Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Appendix B Food Aid Requirements of Developing Countries KLAUS FROHBERG* Organization for Economic Cooperation and Development, Paris, France This paper summarizes results obtained with the Basic Linked System (BES) on food aid requirements in developing countries (LDCs). The simulations of the scenarios for which results are described in this paper were carried out at the Food and Agriculture Program (FAP) of the International Institute for Applied Systems Analysis (ORISSA) where the BES was developed. They are published by Parikh et al. (1988) and, as an executive report, by Parikh and Tims (1986~. The BES is a toot for analyzing agricultural policies in an international setting. It consists of 18 national models: 2 models comprising economically integrated regions, the European Community (EC) and the Countries for Mutual Economic Assistance (CMEA); and 14 regional models including all other countries. The national models and both the EC and the CMEA models are detailed in their representation of the behavior of producers, consumers and governments. The regional models have a somewhat less detailed specifi- cation. They all are of the general equilibrium type, are recursively dynamic and run in annual time increments. Since the BES is used mainly for analyzing agricultural policies, the representation of the agricultural sector is more detailed relative to the non-agricultural sectors which are summarized in one aggregate. Agricultural commodities are aggregated to nine subsectors which are the following: wheat, rice, coarse grains, ovine and bovine meat, dairy products, other animal products (pork, poultry, eggs and fish), protein feed (both of crops and animal origin), other food (oils and fats, sugar, vegetables, fruits, nonalcoholic beverages such as coffee, tea and cocoa), and nonfood agriculture (fibre, industrial commodities originating from agriculture). For each of these aggregates, production, disappearance (human consumption, feed, intermediate consumption), storage, net trade, and prices are calculated both at the national and international level. The BES ensures consistency among quantities traded and the countries' trade balances at the international level and, at the national level among supply, disappearance and net trade as well as expenditure and income. These consistencies are an important element of *The view expressed in this paper is not necessarily that of the OECD. 91
the BES as of any general equilibrium-type mode! and are missing in partial equilibrium models. Relevant for the topic of this paper is an explanation of how the nutritional status of the population is assessed in the BLS. Two indicators are calculated for this purpose with the BLS; nutritional intake and number of hungry people. A third indicator, food requirement is taken from calculations jointly established by FAO, the World Bank and the World Health Organization. The nutritional intake is calculated in form of calories and protein intake and based on the per capita consumption of food in a given country. Consumption, in turn, is arrived at by assuming that consumers maximize their utility given prices and income. The nutritional content of the various food items was calculated from FAO data simultaneously with the aggregation of the products to subsectors. It may vary from country to country for the same item. The number of people hungry is another indicator which is calculated based on the results obtained with the BLS. It should be pointed out that only chronic hunger is dealt with in this analysis. Famines are not considered since the BLS is basically a deterministic system. The Fourth World Food Survey (FAO 1977) provides estimates of this indicator for each country. These FAO estimates are based on country-specific data and on cross-country comparisons. FAO did not formalize the method completely. The same procedure has been adopted for the BLS by estimating the following regression (Parikh et al., 1988~: Hungry = f 0.01338 (138.6 - CALAR32 if CALAR < 138.6 where HUNGRY = percentage of population with calorie intake 1.2 times less than the required norm (basal metabolic rate) CALAR = calories available as a percentage of requirement. This cross-country regression provides a good fit of the FAO procedure (R2 = 0.87~. However, the good fit could be expected since the independent variable was used in gen- erating the dependent variable, among others and, obviously, had a strong impact. The unexplained variation of the dependent variables is influenced by country-specific variables like income distribution and genetic and climatic characteristics. Several scenarios have been analyzed with the help of the BES. They can be grouped into two categories; scenarios dealing with issues of trade liberalization in agriculture and scenarios designed to analyze the efficacy of aid. All scenarios were simulated for the period 1980-2000. The discussions of the results provided in the two references cited above are focusing on the outcomes obtained for the year 2000. This will be followed in the current report as well. The assessment of the various policies is done by comparing the scenario results of a specific year with those obtained for the same year in a reference run. The outcome of the latter with regard to the nutritional status of the population and the number of people suffering from hunger will be discussed before an assessment of the scenario results is provided. Results of the Reference Run The underlying assumption in generating the reference run has been a continuation of policy responses as in the past. With this assumption, it is hoped to have a base for 92
