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Profiles of Third World mineral producers
Profiles of Third World mineral producers
Robert E. Looney and Craig R. Knouse
The paper attempts to determine whether Third World mineral and nonmineral economies can be profiled on the basis of a limited number of economic variables. Using discriminant analysis, the study finds that mineral economies differ significantly from their non-mineral counterparts. Of significance is the fact that external debt variables rather than such standard candidates as export instability or the share of the government sector in GNP are critical in this differentiation. Keywords: Economic development; Mineral economies; Discriminant analysis Robert Looney is Professor of National Security Affairs at the Naval Postgraduate School. Craig Knouse is a graduate student at the Naval Postgraduate School, Monterey, CA 93943, USA. ‘For the purposes of classification in this paper, a mineral economy is defined as one whose exports (in 1980) of minerals and or oil accounted for at least 40% of its export earnings. Data for this purpose are from the World Bank. World Tables, Third edition, Vol I, Econo& Data, Johns Hopkins Press, Baltimore, MD, 1983. ‘Jerker Carlsson, ‘The impact of mining TNCs on developing countries in Africa? Raw Materials Report, Vol 4, No 2, 1986, PP 6-7. 3An excellent early assessment of these factors is given in R. Mikesell, ed, Foreign Investment in the Petroleum and Mineral Industries: Case Studies in Investor-Host Country Relations, Johns Hopkins University Press, Baltimore, MD, 1971. 4R.F. Mikesell, ‘The contribution of petroleum and mineral resources to economic development’, in op tit, Ref 3, pp 16-17. ‘Cf E.J. Chambers and D.F. Gordon, ‘Primary products and economic growth: an empirical measurement’, Journal of Political Economy, Vol 74, No 4, August 1966, pp 31.5-332. 60p tit, Ref 2, p 6.
0301-4207/87/010055-13$03.00
0
One of the distinguishing characteristics of a number of developing countries is their relatively large deposits of minerals and/or hydrocarbons. How do we recognize a mineral economy when we see one? This may at first sight seem to be fairly simple, but certain definitional issues nevertheless need to be clarified. A mineral economy is a developing economy, highly dependent on the extraction of one or two minerals for its survival. Qualifying criteria for such dependency may be the share of mineral production in total GDP (at least 15%) and the share of total export earnings (at least 40%).’ These are economic criteria; but dependence also has a political dimension. The extent to which the mining sector is dominated by foreign mining companies clearly conditions the formulation and implementation of economic policies by the host country.2 Needless to say, Third World mineral economies vary enormously in the size of their population, the extent and stage of exploitation of their mineral wealth, their agricultural potential, the level of their human resource development and their economic and social infrastructure. Still, they appear to share the peculiar advantages and problems that arise from not only having an important mining sector but perhaps, more importantly, from their dependence on an exhaustible resource.’ In this respect they are said4 to differ markedly in terms of their economic structure and growth patterns from other groups of developing countries such as the predominantly agricultural nations or the semi-industrialized countries. Structurally, however, it is often argued that there is little difference between a mineral economy and any other primary producing economy.” However, the type of raw materials produced - for example cocoa or tin - to a large extent determines the terms of integration into the world economy. The production and marketing of tin, for example, takes place largely within the framework of transnational mining companies, while cocoa is less tied to transnational companies for its production but is definitely so for its marketing. In general, then, it is safe to say that mining activities in developing countries are more integrated into transnational company networks than the production of other primary commodities.6 The purpose of this paper is to test the hypothesis that the mere possession of a high concentration of minerals in the exports of Third World countries imparts certain unique structural characteristics to these countries sufficient to differentiate them as a unique group of
1987 Butter-worth & Co (Publishers)
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economies. Put differently, can Third World mineral economies be uniquely classified (profiled) and grouped separately (in a statistical sense) from non-mineral countries on the basis of a limited number of economic indices, reflective of the impact mineral production has on the structure and growth pattern of their economies? The results presented below indicate that in fact Third World mineral economies are significantly different from non-mineral economies, but that contrary to common perception, it is their debt structure that provides the ultimate basis for this differentiation.
Mining and development The crucial significance of mineral exports to particular LDC countries clearly lies in the fact that for many mineral Third World exporting countries a single mineral comprises a substantial if not predominant percentage of their total exports. Of course, the importance of mineral production varies from country to country. Yet in countries where mineral production is the primary export industry, as well as in those countries where it is less crucial, the impact of the mining sector upon the country’s development may be significant. The importance of mineral production to GNP, however, is often underestimated. On the one hand, ‘available statistics stop showing the contribution of minerals once the resources move from the mining sector to the manufacturing sector’.’ On the other hand, the enclave nature of the mining sector (ie its greater integration into the world economy rather than into the economy of the producing country) has important consequences.x The absence of substantial backward linkages, the frequent location of mining activities in remote, out of the way regions within the producing country, their limited labour absorption and the consequent possibility of conceding high wage levels, their dependence on foreign markets and on the availability of ores, make producing regions potentially unstable and a source of political and economic dislocation within the country.” In considering the impact of the mineral sector on the economic development of producing countries, the literature tends to distinguish between positive and negative effects. On the positive side, the mineral sector: I” %. Bosson and B. Varon, The Mining industry and the Developing Countries, Oxford University Press, New York, 1983, P 7. ‘Many of the social-political consequences are treated in N. Girvan, ‘The development of dependency economies in the Caribbean and Latin America: review and comparison’, Social and Economic Studies, No 18, March 1973, pp l-33; and 0. Sunkel, ‘Transnational capitalism and national disintegration in Latin America’, Social and Economic Studies, March 1973, pp 132-l 76. %. Sider and S. Johns, Mining for Development in the Third World, Pergamon Press, Elmsford, New York, 1980, pp 56. “‘/bid, pp 6-7. “Stephen Ft. Lewis, ‘Development problems in mineral-rich countries’, in Moshe Syrquin, ed, Economic Structure and Performance: Essays in Honor of Hot/is 6. Chenery, Academic Press, New York, 1984, pp 162-l 63.
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0 0 0
provides foreign exchange earnings; generates additional government revenue through taxes and royalties; and provides some employment and helps create a skilled labour force.
On the negative
l
a 0 0
side, the mining
sector:
Is mostly an enclave industry with all the problems related to such a situation: ’ ’ it utilizes a very high capital intensive technology, mostly imported; it absorbs a relatively limited amount of indigenous labour; it requires the import of a large share of inputs, materials and services to which the mining multinational may have non-market access through subsidiaries or associated companies. It has little backward integration with the economy of the producing country. It experiences wide fluctuations in both foreign exchange earnings and in government revenues. It tends to create environmental damage and is often operated under poor working and living conditions.
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Profiles of Third World minrrul producers 0
l
l
0
It involves the exploitation of non-renewable resources; once the ore bodies are mined out, or the market disappears, there is nothing left to generate revenues or employment for the local economy. It creates labour elites which can form a constraint upon government’s policies, while constituting a group whose interests do not necessarily coincide with those of the nation and whose pattern of consumption tends to be higher and different-especially in terms of foreign products - from that of most of the rest of the population. It has been characterized since the beginning of this century by a highly monopolistic industrial structure, the rent of which has tended to be appropriated largely by international capital or foreign buyers. The problem of the distribution of such a monopolistic rent has increasingly become the dominant issue for both foreign investors and LDC governments. The issue is further complicated by the difficulties of determining the size of the rent and of measuring its appropriation, not least because of possible transfer pricing practices which tend to hide real profit levels and minimize the relative tax burden. It often competes with agriculture for the utilization of fertile soil and scarce water resources.
In part, the negative impacts largely stem from several economic characteristics of mining projects:
institutional
and
Mining projects are generally very ‘lumpy’. That is, they can involve substantial capital investment over a long gestation period resulting in a rapid growth of physical output in a short time to a level that represents the ‘capacity’ of production for that mine. Thus mineral economies are likely to be characterized by large jumps in measured GDP and exports and not by a continuous steady growth rate. Government revenue may also be characterized by similar jumps, followed by periods of relative flatness (apart from cyclical variations). If the deposits are relatively ‘rich’ with low extraction cost relative to market prices, the rents will be significant and there will be a sizable difference between variable costs and price. Mining ventures tend to be capital intensive, both in terms of their capital/output ratios and their CapitaYlabour ratios; thus mining output is relatively insensitive to wage changes. Due to the low share of labour in value-added, a very large fraction of value-added goes to either government or the operating companies. In countries with limited financial intermediation, this results in the crowding out of local practice investment. Mineral markets are likely to be unstable internationally, and since the greatest share of mining output is sold internationally, there is often substantial instability of both export earnings and, more importantly, local government revenue.
“Gobind Nankani, Developmentproblems mineral exporting countries, World Bank Staff Working Paper No 354, August 1979. la/bid, pp ii-vi.
of
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The above departures from the conditions of divisibility, factor mobility and efficient workings of asset markets, are sufficiently systematic so that, in time, they may impart a number of unique structural characteristics to the mineral economies. The above considerations led Nankani” to formulate a number of propositions and subpropositions about mineral economies:r3 0
The
mineral
economies
differ
structurally
from
other
developing
57
Profiles of Third World mineral producerv
0
0
0
countries and, in particular, from other primary exporting (ie agricultural) developing countries. As noted above, the mineral economies differ from non-mineral economies because the mining industry is characterized by the presence of large foreign mining companies and by the existence of a large element of rent in the market value of minerals. The rent element, if not tapped, tends to migrate out of the mineral economy because of the dominant role of the international mining companies in the industry, and because a high proportion of mining output is exported. The mineral economies are also less likely to be subject to fiscal and/or foreign exchange gaps for a reasonable range of growth rates, at least while their mineral reserves last. To a somewhat greater degree than other developing countries mineral economies have the option of pursuing a resource-based industrialization strategy. But their resource is exhaustible and thus transforming and diversifying their economies (before the mineral wealth is entirely depleted) are objectives of greater priority for them than for predominantly agricultural economies. These structural differences and the typical responses to them tend to render the mineral economies more prone to a number of economic problems as compared to non-mineral economies: the saving performance of the mineral economies is poorer than that of the non-mineral economies; the mineral economies are characterized by greater technological and wage dualism, higher unemployment, and lower school enrolment rates than the non-mineral economies; inflation rates tend to be higher in the mineral economies than the non-mineral economies; agriculture tends to grow slowly and food constitutes a larger share of total imports in mineral than in non-mineral economies; mineral economies are more subject to export earnings instability than non-mineral economies; and the exports of mineral economies tend to remain more concentrated than those of non-mineral economies. The recent economic performance of the mineral economies suggests that their long term prospects are moderately favourable, but depend critically on the choice of policy objectives and instructions: the economic performance of the mineral economies judged by their rates of saving, growth in agricultural production, export diversification, inflation and the choice of investment priorities, shows no clear country patterns and exhibits both positive and negative findings. The economic performance of the mineral economies when evaluated against alternative pessimistic and optimistic senarios, suggests that their prospects are moderately favourable. To sustain vigorous economic growth and diversify their economies as their mineral reserves are depleted, and to increase employment, will require a wide array of changes that are largely institutional in nature and the appropriate setting of two key prices: the mining sector wage rate and the exchange rate.
