SKUAST Journal of Research 20(1): 9-18 (2018)
Research Paper
Marketable surplus and its determinants among small scale maize producers in the Ashanti and Northern regions of Ghana Richard Kwasi Bannor1*, Emmanuel Adjei-Addo2 and Helena Oppong-Kyeremeh1 1
Department of Agricultural Economics, Agribusiness and Extension, University of Energy and Natural Resources, Sunyani- Ghana; 2UN World Food Programme, Accra ,Ghana * e-mail:
[email protected] (Received April 19, 2017; accepted January 01, 2018)
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ABSTRACT The study estimated and analysed factors affecting marketable surplus of maize in Northern and Ashanti regions of Ghana. The data employed for this study was accessed from World Food Programme’s Purchase for Progress (P4P) Farmer Livelihood and Agricultural Production Baseline Survey conducted in 2011 in Northern and Ashanti Regions of Ghana. Descriptive statistics, Lorenz curve, Gini coefficient and Tobit regression were used in the analysis. The results indicate that unit price per kilogram for two seasons of production, total quantity of maize harvested per annum, quantity of maize harvested in the minor season, proportion of certified seeds used in production, total fertiliser used, and household size influence the amount of maize marketable surplus in Ghana. Key words: Ghana, maize, marketable surplus, marketed surplus
Maize (Zea mays) is the most important cereal crop in Sub-Saharan Africa (SSA) and an important staple food for more than 1.2 billion people in SSA and Latin America. All parts of the crop can be used for food and non-food products. Worldwide production of maize (Zea mays) is estimated to be 785 million tons, with Africa producing 6.5% and importing 28% of the required maize from countries outside the continent (Anonymous, 2013). Currently, in Ghana, maize (Zea mays) is the most important cereal crop and one of the major staple crops accounting for 55% grain output (MOFA, 2012; Bannor and Bentil, 2015). Additionally, it represents the second largest commodity crop in the country, after cocoa (ISSER, 2012). It is also the largest staple crop and the mainstay of the diet of the majority of Ghanaians, because it is the base for several traditional food preparations such as banku, kenkey, tuozafi etc. (Morris et al., 1999). Ghana produced a little over 1 million tonnes of maize on an area of approximately 1 million hectares in the year 2014 (FAOSTAT, 2016). The average maize yield for the same year was a little over 17 thousand kilogram per hectare. This level of yield was lower than 20 thousand kilogram per hectare and 55 thousand kilogram per hectare for the whole Africa and the world, respectively. The low level of yield and production can be attributed to traditional production methods and also production done under rain fed conditions (Armah, 2000). Maize in the country is produced in all the ten regions with Ashanti, Northern, Central, Brong-Ahafo and the Eastern Regions as the five major growing areas in Ghana (MOFA, 2012). Ashanti and Northern Regions alone contributed a little over 455 thousand metric tonnes which represents 24.35 percent of the total maize produced in 2010 ( MOFA, 2012). According to Agyare et al., (2014), the Ministry of Food and Agriculture of Ghana estimated the annual domestic deficit from 2007 to 2011 to be between 84,000 and 145,000 metric tons and was projected to reach 267,000 metric tons by 2015. These represented a shortfall in domestic production between 9% and 15% of total human consumption in the years under review (Armah, 2000). However, growth in population, per capita income and the production links from other related economic activities required annual maize output to grow by 2.6% between 2010 and 2015 (MIDA, 2007). Further, beyond these projected figures for household consumption, there is considerable unfulfilled demand for processed maize uses and for the growing animal feed sector. This calls for continuous efforts of generating sufficient marketable surplus through increasing total food production to meet increasing demand (Shah and Makwana, 2013). Thus, in order to feed about 27 million population, it is important to understand the latest pattern of marketable and marketed
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Marketable surplus and its determinants among small scale maize farmers
surplus of major food grains like maize as well as the variables affecting it, so as to formulate sound policies in respect of marketing, price analysis, import and export. Despite the importance of marketable and marketed surplus estimates there is little research on marketable and marketed surplus in the country especially on maize. This paucity of information on maize marketable and marketed surplus is due to less attention paid to the concept by researchers, government and many development partners in agriculture. There is therefore, the need to provide vital information that will give scholars and other stakeholders a better understanding of the actual determinants of maize marketable surplus in the country, hence this research. MATERIALS AND METHODS Sources of data and study area The data employed for this study was accessed from World Food Programme’s Purchase for Progress (P4P) Farmer Livelihood and Agricultural Production Baseline Survey conducted in 2011 in Northern and Ashanti Regions of Ghana. The Northern Region of Ghana falls in the Guinea-Savanna agro-ecological zone with only one cropping season in a year spanning between May and October. The Ashanti Region however, falls in the semi‐deciduous rainforest agro-ecological zone with two cropping, major and the minor, seasons. The major season spans between March to July whereas the minor season is between September and November.
