SWP562 Capital Accumulation in Eastern and Southern Africa A Decade of Setbacks Ravi Gulhati Gautam Datta WORLD BANK STAFF WORKING PAPERS Number 562 /-/- WORLD BANK STAFF WORKING PAPERS MV/5- Number 562 57 4u J 7 Capital Accumulation in Eastern and Southern Africa A Decade of Setbacks Ravi Gulhatia Gautam Datta The World Bank Washington, D.C., U.S.A. Copyright © 1983 The International Bank for Reconstruction and Development / THE WORLD BANK 1818 H Street, N.W. Washington, D.C. 20433, U.S.A. First printing April 1983 All rights reserved Manufactured in the United States of America This is a working document published informally by the World Bank. To present the results of research with the least possible delay, the typescript has not been prepared in accordance with the procedures appropriate to formal printed texts, and the World Bank accepts no responsibility for errors. The publication is supplied at a token charge to defray part of the cost of manufacture and distribution. The views and interpretations in this document are those of the author(s) and should not be attributed to the World Bank, to its affiliated organizations, or to any individual acting on their behalf. Any maps used have been prepared solely for the convenience of the readers; the denominations used and the boundaries shown do not imply, on the part of the World Bank and its affiliates, any judgment on the legal status of any territory or any endorsement or acceptance of such boundaries. The full range of World Bank publications is described in the Catalog of World Bank Publications; the continuing research program of the Bank is outlined in World Bank Research Program: Abstracts of Current Studies. Both booklets are updated annually; the most recent edition of each is available without charge from the Publications Distribution Unit of the Bank in Washington or from the European Office of the Bank, 66, avenue d'Iena, 75116 Paris, France. Ravi Gulhait is the chief economist of the Eastern Africa Regional Office of the World Bank; Gautam Datta is a consultant to the World Bank. Library of Congress Cataloging in Publication Data Gulhati, Ravi. Capital accumulation in eastern and southern Africa. (World Bank staff working papers ; no. 562) Bibliography: p.'' 1. Saving and' investment--Africa, Eastern. 2. Saving and investment--Africa, Southern. 3. Capital producti- vity--Africa, East'ern. 4. Capital productivity--Africa, Southern'. I. Datta, Gutam, 1947- . II. Title. III. Series. RC860.Z9S34 1983 332'.0415'09676 83-5899 ISBN 0-8213-0169-1 ABSTRACT The paper attempts to analyze the magnitude of the setback in capital accumulation in Eastern and Southern Africa and the proximate causes of this phenomenon. The sample consists of 16 countries and available data for the late 1960s and 1970s are explored. Given the weakness of the statistics, the authors rely more on expert observations than on rigorous quantitative assessments; although available data are analysed. Capital formation increased fairly rapidly during 19 67-1974 but then slowed down considerably. Investment was financed to a considerable extent by external concessional assistance; rapid growth in such funds during the late 1970s helped offset declining national savings rates to some extent. The setback in investment rates was greatly accentuated by a large and widespread deterioration in the productivity of capital brought about by the impact of government policy, strained absorptive capacity and a variety of exogenous factors. -ACKNOWLEDGMENTS We are grateful to Ram Agarwala, Rolf Gusten, Robert Armstrong and Peter Hansen for valuable comments on an earlier draft of this paper. CONTENTS Section Page No. I. Introduction . .................................... 1 II. First, A Look At the Record ....................... 4 III. Behavior of Investment ............................ 10 IV. Productivity of Capital ........................... 23 Capacity Utilization 24 Sector-Mix and Sectoral ICORs 28 Absorptive Capacity 30 Impact of Government Policy 31 V. Conclusion ......................................... 34 Figures Figure 1. The Investment Ratio and GDP Per Capita ....... 13 Figure 2. The Median Ratios of Savings and Investment to GDP, Eastern Africa ..... 16 Figure 3. The Savings Ratio and GDP Per Capita .......... 18 Figure 4. The Savings Ratio and Terms of Trade, Zambia and Zaire ..................................... 20 Figure 5. The Savings Ratio and Terms of Trade, Ethiopia and Uganda .................................... 21 Page No. Annex I - Statistical Tables Table 1 The Growth of GDP in Constant Prices, Eastern Africa and Comparator Countries, 1960-70 and 1970-79 ................................................ 38 Table 2 The Growth of GDP in Constant Prices, 1967-78 and Sub-Periods 1967-73 and 1973-78 ..................... 39 Table 3 The Growth of Gross Domestic Investment in Constant Prices, Eastern Africa and Comparator Countries, 1960-70 and 1970-79 ................................... 40 Table 4 The Growth of Gross Domestic Investment in Constant Prices, 1967-78 and Sub-Periods 1967-73 and 1973-78 .... 41 Table 5 The Incremental Capital Output Ratio In The Periods 1961-68, 1967-73 and 1973-79 .......................... 42 Table 6 Incremental Gross Capital Output Ratios in Five Developed Countries, 1967 to 1974 ...................... 43 Table 7 Historical Incremental Capital Output Ratios In Developed Countries ................................... 44 Table 8 The Ratio of Gross Domestic Investment to GDP, 1967-78. Three-Year Moving Averages ................... 45 Table 9 Index of Real Gross Fixed Capital Formation By the Central Government .................................... 46 Table 10 The Ratio of Gross National Savings to GDP. Three-Year Moving Averages, 1967-78 .... ............... 47 Table 11 Terms of Trade Estimates, 1967 to 1978. Three-Year Moving Averages ........................................ 48 Table 12 Gross National Savings as a Percentage of Gross National Investment. Three-Year Moving Averages, 1967-78 .... ... 49 Table 13 Net Official Development Assistance as a Percentage of External Resources Inflow ........................... 50 Table 14 Direct Investment as a Proportion of Long-Term Capital Inflows ................................................ 51 Table 15 New Private Direct Investment From DAC Sources .... ..... 52 Page No. Annex I - Statistical Tables (Cont'd) Table 16 The Stock of Foreign Direct Investment in Eastern Africa, End 1978 ............................... 53 Table 17 Gross Eurocurrency Credit to Eastern Africa .... ........ 54 Table 18 Capacity Utilization in Selected Sectors in Tanzania, 1978-79 ...................................... 55 Table 19 Capacity Utilization in a Sample of Parastatal Firms in Tanzania, 1979 ...................................... 56 Table 20 Capacity Utilization in a Single of Public Enterprises, 1976-78, Somalia .......................... 57 Table 21 Capacity Utilization in Certain Manufacturing Firms in Sudan, 1973 ......................................... 58 Table 22 Capacity Utilization in the Public Industrial Sector in Sudan, 1975-76 ...................................... 59 Table 23 Frequency Distribution of Capacity Utilization in Plants/Processes of the INDECO Group, Zambia, 1981-82 .. 60 Table 24 Quantum Index of Imports, 1967 to 1978 .... ............. 61 Table 25 Petroleum Imports Into Eastern Africa. Three-Year Moving Averages ........................................ 62 Table 26 Public Current Expenditure Per Pupil in Constant Prices At The First Level (Ages 7 to 13) .... ........... 63 Table 27 Share of Public Investment (Including Parastatal Investment) in Total (Three-Year Moving Averages) ....... 64 Table 28 Index of Real Recurrent Expenditure on Economic Services In Four Eastern African Countries ...................... 65 Annex II Interrelations between the ICOR, Growth Rate, Invest- ment Ratio and the Investment Rate ..................... 66 Annex III Limitations of National Account Data in Eastern Africa 71 References ........... ............................................ 71 I. Introduction 1. The 1970s was a disappointing decade for the economic development of Sub-Saharan Africa and particularly of the oil-importing countries of Eastern and Southern Africa. The aim of this paper is to study this experience in 16 countries with a special focus on capital accumulation. We try to answer the following questions: - What were the common characteristics of this experience and what were the elements of diversity? - Was the setback in development mainly the result of a slowing down in the rate of investment or was it caused in large part by a fall in the productivity of capital? - To the extent that capital accumulation slowed down, was it the result of a lag in domestic savings or a turnaround in external capital inflow? - What factors explain the declining productivity of capital, in cases where this phenomenon was a prominent part of the setback in economic development? 2. By focusing on capital accumulation, we do not intend to take part in the debate on the role of capital in economic development. Much has been written on this topic by those (e.g. Arthur Lewis, Rostow, Harrod, Domar) who assign capital a strategic part, and by others (e.g. Cairncross, Frankel) who emphasise the contribution of technology, organization, entrepreneurship, etc. (Meier, 1964). The long run development of Eastern and Southern African - 2 - countries requires large doses of capital combined in appropriate ways with the growth of human skills, the evolution and adoption of suitable innovations and the maturation of indigenous institutions. The setback in capital accumulation and in economic development during the 1970s might have occurred precisely because factors of production have not been combined in the right quantities. In any event, our emphasis on capital in this paper should not be read to mean that we assign this factor a preeminent role. 3. Our analysis of capital productivity is cast in terms of the incremental capital-output ratio (ICOR) which relates investment to changes in GDP during the decades of the 1960s and 1970s. The intention is to capture long-term changes in this coefficient and thereby to study the secular relationship in the supply of capital and that of net production. The ICOR, in this context, will be influenced by the pace of technical progress, the growth of professional and managerial skills and the quality of organizations. 4. The ICOR is not narrowly concerned with new investment and its impact on output. It is influenced not only by income attributable to new investment but also by income generated by existing assets. And since existing assets are generally very much larger than additions to the capital stock, the ICOR is much more powerfully affected by the productivity of existing assets than by the quality of new investment. For example, a decline in capacity utilization throughout the economy caused by chronic scarcity of foreign exchange will raise the ICOR substantially even though new investments are highly productive. 5. An increase in the ICOR associated with the slowing down of GDP growth is not by itself a convincing explanation. To trace the final causes of the retardation, it is necessary to look further back into myriad factors that determine this coefficient. Nevertheless, the ICOR is a convenient summary statistic that allows us to decompose changes in GDP growth into those attributable to a deterioration in capital productivity and others related to a fall in the rate of investment. 6. The ICOR is a familiar enough coefficient with many defects (see Reddaway, 1962). In the Eastern Africa context, these defects are compounded by the following problems. Firstly, the proper measure of ICOR should utilize net fixed investment. Using gross rather than net investment introduces a bias, since the replacement component of investment is smaller at higher rates of growth of investment. Total investment includes inventories which may be sizable in primary-producing (and especially mineral-producing) countries in some years. Unfortunately, neither the extent of depreciation nor the fixed component of investment is known in many African economies and the measure of investment used in this paper is gross, total investment 1/. Secondly, the ICOR is not a very stable statistic. Investment is a volatile variable and so is output. Eastern African countries generally have large agricultural sectors, subject to the vagaries of weather. We have used three-year averages to deal with these fluctuations but we may not have entirely eliminated them. Thirdly, many countries in Africa undertook massive, once-for-all type of investment projects during our period of study. Examples of these are the Tazara Railroad (Tanzania and Zambia), and the Inga-Shaba hydroelectric project (Zaire). In these cases a marked rise in the ICOR over several years is inevitable, but this rise does not necessarily mean that capital productivity is falling. 1/ This is not unprecedented in empirical, development literature. Kuznets (1961), for instance, has used this concept. - 4 - 7. The data base for analysis is weak. Statistics on investment and output in the non-monetized sector are particularly unreliable. National account statistics prepared by official agencies in Eastern Africa are subject to many other pitfalls (Annex III). We have relied mainly on data from these sources, but it has been subjected to tests of consistency and adjusted in some cases. Most of the statistical analysis in this paper is at the economy-wide level. A brief enquiry into sectoral ICORs did not lead very far. We have not attempted to establish the statistical relationship between investment rates or ICORs and other structural or policy variables, given the scarcity of reliable information. 