|Famine, Needs-assessment and Survival Strategies in Africa (Oxfam, 1993, 40 p.)|
|2 A case of crying wolf?|
|2.1 Some distortions in the process of needs-assessment|
Appeals for emergency relief in Africa tend to be greatly shaped by annual assessments of food needs that are made by the UN's Food and Agriculture Organisation (FAO). FAO estimates of food needs are obtained by calculating the total quantity of food available for consumption in a country in a given year (allowing for imports, exports, use of food for Animals, seeding, industrial purposes, and losses during storage and transportation, as well as changes in stocks), and then subtracting this figure from the total food consumption needs of the country's population. In performing these calculations, the FAO generally relies heavily on government production estimates, whose methodologies are often not explained.
Difficulties surrounding the assessment of food production in Africa are formidable indeed. African countries are often sparsely populated, with many different climatic zones and cropping systems. Non-cereal crops may be particularly neglected in of ficial estimates. Animals and undomesticated plants are likely to provide a substantial portion of the diet. Non-cereal foods, including tubers, pulses, fruit and fish, may be ignored. Indeed, the neglect of relatively 'invisible' crops such as root crops has a long history. Colonial of ficials in Malawi in the 1940s came to the conclusion that households in one area had a chronic maize deficit, but took no account of sorghum, cassava and root crops (Vaughan).
Aerial photography may underestimate acreage, for example, if two or more crops are planted on the same land. On the other hand, satellite photographs create the danger that weeds like striga will be mistaken for crops, and that areas seen to be green may yet fail to flower and may yield virtually no crop (as happened recently in parts of Eritrea). Significantly, US Department of Agriculture estimates of crop production tend to make the weaknesses and uncertainty in the data more explicit than do FAO estimates. There is an element of false certainty about much of the FAO data.
The origins of the data on losses and uses of food other than for human consumption are not clear. Figures on stocks are likely to be unreliable. Official trade figures may fail to take account of widespread smuggling, and may in any case be inaccurate: one recent study of African trade flows found that a particular country's records of imports and exports to another country rarely bore much relation to the records of these same trade flows that were kept in this second country. Population data are also likely to be inaccurate, not least because regions can hope to gain more government resources by overestimating their populations. Inaccurate production estimates may not simply be the result of chance errors, but also of repeated, and perhaps rational, under-reporting of production by a number of parties. Rural producers may underestimate their own production and resources as a result of a desire to avoid taxation or compulsory government purchase of crops. Many people (at local, regional and national levels) may be influenced by a desire to solicit aid.
It is arguable that the FAO itself has an interest in accepting exaggerated shortfalls in production, since the notion of large-scale food problems in Africa provides much of the justification for the organisation's existence. Aid agencies may have a number of pragmatic reasons of their own for supporting major appeals: at ground level, endorsing UN appeals may give improved access to scarce UN resources like transport and radios; back at headquarters, large-scale emergencies are acknowledged as an important trigger for raising funds. Meanwhile, the consequencesin terms of human sufferingof 'getting it wrong' are likely to be far less grave when needs are overestimated than when they are underestimated.