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Estimation of marketable surplus To calculate the marketable surplus of maize among producers in the two selected regions of Ghana, the formula given below was used: MS = Marketable surplus in kilograms P = Total production of maize by a farmer in kilograms C = Total requirements of a farmer in kilograms MS = P-C…………………………………………………………….……………1 Where C = Total quantity consumed (kg) + Total quantity for seeds (kg) + Total quantity lost through spoilage (kg). Quantity consumed included the quantity consumed from own production and quantity bought from the market in a later period to meet farmers family and or farm requirements. Inequality of marketable surplus To assess marketable surplus inequality among maize producers in Ashanti region, Northern region and Ghana in general, the researchers adopted Lorenz curve and Gini coefficient. In this study, the element chosen to be measured in the context of the conventional understanding of inequality is the marketable surplus. Inequality represents only the value judgment of the absence of a homogeneous distribution of marketable surplus. Lorenz curve The Lorenz curve was the tool used to represent marketable surplus distributions; it tells us which proportion of total marketable surplus is in the hands of a given percentage of maize producers. The shape of the Lorenz curve is a good visual indicator of how much inequality of maize marketable surplus exists among producers (figure-1). The Lorenz curve is obtained as follows: The X-axis records the cumulative proportion of population ranked by maize marketable surplus. Its range is (0, 1). The Y-axis records the cumulative proportion of marketable surplus, for the proportion of producers. Y, as follows:
Fig. 1: Lorenz curve showing section A and B used in Gini-coefficient
Bannor et al.
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Since, A+B equals 0.5 (Area of equality triangle), the Gini - coefficient will be:
Where, k =1…………….is the position of each maize producer in the marketable surplus distribution i=1………...……is the position of each producer in the marketable surplus distribution p……………….. is the total number of maize producers in the distribution yi ………….…. is the marketable surplus of the ith maize producer in the distribution …….…..is the cumulated marketable surplus up to the kth maize producer ranges between 0, for k=0, and Y, for k = n, therefore the equation
ranges
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between 0 and 1.
The Gini-coefficient Gini-coefficient is by far the most widely used measure of inequality; the reason for this may be the fact that it is straight forward, easy to understand and not at all complicated to calculate (Melkamu and Bannor, 2015). Its value ranges from 0 to 1, (Although it is commonly multiplied by 100 in empirical studies) being 0 the value of perfect equality and 1 of maximum inequality (i.e. one individual holds the entire marketable surplus and the rest hold no marketable surplus). The Gini-coefficient was calculated as the ratio of the area between the Lorenz curve and the absolute equality line, divided over the total area under the 45o line. Factors affecting marketable surplus in Ghana To determine the factors affecting marketable surplus in Ashanti region, Northern Region and Ghana, Tobit regression model was used. This is because after calculation of marketable surplus of each maize producer, the researchers realised that not all producers had marketable surplus after meeting their requirements. Based on this, the researchers adopted Tobit model which was the best fit model for data from the field. The Tobit or censored normal regression model assumes that the observed dependent variables for observations j = 1,…, n satisfy: Where
is called a latent variable, the variable of primary interest which we did not actually observe
for all the observations. The latent variable
Where
is generated by the classical linear regression model:
denotes vector of regressors, possibly including 1 for the intercept, and
corresponding vector of parameters. The model errors
the
are assumed to be independently normally
distributed: . We only observe for those observations with positive quantity of marketable surplus because of the censoring. In this model, we assume that the error term is normally distributed with zero mean and constant (or homoscedastic) variance. The Tobit model uses the method of maximum likelihood (ML) for estimation (Gujarati, 2012). Following from the aforementioned discussions, the empirical model for quantifying the factors which influence marketable surplus in Ghana is specified as follows: = βo+ β1X1+ β2X2 + β3X3+ β4X4+ β5X5 + β6X6 + β7X7 + β8X8 + β9X9 +β10X10+β11X11+β12X12+ β13X14+ X15+ X16+Uj…………………..………………………………………………………….….…...…6