TABLE 1 GDP Per Capita, Calorie Intake, and People Hungry in Some Developing Countries GDP/capita Calorie (US$ 1970) 1980 2000 intake (kCal/capita/day) 1980 2000 People hungry (10 ~ 1980 2000 Argentina 1~350 1,795 3~653 3,656 ~ 1 Brazil 822 1,818 2,860 3,283 12 3 Mexico 798 1,157 2,487 2,588 3 3 Egypt 266 448 2J799 3,134 ~ O Kenya 166 200 2,495 2,802 6 7 Nigeria 181 390 2,254 3,168 25 2 India 104 181 2,141 2,533 219 156 Indonesia 83 151 1,840 2,374 21 0 Pakistan 182 224 2,460 2,718 9 6 Thailand 219 423 2,856 3,235 8 Turkey 580 1,231 3,137 3,219 1 1 SOURCE PariLh Ate Al ^., 1988, Table 4.16, p. 84. comparison of the scenario runs which is as neutral as possible in the sense that it "does not accentuate the impact of some policies while muting that of others" (Parikh et al., 1988, p. 393. It is not to be seen as a forecast because the BES is not a forecasting tool but an analytical device to explore and better understand the impact of alternative policy scenarios. The reference run very strongly points to the persistence of hunger. If no drastic policy changes are introduced as assumed for the reference run hunger is not eliminated by the end of the century. Results obtained with the BES indicate that a large part of the population in LDCs still suffers from undernutrition; 17 percent or 470 million people in 1990 and 11 percent or 400 million in 2000. To put this into perspective, 660 million hungry people is the estimate by FAO to have prevailed in 1970. The BES results indicate the number of hungry people to have peaked in the early 1980s and a steady decline from then on. Although the number of hungry persons remains disappointingly high, only relatively small quantities of additional food are required to raise the level of the nutritional status of all people to the accepted minimum. It amounts to about 50 million tons of grain or 3 per cent of the world cereal output. The reason why hunger is not eliminated during this century if past policies are extended into the future is, in general, the lack of marketable resources and skills of the poor which constrains their purchasing power. Obviously, BES results indicate progress in terms of eliminating hunger. Income increases in LDCs, but not to the necessary extent (see Table 1~. Also, increases in some food prices reduce purchasing power. The calorie intake reported in Table 1 refers to an average person and does not indicate 93
the situation of the undernourished people. The change over time (from 1980 to 2000), however, provides some information as to how the nutritional status of these people might also evolve as Tong as their income situation does rot worsen relative to the average person, and as Tong as price changes are not detrimental for them. The last two columns in Table 1 give estimates of hungry people in LDCs based on BES results. "Success" can be claimed only by Egypt and Indonesia, the two countries which are able to eliminate hunger by the year 2000, according to BES results. Brazil, Nigeria, India, Pakistan and Thailand reduce the occurrence of hunger in their countries, while in Argentina, Kenya and Turkey no improvement seems to be possible with a continuation of past policies. What generates the "success" of Egypt and especially Indonesia? The latter has a very strong per-capita income growth, averaging 3.0 percent per annum. But other countries have an even changes growth rate and still have problems with regard to feeding all people adequately (e.g., Turkey). Indonesia's prices of staple food decline or remain relatively constant. The same holds for Egypt which has a slightly lower growth rate of per-capita income. The countries with no progress in solving the food problem are suffering either from low income growth (Kenya, O.9 percent per annum per capita; Argentina, 1.4 per cent) and/or have less favorable staple food prices. Of course, one cannot rule out the possibility that a worsening of income distribution occurs simultaneously with the other changes. This explains why the number of hungry people increases in Turkey.* Usually, for a country as a whole the PAP study found a relatively Tow income elasticity of aggregate food demand expressed in calorie intake. In many of the LDCs, the figure is about 0.2 for the average population and nearly 1.0for the very Tow income groups. This also indicates the importance of assuring income growth across the various income classes. IMPACT OF TRADE LIBERALIZATION ON HUNGER Several scenarios regarding trade liberalization in agriculture have been analyzed with the BLS. Their impact on the nutritional status of many people in the DCs depends strongly on which countries participate in the trade liberalization and how the world market prices are affected (Table 2~. Three scenarios of agricultural trade liberalization will be briefly discussed here; lib- eraTization by OECD countries, except Turkey; by LDCs and by all market economies. Relative world market prices of agricultural commodities increase in all three scenarios, in comparison to the reference run. The strongest price rise is estimated to be for dairy products and for bovine and ovine meat followed by grains. Between the three liberalization scenarios, the price increases are more pronounced when OECD countries participate, i.e. in the liberalizing countries alone than when LDCs are the only liberalizing countries. This is a reflection of the strong protection agriculture gets in OECD countries. These increases in relative world market prices of agricultural commodities are trans- mitted onto the domestic markets. That stimulates agricultural output in LDCs but not necessarily the income of the entire economy, to an extent to offset the reduction in pur- chasing power due to higher food prices. Therefore, both indicators calorie intake and the number of people hungry worsen in many I.DCs. That might be accentuated under a *The reader is reminded that for all countries but India income distribution is not explicitly included in the model. 94