Pattern of mineral/non-mineral 14Data are from World Bank, World Development Reporf, 7984, Oxford University Press, New York, 1984.
An examination of the structural mineral and non-mineral LDCs’” of structural differences between
development and performance difference between (Table 1) both confirms the high level mineral and non-mineral economies
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Profiles of Third World mineral producers Table 1. Structural and performance
differences
between mineral, non-mineral and oil exporting developing countries.
(Means Values)
Symbol
Total sample
Variable
Nonmineral
oil
Mineral
Nonmineral, non-oil
Oil
Export-external variables Commodity concentration ratio CIX Export instability, 1968-71 El Growth in imports, 1970-82 ZGB Growth rn exports, 197&82 EGB Growth in exports, 1960-70 EGA Share rn exports GDP, 1982 EB Current account balance, 1970 CAA Current account balance, 1982 CAB Share of other primary commoditres rn exports, 1982 OPCEB IMPFB Share of local imports rn merchandise imports, 1982
54.6 10.1 4.3 13 a.5 27.3 -131 6 -452 1 42.2 14.5
71.7 100 7.7 1.0 9.4 32.2 103.7 1 073.0 12.7 17.2
46.0 10.1 2.4 3.1 8.0 24.9 -144.1 -1 204.7 52.5 13.2
66.8 9.7 2.1 0.2 a.3 30.7 -29.2 -854.5 19.4 21.1
75.0 10.5 12.5 -3.8 13.1 35.4 - 162.6 3 496.9 2.4 14.2
46.8 10.0 23 3.7 7.3 24.9 -147.0 -1 201.3 52.0 17.6
External debt variables External publrc debt, 1970 PDA External publrc debt, 1982 PDB PDPA External public debt as % GDP, 1970 External public debt as % GDP, 1982 PDPB External public debt as % exports, 1970 DSEA External public debt as % exports, 1982 DSEB Gross inflow public external debt as % exports, 1982 ECIBE
621.7 4 986.6 32.0 36 8 7.6 129 0.6
706.9 6 493.3 68.7 37.9 8.5 16.2 0.3
580.7 4 337.1 14.0 36.3 7.1 11.5 0.8
581.7 3 898.4 120.3 61.2 10.6 21.2 0.4
831.6 9 828.7 10.3 15.4 6.1 12.3 0.1
583.0 4 330.9 14.6 34.9 7.2 11.4 0.8
Fiscal-savings AS MS RTCRYB GETYB GDB
variables Average national savings, 197&81 Average marginal national savings, 1970-81 Government revenue as % GDP, 1982 Government expenditures as % GDP, 1982 Government deficit as % GDP, 1982
16.9 12.7 21.2 26.3 -48
25 2 21.3 26.0 29.9 -3.1
12.9 a.4 19 1 24.9 -5.5
14.3 10.2 25.8 32.6 -7.1
35.9 33.3 26.7 26.6 2.0
13.1 a.4 192 15.1 -5.6
Composition AB IB MB SB
of GDP Share of Share of Share of Share of
24.4 29.9 13.9 45.7
14.4 40.3 12.0 45.3
2.9 24.5 14.9 46.0
18.1 32.4 13.3 49.4
9.4 49.3 10.5 41.3
29.6 24.6 14.9 43.4
Performance GDPGB INFB GDIGB GDIB ICOR GIRA GIRB AGB
variables Growth in GDP, 197&82 Inflation, 1970-82 Growth in investment, 197&82 Share of investment in GDP, 1982 Incremental capital-output ratio Gross international reserves, 1970 Gross international reserves, 1982 Growth in agriculture, 1970-82
4.3 14.5 6.3 22.9 4.0 288.1 2 389.7 2.5
4.2 20 2 7.4 24.9 4.0 330.4 3 835.8 2.6
4.3 13.2 5.8 22.0 3.9 270.6 1 776.9 2.5
3.3 24.0 31 24.6 5.1 171.3 728.2 2.1
5.4 15.5 12.9 27.2 2.9 452.2 7 213.8 3.4
4.4 17.6 5.8 21.7 3.9 275.3 1 774.6 2.5
agriculture in GDP, 1982 industry in GDP, 1982 manufacturing in GDP, 1982 services in GDP, 1982
Source: World Bank, Wodd Development Report, 1984, Oxford University Press, New York, 1984. World Bank, World Tables, Third edition, Vol I, Economic Data, Johns Hopkins Press, Baltimore, MD, 1983.
and provides a valuable frame of reference for the analysis As might be expected, the mineral economies have:
0 0 0 0 0 0
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1987
that follows.
a much more concentrated export structure; more rapid increase in imports over the 1970-82 period; higher export growth during 196&70 but lower for the 197C82 period; better current account position; a higher proportion of food imports; higher levels of external public indebtedness, public external indebtedness as a percentage of GDP and external public debt service as a percentage of exports; higher average and marginal savings; higher government revenues and expenditures as a percentage of GDP; lower government deficits as a percentage of GDP; a smaller percentage of output devoted to agriculture, manufacturing and services;
59
Profiles of Third
World
mineral
producers
higher inflation rates; a higher proportion of GDP growth of investment; and a higher level of international
allocated
to investment
and a higher
reserves.
On the surface, therefore, the mineral economies seem to have both relative strengths - higher savings and investment rates, together with a stronger current account balance - and weaknesses - less diversified productivity of investment (growth in GDP 1970 divided by growth in gross domestic investment 197042). The debt ratios incurred by the mineral exporters do appear to be higher by all measures than those of the non-mineral economies. These ratios do not suggest, however, that the mineral exporting countries must necessaarily encounter debt servicing problems. Other countries with similar ratios have succeeded in avoiding multilateral debt rescheduling and in servicing debt successfully. What these indicators do, however, is reveal that the countries with exportable mineral reserves are inclined to believe that they can afford increased foreign credits and that foreign lenders will be more than ready to grant a large amount of external credits. Clearly if the mineral or oil producing LDCs experience a relative difficulty in servicing these debts, it must stem not so much from their possession of minerals and oil per se but rather from their inclination to overborrow and/or misallocate external resources.
Previous attempts at classification There have been numerous studies conducted on the problems of developing countries. A majority of these studies appear to have as their aim the desire to prescribe a ‘best’ path of development for individual mineral exports. In one major study, Nankani notes that Third World mineral economies tend to become increasingly dominated by a syndrome in which three factors interact: an incentive structure that is biased against agriculture and export diversification, high sectoral wage differentials, and high relative macroeconomic consumption. I5 Nankani uses a list of selected indicators (Table 2) for both mineral and non-mineral economies to support his assertion. Clearly during the 1968-70 period the largest differences appear in the incremental gross national savings rate. However the savings rates seem to even out in 1970-73 and by 1973-76 the difference appears again, but much smaller. During 1971-73, the largest difference is in the share of primary commodities in total merchandise exports. With regard to external debt Nankani notes: High external debt-to-GDP ratios may, in addition, be regarded as an advantage rather than a liability, in that mineral wealth increases the creditworthiness of such economies and permits them to undertake investments by borrowing abroad.16
15Gobind Nankani, ‘Development problems of nonfuel mineral exporting countries’, Finance and Development, No 17, March 1980, pp 6-10. 16/bid.
60
Clearly Nankani’s analysis is suggestive of certain characteristics that are unique to mineral countries and that can be used to produce profiles of ‘typical’ Third World mineral exporters. It is apparent, however, that many of the indices used by Nankani are highly correlated and therefore redundant for purposes of classification.
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Profiles of Third World mineral producers Table 2. Non-fuel
and non-mineral
economies:
selected indicators. Mineral
Export earnings - GDP ratio Tax revenue - GDP ratio Growth of agriculture production (%) Share of food imports in total imports (%) Share of minerals in total merchandise exports (%) Share of primary commodities merchandise exports (%)
in total
Gross national saving rates (%) Incremental
gross national saving rates (%)
Export earnings instability index Inflation rates (%) External debt-GDP
ratio
Growth rates (%) GDP GDP per capita
196%70 33.4 196&70 16.8 1960-76 3.0 1976 14.2 1960 67.0 1960 86.0 1968 17.6 1968-73 5.7 1961-72 8.5 196&70 8.3 1970 27.2 196&76 4.4 1.9
Non-mineral
Mineral
Non-mineral
Mineral
Non-mineral
18.1
1974-76 35.2
20.1
na
1971-73 35.9 1971-73 17.0 1970-76 2.6 1970-75 19.4 1976 72.0
na
83.0
1976 89.0
50.0
17.1 13.0 3.6 16.8
13.5 23.6 7.9 5.5 13.2
1970 14.8 1970-73 6.5 1968-73 8.8 197&76 12.2 1976 45.7
13.5 3.4 14.6
15.2 6.3
1976 14.9 1973-76 4.1
16.2 13.8
9.3 12.6 19.2
6.3 3.8
Source: World Bank staff estimates.
Using an updated and more extensive data base than the one available at the time of Nankani’s study, the following variables suggested by Nankani were introduced into a stepwise discriminant analysis. ” The purpose of this analysis was to determine if mineral countries could be profiled as a distinct subset of Third World countries and if so the most significant (in a statistical sense) indices responsible for their differentiation from other Third World economies. The variables (and their symbols) included: lx
l 17Discriminant analysis is a statistical technique that reduces multiple measurements to composite scores. These scores measure the probability that a country will fall into one of the groups. A country is placed in the group that has composite scores most similar to its own. On the technical exposition of this procedure, see Donald Morrison, ‘On the interpretation of discriminant analysis’, Journal of Marketing Research, Vol 15, May 1968, pp 156-163. Computations were made using the program designed by the Statistical Analysis System Institute; see SAS Institute, Users Guide: Statistics, SAS Institute, 1982, Cary, NC. “Unless otherwise noted the data is all from op tit, Ref 14. “Data from op tit, Ref 1. ?bid. ” Ibid. “Ibid. 23The World Bank, World Tab/es, 7976, Johns Hopkins Press, Baltimore. MD. 1976.
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0 0 0 l l 0 0 0 l
RTCRYB - total central government current revenue to GNP (1981); CIX, commodity concentration (197&80);‘” AGB, growth of the agricultural sector (197042); AS, average national savings rate (1970-81);20 MINFB, rate of inflation (197~82);*’ MS, average marginal savings rate (197&81);22 EI, export instability index (1968-71);2” RBB, resource balance (1982); GDB, government surplus deficit (percentage of GNP, 1982); and GBTYB, total central government expenditure (percentage of GNP, 1981).
