Rural Income Generation and Diversification - A Case Study ... - Doria

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92 number of adult members, was critical in terms of labour: there was a significant positive correlation between the household size and the area of cultivated land. The female-headed households were smaller in size (5.8) than the male-headed (6.3) which meant a smaller labour force and often indicated that the husband had died or moved out of the farm. On the other hand, a smaller household size meant there was less need to produce food for household consumption. In order to capture the effect of the number of adult household members in relation to the cultivated land area a new variable - cultivated land/number of adults - was calculated and used in the analyses. The dependency ratio illustrates the number of young dependents per adult in the household. The effect of a higher number of children was twofold. They were able to contribute to the total income particularly through participating in forest and business activities: they often seemed to be responsible for collecting and selling non-wood products and were also involved in small-scale selling of agricultural produce. On the other hand, the more adults in relation to the number of children there were, the higher was the proportion of farm income. Age and sex of the household head. The age of the household head did not differ significantly between the income groups: the average was 48 years, 47 for the male heads and 52 for females. Households with an older head had more land in their possession but the same size of cultivated area as the younger ones. Age also correlated positively with the value of assets indicating an accumulation of wealth in the more mature households. The older the head, the smaller was the dependence ratio indicating a diminishing number of children per adult. The interviewees said that an old head made the household more vulnerable. This was supported by the observation that the older the head, the earlier the household had run short of food during the previous year. Less than one third of the households had a female head (30%), the percentage being highest (38%) in the low-income group. The female-headed households were worse-off than the male-headed in many respects: their total income was lower, they cultivated less land, had fewer valuable assets, and used fewer inputs. Moreover, the heads were older, had less education and smaller families. Education of the household head. On average, the household heads had three or four years of school education, the male heads having more than the female heads who often had less than two years of formal education. Thirty-five per cent of the female heads and 20 per cent of the male had no formal education. The older heads had less education than the younger ones. The use of inputs and the size of cultivated land increased along with the level of education, thereby resulting in slightly higher income levels. Furthermore, the more education the head had had, the higher the percentage of children in the household going to school.
Table 14. Household characteristics by income tercile. I Tercile II Tercile III Tercile Mean household size 5.3 6.4 6.7 6.1 no of adults 3.5 4.2 4.2 3.9 dependency ratio 0.58 0.59 0.75 0.64 age of hh head 49 49 47.5 48.5 % of women headed hh 38 33 15 29 education 4.3 4.2 5.3 4.6 total land area, ha 2.73 3.72 4.7 3.7 size of cultivated land, ha 1.07 1.67 2.5 1.73 cultivated land/adult, ha 0.38 0.45 0.66 0.49 household assets, ZMK 272,477 1,216,209 2,773,557 1,412,548 total hh income, ZMK 447,856 1,224,922 2,849,616 1,499,939 Source: the researcher’s own dataset 2003 Natural capital Size of cultivated land. The mean size of cultivated land was 1.9 hectares for the maleheaded and 1.3 hectares for the female-headed households. By income terciles the cultivated land area was 2.5, 1.7 and 1.1 hectares in the highest, middle- and the lowest terciles, respectively (Table 14). Access to animal draught power increased the size of the cultivated area significantly: households relying mainly on hand hoes cultivated, on average, 1.5 hectares (0.45 ha/capita) and those using oxen (28 per cent of all households) 2.5 hectares (0.68 ha/capita). Most of the households considered the land in their possession to be enough for the family needs: almost all of them had more land than they actually cultivated. Those in the lowest tercile had 2.7 hectares on average, of which 41 per cent was cultivated: respective figures for the middle and highest terciles were 3.7 hectares and 46 per cent and 4.7 hectares and 53 per cent. In the in-depth interviews the farmers mentioned soil degradation, the need to allow land to rest, the non-availability of inputs, and the shortage of labour and draught power as reasons for not cultivating their entire land area. The number of household members, and specifically of adults, had a significantly positive correlation with the size of cultivated land, suggesting that labour was more critical than land availability in determining the cultivated area. Table 15 groups the households in three categories based on the area of cultivated land in order to assess the differences in certain characteristics 45 . Households cultivating larger areas were in a better position to send their children to school, possessed more assets, and were 45 Land was used as a categorisation criterion by Reardon et al. (2001), for example 93
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Kaisa Karttunen Rural Income Genera
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University of Helsinki Department o
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CONTENTS 1. Introduction ..........
