5th International Conference on Humanities, Economics and Social Sciences (ICHESS'2015) August 16-17, 2015 Bali (Indonesia)

Status and Participation of Women Farmers in Farm Household Income Generation and Management in Isiala- North Local Government Area of , Nigeria

*Osondu, Charles Kelechi and Ijioma, John Chinasa

 understanding of gender issues in management of rural farm Abstract—The study determined status and participation of households is a necessary condition for agricultural women farmers in farm household income generation and development. Women farmers contribute significantly to management in Isiala-Ngwa North Local Government Area (LGA) of household welfare. Recognition of the role played by women Abia State, Nigeria. The specific objectives of the study were to: farmers in rural farm household management is important in describe socio-economic characteristics of women in farm developing countries like Nigeria where the major concern is households; identify types of income generation sources available to women in farm households; compute the range of income managed to boost rural economies and sustain adequate food supplies. by women; examine women involvement in farm household income In Africa most rural households rather than being nuclear management; determine factors that influenced farm household family are usually extended with more individual production income management by women and identify the problems militating and consumption units embedded within it [2]. Women in each against earning and managing income by women in farm households unit have some responsibilities independent of the household in the study area. Multi-stage random sampling technique was used to to feed, clothe or educate the children in the unit. The women select 70 farm households from the study area. Data were collected are also responsible for other needs or all family needs during using semi structured questionnaire that was personally administered. certain periods [3]. In most cases they fulfill this responsibility Data were analyzed by descriptive statistics and probit regression with an income got from farming activities. The separate model. The result of the analyses showed that women in farm households derived income from farming which accounted for activity of income and expenditure management by women is a 56.69% of annual total income. Crop farming was subsistence in unique feature in rural farm households. Husbands and wives nature and was by far the most important single source of income for sometimes lend money to each other at rates slightly less than the women, providing about 32.70% of total income of women in prevalent interest rate or pay themselves wages for services farm households. 37.14% of women managed between N21, 000 to rendered in the household. The household is seen as a joint N40, 000. 40.00% of the women took decision on household firm rather than a unitary entity in which wife’s budget is expenditure budget. The probit regression analysis revealed that age, distinct from her husband’s. employment status and farm income of women were positive In Nigeria, income generation and management vary within significant determinants of farm household income management at different farm households. According to [4] women varied alpha levels, while, spouse educational level was the only negative but significant determinant of the dependent variable at responsibilities associated with farming and reproductive 5.0% alpha level. We recommend that Government should motivate functions are increasing. Women are heads of 25 percent to 35 women to enroll in training programmes in order to improve their percent of households [5]. Their husbands are always away for involvement in income generating activities and management to long periods making it necessary for the women to make improve their standard of living and also enhance their productivity economic decisions alone. within the farm households in the country. Within the household structure, decision making status may be influenced by personal wealth, access to resources of other Keywords— Women, status, Income management, farm family members, type of household head and cultural household preferences, particularly in patriarchal societies [6]. The focus of household decision-making is determined by who controls I. INTRODUCTION and allocates economic resources within the family. A change GRICULTURE is a major source of livelihood to the rural in income generating capacity of partners precipitates a change A households, generating employment opportunities, source in household decision-making prerogatives [6]. Household’s of food and a major facilitator for income [1]. An leadership structure is classified into two: male headed and female headed households. Female headed households are Kelechi Charles Osondu lectures in Department of Agricultural Economics further disaggregated into de jure and de facto female headed and Extension, Abia State University uturu, Campus PMB 7010, households. The first arises in households headed by widows Abia State Nigeria (+2347037400876; e-mail: [email protected]). John Chinasa Ijioma is an Asso. Prof in Department of Agricultural or unmarried, separated or divorced women. The latter occurs Economics and Extension, Abia State University uturu, Umuahia Campus in households headed by females following migration or PMB 7010, Abia State Nigeria (e-mail: [email protected]). illness of the male head. Widowed and single parent heads