These ten variables were entered into a stepwise discriminant analysis to determine the relative significance and order of importance in differentiating mineral from non-mineral countries. The results (Table 3) indicated that five variables (RTCRYB, CIX, AGB, AS and INFB) were statistically significant in distinguishing mineral from non-mineral economies. Utilizing these variables, a reasonably high degree of correct placement and probability of correct classification was obtained. However, five non-mineral economies - El Salvador, Ivory Coast, Ghana, Uganda and Argentina - were incorrectly classified as mineral
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Profiles of Third World mineral producers Table 3. Test of World Bank classification
aMisclassified by discriminating variables; bsee text for description of discriminating variables.
Non-mineral economies
Probability of correct classification %
Nicaragua India Honduras Cameroon Sudan Costa Rica Senegal Korea Guatemala Malawi Singapore El Salvador Pakistan Turkey Yugoslavia Spain Paraguay Brazil Philippines Thailand Malaysia Dominican Republic Ivory Coast Sierra Leone Panama Uruguay Tanzania Uganda CAR Ghana Burma Sri Lanka Argentina Burundi Kenya Jordan Haiti
78.8 94.3 69.1 70 3 87.0 60.4 90.1 97.0 93.0 64.1 78.9 46.7= 97.6 84.1 95.9 94.4 97.5 92.2 91.7 94.4 61.7 80.0 49.3a 99.1 50.4 73.3 88.0 17.9a 92.9 41 .6a 85.2 68.5 44.3a 53.2 83.9 92.2 89.1
of mineral and non-mineral economies.
Mineral economies
Probability of correct classification %
Indonesia Bolivia Togo Tunisia Morocco Venezuela Mexico Ecuador Liberia Congo Chile Zaire Trinidad Jamaica Zambia Peru Papua New Guinea Kuwait
55.8 17.2a 91.7 57.1 67.4 95.4 26.0a 59.0 76.5 94.5 77.0 88.4 99.1 95.2 97.3 34.2a 37.2a 100.0
Discriminating
variable&’
Variables included in discriminant analysis Variable F Step 1 RTCRYB 7.23 2 CIX 5.6 3 AGB 4.7 4 AS 6.8 5 INFB 5.6
Wilks’ Lambda 0.815 0.691 0.597 0 484 0.406
Variables excluded from discriminant analysis MS 0.01 El 0.47 RBB 0.12 GDB 0.38 GETYB 0.03
economies while Bolivia, Mexico, Peru and Papua New Guinea were classified as non-mineral economies. To determine whether it was possible to improve the classification and probability of correct placement of mineral and non-mineral countries, several variables but not utilized by Nankani, were suggested by the above analysis, introduced into the discriminant analysis. These variables represented various aspects of external public debt,24 export, foreign exchange reserves, the structure of non-mineral exports, and the sectional composition of output. Specifically the variables included: 0 0 0
“The causes and consequences of the economic debt situation facing Third World mineral economies was first discussed by Susanne Schattner, ‘Mineral economies, indebtedness without growth’, ktterfconomics, Vol 17, September/October 1982, pp 234-243.
62
0 0 0 0 0 0 The
OPCEB, the percentage of other (non-fuels, minerals and metals) in merchandise exports (1981); DSEA, external public debt service as a percentage of exports (1970); DSEB, external public debt service as a percentage of exports (1982); PDA, total external public debt (1970); PDB, total external public debt (1982); PDPA, external public debt as a percentage of GNP (1970); PDPB, external public debt as a percentage of GNP (1982); EGA, export growth (1960-70); and EGB, export growth (1970-82). first
stepwise
discriminant
analysis
(Table
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selected
three
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Profiles Table 4. Variables used in mineral, non-mineral-oil
of Third World
discriminant
mineral producers
analysis.=
Mineral, non-mineral classification First discriminant
analysis
Step
Variable
F Statistic
Wilks’ Lambda
1
OPCEB CIX DSEB
3.17 05.7 10.5
0.60 0.22 0.17
2 3 Second discriminant
analysis
Step
Variable
F Statistic
Wilks’ Lambda
1
AB CIX PDB EGB GIRA
21 .a 36.6 7.26 10.27 4.23
0.72 0.44 0.39 0.33 0.28
2 3 4 5 Variables in discriminant
%ee text for description ables.
of discriminating
vari-
analysis
step
Variable
F Statistic
Wilks’ Lambda
1 2 3 4 5 6 7 8
OPCEB CIX AS DSEA EGB PDB PDPB EGA
21.7 27.4 7.9 4.1 3.7 3.4 2.5 2.3
0.42 0.15 0.10 0.08 0.06 0.05 0.04 0.03
variables - the share of other primary exports in total exports (OPCEB), the commodity concentration (CIX), and public external debt service as a share of exports (DSEB) - as most significant in differentiating between mineral and non-mineral economies. Introducing the variables in a stepwise fashion to test our mineral classification (Table 5) showed that OPCEB by itself correctly classified all but one mineral economy (Togo), while CIX by itself misclassified six countries (Egypt, Tunisia, Morocco, Venezuela, Mexico, Trinidad and Peru). Both variables correctly classified all mineral economies with the probability of current placement for several countries improving considerably with the introduction of the third statistically significant variable, debt service as a percentage of exports (DSEB). The non-mineral countries are not as easily classified by OPCEB, with nine misclassifications (and ten with CIX). Again, however, OPCEB and CIX combined to correctly classify all the non-mineral economies with DSEB slightly improving in several cases the probability of correct classification. However, one might well argue that OPCEB (the share of other primary commodities in exports) is not very enlightening as a means of classifying mineral exports, given that by the nature of their abnormally high level of mineral exports an automatically low share of non-primary exports is more or less assured. In other words OPECB represents a classification scheme based on semitautology. Leaving out OPCEB from the set of discriminating variables, a second stepwise discriminant analysis was performed (Table 5). This analysis produced five variables that were statistically significant in profiling mineral and non-mineral economies: 1. 2. 3.
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AB, the share of agriculture in GDP, 1982; CIX, the commodity concentration, 197&80; PDP, external public debt, 1982;
63
Profiles
of Third
World mineral producers
Table 5. Discrfminant analysis of mineral, non-mineral developing countries.
_
Discriminating variables Mineral economies Nigeria Indonesia Bolivia Egypt Togo Tunisia Morocco Venezuela Mexico Algeria Libya Ecuador Congo Chile Zaire Jamaica Trinidad Zambia Peru Saudi Arabia Kuwait Syria Liberia Oman Non-mineral economies Israel Greece Nicaragua India Honduras Cameroon Sudan Costa Rica Senegal Somalia Korea Guatemala Malawi Niger Singapore El Salvador Pakistan Upper Volta Turkey Yugoslavia Spain Brazil Philippines Hong Kong Colombia Thailand Malaysia Dominican Republic Ivory Coast Sierra Leone Panama Uruguay Madagascar Tanzania Ethiopia CAR Bangladesh Portugal Sri Lanka Argentina South Africa Kenya North Yemen Jordan Nepal
64
OPCEB
CIX
_b
86.7 67.5 53.9 48.Ba 73.3 45.7a 42.1a 56.7 33.7= 77.6 86.5 64.8 76.7 53.9 69.5 71.8 24.7a 86.0 31 .6a 84.3 70.0 71.8 80.0
77.8 64.9 49.3a 80.9 57.3 90.0 _ 88.3 90.0 86.2 61.9 77.8 87.6 70.5 88.9 88.3 _ 52.5 88.3
26.ga 42.7a 97.2 50.7 96.2 88.2 98.0 90.0 44.3a 98.0 17.1a 91.1 97.9 26.9= 24.4a 81.7 61.6 96.6 81.7 24.4a 30.9a 68.8 60.1 12.3= 91.6 88.8 67.5 95.1 95.9 88.8 90.0 91.1 95.1 94.1 97.6 93.4 49.0a 30.9= 88.8 92.5 22.2a 77.6 74.0 36.5 91.1
OPCEB CIX
OPCEB CIX DSEB
100.0
100.0
95.4 99.7 99.6 62.4 100.0 _ 100.0 100.0 _ 100.0 97.3 _
100.0 100.0 100.0 _ 100.0 100.0 _ _ 99.8 _
100.0 93.5
100.0 85.3
_
_
58.5 100.0 100.0 _
99.9 100.0 100.0 _
100.0
100.0 _
92.7 88.2 50.4 89.5 44.7= 53.5 32.Ba 48.4= 59.5 28.2= 94.5= 57.1 20.0a
100.0 100.0 100.0 100.0 100.0 99.9 100.0 99.9 52.1 100.0 100.0 100.0 100.0 _
93.9 34.1a 82.9 48.ga 79.9 92.5 93.3 78.3 72.3 94.6 41.98 76.8 60.1 50.6 39.5a 82.1 68.6 74.9 61 .l 64.1 43.6a 39.4a 80.0 94.2 39.4a 82.1 91.1 59.5
100.0
75.0
99.7 _
77.8 100.0 100.0 100.0 99.9 100.0 100.0 99.5 99.8 99.8 100.0 97.7 100.0 100.0 100.0 100.0
100.0 100.0 100.0 100.0 99.9 99.7 100.0 98.8 100.0 99.8 99.6 _ 92.1 _
100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 _ 100.0 100.0 98.7 _ 100.0 100.0 100.0 97.4 99.9 100.0 100.0 100.0 99.9 100.0 99.8 100.0 100.0 100.0 _ 100.0 100.0 100.0 100.0 100.0 100.0 100.0 _ 99.0 98.8
AB CIX PDB EGB
AB CIX PDB EGB GIRA
AB
AB CIX
AB CIV PDB
49.Ba 43.ia 58.3 53.3 48.1a 61.5 56.7 74.7 73.4 74.7 80.0 67.8 74.7 74.7 33.4a 73.4 79.6 63.2 72.1 80.6 80.6 54.9
98.3 67.8 74.6 51.5 87.2 66.7 45.4= 96.5 73.0 99.6 100.0 96.1 99.6 95.6 46.4 99.0 71.5 99.6 64.4 99.9 99.6 92.2
99.4 96.1 66.9 84.2 84.0 57.7 55.9 99.1 100.0 100.0 100.0 100.0 99.5 96.3 48.2a 99.0 42.4a 99.7 62.8 100.0 99.5 92.5
99.4 91.9 88.7 93.4 75.6 67.8 73.2 100.0 100.0 100.0 100.0 98.3 99.3 73.8 76.5 99.7 93.4 99.7 52.3 99.9 100.0 97.2
99.5 92.3 91.6 95.3 74.0 73.1 77.5 100.0 100.0 100.0 100.0 98.9 99.6 73.1 71.0 99.8 97.3 99.7 55.7 99.9 100.0 97.9
23.9= 45.0a 4a.oa 68.0 58.6 58.6 72.3 55.2 50.1
94.8 98.6 51.3 99.9 65.2 80.7 75.4 64.6 74.5
93.0 99.4 63.0 99.8 78.4 90.0 72.9 75.8 88.3
95.5 99.9 71.2 99.8 92.9 97.1 48.1 92.9 79.0
94.8 99.9 72.5 99.9 95.1 98.2 54.7 94.7 79.1
40.0a
99.6
99.1
100.0
100.0
_ 64.9 19.4a 50.1 64.9 78.5 4a.4a 35.2= 25.2= _ 50.1 _ 56.9 50.1 51.8 43.3a 56.8 66.5 85.5 27.9 78.6 88.6 86.3 70.9 84.6 33.7= 58.6 _ _ 68.0 56.8 26.6a
_ _
_
_
93.0 21.3= 99.6 97.3 95.9 98.6 96.4
99.0 29.9= 99.7 99.1 90.0 99.6 99.6
91.6 54.6 94.9 78.8 38.3a 48.ga 99.6 98.1 53.2 99.1 99.9 99.0 83.0 100.0 99.1 52.0 _
55.5 99.9 100.0 88.7 _
60.0 99.2 100.0 90.7
99.9
100.0
91.7
98.3
98.9
50.1 97.9 77.3 54.1 47.7a 99.9 99.9 77.1 99.7 100.0 99.6 91.8 100.0 99.6 62.5
66.0 99.6 87.2 77.6 68.8 99.4 99.4 89.6 99.3 99.3 99.9 97.9 100.0 _
73.1 99.9 93.5 83.5 74.7 99.6 99.6 90.0 100.0 100.0 100.0 98.9
69.7
74.6
95.8
97.6
99.6
99.8
_
_ 95.6 _ 48.9 _
98.2 _ 74.2 _
RESOURCES
_ _
POLICY
March 1987
Profiles of Third World minerul producers Table 5. Oiscriminant
analysis of mineral, non-mineral developing
Discriminating variables Non-mineral Ruanda Benin Paraguay Burma Haiti Ghana Uganda Burundi Lesotho
OPCEB
OPCEB CIX
CIX
countries.
