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DETERMINANTS OF WOMEN INTEREST IN AGRICULTURE:
EVIDENCE FROM SOKOTO STATE, NIGERIA
Jatto N.A.1, Galadima Z.I.2, Maikasuwa M.A.1, Jabo M.S.M.1, Ala A.L.1, Researchers 1Usmanu Danfodiyo University Sokoto, Sokoto, Nigeria 2Shehu Shagari College of Education, Sokoto, Nigeria E-mail: [email protected]
ABSTRACT
Absence of first hand information regarding women’s interest in agriculture is a major bottleneck to their level of participation which limit the opportunity to predict or formulate appropriate policy to boost their agricultural activities in Sokoto State. Towards this end, a study has been conducted within Sokoto metropolis to analyze the determinants of women interest in agriculture. The targeted populations for this study were women farmers group within Sokoto metropolis of Sokoto State. The data used in this study were primary data administered on a random sample of 60 women within the metropolis. Two local government areas were purposively selected because they form the largest population of Sokoto metropolis (Sokoto South and Sokoto North). Three districts were then randomly selected from each studied local government areas. In each of the districts, 10 women were randomly selected and interviewed. Data analyses were done with descriptive statistics, binary Logit regression and exponential regression. The result showed that variables such as years of education, experience in agricultural activities, family size, farm size, and participation in women group contributed significantly to women’s interest in agricultural production. Participation in women group had the highest influence on women’s interest in agricultural production. The result of the exponential regression showed that Age, years of education, group experience and farm size had regression coefficients that were positive, showing a direct relationship between participation of women in women groups and their interest in agriculture. It was recommended that: in order to improve on women interest in agriculture, more women group should be formed; they should equally be provided with farm inputs, increase their access to credits and be trained through workshops.
KEY WORDS
Women; Interest; Agriculture; Sokoto.
When focusing on agriculture as an economic activity in Nigeria the role of women cannot be undervalued, as they account for about 49% of Nigeria population (NPC, 2007). Auta et al. (2000) suggested that women’s contribution to farm work is as high as between 60% to 90% of the total farm task performed. The contribution of women ranges from such tasks as land clearing, land tilling, planting, weeding, fertilizer application to harvesting, food processing,threshing ,milling and marketing as well as management of livestock (Damisa et al., 2007).With these, most tasks are supposedly meant for man but the benefits gained by them are not commensurate to the hours women spend on it. Many women believed that agricultural industry is still for men only, making them entrenched in a vicious cycle of poverty that placed them at less advantage vantage of income and resource empowerment (Damisa et al., 2007).
The national research centre for women in agriculture (NRCWA) stated in their 20032004 report that women are faced with health hazards and about 50% comes from transplanting on farm activities, 50% in post harvest activities comes from threshing and 47% in livestock management comes from shed cleaning, these may be the part of reason while women’s participation in agriculture is impeded. Policy issues in the past failed to address the unpleasant and deploring condition under which women in the country contribute to agriculture. This perception arises because there is limited knowledge among the policy makers about the numerous contributions of women to agriculture especially in the area of food production in the country.
Understanding women interest in agriculture may be difficult for the fact that they might be unwilling to participate in agricultural activities because of traditions or customs that restrict women from feeding the family (Jatto et al., 2013). This has resulted to inadequate information that is necessary to predict the level of women preference in agricultural activities as compared to other non agricultural businesses. In other to address women problems with respect to their participation in agriculture so that their level of interest in agriculture is properly understood; a study has been conducted to ascertain factors that determine the interest of women in agriculture.
The study was carried out in Sokoto metropolis, the capital of Sokoto state, Nigeria. The state is located in the extreme Northwest of Nigeria and shares a boundary with Niger republic to the north, Kebbi state to the west and Zamfara state to the south. It had an estimated population of about 4,244,399 people as of 2006 (NPC, 2007). It lies within the dry Savannah and isolated hills. The predominant occupation of the people in the area is Agriculture.