8. This paper is not intended as a rigorous, quantitative analysis of the setback in Eastern and Southern African development. Data are cited in support of conclusions, but the statistical analysis does not generate them: we have relied much more on expert observations of colleagues who have followed developments in these countries over a fairly long time and who have familiarity with field conditions in individual countries. II. First, A Look At the Record 9. Eastern Africa passed through a disappointing decade of economic growth in the seventies. The median growth rate in Eastern Africa, in the 1960s was above that of a group of largely Asian countries at similar, low levels of per capita income. During the 1970s the reverse was true; growth in comparator countries was higher than in Eastern Africa (Annex Table 1). If the period 1968-1978, on which this paper focuses, is considered, then the decline in growth in Eastern Africa is seen to be concentrated in the latter half of the period (Annex Table 2). The relative position of Eastern Africa is worse, if comparison is made with a group of oil-importing middle-income countries in East Asia. They recorded GDP growth rates of 8.2% per year during the 1960-1973 period and 7.5% per annum during 1973-1980, compared to the Eastern African average which fell short of 5% per annum in both periods. 10. However, the Eastern Africa experience has been diverse. In a few countries such as Malawi, Kenya, Botswana and Lesotho the growth rate of output in the seventies exceeded that of China, the low-income comparator country with the most impressive record. In over a third of the Eastern Africa countries, the growth rate was higher than in India or Pakistan. Counterbalancing this was the experience of Ethiopia, Zaire, Uganda, Madagascar, Zimbabwe and Zambia. In these countries output growth was either very low or even negative, especially in the 1973-78 period; and they greatly lowered the Eastern Africa averages. 11. The decline in the growth of income in Eastern Africa has been paralleled by a decline in the growth rate of investment. In real terms, the median annual growth rate of investment fell from almost 10% in the 1960s to less than 3% in the 1970s (Annex Table 3). At the same time, the median ICOR rose from 4.3 in 1967-1973 to 5.2 in 1973-79 (Annex Table 5). In this area too, however, there is considerable diversity. Overall investment growth rates have been impressive in Burundi, Malawi, Rwanda, Lesotho, Swaziland and Botswana (Annex Table 4). On the other hand, negative investment growth rates characterized Ethiopia, Uganda and Zambia. 12. The rise in ICORs is observed mainly in the 1973-79 sub-period. The ratio rose in eight countries and in another three (Zaire, TJganda and Zimbabwe) it had turned negative. In contrast, Malawi, Somalia, Sudan and Tanzania showed a falling ICOR in the 1973-79 period. In six - 6 - countries--Burundi, Malawi, Rwanda, Lesotho, Kenya and Botswana, ICORs were relatively low (between 2.8 and 5.3), even in 1979 2/. Yet in six others the ICORs had reached double digit or negative magnitudes. 13. These preliminary findings suggest that it is misleading to treat the Eastern African countries as a homogenous group which suffered declining growth of output as well as investment, accompanied by rising ICORs. While this was true of countries with the bulk of population and GNP in the region, there were significant exceptions. In this paper, accordingly, two statistical groupings have been used. In the first group are countries with relatively high rates of growth of investment and output and reasonable levels of ICOR. In this group are included Botswana, Lesotho, Rwanda, Malawi, Swaziland, Burundi, Kenya, Tanzania and Sudan. The second group consists of countries with low rates of investment and output growth, accompanied by high or even negative ICORs. In this category fall Somalia, Zaire, Uganda, Zambia, Ethiopia, Madagascar and Zimbabwe; they account for almost 60% of the population and only a slightly smaller fraction of GDP of the entire sample. 14. The criterion chosen to distinguish the two groups is whether the rate of GDP growth for the 1967-1978 period exceeded or fell short of 4% per annum 3/. Too much should not be read into the classification; it is purely statistical. While there are similarities between the growth and investment experience of countries in each category, their ranking by the investment 2/ Kuznets (1960) and Kuznets (1961) found gross ICORs lying between 4 and 6 in many countries. Carrington and Edwards (1979) estimated gross ICORs to be between 4 and 8 in the mid-seventies in several major OECD countries. See Annex Tables 6 and 7 for details. 3/ In terms of growth of per capita GDP, this would mean a growth rate of approximately 1 to 1.5% for most of the same countries. rate, ICOR, growth rate of GDP or other relevant series is not always congruent. The Sudan and Tanzania deserve special mention in this context; while we have put them in the first group on the basis of the chosen growth in GDP criterion, they could just as well be assigned to the second group, if emphasis was given to the behavior of savings or capacity utilization. 15. The timing of the setback in investment and output also shows considerable inter-country variability. The first oil price increase of 1973-74 is often taken as a watershed in the recent growth history of oil importing developing countries. This event was clearly of importance in the region, but it was far from decisive. Very specific influences were at work in each country. In 1972, Idi Amin came to power in Uganda and initiated major changes in policy. In 1974, Ethiopia underwent a revolutionary change in government. In 1975 the civil conflict in Zimbabwe escalated. The same year also saw a decline in copper prices which severly affected Zambia and Zaire. Drought affected several countries during the mid-seventies. Many countries reaped the benefits of the coffee boom of 1976-77 to variable degrees. The East African Common Market collapsed in 1977. Thus, while the oil price rise of 1973 was, undoubtedly, a major factor in the economy of each country, it was not the only and perhaps not even the predominant shock in all of them. For presentational purposes, the three-year average centered on 1973 has been taken as a rough dividing line to separate the data for the period under study 4/. 16. No country experienced a fall in GDP in the 1967-1973 sub-period, but four countries suffered an absolute reverse during the 1973-78 sub-period. Moreover, during 1973-78 growth rates in output were lower in 10 4/ All growth rates are calculated using three-year averages as the base and terminal period. - 8 - countries, relative to the earlier sub-period. In 11 countries the growth rate of investment was lower in 1973-78 compared to 1967-73. In six countries real investment declined in the latter sub-period, while this was the case in only three countries in the 1967-73 period. The ICOR remained at a satisfactory level in 1967-1973. ICORs were higher (ignoring very small variations) in six countries and lower in eight, compared to the 1961-68 period. Except for Madagascar, no country had an unusually high ICOR in the period upto 1973. The 1973-79 experience was much more unidirectional; in 12 countries the ICOR rose relative to the earlier sub-period. 17. We recognize that splitting the sample of 16 countries into two groups, on the basis of a purely statistical criterion, is useful, but hardly sufficient. A great deal of diversity remains in each group. For example, Group I could be subdivided into (i) the BLS countries, i.e. Botswana, Lesotho and Swaziland; (ii) countries facing acute demographic pressures, i.e., Malawi, Kenya, Rwanda and Burundi; (iii) the rest, i.e., Tanzania and Sudan. The BLS countries are not typical. Their distinguishing characteristics are the following: (a) Each has a population of less than 1 million; (b) Given their geographical position and land-locked nature, they have very intensive economic relations with the Republic of South Africa (RSA). These include trade, a large flow of migrant-worker remittances from RSA to BLS countries, private investment from RSA into mining, tourism and commercial agriculture in BLS countries and fiscal arrangements under the Southern African Customs Union. The seeming economic success of BLS countries, at least in terms of macro-economic variables, must be related in large part to the prosperity of RSA. _ 9 - 18. Demographic pressure is present in all 16 countries. In fact, this is a characteristic of the entire Sub-Saharan African region (see Faruqee and Gulhati, 1983). However, in Malawi, Kenya, Rwanda and Burundi, the demographic problem exists in a much more acute phase because the margin of cultivable, but not yet cultivated, land has narrowed considerably or disappeared altogether. This subset of countries also has policy frames which share several common characteristics, i.e., openness to foreign private investment, encouragement of indigenous private enterprise, tolerance for large numbers of expatriates and relative emphasis on the economic growth objective as against equity. 19. Tanzania and Sudan fall in a residual category, but they are very different from one another. Tanzania is distinguished by its plentiful physical potential and its sharp change of course symbolized by the Arusha Declaration which rejected the private sector, outward-oriented, capitalist strategy. Sudan also had its wave of nationalizations in 1970, but this socialistic doctrine was reversed later on. It is a very large country in physical size, but it is not richly endowed with infrastructure or natural resources. 20. Countries in Group II are also a diverse lot in terms of institutional and policy frames as well as per capita income levels (Ethiopia $120 and Zambia $540 in 1979). Ethiopia, Uganda and Zimbabwe have been victims of civil strife to a much larger extent than the rest. Zambia and Zaire share a heavy dependence on copper and the sharp fluctuation in its international price. Ethiopia, Madagascar and Zambia have assigned a commanding role to the public sector and placed a heavy emphasis on the equity objective. - 10 - 21. These brief, descriptive notes bring out the complex nature of social, political and economic reality in Eastern Africa. The aim of explaining the setback in capital accumulation in terms of some easily identifiable factors is not at all easy. III. Behavior of Investment 22. The slowing down in GDP growth could be the result of rising ICORs or of declining investment ratios or of some combination of these factors. We will examine the detailed evidence, first by focusing on the behavior of investment and its ratio to GDP and later by studying ICORs. 23. The investment ratio in the mid-sixties (see text table page 11) was very low in Burundi and Rwanda and already on the high side in five countries. During 1967-1973, the volume of investment expanded briskly, i.e., at double-digit growth rates in Malawi, Zaire and Lesotho (Annex Table 4). The investment ratio rose rapidly in these countries and also in some other cases. - 11 - RELATIVE GROWTH OF INVESTMENT AND GDP IN EASTERN AFRICA, 1968-1973 a! Rate of Investment Growth Investment/GDP Less than Equal to More than ratio in 1966/68 Negative GDP Growth GDP Growth GDP Growth Less than 10% Burundi Rwanda --------------------------------------------------------------__----------- Between 10% & 15% Sudan Madagascar Somalia Lesotho Between 15% & 20% Uganda Ethiopia Zaire Malawi Tanzania -------------------------------------------------------------__------------ Above 20% Kenya Botswana Zambia Zimbabwe Swaziland a/ All growth rates use three-year averages for the base and terminal period. source: Data files, The World Bank. 24. A comparison of investment rates in the mid-seventies between Eastern Africa and other LDCs suggests that the former was not much handicapped. We generated a sample of 24 low-income countries, 15 from the region and 9 non-African low-income countries. A regression equation was fitted for the pooled sample of countries, relating the investment ratio to per capita GDP in 1974-76. The estimated equation was: _2 I/Y = 8.4202 + 0.0516 (y) (R = 0.51) Where I = gross national investment Y = GDP at factor cost and y = GDP per capita in US dollars. - 12 - In Ethiopia, Sudan, Burundi, Madagascar and Zimbabwe the actual ratio lay below the regression line (see Figure 1). The actual investment ratio was above the regression line in Malawi, Tanzania, Lesotho, Botswana, Somalia, Zaire and Zambia. Malawi, Lesotho and Zaire stand out in having an investment ratio far higher than warranted by their level of per capita GDP. In Kenya the actual and predicted ratios were approximately equal. We also calculated a regression equation of 15 East African countries separately 5/. The East African regression line remains above the regression line for the pooled sample, but the distance between the two tends to diminish at higher levels of per capita income. 25. From this favorable position in the mid-seventies, the pace of capital accumulation has slowed down considerably. The median growth rate in the volume of investment slackened from a brisk 6.4% per annum during 1967-1973 to only 2.4% per annum in 1973-78. The text table on page 14 shows that the volume of investment declined in absolute terms in six countries. It is surprising to note, therefore, that in this period of widespread slowing down, a number of countries experienced large increases in investment. There was a dramatic turnaround in Burundi and Sudan who had experienced an investment decline in the early 1970s, but who now saw a sharp rise (Annex Table 4). Lesotho, Swaziland and Somalia maintained a substantial expansior. in investment. 5/ The regression equation for 15 East African countries separately was 2 I/Y = 11.6 + 0.0454(y) (R= 0.44) FIG. 1 THE INVESTMENT RATIO AND GDP PER CAPITA, 1974-76 45 , , , , , , , _ , , BOTSMAM 40 LOSOTMW REGRESSION LINE, *ZA3RE p RE0GRESS ION L INE, I- // _ 5 COMBINED SAMPLE w > 20 z H e . . .. II I I I B 5Q t 0Q 15Q 20e 2SQ 300 350 4B0 450 500 558 GDP PER CAPITA (u.s DOLLARS) - 14 - a/ RELATIVE GROWTH OF INVESTMENT AND GDP IN EASTERN AFRICA, 1973-1978 Rate of Investment Growth Investment/GDP Less than Equal to More than Ratio in 1973 Negative GDP Growth GDP Growth GDP Growth Less than 10% Burundi -----------------------------------------------------------------__-------- Between 10% & 15% Ethiopia Rwanda Sudan Madagascar Uqanda Between 15% & 20% Lesotho Above 20% Zambia Tanzania Somalia Zaire Zimbabwe Kenya Swaziland Botswana Malawi Somalia a/ All growth rates are based on three year averages for the base and terminal period. Source: Data files, the World Bank. 26. Looking at the situation at the end of the 1970s, the investment picture is particularly stark in two countries. In Uganda, the investment ratio has dropped from a respectable 16% to 17 % of GDP in the late 1960s to an abysmally low level of 3% to 4% now. This is catastrophic. In Ethiopia, the drop is not as precipitous, i.e., from 15% to 9% in the same period, but it is a cause for concern (Annex Table 8). 