OPCEB CIX DSEB
AB
_ _ _ _
83 7 81 8 56.8 85.5 _
_ _ _ _
87.9 98.3 91.6 51.8
AB CIX
AB CIV PDB
AB CIX PDB EGB GIRA
AB CIX PDB EGB
economies
_ _ _ _ _ _
aMisclassified by discriminating
18.la 54.5 59.5 94.2 58.1 _ _ _
_ _ _ _ _ _ _ _ _
variables: b no value computed due to missmg observation;
4. 5.
75.5 99.0 85.9 98.1 _
81.5 99.7 94.5 99.1 _
96.7 99.9 90 1 96.9
98 1 100.0 92 4 99.4
97.4 99.4 99.1 99.8
99.1 99.8 99.4 99.9
97.8 99.9
99.2 100.0
_
_ _
‘see text for description of discriminating
variables
EGB, the growth of exports, 197&82; and GIRA, gross international reserves in 1970.
As with the first classification exercise, these variables were introduced one at a time to measure the improvement in classification obtained through the formation of additional discriminating functions. The results indicated (Table 5) that:
l 0 0
0
Four variables, AB, CIX, PDB and EGB are sufficient for correctly classifying all mineral economies. Only one mineral country (Morocco) is incorrectly classified using just two variables, AB and CIX. Two variables, AB and CIX, are sufficient to classify all but three non-mineral countries, El Salvador, Dominican Republic and Ivory Coast. All the non-mineral economies are correctly classified with only four variables: AB, CIX, PDB and EGB.
Finally, to determine whether or not it was possible to profile Third World countries to three groups, mineral, oil and non-mineral non-oil economies, a final stepwise discriminant analysis was performed. The results indicate that eight variables were statistically significant in delineating three groups of countries: CIX, AS, DSEA, EGB, PDB, OPCBB, PDPB and EGA. The results obtained by forming additional discriminant functions indicated (Table 6) that:
a 0
a 0 0 0 0
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March 1987
All but one oil country, Indonesia, is correctly classified by four variables, OPCEB, CIX, AS and DSEA. Seven variables are necessary to correctly classify the oil economies. While one variable, OPCEB, correctly classifies all the oil economies but one (Indonesia), the probabilities of correct placement average only 54.7%. Three variables, OPCEB, CIX and AS, correctly classify all the mineral economies. By themselves OPCEB and CIX are poor at classifying mineral economies. Three variables, OPCEB, CIX and AS, are sufficient for classifying all the non-mineral economies except Senegal and Jordan. Seven variables, OPCEB, CIX, AS, DSBA, EGB, PDB and PDPB, are needed to achieve correct classification of oil, mineral and non-mineral non-oil economies. Surprisingly, it then appears
65
Profiles of Third World mineral producers Table 6. Discriminant Discriminating
analysis
of oil, mineral
and non-mineral
economies.
variables
OPCEB CIX AS DESA
EGB PDB PDPB OPCEB CIX AS DESA
OPCEB
CIX
OPCEB CIX AS
43.ia 57.3 56.2 57.3 55.2 57.3 56.2 54.7
40.8= 33.7a 48.4a 57.0 15.5= 54.7 42.4a 41 .Ea
12.1= 87.9 99.4 100.0 35.0= 100.0 100.0 76.3
13.9= 96.2 99.8 100.0 60.5 100.0 100.0 81.5
68.1 100.0 100.0 100.0 91 .l 100.0 100.0 94.2
43.2= 40.7= 44.2= 37.6a 44.3a 41.9a 43.7a 43.7= 42.4
37.1a 36.3a 35.7a 36.5a 37.4a 37.3a 32.ga 35.7a 36.1
95.4 93.2 78.8 88.8 93.2 98.5 79.1 94.7 90.2
88.4 99.6 75.4 98.1 99.9 96.3 92.7a _b
98.7 100.0 86.3 99.9 99.8 96.8 91.8 _
92.9
96.2
16.1= 29.0= 87.4 34.7a 84.9 70.6 90.0 73.4 30.1a 90.0 11.6a 75.1 89.6 62.4 85.9 62.4 20.8= 42.0= 8.3” 75.9 71.6 48.2=
77.0 69.7 33.6a 71.7 29.7a 35.9= 21.9= 32.2= 40.3a 18.9= 80.5 38.F 19.5” 79.3 32.6 58.9 78.1 51.3 81.5 27.Ea 55.7 40.9a
88.5 90.3 98.7 95.4 96.8 89.6 97.0 88.3 24.3a 95.4 86.2 95.0 95.5 91.6 98.0 97.9 93.4 77.4 80.4 86.4 98.8 65.3
99.8 99.2 99.8 72.2 100.0 99.7 99.3 95.6 70.3 99.9 45.1a 99.6 99.6 100.0 100.0 97.9 100.0 95.8 99.8 89.9 100.0 98.8
99.7 99.6 99.2 77.4 100.0 99.9 99.3 79.4 54.8 100.0 67.8 99.9 99.9 95.4 100.0 98.3 100.0 98.4 99.9 96.6 100.0 98.4
82.5 84.3 71.6 73.4 75.1 82.5 80.5 88.8 79.1 71.6 77.5 57.8 24.7a 16.5= 43.2a 16.5a 33.F 20.Ea 49.4= 58.3
33.7= 26.2= 61.5 47.9a 53.8 41 .6a 44.ia 28.ga 26.1a 25.8= 61.5 40.4a 53.9 79.3 62.6 76.6 _
97.0 94.8 99.3 97.8 99.0 98.7 98.6 98.4 76.5 73.1 99.7 79.8 44.7a 91.6
99.9 99.7 100.0 99.9 94.6 100.0 100.0 99.7 99.0 79.2 99.4 97.9 88.4 100.0
100.0 99.5 99.9 99.1 95.4 100.0 100.0 99.9 99.7 81.9 99.6 96.8 97.0 _
87.1
98.2
79.8 57.4 49.2=
94.8 92.4 88.6
95.7 95.1
Oil economies Indonesia Venezuela Algeria Libya Trinidad Saudi Arabia Kuwait Average Mineral
economies
Togo Tunisia Morocco Congo Chile Jamaica Peru Liberia Average Non-mineral
aMisclassified by discriminating variables; %o value computed due to missing values: ‘see text for description of discriminating variables.
66
economies
Israel Greece Nicaragua India Honduras Cameroon Sudan Costa Rica Senegal Somalia Korea Guatemala Malawi El Salvador Upper Volta Turkey Spain Philippines Hong Kong Colombia Thailand Malaysia Dominican Republic Ivory Coast Sierra Leone Panama Uruguay Madagascar Tanzania Ethiopia CAR Sri Lanka Argentina Kenya Jordan Singapore Pakistan Yugoslavia Bangladesh Portugal Brazil Averaoe
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_
99.8 95.4
March 1987
Profiles
of Third
World
minerul
producers
that the oil countries are not as easy to profile as one might imagine, and that the oil, mineral and non-mineral non-oil classification, while feasible, is much more complicated than the twofold classification of mineral and non-mineral.
Conclusions The purpose of this paper, to determine whether mineral and non-mineral economies can be profiled on the basis of a limited number of economic variables, appears to have been achieved. The sample of 56 countries is by no means exhaustive, but it would be safe to assume that external debt and export variables are critical in differentiating mineral and non-mineral economies and could have universal applicability. Nankani’s original conclusions as to the nature of structural differences between mineral and non-mineral countries are confirmed in a general way. The evidence presented above indicated that since his study there seems to have been an increase in the relative importance of external debt in differentiating the mineral from the non-mineral economies. In fact, debt variables rather than such standard candidates as export instability or the share of the government sector in GNP are now a critical ingredient in the profile of mineral rich countries. The results presented also have relevance in a wider context. Traditionally, observers of mineral economies have noted that over time, these economies tend to become increasingly dominated by a syndrome in which three factors interact:” 0 0 0
250p tit, Ref 15, p 8. Robert Pollin, ‘The multinational mineral industry’, Crisis lMonth/y Review,
?f
Vol 31, April 1980, pp 25-38.