11 5th International Conference on Humanities, Economics and Social Sciences (ICHESS'2015) August 16-17, 2015 Bali (Indonesia) make all decisions on income generation and management Isiala Ngwa North Local Government Area has 53 autonomous affairs of the household. Good as these household structures communities. The LGA has distinct wet and dry seasons, may be, women confront several risks and experience which characterize its humid tropical climate, with the dry uncertainties in their farming operations. Most farms at the end season extending from November to March. The state has an of the season do not realize the expected yield and income annual mean temperature of about 270-300c and a relative from output for reasons of pests and diseases, damages arising humidity ranging from 70% to 80%, with January to march as from poor product handling, storage problem and the likes. the hottest months. The people are largely farmers growing This affects the income generation in the households and this yams, cassava, cocoyam, maize, melon, garden egg, okra, oil have led to lower standard of living and denied access to palm, cocoa, fruits and vegetables. Animals reared are Sheep, investment. Goats, Cattle, Pigs and Poultry. Some prominent markets in In many co-gender headed households, women most times the area include Orie-altigha, Orie-Ukwu Amaorji, Obikabia work for the men who earn the incomes, take decisions and Modern Market, Nkwo-Ebe and Nbawsi township market. spend the income with the women simply making requests for money for household upkeep. This condition has left the B. Sampling Technique women dependents and minors on household money control Multi-stage random sampling technique was adopted in this and uses. This is a case of gender imbalance in household study. financial management. Stage I: Five autonomous communities were selected A starting point for determining the extent of women’s randomly from the 53 autonomous communities in the LGA. participation in agriculture and household welfare is the The selected autonomous communities are Ahiaba Ubi, gender division of labour and household work as to who does Amachi, Eziala-Nsulu, Ikputu and Umuekpe. what in household’s income, savings and management of Stage II: Two villages were selected randomly from each of financial resources. For a woman who is a household head, all the five communities to give ten villages. income earned and financial expenses made would have to be Stage III: In the final stage seven farm households were solely accounted for by her, hence her personal cash flow selected randomly from each chosen village. This gave seventy (income earning and management) becomes complex. This farm households from which seventy women were chosen as special feature of women’s role in income generation and respondents. management is worth investigating. It is on this premise that C. Method of Data Collection this study is predicated to investigate position of women farmers in generation of farm income and its management in Primary data was gathered and used in this study. Semi- Isiala-Ngwa North Local Government Area (LGA) of Abia structured questionnaire was used to collect the primary data. State. The overall purpose of the study is to determine the collected Data include socio-economic characteristics of the status and participation of women in farm household income respondents, participation status of women in household and management in Isiala-Ngwa North of Abia State, Nigeria. financial management. The questionnaire was pre-tested and Specifically the study sought to: (i) describe socio-economic standardized before its administration by personal interview of women in farm households; (ii) identify types of income method. Pre-testing was done by issuing fifteen (15) sample generation sources available to women in farm households in questionnaires to each community. This was to test the the study area; (iii) compute the proportion and component of farmers’ ability to understand and answer the question. farm household income managed by women in the study area; Data collection lasted for four months, from July to end of (iv) examine women involvement in household farm income October, 2014. management in the study area; (v) determine factors that D. Analytical Technique influenced farm household income management by women in Descriptive statistics involving the use of tables, the study area and (vi) identify problems militating against percentages, mean and frequencies were used to analyze earning and managing income by women in farm households objectives i, ii, iii and v. Objective (iv) was analyzed using in the study area. probit regression model.

II. METHODOLOGY E. Model Specification The Probit model is appropriate when a response takes one A. Study Area of only two possible values representing presence or absence. This study was carried out in Isiala-Ngwa North Local The model was adopted as expressed by [8]. Government Area (L.G.A.) of Abia State. It’s headquarter is at Pi [Y=1] = [Fzi] ……………………………………(1) 3 Okpula – Ngwa and it occupies an area of 283km with a Where Zi = β0 + β1Xi Yi = β1Xi Yi = β1 = βX2i + population of 155,734 persons [7]. The Local Government …………………+ βKXKi + μ………...(2) Area is bounded on the North by LGA, on the Y* is unobserved but Yi = 0 if Yi* < 0, Y* ≥ 0. West by Ahiazu Mbaise LGA of Imo state, on the East by P (yi =1) = P (yi*≥ 0) Ikot-Ekpene and Abak LGA of Akwa Ibom State and on the = p (μ1 ≥ - β1 – β2X2i……………………….. South by Isiala-Ngwa South LGA. At no point does the land βkxki)……………………(3) rise above an elevation of 50 feet (15.2m). I = 1, 2……………………70 women farmers.