27. The setback in investment is largely an African phenomenon. Out of 63 non-African low-and middle-income countries listed in the World Development Report, 1981, only 8% of the sample had negative investment growth rates in the seventies. In Eastern Africa this was the case in 40% of the sample. All the countries in Group II with the exception of Somalia had declining real investment rates in this period. - 15 - 28. The slowing down of investment activity in Eastern Africa could be the result of a relative scarcity of investable funds or strains on absorptive capacity (reflected in lack of projects, shortages of trained personnel, emergence of bottlenecks and delays in decision making (see Gulhati, 1967) or some combination of these two factors). Given that at least eight countries have experienced an expansion of investment at a rate of 6% per year or more over the whole period 1967-1978, we should not discount the impact of strained absorptive capacity in reining in investment. Central government investment outlays in real terms doubled in Zaire in the early 1970s and trebled in Malawi, Lesotho and Botswana during 1972-79 (Annex Table 9). Lack of projects has been an issue in several instances. Availability of project managers, engineers and accountants has been a chronic problem in most of these countries. Bottlenecks, such as limited construction capacity and congestion in ports have delayed project implementation in many places. Finally, slowness of government decision making has been a pervasive phenomena affecting all aspects of economic activity. These strains have not only influenced the trend of capital accumulation but also its quality; a topic we will discuss in the context of ICORs. 29. Meanwhile, we will focus on the availability of savings--internal and external--as a factor bearing on capital accumulation. Figure 2 shows that while the median investment ratio for the whole sample rose from 16.5% to 24.1% between 1966/68 and 1973/75, the national savings ratio was fairly flat. Subsequently, the average investment ratio dropped by about 3 points and the savings ratio by almost 4 points. The proportionate contribution of external savings in financing capital accumulation has tended to rise during the period as a whole. -16 - FIGURE 2: THE MEDIAN RATIOS OF SAVINGS AND INVESTMENT TO GDP,EASTERN AFRICA sB- - THE INVESTIENT RATIO (PERCENT)' THE SAVINGS RATIO 24- s-I 12- |~~~~~~~~~~~~~~~~~~~~~ % 19;7 1198 1888 t878 t871 1872 1873 1874 1879 1878 1977 19;8 YEARS - 17 - 30. National savings during the late 1960s were very low or negative in more than one-third of the sample, as the table below shows. Burundi, Lesotho and Botswana had negative savings at that time. Only Zambia had a high savings coefficient. The record shows a substantial rise in savings till about the middle of the 1970s. This was particularly the case in Malawi, Swaziland, Botswana and Zimbabwe (see Annex Table 10). RATIO OF SAVINGS TO GDP (Number of countries) 1966/68 1972/74 1976/78 Low Ratios (less than 5%) 6 3 3 Middle Ratios (5% up to 20%) 9 9 8 High Ratios (above 20%) 1 4 5 31. The savings ratios of African countries were not atypical when compared with a broad sample of low-income countries. A regression of the savings ratio in 1974-76 against per capita GDP for a sample of 9 comparator low-income countries and 15 Eastern Africa countries indicated that actual savings in Malawi, Tanzania, Kenya, Swaziland, Ethiopia and Somalia were above the predicted level (see Figure 3). Actual savings lay below the predicted level in Lesotho, Sudan, Botswana, Zaire and Madagascar. We also calculated a FIG 3. THE SAVINGS RATIO AND GDP PER CAPITA, 1974-76 45 . a -s 40 35 30 2.5 H 2 5 REGRESSION LINE, ' << ~~~~~~~~~~~~~~COMBINEDDSAMPLE 20 U) ~~~~~~~~~~~~~~~~~~REGRESSION LINE, z l X#XU E. AFRICA_ z iS - / _ 0 H A 35 -5 -10 LEBHOW 0 50 801 1 5Q 200 250 300 35Q 488 458 58a8 550 QDP PER CAPITA (u.S. DOLLARS) - 19 - regression equation for 15 Eastern African countries separately 6/. The regression line for Eastern Africa remained below the pooled regression line for a substantial range of per capita incomes. 32. During the second half of the 1970s, the trend was distinctively towards lower domestic saving ratios, particularly in Group II and in Tanzania and Sudan from Group I. In the case of copper exporting economies, declining saving ratios went hand in hand with a serious deterioration in the terms of trade (Figure 4) but this relation did not hold in many other instances. The collapse of savings in Ethiopia and Uganda took place despite the rise of coffee prices and substantial improvement in terms of trade (Figure 5; also see Annex Table 11). 33. The reliance of Eastern Africa on external savings to finance its investment program has always been high and this has increased (Annex Table 12). The median ratio of gross national savings to gross national investment exceeded 700% only once during this period. In seven out of fourteen countries for which data are available for 1977-79, this ratio was below 50%. In Group I countries, domestic savings financed only approximately a quarter of total investment at the beginning of the period. This proportion had risen to over a half by 1973, but it has shown no sustained increase threafter. In Group II countries the reliance on domestic resources for investment was much higher at 6/ It should be stressed that the data base for this exercise is quite weak. Apart from the data problems in Africa, savings data on economies such as Nepal or Afghanistan are largely conjectural. Even in Bangladesh or India savings estimates are not felt to be very accurate. The regression equation for the pooled sample was: 2 S/Y = 1.06 + 0.0549 y (R = 0.41) where S = savings, Y = GDP and y = per capita GDP. For 15 Eastern Africa countries the equation was: 2 S/Y = 4.15 + 0.0609 y (R = 0.43) - 20 - FIGURE 4: THE SAVINGS RATIO AND TERMS OF TRADE<,ZAMBIA AND ZAIRE -_TERMS OF TRAD. ZAMBIA - TERMS OF TRADE ZAIRE -- - SAVINGS RATIO, ZAMBIA ---- SAVINGS RATIO ZAIRE _ I 4% IL -zfi;: e . . . . -11 %~~~~~~~~~~~~~~~~~~~4 NC 023- 1867 1888 sass 1870 1871 1872 1873 1974 1975 1876 -1977 1878 YEARS *~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The terms of trade is an index with the value for the year 1975 = 10. The plotted points are three-year averages. -21 - FIGURE S:THE SAVINGS RATIO AND TERMS OF TRADE*ETHIOPIA AND UGANDA -fi TERMS OF TRADE ETHIOPIA - - TERMS OF TRADE UGANDA -- --SAVIN6S RATIO UGANDA ---- SAVINGS RATIO ETHIOPIA 20- ~ ~ ~ ~ ~ ~ ~ ~ ~ 7 i- / le-~~~~~- 19B7 19B8 18B8 1870 1871 1272 1973 1874 1975 1876 1977 1978 YEARS The terms of trade is an index with the value for the year 1975 = 10. The plotted points are three-year averages. - 22 - the beginning of the period, approximately 90%. By 1978 this ratio had fallen to almost 55%. Five cases of striking increase in the domestic financing of investment can be identified: these are Burundi, Malawi, Rwanda, Swaziland and Botswana. However, all these countries started the period with very low or even negative savings rates so that with the exception of Swaziland they are still heavily dependent on external capital flows. In Tanzania, Sudan, Zaire and Ethiopia the ratio of gross domestic savings to investment has declined; the drop is precipitous in the case of the first three countries. 34. Most of the external savings in Eastern Africa take the form of official development assistance or ODA. Annex Table 13 shows that ODA exceeded 50% of external resources inflow in all countries and exceeded 75% in 11 of them. In earlier years, non-concessional capital flows constituted an important source of external capital in Zambia, Zaire, Sudan and Kenya. This resulted in a rapid buildup of debt service payments, and in Zaire and Sudan it was necessary to negotiate postponement in scheduled debt service payments. The role of direct investment has not been of much importance in the Eastern African countries, with the exception of Zaire and the countries of the Southern African Customs Union. On the basis of the IMF figures, direct investment accounted for only 5% to 9% of long-term capital flows to Sub-Saharan Africa 7/ (Annex Table 14). Even in countries such as Kenya or Malawi which have been very receptive to foreign equity capital, net private 7/ There are major statistical gaps in this area. The two sources of primary data, the OECD and the IMF, each suffer from crucial deficiences. The OECD data omit South African investment since it is concerned only with the DAC group. The IMF data do not cover Zaire, an important recipient country. IMF data also include flows between South Africa and its customs union partners originating in the customs union payments provisions. Data for the BLS countries are, therefore, not comparable to that of other countries. - 23 - direct investments have been only 10% to 15% of total long-term capital inflows. Moreover, much of the investment is in the form of reinvestment of profits by established foreign companies. Besides the mineral producers, only Kenya has any substantial stock of foreign capital (Annex Table 16). 35. To conclude this section, the supply of investable funds has had a considerble influence on the tempo and pattern of capital accumulation. Declining national saving rates during the late 1970s affected investment adversely and this tendency would have been more pronounced had it not been for some offsetting changes in the flow of external funds. ODA from all sources to the sample of 16 countries expanded by 7% per annum in real terms during 1976-79. Heavy reliance on ODA also emphasizes the vulnerability of Eastern Africa in that future investment prospects are intimately tied up with what happens to official aid. It is clear that the region is not of particular interest to private foreign investors and that considerations of creditworthiness will stand in the way of external borrowing on commercial terms, except on a limited scale. IV. Productivity of Capital 36. The deterioration in ICORs has been a widespread phenomena. In trying to understand why this has happened, we will look at the following factors: - extent of capacity utilization; - changes in sectoral-mix of investment and output, and in sectoral ICORs; - strains on absorptive capacity; and - impact of government policy. - 24 - Capacity Utilization 37. Our hypothesis regarding utilization is that it has fallen sharply, partly because of a scarcity of imports. The emergence of idle capacity raised ICORs sharply, but this decline in capital productivity is caused not so much by the quality of new investment projects as by the economy-wide constraint on imports. It follows that ICORs will fall as soon as extra foreign exchange is available to purchase critical production inputs. 38. Direct evidence to support this hypothesis is scant. Measurements of capacity utilizations are crude and observations over time are seldom available. Some statistics are available for Tanzania, Somalia, Sudan, and Zambia (Annex Tables 18-23). The Tanzanian figures related to the late 1970s and showed capacity utilization varying from a low of 12% in motorcycles and bicycles to a high of 94% in tobacco manufactures. There was some tendency for utilization to vary inversely with the degree of dependence of the activity on imports. In Somalia, however, utilization was low even in industries relying on domnestic materials, e.g. meat. Plant capacity had been designed with exports in view, but these failed to materialize. In Sudan, Zambia and Zaire the import constraint had been much more severe and this had affected local farm production; thereby reducing supplies of local and imported raw materials to manufacturers. 39. No capacity utilization data was available for agriculture, but there was no doubt that mechanized agricultural production was severely reduced, partly because of the unavailability of imported spare parts or fuel for tractors and fertilizers, etc. Events in the Geizera Scheme in the Sudan are pertinent in this context. The sharp decline in Geizera cotton should not all be attributed to the foreign exchange constraint; there were many other - 25 - factors involved, but unavailability of critical imports was an important part of the picture. In Tanzania, the shortage of foreign exchange was partly responsible for the collapse of agriculture. Many crops such as wheat, rice, sugar, tea, tobacco, sisal and mild coffee rely heavily on imported inputs. Even maize grown for the urban market uses a large amount of inputs purchased abroad. In addition, transportation of farm output in a country as geographically dispersed as Tanzania is very demanding of foreign exchange for vehicle parts and fuel. 40. We can also cite some evidence at the macro-level on this issue. Ideally one would study the relation between the flow of intermediate good imports and ICORs but data for this exercise is not available. Instead, we have examined the connection between ICORs, total imports and petroleum imports. Overall there is some correlation between rising ICORs and declining imports. Group II countries have experienced both phenomena in a more intensive form than Group I. However, there are cases such as Kenya, and to a lesser extent, Malawi, where declines in import coefficients allowed GDP growth with a less than proportionate expansion in imports and without a sacrifice of productivity. There are also cases such as Somalia and Sudan, where capacity utilization problems were evident even in a period when the volume of imports was rising significantly. It was difficult in these countries to divert foreign exchange earnings to the import of intermediate goods, since a sizeable part of these earnings accrued to migrants and did not pass through official channels. Remittances from migrant workers typically came in the form of non-essential consumer good imports which could be sold in local markets at premium prices. Furthermore, a large part of imports were financed by external aid tied to capital goods required by new projects and not available for purchasing intermediates required for using already installed capacity. - 26 - THE RELATION BETWEEN CHANGE IN ICORS, CHANGE IN IMPORTS AND THE CHANGE IN PETROLEUM IMPORTS Percentage Percentage Percentage Change in Change in Change in Volume of ICOR between Import Petroleum 1967-73 and Volume Imports 1973-79 1973-77 a/ 1973-77 a/ Group I 1. Burundi 47 45 6 2. Malawi -12 14 8 3. Rwanda 174 1164 462 4. Tanzania 13 -4 42 5. Lesotho 93 89 -- 6. Sudan c/ 47 -- 7. Kenya 71 -8 8. Swaziland 197 41 -- 9. Botswana 73 49 __ Median 25 38 8 Group II 10. Ethiopia 112 14 -10 11. Somalia c/ 27 200 12. Zaire b/ -50 -- 13. Madagascar -17 -6 -11 14. Uganda b/ -23 -6 15. Zimbabwe b/ -31 11 16. Zambia 247 -29 23 Median 326 -8 1 Eastern Africa Median 21 12 4 a/ These changes are calculated on the basis of three-year averages for the base and the terminal. b/ ICOR was negative in latter period implying severe deterioration in the productivity of investment. c/ Available data show reduction in ICOR but this is inconsistent with expert observations. Source: Annex Table 5, 24 & 25. - 27 - 41. Also significant was the sluggishness or decline in the volume of petroleum imports in recent years in several countries. Typically, petroleum imports increased much more rapidly than GDP in the late 1960s and early 1970s. The subsequent slowing down was a major impediment in the efficient functioning of the transport network which was the major end-user of oil imports. This generated a major setback for many economic activities, especially agricultural marketing, in many countries. 