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Marketable surplus and its determinants among small scale maize farmers
= The total quantity of marketable surplus in kilograms X1…………. + X15= Independent variables explained in table 1. Uj = error term Table 1 shows the description of both dependent and independent variables used in the Tobit model regression Table 1: Description of variables used in the Tobit regression model
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S. No
Variable
Description
Measurement
Marketable surplus
The total quantity of maize to be sold after satisfying requirements
Kilogram (kg)
1 2 3 4 5 6 7 8
Unit price for two seasons Maize quantity harvested per annum Quantity harvested in the minor season Farm size Marketing cost Proportion of certified seeds used Quantity of fertiliser used Sold through farm gate
Price received per kg Total quantity harvested per annum Quantity harvested Farm size Cost of marketing of produce Proportion of certified seeds used for productions Quantity of fertiliser applied Farm gate as marketing outlet used by farmer
9
Intercropping of maize
Farmer intercropped maize with other crops
10
Household size
Number of people in household
11 12 13 14
Age Educational level Income Gender
Age of respondent Number of years of education Total income per annum Gender of the respondent
15
Off farm Job
Off farm job
Kilogram (kg) Kilogram (kg) Kilogram (kg) Acres Ghana Cedis (GH¢) Proportion Kilogram (kg) Dummy (1=Yes, 0=otherwise) Dummy (1=Yes, 0= otherwise) Number of people in the household Number of years Number of years Ghana Cedis (GH¢) Dummy (1=Female , 0=Male) Dummy (1=Yes, 0= otherwise)
Expected sign Response variable (+) (+) (+) (+) (-) (+) (+) (-/+) (-/+) (-) (-) (+) (+) (-) (+)
Source: Authors computation
RESULTS AND DISCUSSION Results in table-2 provide important characteristics of maize farmers sampled for the study. About 61 percent of the households were headed by males. In the Ashanti region and Northern region, the percentage of males heading households was about 62 and 60 percent, respectively. More than half, represented by about 57 percent of the household heads interviewed, had no formal education. In the Northern region, the results indicate a very high level of illiteracy constituting 84 percent of the respondents. Only 39 percent of the respondents in the Ashanti region had no formal education. Just a small proportion had attained a tertiary education with about 5 percent in the Ashanti region and 1 percent in the Northern region. Most of the households in the Ashanti region had household size ranging from 4 to 6 whereas, in the Northern region, households with household size of above 9 constituted the largest. This implies that, households in the Northern region had large household size as compared to the Ashanti region. With regards to age, about 10 percent of the household heads were aged 30 years or less whilst 16 percent were above 60 years. Households aged from 31 to 60 years represented about 74 percent. Specifically, 8 percent and 12 percent of the respondents in the Ashanti and the Northern regions, respectively were less than 30 years. Again, about 18 percent of the household heads in the Ashanti region were above age of 60 years with about 13 percent in the Northern region. Land ownership is an important factor for farm investment as land is considered the principal input in agricultural production. All the households in the Northern region at least owned some amount of land whereas, in the case of the Ashanti region, about 14 percent of the households did not own land. In both regions, majority of the households (41% in Ashanti and 57% in Northern region) owned between 2 to 2.5 hectares of land. In all, about 47 percent of the household heads owned between 2 and 2.5 hectares of land. Most of the households in the Ashanti region (about 65.0 %) cultivated an average of 2.01 hectares to 2.5 hectares per season. On the other hand, 9.5 percent in the Northern region cultivated between 2.01 hectares and 2.50 hectares. Specifically, the area of land allocated for maize in the Ashanti region was higher than in the Northern region. For the two seasons combined (major and minor). Based on the results from table-3, the total quantity of maize consumed was approximately 384,202.5kg which is represented by about 82.54 percent of the total production. The huge percentage of maize consumed by
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Bannor et al.