12 5th International Conference on Humanities, Economics and Social Sciences (ICHESS'2015) August 16-17, 2015 Bali (Indonesia)

Where Yi = Household income management by women It has been shown in the past, farmers had married many wives (Dichotomous variable, if a woman managed household and had large household sizes to be able to provide enough income = 1, otherwise = 0) labour for agricultural production. This scenario was X1 = Age of household head (years) responsible for high levels of malnutrition, mortality, illiteracy, X2 = Household size (number) unemployment especially in the rural economy which led to a X3 = Education Level (number of years spent in school) change in family emphasis [13]. X4 = Spouse education level (number of years spent in In terms of primary occupation Table 1 showed that 55.71% school) of the women were primarily engaged in farming while X5 = Employment status (civil servant = 1, otherwise = 0) 15.71% of them were Artisans. Also, 14.29% of the women X6 = Farming experience (years) were civil servants and traders respectively. The predominance X7 = Farm Income (Naira) of the women in farming explains the rural nature of the area. Lastly, Table 1 showed that the mean farm size of the III. RESULT AND DISCUSSION women was 1.61 hectares. This is a clear indication that the women in the area operated mostly on marginal farm land. A. Socio-economic characteristics of Respondents This is because in the study area, women’s rights of access and The distribution of the women in farm households according ownership to land are secondary to those of men on grounds of to socio-economic characteristics is presented in Table 1. The customs and is still mediated via patrilineal systems [14]. This table showed that the mean age of the women was 46.42 years. has remained so in spite of the intentions of the 1978 Land Use This result indicates that the respondents were mostly middle- Act. For women, user rights often follow marriage, inheritance aged that were within the national active productive work or borrowing. An increase in farm size especially to women force age of 18 to 65 years. This has implication on will lead to gains through economies of scale [15]. agricultural production because of the ability of this segment TABLE I DISTRIBUTION OF WOMEN FARM HOUSEHOLDS BY SOCIO-ECONOMIC of the population to effectively withstand the rigours, strain CHARACTERISTICS IN ISIALA NGWA NORTH LOCAL GOVERNMENT AREA OF and stress involved in agricultural production [9]. ABIA STATE, NIGERIA Table 1 also showed that fair proportions (48.57%) of the Variables Frequency Percentage women were married, while 21.4% of them were single. Going Age (Years) down the gender status, it is seen that 24.29% and 5.7% of the 30-40 29 41.43 41-50 23 32.86 women respondents were widowed and divorced respectively. 51-60 12 17.14 Married women in farm households have access to extra Above 60 6 8.57 financial, moral and physical supports from their spouse that Mean = 46.42; could go a long way improving their production activities and Standard dev. = 15.14 Marital Status earnings [10]. Single 15 21.43 In relation to education level, Table 1 showed that 47.12% Married 34 48.57 of the women respondents had secondary school education, Widowed 17 24.29 while 7.14% of them had primary school education. The table Divorced 4 5.71 Educational Status further showed that appreciable percentage (30.00%) of the No formal Education 11 15.71 women farm household in the study area had tertiary Primary Education 5 7.14 education. In summary, 84.29% of the respondents received Secondary Education 33 47.12 formal education ranging from primary school education to Tertiary Education 21 30.0 Farming experience tertiary school education. The ability to read and write often (Years) acquired from formal educational institutions would enable 1-5 26 37.14 them to utilize effectively and efficiently whatever resources at 6-10 15 21.34 their disposal. Acquisition of higher education by farmers 11-15 12 17.14 16-20 6 8.57 would enhance improved technology adoption hence increased Above 20 11 15.71 farm income [11]. Mean = 12.56; Table 1 further showed that the mean years of farming Standard dev. = 12.66 experience of the women was 12.56 years. This implies that the women in farm households had appreciable years of Household size 1-4 52 74.26 farming experience. The number of years spent in farming 5-9 15 21.43 gives an indication of the practical knowledge acquired on Above 9 3 4.29 how to overcome certain inherent problems in such farm Mean = 4.38; enterprise [12]. Standard deviation = 3.43 Table 1 also showed that the mean household size of the Primary Occupation women was 4 persons. This indicates moderate household size Farming 39 55.71 and a shift downwards from earlier large household sizes in Trading 10 14.29 rural areas. The present economic crises and deepening Civil Service 10 14.29 Artisan 11 15.71 poverty levels have forced rural households to embark on Farm Size (hectares) family planning measures to reduce their number of children. <1 33 47.12

