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

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Table 4.3.40-Percentage of GVs in which members didn`t buy all they ordered Fertilizer Pesticide Herbicide Cotton seed Atacora 29% 6% 0% 0% Borgou 6% 7% 2% 4% Mono/Ouémé 20% 20% 22% 15% Zou 2% 6% 0% 0% Total 9% 8% 7% 4% Source: IFPRI-LARES Survey of Groupements Villageois Table 4.3.41-Percentage of members not buying all they ordered Percentage among GVs with problem Percentage across all GVs Atacora 37% 12% Borgou 24% 4% Mono/Ouémé 58% 15% Zou 6% 1% Total 29% 5% Source: IFPRI-LARES Survey of Groupements Villageois Table 4.3.42-Problem of members not repaying credits from GV Pct. of GVs reporting Pct. of members among Pct. of members problems of repayment GVs with problem across all GVs Atacora 59% 2% 1% Borgou 46% 6% 3% Mono/Ouémé 55% 52% 23% Zou 59% 6% 2% Total 52% 10% 5% Source: IFPRI-LARES Survey of Groupements Villageois Table 4.3.43-Frequency of sanctions against members not paying debts to GV <strong>Market</strong> No more credit Removed from GV Relatives reimburse members reimburse GV members reimburse Always 3% 30% 4% 18% Generally 21% 10% 18% 18% 12% Sometimes 39% 17% 46% 19% 35% Never 37% 74% 6% 59% 35% Total 100% 100% 100% 100% 100% Source: IFPRI-LARES Survey of Groupements Villageois 229
Table 4.3.44-Opinion of changes in input marketing since 1992 <strong>In</strong>put availability Timing of delivery Delivery location Fertilizer quality Pesticide/ herbicide quality Member repayment Has improved 79% 69% 64% 64% 26% 53% Has worsened 15% 22% 13% 21% 67% 24% No change 5% 8% 22% 14% 6% 6% Was never a problem 1% 1% 15% Doesn`t know 1% 1% 1% Total 100% 100% 100% 100% 100% 100% Source: IFPRI-LARES Survey of Groupements Villageois Table 4.3.45-Average delay in payment (months) 1st cotton delivery 2nd cotton delivery 3rd cotton delivery 4th cotton delivery Atacora 0.8 0.9 1.4 2 Borgou 0.6 0.9 1.3 1.5 Mono/Ouémé 3.2 3.1 3 2.6 Zou 1.3 2 1.8 2 Total 1.1 1.2 1.5 1.7 Source: IFPRI-LARES Survey of Groupements Villageois Table 4.3.46-Problems in cotton marketing (percent of GVs citing) Problems in cotton grading Problems in cotton weighing Problems with cotton theft Atacora 65% 94% 6% Borgou 76% 94% 22% Mono/Ouémé 95% 95% 0% Zou 31% 57% 6% Total 65% 85% 14% Source: IFPRI-LARES Survey of Groupements Villageois Table 4.3.47-Opinion of changes in cotton marketing since 1992 Cotton extension Cotton classification Cotton weighing Timing of payment Cotton theft Has improved 26% 61% 78% 19% 23% Has worsened 68% 24% 11% 73% 5% No change 6% 14% 11% 7% 6% Was never a problem 1% 62% Doesn`t know 1% 3% Total 100% 100% 100% 100% 100% Source: IFPRI-LARES Survey of Groupements Villageois 230
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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
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it is clear that virtually all grow
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production to total expenditure is
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a significant number of household (
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non-food spending. These are follow
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Larger farms are associated with hi
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This would not be surprising in lig
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Female-headed households appear to
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poorest expenditure category to jus
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headed household were more likely t
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Households in every expenditure cat
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An important result of this analysi
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oad network, although those citing
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questions posed by the IFPRI-LARES
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With regard to cotton marketing, al
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Village leaders were asked to ident
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Marketing patterns Village leaders
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4.3: Results of the Bénin Survey o
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4.3.2 Survey methods At the time of
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officers have CM2 certificates. Thi
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Suppliers The GV representatives we
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Cotton area per GV ranges from 145
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The largest cost items are schools