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Table 2: Household characteristics of sampled farmers farmers reaffirms that, maize is a major staple in the diets of Ashanti Northern Total Variable Ghanaians and also serves as a major Frequency % age Frequency % age Frequency % age food security crop in the country. In (N=414) (N=263) (N=677) addition, the P4P intervention mostly Gender of the FO member targeted small holder farmers Male 358 86.5 253 96.2 611 90.3 cultivating not more than 2.5 Female 56 13.5 10 3.8 66 9.7 hectares per season and for that Gender of the household head matter high proportion of the Male 258 62.3 157 59.7 415 61.3 produce are used for consumption. Female 256 37.7 106 40.3 262 38.7 The total quantity of maize lost Educational level through spoilage to total production None 163 39.4 221 84.0 384 56.7 was very high in Ashanti region Some Primary School 59 14.3 15 5.7 74 10.9 (7.55%) compared to Northern Completed Primary School 85 20.5 7 2.7 92 13.6 Some Secondary 29 4.3 2 0.8 31 4.6 region (0.97%). This could be due to Complete Secondary 56 8.3 15 2.2 71 10.5 long dry period in the Northern Tertiary (college/univ) 22 5.3 3 1.1 25 3.7 region of Ghana, which provides Household size opportunity for farmers in the said 1–3 66 15.9 7 2.7 73 10.8 region to access long uninterrupted 4–6 205 49.5 73 27.8 278 41.1 dry period for drying maize thereby, 7–9 103 24.9 86 32.7 189 27.9 reducing post-harvest losses. In Above 9 40 9.7 97 36.9 137 20.2 addition, there are a lot of nonAge (years) governmental organisations in the 30 or less 34 8.2 32 12.2 66 9.7 Northern region educating farmers 31 – 40 97 23.4 76 28.9 173 25.6 on how to reduce post-harvest losses 41 – 50 109 26.3 67 25.5 176 26.0 in grains (maize, rice) compared to 51 – 60 100 24.2 53 20.2 153 22.6 the Ashanti region.The differences Above 60 74 17.9 35 13.3 109 16.1 can also be linked to the large Owned land (ha) quantity of maize produced in the None 57 13.8 0 0.0 57 8.4 Ashanti region compared to Northern 0.01 – 2.00 88 21.3 39 14.8 127 18.8 region. Thus the larger the quantity 2.01 – 4.00 137 33.1 129 49.0 266 39.3 of maize harvested or produced, the 4.01 – 6.00 85 20.5 57 21.7 142 21.0 larger the quantity lost through 6.01 – 8.00 21 5.1 17 6.5 38 5.6 spoilage. It is a very worrying Above 8.00 26 6.3 21 8.0 47 6.9 situation because even farmers who Total area cultivated (ha) are commercially oriented like 0.50 or less 5 1.2 2 0.8 7 1.0 farmers in the Ashanti region are still 0.51 – 1.00 38 9.2 11 4.2 49 7.2 battling with the problem of post1.01 – 1.50 71 17.1 25 9.5 96 14.2 harvest losses in the country. The 1.51 – 2.00 131 31.6 75 28.5 206 30.4 results from table 4 show marketable 2.01 – 2.50 169 40.8 150 57.0 319 47.1 and marketed surplus among maize Area cultivated for maize (ha) producers interviewed in the country. 0.50 or less 10 2.4 33 12.5 43 6.4 From the results, the percentage of 0.51 – 1.00 25 6.0 128 48.7 153 22.6 marketable surplus (89.04%) to total 1.01 – 1.50 33 8.0 59 22.4 92 13.6 maize production in the Ashanti 1.51 – 2.00 77 18.6 18 6.8 95 14.0 region is higher than the total 2.01 – 2.50 269 65.0 25 9.5 294 43.43 percentage of marketed surplus NB: Small scale maize producer: = or < 2.5 hectares of maize per annum; Source: Authors computation based on WFP field data, 2011 (7.72%) to the total maize production. This is because majority of the farmers in the Ashanti region are commercial farmers hence their better retention capacity. They retain extra produce in the hope that, they would get higher price in the later period. On the contrary maize pro ducers in the Northern region of Ghana had less marketable surplus which is represented by 28.37 percent to marketed surplus represented by 65.75 percent. This is because; most of the farmers in the Northern region of Ghana are small and marginal farmers whose need for cash is more pressing and immediate, resulting in distress sales. They then retain smaller quantity of their total production than their actual requirements for family and farm needs. They buy
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Marketable surplus and its determinants among small scale maize farmers
Table 3: Total requirements of maize among sampled farmers in Ghana Ashanti region Variable Total quantity consumed (kg) Total quantity for seeds (kg) Total quantity lost through spoilage (kg) Total requirement (kg)
Sum 141873.50
maize from the market in a later period to meet their family and farm requirements. In addition, most of the farmers sampled from the Northern region of Ghana produce rice which serves as a substitute for maize hence easily sell maize to meet immediate cash demands. Also, during the lean period, maize prices soar high in the region hence farmers’ cash on the high prices by selling more than their marketable surplus and then later buy maize
Northern region
% of Sum total 70.41 242329.00
Two regions combined % of Sum % of total total 91.80 384202.50 82.54
22.04
19082.93
7.23
63493.48
13.64
7.55
2562.28
0.97
17775.17
3.82
100.00 465471.15
100.00
44410.54 15212.89
201496.93 100.00 263974.21
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Source: Authors computation based on WFP field data, 2011
Table 4: Total marketable surplus of maize among sample farmers in Ghana from the market to meet family needs when the Regions Total Total Marketable Marketed % of total production Marketable Marketed production requirement surplus surplus maize prices tumble due to surplus surplus (kg) (kg) (kg) (kg) bumper harvest. Generally, Ashanti 1838159.40 201496.93 1636662.47 141873.50 89.04 7.72 the marketable surplus Northern 368549.00 263974.21 104574.78 242329.00 28.37 65.75 (78.91%) to total All regions 2206708.40 465471.15 1741237.25 384202.50 78.91 17.41 production and marketed Source: Authors computation based on WFP field data, 2011 surplus to total production (17.41%) in the country indicates maize producers in the country do not sell under distress sales and are commercially oriented.