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March
1987
an incentive structure that is biased against diversification; high sectoral wage differential; and high relative macroeconomic consumption roeconomic saving).
agriculture
and export
(or low relative
mac-
The long term implications of allowing this syndrome to persist are severe. As the mineral wealth is exhausted, the economy finds itself unable to support its population, and its earlier living standards; in the long run, stagnation and poverty become increasingly likely. Clearly, the recent stepped up levels of external debt contracted by these countries, together with the decline in most mineral (and oil) prices have made the development prospects of mineral economies even bleaker than forecast several years ago.2”
67
Robert E. Looney and Craig R. Knouse
The paper attempts to determine whether Third World mineral and nonmineral economies can be profiled on the basis of a limited number of economic variables. Using discriminant analysis, the study finds that mineral economies differ significantly from their non-mineral counterparts. Of significance is the fact that external debt variables rather than such standard candidates as export instability or the share of the government sector in GNP are critical in this differentiation. Keywords: Economic development; Mineral economies; Discriminant analysis Robert Looney is Professor of National Security Affairs at the Naval Postgraduate School. Craig Knouse is a graduate student at the Naval Postgraduate School, Monterey, CA 93943, USA. ‘For the purposes of classification in this paper, a mineral economy is defined as one whose exports (in 1980) of minerals and or oil accounted for at least 40% of its export earnings. Data for this purpose are from the World Bank. World Tables, Third edition, Vol I, Econo& Data, Johns Hopkins Press, Baltimore, MD, 1983. ‘Jerker Carlsson, ‘The impact of mining TNCs on developing countries in Africa? Raw Materials Report, Vol 4, No 2, 1986, PP 6-7. 3An excellent early assessment of these factors is given in R. Mikesell, ed, Foreign Investment in the Petroleum and Mineral Industries: Case Studies in Investor-Host Country Relations, Johns Hopkins University Press, Baltimore, MD, 1971. 4R.F. Mikesell, ‘The contribution of petroleum and mineral resources to economic development’, in op tit, Ref 3, pp 16-17. ‘Cf E.J. Chambers and D.F. Gordon, ‘Primary products and economic growth: an empirical measurement’, Journal of Political Economy, Vol 74, No 4, August 1966, pp 31.5-332. 60p tit, Ref 2, p 6.
0301-4207/87/010055-13$03.00
0
One of the distinguishing characteristics of a number of developing countries is their relatively large deposits of minerals and/or hydrocarbons. How do we recognize a mineral economy when we see one? This may at first sight seem to be fairly simple, but certain definitional issues nevertheless need to be clarified. A mineral economy is a developing economy, highly dependent on the extraction of one or two minerals for its survival. Qualifying criteria for such dependency may be the share of mineral production in total GDP (at least 15%) and the share of total export earnings (at least 40%).’ These are economic criteria; but dependence also has a political dimension. The extent to which the mining sector is dominated by foreign mining companies clearly conditions the formulation and implementation of economic policies by the host country.2 Needless to say, Third World mineral economies vary enormously in the size of their population, the extent and stage of exploitation of their mineral wealth, their agricultural potential, the level of their human resource development and their economic and social infrastructure. Still, they appear to share the peculiar advantages and problems that arise from not only having an important mining sector but perhaps, more importantly, from their dependence on an exhaustible resource.’ In this respect they are said4 to differ markedly in terms of their economic structure and growth patterns from other groups of developing countries such as the predominantly agricultural nations or the semi-industrialized countries. Structurally, however, it is often argued that there is little difference between a mineral economy and any other primary producing economy.” However, the type of raw materials produced - for example cocoa or tin - to a large extent determines the terms of integration into the world economy. The production and marketing of tin, for example, takes place largely within the framework of transnational mining companies, while cocoa is less tied to transnational companies for its production but is definitely so for its marketing. In general, then, it is safe to say that mining activities in developing countries are more integrated into transnational company networks than the production of other primary commodities.6 The purpose of this paper is to test the hypothesis that the mere possession of a high concentration of minerals in the exports of Third World countries imparts certain unique structural characteristics to these countries sufficient to differentiate them as a unique group of
1987 Butter-worth & Co (Publishers)
Ltd
55
economies. Put differently, can Third World mineral economies be uniquely classified (profiled) and grouped separately (in a statistical sense) from non-mineral countries on the basis of a limited number of economic indices, reflective of the impact mineral production has on the structure and growth pattern of their economies? The results presented below indicate that in fact Third World mineral economies are significantly different from non-mineral economies, but that contrary to common perception, it is their debt structure that provides the ultimate basis for this differentiation.
Mining and development The crucial significance of mineral exports to particular LDC countries clearly lies in the fact that for many mineral Third World exporting countries a single mineral comprises a substantial if not predominant percentage of their total exports. Of course, the importance of mineral production varies from country to country. Yet in countries where mineral production is the primary export industry, as well as in those countries where it is less crucial, the impact of the mining sector upon the country’s development may be significant. The importance of mineral production to GNP, however, is often underestimated. On the one hand, ‘available statistics stop showing the contribution of minerals once the resources move from the mining sector to the manufacturing sector’.’ On the other hand, the enclave nature of the mining sector (ie its greater integration into the world economy rather than into the economy of the producing country) has important consequences.x The absence of substantial backward linkages, the frequent location of mining activities in remote, out of the way regions within the producing country, their limited labour absorption and the consequent possibility of conceding high wage levels, their dependence on foreign markets and on the availability of ores, make producing regions potentially unstable and a source of political and economic dislocation within the country.” In considering the impact of the mineral sector on the economic development of producing countries, the literature tends to distinguish between positive and negative effects. On the positive side, the mineral sector: I” %. Bosson and B. Varon, The Mining industry and the Developing Countries, Oxford University Press, New York, 1983, P 7. ‘Many of the social-political consequences are treated in N. Girvan, ‘The development of dependency economies in the Caribbean and Latin America: review and comparison’, Social and Economic Studies, No 18, March 1973, pp l-33; and 0. Sunkel, ‘Transnational capitalism and national disintegration in Latin America’, Social and Economic Studies, March 1973, pp 132-l 76. %. Sider and S. Johns, Mining for Development in the Third World, Pergamon Press, Elmsford, New York, 1980, pp 56. “‘/bid, pp 6-7. “Stephen Ft. Lewis, ‘Development problems in mineral-rich countries’, in Moshe Syrquin, ed, Economic Structure and Performance: Essays in Honor of Hot/is 6. Chenery, Academic Press, New York, 1984, pp 162-l 63.
56
0 0 0
provides foreign exchange earnings; generates additional government revenue through taxes and royalties; and provides some employment and helps create a skilled labour force.
On the negative
l
a 0 0
side, the mining
sector:
Is mostly an enclave industry with all the problems related to such a situation: ’ ’ it utilizes a very high capital intensive technology, mostly imported; it absorbs a relatively limited amount of indigenous labour; it requires the import of a large share of inputs, materials and services to which the mining multinational may have non-market access through subsidiaries or associated companies. It has little backward integration with the economy of the producing country. It experiences wide fluctuations in both foreign exchange earnings and in government revenues. It tends to create environmental damage and is often operated under poor working and living conditions.
RESOURCES
POLICY March 1987
Profiles of Third World minrrul producers 0
l
l
0
It involves the exploitation of non-renewable resources; once the ore bodies are mined out, or the market disappears, there is nothing left to generate revenues or employment for the local economy. It creates labour elites which can form a constraint upon government’s policies, while constituting a group whose interests do not necessarily coincide with those of the nation and whose pattern of consumption tends to be higher and different-especially in terms of foreign products - from that of most of the rest of the population. It has been characterized since the beginning of this century by a highly monopolistic industrial structure, the rent of which has tended to be appropriated largely by international capital or foreign buyers. The problem of the distribution of such a monopolistic rent has increasingly become the dominant issue for both foreign investors and LDC governments. The issue is further complicated by the difficulties of determining the size of the rent and of measuring its appropriation, not least because of possible transfer pricing practices which tend to hide real profit levels and minimize the relative tax burden. It often competes with agriculture for the utilization of fertile soil and scarce water resources.
In part, the negative impacts largely stem from several economic characteristics of mining projects:
institutional
and
Mining projects are generally very ‘lumpy’. That is, they can involve substantial capital investment over a long gestation period resulting in a rapid growth of physical output in a short time to a level that represents the ‘capacity’ of production for that mine. Thus mineral economies are likely to be characterized by large jumps in measured GDP and exports and not by a continuous steady growth rate. Government revenue may also be characterized by similar jumps, followed by periods of relative flatness (apart from cyclical variations). If the deposits are relatively ‘rich’ with low extraction cost relative to market prices, the rents will be significant and there will be a sizable difference between variable costs and price. Mining ventures tend to be capital intensive, both in terms of their capital/output ratios and their CapitaYlabour ratios; thus mining output is relatively insensitive to wage changes. Due to the low share of labour in value-added, a very large fraction of value-added goes to either government or the operating companies. In countries with limited financial intermediation, this results in the crowding out of local practice investment. Mineral markets are likely to be unstable internationally, and since the greatest share of mining output is sold internationally, there is often substantial instability of both export earnings and, more importantly, local government revenue.
“Gobind Nankani, Developmentproblems mineral exporting countries, World Bank Staff Working Paper No 354, August 1979. la/bid, pp ii-vi.
of
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The above departures from the conditions of divisibility, factor mobility and efficient workings of asset markets, are sufficiently systematic so that, in time, they may impart a number of unique structural characteristics to the mineral economies. The above considerations led Nankani” to formulate a number of propositions and subpropositions about mineral economies:r3 0
The
mineral
economies
differ
structurally
from
other
developing
57
Profiles of Third World mineral producerv
0
0
0
countries and, in particular, from other primary exporting (ie agricultural) developing countries. As noted above, the mineral economies differ from non-mineral economies because the mining industry is characterized by the presence of large foreign mining companies and by the existence of a large element of rent in the market value of minerals. The rent element, if not tapped, tends to migrate out of the mineral economy because of the dominant role of the international mining companies in the industry, and because a high proportion of mining output is exported. The mineral economies are also less likely to be subject to fiscal and/or foreign exchange gaps for a reasonable range of growth rates, at least while their mineral reserves last. To a somewhat greater degree than other developing countries mineral economies have the option of pursuing a resource-based industrialization strategy. But their resource is exhaustible and thus transforming and diversifying their economies (before the mineral wealth is entirely depleted) are objectives of greater priority for them than for predominantly agricultural economies. These structural differences and the typical responses to them tend to render the mineral economies more prone to a number of economic problems as compared to non-mineral economies: the saving performance of the mineral economies is poorer than that of the non-mineral economies; the mineral economies are characterized by greater technological and wage dualism, higher unemployment, and lower school enrolment rates than the non-mineral economies; inflation rates tend to be higher in the mineral economies than the non-mineral economies; agriculture tends to grow slowly and food constitutes a larger share of total imports in mineral than in non-mineral economies; mineral economies are more subject to export earnings instability than non-mineral economies; and the exports of mineral economies tend to remain more concentrated than those of non-mineral economies. The recent economic performance of the mineral economies suggests that their long term prospects are moderately favourable, but depend critically on the choice of policy objectives and instructions: the economic performance of the mineral economies judged by their rates of saving, growth in agricultural production, export diversification, inflation and the choice of investment priorities, shows no clear country patterns and exhibits both positive and negative findings. The economic performance of the mineral economies when evaluated against alternative pessimistic and optimistic senarios, suggests that their prospects are moderately favourable. To sustain vigorous economic growth and diversify their economies as their mineral reserves are depleted, and to increase employment, will require a wide array of changes that are largely institutional in nature and the appropriate setting of two key prices: the mining sector wage rate and the exchange rate.