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Table 6. Percentages of income from
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WFP World Food Programme WHO World
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12 man 2002). These include income-
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14 The following questions were for
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16 of household comsumption is also
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18 Zambian farmers fall into three
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20 impact on rural poverty. Startin
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22 1992 consumer and transportatio
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24 The Government of Zambia (GRZ) i
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26 inadequate monitoring of the act
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28 Distributor Scheme was fully in
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30 as tobacco and cotton the out-gr
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32 households were directly afflict
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34 If it had no control over the m
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36 According to the AHM, a househol
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icultural economy was opened up to
Page 41 and 42: Similar concerns were shared by Tay
Page 43 and 44: order to reduce income variablity.
Page 45 and 46: of infrastructure development, the
Page 47 and 48: which implies that diversification
Page 49 and 50: Haggblade et al. (2002) argue that
Page 51 and 52: In many cases the processing of the
Page 53 and 54: 4.9 Rural income diversification in
Page 55 and 56: Table 3. Rural income-diversificati
Page 57 and 58: 1990s - made the farmers reluctant
Page 59 and 60: In addition to asset endowments and
Page 61 and 62: 5.1.2 The 2003 dataset The second s
Page 63 and 64: clarifying some concepts and assess
Page 65 and 66: 5.2 Methods The theoretical grounds
Page 67 and 68: able random variables not explicitl
Page 69 and 70: Incshare 25 or Inclevel 26 = β0 +
Page 71: 5.2.4 Choosing the estimation metho
Page 74 and 75: 74 Both cash and in-kind income wer
Page 76 and 77: 76 Share of income 100 90 80 70 60
Page 78 and 79: 78 The households considered market
Page 80 and 81: 80 The proportion of income generat
Page 82 and 83: 82 The seasonality effect was clear
Page 84 and 85: 84 Since a lack of money was given
Page 86 and 87: 86 % of income 100 90 80 70 60 50 4
Page 88 and 89: 88 100 90 80 70 60 50 40 30 20 10 0
Page 90 and 91: 90 6.1.7 Grouping households accord
Page 94 and 95: 94 more likely to use fertilisers a
Page 96 and 97: 96 holds. According to the responde
Page 98 and 99: 98 The following process was follow
Page 100 and 101: 100 6.1.9 The results of the econom
Page 102 and 103: 102 The categorisation of household
Page 104 and 105: 104 Table 20. Determinants of the s
Page 106 and 107: 106 In some cases the former househ
Page 108 and 109: 108 indicated thus an opposite tren
Page 110 and 111: 110 The Simpson diversification ind
Page 112 and 113: 112 tares - the difference being st
Page 114 and 115: 114 which brought more purchasing p
Page 116 and 117: 116 diversification index. Block an
Page 118 and 119: 118 evidence that households had no
Page 120 and 121: 120 such as piecework and forest la
Page 122 and 123: 122 7.2 Changes in the households b
Page 124 and 125: 124 lower soil fertility, and the l
Page 126 and 127: 126 8. Conclusions and recommendati
Page 128 and 129: 128 Rural non-farm activities are l
Page 130 and 131: 130 Politiikkamuutosten seurauksena
Page 132 and 133: 132 References Abdulai, A. & CroleR
Page 134 and 135: 134 CSO. 1997. Living Conditions Mo
Page 136 and 137: 136 Ellis, F., Kutengele, M. & Nyas
Page 138 and 139: 138 Heltberg, R. (mimeo) 2001. Comm
Page 140 and 141: 140 Lanjouw, J.O. & Lanjouw, P. 200
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142 Ruotsi, J., Lindberg, O., Seger
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144 Zulu, B., Nijhoff, J.J., Jayne,
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146 Annex 2. The theoretical framew
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148 1,050 millimetres, while in the
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150 Annex 4. Schedule of the field
Page 152 and 153:
152 Annex 5. Three household cases
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154 In the 1970s and 1980s, and eve
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