Cropping pattern of respondents Results in table-5 show total land size in hectares of various crops produced by sampled maize producers. Out of the total land size of 2004.38 hectares farmed by sample maize producers in the Ashanti region, 1395.69 hectares representing 71.45percent of the total land size was under maize whereas, 270.97 hectares represented by 44.52 was allocated to maize farming in the Northern region. Cumulatively, about 63.27 percent of the total area sown was allocated to maize in the two regions. This is followed by rice with total land size of 277.97 hectares representing 13.87 percent. Table 5: Cropping pattern adopted by sampled producers Crop
Maize
Ghana Land size in hectares Mean Sum 1.87 1268.14
% of Gross Area 63.27
Ashanti Land size in hectares Mean Sum 2.41 997.17
% of Gross Area 71.45
Northern Land size in hectares % of Gross Area Mean Sum 1.03 270.97 44.52
Rice
0.91
277.97
13.87
0.75
45.14
3.23
0.95
232.83
38.25
Cowpea
1.18
239.24
11.94
1.22
236.00
16.91
0.40
3.24
0.53
Groundnut
0.66
90.26
4.50
0.71
30.36
2.18
0.64
59.90
9.84
Yam/Sweet Potato
0.50
60.05
3.00
0.54
47.77
3.42
0.40
12.29
2.02
Other crops
0.63
68.73
3.43
0.63
39.26
2.81
0.56
29.47
4.84
Gross Area Sown
1.29
2004.38
100.00
1.61
1395.69
100.00
0.89
608.70
100.00
In this study the shape of the Lorenz curve which is mathematically explained by Gini coefficient was used in the identification of inequality of marketable surplus among maize producers. Zero (0) means, perfect equality of marketable surplus distribution between farmers whereas one (1) represents perfect inequality of marketable surplus between farmers. The Lorenz curve in figure 2 clearly shows that, there is less marketable surplus inequality among maize producers in the Ashanti region. The Gini coefficient value of marketable surplus inequality is 0.37. The Gini value confirms the Lorenz curve depicted in figure. From figure 3, the Lorenz curve clearly shows that, there is high marketable surplus inequality among maize producers in the Northern region. This is supported by the Gini coefficient value of marketable surplus as 0.67. The high inequality among farmers interviewed can be attributed to differences in the commercialisation orientation of farmers in the region. A number of them are extremely commercially oriented whereas many are subsistence oriented.
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Bannor et al.
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Source: Authors computation, Gini Coefficient: 0.37
Source: Authors computation, Gini Coefficient: 0.67
Fig. 2: Lorenz curve of maize marketable surplus in Ashanti region
Fig. 3: Lorenz curve of maize marketable surplus in Northern region
From figure 4, the Lorenz curve clearly shows that, there is high marketable surplus inequality among maize producers in the Northern region whereas less marketable surplus inequality exists among the farmers from Ashanti region. This can be attributed to the fact that most maize producers in the selected district of Ashanti region are commercial farmers who are having business orientation compared to farmers from the Northern part of Ghana. These farmers also have the benefit of storage facilities in their production areas among other reasons. The less marketable surplus inequality among producers in the Ashanti region of Ghana is an indication that there is no single producer who exercise control over the market price. This is a typical feature of a purely competitive market structure indicating a sign of efficiency in the market.
Source: Authors computation, Gini coefficient of maize marketable surplus for Ghana; 0.53
Fig. 4: Lorenz curve of maize marketable surplus in Ghana
In other words, there is also a reflection of low level of income inequality from sales among the producers (Bannor, 2015). However, the inequality figure attributed to the Northern region indicates the possibility of few producers’ exercising control over the market price of maize in the area. Generally, there is marketable surplus inequality among maize producers in the country which is represented by Gini-coefficient of 0.53. The high marketable surplus inequality among producers in different parts of the country could be attributed to the differences of the adoption of good cultural practices to increase maize production in the country among other reasons. Results presented in table-6 show Tobit regression analysis output using the variables presented in table 3. LR chi2 (14) is the likelihood ratio (LR) chi-square test which shows that at least one of the predictors' regression coefficient is not equal to zero. The number in the parentheses indicates the degrees of freedom of the chi-square distribution used to test the LR Chi-Square statistic and is defined by the number of predictors in the model which are fourteen (14). Quantity harvested in the minor season was not included in the regression analysis because the Northern part of Ghana has only one major season. The pseudo R2 value of 0.1452 is called McFadden's pseudo R-squared. Tobit regression does not have an equivalent to the R-squared that is found in OLS regression; however, many people have tried to come up with one. There are a wide variety of pseudo-R-square statistics but because this statistic does not mean what R-square means in OLS regression (the proportion of variance of the response variable explained by the predictors) the researchers just mentioned the value of the pseudo R square. From the table 6, total quantity of maize harvested per annum by maize farmers is significant at one (1) percent level. The results show that a one (1) kg increase in the total quantity of maize harvested per annum results in an increase of approximately one (1) kg of marketable surplus. Again, one (1) kilogram increase in the amount of fertiliser used for production of maize in the Northern region of Ghana increases the amount of marketable surplus by 0.491 kilogram.
