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

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Table 4.1.114-<strong>Market</strong>ed share of output for cotton growers and other farmers Type of farm Cotton growers Other farmers Average Maize 64% 59% 64% Sorghum/millet 42% 46% 48% Rice 64% 59% 64% Cowpeas 42% 46% 48% Groundnuts 64% 59% 64% Manioc 42% 46% 48% Yams 64% 59% 64% Sweet potatoes 42% 46% 48% Tomatoes 64% 59% 64% Okra 42% 46% 48% Hot pepper 64% 59% 64% Other vegetables 42% 46% 48% Cotton 64% 59% 64% Other crops 42% 46% 48% Sales as % of output 65% 65% 65% Average % sold 55% 46% 50% Source: IFPRI/LARES Small Farmer Survey. Table 4.1.115-Distribution of households by marketed share of crop production <strong>Market</strong>ed share of output (%) Percentage of farm households 0-10 11% 11-20 7% 21-30 9% 31-40 8% 41-50 9% 51-60 12% 61-70 12% 71-80 15% 81-90 10% 91-100 6% Total 100% Source: IFPRI/LARES Small Farmer Survey. 173
Table 4.1.116-Descriptive statistics Variable Obs Mean Std. Dev Min Max lnexppc 899 11.42784 .5208458 9.759819 13.87848 mktsurp 899 49.925 26.79296 0 100 change 899 2.29366 .8537053 1 3 hhsize 899 8.958843 4.958792 1 40 under15p 899 .4508652 1922644 0 .8571429 over65p 899 .0328324 1050383 0 1 femhead 899 .0433815 2038278 0 1 agehead 899 46.42158 13.83281 0 95 age2 899 2346.097 1384.6 0 9025 edhead 899 1.69188 3.318916 0 19 lithead 899 .2313682 4219419 0 1 spouse 899 .8932147 309012 0 1 edsps 899 .3784946 1.499432 0 16 litsps 899 .6889816 3765098 0 1 fsize1 899 3.809033 4.097106 0 50.35997 fsize2 899 .8868974 1.594825 0 12.02479 cotton 899 .4393771 4965875 0 1 irrig 899 .0200222 1401542 0 1 basfond 899 .1290323 3354222 0 1 connect 899 .3303671 4706071 0 1 fon 899 .2013348 4012209 0 1 gv 899 .5116796 5001418 0 1 tontine 899 .5439377 .498343 0 1 coop 899 .2602892 .4390366 0 1 extcont 899 .1913237 .3935622 0 1 distroad 888 5.792925 13.21275 0 100 distsp 898 18.52171 17.64196 0 120 distpave 898 28.83536 32.98809 0 140 goodflor 899 .4404894 4967222 0 1 goodwall 899 .0678532 .2516338 0 1 goodroof 899 .6674082 .4714039 0 1 goodwatr 899 .1913237 .3935622 0 1 electric 899 .0378198 .1908664 0 1 chair 899 .5784205 .4940868 0 1 bed 899 .5951057 .4911448 0 1 table 899 .6040044 .4893357 0 1 radio 899 .5684093 .4955738 0 1 tv 899 .0444939 .2063044 0 1 bike 899 .7107898 .4536481 0 1 mbike 899 .2625139 .4402453 0 1 dpt1 899 .1501669 .3574337 0 1 dpt3 899 .269188 .4437847 0 1 dpt4 899 .1001112 .3003153 0 1 dpt5 899 .1902113 .3926863 0 1 dpt6 899 .1902113 .3926863 174
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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
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 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 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 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
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
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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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Impact Of Agricultural Market Reforms On Smallholder Farmers In ...

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