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2.3 Functions of the livestock sector


2.3.1 Two ways to classify livestock sector functions
2.3.2 Relative importance of livestock sector functions in sub-Saharan Africa
2.3.3 Farmers' tendency to increase herd size: An important policy issue

It is necessary to know the present functions of the livestock sector in order to gauge how well it is performing in relation to policy objectives, and to ensure that new policies designed to achieve new objectives do not, unintentionally or to an unexpected degree, disrupt the performance of existing socially desirable functions. Analysts should be aware of the multiple functions of livestock and of the complex relationships between those functions. They should know which functions are important to which social classes or ethnic groups in which areas of their country. They should understand the different kinds of production systems found in their country and how those systems are changing over time. Finally, they should understand that expanding the output of one function may diminish the output of another.

2.3.1 Two ways to classify livestock sector functions

A first step in the classification process is to quantify the relative importance of different present functions as a prelude to judging how much they may be disrupted by new policies. Livestock sector function(s) can be classified in several ways. However, two widely used classifications are conceptualised in terms of:

· kinds of output produced
· uses to which these outputs are put.

Among the kinds of output produced are: food (i.e. meat, milk, eggs); inputs to cropping (i.e. manure and farm power in the form of animal traction); and raw materials (e.g. wool and skins to make other goods). Among output uses are: subsistence consumption by the livestock holder's household; direct supply of inputs (e.g. traction and manure to crop production); cash income through sales of live animals or their output; savings and investment through increasing the size and quality of the herd; and social functions such as paying bride wealth, helping destitute families by lending them livestock or providing animals for communal feasts or sacrifices.

2.3.2 Relative importance of livestock sector functions in sub-Saharan Africa

Table 2.1 shows, for sub-Saharan Africa as a whole and for different geographical regions within it, the relative importance during the late 1970s of different kinds of outputs when these are calculated in terms of monetary value. The table shows that for sub-Saharan Africa, meat is the most valuable output, accounting for 47% of the total. Of this meat, beef accounts for 57% and small ruminant meat for 22%. The second most valuable output is animal traction, accounting for 31%; milk, the third most valuable output, accounts for 15%. At the same time, regional variations in terms of the relative contributions of outputs can be noted. For example, animal traction is very important in East Africa but is much less so in other regions.

Table 2.1. Share of different kinds of output of the total livestock output in sub-Saharan Africa and its regions.

Kind of output1

% share of total output2

West Africa

Central Africa

East Africa

Southern Africa

Sub-Saharan Africa

Animal traction

21

3

39

26

31

Manure

4

1

3

2

3

Meat

56

79

38

58

47

Milk

11

12

17

9

15

Eggs

8

5

3

5

4

Total %

100

100

100

100

100

Total value (US$ millions)

1460

349

3747

930

6486

Source: Addis Anteneh et al (1988).

1 Excludes hides, skins, wool and slaughterhouse by-products.
2 Share of output in 1975 US$ at uniform continent-wide prices.

Table 2.2 presents sample-based data on types of output in a mixed peasant farming system in the Ethiopian highlands. It also presents data on the use to which livestock output is put. Note the importance of livestock in generating cash for the farm (responsible for 87% of farm cash income), even though only a small proportion (24%) of the gross value of livestock output is sold for cash. Note also the importance, in overall livestock output, of the value of its contribution of inputs, in the form of animal traction and manure, to cropping. As stated earlier, policies can have unintended (and potentially adverse) effects. The data provided in Table 2.2 indicates how policy could negatively affect the welfare of certain groups. For example, policy changes intended to produce higher quality meat for export, which ignored the role of livestock in providing inputs into the farm and generating cash, could run into severe problems in terms of both peasant acceptance and domestic food security.

Table 2.2. Types and uses of livestock output in the Ethiopian highlands, 1979-83.1


1979

1980

1981

1982

1983

Annual average

Gross value of livestock output








Food output of ruminants2

301

340

397

401

427

373


Crop inputs3

584

621

591

661

788

649


Raw materials4

19

22

33

26

30

26


Others5

330

249

542

424

341

377


Total

1234

1232

1563

1512

1586

1425

Uses of livestock output








Sold for cash

230

412

432

274

334

336


Crop inputs used on farm

552

589

542

612

739

607


Raw materials used on farm

7

7

15

15

15

12


Other outputs consumed or retained on farm

445

224

574

611

498

470


Total

1234

1232

1563

1512

1586

1425

Investment in livestock








Value of livestock held

1343

1375

1491

1522

1850

1516


No. livestock held (TLU)6

5.9

6.6

6.8

7.3

7.9

6.9

Some ratios (%)








Livestock gross output/farm gross output

60

43

50

55

50

51


Livestock cash income/farm cash income

90

84

82

85

96

87


Livestock cash income/livestock gross output

19

33

28

18

21

24

Source: Gryseels (1988).

1 Value in Ethiopian Birr per farm.
2 Milk, butter, meat and live animals sold.
3 Manure and animal traction including transport of products and feed.
4 Wool, hides and skins.
5 Residual category includes eggs, chicken, value of young stock born and unidentified items.
6 TLU = tropical livestock unit of 250 kg live weight. The TLU is a common unit in which different kinds of livestock (cattle, small ruminants etc) can be compared.

