Impact Of Agricultural Market Reforms On Smallholder Farmers In ...

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Table 4.1.13-Ethnic background of household head Expenditure category (quintile) Poorest 2 3 4 Richest Total Fon 15% 26% 21% 24% 26% 23% Adja 18% 8% 14% 9% 10% 12% Nago 6% 13% 7% 16% 8% 10% Bariba 4% 15% 9% 8% 7% 8% Mahi 1% 1% 3% 1% 1% Dendi 0% 0% 1% 0% 1% 1% Otamari 5% 2% 1% 1% 1% 2% Holli 3% 4% 1% 1% 2% 2% Yom 7% 1% 4% 2% 3% Lopka 0% 0% 1% 0% 0% Other 41% 29% 36% 40% 44% 38% Total 100% 100% 100% 100% 100% 100% Source: IFPRI/LARES Small Farmer Survey. Table 4.1.14-Households by religion and department Department Atacora Atlantique Borgou Mono Ouémé Zou Total Animist 43% 56% 22% 56% 17% 45% 39% Muslim 33% 3% 58% 11% 9% 18% Catholic 21% 24% 7% 19% 35% 30% 23% Protestant 2% 15% 13% 20% 36% 15% 18% Other 1% 2% 6% 2% 1% 2% Total 100% 100% 100% 100% 100% 100% 100% Source: IFPRI/LARES Small Farmer Survey. Table 4.1.15-Membership in cooperative or GV Department Atacora Atlantique Borgou Mono Ouémé Zou Total GV 43% 1% 39% 33% 17% 58% 34% Cooperative 28% 19% 7% 14% 10% 8% 13% GV and Cooperative 6% 2% 30% 1% 5% 7% 8% Not member 23% 77% 25% 52% 68% 28% 45% Total 100% 100% 100% 100% 100% 100% 100% Source: IFPRI/LARES Small Farmer Survey. Table 4.1.16-Membership in a credit club Department Atacora Atlantique Borgou Mono Ouémé Zou Total Yes 21% 92% 31% 57% 75% 63% 57% No 79% 8% 69% 43% 25% 37% 43% Total 100% 100% 100% 100% 100% 100% 100% Source: IFPRI/LARES Small Farmer Survey. 135
Table 4.1.17-Main activity of head of household by department Department Atacora Atlantique Borgou Mono Ouémé Zou Total Crop production 94% 98% 91% 94% 65% 96% 89% Livestock production 1% 4% 2% 1% Fishing 6% 1% Food processing 0% 1% 1% 0% Manufacturing 1% 1% 1% 0% Construction 2% 0% 1% 1% 1% 1% <strong>Agricultural</strong> trade 0% 1% 0% Other trade & services 1% 0% 1% 1% 24% 1% 5% Retired/Not working 2% 2% 1% 1% 1% Housework 0% 1% 0% Total 100% 100% 100% 100% 100% 100% 100% Source: IFPRI/LARES Small Farmer Survey. Table 4.1.18-Main activity of adults (15+ years) Department Atacora Atlantique Borgou Mono Ouémé Zou Total Crop production 71% 80% 48% 89% 29% 71% 64% Livestock production 1% 2% 1% 0% 0% Fishing 2% 0% 0% Food processing 3% 1% 1% 0% 24% 2% 5% Manufacturing 1% 0% 0% 2% 0% 1% Construction 1% 0% 0% 0% 1% 0% <strong>Agricultural</strong> trade 0% 11% 0% 0% 3% 5% 3% Other trade & services 1% 3% 1% 5% 24% 6% 7% Unemployed 0% 2% 1% Student 3% 4% 2% 4% 9% 7% 5% Retired/Not working 5% 1% 4% 0% 4% 4% 3% Housework 14% 0% 41% 2% 1% 10% Total 100% 100% 100% 100% 100% 100% 100% Source: IFPRI/LARES Small Farmer Survey. 136
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IMPACT OF AGRICULTURAL MARKET REFOR
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TABLE OF CONTENTS CHAPTER 1 - INTRO
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5.1.10 Expenditure patterns .......
