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

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88 100 90 80 70 60 50 40 30 20 10 0 ≤ 1 ha 1- 2 ha ≥ 2 ha Figure 8. Household income shares and scaled levels by cultivation size. Source: the researcher’s own dataset 2003 Table 11. Percentages of household earning income from each source by income tercile. I Tercile II Tercile III Tercile Mean % % % % cash crops 56 88 89 78 crops for consumption 89 100 100 96 livestock 33 56 62 50 forestry 48 61 45 51 business activities 41 61 74 58 wages 45 68 46 53 transfers 45 50 63 53 farm income 88 100 100 96 non-farm income 88 94 94 92 income sources/hh 2.7 3.8 3.8 3.4 Source: the researcher’s own dataset 2003. Farm income share Non-farm income share Farm income level (scaled) Non-farm income level (scaled) Of the 197 households, one reported no income from any source, and eight produced crops neither for home consumption nor for selling during the 2001/02 season (Table 11). Family health problems prevented household members from working either on-farm or off-farm. On average, the households in the lowest income group had 2.7 sources of income, while those in the middle- and high-income group had 3.8 sources. According to the Central Statistical
Office figures, 99 per cent of Eastern Province households were engaged in crop production, and 68 per cent in livestock production (either cattle, poultry or both) during the 2000/01 season (CSO 2001), while according to the EPIDS survey the percentage of households with livestock was lower. The sex of the household head was found to influence the household's earning capacity (Table 12). There were statistically significant differences between female-headed and maleheaded households in areas of cultivated land, which led to significant differences in crop incomes, and consequently in total income: women earned 66 per cent of men’s income. The sex of the household head had no impact on crop income when calculated per hectare, but the expansion of cultivated land among the women was restricted by their less frequent use of oxen for ploughing, for example, and also by the smaller number of adults in the household. Of the income sources, livestock and forest activities were most unevenly distributed between the male- and female-headed households. Livestock and total assets also differed between the male- and female-headed households, which may have affected the capacity of the latter to escape from poverty. The significantly lower educational level and the higher age of the female household heads may also have contributed to the same effect. The proportion of female-headed households was highest in the poorest income group, and disproportionally small in the highest group. A higher age, a lower educational level and a smaller area of cultivated land contributed to the lower incomes of both men and women, and even when these were controlled, the income differences remained clear between the male- and female-headed households. Table 12. Household characteristics disaggregated by the sex of the household head. Variable Female Male On average household size 5.7 6.3 6.1 education of hh head a 3.1 5.2 4.6 age of hh head 52 47 49 size of cultivated land (ha) 1.3 1.9 1.7 net income in ZMK 1,196,413 1,821,591 1,640,701 farm income share % 69.7 69.8 69.8 non-farm income share % 30.3 30.2 30.2 value of livestock, ZMK 458,079 1,352,329 1,093,587 value of all assets, ZMK 606,237 1,736,457 1,423,449 % female-headed hh in poorest group 38 % female-headed hh in middle group 33 % female-headed hh in highest group 15 a 3= finished standard 1, grade 2; 5=finished standard 3, grade 4 Source: the researcher’s own dataset 2003. 89
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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
Page 39 and 40: 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 90 and 91: 90 6.1.7 Grouping households accord
Page 92 and 93: 92 number of adult members, was cri
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
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138 Heltberg, R. (mimeo) 2001. Comm
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140 Lanjouw, J.O. & Lanjouw, P. 200
Page 142 and 143:
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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Rural Income Generation and Diversification - A Case Study ... - Doria

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