA v -0.02- z -0.03 - URUGAY YUGUSLAVIA OBRAZI -0.04-3 JAMAICA of n6 -0.05 - 0 COTE DHVOIHIUPPINES 0 MEXICO ( -0.06 - of ~~~~~~~OVENEZU%AARENTINA I'- -0.07- z O ECUADOR , -0.08 - 0 COSTA RICA > -0.09 - -0. 1 0 CHILE -0.12 - O CHILE 0 20 40 60 80 (Thousands) COMMERCIAL+ST+PNG DEBT 1982 (SB) 0 1:MOROCCO 2: PERU Correlation Coefficient: -.12 (-.34 excluding Brazil and Mexico) Statistically Significant at 5% Level FICURE 4a WORLD BANK ADJUSTMENT LENDING & TOTAL NET TRANSFERS (1982-1986) 0.02 - 0.01 0 NUNGARY 03 TUNISIA 0 MOROCCO 0.01 - o0 ZIMBABWE Ci TURKEY 0 - n PAKISTAN I ~IALL N&PAIHND No -0.01 0 NIGERIA OJA AICA 0 KENYA -0.02 _ I:j3 * 4 SAIS z 0 -0.0 MAURITIUS 0 COTE D'IVORE .. -0.03 -0.04 03 ARGENTINA U) 0 MEXICO 0 PANAMA z -0.05 - z -0.06 0 ECUADOR 0 COSTA RICA O -0.07 - 0 -0.08 03 CHILE -0.09 I-i I I I I I I I I I I I I 0 0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 SAL+SECAL/GNP (AVG. 1982-1986) 0 1:PHL 2:BRA 3:KOR Correlation Coefficient: -.01 (.24 including Mauritania and Zambia - not shown) FIGURE 4b WORLD BANK ADJUSTMENT LENDING & NET TRANSFERS FROM OFFICAL CREDITORS 0.03 - - JANICA ~~~j 0.025 ~~~~~~~~~~0 ZAMBIA , 0.025 - OZl 10 S 0.02 - 0 KENYA O a MOROCCO > 0 ZIMBABWE z 0.015 - a TUNISIA z lr 0.01 03 HUNGARY 13 CHILE PAA i DOCOSTA RIA z 0 ECUADOR _ 0.005 JI ALL NfN SAPLSKN 4 ALL~~9 0 PAKISTAN w bl 02 a A%ISALS * COTE D'IVOIRE z 0 NIGERIA -J ~0- 0 KOREA 0 MAURITIUS O -0.005 0 YUGOSLAVIA 0 TURKEY 0 0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 SAL+SECAL/GNP (AVG. 1982-1986) 0 1:PHL 2:BRA 3:MEX Correlation Coefficient: .44 Statistically Significant at 5% Level FIGURE 4c WORLD BANK ADJUSTMENT LENDING & NET TRANSFERS FROM PRIVATE CREDITORS 0.02 - 0.01 0 TURKEY 0 14UNCARY ~~~~~~~0 ZAMBIA e 0- o HUNGARY I 0 3 0 TUNISIA c4 0 MOROCCO ! -0.01 1 ALL NON SALS 0 5 -0.02 - KOREA IL 0 2 #*h4 SALS 0 MAURMUS z o -0.03 - OCOTE D'IVO1RE 0 KENYA JAC °C _o,o - O Y - OS>VV n~~~~~~~~~~~~~~~~~ JAI IACA Y-0.0U - iGOSLAVIA w -0.05 - A~H 0 PANAMA ,_ -0.06 - z -0.07 - -0.07 0 ECUADOR 0 COSTA RICA -0.08 - 0 0.9 0 CHILE -0. - I I 1 I I I I I I I I I I I I I I 0 0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 SAL+SECAL/GNP (AVG. 1982-1986) 0 1:PHL 2:BRA 3:PAK Correlation Coefflcient: -.15 FICURE 4d IDA ADJUSTMENT LENDING TO THE LICs & TOTAL NET TRANSFES 0.07 - a SENEGAL 0.06 - O BURUNDI 0.05 - 0.04 - 0 SOMALIA O BURKINA ElC.A.R II ALL NON-SALS a. 0.03- a ABA O 0 MADAGASCAR 0 OSIERA LEONE 0.02 -0 GHANA OTANZANIA ffi 0.01 31 a,SUDAN s WALL SALS 0^S ° - 0 s GUINEA z O NIGER .( -0.01 - O 0 KENYA -0.02 - 0 ZAIRE -0.03 - . 1 1 1 1 1 1 1 1 1 0 0.002 0.004 0.006 0.008 0.01 0.012 SAL+SECAL/GNP (AVG. 1982-1986) 0 1:MALAWI 2:PAKISTAN Correlation Coefficient: .02 FIGURE 4e IDA ADJUSTMENT LENDING TO THE LICs & NET TRANSFERS FROM OFFICIAL CREDITORS 0.08 - 0 SENEGAL 0.07- N 0.06 0 BURUNDI IL 0.05 z oN 0 SOMALL& 0 MADAGASCAR oc 0 MALWI BURKINA w 0.04- SUDAN I I ALL NON-OiLS 3 NGER C.A.R-R 0.03 _ O TANZANIA 0 GHANA 0 ABIA A 0.02 - * ALL SALS 0 KENYA < *0 SIERA LEONE o 0.01 0 ZAIRE 0 PAKISTAN 0 GUINEA 