42. Capacity utilization has also fallen because governments have not provided sufficient funds in the recurrent budget to purchase inputs required for maintenance and operation of schools, health clinics, roads, agricultural research and extension services, etc. Although this generalization was supported by field observations of economic and technical analysts familiar with Eastern Africa, it was not possible to cite systematic statistical evidence for all countries. Faced with budgetary difficulties, governments responded by a series of actions during the late 1970s which cumulatively led to an anomalous situation, namely underfunding of already completed economic assets in the public sector while new projects were being launched. 43. Conditions regarding road maintenance are a source of concern in most countries, particularly with respect to secondary and feeder roads. Underfunding was not the only difficulty but it was a major impediment in securing the full benefits of past investments in the road network. Similarly, very large capital outlays on primary schools during the 1970s were not producing the expected benefits because of inadequate recurrent budget provisions. Annex Table 26 shows that real recurrent provisions per primary school student declined during 1970-75 by 42% in Uganda, by 41% in Malawi, by 38% in Madagascar and by 37% in Lesotho. - 28 - 44. We were able to find data on real recurrent budget outlays on economic services for only four countries, and even this information is subject to many qualifications (Annex Table 28). In the Sudan, the peak was reached in 1974; since then recurrent outlays for economic services have been falling. In 1979 the index of these outlays had declined by 53 points. Similarly, these outlays in Zambia peaked in 1975 and by 1978 they had declined by 80 points. Kenyan and Tanzanian data show rising indices, but we are not able to determine whether or not these increases were adequate. We do know that Tanzanian agriculture has been deprived adequate recurrent budget funds, impeding the mobility of research and extension staff and creating shortages of needed materials and provisions. Sector-Mix and Sectoral ICORs 45. The economy-wide ICOR is a weighted average of sectoral ICORs. Typically, agriculture has the lowest ratio and this situation persists until a rather advanced state of development when agriculture gets increasingly mechanized (Kuznets, 1960 and 1961). In Eastern Africa, agricultural ICORs are particularly low, reflecting the very low technology and the general absence of draft animals and irrigation. 46. The upward shift in ICORs can be attributed to some extent to the decline in the share of agriculture in investment and output. Available data are summarized in the table on page 29. They show a substantial contraction in agriculture's share in total capital formation in Burundi, Tanzania and Kenya, although many gaps in the statistical series limit their usefulness. The contribution of agriculture to GNP also fell in these cases as well as in Malawi, Ethiopia, Somalia and Zimbabwe. - 29 - CHANGES IN SHARE OF AGRICULTURE IN OUTPUT AND INVESTMENT (in percent) Output Investment 1967 1973 1978 1967 1973 1978 Burundi 66 67 62 - 35 20 Malawi 54 49 44 - - - Tanzania 44 39 41 11 6 - Kenya 37 32 32 13 9 9 Ethiopia 56 50 48 6 8 - Somalia 90 53 55 23/a 16/b 25 Zimbabwe - 17 14 - 10 11/c Zaire - 16 18 - - - Zambia - 11 12 7 5/d - a/ 1963-66 b/ 1975 c*/ 1977 d-/ 1971 Source: Data Files: The World Bank 47. Time series data on sectoral investment and output are not available for most countries. We have, nevertheless, tried in two cases to break down each sector's contribution to the change in the economy-wide ICOR, using Martin Wolf's formula (see Annex II). In the Tanzanian case, the decomposition exercise reveals the impact of countervailing sectoral trends which more or less offset each other, thereby making for an almost stable economy-wide ICOR. The agricultural ICOR declined but this was counteracted by a sharp increase in the industrial ICOR. The role of the services sector remained unchanged. - 30 - 48. The second decomposition exercise for Kenya was based on data which is not consistent with that used in this paper. We cite the results, nevertheless, simply to illustrate the nature of the calculations. Accordingly, ICORs rose in all sectors; the services sector was responsible for 64% of the rise in the overall ratio; industry contributed 33% and agriculture only 3%. Absorptive Capacity 49. We have mentioned, earlier (para. 28) that rapid expansion in the volume of investment during the late 1960s and 1970s created a number of bottlenecks, particularly in the public sector. The supply of skills for example, did not keep pace with the growing number of projects started. Although a concerted attempt was made to expand enrollment and train available personnel, the demand for project staff could not be satisfied in a timely fashion. The period witnessed an outflow of colonial officers as part of the indigenization drive and after 1973, there was another migration of Somalis and Sudanese (including professionals) to the Gulf countries in search of attractive salaries. The local supply of middle- and high-level skills was supplemented to some extent by expatriates financed by technical assistance or on direct hire. Nevertheless, vacancies persisted and available staff was moved from post to post in a desperate attempt to fill gaps. All this was well understood among development practitioners familiar with Eastern Africa, even though we have not found systematic evidence to buttress these impressions. 50. In this context it is instructive to examine the experience of the World Bank in project implementation during the 1970s. Our focus is on 32 agricultural projects. In one-fifth of these cases, actual costs were higher - 31 - than estimated costs. In no less than half the sample, actual unit costs were higher than estimated. In one-third of the sample, the planned project size had to be reduced. The reasons for this varied, but stringency of budget funds, inability on the part of the governments to set up implementation units in time as well as the failure to mobilize project beneficiaries figured prominently. In about one-third of the projects, the actual completion time substantially exceeded the estimated time. Furthermore, in almost all these cases problems relating to administration and staff were partly responsible for delays. There were relatively few instances where purely technical or natural factors were responsible for the delay in project completion. Impact of Government Policy 51. It can be argued that a number of structural factors in Eastern and Southern Africa countries tend to raise capital costs, compared to say those prevailing in the Indian sub-continent. Many Eastern and Southern African countries are landlocked and this makes for higher transportation costs. Also, they are of small economic size and thereby unable to exploit economies of scale and agglomeration. They face a large element of uncertainty, making it necessary to hold substantial inventories. Labor, including unskilled labor, is relatively more expensive (Gulhati and Sekhar, 1981). And the acute scarcity of skills and experience tends to reduce productivity all around. To these structural factors should be added the impact of government policy on the efficiency of investment. This impact is visible at macro, sectoral and project levels, particularly during the latter 1970s, when these economies had to confront a substantial deterioration in the international economic climate. - 32 - 52. The sharp fall in capacity utilization related to the import squeeze in many Eastern and Southern African countries was the result not only of declining terms of trade but also of the policy-induced bias against exports reflected in the price and exchange rate regimes. In the event, the volume of exports declined during 1970-79 in Tanzania, Kenya and Sudan (Group I) as well as in Ethiopia, Zaire, Zambia, Madagascar and Uganda (Group II) (see World Bank, 1981). Their marketing was frequently the sole responsibility of parastatals which tended to absorb a growing part of the border price, thereby undermining farm incentives. Furthermore, many of these governments opted to deal with the pressure on the balance of payments by import restrictions rather than by pursuing an active exchange rate policy (Gulhati and Autokorala, forthcoming). The scarcity value of foreign exchange was not reflected in the payment made to exporters. Those who earned foreign exchange by exportation were not rewarded suitably, leading in time to the accentuation' of the import constraint, fall in the utilization of capacity and the corresponding rise in ICORs. 53. The decline in the share of agriculture in investment and output and the parallel emphasis on industrialization and urban infrastructure were also policy induced to a large extent. While farm prices were regulated at low levels, manufactured goods' production was stimulated by raising their prices to levels far above those prevailing internationally. For some time this strategy produced rapid growth of the manufacturing sector, but this advance could not be sustained (Gulhati and Sekhar, 1981). The incentive system was tilted in favor of both import and capital-intensive industrialization oriented mainly to the home market. The new manufacturers became the victim of the economy-wide foreign exchange constraint. Their high costs prevented them from selling abroad in order to finance their import needs. - 33 - 54. Investment activity in the public sector rose at a faster rate than in the private sector in many Eastern and Southern African countries (Annex Table 27). This was true not only of Ethiopia and Zambia, i.e. socialist economies, but also of Burundi and Malawi who remain capitalistic in their ideology. At the end of the 1970s, there was scarcely any country in our sample in which the share of public investment fell short of 40% of total investment in the formal or monetized sector and in several this share was much higher. In principle, this public investment was subject to scrutiny via the planning, project appraisal and budgeting processes. Since a substantial part of public investment was financed with ODA, many of the bigger projects were scrutinized by technical and economic staffs of aid agencies. The deterioration in the productivity of investment took place despite all these ex-ante analyses and supervision missions during the course of project implementation. 55. An examination of 21 agricultural projects in Eastern and Southern Africa, financed partly by the World Bank Group, is instructive in this context. The weighted average economic rate of return ex-ante was nearly 20%: a re-evaluation of these same projects (after construction was completed and the flow of benefits had started) resulted in a weighted rate of return ex-post of only 12%. Of course, even the latter was an estimate since an actual rate of return could be calculated only at the end of the project's life. The substantial deterioration in capital productivity captured by these ex-ante and ex-post estimates was the result of some combination of cost overruns, time delays and scaling down of project benefits. - 34 - V. Conclusion 56. Now we will try to answer some of the questions listed in the introduction: - the relative roles of the investment rate and investment productivity in bringing about a retardation in GDP growth; - factors responsible for the declining productivity of investment. 