Box 2.1: Construction of regional output tables.

It would be relatively simple to construct tables similar to Table 2.1 for different regions within a country. To do so, one would need to have data for the different regions on:

· Size (numbers) of total regional herds (flocks).

· Sex and age composition of herds (flocks).

· Offtake rates for slaughter of different ages/sex.

· Live weights at slaughter of different ages/sex and dressing-out percentages.

· Milk yields per lactation.

· Calving rates and lengths of lactations; or, if there is no marked seasonality, proportion of breeding females lactating at any point in time and average daily milk yield.

· Meat or liveweight and milk prices (see module 4 for further discussion of which prices to use).

· Area (ha) cultivated by animal traction and the per ha rental cost of such cultivation; or number of ploughing animals (e.g. oxen), number of days on average worked per year and daily hire charge per animal.

· Value of manure; this might be expressed in terms of quantity of manure (e.g. US$ per half-tonne cart-load) or of animal-nights, where, under contractual arrangements, for a fee, animals are kept in night enclosures to fertilise fields.

It is more difficult to construct reliable tables, such as Table 2.2, showing how total output is allocated to different uses. However, while accurate data are always desirable, even quite rough guesses yield interesting insights. Table 2.3 shows examples where the mixed farming system of the Ethiopian highlands is compared to a pastoral system. Such regional comparisons are useful not only in terms of identifying functions of various outputs across different production systems, they also help analysts define the potential impact of their policies amongst these varied systems.

Table 2.3. Types and uses of livestock output in two systems in Ethiopia.


Highland system

Pastoral system

Composition of livestock output by value (%)




Food

26

61


Crop input

46

<1


Raw material

2

3


Other (includes values of young stock borne)

26

35


Total

100

100

Uses of livestock output by value (%)




Sold for cash

24

31


(within which exported)

(0)

(13)


Crop inputs used on farm

42

<1


Other raw materials used on farm

<1

3


Other outputs consumed or retained on farm

33

65


Total

100

100

Some ratios (%) by value:




Livestock gross output/farm gross output

51

>90


Livestock cash income/farm cash income

87

>90


Livestock cash income/livestock gross output

24

33

Source: Table 2.2 and ILCA (unpublished data).

2.3.3 Farmers' tendency to increase herd size: An important policy issue

Non-economic motivation vs economic motivation

One issue with policy implications is the tendency of African pastoralists and mixed farmers to invest their savings in increasing herd size. This investment may take the form of purchasing additional animals or allowing "natural" measures (i.e. births into the herd exceed deaths and other exits) to take their course. The tendency to increase herd size is often attributed to "non-economic motivation", in particular to the prestige and status which large herds imply and to the need for large payments of bride wealth. Because governments are worried about desertification caused by overstocking, they tend to be unsympathetic to these non-economic motivations and to feel they should compel stockholders to limit their herd sizes.

Let us, for the moment, accept that some individuals or groups increase their herd size for "economic reasons" and others for "non-economic motivations" and that governments may be more justified in interfering to control the latter than the former. In a particular situation, how do we decide the relative importance of different forms of motivation? The first step is to find out the actual size of the herd. Knowing the average herd size is not very useful since herd sizes often vary enormously between families and the motivations of the wealthy may be quite different from those of the poor. Thus, we need to know the statistical distribution of herd sizes.

Because households with large herd sizes often have more persons than households with small herds, it may also be useful to know the distribution of herd sizes per person as well as, or instead of, per household. Table 2.4 presents examples of herd size distributions per household and per person. The appendix of this module shows how to compare the relative distribution of herd sizes in two situations, using Lorenz curves.

Table 2.4. Household size and distribution of cattle holdings in north-eastern Senegal.

 

Herd size group (number of cattle)

0-9

10-24

25-49

50-99

100+

Total

Percentage of households

21

27

22

17

13

100

Percentage of people

19

26

22

18

15

100

Percentage of cattle

1

9

17

27

46

100

Average number of people/household

7.6

7.9

8.3

9.2

9.4

8.3

Average number of cattle/household

3

15

33

71

146

43

Source: Sutter (1987).

One reason why pastoralists and farmers in Africa invest their savings in livestock is that, because of unreliable weather, their farm output fluctuates enormously from year to year. Therefore, part of the income made in good years needs to be kept in an easily cashable form (in "liquid assets") so that, in bad years, it can be used to purchase essential food for the family. Banking services are not well developed in rural Africa and investment in livestock is often the next-best alternative. Livestock can easily be converted into cash and earns a return. Figure 2.1 shows the relationship, over six years, between the yields of the main cereal crop (barley) and the number of small ruminants kept by peasants in the Ethiopian highlands. The figure demonstrates that, in the year after a poor barley yield, the number of small ruminants declined as lambs were sold in order to generate cash to purchase grain. In deciding whether investment takes place for economic or non-economic reasons, one needs to take into account this pattern of offsetting investment and encashment.

