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

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Table 4.1.1-Description of sample of Bénin Small Farmer Survey Number of Percent of Number of villages in sample total households in sample Percent of total Sum of Percent of weights total Department Atacora 15 15% 135 15% 62,189 13% Atlantique 10 10% 90 10% 60,806 13% Borgou 27 27% 242 27% 74,908 16% Mono 10 10% 90 10% 86,923 18% Ouémé 19 19% 171 19% 85,194 18% Zou 19 19% 171 19% 104,944 22% Total 100 100% 899 100% 474,964 100% Table 4.1.2-Household characteristics by department Department Atacora Atlantique Borgou Mono Ouémé Zou Total Household size 8.8 7.6 11.3 7.4 8.4 9.1 8.8 Children under 15 yrs 4.2 3.5 5.7 3.2 4.3 4.4 4.2 Adults 15-65 yrs 4.3 3.9 5.4 3.9 4.0 4.5 4.3 Adults over 65 yrs .4 .2 .2 .2 .1 .2 .2 Dependency ratio (%) 48% 46% 50% 45% 50% 49% 48% Femaled headed (%) 0% 7% 2% 2% 3% 12% 5% Polygamous (%) 30% 42% 29% 31% 39% 45% 36% Source: IFPRI/LARES Small Farmer Survey. Table 4.1.3-Household characteristics by sex of head Sex of household head Male Female Total Household size 8.9 6.4 8.8 Children under 15 yrs 4.3 3.1 4.2 Adults 15-65 yrs 4.4 3.1 4.3 Adults over 65 yrs .2 .2 .2 Dependency ratio (%) 48% 47% 48% Femaled headed (%) 0% 100% 5% Polygamous (%) 38% 5% 36% Source: IFPRI/LARES Small Farmer Survey. 131
Table 4.1.4-Household characteristics by expenditure category Expenditure category (quintile) Poorest 2 3 4 Richest Total Household size 9.9 10.8 8.4 7.6 7.2 8.8 Children under 15 yrs 5.2 5.6 3.9 3.3 3.2 4.2 Adults 15-65 yrs 4.4 5.0 4.4 4.0 3.9 4.3 Adults over 65 yrs .3 .2 .2 .2 .1 .2 Dependency ratio (%) 55% 51% 46% 44% 44% 48% Femaled headed (%) 6% 7% 3% 6% 3% 5% Polygamous (%) 35% 48% 38% 28% 33% 36% Source: IFPRI/LARES Small Farmer Survey. Table 4.1.5-Years of education and literacy of adults (15 yrs and over) Department Atacora Atlantique Borgou Mono Ouémé Zou Total Education (years) .7 1.2 .6 2.0 2.5 1.5 1.4 Can read 3% 4% 0% 4% 4% 2% 3% Can write 0% 0% 0% 0% 2% 1% Both 8% 12% 8% 21% 29% 17% 16% Neither 89% 83% 92% 75% 67% 78% 81% Total 100% 100% 100% 100% 100% 100% 100% Source: IFPRI/LARES Small Farmer Survey. Table 4.1.6-Age, education, and literacy of head of household by department Department Atacora Atlantique Borgou Mono Ouémé Zou Total Age (years) 48.9 47.0 47.4 46.2 42.0 47.1 46.3 Education (years) .6 1.7 1.2 3.6 3.9 1.3 2.1 Literacy Can read 5% 9% 0% 4% 4% 2% 4% Can write 1% 1% 0% 0% Both 8% 14% 14% 33% 44% 16% 23% Neither 87% 77% 86% 62% 52% 82% 73% Total 100% 100% 100% 100% 100% 100% 100% Source: IFPRI/LARES Small Farmer Survey. 132
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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
Page 88 and 89: Changes in crop marketing In this s
Page 90 and 91: 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 140 and 141: Table 4.1.7-Age, education, and lit
Page 142 and 143: Table 4.1.13-Ethnic background of h
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
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Table 4.1.135-Main reason for stori
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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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