57. Nine out of 16 countries in our sample experienced a retardation in the growth of GDP. The extent of the setback was relatively minor in Rwanda but very large in Botswana, Zimbabwe, Zaire and Zambia (see table on page 35). In Swaziland and Rwanda the setback in GDP growth took place despite a large rise in the investment rate: it was entirely due to a decline in the return to capital. In Zimbabwe, the investment rate remained more or less unchanged and the slowing down in the expansion of GDP was attributable to a fall in capital productivity. The last column shows that GDP growth would have increased very slightly, if the ICOR had remained constant during the 1970s. Deterioration in capital productivity was also the dominant factor in Zambia, Zaire, Botswana and Uganda. Zambia's GDP growth rate declined by seven percentage points, despite a substantial rise in the investment rate. In Zaire, Botswana and Uganda the setback was the combined result of falling investment and deteriorating capital productivity, but the latter clearly played the dominant role. For example, in Zaire, GDP expansion was reduced by 8.6 percentage points; of this less than one percentage point could be explained by the fall in the investment rate (see last column), and the rest was attributable to a deterioration in capital productivity. In contrast, the decline in the investment rate was exclusively responsible for the setback in GDP in Madagascar (which experienced an improvement in capital productivity), and it was the major culprit in Ethiopia. - 35 - Analysis of Setback in Growth Rate of GDP 1967-73 Compared to 1973-78 (percentage points) Change in the Rate of Change in GDP Extent of Investment Growth Rate Setback in GDP & Savings* Assuming (percent p.a.) I S Change in ICOR Constant ICOR Swaziland - 4.9 14.2 23.4 197 +0.9 Rwanda - 0.8 13.8 9.5 174 +1.6 Zimbabwe - 9.1 - 0.5 1.5 x +0.6 Zambia - 7.0 4.0 -12.2 247 -0.6 Zaire - 8.6 - 1.3 -18.8 x -0.7 Botswana -13.1 - 1.8 21.7 73 -3.2 Uganda - 4.5 -11.8 - 9.9 x -1.7 Madagascar - 1.4 - 3.4 0.0 - 17 -0.9 Ethiopia - 2.9 - 3.4 - 5.1 112 -1.4 * 1976-78 compared to 1969-71. x ICOR was negative in latter period implying severe deterioration in the return to existing capital and new investment. Source: Annex Tables 2, 5, 8 and 10. 58. We cannot assess quantitatively the role of various factors contributing to a decline in the productivity of investment. The attempt by many countries to raise rapidly the level of overall investment, to industrialize and modernize their economies at the expense of agriculture and to expand the public sector at a rate which far exceeded the availability of relevant professional skills has led to a massive deterioration in the quality of projects and the effectiveness of their implementation. Superimposed on these factors was the deterioration in the international economic climate - 36 - which made it even more difficult to manage the public finances and the foreign exchange budgets, thereby compounding the problems of project execution and causing capacity utilization to decline drastically. 59. The analysis in this paper is based on data up to 1979. Systematic information is not available for the subsequent period but it is clear that economic difficulties facing these countries have multiplied. The retardation in GDP growth became even more pronounced in 1980 and 1981. The constraint on foreign exchange for the import of intermediate goods remained acute. Budgetary pressures made it very difficult to fund recurrent economic needs adequately, and so on. 60. Economic recovery will necessitate a reconsideration of major elements of the economic and institutional policy frame. First, the emphasis will have to be on consolidation and rehabilitation rather than on starting many new projects. The aim of obtaining a reasonable pay off from already completed investments must take precedence over starting new schemes. The efficiency of the existing capital stock must be increased before launching the next round of capital accumulation. Secondly, the emphasis will have to be on reviving traditional agriculture (food plus cash crops), thereby securing some relaxation of the constraint on foreign exchange through volume increases of exports and reduction of the need for food imports. Once this phase is over, attention can be given to the promotion of new crops and technological changes to raise yields. A prosperous and dynamic agriculture is a good foundation for industrialization, since it provides many inputs for manufacturing and since it is also a major consumer of industrial goods. The plea to revive and strengthen agriculture should not be viewed as a step - 37 - detrimental to the industrialization drive of African countries. Finally, the recovery program requires institutional adjustments aimed at improving the efficiency of the public sector and at expanding its capacity to manage the economy. ANNEX I Statistical Tables - 38 - ANNEX Table 1: THE GROWTH OF GDP IN CONSTANT PRICES, EASTERN AFRICA AND COMPARATOR COUNTRIES, 1960-70 AND 1970-79 Average annual growth rate 1960-70 1970-79 Group I 12.Burundi 4.4 3.0 2. Malawi 4.9 6.3 3. Rwanda 2.7 4.1 4. Tanzania 6.0 4.9 5. Lesotho 4.6 7.0 6. Sudan 1.3 4.3 -7. Kenya 6.0 6.5 8. Swaziland 8.6 4.6 9. Botswana 5.7 13.5 Median 4.9 7.0 Group II 1UT Ethiopia 4.4 1.9 11. Somalia 1.0 3.1 12. Zaire 3.6 -0.7 13. Madagascar 2.7 0.3 14. Uganda 5.9 -0.4 15. Zimbabwe 4.3 1.6 16. Zambia 5.0 1.5 Median 4.3 1.5 Eastern Africa median 4.5 3.6 Comparator countries Median /a 3.5 4.2 /a Consists of nine low income Asian countries and Haiti. Source: 1. Accelerated Development in Sub-Saharan Africa: An Agenda for Action, World Bank, 1981. 2. World Development Report, 1981, World Bank. - 39 - ANNEX Table 2: THE GROWTH OF GDP IN CONSTANT PRICES, 1967-78 AND SUB-PERIODS 1967-73 AND 1973-78 Average annual growth rate /a 1967-78 1967-73 1973-78 Group I 1. Burundi 4.1 4.1 4.1 2. Malawi * 5.7 5.4 6.0 3. Rwanda 5.2 5.6 4.8 4. Tanzania 4.7 4.4 5.1 5. Lesotho 5.2 3.7 6.9 6. Sudan * 4.3 4.3 4.3 7. Kenya 6.3 6.7 5.8 8. Swaziland 5.8 7.8 2.9 9. Botswana * 13.8 22.0 8.9 Median 5.2 5.4 5.1 Group II 10. Ethiopia 2.7 4.0 1.1 11. Somalia * 3.4 1.8 5.3 12. Zaire 3.1 7.1 -1.5 13. Madagascar 1.1 1.7 0.3 14. Uganda * 1.2 3.3 -1.2 15. Zimbabwe 3.9 8.2 -1.1 16. Zambia 2.4 5.8 -1.4 Median 2.7 4.0 -1.1 Eastern Africa median 4.2 4.9 4.2 /a Compound rate of growth of GDP at factor cost based on three year end point averages. * = For countries marked with an asterisk, GDP at market prices was used for lack of data. Source: Data Files, World Bank. - 40 - ANNEX Table 3: THE GROWTH OF GROSS DOMESTIC INVESTMENT IN CONSTANT PRICES, EASTERN AFRICA AND COMPARATOR COUNTRIES, 1960-70 AND 1970-79 /a Average annual growth rate /a 1960-70 1970-79 Group I 1. Burundi 4.3 16.5 2. Malawi 15.4 2.3 3. Rwanda 3.5 18.9 4. Tanzania 9.8 3.0 5. Lesotho 18.5 24.4 6. Sudan -1.3 8.0 7. Kenya 7.0 1.2 8. Swaziland 10.6 13.3 9. Botswana 25.3 5.6 Median 9.8 8.0 Group II 10. Ethiopia 5.7 - 1.8 11. Somalia 4.3 8.5 12. Zaire 9.6 - 5.0 13. Madagascar 5.4 - 1.8 14. Uganda 9.8 -13.1 15. Zimbabwe -- - 2.1 16. Zambia 10.6 - 5.6 Median 7.7 - 2.1 Eastern Africa median 9.6 2.7 Comparator countries median 5.5 6.7 -- = Not available. /a Least squares growth rates. Source: Accelerated Development in Sub-Saharan Africa: An Agenda for Action, World Bank, 1981. - 41 - ANNEX Table 4: THE GROWTH OF GROSS DOMESTIC INVESTMENT IN CONSTANT PRICES, 1967-78 AND SUB-PERIODS 1967-73 AND 1973-78 /a Average annual growth rate /a 1967-78 1967-73 1973-78 Group I 1. Burundi 8.9 -1.0 22.0 2. Malawi 9.3 13.9 4.1 3. Rwanda 15.2 9.4 23.0 4. Tanzania 6.0 7.3 4.5 5. Lesotho 17.3 11.5 25.0 6. Sudan 3.5 -2.2 10.6 7. Kenya 4.9 6.9 2.5 8. Swaziland 9.1 7.4 9.3 9. Botswana 18.1 36.0 - 4.3 Median 9.1 7.3 4.5 Group II 10. Ethiopia -1.8 0.2 - 4.0 11. Somalia 6.2 5.5 7.2 12. Zaire 2.9 13.0 0.4 13. Madagascar 0.4 1.9 - 1.3 14. Uganda -8.0 -4.4 -12.4 15. Zimbabwe 0.4 9.1 - 9.1 16. Zambia -2.4 5.8 -11.4 Median 0.4 5.5 - 4.0 Eastern Africa median 6.0 6.4 2.4 /a Compound rates of growth based on three-year averages. Source: Data Files, Warld Bank. - 42 - ANNEX Table 5: THE INCREMENTAL CAPITAL OUTPUT RATIO IN THE PERIODS 1961-68, 1967-73 AND 1973-79 /a ICOR 1961-68 1967-73 1973-79 Group I IIi-Ftundi 1.8 1.9 2.8 2. Malawi 2.8 4.3 3.8 3. Rwanda 4.5 1.9 5.2 4. Tanzania 2.7 5.3 4.6 5. Lesotho 2.0 2.7 5.2 6. Sudan 16.5 5.7 3.6 7. Kenya 4.1 4.2 4.5 8. Swaziland 3.9 3.6 10.7 9. Botswana 3.3 2.6 4.5 Median 3.3 3.6 4.5 Group II 10. Ethiopia 3.6 4.2 8.9 11. Somalia 6.0 8.0 4.2 12. Zaire 6.2 4.5 neg. 13. Madagascar 8.6 17.5 14.5 14. Uganda 2.5 5.7 neg. 15. Zimbabwe 6.8 3.2 neg. 16. Zambia 9.2 7.0 24.3 Median 6.2 5.7 24.3 Eastern Africa median 4.0 4.3 5.2 neg. = Negative. /a The years 1961-68 were chosen rather than 1960-67 because of data constraints. The method used for computing ICORs is described in Annex 2. Source: Data Files, World Bank. - 43 - ANNEX Table 6: INCREMENTAL GROSS CAPITAL OUTPUT RATIOS IN FIVE DEVELOPED COUNTRIES, 1967 TO 1974 1967 1968 1969 1970 1971 1972 1973 1974 1. France 6.5 5.1 3.4 3.5 4.7 4.4 4.8 8.6 2. Japan 2.6 2.7 3.5 - 3.6 5.2 4.4 4.2 -- 3. West Germany 7.3 -- 3.3 4.7 9.5 8.2 5.3 -- 4. UK 7.2 5.6 14.0 8.2 7.6 7.4 3.3 -- 5. USA 6.9 4.3 7.2 6.3 -- 4.3 3.6 -- -- = Not available. Source: John C. Carrington and George T. Edwards Financing Industrial Investment, The Macmillan Press, 1979. - 44 - ANNEX Table 7: HISTORICAL INCREMENTAL CAPITAL OUTPUT RATIOS IN DEVELOPED COUNTRIES /a ICOR 1. UK 6.3 2. Germany 6.1 3. Italy 5.7 4. Denmark 4.4 5. Norway 7.3 6. Sweden 5.5 7. USA 6.5 8. Canada 5.6 9. Australia 6.9 10. Japan 4.3 11. Argentina 7.6 12. Union of South Africa 4.9 /a Based on a varying number of years from the late 19th to the mid 20th century. Source: Simon Kuznets "Quantitative Aspects of the Economic Growth of Nations" in Economic Devel- opment and Cultural Change, Vol. IX, No. 4, Part II, July 1961. Table 8: THE RATIO OF GROSS DOMESTIC INVESTMENT TO GDP, 1967-78 Three-Year Moving Averages /a (Percentages) 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 Group I 1. Burundi 7.8 8.3 7.5 7.3 5.5 5.8 6.2 7.8 9.1 10.2 12.7 14.0 2. Malawi 16.7 17.1 21.6 22.8 25.1 23.8 25.4 26.7 24.3 23.6 26.2 31.5 3. Rwanda 8.8 7.7 7.7 8.1 9.3 10.5 11.2 12.8 13.7 15.9 21.9 24.0 4. Tanzania 18.6 18.7 20.6 23.9 26.3 25.9 24.5 24.2 23.9 22.8 22.2 22.3 5. Lesotho 11.2 11.4 11.5 12.2 12.9 15.9 17.0 24.0 30.8 37.5 40.2 39.0 6. Sudan 10.8 10.3 10.5 10.1 9.1 8.6 11.9 15.7 18.9 17.9 17.3 16.5 7. Kenya 21.4 21.7 23.3 24.9 25.9 24.5 26.4 25.1 25.3 23.5 28.0 28.9 8. Swaziland 25.2 22.7 20.3 19.8 20.7 22.8 24.6 27.7 31.2 33.3 34.0 -- 9. Botswana 23.0 28.1 34.4 41.2 47.5 50.0 52.3 51.2 49.0 41.8 39.4 -- UL Median 16.7 17.1 20.3 19.8 20.7 22.8 24.5 24.2 24.3 23.5 26.2 24.0 Group II 10. Ethiopia 15.1 14.8 13.8 13.0 12.9 12.9 12.2 11.5 10.9 10.6 9.6 9.4 11. Somalia 13.3 13.7 13.6 13.6 14.0 15.1 21.2 23.0 24.5 22.1 21.4 20.8 12. Zaire 17.7 20.8 22.9 27.3 30.8 32.1 31.2 30.3 28.8 30.8 26.0 21.0 13. Madagascar 14.7 15.9 16.3 16.7 15.7 15.3 14.2 13.8 13.3 12.9 13.3 16.4 14. Uganda 16.2 17.6 16.9 17.1 14.8 12.9 11.1 9.8 8.9 6.6 5.3 4.7 15. Zimbabwe 22.6 23.4 22.7 22.0 22.7 24.1 26.4 29.2 28.1 25.6 21.5 20.0 16. Zambia 32.7 28.9 27.4 28.3 - 33.6 33.9 33.7 35.4 36.5 35.8 32.3 26.5 Median 16.2 17.6 16.9 17.1 15.7 15.3 21.2 23.0 24.5 22.1 21.4 16.4 Eastern Africa median 16.5 17.9 18.6 18.5 18.2 19.4 22.9 24.1 24.4 23.2 22.1 20.9 -- = Not available. /a Average of share of investment in current prices. For Ethiopia from 1971 onwards and for Burundi from 1977, only fixed investment data are available. Source: Data Files,World Bank. Table 9: INDEX OF REAL GROSS FIXED CAPITAL FORMATION BY THE CENTRAL GOVERNMENT /a (1972 = 100) 1972 1973 1974 1975 1976 1977 1978 1979 Group I I. Burundi -- -- -- -- -- -- -- -- 2. Malawi 100.0 128.7 183.6 264.8 186.7 242.4 253.6 341.2 3. Rwanda /b -- 100.0 133.0 279.9 571.1 571.9 154.5 -- 4. Tanzania 100.0 85.6 120.2 136.7 150.2 162.2 175.9 -- 5. Lesotho 100.0 86.5 169.9 -- -- -- -- -- 6. Sudan 100.0 78.4 111.3 215.1 236.1 411.4 300.3 -- 7. Kenya 100.0 96.0 81.3 82.0 91.4 108.3 119.7 126.2 8. Swaziland 100.0 243.0 171.9 185.1 185.1 261.1 -- -- 9. Botswana 100.0 140.8 164.2 155.7 190.5 239.8 308.0 315.2 Group II 10. Ethiopia 100.0 82.6 59.7 71.4 102.1 127.9 -- -- 11. Somalia -- -- -- -- -- -- -- -- 12. Zaire 100.0 203.8 273.1 113.0 233.4 217.8 194.1 -- 13. Madagascar 100.0 69.3 -- -- -- -- -- -- 14. Uganda -- -- -- -- -- -- -- -- 15. Zimbabwe -- __ __-- -- -- -- _ 16. Zambia 100.0 - 34.1 63.1 -- -- 60.3 48.2 -- -- = Not available. /a Gross fixed capital formation deflated by the unit value index of manufactured exports of developed countries (MUV Index) from U.N. Monthly Bulletin of Statistics. /b 1973 = 100 instead of 1972. Source: 1. IMF (1981) Government Finance Statistics Yearbook. 2. U.N. Monthly Bulletin of Statistics. Table 10: THE RATIO OF GROSS NATIONAL SAVINGS TO GDP Three-Year Moving Averages, 1967-78 (Percentages) 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 Group I 1. Burundi - 1.4 - 1.2 -0.8 -0.6 - 2.1 - 2.2 - 1.4 2.2 3.4 6.6 5.9 5.3 2. Malawi 0.6 1.3 4.9 8.0 10.9 11.9 14.7 14.8 12.6 12.0 14.9 16.4 3. Rwanda 2.6 2.1 1.9 1.4 0.9 1.4 2.2 3.3 4.6 7.7 10.9 12.3 4. Tanzania 17.0 17.2 17.7 18.6 19.0 17.6 14.4 11.4 12.7 14.2 14.2 10.5 5. Lesotho -10.3 - 8.7 -6.4 -6.9 -13.1 -10.2 -12.4 -6.9 -14.6 -14.1 -9.4 -2.9 6. Sudan 7.8 7.9 9.1 9.2 8.2 6.6 6.1 4.3 3.5 2.1 2.2 1.5 7. Kenya 17.7 17.8 19.3 19.0 18.8 16.5 17.5 15.0 16.2 18.4 20.7 19.4 8. Swaziland 12.0 5.7 3.5 8.9 15.5 21.1 25.5 33.4 42.8 44.9 32.3 -- 9. Botswana -11.5 -12.1 -8.4 -0.7 6.4 11.2 20.3 25.9 30.6 25.1 21.0 -- Median 2.6 2.1 3.5 8.0 8.2 11.2 14.4 11.4 12.6 12.0 14.2 10.5 Group II 10. Ethiopia 11.9 12.0 11.7 11.0 10.8 11.4 12.6 11.2 9.8 7.4 5.9 4.0 11. Somalia 4.5 4.8 6.1 6.1 7.8. 