13 5th International Conference on Humanities, Economics and Social Sciences (ICHESS'2015) August 16-17, 2015 Bali (Indonesia)

1-2.0 19 27.14 TABLE II 2.1-3.0 7 10.00 TYPES OF INCOME AVAILABLE TO WOMEN IN FARM HOUSEHOLDS IN ISIALA 3.1-4.0 4 5.71 NGWA NORTH LOCAL GOVERNMENT AREA OF ABIA STATE, NIGERIA. Above 4 7 10.00 Type of Farm Mean income Share of total Women Mean = 1.61; Standard income per capita (N) income (N) Participation dev. = 1.58 rate (%) Total 70 100.00 Total 178426.71 100.00 - Source: Field Survey, 2014 Household income B. Types of income Generation Sources Available to Women Total on-farm 101156.81 56.69 - in Farm Households Income Crop Income 58341.43 32.70 82.86 Table 2 shows the types of income generation sources Livestock 23815.38 13.35 58.57 available to women in farm household and how much different Income income sources contribute to total income of women in farm Agric wage 19000 10.65 14.29 households in Isiala Ngwa North Local Government Area of income Total off-farm 77269.9 43.31 - Abia State. The table indicates that all the women in farm income households derived income from farming, which however, Non-Agric wage 12244.9 6.86 4.29 accounted for 56.69% of annual total income. Crop farming, income was subsistence in nature and was by far the most important Remittance 18482.14 10.36 10.0 Self employed 28000 15.69 7.14 single source of income for the women providing 32.70% of Other income 18542.86 10.39 21.43 total income of women in households. Despite the growing Source: Field Survey, 2014 skepticism on the role of agriculture in reducing poverty among rural household, this result shows that crop farming C. Women participation in Household income management remains the major source of income for rural households. The literature is replete with varying degrees of women’s A good proportion of the women in farm household have involvement in household income management across different derived income from livestock enterprises, with income from cultural contexts. Limited efforts have, however, been made in this source constituting were only 11.35% of their total Nigeria particularly during the period of economic hardship. income. This suggests that they had small scale livestock kept Table 3 presents women’s involvement in household income extensively on free range. management in the study area. They were asked to respond to The other income proportion 19.98% was derived from the question on ―their participation in selected household different off-farm sources. Self-employed income was income management decision-making‖. The table revealed that important as it accounted for 15.69% of total income by of the 40.0% of the women keep household income in their women in farm household. Self-employed income came mainly possession while a good proportion (51.43%) had their spouse from handicrafts, food processing, shop-keeping and other were in possession of household income in the study area. local services, as well as trade in agricultural and non- Majority (84.29%) of the women in household who kept agricultural goods. household money saved it in the bank while 15.17% kept the Table 2 further revealed that 4.29% of the women in farm money in their homes. Similarly, half (50.0%) of the women households participated in non-agricultural wage activities. took decisions on what to buy in their home, while 45.71 and This source contributed only 6.86% to their total annual 4.29 claimed that decision on what to buy in their homes are income. The non-agricultural wage employment included jobs taken by their spouse and children respectively. Meanwhile, in construction, manufacturing, education, health, commerce, 40.0% of the women respondents took decision on household administration and other services. The smaller contribution of expenditure budget and 45.71% of the respondents indicated non-agricultural wage income to total annual income was that their spouse took decision on household expenditure based on account of low paying jobs secured outside the farms budget. The table further showed that 35.71% of the by the farmers and their household numbers. respondents planned for their household income while 32.86% Another source of income to the women farm households of the women earned higher income and has greater control of was supply of agricultural labour which accounted for 10.65% material resources than their spouse in the study area. The of their total annual income. This suggest a phenomenon by result corresponds with [6] that women are more involved in which landless farmers as opposed to land-owning farmers, their children’s education than spending of family income. participated in supplying wage labour to farms and was [17] pointed on the fact that women with greater control of common in the study area. The reasons for this included the material and social resources tend to make more inputs into need to earn additional cash income to meet urgent financial household decision making. need; reduce income risks and finance farm expansion [16].

Other income sources comprised of capital earnings and pensions which contributed 10.39% of total annual income of women farm households.