The targeted populations for this study were women farmers group within Sokoto metropolis of Sokoto state. The data used in this study were primary data administered on a random sample of 60 women within the metropolis. Two local government areas were purposively selected because they form the largest population of Sokoto metropolis (Sokoto South and Sokoto North). Three districts were then randomly selected from each of the study local government areas. In each of the districts, 10 women were randomly selected and interviewed.
A questionnaire was used to obtain information on variables such as farm size, age, and years of experience, income, participation in the group, years of education, credit, marital status, extension visit, household size. Analyses were done using descriptive statistics, binary Logit regression and exponential regression.
Binary logit model specification:
Zi is an unobservable variable in the sense that X’s are generated from the field; P’s are not observable. In order to obtain the value of Zi the likelihood of observing the sample needs to be formed by introducing a dichotomous response variable Yi:
Y [1 if >-*>0 i [ 0 otherwise
1 = women interested in agricultural activities
0 = women not interested in agricultural activities
1 = Number of women sampled
j = 1-8 are the socio economic characteristic of women interested defined as:
X1 = Farming experience (yrs)
X2 = Education (yrs)
X3 = Farm size (ha)
X4 = Age (yrs)
X5 = Income (N)
X6 = Extension visit (number of visits)
METHODOLGY
1
Where,
zi - &+ P\Xi1 + AXi2 + + A8Xi8 + U
2
F (.)= cumulative logistic distribution.
X7 = Years participation in the group (years)
X8 =Household size (numbers) p1- p8 = Logit coefficient a = Constant term.
U = error term which will be assumed to be normally distributed with zero mean and constant variance.
Marginal Probability Estimation. The marginal probability of factor determines the interest of women in agriculture and was estimated based on derived expression from the Logit models as:
The exponential regression was taking as the lead equation based on the overall goodness of fit as judged by the value of R2 , the significant of f-value, and appropriateness of the signs of regression the coefficients.
Y= Participation in the group (years)
X1=Farming experience (yrs)
X2=Education (yrs)
X3=Farm size (ha)
X4=Age (yrs)
X5= Income (N)
X6= extension visit (number)
X7= Household size (numbers) b1- b7 = Regression coefficient ln=logarithm to base 10
Age: Age is one of the factors affecting decisions and actions made in agriculture, because people’s thoughts, behaviors and needs are primarily related to their ages (Simsek and Karkacur, 1996). Age may also influence an individual’s level of participation in agriculture and it could be that older women have access to information from developmental project works within their different groups (Damisa et al., 2007). The results showed that majority of the women were relatively young and are still in their active age. The implication is that younger people are likely to adopt new innovation faster than the older ones. This means that there is high potential for women farmers in the study area which is an assurance for increased food in the state if properly utilized.
Family Size: The result showed that most of the women have family size range from 4 and above. Generally, an increase family size is likely to increase the chance of participation in agricultural activities (Nkamleu and Adesina, 2000). The implication is that they will spend more on feeding, education, health care and other living expenses on their dependants. These expenses may account for low savings at the end of every harvest season.
Participation in Women Group: The results showed that majority of the women have been participating in women group for more than six years. The implication of this result is that most of the women will have access to different facilities from the group they belong to enhance their production and productivity in terms of sourcing for credit or other sundries. It also helps them share information and have a common stand on issues affecting their day-to-day farming activities.
3
Specified exponential regression equation:
ln > — a + blX 1 + b2 X 2 + b3 X 3 + b4 X 4 + b5 X 5 + be X 6 + bl X 7
4
RESULT AND DISCUSSIONS
Table 1 - Socio-economic and institutional variables
Variables Frequency percentage
Age (years)
26-40 35 58.4
41 Above 25 41.6
Total 60 100
Family size (numbers)
2-3 20 33.3
4 Above 40 66.7
Total 60 100
Participation in group (years)
1-5 24 40
6 Above 36 60
Total 60 100
Source: Field survey, 2013.
