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

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This would not be surprising in light of increases in cotton production. As discussed in Chapter 2, increases in cotton prices and cotton output have resulted in an additional 63 thousand FCFA of gross cotton revenue per farm household in Benin. crease in gross revenue from cotton of 63 thousand FCFA per farm household in Bénin. The level of poverty in different household groups can be summarized as follows: The incidence of poverty is highest in Atacora (42 percent) and lowest in Atlantique (6 percent) and Zou (16 percent). This is what we would expect given the patterns in average per capita expenditure discussed earlier. The poverty gap measure shows roughly the same order. Male- and female-headed households have the same incidence of poverty (21 percent). On the other hand, the poverty gap for male-headed households is larger, suggesting that the depth of poverty among poor male-headed households is greater. The poverty rate is higher among households with many members compared to those with few members. In fact, the incidence of poverty is twice as great among households with more than 10 members compared to households with 5 or fewer members. Larger farms are associated with lower levels of poverty. Although the smallest farms do not fit well in the pattern, across the next four farm size categories, the incidence of poverty falls steadily from 30 percent to 11 percent. The poverty gap falls in a similar fashion. Similarly, poverty is lower among farm households that sell a larger share of their output. The poverty rate is around 30 percent for those selling less than half of their crop output (in value terms) and just 12 percent for those selling more than three-quarters of the total. Finally, the poverty rate among cotton farmers is essentially the same as that of other farmers in Bénin. Given the large increases in cotton production and the increases in the real price of cotton, it is quite possible that cotton farmers were poorer than other farmers a decade ago, but have now achieved parity. It should be recognized that the ECVR poverty line is relatively low. If we adopt the World Bank’s international poverty line of US$ 1 per person per day, then almost all the 95
farm households in Benin (95 percent) would be classified as poor. Thus, the poverty rate among rural households appears to be declining, but these households remain quite poor. 4.1.9 Household assets and housing characteristics Household assets Household assets are defined as goods that last more than a year or two and that directly contribute to the well-being of the household. Thus, this definition includes furniture, bicycles, radios, and electrical appliances, but excludes farm equipment which only contributes to well-being indirectly and consumables such as soap and fuel. Ownership of household assets is a reflection of income over recent years, as well as being a measure of the household's ability to cope with future changes in income. Families with many assets have the option of selling them if their income falls temporarily. Finally, ownership of household assets provides an intuitive picture of the household's standard of living. According to the IFPRI-LARES Small Farm Survey, a majority of farm households in Bénin own each of the following assets: chairs, tables, beds, bicycles, and radio/CD players. On the other hand, for each of these items, 33-42 percent of the households do not own one. Motorbikes are owned by 26 percent and sewing machines and televisions/video cassette recorders (VCRs) by just 5-6 percent of the households. Barely 1 percent of Bénin farm households own a car or truck (see Table 4.1.151). The average value of household assets is 226 thousand FCFA. Motorbikes are the largest component, accounting for more than one third of the total (see Table 4.1.152). Looking at the pattern of asset ownership across departments, Zou has the highest frequency of many assets, including chairs, radio/CD players, bicycles, and vehicles. Atlantique and Ouémé are leaders in ownership of some other items. Atacora appears to the have the lowest frequency of ownership for various assets, including tables, beds, and television/VCRs, while Mono has the fewest of other items. The value of these household assets is highest in Zou (422 thousand FCFA) and lowest in Mono (94 thousand FCFA) and Atacora (120 thousand FCFA) (see Tables 4.1.153 and 4.1.154). 96
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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
Page 52 and 53: Somewhat surprisingly, the relation
Page 54 and 55: It is no more common among richer h
Page 56 and 57: production, and women actually spen
Page 58 and 59: Seed use by crop Although only 18 p
Page 60 and 61: Looking at the results by departmen
Page 62 and 63: Ouémé presents an unusual case: j
Page 64 and 65: Market prices have significant effe
Page 66 and 67: policies of SONAPRA to discourage
Page 68 and 69: crops are responsible for this incr
Page 70 and 71: Respondents were asked whether the
Page 72 and 73: Female-headed households, not surpr
Page 74 and 75: households are not considered credi
Page 76 and 77: In almost every category of agricul
Page 78 and 79: This discussion implies that farms
Page 80 and 81: eturns per hectare and labor-intens
Page 82 and 83: farm household and tends to be smal
Page 84 and 85: Surprisingly, the value of sales as
Page 86 and 87: 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 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 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
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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 4.1.102-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
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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 4.1.144-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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