14 5th International Conference on Humanities, Economics and Social Sciences (ICHESS'2015) August 16-17, 2015 Bali (Indonesia)

TABLE III E. Factors influencing Women Management of household WOMEN PARTICIPATION IN HOUSEHOLD INCOME MANAGEMENT IN ISIALA income NGWA NORTH LOCAL GOVERNMENT AREA OF ABIA STATE, NIGERIA. Household Frequency Percentage The result of the probit regression estimates of factors that management influenced household income management by women in Isiala Who keeps the money Ngwa North Local Government Area of Abia State, Nigeria in your house? Husband 36 51.43 was estimated with maximum likelihood and is presented in Wife 28 40.00 Table 5. Overall, the model posted a log likelihood value of - Children 6 8.57 32.819718 and a goodness of fit chi-square value of 29.33 Where do you keep which was statistically significant at 1.0% level. Four out of household income? Home 11 15.71 seven explanatory variables fitted to the model were Bank 59 84.29 statistically significant at given critical levels and these Who takes decision on included age, farm income, employment status and spouse what to buy in your education level. home? Specifically, the coefficient of age (0.0284717) was positive Husband 32 45.71 Wife 35 50.00 and statistically significant at 5.0% alpha level. This implies Children 3 4.29 that an increase in age of women increased with management Who takes decision on of household income. The sign identity of this variable is in household expenditure tandem with a priori expectation. It has been reported that budget? Husband 32 45.71 management capacity is enhanced as age rises. Old people are Wife 28 40.00 said to be more fragile and thrifty [18]. Children 10 14.29 Another important factor is the employment status of Who plans for women. Its coefficient (0.0029276) was significant at 10.0% household income? Husband 31 44.29 risk level implying that the tendency to manage household Wife 25 35.71 income increase among women who were employed. Decision Children 14 20.00 making authority of employers of labour, employees and self- Who earns higher employed tends to be more enhanced relative to the income and has greater control of material unemployed or full homemaker. Indeed, employment status resources? fosters stronger participation in economic decision making Husband 38 54.29 relative to the unemployed and full homemakers [6]. Wife 23 32.86 The coefficients of spouse educational level (-0.312993) Children 9 12.86 Source: Field Survey, 2014 was negative and statistically significant at 5.0% alpha level. The implication is that an increase in spouse educational level D. Proportion of Income managed by Women lead to lower management of household income by the women. The distribution of the women according to the proportion This result is in line with a priori expectations. It must be of household income managed is shown in Table 4. The results connected with the fact that acquisition of higher education by show that on the average, the amount of household income the respondents enables women to better utilize available managed by the women per month was N40, 005.00. It was resources in their possession. also be observed that a good proportion (37.14%) of the The positive coefficient of farm income (4.70e-06) was women managed between N21,000 and N40,000 per month statistically significant at 10.0% risk level. This implies that an and a fairly good proportion (22.86%) of them managed increase in farm income increased women ability in managing between N1,000-N20,000 per month. This implies that the household income. This result was in consonance with a priori women in the study area were of low household income status expectation. [17] Pointed on the fact that women with greater and managed small incomes. control of material and social resources tend to make more

TABLE IV input into household decision making. PROPORTION OF MONTHLY INCOME MANAGED BY WOMEN IN ISIALA NGWA NORTH LOCAL GOVERNMENT AREA OF ABIA STATE, NIGERIA. Income managed (N) Frequency Percentage 1000-20,000 16 22.86 21,000-40,000 26 37.14 41,000-60,000 13 18.57 61,000-80,000 9 12.86 81,000-100,000 6 8.57 Total 70 100.00

Mean income managed 40,005.00

Source: Field Survey, 2014

15 5th International Conference on Humanities, Economics and Social Sciences (ICHESS'2015) August 16-17, 2015 Bali (Indonesia)

