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

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146 Annex 2. The theoretical framework of the study Zambia in 1985/86 and 2003 Opportunities contributing to Household income strategies Household asset stock materializing in Farm income Non-farm income Market production Agricultural household model A smallholder household aiming at Utility maximisation factors contributing to Own consump tion describes Food security Leisure Market - purchased goods
Annex 3. General features of the Eastern Province of Zambia Eastern Province is bordered by Malawi and Mozambique. The provincial capital, Chipata, lies 25 kilometres from the Malawian border at a distance of approximately 580 km from the national capital Lusaka. With an area of 69,106 square kilometres the Province comprises eight districts. As indicated in Table 28, according to the 2000 census the Province had a population of 1.3 million, of whom 205,076 were farmer households. The number of male farmers was 148,593 and of female farmers 56,483 (MAFF 2001b), the proportion of female-headed farm households thus being 27.5 per cent. Table 28. District-level statistics, 2000/01 season, Eastern Province. District Femaleheaded hh Maleheaded hh Total No of farm hh Total population/2000 census Female Male Total Planted area ha 147 Maize production (in 50 kg) Mambwe 2,546 6,475 9,021 25,994 25,950 51,944 12,087 74,034 Nyimba 4,780 10,990 15,770 34,108 32,941 67,049 27,567 210,000 Katete 3,740 14,025 17,765 92,805 89,693 182,489 80,476 348,971 Petauke 8,269 22,366 30,286 119,593 122,940 242,533 69,286 961,758 Chipata 19,094 41,382 60,476 182,682 179,450 362,132 68,540 476,701 Lundazi 7,237 32,366 39,603 120,012 116,720 236,732 154,630 2,223,116 Chadiza 4,196 10,090 14,103 41,482 40,918 82,400 40,103 300,006 Chama 7,153 10,899 18,052 38,517 37,168 75,685 15,965 120,670 Total 56,483 148,593 205,076 658,540 642,433 1,300,973 468,646 4,715,256 Source: Ministry of Agriculture statistics (MAFF Chipata 2001b). The population of the Province falls under several ethnic groups which determine, whether land is handed from one generation to another through a matrilineal or patrilineal system. The Chewa, Kunda, Lala, and Nsenga groups follow the matrilineal descent systems, while Ngoni, Senga, Tumbuka, and Yao groups follow the patrilineal system (Milimo 1991). The province has two different agro-ecological regions, the plateau and the Luangwa valley, which differ in altitude, soil quality, temperature and annual rainfall. The valley is considered suitable for the production of rice, cotton, sorghum and millet, whereas the plateau is more fertile and can grow hybrid maize, groundnuts, cotton, sunflower, tobacco and soybeans (Milimo 1991). Most of the population is concentrated on the plateau because of the harsh conditions, including higher temperatures, less rainfall, and tsetse-fly infestation in the valley (Jha et al. 1991). The annual rainfall on the plateau varies between 850 and
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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
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Similar concerns were shared by Tay
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order to reduce income variablity.
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of infrastructure development, the
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which implies that diversification
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Haggblade et al. (2002) argue that
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In many cases the processing of the
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4.9 Rural income diversification in
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Table 3. Rural income-diversificati
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1990s - made the farmers reluctant
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In addition to asset endowments and
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5.1.2 The 2003 dataset The second s
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clarifying some concepts and assess
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5.2 Methods The theoretical grounds
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able random variables not explicitl
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Incshare 25 or Inclevel 26 = β0 +
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5.2.4 Choosing the estimation metho
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74 Both cash and in-kind income wer
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76 Share of income 100 90 80 70 60
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78 The households considered market
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80 The proportion of income generat
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82 The seasonality effect was clear
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84 Since a lack of money was given
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86 % of income 100 90 80 70 60 50 4
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88 100 90 80 70 60 50 40 30 20 10 0
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90 6.1.7 Grouping households accord
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92 number of adult members, was cri
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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
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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
Page 142 and 143: 142 Ruotsi, J., Lindberg, O., Seger
Page 144 and 145: 144 Zulu, B., Nijhoff, J.J., Jayne,
Page 148 and 149: 148 1,050 millimetres, while in the
Page 150 and 151: 150 Annex 4. Schedule of the field
Page 152 and 153: 152 Annex 5. Three household cases
Page 154 and 155: 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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