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

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Surprisingly, the value of sales as a percentage of output (the aggregate market surplus) is more-orless constant across farm-size categories. This is due to the influence of a number of small farms that produce high-value commodities, particularly vegetables, for the market. “Other vegetables” account for one third of the value of output in the smallest farm-size category, and these vegetables are produced almost exclusively for sale. The average proportion sold (the average market surplus), on the other hand, rises from 42 percent in the smallest farm-size category to 59 percent in the largest (see Table 4.1.113). The difference in marketed surplus between cotton growers and other farmers is less than one might expect. The aggregate market surplus ratio is actually the same for these two groups, and the average market surplus ratio is only moderately higher for cotton growers (55 percent) than for other farmers (46 percent). Although cotton sales obviously contribute to the marketed surplus, this is partly offset by two factors. First, cotton growers sell a smaller proportion of their maize output than other farmers do (36 percent compared to 52 percent). Second, they also grow crops such as yams and sorghum/millet, only a small portion of which is sold (see Table 4.1.114). Finally, it is useful to examine the distribution of farm households by the level of market surplus. Barely one-quarter (27 percent) of the farms in Bénin sell 30 percent or less of their harvest. At the other extreme, one farm in six (16 percent) sells more than 80 percent of its output. <strong>In</strong> biggest concentration of farms occurs in the middle: 39 percent of the farm households in Bénin sell 51-90 percent of their crop production. These results highlight the fact that the high aggregate market surplus ratio is not due to the influence of a small number of highly commercial farmers. Rather, over half of the farmers in Bénin sell the majority of their crop production (see Table 4.1.115). Regression analysis of marketed surplus This section uses regression analysis to examine the household characteristics that are associated with a strong market orientation, as measured by the share of crop production that is sold. The value of R 2 is 0.47, suggesting that close to one-half of the variation in marketed surplus is “explained” by the 34 independent variables included in Table 4.1.117. The analysis produced the following results: Larger households generate smaller marketed surpluses. This is expected, since larger households have greater consumption needs, reducing the portion of the total output that can be 77
sold on the market. Nonetheless, the effect is rather small: each additional household member is associated with a reduction in the market surplus ratio of 0.4 percentage points. Oddly, marketed surplus is positively associated with literacy but negatively associated with education. The coefficients imply that a head with three years of education who is literate will market more than an illiterate head with no education, but household heads with more than 10 years of education will have a smaller market surplus. Perhaps some basic education is necessary to take advantage of market opportunities, but highly educated household heads have better employment options outside agriculture and only produce for their household needs. Larger farms sell a larger percentage of their output, though the effect is modest. Each additional hectare in the main season raises the marketed surplus by 1.1 percentage points and each extra hectare in the second season increases marketed surplus by 2.5 percentage points. Growing cotton is associated with a larger marketed surplus. Given two otherwise identical farms in the same department, the one growing cotton will have a marketed surplus 16 percentage points higher than the one that is not. Membership in a groupement villageois (GV) is associated with another 5 percentage points in the marketed surplus ratio. Irrigation is associated with a 29 percentage point increase in the marketed surplus ratio. Irrigation increases production, allowing more to be sold, but it also allows the cultivation of crops such as vegetables and rice that are often commercialized. Finally, the departmental variables have a strong effect on the level of marketed surplus. Other factors equal, a farm in Atacora will have a market surplus ration 51 percentage points below that of those in Atlantique, while the corresponding figure for Borgou is 44 percentage points. Farms in Mono, Ouémé, and Zou also have significantly smaller market surplus rations, though the difference is somewhat less (22-35 percent). Since distance to road and sous-prefecture have already been controlled, these regional results suggest that access to major urban centers may be more important than access to a road or a provincial capital in terms of stimulating large market surpluses. Some of the statistically insignificant results are also interesting. Poor households are no more subsistence-oriented that rich households, after controlling for farm size and other factors. Furthermore, female-headed households are just as market oriented as male-headed households. 78
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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
Page 33 and 34: the reduction of its operations in
Page 35 and 36: crops is also difficult because tob
Page 37 and 38: Table 3.1 CROP 1982/83 1983/84 1984
Page 40 and 41: CHAPTER 4: RESULTS OF THE BÉNIN SM
Page 42 and 43: where W v is the weight for a house
Page 44 and 45: heads. This suggests that some of t
Page 46 and 47: And school attendance is much highe
Page 48 and 49: Crop production is the main activit
Page 50 and 51: (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 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 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
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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 4.1.102-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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