Table 2 - Maximum likelihood estimate of women in agriculture’s level of interest as related to their socio-economic characteristic in Sokoto metropolis
n/n Coefficient Std. Error Z p-value
Constant 10.3433 7.12417 1.4519 0.14654
Age -0.337979 0.236475 -1.4292 0.15294
Years of education -0.515381 0.296263 -1.7396 0.08193 *
Experience -1.333 0.642829 -2.0737 0.03811 **
Family size -1.09637 0.47838 -2.2918 0.02192 **
Farm size 0.0541193 0.0241646 2.2396 0.02512 **
Participation in group 2.38963 1.0045 2.3789 0.01736 **
Credit 1.91721e-06 1.85617e-06 1.0329 0.30166
Income 0.00152139 0.00244992 0.6210 0.53460
Source: Field survey 2013; *=10%, **=5%.
The result indicated that years of education, experience, family size, farm size and participation in group are the factors that influenced women’s interest in Sokoto metropolis in agriculture. Though, years of education, experience and family size have negative coefficients, farm size and participation in group which had positive coefficients. Considering the negative coefficient of years of education it implies that for every additional increase in education acquired it reduces the interest of women to participate in agricultural activities by 0.51538. An increase in years of experience gained it is likely to reduce the interest of women in agricultural activities by 1.333. While an increase in number of family size might reduces women’s interest in agricultural activities by 1.0963. This may be due to the fact that when a woman advances in education she gains more experience on ways to reduce her exposure to hazards and instead pay more attention to her children.
While for every one unit increase in number of farm size it increases the likelihood of women’s interest in agricultural activities. The implication of this is that increase in farm size is expected to increase the income of the women and participation in group association may increase their income which may increase their interest in participating in agricultural activities.
Table 3 - Predicted marginal Probability
Variables Marginal probability ■
Constant 0.8602 :
Years of education -0.0215899 :
Experience -0.0862529 :
Family size -0.0746976 :
Farm size 0.00214795 i
Participation in group 0.139513 :
Source: Field survey, 2013.
The result showed that years of education, experience and family size may not necessary be a factor contributing to women’s interest in agricultural activities. Participation in group associations has the highest extent of influence to which a unit change increases the probability of the women’s interest in agricultural activities. The implication of this is that it may create more opportunity for women to have access to different facilities that may enhance their interest and continuity in agricultural activities. Sometimes the more they tend to participate in the group they belong they tend to have access to credit which may lead to increased farm size, with a tendency to increased income (Jatto et al., 2013).
Table 4 - Effect of participating in women groups on their socio economic characteristics
Variables (3 value Standard error f-value
constant -0.983 0.531 -1.852*
Age 0.42 0.11 3.840***
Years of education 0.070 0.029 2.363**
Group experience 0.069 0.020 3.431***
Farm size 0.000 0.000 -3.658***
Family size -0.042 0.052 -0.807ns
Credit 0.00000004 0.000 0.980'-b
Income 0.000011 0.000 0.053---
R square 59.8% Adjusted R' 53.4%
Source: Field survey, 2013;***=1%; **=5%;*=10%.
The coefficient of determination R2 was 59.8%. This implies that the independent variables explain at least 59.8% of the variability in determining the effect of women participation in women groups. Age, years of education, group experience and farm size have regression coefficients that are positive, showing a direct relationship with participation of women in agriculture. This implies that increase in a unit will increase their participation by their respective p units. The results showed that, the age of the women, group experience and farm size are significant at 1% while years of education is significant at 5%. This supports the finding of Henri-Ukoha et al (2011).
CONCLUSIONS
It can be deduced from the study that despite gender inequalities, women still have interest in agricultural activities. The variables such as years of education, experience in agricultural activities, family size, farm size, and participation in women group contributed significantly to women’s interest in agricultural production. Participation in women group had the highest influence on women’s interest in agricultural production. The exponential regression showed that increase in age, years of education, group experience and farm size increase participation of women in agriculture. It was recommended that: in order to improve on women interest in agriculture, more women group should be formed; they should equally be provided with farm inputs, increase their access to credits and be trained through workshops.
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