Pattern of mineral/non-mineral 14Data are from World Bank, World Development Reporf, 7984, Oxford University Press, New York, 1984.
An examination of the structural mineral and non-mineral LDCs’” of structural differences between
development and performance difference between (Table 1) both confirms the high level mineral and non-mineral economies
RESOURCES
POLICY March 1987
Profiles of Third World mineral producers Table 1. Structural and performance
differences
between mineral, non-mineral and oil exporting developing countries.
(Means Values)
Symbol
Total sample
Variable
Nonmineral
oil
Mineral
Nonmineral, non-oil
Oil
Export-external variables Commodity concentration ratio CIX Export instability, 1968-71 El Growth in imports, 1970-82 ZGB Growth rn exports, 197&82 EGB Growth in exports, 1960-70 EGA Share rn exports GDP, 1982 EB Current account balance, 1970 CAA Current account balance, 1982 CAB Share of other primary commoditres rn exports, 1982 OPCEB IMPFB Share of local imports rn merchandise imports, 1982
54.6 10.1 4.3 13 a.5 27.3 -131 6 -452 1 42.2 14.5
71.7 100 7.7 1.0 9.4 32.2 103.7 1 073.0 12.7 17.2
46.0 10.1 2.4 3.1 8.0 24.9 -144.1 -1 204.7 52.5 13.2
66.8 9.7 2.1 0.2 a.3 30.7 -29.2 -854.5 19.4 21.1
75.0 10.5 12.5 -3.8 13.1 35.4 - 162.6 3 496.9 2.4 14.2
46.8 10.0 23 3.7 7.3 24.9 -147.0 -1 201.3 52.0 17.6
External debt variables External publrc debt, 1970 PDA External publrc debt, 1982 PDB PDPA External public debt as % GDP, 1970 External public debt as % GDP, 1982 PDPB External public debt as % exports, 1970 DSEA External public debt as % exports, 1982 DSEB Gross inflow public external debt as % exports, 1982 ECIBE
621.7 4 986.6 32.0 36 8 7.6 129 0.6
706.9 6 493.3 68.7 37.9 8.5 16.2 0.3
580.7 4 337.1 14.0 36.3 7.1 11.5 0.8
581.7 3 898.4 120.3 61.2 10.6 21.2 0.4
831.6 9 828.7 10.3 15.4 6.1 12.3 0.1
583.0 4 330.9 14.6 34.9 7.2 11.4 0.8
Fiscal-savings AS MS RTCRYB GETYB GDB
variables Average national savings, 197&81 Average marginal national savings, 1970-81 Government revenue as % GDP, 1982 Government expenditures as % GDP, 1982 Government deficit as % GDP, 1982
16.9 12.7 21.2 26.3 -48
25 2 21.3 26.0 29.9 -3.1
12.9 a.4 19 1 24.9 -5.5
14.3 10.2 25.8 32.6 -7.1
35.9 33.3 26.7 26.6 2.0
13.1 a.4 192 15.1 -5.6
Composition AB IB MB SB
of GDP Share of Share of Share of Share of
24.4 29.9 13.9 45.7
14.4 40.3 12.0 45.3
2.9 24.5 14.9 46.0
18.1 32.4 13.3 49.4
9.4 49.3 10.5 41.3
29.6 24.6 14.9 43.4
Performance GDPGB INFB GDIGB GDIB ICOR GIRA GIRB AGB
variables Growth in GDP, 197&82 Inflation, 1970-82 Growth in investment, 197&82 Share of investment in GDP, 1982 Incremental capital-output ratio Gross international reserves, 1970 Gross international reserves, 1982 Growth in agriculture, 1970-82
4.3 14.5 6.3 22.9 4.0 288.1 2 389.7 2.5
4.2 20 2 7.4 24.9 4.0 330.4 3 835.8 2.6
4.3 13.2 5.8 22.0 3.9 270.6 1 776.9 2.5
3.3 24.0 31 24.6 5.1 171.3 728.2 2.1
5.4 15.5 12.9 27.2 2.9 452.2 7 213.8 3.4
4.4 17.6 5.8 21.7 3.9 275.3 1 774.6 2.5
agriculture in GDP, 1982 industry in GDP, 1982 manufacturing in GDP, 1982 services in GDP, 1982
Source: World Bank, Wodd Development Report, 1984, Oxford University Press, New York, 1984. World Bank, World Tables, Third edition, Vol I, Economic Data, Johns Hopkins Press, Baltimore, MD, 1983.
and provides a valuable frame of reference for the analysis As might be expected, the mineral economies have:
0 0 0 0 0 0
RESOURCES
POLICY
March
1987
that follows.
a much more concentrated export structure; more rapid increase in imports over the 1970-82 period; higher export growth during 196&70 but lower for the 197C82 period; better current account position; a higher proportion of food imports; higher levels of external public indebtedness, public external indebtedness as a percentage of GDP and external public debt service as a percentage of exports; higher average and marginal savings; higher government revenues and expenditures as a percentage of GDP; lower government deficits as a percentage of GDP; a smaller percentage of output devoted to agriculture, manufacturing and services;
59
Profiles of Third
World
mineral
producers
higher inflation rates; a higher proportion of GDP growth of investment; and a higher level of international
allocated
to investment
and a higher
reserves.
On the surface, therefore, the mineral economies seem to have both relative strengths - higher savings and investment rates, together with a stronger current account balance - and weaknesses - less diversified productivity of investment (growth in GDP 1970 divided by growth in gross domestic investment 197042). The debt ratios incurred by the mineral exporters do appear to be higher by all measures than those of the non-mineral economies. These ratios do not suggest, however, that the mineral exporting countries must necessaarily encounter debt servicing problems. Other countries with similar ratios have succeeded in avoiding multilateral debt rescheduling and in servicing debt successfully. What these indicators do, however, is reveal that the countries with exportable mineral reserves are inclined to believe that they can afford increased foreign credits and that foreign lenders will be more than ready to grant a large amount of external credits. Clearly if the mineral or oil producing LDCs experience a relative difficulty in servicing these debts, it must stem not so much from their possession of minerals and oil per se but rather from their inclination to overborrow and/or misallocate external resources.
Previous attempts at classification There have been numerous studies conducted on the problems of developing countries. A majority of these studies appear to have as their aim the desire to prescribe a ‘best’ path of development for individual mineral exports. In one major study, Nankani notes that Third World mineral economies tend to become increasingly dominated by a syndrome in which three factors interact: an incentive structure that is biased against agriculture and export diversification, high sectoral wage differentials, and high relative macroeconomic consumption. I5 Nankani uses a list of selected indicators (Table 2) for both mineral and non-mineral economies to support his assertion. Clearly during the 1968-70 period the largest differences appear in the incremental gross national savings rate. However the savings rates seem to even out in 1970-73 and by 1973-76 the difference appears again, but much smaller. During 1971-73, the largest difference is in the share of primary commodities in total merchandise exports. With regard to external debt Nankani notes: High external debt-to-GDP ratios may, in addition, be regarded as an advantage rather than a liability, in that mineral wealth increases the creditworthiness of such economies and permits them to undertake investments by borrowing abroad.16
15Gobind Nankani, ‘Development problems of nonfuel mineral exporting countries’, Finance and Development, No 17, March 1980, pp 6-10. 16/bid.
60
Clearly Nankani’s analysis is suggestive of certain characteristics that are unique to mineral countries and that can be used to produce profiles of ‘typical’ Third World mineral exporters. It is apparent, however, that many of the indices used by Nankani are highly correlated and therefore redundant for purposes of classification.
RESOURCES
POLICY March 1987
Profiles of Third World mineral producers Table 2. Non-fuel
and non-mineral
economies:
selected indicators. Mineral
Export earnings - GDP ratio Tax revenue - GDP ratio Growth of agriculture production (%) Share of food imports in total imports (%) Share of minerals in total merchandise exports (%) Share of primary commodities merchandise exports (%)
in total
Gross national saving rates (%) Incremental
gross national saving rates (%)
Export earnings instability index Inflation rates (%) External debt-GDP
ratio
Growth rates (%) GDP GDP per capita
196%70 33.4 196&70 16.8 1960-76 3.0 1976 14.2 1960 67.0 1960 86.0 1968 17.6 1968-73 5.7 1961-72 8.5 196&70 8.3 1970 27.2 196&76 4.4 1.9
Non-mineral
Mineral
Non-mineral
Mineral
Non-mineral
18.1
1974-76 35.2
20.1
na
1971-73 35.9 1971-73 17.0 1970-76 2.6 1970-75 19.4 1976 72.0
na
83.0
1976 89.0
50.0
17.1 13.0 3.6 16.8
13.5 23.6 7.9 5.5 13.2
1970 14.8 1970-73 6.5 1968-73 8.8 197&76 12.2 1976 45.7
13.5 3.4 14.6
15.2 6.3
1976 14.9 1973-76 4.1
16.2 13.8
9.3 12.6 19.2
6.3 3.8
Source: World Bank staff estimates.
Using an updated and more extensive data base than the one available at the time of Nankani’s study, the following variables suggested by Nankani were introduced into a stepwise discriminant analysis. ” The purpose of this analysis was to determine if mineral countries could be profiled as a distinct subset of Third World countries and if so the most significant (in a statistical sense) indices responsible for their differentiation from other Third World economies. The variables (and their symbols) included: lx
l 17Discriminant analysis is a statistical technique that reduces multiple measurements to composite scores. These scores measure the probability that a country will fall into one of the groups. A country is placed in the group that has composite scores most similar to its own. On the technical exposition of this procedure, see Donald Morrison, ‘On the interpretation of discriminant analysis’, Journal of Marketing Research, Vol 15, May 1968, pp 156-163. Computations were made using the program designed by the Statistical Analysis System Institute; see SAS Institute, Users Guide: Statistics, SAS Institute, 1982, Cary, NC. “Unless otherwise noted the data is all from op tit, Ref 14. “Data from op tit, Ref 1. ?bid. ” Ibid. “Ibid. 23The World Bank, World Tab/es, 7976, Johns Hopkins Press, Baltimore. MD. 1976.
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March 1987
0 0 0 l l 0 0 0 l
RTCRYB - total central government current revenue to GNP (1981); CIX, commodity concentration (197&80);‘” AGB, growth of the agricultural sector (197042); AS, average national savings rate (1970-81);20 MINFB, rate of inflation (197~82);*’ MS, average marginal savings rate (197&81);22 EI, export instability index (1968-71);2” RBB, resource balance (1982); GDB, government surplus deficit (percentage of GNP, 1982); and GBTYB, total central government expenditure (percentage of GNP, 1981).