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16
Marketable surplus and its determinants among small scale maize farmers
Furthermore, one person added to a household decreases the amount of marketable surplus by 27.61 kilogram. In addition a farmer who has off farm job increases his/her marketable surplus by 166 kilograms compared to a farmer who doesn’t have off farm job. Table-7 shows the factors affecting marketable surplus in the Ashanti region of Ghana. From the table, when the total quantity of maize harvested per annum increases by one (1) kilogram, marketable surplus of maize increases by 0.98 kilogram. Also, when the proportion of certified seeds used by maize farmers or producers for production increases by one (1) unit, the amount of marketable surplus increases by 150.820 kilograms in the Ashanti region of Ghana. Moreover, one person added to a household decreases the amount of
Table 6: Factors affecting marketable surplus in Northern region (Tobit regression model estimates) Variable
Marginal Effect
Std. error
z value
p value
Unit price per kg for two seasons Total quantity harvested per annum Farm Size Marketing cost Proportion of certified seeds used Total fertilizer used Sold through farm gate Household size Age Educational level Total income Intercropped maize with other crops Gender Off farm Job Constant LR Chi2(14) Prob>Chi2 Pseudo R2
-157.102 0.997 40.465 0.912 66.638 0.491 141.2027 -27.611 -1.950 33.669 0.003 225.791 -100.819 166.207 -450.023 236.320 0 0.1452
350.575 0.060 91.425 0.983 151.682 0.129 83.5193 13.229 3.298 31.755 0.332 187.848 219.977 94.604 215.9941
-0.450 19.56 0.44 0.930 0.440 3.790 1.690 -2.090 0.590 1.060 0.080 1.200 -0.460 1.760 -2.80
0.665*** 0.000*** 0.654*** 0.353*** 0.660*** 0.000*** 0.091*** 0.037*** 0.554*** 0.289*** 0.939*** 0.229*** 0.647*** 0.079*** 0.040***
Source: Authors computation based on WFP field data, 2011, NB: Significance; 1%= *, 5%=**, 10%=***
maize marketable surplus in the Ashanti region of Ghana by 26.484 kg. A one Marginal Std. (1) year increase in the educational level Variable z value p value Effect error of maize producers in the Ashanti Unit price per kg for two seasons 69.734 58.076 1.200 0.231*** Region increases the amount of Total quantity harvested per annum 0.980 0.023 42.030 0.000*** marketable surplus by approximately 20 Farm Size -1.946 19.778 -0.100 0.922*** kilograms. Furthermore, a farmer who Quantity harvested during the minor season 0.023 0.027 0.850 0.395*** intercropped maize with other crops had Marketing cost -0.172 0.213 -0.810 0.418*** approximately 396 kilograms of Proportion of certified seeds used 150.820 90.340 1.670 0.096*** marketable surplus less compared to a Total fertilizer used -0.0177 0.053 -0.330 0.740*** farmer who did not intercrop maize with Sold through farm gate 0.923 1.480 -0.700 0.483*** other crops. In addition, a farmer who Household size -26.484 7.207 -3.670 0.000*** had off farm job increased his/her Age -1.039 1.480 -0.700 0.483*** marketable surplus by approximately *** Educational level 20.279 11.245 1.800 0.072 151 kilograms compared to a farmer *** Total income 0.002 0.010 0.180 0.855 who did not have off farm job. From *** Intercropped maize with other crops -395.875 137.263 -2.880 0.004 Table-8, unit price of maize per kg for Gender 20.870 57.076 0.370 0.715*** two seasons is significant at one (1) Off farm Job 151.051 42.799 3.530 0.000*** percent level. The results show that a *** Constant -257.675 106.586 -2.420 0.016 one Ghana Cedi (GH¢1) increase in the 2 LR Chi (15) 1490.85 unit price of maize for two seasons 2 Prob>Chi 0 increases the total maize marketable 2 Pseudo R 0.2088 surplus in Ghana by approximately one Source: Authors computation based on WFP field data, 2011, NB: Significance; 1%=*, 5%=**, 10%=*** hundred and fifty one (151kg). These results indicate that, maize producers in Ghana, do not only produce to meet family needs but also to get income hence increase in the price of maize motivates them to invest much in production which is translated in increased marketable surplus. The results agree with Sharma and Wardhan (2015) who reported that, higher price of rice resulted in larger marketable and marketed surplus. They further indicated that, a one per cent higher price was likely to induce a 0.08 per cent larger marketable surplus. Table 7: Factors affecting marketable surplus in Ashanti region (Tobit regression model estimates)
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Bannor et al.