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members and 10 percent of the membe
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Table 4.1.1-Description of sample o
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Table 4.1.7-Age, education, and lit
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Table 4.1.13-Ethnic background of h
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Table 4.1.19-Importance of each sou
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Table 4.1.25-Number of plots and ar
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Table 4.1.31-Land tenure by expendi
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Table 4.1.37-Change in labor alloca
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Table 4.1.42-Seed use by sex of hea
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Table 4.1.47-Perceived change in av
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Table 4.1.54-Share of producers of
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Table 4.1.59-Fertilizer use by farm
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Table 4.1.64-Characteristics of fer
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Table 4.1.69-Change in fertilizer a
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Table 4.1.75-Allocation of labor by
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Table 4.1.82-Allocation of labor by
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Table 4.1.89-Change in credit avail
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Table 4.1.94-Percent of households
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Table 4.1.98-Percent of households
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Table 4.1.102-Area allocation by cr
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Table 4.1.106-Area allocation by cr
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Table 4.1.110-Marketed share of out
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Table 4.1.114-Marketed share of out
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Table 4.1.117-Regression for market
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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
Page 192 and 193: Table 4.1.142-Percent of households
Page 194 and 195: Table 4.1.144-Food consumption by e
Page 196 and 197: Table 4.1.149-Results of regression
Page 198 and 199: Table 4.1.152-Value of household as
Page 200 and 201: Table 4.1.156-Value of household as
Page 202 and 203: Table 4.1.160-Housing characteristi
Page 204 and 205: Table 4.1.162-Housing characteristi
Page 206 and 207: Table 4.1.165-Main source of water
Page 208 and 209: Table 4.1.170-Source of information
Page 210 and 211: Table 4.1.176-Source of information
Page 212 and 213: Table 4.1.181-Regression for percei
Page 214 and 215: Table 4.2.5-Change in number of veh
Page 216 and 217: Table 4.2.12-Availability and sourc
Page 218 and 219: Table 4.2.21-Number of GFs per vill
Page 220 and 221: Table 4.2.30-Percentage of villages
Page 222 and 223: Table 4.2.34-Distribution of villag
Page 224 and 225: Table 4.3.1-Distribution of GVs by
Page 226 and 227: Table 4.3.9-Number of each type of
Page 228 and 229: Table 4.3.12-Percentage of secretar
Page 230 and 231: Table 4.3.19-Distribution of GVs by
Page 232 and 233: Table 4.3.24-Percentage of inputs s
Page 234 and 235: Table 4.3.32-Average value of curre
Page 238 and 239: CHAPTER 5 - RESULTS FROM THE MALAWI
Page 240 and 241: The weights are used to calculate a
Page 242 and 243: On average, around 20 percent of th
Page 244 and 245: agricultural work. Other less commo
Page 246 and 247: 5.1.4 Time allocation In Malawi, as
Page 248 and 249: attributed it to the fact that fert
Page 250 and 251: insignificant. The coefficient on t
Page 252 and 253: As in the results from the previous
Page 254 and 255: most important sources of input on
Page 256 and 257: applied for credit compared to 20 p
Page 258 and 259: less than 1 mt per ha which are fai
Page 260 and 261: 5.1.9 Agricultural marketing Market
Page 262 and 263: Households that belong to a club al
Page 264 and 265: most important contractors are the
Page 266 and 267: indicates that the extent of povert
Page 268 and 269: wheat, and fruits and nuts, a highe
Page 270 and 271: Surprisingly, the education of the
Page 272 and 273: Housing characteristics The overwhe
Page 274 and 275: It was also important to find out w
Page 276 and 277: Surprisingly, tobacco growers are m
Page 278 and 279: Over three-quarter of the EPAs repo
Page 280 and 281: The changes in the number and types
Page 282 and 283: 5.2.11 Storage Facilities On averag
Page 284 and 285: 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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