9.0 8.9 7.1 6.8 9.1 8.1 6.4 12. Zaire 16.2 20.7 21.8 21.1 18.8 18.0 17.7 15.2 8.5 2.7 2.3 4.9 13. Madagascar 6.9 8.9 9.8 9.6 8.8 8.1 8.0 7.8 8.4 8.9 9.6 9.0 14. Uganda 15.1 17.0 17.4 15.6 13.9 12.2 12.1 9.4 8.2 6.8 5.7 4.6 15. Zimbabwe 19.7 20.9 20.7 20.6 21.0 22.6 25.2 26.2 25.7 24.2 22.1 19.3 16. Zambia 36.0 38.9 41.0 38.1 31.8 30.6 34.3 29.5 27.1 23.2 25.9 22.8 Median 15.1 17.0 17.4 15.6 13.9 12.2 12.6 11.2 8.5 8.9 8.1 6.4 Eastern Africa median 9.9 8.4 9.5 9.4 10.9 11.7 11.7 11.3 9.2 9.0 10.3 7.7 x -- = Not available. Source: Data Files, World Bank. Table 11: TERMS OF TRADE ESTIMATES, 1967 TO 1978 Three-Year Moving Averages 1975 = 100 /a 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 Group I i. Burundi -- -- -- -- -- -- -- -- -- -- -- -- 2. Malawi 87 83 89 98 106 106 101 98 97 101 102 99 3. Rwanda 114 108 113 116 118 115 115 110 120 156 182 182 4. Tanzania 98 96 99 99 100 101 106 107 111 120 127 122 5. Lesotho -- -- -- -- -- -- -- -- -- -- -- -- 6. Sudan 77 76 79 82 83 94 94 99 101 100 95 90 7. Kenya 115 108 112 113 119 119 115 109 109 130 146 143 8. Swaziland -- __ __ __ __ __ __ __ __ __ __ __ 9. Botswana -- -- -- -- -- -- -- -- 4- -- -- -- Median 98 96 99 99 106 106 106 107 109 120 127 122 Group II 10. Ethiopia 131 128 136 136 138 133 128 116 122 155 175 171 11. Somalia 138 134 133 135 136 132 123 110 102 102 105 104 12. Zaire 164 175 190 183 160 149 151 140 121 107 103 97 13. Madagascar 112 111 113 117 121 123 118 110 106 119 124 122 14. Uganda 117 117 122 125 126 121 112 106 112 152 168 168 15. Zimbabwe -- -- -- -- -- -- -- -- -- -- -- -- 16. Zambia 183 197 217 204 172 160 169 157 130 102 96 93 Median 135 131 135 136 137 133 126 113 117 113 115 113 Eastern Africa median 115 111 113 117 121 121 115 110 111 119 124 122 x -- = Not available. /a The index for the year 1975 rather than the three-year moving average for that year was equal to 100. Source: UN (1980) UNCTAD Handbook of International Trade and Development Statistics. Table 12: GROSS NATIONAL SAVINGS AS A PERCENTAGE OF GROSS NATIONAL INVESTMENT Three-Year Moving Averages, 1967-78 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 Group I 1. Burundi -17.9 -14.5 -10.7 - 8.2 - 38.2 -37.9 -22.6 28.2 37.4 64.7 46.5 37.9 2. Malawi 3.6 7.6 22.7 35.1 43.4 50.0 57.9 55.4 51.9 50.8 56.9 52.1 3. Rwanda 29.5 27.3 24.7 17.3 9.7 13.3 19.6 25.8 33.6 48.4 49.8 51.3 4. Tanzania 91.4 92.0 85.9 77.8 72.2 68.0 58.8 47.1 53.1 62.3 64.0 47.1 5. Lesotho -92.0 -76.3 -55.7 -56.6 -101.6 -64.2 -72.9 -28.8 -47.4 -37.6 -23.4 -7.4 6. Sudan 72.2 76.7 86.7 91.1 90.1 76.7 51.3 27.4 18.5 11.7 12.7 9.1 7. Kenya 82.7 82.0 82.8 76.3 72.6 67.3 66.3 59.8 64.0 78.3 73.9 67.1 8. Swaziland 47.6 25.1 17.2 44.9 74.9 92.5 104.9 120.6 137.2 134.8 95.0 -- 9. Botswana -50.0 -43.1 -24.4 - 1.7 13.5 22.4 38.8 50.6 62.4 60.0 53.3 -- Median 29.5 25.1 22.7 35.1 43.4 50.0 51.3 47.1 51.9 60.0 53.3 47.1 Group II 10. Ethiopia 78.8 81.1 84.8 84.6 83.7 88.4 103.3 97.4 89.9 69.8 61.5 42.6 11. Somalia 33.8 35.0 44.9 44.9 55.7 59.6 42.0 30.9 27.8 41.2 37.9 30.8 12. Zaire 91.5 99.5 95.2 77.3 61.0 56.1 56.7 50.2 29.5 8.8 8.8 23.3 13. Madagascar 46.9 56.0 60.1 57.5 56.1 52.9 56.3 56.5 63.2 69.0 72.2 54.9 14. Uganda 93.2 96.6 103.0 91.2 93.9 94.6 109.0 95.9 92.1 103.0 107.5 97.9 15. Zimbabwe 87.2 89.3 91.2 93.6 92.5 93.8 95.5 89.7 91.5 94.5 102.8 96.5 16. Zambia 110.1 134.6 149.6 134.6 94.6 90.3 101.8 83.3 74.2 64.8 80.2 86.0 Median 87.2 89.3 91.2 84.6 83.7 88.4 95.5 83.3 74.2 69.0 72.2 54.9 Eastern Africa median 59.9 66.4 71.5 66.9 66.6 63.5 57.3 53.0 57.8 63.5 59.2 49.2 -- = Not available. 3ource: Data Files, World Bank. - 50 - ANNEX Table 13: NET OFFICIAL DEVELOPMENT ASSISTANCE AS A PERCENTAGE OF EXTERNAL RESOURCES INFLOW /a Average 1976 1977 1978 1979 1977-79 Group I 1. Burundi 100.0 89.4 99.1 100.7 96.4 2. Malawi 78.7 83.0 80.8 76.3 80.0 3. Rwanda 98.4 100.4 101.2 99.7 100.4 4. Tanzania 79.3 80.9 82.1 79.9 81.9 5. Lesotho 100.0 99.2 96.5 102.4 99.4 6. Sudan 57.9 54.6 63.5 87.2 68.4 7. Kenya 39.8 32.1 60.6 77.2 56.6 8. Swaziland 74.4 77.4 88.6 66.7 77.6 9. Botswana 83.4 112.9 392.0 70.4 191.8 Median 79.3 83.0 88.6 79.9 81.9 Group II 10. Ethiopia 102.6 108.0 106.8 78.9 97.9 11. Somalia 88.9 71.1 91.8 70.3 77.7 12. Zaire 39.6 51.0 45.1 55.5 50.5 13. Madagascar 102.4 113.1 76.7 57.0 82.3 14. Uganda 50.1 73.3 -- 104.3 88.8 15. Zimbabwe 21.4 446.7 161.4 145.3 251.1 16. Zambia 46.9 64.5 58.5 84.1 69.0 Median 50.1 73.3 84.3 78.9 82.3 Eastern Africa median 79.0 82.0 88.6 79.4 82.1 -- = Not available. /a Net Official Development Assistance refers to disbursements of concessional loans or grants. External Resource Flows include, in addition, private grants, transactions on commercial terms, direct investment and purchases of securities of inter- national development organizations. All defense related trans- actions are excluded. Source: OECD (1980) Development Co-operation, 1980 Review. - 51 - ANNEX Table 14: DIRECT INVESTMENT AS A PROPORTION OF LONG-TERM CAPITAL INFLOWS /a (Percentages) Average 1974 1975 1976 1977 1978 1979 1977-79 Group I 1. Burundi -- -- -- -- -- -- -- 2. Malawi 32.6 15.1 20.7 7.4 10.9 11.2 9.8 3. Rwanda 23.4 17.5 25.2 16.0 18.5 55.4 30.0 4. Tanzania 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5. Lesotho - -- -- -- -- -- 6. Sudan 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7. Kenya -- 10.1 19.4 26.3 13.9 14.0 18.1 8. Swaziland -60.0 6.3 36.7 59.8 44.4 74.7 59.6 9. Botswana /b -- -54.3 236.6 -54.8 78.1 122.3 48.5 Group II 10. Ethiopia 56.7 27.7 6.5 16.0 0.0 0.0 5.3 11. Somalia 1.2 12.9 3.2 12.1 0.3 -- 6.2 12. Zaire -- -- -- -- -- -- -- 13. Madagascar 57.1 13.6 15.4 -16.7 -25.0 -2.9 -14.9 14. Uganda 12.2 35.4 -7.2 - 6.9 - 2.5 -4.8 - 4.7 15. Zimbabwe -- -- -- -- -- -- .16. Zambia 50.8 10.2 25.0 88.2 -- -- -- __ e Not available. /a Both direct investment and long-term capital inflow are from the IMF source listed below. OECD estimates of direct investment are differ- ent. /b The entries for Botswana, Lesotho and Swaziland cover imputed pay- ments to South Africa under the Customs Union Agreement. In some years Botswana is a net creditor. Source: Balance of Payments Yearbook, Vol 31, December 1980, IMF. - 52 - ANNEX Table 15: NET PRIVATE DIRECT INVESTMENT FROM DAC SOURCES /a (In US$ millions) /b 1976 1977 1978 1979 Group I 1. Burundi -0.6 ( --) -0.3 ( --) 0.9 ( --) -0.3 ( --) 2. Malawi 5.3 ( 9.7) 0.2 ( 5.7) -7.9 (10.1) -- ( 13.7) 3. Rwanda 0.1 ( 5.9) 0.1 ( 5.2) -0.7 ( 4.9) 0.4 ( 12.9) 4. Tanzania 6.5 ( 0.0) 2.9 ( 0.0) 6.2 ( 0.0) 2.0 ( 0.0) 5. Lesotho -- ( --) 0.4 ( --) -- ( --) -- ( --) 6. Sudan 5.9 ( 0.0) 4.8 ( 0.0) 4.1 ( 0.0) -4.7 ( 0.0) 7. Kenya 20.5 (75.4) 6.1 (75.0) -0.6 (63.7) 1.4 ( 17.2) 8. Swaziland 2.0 ( 4.6) 1.7 (12.2) 0.3 (16.1) 1.3 ( 62.3) 9. Botswana 3.2 (11.3) 0.3 (12.5) -0.3 (42.1) -- (154.2) Group II 10. Ethiopia 0.2 ( 4.3) -1.2 ( 5.9) -- ( 0.0) -- ( 0.0) 11. Somalia 1.3 ( 2.2) 56.6 ( 8.1) -0.1 ( 0.3) -- ( --) 12. Zaire 245.2 ( --) 16.4 ( --) 93.8 ( --) 143.9 ( --) 13. Madagascar -0.4 ( 2.3) -5.5 (-3.5) 0.6 (-3.8) -0.6 ( -6.5) 14. Uganda 2.2 ( 1.2) -- ( 0.8) 0.1 ( 1.0) -- ( 1.5) 15. Zimbabwe 27.5 ( --) -1.7 t --) -0.6 ( --) -0.9 ( --) 16. Zambia 26.7 (31.1) 2.8 (17.7) 25.9 ( --) 0.8 ( --) -- = Not available. /a The figures in parentheses are from the IMF. They also refer to all direct in- vestment. Both sets of data include reinvestments by non-resident entities. Portfolio investment and export credits are excluded. The Development Assistance Committee (DAC) forms part of the Organization for Economic Co-operation and Development (OECD). lb The IMF figures are in SDRs in the source publication. They have been con- verted to dollars at the period average exchange rates. Source: 1. OECD (1981) Geographical Distribution of Financial Flows to Develop- ing Countries. 2. IMF (1980) Balance of Payments Yearbook. - 53 - ANNEX Table 16: THE STOCK OF FOREIGN DIRECT INVESTMENT IN EASTERN AFRICA, END 1978 /a (In US$ million) Stock Group I 1. Burundi 26 2. Malawi 100 3. Rwanda 25 4. Tanzania 170 5. Lesotho 4 6. Sudan 60 7. Kenya 520 8. Swaziland 50 9. Botswana 57 Group II 10. Ethiopia 100 11. Somalia 100 12. Zaire 1,250 13. Madagascar 190 14. Uganda 10 15. Zimbabwe 400 16. Zambia 330 /a Stock figures represent estimated book values. The data refer only to DAC countries' investments in Eastern Africa, and exclude South African investments. Source: OECD (1980) Development Co-operation 1980 Review. - 54 - ANNEX Table 17: GROSS EUROCURRENCY CREDITS TO EASTERN AFRICA /a (US$ million) 1973 1974 1975 1976 1977 1978 1979 Group I 1. Burundi -- -- -- -- -- -- -- 2. Malawi 5.3 - - - 50.0 - 50.0 3. Rwanda -- -- -- -- -- -- -- 4. Tanzania - - - - - 12.0 5. Lesotho - - - - - - 10.0 6. Sudan 3.4 220.0 36.8 19.0 - 9.5 - 7. Kenya 4.5 - - - - - 212.0 8. Swaziland - - - - - 28.0 - 9. Botswana - - - - - 45.0 - Group II 10. Ethiopia - - - - - - 14.0 11. Somalia -- -- -- -- -- -- -- 12. Zaire 223.0 71.3 27.0 - - - - 13. Madagascar - - - - 3.0 29.6 26.3 14. Uganda -- -- -- -- -- -- -- 15. Zimbabwe -- -- -- -- -- -- -- 16. Zambia 150.0 - 160.0 - - - 12.8 -- = Not available. - = Nil or negligible. /a Eurocurrency credits are credits with a maturity of more than one year made by private banks using funds deposited or borrowed by them in external currencies. Source: World Bank, Borrowing in International Capital Markets. - 55 - ANNEX Table 18: CAPACITY.UTILIZATION IN SELECTED SECTORS IN TANZANIA, 1978 and 1979 Industry Production as a pe-rcentage of capacity 1978 1979 Sugar 39 39 Distilled spirits and liquors 102 89 Tobacco manufacturing 92 94 Spinning and weaving 64 63 Madeup textiles 49 66 Footwear 68 56 Fertilizers and pesticides 42 52 Plastic 46 24 Glass 23 15 Cement, lime, plaster 80 88 Iron, steel and metals 55 62 Structural metal products 47 47 Fabricated metal products 42 37 Electrical machinery 74 66 Motor vehicles 42 33 Motorcycles and bicycles 30 12 Source: Data Files, The World Bank - 56 - ANNEX Table 19: CAPACITY UTILIZATION IN A SAMPLE OF PARASTATAL FIRMS IN TANZANIA, 1979 Production as a percentage of Parastatal capacity 1. Tanzania Fertilizer Co. 52 2. Steel Rolling Mills 62 3. ALUCO (Aluminum Sheets) 45 4. PIPECO (Pipes) 71 5. ALAF Steel Cast 54 6. GALCO (Iron Sheets) 74 7. ALAF Steel Co. 25 8. National Bicycle Co. 25 9. Ubungo Farm Implements 67 10. Tanzania Gables 39 11. Tanzania Breweries 89 12. Tanzania Cigarette Co. 94 13. Tanzania Shoe Co. 56 14. Legy Plastics 34 15. Metal Box Co. 27 16. Friendship Textile Mill 82 Soiurce: nsta wiles, The World Rpnk - 57 - ANNEX Table 20: CAPACITY UTILIZATION IN A SAMPLE OF PUBLIC ENTERPRISES, 1976-78, SOMALIA Production as a percentage of capacity Parastatal 1976 1977 1978 1. ITOP Fruit Cannery 36 29 22 2. Mogadishu Meat Factory 51 53 46 3. Kismayo Meat Factory 61 37 -- 4. Flour and Pasta Factory 58 64 61 5. INCAs Box Factory 36 27 25 6. SOMALTEX -- 65 75 Source: Data Files, The World Bank - 58 - ANNEX Table 21: CAPACITY UTILIZATION IN CERTAIN MANUFACTURING FIRMS IN SUDAN, 1973 (Percentages) Percent of Firm and/or Department Product capacity utilized 1. Sudan Knitwear Knitwear 67 2. Khartoum Tannery Leather (i) Beam House Cow hides 92 Sheep skins 38 (ii) Chrome Section Cow hides 52 (iii) Finish Section Da side leather 57 Vegetable process 100 Pickles process 100 3. Sudan Soap Factory Oils & oil products 46 4. Blue Nile Plastic Co. Plastics (i) Plastic crates 67 (ii) Polyethelene filters 51 (iii) Printing 67 5. Karima Canning Factory Food canning 15 6. The Flour Mill Corp. Flour 80 7. Coldair Engineering Co. Electrical appliances (i) Refrigerators 54 (ii) Water coolers 18 (iii) Air conditioners 16 (iv) Commercial refrigerators 8 (v) Air coolers 20 8. Bata Corp. Shoes 42 9. Blue Nile Brewery Beer 99 10. Guneid Sugar Sugar 70 11. Girba Sugar Sugar 118 Source: Public Corporations in Sudan, 1977, bvernment of Sudan. - 59 - ANNEX Table 22: CAPACITY UTILIZATION IN THE PUBLIC INDUSTRIAL SECTOR IN SUDAN, 1975/76 Total number Below 35% 35 to 65% Above 65% of firms Food 6 1 2 9 Sugar and beverages 0 1 2 3 Oil mills 1 2 1 4 Leather 1 3 0 4 Mining 1 1 0 2 Building materials 1 2 0 3 Spinning and weaving 0 2 0 2 10 12 5 27 Source: Public Corporations in Sudan, 1977, Qbvernment of Sudan. - 60 - ANNEX Table 23: FREQUENCY DISTRIBUTION OF CAPACITY UTILIZATION IN PLANTS/PROCESSES OF THE INDECO GROUP, ZAMBIA, 1981-82 Number of Percent of plants/ Percentage 1/ capacity utilized processes of total Industries- 0 to 10 percent 5 9 Oils and fats, car assembly, batteries, engineering. 10 to 30 percent 12 21 Tires, jute, glass, engineering, batteries, fertilizer, canning, detergents, wood products, tiles. 30 to 50 percent 8 14 Milling, glass, cooking oil, coffee, saw milling. 50 to 70 percent 20 35 Cement, stone, pharmaceuticals, polyprope- lene, explosives, engineering, beer, milling, bakery, sugar, gases, wood. 70 to 90 percent 9 16 Lime, explosives, spinning, milling, bakery, beer, sugar. Above 90 percent 3 5 Textile weaving, explosives. Total 57 1/ There may be overlaps because different processes or plants in an industry have different percentages of capacity utilized. Source: INDECO Group Financial Review, 1981-82, mimeo. Table 24: QUANTUM INDEX OF IMPORTS, 1967 TO 1978 Three-Year Moving Averages 1975 = 100 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 Group I 1. Burundi -- 65 70 76 84 86 84 92 100- 113 122 139 2. Malawi 67 64 69 77 87 92 92 98 100 101 105 151 3. Rwanda 49 51 57 63 68 62 62 77 100 116 134 146 4. Tanzania 75 74 82 92 102 104 105 105 100 94 101 101 5. Lesotho /a -- 28 28 29 37 48 64 81 100 114 121 123 6. Sudan 54 57 65 69 71 69 72 88 100 108 106 94 7. Kenya 89 90 98 111 119 120 114 108 100 100 115 116 8. Swaziland /a -- 81 86 90 88 87 88 93 100 110 124 -- 9. Botswana /a- 36 44 48 55 65 78 87 100 106 116 -- Median -- 64 69 76 84 86 84 92 100 108 116 Group II 10. Ethiopia 114 111 117 116 116 111 103 98 100 104 117 119 11. Somalia 60 64 66 70 76 89 95 100 100 112 121 130 12. Zaire 71 78 98 111 125 126 128 112 100 80 64 50 13. Madagascar 113 122 127 133 130 123 107 103 100 101 101 113 14. Uganda 176 176 178 201 188 169 128 113 100 90 98 92 15. Zimbabwe /b -- 82 89 96 105 109 109 109 100 89 75 75 16. Zambia 102 109 112 115 119 112 103 103 100 91 73 64 Median 108 109 112 115 119 112 107 103 100 91 98 92 Eastern Africa Median _ 76 84 91 95 98 99 99 100 103 111 -i /a Data for these countries are from Data Files, EPD. /b Data for Zimbabwe is derived from IFM (1981) International Financial Statistics Yearbook. Source: UN (1980) UNCTAD Handbook of International Trade and Development Statistics. Table 25: PETROLEUM IMPORTS INTO EASTERN AFRICA (In '000 barrels per day of oil equivalent) Three-Year Moving Averages 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 Group I 1. Burundi 0.57 0.6 0.6 0.5 0.4 0.4 0.47 0.47 0.5 0.47 0.5 2. Malawi 1.7 1.8 2.0 2.2 2.4 2.6 2.6 2.7 2.8 2.8 2.8 3. Rwanda 0.3 0.4 0.4 0.4 0.4 0.5 0.5 0.5 0.6 0.7 0.8 4. Tanzania 18.1 21.2 22.7 25.1 27.6 32.6 34.8 31.2 26.0 20.2 20.2 5. Lesotho -- -- -- -- -- -- -- -- -- -- -- 6. Sudan -- -- -- -- -- -- -- -- -- -- -- 7. Kenya 41.6 43.4 45.5 48.9 51.9 54.9 57.3 58.4 56.7 53.9 52.7 c 8. Swaziland -- -- -- -- -- -- -- -- -- -- -- 9. Botswana -- -- -- -- -- -- -- -- -- -- Median 1.7 1.8 2.0 2.2 2.4 2.6 2.6 2.7 2.8 2.8 2.8 Group II 10U7EtiTopia 8.8 10.4 12.1 12.4 13.2 13.9 13.8 13.3 12.5 12.0 12.4 11. Somalia 1.2 1.2 1.2 1.3 1.4 1.4 1.5 2.1 2.7 3.8 4.5 12. Zaire -- -- -- -- -- -- -- -- -- -- -- 13. Madagascar 7.2 8.6 10.2 11.2 12.2 12.7 12.9 13.8 13.2 12.9 11.5 14. Uganda 5.5 6.4 7.7 8.8 9.2 8.9 8.4 8.0 7.7 7.9 7.9 15. Zimbabwe 8.4 9.4 9.7 10.1 10.5 10.9 11.1 11.1 11.4 11.8 12.3 16. Zambia 5.9 7.5 8.1 8.7 9.2 12.4 15.0 19.8 20.0 20.5 18.5 Median 6.6 8.1 8.9 9.5 9.9 11.7 12.0 12.2 12.0 11.9 11.9 t Eastern Africa Median 5.9 7.5 8.1 8.8 9.2 10.9 11.1 11.1 11.4 11.8 11.5 -- = Not available. Source: Data Files, The World Bank. - 63 - ANNEX Table 26: PUBLIC CURRENT EXPENDITURE PER PUPIL IN CONSTANT PRICES AT THE FIRST LEVEL (AGES 7 TO 13) /a Currency unit 1970 1975 1. Botswana Pula 28.1 34.7 2. Ethiopia Birr 42.3 43.6 3. Kenya Shilling 163.0 216.4 4. Lesotho Rand 0.73 0.46 5. Madagascar Franc 9022.0 5613.0 6. Malawi Kwacha 11.0 6.5 7. Uganda Shilling 141.3 81.4 8. Zambia Kwacha 28.2 35.6 /a Both teaching and non-teaching expenditures are in- cluded. The GDP deflator has been used to deflate expenditures at current prices. Sources: 1. UNESCO (1980) Statistical Yearbook. 