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Table 8: Factors affecting marketable surplus in Ghana (Tobit regression Again, from table 8, one (1) model estimates) kilogram increase in the amount of maize harvested during minor Std. z value Marginal Variable p value error season increases marketable surplus Effect by 0.093 kilogram. Similar results Unit price per kg for two seasons 150.754 59.435 2.540 0.012*** were attained by Shah and Makwana Total quantity harvested per annum 0.937 0.021 44.600 0.000** (2013) who indicated that one Farm Size 25.062 19.995 1.250 0.211*** quintal increase in the total Quantity harvested during the minor season 0.093 0.025 3.710 0.000*** production of maize increased Marketing cost 0.063 0.219 0.290 0.774*** marketable surplus by 1.54 quintal Proportion of certified seeds used 153.125 81.745 1.870 0.062*** in Rajasthan. Furthermore, when the Total fertilizer used 0.149 0.051 2.930 0.004*** proportion of certified seeds used by Sold through farm gate 83.556 38.432 2.170 0.030*** maize farmers or producers for Household size -33.227 6.575 -5.050 0.000*** production increases by one (1) unit, Educational level 40.108 10.629 3.770 0.000*** the amount of marketable surplus Age 0.090 1.378 0.060 0.948*** increases by approximately 153 kilograms in Ghana. The results Total income 0.005 0.011 0.430 0.669*** attest to the importance of the use of Intercropped maize with other crops -130.733 116.493 -1.120 0.262*** certified seeds to produce maize. In Gender 48.399 57.816 0.840 0.403*** addition, one (1) kilogram increase Off farm Job 127.418 40.878 3.120 0.002*** in the amount of fertiliser used for Constant -526.804 93.404 -5.640 0.000*** production of maize in Ghana 2 LR Chi (15) 1853.710 increases the amount of marketable 2 Prob>Chi 0 surplus by approximately 0.15 2 Pseudo R 0.2067 kilogram. This reaffirms the Source: Authors computation based on WFP field data, 2011, NB: Significance; 1%=*, 5%=**, 10%=*** importance of fertiliser usage in maize production. This is because, soil nutrient depletion is a common consequence of most African agriculture and it’s ranked among the most serious constraints of maize production; this is mainly brought by reduction in the fallow period because of ever increasing population pressures. Also, Ghana like most countries in tropical climate witness high rainfall which comes with its attendant problem of nutrient leaching and low level of soil organic matter which has made nitrogen the most limiting nutrient in maize production. In light of these considerations, there should be a call for increase in fertilizer usage among maize producers to increase production and marketable surplus subsequently. Also, from table 8, one person added to a household decreases the amount of marketable surplus among maize producers in Ghana by approximately 33 kilograms. The result is in line with Sharma and Wardhan (2015) who reported the existence of an inverse relationship between family size and rice marketed surplus. Borate et al., (2011) reported inverse relationship of marketable surplus with family size and Kumar et al., (2013) also indicated that one person added to a family decreases maize marketable surplus by approximately 0.74 quintal in the state of Karnataka in India. The economic implication is, since maize is a major staple crop in the country, the higher the household size, the higher the amount of maize consumed hence the lower the marketable surplus. The results further revealed that, a one (1) year increase in the educational level of maize producers in Ghana increases the amount of marketable surplus by approximately 40 kilograms. The results agree with Alagh (2014), who reported that, there was positive relationship between the quantity of rice sold to the market and educational level of farmers in Gujarat (India). He further argued that, a one year increase in the educational level of a farmer increased the amount of marketable surplus of Tur by 127.191quintals. Lastly, from table 8, a farmer who had off farm job increased his/her marketable surplus by approximately 127 kilograms compared to a farmer who did not have off farm job. Most farmers who had other jobs apart from farming were able to invest additional amount of money generated in their maize production which resulted in larger amount of surplus after meeting requirements for family consumption, farm needs or seeds and feed for livestock, payment to labour in kind and payment to landlords as rent (as abunum or abusa in Ghanaian farming communities).