0- I I I I I I I I I I I 0 0.002 0.004 0.006 0.008 0.01 0.012 SAL+SECAL/GNP (AVG. 1982-1986) Correlation Coefficient: .05 (-.18 including Togo and Cuiner. Bisseau - not shown) FIGURE 5a Investment Change & Int. rate shock Middle Income Countries 0.04 Jamaica U 0.03 0.02 Comer on 0 0.01 0 Turkey 0 00 Indonesiallipua New Guinea 0 0 -0.01 Korea 0 Costa Rica 0 -0.02 - Morocco 0 I -0.03 I -0.03 -Tunisia 1 -0.04 _ Guyana 0 -0.04 ~~~~Alg eria hlaziilm c -0.05 Domin. Rep 0 Mexico 0.06 Eg Guatemala 0 Chile * * -0.06 Egpt 0t g -0.07 y oPeru * Ecuador- c Urugu ay 0 c -0.08 - ffi -0.09 - Argentina U -0.1 - Panama Portugal 0 oJ -0.11 - Nigerp Vene?dea0 -0. 1 2- -0.1 3 - Philippines U Ivory Coast a -0.14- Jordan __._l_l__ -0.05 0.05 0.15 0.25 0.35 Interest rate shock 1981 to 1986 Correlation Coefficient: -.10 FIGURE 5b Change in Res Bal & Interest Rate Shock Middle Income Countries 0.16 - Jordan 0.15 0.14 Ivory Coast 0 to 0.13 Ii) 0.12 - ID 0.11 - Comern on 0 ° 0.1- Portugol ° 0.09 - Mauritius 0 T 0.08 - Uruguoy 0 0.0 0.07 - Kproo 0 ~~~~~~~~~~~~~~~~Chile U 0.06 - Philippines M Mexico E+ Panama o 0.05 - BrOzil U + Domin. fEeo c U o.ox - Y"uos°o«clcaSgentina e Ecuador E 0.04 Mr cc%gantina0 c 0.03 - Eg ptrgnilG Mayia Venezuela 0 0.02 Guya na 0 ~Tre c 0.01 - + Tu rkey o 0.01 Papua New Guinea 0 0 - araguac' Aleria0 + Nigeria -0.01 Tunisia Jamaica 0 C) -0.02 - -0.03 - -0.04 - El Salvador 0 -O_OS_- Indonesia al -0.05 0.05 0.15 0.25 0.35 Interest Rate Shock 1981-1986 Correlation Coefficient: .14 FIGURE 5c Invest. Change & Interest Shock 81-86 Low Income Countries 0.05 -_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 0.04 Central AUr. RepO 0.03 Mali OBurundi 0 0.02 R a 0.01 o Ghanaghhopi o 0R O - Sudan O Indl_Cl o -0.01- + Pakistan -0.02 Banglades OZdre O 0 -0.03 Guinea 0 Mait O -0.04 Zambia a + Sierra Leone Kenya ° + Sri Lanka -0.05 c -0.06 Madagascoro Bur a a3 -0.07- + Tanzania CaOMlw -0.08 - Chado | MdowiO| t; -0.11 Togo 0 .2 -0.13 ~1enin 0 -0.14 -0.15 MGaurita nia a -0.1- I I I- -0.09 -0.07 -0.05 -0.03 -0.01 0.01 0.03 0.05 0.07 Interest Rate Shock 1981-1986 Correlation Coefficient: -.16 FIGURE 5d Change in Res Bal & Interest Rate Shock Low Income C;ountries 0.17 - . 0.16 - Benin 1 0.15 - 0 0.14 - A 0.13 o 0.12 - Mauritania 0 °. 0.11 - C4 0.1 OD Togo 0 0.09 > 0.08- Sierra Leone 0 + Moad goscar Maoawi O v 0.06 - Kenya°+ Sri Lanka 3 0.05 NigerO 0 0.04 - Zambia O Senegal 0 0.03 Zaire a c 0.02 - Sudan O Haiti O & Td&Aln 0 Bangladesh O 0 n O BuruMdd; O + Pakistan o 0 - Guinea ORw-da u -0.01 - wntral AMr. Repu -0.02 -0.03 Mali E1hiopia -0.04 - -0.09 -0.07 -0.05 -0.03 -0.01 0.01 0.03 0.05 0.07 0.09 0.11 Interest Rate Shocks 1981 to 1986 Correlation Coefficient: .22 FIGURE 6a Investment Change & TOT Shocks to 1986 Middle Income Countries 0.04 Jamaica 0 0.03 to 0.02 - , ameroon 0 0.01 -Tu rkey 0 -euGrinea* It idonesia 0 Yugoslavian Paua New Guinea 0 -0.01 - Costa Rica -orea + El Salva0or Mt rocco o -0.02 Mal sia 0 Thailand O CD -0.03 - Tunisia 0 tN -0.04 - Algeria 0 Honduras 0 zil * Guyana 0 ~ -0.05 - Mexic0amin. p0 Hungoryo 4.1 -0.05 Guatemala 0 Chile U -G4.06 - gypt 0. -0.07 - Ecuador* Peru O I 0 Uruguay o > -0.08 - c c -0.09 - Argentina U -0. 