These ten variables were entered into a stepwise discriminant analysis to determine the relative significance and order of importance in differentiating mineral from non-mineral countries. The results (Table 3) indicated that five variables (RTCRYB, CIX, AGB, AS and INFB) were statistically significant in distinguishing mineral from non-mineral economies. Utilizing these variables, a reasonably high degree of correct placement and probability of correct classification was obtained. However, five non-mineral economies - El Salvador, Ivory Coast, Ghana, Uganda and Argentina - were incorrectly classified as mineral
61
Profiles of Third World mineral producers Table 3. Test of World Bank classification
aMisclassified by discriminating variables; bsee text for description of discriminating variables.
Non-mineral economies
Probability of correct classification %
Nicaragua India Honduras Cameroon Sudan Costa Rica Senegal Korea Guatemala Malawi Singapore El Salvador Pakistan Turkey Yugoslavia Spain Paraguay Brazil Philippines Thailand Malaysia Dominican Republic Ivory Coast Sierra Leone Panama Uruguay Tanzania Uganda CAR Ghana Burma Sri Lanka Argentina Burundi Kenya Jordan Haiti
78.8 94.3 69.1 70 3 87.0 60.4 90.1 97.0 93.0 64.1 78.9 46.7= 97.6 84.1 95.9 94.4 97.5 92.2 91.7 94.4 61.7 80.0 49.3a 99.1 50.4 73.3 88.0 17.9a 92.9 41 .6a 85.2 68.5 44.3a 53.2 83.9 92.2 89.1
of mineral and non-mineral economies.
Mineral economies
Probability of correct classification %
Indonesia Bolivia Togo Tunisia Morocco Venezuela Mexico Ecuador Liberia Congo Chile Zaire Trinidad Jamaica Zambia Peru Papua New Guinea Kuwait
55.8 17.2a 91.7 57.1 67.4 95.4 26.0a 59.0 76.5 94.5 77.0 88.4 99.1 95.2 97.3 34.2a 37.2a 100.0
Discriminating
variable&’
Variables included in discriminant analysis Variable F Step 1 RTCRYB 7.23 2 CIX 5.6 3 AGB 4.7 4 AS 6.8 5 INFB 5.6
Wilks’ Lambda 0.815 0.691 0.597 0 484 0.406
Variables excluded from discriminant analysis MS 0.01 El 0.47 RBB 0.12 GDB 0.38 GETYB 0.03
economies while Bolivia, Mexico, Peru and Papua New Guinea were classified as non-mineral economies. To determine whether it was possible to improve the classification and probability of correct placement of mineral and non-mineral countries, several variables but not utilized by Nankani, were suggested by the above analysis, introduced into the discriminant analysis. These variables represented various aspects of external public debt,24 export, foreign exchange reserves, the structure of non-mineral exports, and the sectional composition of output. Specifically the variables included: 0 0 0
“The causes and consequences of the economic debt situation facing Third World mineral economies was first discussed by Susanne Schattner, ‘Mineral economies, indebtedness without growth’, ktterfconomics, Vol 17, September/October 1982, pp 234-243.
62
0 0 0 0 0 0 The
OPCEB, the percentage of other (non-fuels, minerals and metals) in merchandise exports (1981); DSEA, external public debt service as a percentage of exports (1970); DSEB, external public debt service as a percentage of exports (1982); PDA, total external public debt (1970); PDB, total external public debt (1982); PDPA, external public debt as a percentage of GNP (1970); PDPB, external public debt as a percentage of GNP (1982); EGA, export growth (1960-70); and EGB, export growth (1970-82). first
stepwise
discriminant
analysis
(Table
RESOURCES
4)
selected
three
POLICY March 1987
Profiles Table 4. Variables used in mineral, non-mineral-oil
of Third World
discriminant
mineral producers
analysis.=
Mineral, non-mineral classification First discriminant
analysis
Step
Variable
F Statistic
Wilks’ Lambda
1
OPCEB CIX DSEB
3.17 05.7 10.5
0.60 0.22 0.17
2 3 Second discriminant
analysis
Step
Variable
F Statistic
Wilks’ Lambda
1
AB CIX PDB EGB GIRA
21 .a 36.6 7.26 10.27 4.23
0.72 0.44 0.39 0.33 0.28
2 3 4 5 Variables in discriminant
%ee text for description ables.
of discriminating
vari-
analysis
step
Variable
F Statistic
Wilks’ Lambda
1 2 3 4 5 6 7 8
OPCEB CIX AS DSEA EGB PDB PDPB EGA
21.7 27.4 7.9 4.1 3.7 3.4 2.5 2.3
0.42 0.15 0.10 0.08 0.06 0.05 0.04 0.03
variables - the share of other primary exports in total exports (OPCEB), the commodity concentration (CIX), and public external debt service as a share of exports (DSEB) - as most significant in differentiating between mineral and non-mineral economies. Introducing the variables in a stepwise fashion to test our mineral classification (Table 5) showed that OPCEB by itself correctly classified all but one mineral economy (Togo), while CIX by itself misclassified six countries (Egypt, Tunisia, Morocco, Venezuela, Mexico, Trinidad and Peru). Both variables correctly classified all mineral economies with the probability of current placement for several countries improving considerably with the introduction of the third statistically significant variable, debt service as a percentage of exports (DSEB). The non-mineral countries are not as easily classified by OPCEB, with nine misclassifications (and ten with CIX). Again, however, OPCEB and CIX combined to correctly classify all the non-mineral economies with DSEB slightly improving in several cases the probability of correct classification. However, one might well argue that OPCEB (the share of other primary commodities in exports) is not very enlightening as a means of classifying mineral exports, given that by the nature of their abnormally high level of mineral exports an automatically low share of non-primary exports is more or less assured. In other words OPECB represents a classification scheme based on semitautology. Leaving out OPCEB from the set of discriminating variables, a second stepwise discriminant analysis was performed (Table 5). This analysis produced five variables that were statistically significant in profiling mineral and non-mineral economies: 1. 2. 3.
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March 1987
AB, the share of agriculture in GDP, 1982; CIX, the commodity concentration, 197&80; PDP, external public debt, 1982;
63
Profiles
of Third
World mineral producers
Table 5. Discrfminant analysis of mineral, non-mineral developing countries.
_
Discriminating variables Mineral economies Nigeria Indonesia Bolivia Egypt Togo Tunisia Morocco Venezuela Mexico Algeria Libya Ecuador Congo Chile Zaire Jamaica Trinidad Zambia Peru Saudi Arabia Kuwait Syria Liberia Oman Non-mineral economies Israel Greece Nicaragua India Honduras Cameroon Sudan Costa Rica Senegal Somalia Korea Guatemala Malawi Niger Singapore El Salvador Pakistan Upper Volta Turkey Yugoslavia Spain Brazil Philippines Hong Kong Colombia Thailand Malaysia Dominican Republic Ivory Coast Sierra Leone Panama Uruguay Madagascar Tanzania Ethiopia CAR Bangladesh Portugal Sri Lanka Argentina South Africa Kenya North Yemen Jordan Nepal
64
OPCEB
CIX
_b
86.7 67.5 53.9 48.Ba 73.3 45.7a 42.1a 56.7 33.7= 77.6 86.5 64.8 76.7 53.9 69.5 71.8 24.7a 86.0 31 .6a 84.3 70.0 71.8 80.0
77.8 64.9 49.3a 80.9 57.3 90.0 _ 88.3 90.0 86.2 61.9 77.8 87.6 70.5 88.9 88.3 _ 52.5 88.3
26.ga 42.7a 97.2 50.7 96.2 88.2 98.0 90.0 44.3a 98.0 17.1a 91.1 97.9 26.9= 24.4a 81.7 61.6 96.6 81.7 24.4a 30.9a 68.8 60.1 12.3= 91.6 88.8 67.5 95.1 95.9 88.8 90.0 91.1 95.1 94.1 97.6 93.4 49.0a 30.9= 88.8 92.5 22.2a 77.6 74.0 36.5 91.1
OPCEB CIX
OPCEB CIX DSEB
100.0
100.0
95.4 99.7 99.6 62.4 100.0 _ 100.0 100.0 _ 100.0 97.3 _
100.0 100.0 100.0 _ 100.0 100.0 _ _ 99.8 _
100.0 93.5
100.0 85.3
_
_
58.5 100.0 100.0 _
99.9 100.0 100.0 _
100.0
100.0 _
92.7 88.2 50.4 89.5 44.7= 53.5 32.Ba 48.4= 59.5 28.2= 94.5= 57.1 20.0a
100.0 100.0 100.0 100.0 100.0 99.9 100.0 99.9 52.1 100.0 100.0 100.0 100.0 _
93.9 34.1a 82.9 48.ga 79.9 92.5 93.3 78.3 72.3 94.6 41.98 76.8 60.1 50.6 39.5a 82.1 68.6 74.9 61 .l 64.1 43.6a 39.4a 80.0 94.2 39.4a 82.1 91.1 59.5
100.0
75.0
99.7 _
77.8 100.0 100.0 100.0 99.9 100.0 100.0 99.5 99.8 99.8 100.0 97.7 100.0 100.0 100.0 100.0
100.0 100.0 100.0 100.0 99.9 99.7 100.0 98.8 100.0 99.8 99.6 _ 92.1 _
100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 _ 100.0 100.0 98.7 _ 100.0 100.0 100.0 97.4 99.9 100.0 100.0 100.0 99.9 100.0 99.8 100.0 100.0 100.0 _ 100.0 100.0 100.0 100.0 100.0 100.0 100.0 _ 99.0 98.8
AB CIX PDB EGB
AB CIX PDB EGB GIRA
AB
AB CIX
AB CIV PDB
49.Ba 43.ia 58.3 53.3 48.1a 61.5 56.7 74.7 73.4 74.7 80.0 67.8 74.7 74.7 33.4a 73.4 79.6 63.2 72.1 80.6 80.6 54.9
98.3 67.8 74.6 51.5 87.2 66.7 45.4= 96.5 73.0 99.6 100.0 96.1 99.6 95.6 46.4 99.0 71.5 99.6 64.4 99.9 99.6 92.2
99.4 96.1 66.9 84.2 84.0 57.7 55.9 99.1 100.0 100.0 100.0 100.0 99.5 96.3 48.2a 99.0 42.4a 99.7 62.8 100.0 99.5 92.5
99.4 91.9 88.7 93.4 75.6 67.8 73.2 100.0 100.0 100.0 100.0 98.3 99.3 73.8 76.5 99.7 93.4 99.7 52.3 99.9 100.0 97.2
99.5 92.3 91.6 95.3 74.0 73.1 77.5 100.0 100.0 100.0 100.0 98.9 99.6 73.1 71.0 99.8 97.3 99.7 55.7 99.9 100.0 97.9
23.9= 45.0a 4a.oa 68.0 58.6 58.6 72.3 55.2 50.1
94.8 98.6 51.3 99.9 65.2 80.7 75.4 64.6 74.5
93.0 99.4 63.0 99.8 78.4 90.0 72.9 75.8 88.3
95.5 99.9 71.2 99.8 92.9 97.1 48.1 92.9 79.0
94.8 99.9 72.5 99.9 95.1 98.2 54.7 94.7 79.1
40.0a
99.6
99.1
100.0
100.0
_ 64.9 19.4a 50.1 64.9 78.5 4a.4a 35.2= 25.2= _ 50.1 _ 56.9 50.1 51.8 43.3a 56.8 66.5 85.5 27.9 78.6 88.6 86.3 70.9 84.6 33.7= 58.6 _ _ 68.0 56.8 26.6a
_ _
_
_
93.0 21.3= 99.6 97.3 95.9 98.6 96.4
99.0 29.9= 99.7 99.1 90.0 99.6 99.6
91.6 54.6 94.9 78.8 38.3a 48.ga 99.6 98.1 53.2 99.1 99.9 99.0 83.0 100.0 99.1 52.0 _
55.5 99.9 100.0 88.7 _
60.0 99.2 100.0 90.7
99.9
100.0
91.7
98.3
98.9
50.1 97.9 77.3 54.1 47.7a 99.9 99.9 77.1 99.7 100.0 99.6 91.8 100.0 99.6 62.5
66.0 99.6 87.2 77.6 68.8 99.4 99.4 89.6 99.3 99.3 99.9 97.9 100.0 _
73.1 99.9 93.5 83.5 74.7 99.6 99.6 90.0 100.0 100.0 100.0 98.9
69.7
74.6
95.8
97.6
99.6
99.8
_
_ 95.6 _ 48.9 _
98.2 _ 74.2 _
RESOURCES
_ _
POLICY
March 1987
Profiles of Third World minerul producers Table 5. Oiscriminant
analysis of mineral, non-mineral developing
Discriminating variables Non-mineral Ruanda Benin Paraguay Burma Haiti Ghana Uganda Burundi Lesotho
OPCEB
OPCEB CIX
CIX
countries.