TABLE 2 Percentage Change Relative to the Reference Run in Calorie Intake and Number of People Hungry in the Year 2000 in Three Trade Liberalization Scenarios: By All Market Economies (ALLME), by OECD Countries excluding Turkey, and by DC Market Economies ALLME Calorie Number Calorie Countries intake hungry intake OECD Countries LDC Countries Number Calorie Number hungry intake hungry Argentina -1.5 31.0 -0.3 6.7 -1.2 24.1 Brazil -2.0 49.8 -0.5 12.3 1.4 34.1 Mexico 0.2 -2.8 -0.5 8.8 0.3 -5.5 Egypt -0.4 0 -0.5 0 0.6 0 Kenya 3.1 -14.2 1.8 -8.8 1.3 -6.3 Nigeria 1.1 -56.9 0.4 -47.4 1.3 -59.6 India -0.4 2.2 -0.9 5.6 1.5 -9.1 Indonesia 1.8 0 0 0 0.3 0 Pakistan 1.4 Thailand -0.3 Turkey 0.2 -16.9 -0.6 8.1 2.7 -31.9 3.3 -0. 1 l.0 -0.4 4.0 -5.7 -0.1 1.7 0.1 -2.1 SOURCE: Various tables in Parikh et al., 1988. scenario of trade liberalization by LDCs in those countries in which agriculture is taxed. In those cases, food price increases are even stronger. Maybe a discussion of the impact of trade liberalization on Argentina and Nigeria brings out this point more strongly. In Argentina, value added increases in all these scenarios. But so do food prices. The income increase is not strong enough to offset the rise in food prices and hence the decline in food consumption. In Nigeria, total value added goes up only when OECD countries alone liberalize, but not when the country itself participates. In the former case, food prices also go up slightly and in the latter two scenarios they go down. The offsetting mechanism is not strong enough in all three scenarios to allow the Nigerian population a higher food consumption and a reduction of the number of hungry people. IMPACT OF AID ON HUNGER The scenarios of trade liberalization in agriculture do not show any significant progress on the hunger issues. Can aid given to LDCs by the rich countries help? Several scenarios were analyzed with the BES which address this issue. Aid is a much more effective means for eradicating hunger than is free trade in agricul- ture. Yet, the most promising one is a combination of the two. Table 3 lists the impact of two aid scenarios on the number of hungry people in LDCs by 2000. Both scenarios assume the same amount of aid given; 0.5 percent of the GDP of the rich countries in addition to the 0.35 percent aid given currently. This additional aid is distributed to the LDCs in 95
TABLE 3 Impact of Aid of 0.5 Percent of GDP by the Rich Countries to the LDCs in Addition to the 0.35 Percent Presently Given--Results in 2000 Hungry Persons 6 Percent Change over Country Groups Reference Scenario(10 ~ Reference Scenarig (10 ~ A-Cap~ A-Bop All Developing Countries 400 -32 -32 Middle Income 30 0 +4 Low-Middle Income 60 -13 -8 Low Incomea 310 -40 -40 of which India 155 -54 -56 b Aid given to LDCs is added to investment. Aid given to LDCs as support of balance of payments. SOURCE: Parikh and Tims, 1986. inverse relation to their per-capita incomes. In one scenario, aid is tied to be spent as capital investment (A-Cap). The other scenario assumes that aid is given as a balance-of-payment support (A-Bop). The A-Cap scenario has a direct impact on the growth of the economy and indirect then on food consumption. The A-Bop scenario affects food consumption immediately since the marginal expenditure propensities of the recipient countries apply to balance of payments changes in the same way as to domestically-generated income. As can be seen from Table 3, the two scenarios provide a much stronger reduction of hunger in LDCs than the free trade scenarios discussed earlier. This impact is more pronounced in low-income LDCs because they receive a relatively high share of the aid . given. Donating countries might be hesitating in providing this additional aid, as one currently can observe, by the fact that the aid given is far below the amount the rich countries promised. If one compares free trade with aid the donating countries can recapture more than they give to the LDCs. Trade liberalization by all market economics and 0.5 percent of GDP as aid to the I,DCs results in a significant reduction in the number of hungry people. The impact, however, is slightly less than in a pure aid-giving scenario because of a food price increase. The donating countries can recover all the aid given and even have a 0.25 percent growth in income. The scenario described last is one of the more "sweetened" ones in terms of making it easier for the rich countries to donate aid and, at the same time, have a considerable effect on the developing countries and their hunger problem. The disappointing aspect is that it will not eradicate hunger entirely. The developing countries still can, in addition, introduce some of their own measures to accelerate this process. If they use some redistribution schemes, like food for work, hunger might not be a problem any more. Analyses with the mode} for India, which is part of the BES and very detailed in terms of income distribution, indicate that this is the best of all scenarios. Trade liberalization coupled with aid to LDCs and income redistribution schemes in LDCs is a feasible solution for eradicating hunger and minimizing the negative impact of aid on developed countries. 96
REFERENCES Parikh, K.S., G. Fischer, K. Frohberg & O. Gulbrandsen. 1988. Towards Fire Made in Agriculture, Martinus NiJhoff Publishers, Dordrecht, Netherlands. Parikh, K.S. & N. Tims. 1986. From Burner Arnsd~t Abundar~cc to Abundar~cc Without Hunger. Executive Report 13. International Institute of Applied Systems Analysis, Laxenberg, Austria. 97