1 Po gal Nigeria * Panama 0 -0.f' uelaEa -0.12 - -0.13- Phil pines 0 -0.14 - Jor1an 0 -2.5 -1.5 -0.5 0.5 1.5 2.5 TOT Shock to 1986 Correlation Coefficient: .20 FIGURE 6b Change in Res Bal & TOT Shock Middle Income Countries 0.16 - Jordan O. 0.15 0.14- t0 0.14 - Ivory Coast SD 0.13 0.12 0.11 Cameroon a v- 0.1 Poi tugal ° 0 0.09 0 0.08 - Uruguay O 0.07 -ahle1 g 0.06 - Mexico 0 Phi piea Chile D 0.05 - Panama E3 O+ Brazil +Yua.osIvia 0.04 - Argentina0 M rocco _ 0 Otrw zuela 0 Malaysia 0 Peru land + G;untemala 0.02 - Guya O 0.01 Tu rke 0 Guna _______________________________ Papua New Guinea O § O0- Nigeria °AMgeria O ColombiI guOy 1 ° -0.01 - Tunisia l Jamoica a o) -0.02 - -0.03 - -0.04 - El SalvadorO I donesia O -0.05-1III - -2.5 -1.5 -0.5 0.5 1.5 2.5 TOT Shock to 1986 Correlation Coefficient: .21 FICURE 6c Change In Investment & TOT Shock to '86 Low Income Countries 0.05 0.04 Central Mr. tep 0 0.03 G ,IAali 0 Burundi O lo ~~~~~Guinea Blssauu CD 0.02 - Rwan do3hano3Rwanda Ethiopia Ghana 1 0- Sudan O Li -0.01 Senegal 0 Brino FasoIl + Pakistan NW -0.02 - Banglad sh O -0.03 - Guinea D Ha ti O 1 o.004 - Sri Lanka 0 Kenya O Serra Leone O -0.05 - -0.06 t -0.07 - Tanzonia O Burma O MadagascarD 07 Tanzania D Chad 0 alawi 20.08 Ca aow 0.09 c -10.1 0.11 -0.12 TogoO -0.13 - Benin 0 -0.14 -0.15 -NigerO Maurita ia 0 -0.16- -1 -0.6 -0.2 0.2 0.6 1 1.4 TOT Shock to 1986 Correlation Coefficient: 0.00 FIGURE 6d TOT Shock & Change in Res Bal Low Income Countries 0.18 - 0.16- Benin 0 0.14- 03 I 0.12 - Mourito ia O 0 0.1 ~~~~~~Togo 0 CD 0.08- TogoO Sierra Leone O3 MadagascarOJAalawi0 I 0.08 Sri Lanka 0 Kenya El 0.04 - Senegal O C 0.02 - Sudan O H iti D anzania O Do nglad Ish ° ______________India D Pa,ds &repfdi Guinea 0 e O .C ~~~~~~~~Cent IM0r4 gp a Malmniopia C -0.04 - -0.06- 1Guinw BjaO I I I -0.9 -0.7 -0.5 -0.3 -0.1 0.1 0.3 0.5 0.7 0.9 1.1 TOT Shock Correlation Coefficient: .15 75 APPEND1I ; Classification of 70 RALI Countries O0 Sub-Saharan 20 Latin America 10 Asia 21 0 EMENA 17 Highly Indebted I1 Ley-Income 39 Mi:dle-Incone Africa I Caribbean Ccuntries C.untries IJ Countr.es Benin Argentina Bangladesh Algeria Argentina Bangladesh Algeria Burkina Faso Bolivia Buret ugypt Bolivia Benin Argentina Burundi Brazil Indonesia Hungary Brazil Burkina Faso Bolivia Caseroon Chile Korea Jordan Chile Bursa Brazil Central Afr Rep Colombia Malaysia Morocco Colcmbia Burundi Caseroon Chad Costa Rica Nepal Pakistan Costa Rica Central Afr Rep Chile Cote DOIvoire Dominican Rep Papua New 6uinea Portugal Cate O Ivoire Chad Colombia Ethiopia Ecuador Philippines Tunisia Ecuador Ethiopia Costa Rica Ghana El Salvador Sri Lanka Turkey Jamaica Ghana Cote DOIvoire Guinea 6uateeala Thailand Yugoslavia Mexico Guinea Oceinican Rep Guinea-Bissau Guyana Morocco Guinea-Bissau Ecuador Kenya Haiti Nigeria Haiti Egypt Madagascar Honduras Peru Kenya El Salvador Malnai Jaeaica Philippines Madagascar Guatemala Mali