OPCEB CIX DSEB
AB
_ _ _ _
83 7 81 8 56.8 85.5 _
_ _ _ _
87.9 98.3 91.6 51.8
AB CIX
AB CIV PDB
AB CIX PDB EGB GIRA
AB CIX PDB EGB
economies
_ _ _ _ _ _
aMisclassified by discriminating
18.la 54.5 59.5 94.2 58.1 _ _ _
_ _ _ _ _ _ _ _ _
variables: b no value computed due to missmg observation;
4. 5.
75.5 99.0 85.9 98.1 _
81.5 99.7 94.5 99.1 _
96.7 99.9 90 1 96.9
98 1 100.0 92 4 99.4
97.4 99.4 99.1 99.8
99.1 99.8 99.4 99.9
97.8 99.9
99.2 100.0
_
_ _
‘see text for description of discriminating
variables
EGB, the growth of exports, 197&82; and GIRA, gross international reserves in 1970.
As with the first classification exercise, these variables were introduced one at a time to measure the improvement in classification obtained through the formation of additional discriminating functions. The results indicated (Table 5) that:
l 0 0
0
Four variables, AB, CIX, PDB and EGB are sufficient for correctly classifying all mineral economies. Only one mineral country (Morocco) is incorrectly classified using just two variables, AB and CIX. Two variables, AB and CIX, are sufficient to classify all but three non-mineral countries, El Salvador, Dominican Republic and Ivory Coast. All the non-mineral economies are correctly classified with only four variables: AB, CIX, PDB and EGB.
Finally, to determine whether or not it was possible to profile Third World countries to three groups, mineral, oil and non-mineral non-oil economies, a final stepwise discriminant analysis was performed. The results indicate that eight variables were statistically significant in delineating three groups of countries: CIX, AS, DSEA, EGB, PDB, OPCBB, PDPB and EGA. The results obtained by forming additional discriminant functions indicated (Table 6) that:
a 0
a 0 0 0 0
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March 1987
All but one oil country, Indonesia, is correctly classified by four variables, OPCEB, CIX, AS and DSEA. Seven variables are necessary to correctly classify the oil economies. While one variable, OPCEB, correctly classifies all the oil economies but one (Indonesia), the probabilities of correct placement average only 54.7%. Three variables, OPCEB, CIX and AS, correctly classify all the mineral economies. By themselves OPCEB and CIX are poor at classifying mineral economies. Three variables, OPCEB, CIX and AS, are sufficient for classifying all the non-mineral economies except Senegal and Jordan. Seven variables, OPCEB, CIX, AS, DSBA, EGB, PDB and PDPB, are needed to achieve correct classification of oil, mineral and non-mineral non-oil economies. Surprisingly, it then appears
65
Profiles of Third World mineral producers Table 6. Discriminant Discriminating
analysis
of oil, mineral
and non-mineral
economies.
variables
OPCEB CIX AS DESA
EGB PDB PDPB OPCEB CIX AS DESA
OPCEB
CIX
OPCEB CIX AS
43.ia 57.3 56.2 57.3 55.2 57.3 56.2 54.7
40.8= 33.7a 48.4a 57.0 15.5= 54.7 42.4a 41 .Ea
12.1= 87.9 99.4 100.0 35.0= 100.0 100.0 76.3
13.9= 96.2 99.8 100.0 60.5 100.0 100.0 81.5
68.1 100.0 100.0 100.0 91 .l 100.0 100.0 94.2
43.2= 40.7= 44.2= 37.6a 44.3a 41.9a 43.7a 43.7= 42.4
37.1a 36.3a 35.7a 36.5a 37.4a 37.3a 32.ga 35.7a 36.1
95.4 93.2 78.8 88.8 93.2 98.5 79.1 94.7 90.2
88.4 99.6 75.4 98.1 99.9 96.3 92.7a _b
98.7 100.0 86.3 99.9 99.8 96.8 91.8 _
92.9
96.2
16.1= 29.0= 87.4 34.7a 84.9 70.6 90.0 73.4 30.1a 90.0 11.6a 75.1 89.6 62.4 85.9 62.4 20.8= 42.0= 8.3” 75.9 71.6 48.2=
77.0 69.7 33.6a 71.7 29.7a 35.9= 21.9= 32.2= 40.3a 18.9= 80.5 38.F 19.5” 79.3 32.6 58.9 78.1 51.3 81.5 27.Ea 55.7 40.9a
88.5 90.3 98.7 95.4 96.8 89.6 97.0 88.3 24.3a 95.4 86.2 95.0 95.5 91.6 98.0 97.9 93.4 77.4 80.4 86.4 98.8 65.3
99.8 99.2 99.8 72.2 100.0 99.7 99.3 95.6 70.3 99.9 45.1a 99.6 99.6 100.0 100.0 97.9 100.0 95.8 99.8 89.9 100.0 98.8
99.7 99.6 99.2 77.4 100.0 99.9 99.3 79.4 54.8 100.0 67.8 99.9 99.9 95.4 100.0 98.3 100.0 98.4 99.9 96.6 100.0 98.4
82.5 84.3 71.6 73.4 75.1 82.5 80.5 88.8 79.1 71.6 77.5 57.8 24.7a 16.5= 43.2a 16.5a 33.F 20.Ea 49.4= 58.3
33.7= 26.2= 61.5 47.9a 53.8 41 .6a 44.ia 28.ga 26.1a 25.8= 61.5 40.4a 53.9 79.3 62.6 76.6 _
97.0 94.8 99.3 97.8 99.0 98.7 98.6 98.4 76.5 73.1 99.7 79.8 44.7a 91.6
99.9 99.7 100.0 99.9 94.6 100.0 100.0 99.7 99.0 79.2 99.4 97.9 88.4 100.0
100.0 99.5 99.9 99.1 95.4 100.0 100.0 99.9 99.7 81.9 99.6 96.8 97.0 _
87.1
98.2
79.8 57.4 49.2=
94.8 92.4 88.6
95.7 95.1
Oil economies Indonesia Venezuela Algeria Libya Trinidad Saudi Arabia Kuwait Average Mineral
economies
Togo Tunisia Morocco Congo Chile Jamaica Peru Liberia Average Non-mineral
aMisclassified by discriminating variables; %o value computed due to missing values: ‘see text for description of discriminating variables.
66
economies
Israel Greece Nicaragua India Honduras Cameroon Sudan Costa Rica Senegal Somalia Korea Guatemala Malawi El Salvador Upper Volta Turkey Spain Philippines Hong Kong Colombia Thailand Malaysia Dominican Republic Ivory Coast Sierra Leone Panama Uruguay Madagascar Tanzania Ethiopia CAR Sri Lanka Argentina Kenya Jordan Singapore Pakistan Yugoslavia Bangladesh Portugal Brazil Averaoe
RESOURCES
POLICY
_
99.8 95.4
March 1987
Profiles
of Third
World
minerul
producers
that the oil countries are not as easy to profile as one might imagine, and that the oil, mineral and non-mineral non-oil classification, while feasible, is much more complicated than the twofold classification of mineral and non-mineral.
Conclusions The purpose of this paper, to determine whether mineral and non-mineral economies can be profiled on the basis of a limited number of economic variables, appears to have been achieved. The sample of 56 countries is by no means exhaustive, but it would be safe to assume that external debt and export variables are critical in differentiating mineral and non-mineral economies and could have universal applicability. Nankani’s original conclusions as to the nature of structural differences between mineral and non-mineral countries are confirmed in a general way. The evidence presented above indicated that since his study there seems to have been an increase in the relative importance of external debt in differentiating the mineral from the non-mineral economies. In fact, debt variables rather than such standard candidates as export instability or the share of the government sector in GNP are now a critical ingredient in the profile of mineral rich countries. The results presented also have relevance in a wider context. Traditionally, observers of mineral economies have noted that over time, these economies tend to become increasingly dominated by a syndrome in which three factors interact:” 0 0 0
250p tit, Ref 15, p 8. Robert Pollin, ‘The multinational mineral industry’, Crisis lMonth/y Review,
?f
Vol 31, April 1980, pp 25-38.
RESOURCES
POLICY
March
1987
an incentive structure that is biased against diversification; high sectoral wage differential; and high relative macroeconomic consumption roeconomic saving).
agriculture
and export
(or low relative
mac-
The long term implications of allowing this syndrome to persist are severe. As the mineral wealth is exhausted, the economy finds itself unable to support its population, and its earlier living standards; in the long run, stagnation and poverty become increasingly likely. Clearly, the recent stepped up levels of external debt contracted by these countries, together with the decline in most mineral (and oil) prices have made the development prospects of mineral economies even bleaker than forecast several years ago.2”
67