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CHAPTER 1 - INTRODUCTION 1.1 Backgr
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villageois, (GV)) was needed as the
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CHAPTER 2: POLICY BACKGROUND FOR BE
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2.3 Evolution of Economic Policy 2.
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Under pressure from the World Bank
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anking system has been restored to
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Fertilizer can be imported outside
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particularly urban wage-earners. On
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Soulé (1996) describes the evoluti
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led to a more sustainable agricultu
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Table 2.4 - Gross farm revenue from
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Malawi’s economy is heavily depen
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the reduction of its operations in
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crops is also difficult because tob
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Table 3.1 CROP 1982/83 1983/84 1984
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CHAPTER 4: RESULTS OF THE BÉNIN SM
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where W v is the weight for a house
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heads. This suggests that some of t
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And school attendance is much highe
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Crop production is the main activit
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(33 percent). Livestock income is m
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Somewhat surprisingly, the relation
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It is no more common among richer h
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production, and women actually spen
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Seed use by crop Although only 18 p
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Looking at the results by departmen
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Ouémé presents an unusual case: j
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Market prices have significant effe
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policies of SONAPRA to discourage
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crops are responsible for this incr
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Respondents were asked whether the
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Female-headed households, not surpr
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households are not considered credi
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In almost every category of agricul
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This discussion implies that farms
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eturns per hectare and labor-intens
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farm household and tends to be smal
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Surprisingly, the value of sales as
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Finally, proximity to an all-season
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Changes in crop marketing In this s
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Poor households are more likely to
Page 92 and 93: it is clear that virtually all grow
Page 94 and 95: production to total expenditure is
Page 96 and 97: a significant number of household (
Page 98 and 99: non-food spending. These are follow
Page 100 and 101: Larger farms are associated with hi
Page 102 and 103: This would not be surprising in lig
Page 104 and 105: Female-headed households appear to
Page 106 and 107: poorest expenditure category to jus
Page 108 and 109: headed household were more likely t
Page 110 and 111: Households in every expenditure cat
Page 112 and 113: An important result of this analysi
Page 114 and 115: oad network, although those citing
Page 116 and 117: questions posed by the IFPRI-LARES
Page 118 and 119: With regard to cotton marketing, al
Page 120 and 121: Village leaders were asked to ident
Page 122 and 123: Marketing patterns Village leaders
Page 124 and 125: 4.3: Results of the Bénin Survey o
Page 126 and 127: 4.3.2 Survey methods At the time of
Page 128 and 129: officers have CM2 certificates. Thi
Page 130 and 131: Suppliers The GV representatives we
Page 132 and 133: Cotton area per GV ranges from 145
Page 134 and 135: The largest cost items are schools
Page 136 and 137: members and 10 percent of the membe
Page 138 and 139: Table 4.1.1-Description of sample o
Page 140 and 141: Table 4.1.7-Age, education, and lit
Page 144 and 145: Table 4.1.19-Importance of each sou
Page 146 and 147: Table 4.1.25-Number of plots and ar
Page 148 and 149: Table 4.1.31-Land tenure by expendi
Page 150 and 151: Table 4.1.37-Change in labor alloca
Page 152 and 153: Table 4.1.42-Seed use by sex of hea
Page 154 and 155: Table 4.1.47-Perceived change in av
Page 156 and 157: Table 4.1.54-Share of producers of
Page 158 and 159: Table 4.1.59-Fertilizer use by farm
Page 160 and 161: Table 4.1.64-Characteristics of fer
Page 162 and 163: Table 4.1.69-Change in fertilizer a
Page 164 and 165: Table 4.1.75-Allocation of labor by
Page 166 and 167: Table 4.1.82-Allocation of labor by
Page 168 and 169: Table 4.1.89-Change in credit avail
Page 170 and 171: Table 4.1.94-Percent of households
Page 172 and 173: Table 4.1.98-Percent of households
Page 174 and 175: Table 4.1.102-Area allocation by cr
Page 176 and 177: Table 4.1.106-Area allocation by cr
Page 178 and 179: Table 4.1.110-Marketed share of out
Page 180 and 181: Table 4.1.114-Marketed share of out
Page 182 and 183: Table 4.1.117-Regression for market
Page 184 and 185: Table 4.1.120-Change in the type of
Page 186 and 187: Table 4.1.128-Perceived change in r
Page 188 and 189: Table 4.1.135-Main reason for stori
Page 190 and 191: Table 4.1.140-Summary of food expen
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Table 4.1.142-Percent of households
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Table 4.1.144-Food consumption by e
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Table 4.1.149-Results of regression
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Table 4.1.152-Value of household as
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Table 4.1.156-Value of household as