CONCLUSION The study has revealed that, total quantity of maize harvested per annum, total quantity of fertiliser used during production and choice of farm gate as marketing outlet increased marketable surplus in the Northern region whereas the number of people in a household negatively affected the quantity of marketable surplus. Household size also
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Marketable surplus and its determinants among small scale maize farmers
affected marketable surplus negatively in the Ashanti region of Ghana. However, marketed surplus, total quantity harvested, proportion of certified seeds used in production, educational level of farmers, intercropping of maize with other crops and farmers participating in off farm job positively affected marketable surplus. In addition to factors that positively affected the marketable surplus in Ashanti and Northern regions of Ghana, unit price per kilogram of maize for two seasons and quantity of maize harvested during the minor season positively affected marketable surplus in Ghana in general. In the context of policy implications, first the government of Ghana should improve investment in storage facilities and warehouses to aid in the avoidance of selling under distress sales. Thus, farmers can wait for the emergence of favourable market conditions and get the best value for their produce. Warehouses will also help in reducing the high spoilage of maize which was identified in the study and also assist in maintaining the quality of the produce for higher prices. Government must also take up the responsibility through the Directorate of Agricultural Extension Services of Ministry of Food and Agriculture and other stakeholders for educating farmers about the importance of the use of certified seeds and fertilizers. Government should also increase the quota of subsidised fertilisers allocated to the Northern and Ashanti regions of the country. Moreover, certified seeds should be subsidised and also made available and accessible to maize producers in the country. Lastly, despite the importance of marketed and marketable surplus estimates there is no regular system for generating such estimates at regular time interval in the country. Hence, there is a need to make arrangement to generate estimates of marketed and marketable surplus of food grains at pre-determined time interval. Downloaded From IP - 193.197.21.156 on dated 21-Jun-2018
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ACKNOWLEDGEMENT The researchers would like to express their heartfelt gratitude to UN World Food Programme, Ghana for funding of the data collection, collating and allowing for its use in this research. REFERENCES Agyare, W.A., Asare, I.K., Sogbedji, J. and Clottey, V.A. 2014. Challenges to maize fertilization in the forest and transition zones of Ghana. African Journal of Agricultural Research, 9: 593-602. Alagh, M. 2014. Assessment of marketed and marketable surplus of major foodgrains in Gujarat. Final Report, Centre for Management in Agriculture. Indian Institute of Management, Ahmedabad. Anonymous, 2013. Maize. The International Institute of Tropical Agriculture (IITA) culled, from http://www.iita.org/maize. Armah, M. 2000. Maize, soya and rice production and processing. Millennium Development Authority. Investment Opportunity in Ghana, pp. 3-4. Bannor, R.K. and Bentil, K.J. 2015. Comparing the profitability of tilapia farming to maize farming on a hectare of land in the Agona West Municipality of Ghana. Journal of Business Management and Social Science Research, 4: 382-392. FAOSTAT, 2016. FAO Statistics Division. Retrieved from http://faostat3.fao.org/download/Q/QC/E. Gujarati, D. 2012. Econometrics by Example. Macmillan Publishers Limited, Hampshire: England. ISSER, 2012. The State of the Ghanaian Economy, 2011. Institute of Statistical and Economic Research, University of Ghana, 147 pp. Melkamu, M. and Bannor, R.K. 2015. Estimation of agricultural resource inequality in India using Lorenz curve and Gini coefficient approach. International Journal of Current Research and Academic Review, 3: 174-184. MIDA, 2007. Investment Opportunities in Ghana on Maize, Soya and Rice Production and Processing. Institute of Statistical, Social and Economic Research, Ghana. MoFA, 2012. Agriculture in Ghana: Facts and figures. Produced by the Statistics, Research and Information Directorate (SRID), Ministry of Food and Agriculture. Accra. Morris, M.L., Tripp R, and Dankyi A.A. 1999. Adoption and Impacts of Improved Maize Production Technology: A case study of the Ghana Grains Development Project. Economics Program Paper 99-01. Mexico, D.F.: CIMMYT Shah,V.D. and Makwana, M. 2013. Marketed and marketable surplus of major food grains in Rajasthan. AERC REPORT, 150. Sharma, V.P. and Wardhan, H. 2015. Assessment of marketed and marketable surplus of major food grains in India Final Report. Centre for Management in Agriculture (CMA), Indian Institute of Management (IIM), Ahmedabad 380 015.