Mexico Uruguay Halaui Guyana Mauritania Panama Venezuela Kali Honduras Nauritius Paraguay Yugoslavia Mauritania Hungary Niger Peru Nepal Indonesia Nigeria Uruguay Niger Jamaica Rwanda Venezuela Pakistan Jordan Senegal Rvanda Korea Sierra Leone Senegal Malaysia Somalia Sierra Leone Mauritius Sudan Somalia Mexico Tanzania Sri Lanka Morocco Togo Sudan Nigeria Uganda Tanzania Panama Zaire Togo Papua New Suv^ea Zambia Uganda Pariguay Zmababwe Zaire Peru Zambia Philippines Portugal Thailand Tunisia Turkey Uruguay Venezuela Yugoslavia Zimbabwe Notes: I/ GNP Per Capita at 19B5 is below $450. Data for Bolivia, Nepal, Uganda, Zimbabwe: incomplete or not available. 21 Asia Excludes India and China 76 APPENDIX I (Cont'j) 8 Oil Exporting 49 Nonoil, Nonmanufacturing 24 Countrias with 16 Prcblem eobtors 49 Adjustment Landing 22 Non SAL C.untries Countrin CPrisary) Voluntary Ac:uss (:redit crnstrained !SAL I SECAL) C3untr:es Countries Crcuntries! Algar4a Argentina Madagascar Algeria Argentina Argenti'a Algeria Caneroon Bangladesh Malawi CaWeroon 9olivia Bangladesh sen:n Ecuador Benin aaysia Calzmb:a Brazil 8Blivia Peraa Egjpt Bolivia !ali Dominican Rep Chile Brazil Ciaar:cn Indonesia Burkina Faso Mauritania Egypt Ccst& Rica Burkina fiso Ca'd Nexico Surea Mauritius El Salvador Coto D' wvoire 9urundi hcainxcan R Niguria Burundi Nepal Guatemala Ecuador Central African Rep. Egypt Vene:uela Central AYr Pep Nigsr Guyana Jamaica Chile El Sa1qi!;r Chad Panama Honduras Mexico Colombia Eth0;0aa Chile Papua New 6inea Hungary Morocco Costa Rica Guatecala Colcobia Paraguay Indcnnsia NigerLa Cote D'lvoire Haiti Costa Rica Peru Jordan Peru Ecuador Honduras Cote d'lvoire Rianda Korea PhilippinpS Ghana Jordaa Dominican Rep Senegal Malaysia Uruguay Suing& Malaysla El Salvddor Sierra Leone Mauritius Venezuela Guinea-Bissau Mali Ethiopia Somalia torocco Yugoslavia Guyana Papua !N Sui;-ea Ghana Sri Lanka Panaea Hungary Paraguay Guatemala Sudan PIpua New Guinea Indonesia Peru Guinea Tanzania Paraguay Jaaica Portugal Guinea-Bissau Togo Portugal Kenya Rwanda Guyana Uganda Thailand Korea Sri Lanka Haiti Zaire Tunisia Madagascar Venezuela Honduras Zambia Turkey Malaui Jamaica Zimbabw ZibabDue Mauritania Kenya lauritius Mexico Morocco Nepal Niger 3 Manufactured Nigeria Exporting Pakistan Countries 31 Panaea Philippines Senegal Brazil Sierra Leone Hungary Soalia Jordan Sudan Korea Tanzania Morocco thailand Pakistan Togo Philippines Tunisia Portugal Turkey Thailand Uganda Tunisia Uruguay Turkey Yugoslavia Uruguay Zaire Yugoslavia Zambia Zi2babwV Notes: 3/ 1995 Manufacturing exports as I of total exports exceeds 35Z Data for Bolivia, Nepal, Uganda, Zimbabwe: incomplete or not available. PPR Working Paper Series Contact Title Author Datc for paper WPS206 The Effects of Single-Sex Schooling on Student Achievement and Attitudes in Nigerda Valerie E. Lee May 1989 C. Cristobal Marlaine E. Lockheed 33640 WPS207 Occupational Training Among Peruvian Men: Does It Make a Difference Ana-Maria Arriagda May 1989 C. Cristobal 33640 WPS208 Effectie