2. Data Files, The World Bank. Table 27: SHARE OF PUBLIC INVESTMENT (INCLUDING PARASTATAL INVESTMENT) IN TOTAL (THREE-YEAR MOVING AVERAGES) (Percentages) Average d/ 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1977-79 Group I 1. Burundi 64.1 66.0 66.4 64.8 65.3 69.7 75.4 80.1 84.6 87.5 90.4 -- -- 90.4 2. Malawi 52.1 50.1 54.0 57.3 59.9 58.3 60.3 61.7 61.3 61.4 61.5 62.8 62.3 62.2 3. Rwanda -- -- 47.8 51.9 54.2 -- -- -- -- -- -- -- -- -- 4. Tanzania 47.7 51.6 55.5 62.5 69.3 70.7 69.9 66.7 59.9 52.8 46.8 45.8 -- 46.3 5. Lesotho -- -- -- -- -- -- ---- -- -- -- -- -- -- 6. Sudan /a -- -- -- 28.2 26.4 28.5 34.2 36.3 42.9 41.6 42.0 -- -- 42.0 7. Kenya -- -- -- -- -- -- 42.2 -- -- 44.7 44.7 8. Swaziland -- -- -- -- -- -- -- -- -- -- -- -- -- -- 9. Botswana /b -- -- -- -- -- -- -- -- -- -- 56.5 58.2 60.7 58.5 Group II 10. Ethiopia -- -- -- -- -- -- -- -- -- 47.7 56.7 62.6 68.0 62.4 11. Somalia -- -- -- -- -- -- -- -- -- -- -- -- -- 12. Zaire -- -- -- -- -- -- -- -- -- -- -- -- -- __ 13. Madagascar -- -- -- -- -- 39.6 -- -- -- -- -- -- -- -- 14. Uganda 18.1 21.5 27.2 34.0 37.5 -- -- -- -- -- -- -- -- -- 15. Zimbabwe -- -- -- 29.0 -- -- -- 33.0 -- -- -- 40.0 -- 40.0 16. Zambia -- -- -- -- -- -- -- -- -- -- -- -- 93.0/c 93.0 -- = Not available /a Estimates of the Bank of Sudan. The Ministry of Planning has alternative estimates. /b The estimates for Botswana refer to the percentage of total investment financed by public funds (domestic and foreign). /c Figure for 1980. /d Where data for some of the period is missing, the average relates to years for which data is available. Note: This table has been compiled from a variety of national sources. Concepts are not comparable between countries and coverage may not be comprehensive or accurate. Total investment refers in almost all cases to the monetized or formal sector. Source: Data Files, The World Bank. - 65 - ANNEX Table 28: INDEX OF REAL RECURRENT EXPENDITURE ON ECONOMIC SERVICES IN FOUR EASTERN AFRICAN COUNTRIES 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 Kenya 100 113 111 114 118 147La 153 134 171 181 Sudan 100 110 122 118 164 155 158 139 130 111 Tanzania 100 104 115 154 186 --la 291 265 342 -- Zambia 100 140 111 99 97 171 134 127 91 -- -- = Not available. a/ Series broken in this year. Note: The GDP deflator was used to convert series into constant prices. Sources: Data Files, World Bank - 66 - ANNEX II INTERRELATIONS BETWEEN THE ICOR, GROWTH RATE, INVESTMENT RATIO AND THE INVESTMENT RATE The ICOR for the period i to ; is defined as the ratio of invest- ment summed over the period i-1 to j-1 to output in period j minus output ir period i. The ICOR, the rate of growth of output, the investment ratio and the rate of investment in Eastern Africa are related to each other. It is worthwhile examining some identities. Let K = capital stock Y = output I = investment and the operator indicate changes in each variable. Then AK = ICOR Also & = I I/. i ,Ay 'A!!Y = Y/ y ............ -- -- -... .......................... i Y y This identity states that ICOR = investment ratio/growth rate of output AlsoAK AK K y or taking logarithms log ~K- = logi~K_ log +Y log K/ .Mi 8AY = o-KlgS + lgKy ................................(i K Or log (ICOR) = log (growth rate of capital) - log (growth rate of output) + log (average capital output ratio)!/. Thus the ICOR is inversely related to the growth rates of output and capital and directly related to the investment ratio. Kuznets (1960), 1/ See A.A. Walters (1966) and Kazuo Sato (1971) for analysis along similar lines. - 67 - ANNEX II Kuznets (1961), K. Sato (1971) and J. Vanek and A.H. Studenmund (1968) among others have estimated these relations and also other behavioral ones. Some of these exercises cannot be replicated for the Eastern Africa sample since they involve a knowledge of the rate of depreciation of capital stock and net investment magnitudes. Kuznets (op. cit.) found the gross ICOR to be significantly related to the growth rate of output as well as per capita income. The latter association may be due to the relation between sectoral shares in output and income. As incomes rise, the economy generally shifts towards a non-agricultural composition of output and ICORs in the non-agri- cultural sectors are typically higher than in agriculture. There is, how- ever, also capital deepening with development, so that at significantly higher levels of income, the ICOR in all sectors may be higher. Sato also found in some of his regressions that the share of exports in goods and services is related positively to the ICOR. Export items generally require more capital in production, processing and transport than goods intended for domestic consumption, especially if they are minerals. Overall, how- ever, Sato concluded that the relation between various behavioral variables and the ICOR was weak in samples consisting exclusively of low income countries. In the case of the Eastern African countries we are more inter- ested in why growth rates of output decreased and the ICOR rose between periods rather than in an explanation of the ICOR at a point in time. However cross section regressions do reveal some interesting patterns. The inverse relation between the ICOR and growth rate, was, we have seen valid for Eastern Africa on an intertemporal basis. Output growth was lower in the 1973-79 sub-period relative to the 1967-73 one and - 68 - ANNEX II ICORs were on the average higher. The same relation holds cross section- ally. The correlation coefficients between ICOR and the growth rate of output were -0.35 and -0.82 in the two sub-periods respectively, both significant on the basis of the 't' test at the 90 percent level of significance. The correlation coefficient between ICOR for the 1967-73 sub- period and the investment ratio in 1973 was positive and equal to 0.61. This was significantly different from zero at the 90 percent level. For the sub-period 1973-79 however this coefficient was not significantly dif- ferent from zero. This may have been due to the omission of several coun- tries from the data set due to their ICORs taking negative values.-/ Besides the above relations, however, another statistical as- sociation was noticed in the data for Eastern Africa. This was an inverse association between the ICOR and the growth rate of investment. In the 1967-73 period this correlation was not significant, though close to it. In the 1973-79 period, the correlation coefficient was -0.58 and signifi- cant. This relation does not follow from an accounting identity. Evi- dently in countries where the ICOR is high, the growth rate of investment is low. This may indicate that the high ICORs characterizing the Eastern African economies are not merely a transient phenomenon due to the lumpi- ness of investment and gestation lags. If that was the case, it is more likely that high ICOR levels would be associated positively with the rate of growth of investment. However the evidence is too limited to draw any strong conclusions. 1/ A negative ICOR is inadmissible in statistical manipulations as the lower the ICOR the more productive is investment, yet a negative ICOR is an extreme example of inefficiency of investment. - 69 - ANNEX II The contribution of each sector to the change in overall ICOR can be identified according to the following breakdown given in "Capital and Growth in India, 1950-71" by Martin Wolf in World Bank Staff Working Paper No. 279. The symbols are from the original. Let I = aggregate ICOR I = ICOR in sector i Ci = Share of sector i in the increment in output IAYi AtYJ Then the change in ICOR or Al is given by Al=EAI Ci +EACT Ii+EACiAI I/ i ii i ii i i Now the second term on the R.HS. is EACiI + ECi (I - I) But EACiI IEACi and ZAC = 0 as the incremental shares in output of the sectors must cancel each other out and sum to zero. Then AI = EAIiCi + EACi (Ii - I) + EACi i Al C + AC (I - I) + AC AI gives the i sectors contribution to the overall ii i i i i ICOR change. The first term gives the contribution of the ith sectoral ICOR. The second term measures the contribution of the sectoral output increase.-t The last is a cross product term. The details of the exercise for Tanzania and Kenya are summarised below. The change in the ICOR from 1967-73 to 1973-79 was analysed as follows: 1/ The last term is of the second order of smallness, but its inclusion is required as A is a finite rather than an infinitesimal operator. 2/ This contribution is positive or negative depending on whether the ith sectoral ICOR is higher or lower than the overall ICOR. - 70 - ANNEX 11 (1) (2) (3) (4) (5) (6) (7) Percentage Sum of distribution Country and sector Is &jCj aCiAIi ACj(I-I) 3, 4 & 5 of column 6 Kenya Agriculture 1.7 0.204 0.1990 0.0710 -0.1120 0.1580 3.6 Industry 2.4 0.330 1.4560 -0.0180 0.0030 1.4410 32.7 Services 4.5 0.465 3.3950 -0.5020 -0.0860 2.8070 63.7 Tanzania Agriculture 1.5 0.250 -0.1900 -0.1290 -0.5600 -0.870 1/ Industry 10.0 0.190 10.2600 -8.6400 -0.8300 0.790 1/ Services 4.4 0.560 0.0056 -0.0001 -0.0004 0.0059 1/ 1/ Agriculture accounted for the entire decrease of 0.07 in the overall ICOR. Source: Data Files, World Bank - 71 - ANNEX III Limitations of National Account Data in Eastern Africa I. General In this Annex a number of issues relating to data on the Eastern African countries are discussed. An appreciation of these issues will help in evaluating the quantitative information presented in this paper as well as aid the reader in interpreting data from standard sources on Africa. It is generally acknowledged that economic data for Africa are poor. It may be well worth supplementing usual national accounts and macro data for this region by data generated in response to special surveys over whose design and organization the researcher has greater control. Specifically, farm management surveys, special sample surveys, small industry survey, etc., spring to mind. The veracity of the data from these sources should compen- sate for their lack of economy-wide coverage. Currently there is a paucity of such information and reliance has to be placed on national accounts sources which are often estimates based on limited evidence. Some improvements have been effected but if the goal is to obtain reliable information for research and policy design, then a much heavier emphasis on data upgrading is required. Currently, published African data seem to suffer from the following drawbacks. (a) Many estimates are derived from a few verifiable indi- cators. For instance overall investment is sometimes derived from imports of capital goods. Price indices may be obtained from the prices of a handful of commodities in the capital city using very - 72 - ANNEX III outdated weights. Import or export statistics may omit any ad- justment for smuggling when this is recognized to be a major phenomenon. Consequently though a mass of statistics may be avail- able in the standard UN format, there is no guarantee that this information represents the real world or is comparable across countries. In the shakiest of cases the information simply does not accord with qualitative evidence or the experience of observers on the scene. (b) The presence of overvalued exchange rates, multiple exchange rate practices and unreliable price indices makes constant price comparisons as well as cross country comparisons in terms of, say, United States dollars dubious. Trend analysis fares better than any comparison of absolute magnitudes. (c) Data are often volatile from year to year to an extent which casts doubt on their reliability. The procedure adopted in this paper has been to take three year averages centered around the re- porting year whenever possible in order to minimize this effect.-/ Data are also reported at short intervals so as not to miss cycles. We have tried not to draw any inference unless data for several years confirmed an event. 