Approaches to determine non-economic and economic motivations

Three main approaches may be used to help us decide whether investment in increasing herd size arises from economic or non-economic motivations. Specifically:

· Assess the minimum herd size necessary to support the dependent population at a particular standard of living.

· Examine herd management efficiency and ratio of return.

· Verify, by surveys, the validity of claims that herd-size increases are for non-economic (e.g. social, political, cultural) reasons.

Figure 2.1. Crop yield and holding of small ruminants in the highlands of Ethiopia, 1979-85.

Each of these will be discussed in turn. However, it should be noted that economic and non-economic motivations are not necessarily mutually exclusive. Both may be operating at the same time. In addition, as the following points will demonstrate, it is not always easy to identify whether economic or non-economic motives are guiding farmer decisions to increase herd size.

Minimum herd size. Dahl and Hjort (1976) showed that in a typical pastoral society, wholly dependent on food obtained from their own herds, a minimum of 10-11 cattle (or their equivalent in other kinds of livestock) per person is required to provide the necessary calorie intake to support life. Sandford (1982) estimated that in mixed farming systems in Zimbabwe, where it is difficult to buy draft oxen, a minimum herd size of 8-10 cattle is required by a household. With this number, the household can breed replacement oxen so that it can survive as an independent farming unit. This suggests that households which are striving to increase their herd size, but have yet to reach the minimum required, are operating from purely economic motivation. Conversely, for those whose herd size exceeds the minimum, non-economic motives may be operating. Table 2.5, showing the proportions of households to cattle in a farming system in Zimbabwe, demonstrates who, by this criterion, are subject to economic or non-economic motivation, respectively. Obviously this criterion is an extremely severe one in restricting the definition of economic motivation.

Table 2.5. Distribution of cattle holdings in Wedza District, Zimbabwe, 1982.

 

Herd size (head of cattle)

1-3

4-6

7-9

10-19

20-29

30+

Total

Proportion of cattle holders with this size herd

36

32

16

14

1

1

100

Proportion of cattle held in this size herd

13

27

22

32

5

1

100

Source: Sandford (1982).

The box within Table 2.5 indicates the proportion of cattle holders who may be operating for non-economic reasons.

Herd management efficiency and ratio of return. This approach examines the way in which herds are managed and the returns to investment they offer to the owner. Evidence from Kenya, as shown in Table 2.6, can be used to illustrate this point. The table indicates that wealthier households (i.e. those with more livestock per household member) with larger herds milk their animals less intensively and extract less output from them than medium and poor households. This provides, at first sight, some evidence that wealthier families may be less "economically motivated" than medium or poor households. Yet the complexity of the issue is illustrated by the lower half of the table which shows that, although less time per animal is spent on livestock management by wealthy than by other households, the actual time spent per person in managing animals is more. It is possible, therefore, that the lower economic output of the wealthy households' herds reflects not so much lack of economic motivation as an acute labour constraint.

Table 2.6. Economic output and labour input by wealth of household among the Maasai in Kenya, 1981-83.

 

Household wealth category

Poor

Medium

Wealthy

Mean herd size (no. of TLU1)

29

62

272

Percentage of lactating cows actually milked

96

60

30

Gross value of output per TLU in the herd (Kenya shillings/year)

460

334

159

Net return (% yearly) on capital invested in livestock

24

15

9

(result of long-term simulation model)




Hours spent managing livestock: per TLU

0.8

0.5

0.2

per male adult worker

4.5

4.6

6.9

per household

24.0

32.0

48.0

Source: Solomon Bekure et al (1991).

1 TLU = tropical livestock unit of 250 kg live weight.

Verification of non-economic motivations. One way to test the validity of claims that large herds are kept for non-economic reasons, such as payment of bride wealth, is to examine what proportion of the herd has actually been subjected to these transactions. Evidence from Zimbabwe (Sandford, 1982) suggested that bride wealth (lobola) accounted for only about 5% of transactions in male cattle but possibly as much as 20% in female cattle.

Important points (2.2-2.3)

· In prioritising policy issues, knowledge of one's livestock sector is essential in terms of:

- its current functions
- its future objectives
- its current performance and problems
- the scope of policy change.

· Knowledge of current functions helps ensure that new policies do not disrupt the performance of existing desirable functions.

· Livestock sector functions are classified in terms of:

- kinds of outputs
- the use of these outputs.

· The relative importance of the livestock sector's present functions in sub-Saharan Africa in terms of kinds of output and uses of outputs are:

- kinds of output: meat, traction and milk
- uses of outputs: crop inputs used on farm, household consumption, cash income through sale and raw material.

· Restricting the tendency of farmers to increase herd size is an important policy issue for African governments.

· The tendency of farmers to invest savings in increasing the size of their herds could be due to both economic and non-economic motivations.

· Three approaches to deciding if the tendency for farmers to increase herd size is due to non-economic or economic motivations are:

- assessing the minimum herd size needed to support the dependent population

- calculating herd management efficiency and ratio of return

- verifying, by surveys, the validity of claims that herd increases are for non-economic e.g. social, political, cultural) reasons.


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