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Table 4.1.160-Housing characteristi
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Table 4.1.162-Housing characteristi
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Table 4.1.165-Main source of water
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Table 4.1.170-Source of information
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Table 4.1.176-Source of information
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Table 4.1.181-Regression for percei
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Table 4.2.5-Change in number of veh
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Table 4.2.12-Availability and sourc
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Table 4.2.21-Number of GFs per vill
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Table 4.2.30-Percentage of villages
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Table 4.2.34-Distribution of villag
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Table 4.3.1-Distribution of GVs by
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Table 4.3.9-Number of each type of
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Table 4.3.12-Percentage of secretar
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Table 4.3.19-Distribution of GVs by
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Table 4.3.24-Percentage of inputs s
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Table 4.3.32-Average value of curre
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Table 4.3.40-Percentage of GVs in w
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CHAPTER 5 - RESULTS FROM THE MALAWI
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The weights are used to calculate a
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On average, around 20 percent of th
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agricultural work. Other less commo
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5.1.4 Time allocation In Malawi, as
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attributed it to the fact that fert
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insignificant. The coefficient on t
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As in the results from the previous
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most important sources of input on
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applied for credit compared to 20 p
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less than 1 mt per ha which are fai
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5.1.9 Agricultural marketing Market
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Households that belong to a club al
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most important contractors are the
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indicates that the extent of povert
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wheat, and fruits and nuts, a highe
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Surprisingly, the education of the
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Housing characteristics The overwhe
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It was also important to find out w
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Surprisingly, tobacco growers are m
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Over three-quarter of the EPAs repo
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The changes in the number and types
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5.2.11 Storage Facilities On averag
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Table 5.2 - Household characteristi
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Table 5.7 - Percentage of household
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Table 5.12 - Farm labor use and all
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Table 5.15 - Determinants of the de
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Table 5.17 - Sources of fertilizer
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Table 5.22 - Access and use of cred
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Table 5.25 - Percent of households
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Table 5.34 - Crop disposal by type
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Table 5.38 - Determinants of Market
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Table 5.42 - Summary of expenditure
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Table 5.45 - Food consumption by so
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Table 5.51 - Food consumption by ex
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Table 5.56 - Determinants of per ca
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Table 5.59 Percent of households ow
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Table 5.62 - Characteristics of the
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Table 5.68 - Determinants of percei
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Table 5.71 - Average yields per cro
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Table 5.77 - Changes in the availab
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Figure 5.1 Distribution of househol
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Figure 5.7 - Percentage of Househol
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CHAPTER 6 - SUMMARY, CONCLUSIONS AN
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Fertilizer Half of the far
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Regression analysis indicates that
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Among those seeing improvement, the
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Agricultural markets Three quart
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The economic reforms have boosted p
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department. The farms with very lit
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Strengthen the extension service by
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The most time-consuming agricultura
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Most common means of transport to t
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Small farmers in Malawi are mainly
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households have less assets and les
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Place more serious efforts to impro
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REFERENCES Ahoyo Adjovi, N.R. and F
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