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

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policies of SONAPRA to discourage “leakage” of fertilizer to non-cotton fields. Alternatively, some cotton farmers may only be applying their “excess” fertilizer to maize, lowering the average below that of non-cotton farmers who overcome obstacles to fertilize maize. Bottom-land plots (bas-fond), which are generally marshy, receive higher applications of fertilizer, though irrigated ones do not, other things equal. Fertilizer purchase patterns The IFPRI-LARES Small Farmer Survey also collected information on the characteristics of fertilizer purchases. Nationally, 88 percent of the fertilizer used by farm households is obtained through the official SONAPRA distribution channel, another 8 percent is distributed by CARDER, and just 6 percent is obtained from farmers and traders 9 . About 86 percent is purchased on credit, and of these transactions, almost all the credit (93 percent) is provided by the USPP through the groupements villageois (GVs) (see Table 4.1.61). These averages hide dramatic regional differences in purchase patterns, however. In Atacora, Borgou, and Zou, over 90 percent of the fertilizer is obtained from SONAPRA through a GV, 89- 98 percent is purchased on credit, and the credit is provided by the USPP through the GV in over 90 percent of the cases. At the other extreme, farmers in Atlantique and Ouémé obtain almost all their fertilizer (89-92 percent) from CARDER, and they almost always pay cash. Farmers in Mono are in an intermediate position because, as a marginal cotton producer, Mono has some access to fertilizer through the official SONAPRA channel (see Table 4.1.61). The patterns in fertilizer purchases is fairly similar between male- and female-headed households. In fact, female-headed households are somewhat more likely to be able to buy fertilizer on credit from the GV than male-headed households (see Table 4.1.62). This is related to the fact that the percentage of cotton growers is somewhat higher among female-headed households (40 percent) than among male-headed households (35 percent). Similarly, the patterns of fertilizer purchases do not vary markedly between poorer and richer farm households. The percentage of farmers getting fertilizer from the official SONAPRA channel and the percentage buying on credit is around 90 percent in the first three or four expenditure categories, but drops to 79 percent in the highest expenditure category (see Table 4.1.63). 9 It should be noted that some of the fertilizer purchased from farmers and traders may have originally been distributed through the official Sonapra channel and then resold. 59
Finally, if we divided the farm households into those that grow cotton and those that do not, we see sharp differences in the purchasing patterns. Among cotton growers (35 percent of all Bénin farmers), 98 percent of the fertilizer is obtained from SONAPRA through a GV and 97 percent is purchased on credit. In contrast, among non-cotton growers, 80 percent is purchased on a cash basis and the suppliers of fertilizer are much more varied, including CARDER (44 percent), traders (22 percent), GV/SONAPRA (21 percent), and other farmers (12 percent). Similarly, among the 20 percent of non-cotton growers that were able to buy fertilizer on credit, the sources of credit were varied, including the USPP/GVs, other formal financial institutions, and informal lenders (see Table 4.1.64). It may be surprising that non-cotton growers are buying fertilizer from GVs and even purchasing on credit. It should be recalled, however, that the percentage of households reporting GV membership (42 percent) is higher than the percentage growing cotton (35 percent). Changes in the availability of fertilizer Respondents were asked whether the availability of fertilizer was better or worse than it had been in 1992. Overall, the proportion of households reporting better availability (21 percent) was approximately equal to the proportion saying that fertilizer was less available (20 percent). The response was generally positive in Borgou, Atacora, Zou, and Mono and negative in Atlantique and Ouémé (see Table 4.1.65). This may reflect the difference between farmers in the cotton zone and those outside it. Fertilizer prices doubled following the 1994 devaluation of the CFA franc, but for cotton growers the higher price of cotton more than offset this increase. In addition, the reduction in fertilizer subsidies in Nigeria probably affected the availability of fertilizer in neighboring Ouémé. Although male-headed households were neutral on the change in fertilizer availability, femaleheaded households were more likely to report improvement (33 percent) than deterioration (7 percent) (see Table 4.1.66). The reasons for this difference hard difficult to determine, but these results do not support the common belief that female-headed households are more adversely affected by reforms. Poor households are no more and no less likely to report improved availability of fertilizer than richer households. In other words, there is no link between the household’s expenditure category and its view of the changes in fertilizer availability since 1992 (see Table 4.1.67). Changes in fertilizer use Aggregate statistics indicate that national fertilizer use has increased dramatically over the past decade, but they do not tell us which households and which 60
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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.
Page 16 and 17: Under pressure from the World Bank
Page 18 and 19: anking system has been restored to
Page 20 and 21: Fertilizer can be imported outside
Page 22 and 23: particularly urban wage-earners. On
Page 24 and 25: Soulé (1996) describes the evoluti
Page 26 and 27: led to a more sustainable agricultu
Page 28: Table 2.4 - Gross farm revenue from
Page 31 and 32: 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 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 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
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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 4.1.102-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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