Primary Level Science Teaching in the Philippines Marlaine E. Lockheed May 1989 C. Cristobal Joserina Fonacier 33640 Leonard J. Bianchi WPS209 Can the Industrial Countries Return to Rapid Growth? Space Seminar International Economics Department and International Economic Analysis and Prospects Division WPS210 Notes on Cash-Flow Taxation Roger H. Gordon June 1989 A. Bhalla 60359 WPS211 Coffee Pricing Policies in the Dominican Republic Panos Varangis May 1989 D. Gustafson 33714 WPS212 Beyond the Debt Crisis: Alternative Forms of Financing Lessard WPS213 Conditionality and Debt Relief Stijn Claessens June 1989 S. King-Watson Ishac Diwan 33730 WPS214 Adjustment and the Labor Market Peter R. Fallon June 1989 R. Luz Luis A. Riveros 61762 WPS215 Adjustment and Income Distribution: A Counterfactual Analysis Francois Bourguignon William H. Branson Jaime de Melo May 1989 M. Amcal 61466 WPS216 Price and Quality Effects of Vers-Revisited: A Case Study of Korean Footwear Exports Jaime de Melo June 1989 M. Ameal L Alan Winters 61466 WPS217 Public Debt, North and South Helmut Reisen WPS218 Public Finance, Trade and Development: Thc Chilean Experience Vittorio Corbo July 1989 A. Oropesa 61758 WPS219 Rural Credit in Dcveloping Countries Avishay Braverman June 1989 C. Spooner J. Luis Guasch 37570 PPR Working Paper Series Contact Title . Author Date for naner WPS220 Capacity Building for Policy Analysi Samuel Paul July 1989 Bt Madrona David Steedman 61712 Francis X. Sutton WPS221 How Does Uncertainty About the Real Fxchangc Rate Affect Exports? Ricardo J. Caballero June 1989 A. Oropesa Vittorio Corbo 61758 WPS222 Why Stabilisatior. Policies in Zambia Did Not Succeed Christopher Colclough WPS223 Overvalued and Undervalued Exchange Rates in An Equilibrium Optimizing Model Jose Saul Lizondo WPS224 The Economics of the Government Budget Constraint Stanley Fischer May 1989 S. Fischer 33774 WPS225 Targeting Assistance to the Poor Using Household Survey Data Paul Glewwe June 1989 B. Rosa Oussama Kanaan 33751 WPS226 Inflation and the Costs of Stabilization: Historical Cases, Recent Experiences and Policy Lessons Andres Solimano WPS227 Institutional Reforms in Sector Adjustment Operations Samuel Paul WPS228 Economic Performance of Developing Countries in the 1980s Robert Lynn F. Desmond McCarthy WPS229 The Effect of Demographic Changes on Saving for Life-Cycle Motives in Developing Countries Steven B. Webb July 1989 E. Khine Heidi Zia 61765 WPS230 Unemployment, Migration and Wages in Turkey, 1962-1985 Bent Hansen July 1989 J. Timmins 39248 WPS231 The World Bank Revised Minimum Standard Model Doug Addison May 1989 J. Onwuemene- Kocha 61750 WPS232 Women and Food Security in Kenya Nadine R. Horenstein June 1989 M. Villar 33752 WPS233 Public Enterprise Reform in Adjustment Lending Jcnn Nellis WPS234 A Consistency Framework Macroeconomic Analysis William Easterly June 1989 R. Luz 61760 WPS235 Borrowing, Resource Transfems and External Shocks to Developing Countries: Historical and Counterfactual Steven Webb July 1989 E. Khine