1/ If the period to be analyzed was very short then this procedure has not been followed. Use of a moving average results in the omission of a number of years at the end palats and Ie "et practic&l for short series. - 73 - ANNEX III II. Country Specific Notes While national accounts data for most African countries suffer from deficiencies, the series for Sudan, Tanzania and Somalia are even more suspect than others. In the case of Sudan the national authorities claim that the series for the seventies and the sixties are not comparable. They have also stopped releasing national income estimates in constant prices. In the case of Tanzania, the national accounts estimate of a growth rate of 8.8 percent per annum for subsistence production in the seventies is considered implausible. The aggregate growth estimates in this paper as- sume that the subsistence sector has only grown at a rate of 4.3 percent per annum. For Somalia, while World Bank data files show a growth rate of 7.4 percent per annum in the 1973-78 Deriod. lntpr information esti- mates the growth rate to have been only about 2.5 percent between 1972 and 1978. There are no official national accounts and virtually no primary data base, but the economy appears to be in general stagnation. - 74 - REFERENCES Carrington, John C. and Edwards, George T., Financing Industrial Investment, MacMillan Press, London, 1979. Faruqee, Rashid and Gulhati, Ravi, Rapid Population Growth in Sub-Saharan Africa, World Bank Staff Working Paper, No. 559, 1983. Gulhati, Ravi I., "The Need for Foreign Resources, Absorptive Capacity and Debt Servicing Capacity", Capital Movements and Economic Development, Edited by Adler, John H., St. Martin's Press, 1967. Gulhati, Ravi and Sekhar, Uday, "The Industrial Strategy for Late Starters: The Experience of Kenya, Tanzania and Zambia, World Bank Staff Working Paper No. 457. Gulhati, Ravi and Autokorala, Vimal, "Behaviour of Import and the Nature of Related Policies" (Forthcoming). Kim, Kwan S., "Enterprise Performances in the Public and Private Sectors: Tanzanian Experience, 1970-75", The Journal of Developing Areas, 15, April 1981. Kuznets, S., "Enterprise Performances in the Public and Private Sectors: Capital Formation Proportions, International Comparison for Recent Years", Economic Development and Cultural Change, Vol. 8, P&2, July 1960. Kuznets, S., "Quantitative Aspects of the Economic Growth of Nations, VI, Long-Term Trends in Capital Formation Proportions", Economic Development and Cultural Change, Vol. 1, P&2, July 1961. Meier, G.M., Leading Issues in Development Economics, Oxford University, 1964. Reddaway, W.B., The Development of the Indian Economy, George Allen and Unwin Ltd., London, 1962. Sato, Kazuo, "International Variations in the Incremental Capital-Output Ratio", Economic Development and Cultural Change, Vol. 19, No. 4, July 1971. Scott, M.F.G., "The Contributlon of Investment to Growth", Scottish Journal of Political Economy, Vol. 28, November 1981, No. 3. Vanek, J. and Studenmund, A.H., "Towards a Better Understanding of the Incremental Capital-Output Ratio, , The Quarterly Journal of Economics, Vol. LXXXII, No. 3, August 1968. Walters, A.A., "Incremental Capital Output Ratios", Economic Journal, 76, December 1966. Wolf, Martin, "Capital and Growth in India: 1950-71", India Occasional Papers World Bank Staff Working Paper No. 279, November 1978. World Bank; Accelerated Development in Sub-Saharan Africa; An Agenda for Action, 1981. World Bank Aggregate Demand and Capital Market Imperfec- Macroeconomic Imbalances tions and Economic Publications In Thailand: Simulations Development of Related with the SIAM 1 Model Vinayak V. Bhatt and of Related Wafik Grais Alan R. Roe Interest Focuses on the demand-side adjust- World Bank Staff Working Paper ments of the Thai economy to lower No. 338. July 1979. 87 pages agricultural growth and to higher (including footnotes). energy prices. Discusses policy measures and structural changes that Stock No. WP-0338. $3.00. might enable the economy to over- come these problems and continue to maintain high GDP rates of growth. The Changing Nature of World Bank Staff Working Paper No. Export Finance and Its Word ankStff oringPaer o. Implications for Developing 448. April 1981. 70 pages (including Countries 2 appendLxes). onre 2 appendixes). ~Albert C. Cizausk~as Stock No. WP-0448. $3.00. World Bank Staff Working Paper No. 409. July 1980. 43 pages (including An Analysis of 3 annexes). Developing Country Stock No. WP-0409. S3.00. Adjustment Experience and Adjustment Experiences in Growth Prospects of the the 1970s: Low-income Asia Semi-Industrial Countries Christine Wallich Compounding and Dis- Frederick Jaspersen This background study for World counting Tables for This background study for World Development Report 1981 examines Project Evaluation Development Report 1981 examines low-income South Asia's adjustment J. Price Gittinger, editor the successful process of adjustment to the extemal shocks of the 1970s, Easily comprehensible, convenient to extemal 'shocks" of the 1970s especially those factors that helped tables for project preparation and (rising prices of oil imports, reduced make the effects of these external analysis. demand for exports, slower economic developments less severe in the growth in the OECD countries) in the region than in other parts of the The Johns Hopkins University Press, semi-industrial developing countries. developing world. 1973; 7th printing, 1982. 143 pages. Presents an analytical framework for World Bank Staff Working Paper No. LC 75-186503. ISBN 0-8018-1604-1. quantifying the effects of demand 487. August 1981. iv + 39 pages $6.00 paperback. management and structural adjust- (including references). ment in forty-two countries, with par- Arabic: WorldBank 1973. (Auailable ticular reference to Uruguay, Brazil, Stock No. WP-0487. $3.00. from ILS 1715 Connecticut Avenue, Republic of Korea, and Turkey. N.W., Washington, D.C. 20009, U.S.A.) World Bank Staff Working Paper No. Aspects of Development $4.00 paperback. 477. August 1981. 132 pages (including Bank Management French: Tables d'interets composes et 3 appendixes). William Diamond and d'actualisation. Economica, 4th print- Stock No. WP-0477. $5.00. V. S. Raghavan ing, 1979. Deals exclusively with the manage- ISBN 2- 71 78-0205-3, 36 francs. A4|ustment in ment of development banks. The Spanish: Tablas de interes compuesto y Low-income Africa book is divided into eight sections, de descuento para evaluaci6n de proyec- Robert Liebenthal each dealing with one aspect of tos. Editorial Tecnos 1973; 4th print- This background study for World of the various ways of dealing ing, 1980. Deuelopment Report981 analyzes with them. ISBN 84-309-0716-5, 380 pesetas. the adJustment to external shocks during the 1970s made by a group EDI Series in Economic Deuelopment. of middle-income and low-income The Johns Hopkins University Press, A Conceptual Approach to African countries, with particular 1982. 311 pages. the Analysis of External Debt reference to Kenya, Tanzania, LC 81-48174. ISBN 0-8018-2571-7 of the Developing Countries $29.95 hardcover, ISBN 0-8018-2572-5, Robert Z. Aliber World Bank Staff Working Paper No. $12.95 paperback. World Bank Staff Working Paper No. 486.(Aug b io+r56page 421. October 1980. 25 pages (including (Including bibi3ography). appendix, references). Stock (10. WP-0486. $3.00. Stock No. WP-0421. $3.00. Development Banks Developments in and Food Policy Issues in William Diamond Prospects fogr the External Low-income Countries Operating experiences that serve as a Debt of the Developing Edward Clay and others practical guide for developing coun- Countries: 1970-80 A background study for World tries, with a selected list and and Beyond Development Report 1981. Discusses summary description of some Nicholas C. Hope food distribution-especially Its development banks. , d 'd insecurity in the face of external The Johns Hopkins University Prss, Development Report 1981 analyzes conflict withintemrn production 1957; 5th printing, 1969. 141 pages the debt situation and its implica- conflcrswinh genteral anoducwith (including 2 appendixes, index). tions for future borrowing. reference to Bangladesh, Zambia, LC 5 7-13429. ISBN 0-8018-0708-5, World Bank Staff Working Paper No. and India. $5.00 (S3.50) paperback. 488. August 1981. 70 pages (including World Bank Staff Working Paper No. 2 annexes, references). 473. August1981. uli + 715 pages. Development Finance Com- Stock No. WP-0488. $3.00. Stock No. WP-04 73. $5.00. panies: Aspects of Policy and Operation Energy Prices, Substitution, A General Equilibrium William Diamond, editor; and Optimal Borrowing in Analysis of Foreign essays by E. T. Kuiper, the Short Run: An Analysis Exchange Shortages In a Douglas Gustafson, and of Adjustment in Oil- Developing Economy P M. Mathew Importing Developing Kemal Dervis, Jaime de Melo, The Johns Hopkins University Press, Countries and Sherman Robinson 1968.130 pages (including appendix, Ricardo Martin and Examines the consequences of alter- index). Marcelo Selowsky native adjustment mechanisms to LC-68-27738. ISBN 0-8018-0166-4, Develops a short-term model for foreign exchange.shortages in semi- $5.00 (43.25) paperback. evaluating the adjustment (par- industrial economies. Compares French: Les societes flnancieres de ticularly, extemal borrowing) of oil- devaluation to two forms of Import developpement: quelques aspects de importing developing countries to the rationing and flnds that adjusting by leur politique et de leurs activits. increases in oil prices during the rationing is much more costly in (Available free from the World Bank 1970s. Discusses the borrowing terms of lost gross domestic product. Washington, D. C) strategies that can be exdpected in the World Bank Staff Working Paper No. Spansh:Las ompiifa flanciras future and the demands that will be 445. January 1981. 52 pages (includ- Spanish: Las companiias financieras made on multilateral institutions. 44ng reernces)198.32pgs(nld de desarrollo: algunos aspectos de su ing refernces). politica y de sus actividades. Editorial World Bank Staff Working Paper No. Stock No. WP-0443. $3.00. Tecnos, 1969. 466. July 1981. 77 pages (including 300 pesetas. footnotes, references). 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NEW Development Prospects Growth and Structural of Capital Surplus Oil- Exchange Rate Adjustment Adjutm in EastAsa Exporting Countries: Iraq, under Generalized Currency Adjustment in East Asia Kuwait, Libya, Qatar, Floating: Comparative arvez Hasan Saudi Arabia, UAE Analysis among Developing Analyzes the economic performance Rudolf Hablultzel Countries of the five large market economies of Rudolf liabiutzeRomolM ButitaEast Asia-Korea, Thailand, the This background study for World Romeo . utista Philippines, Malaysia, and Development Report 1981 Examines the experiences of twenty- Indonesia-during the last two discusses the production strategies two developing countries in adapting decades; focuses on the key factors and the development policies of the to the generalized floating of the explaining their remarkable economic capital-surplus oil-exporting world's major currencies since 1973 and social progress; and identifles the countries. and discusses the implications that main economic issues for the 1980s. 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The principles market failures and areas for The Johns Hopkins Uniuers~ity Pr~ess, outlined are therefore relevant to a intervention. 1968. 69 pages (including 4 annexes). host of development problems. World Bank Staff Working Paper No. LC 68-8701. ISBN 0-8018-0338-1, $5.00 The Johns Hopkins University Press. 485. August 1982. 57 pages. (X3.00) paperback. February 1983. About 304 pages. ISBN 0-8213-0062-8. $3.00. LC 82-7716. ISBN 0-8018-2803-1, The PAW E xVlcure e of $35.00 hardcover; ISBN 0-8018-2804-X, Tweli1 law D.Pe $12.95 paperback. NEW CA _1II W75-31B Beis a Private Bank Lending to The Niature of Credit Uses the methodology applied In the Developing Countries Markets in Developing author's -The Newly Industrializing Richard O'Brien Countries: A Framework Developing Countries after the Oil for Policy Analysis Crisis" (World Bank Staff Working A background study for World Arvind Vircnani Faper No. 473. October 1980) to Development Report 1981. examine the policy experience of Describes the evolution of relation- The central purpose of the paper is to twelve less developed countries in ships between private banks and analyze various forms of government the period following the quadrupling developing countries. intervention in the loan market in of oil prices In 1973-74 and the World Bank Staff Working Paper No. terms of their effect on efflciency world recessLon of. 1974-75. 482. August 1981. vi + 54 pages World Bank Staff Working Paper N'o. Wo,id 5r SW Working Paper No. (including appendix. bibliography). 524. 1982. 204 pages. 449. Apdl 1. 36 pages (Including Stock No. WP-0482. $3.00. ISBN 0-8213-0019-9. $5.00. appedI. Stock No. WP-Ct449. $3.00. Private Capital Flows to The Newly Industrializing Developing Countries and Developing Countries after The Political Structure of Their Determinations: the Oil Crisis the New Protectionism Historical Perspective, Bela Balassa Douglas R. 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Sweder van Wijnbergen shocks, such as the quadrupling of lSBN 0-8213-0023-7. $3.00. oil prices and the world recession of An analysis of the startling reversal of the 1970s) of developing countries. performance of the South Korean Considers reforms in production World Debt Tables economy in 1979 and 1980 compared incentives, incentives to save and to with the preceding fifteen years, and invest, public investments, sectoralof data on the extemal an exploration of the short-run policies, and monetary policies, and public and publicly-guaranteed debt macro-economic policy options comments on the interdependence of of 101 developing countries plus available to liorea in 1981. 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Thailand: An Analysis of lE RINTh Structural and Non- The Impact of Contractual Savings on Resource Mobilization and Allocation: Vol. III: The Measurement of Structural Adjustments The Experience of Malaysia Tax Effort of State Govern- Arne Drud, Wafik Grais, and Social Security Funds in Singapore ments, 1973-1976 Dusan Vujovic and the Philippines: Ramiflcations of Raja J. Chelliah and This study was prepared as a Investment Policies Niarain Sinha background paper for the preparation Investments of Social Security Funds of a structural-adjustment loan to In India and Sri Lanka: Legislation Attempts to evaluate the tax perfor- Talnadisaflo-ptapr- and Experience mance of particular states in terms of Thailand and is a follow-up to a pre- Parthasarathi Shome and the average tax effort of all states. vious paper entitled "Aggregate Katrine Anderson Saito Demand and Macroeconomic World Bank Reprint Series: Number 144. World Bank Working Paper No. 523. Imbalances in Thailand:' Comparative Reprinted from The Malayan Economic Review, vol. September 1982. uol. 1, 85 pages, vol. II, statistics are used, within the frame- 23, no. I (April 1978):54-72; Labour and Society, 186 pages. vol. III, 85 pages. work of a four-sector macroeconomic vol. 5, no. I (January 1980):19-30: and The Indian ISB082303Xuo , 300o model, to assess alternative ways of Journal of Economics, uol. 60, part 3, no. 238 ISBlY 0-8213-0013-X. vol. I, $5.00, vol. II macroeconomic adjustment in the (January 1980).349-60. $5.00, vol. II, $3.00. Thai economy. Discusses specifically Stock No. RP-0144. Free of charge. fiscal policy interventions, manipula- tions of the exchange rate, and pro- ductivity improvements and their PolHcy Responses to External Shocks In Selected Latin American Countries Bela Balassa World Bank Reprint Series: Nlumber 221. Reprinted from Quarterly Review of Economics and Business. vol. 21, no. 2 (Summer 1981):131-64. Stock tNo. RP-0221. 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