TABLE V TABLE VI BINARY PROBIT REGRESSION ESTIMATES OF FACTORS THAT INFLUENCED CONSTRAINTS MILITATING AGAINST FARM INCOME GENERATION AMONG HOUSEHOLD INCOME MANAGEMENT BY WOMEN IN ISIALA NGWA NORTH WOMEN FARMERS IN ISIALA NGWA NORTH LOCAL GOVERNMENT AREA OF LOCAL GOVERNMENT AREA OF ABIA STATE, NIGERIA ABIA STATE, NIGERIA Constraints Frequency* Percentage Variable Estimated Standard z-ratios P>|z| Denied access to farm 32 45.71 coefficients errors credit Age 0.028472** .0136557 2.08 0.037 Limited access to 15 21.43 Household 0.0607817 0.0818603 0.74 0.458 extension agents size Limited access to land 37 52.86 Education 0.0204555 .0431318 0.48 0.635 Inadequate access to 26 37.14 level mechanized equipment Spouse -0.312993** 0.1541869 -2.03 0.042 Denied Access to 24 34.29 educational mechanized farm input level Inadequate reliable 13 18.57 Employment 0.0029276 0.0019327 1.51 0.130 public transportation status Culture and norms 25 35.71 Farming -0.0120342 0.017806 -0.68 0.499 Inadequate power 21 30.0 experience supply/inadequate Farm income 4.70e-06* 2.46e-06 1.91 0.56 storage facilities Constant 0.9540959 0.894008 1.07 0.286 Source: Field Survey, 2014. Log -32.819718 * Multiple responses recorded likelihood Pseudo R2 0.3089 Wald Chi2 29.22*** G. Constraints to Women Farm Income Management Source: Field Survey, 2014. **, * indicates that variables are significant at 5.0% and 10.0% risk levels, The constraints perceived by women households to militate respectively. against their managing household income are shown in Table 7. The table showed that irregularity or income fluctuation and F. Constraints to Women Farm Income Generation culture and norms were major constraints that militated women The constraints perceived by women farmers in farm management of income in household in the study area. This households that militate against their income generation are was attested by 54.29% and 50.0% of the respondents shown in Table 6. The table showed that the main constraints respectively. Other serious constraints to household income that militated income generation were limited access to land management were inadequate or lack of storage facilities and (52.86%) and denied access to credit (45.61%). Another large family size highlighted by 37.14% of the respondents. hindrance that militated against income generation among the Low literacy level and hindered access to credit were reported women was inadequacy of mechanized equipment which was as minor constraints to women household income management attested by 37.14% of them. Other serious constraints that in the study area. militated against earnings of women households were inadequate power supply/inadequate storage facilities (30.0%), TABLE VII denied access to improved farm input (34.29%), limited access CONSTRAINTS MILITATING AGAINST FARM INCOME MANAGEMENT AMONG to extension agents (21.34%) and inadequate reliable public WOMEN FARMERS IN ISIALA NGWA NORTH LOCAL GOVERNMENT AREA OF ABIA STATE, NIGERIA transportation (18.57%). The implication of these results is Constraints Frequency* Percentage that hindered access to credit and land were major constraints Irregularity or income 38 54.29 that militated against income generation of the women in the fluctuation study area. This supports the findings of [19] that inadequate Limited access to credit 12 17.14 Low literacy 14 20.0 access to credit was a problem confronting small scale farmers Inadequate or lack of 26 37.14 in Nigeria. It has also been established that in most rural areas, storage facilities women’s rights to land is still regarded as secondary to those Large family size 26 37.14 of men and many customs suggest that women’s access to land Culture and norms 35 50.00 is still mediated via patrilineal systems [14]. Source: Field Survey, 2014. * Multiple responses recorded

IV. CONCLUSION AND RECOMMENDATION

Women’s access and control of resources affect their status in homes and their participation in control of household earnings. Women are agents of economic and social change. In the past, women were not supposed to participate in household income generation and expenditure. At a stage, the rural women as this study has revealed assert themselves as economics and social force that effectively control situation in the households of Abia State and Nigeria in general. Analysis of occupation and income diversification showed that land

16 5th International Conference on Humanities, Economics and Social Sciences (ICHESS'2015) August 16-17, 2015 Bali (Indonesia) cultivation continued to constitute the major source of rural [13] C.I. Ezeh. Poverty Profiles and Determinants of Expenditures of Rural women livelihood. Women Households in Abia State, Nigeria‖. The Nigerian Journal of Development Studies 2007; 6(1) 187 – 204. 2007. A government programme, which encourages subsistence [14] B. T. Aluko and A. Amidu. Women and Land Rights Reforms in and commercial farming through a popular poverty alleviation Nigeria. Paper presented at 5th FIG regional conference, on Promoting programme, should be designed for rural women to help them Land Administration and Good Governance, Accra, Ghana, March 8-11, earn and control part of household income. The significance of 2006. [15] U.A.U. Onyebinama. Farm business management for smallholder farm gender and household income and expenditures management firms in Nigeria. Alphabet Nigeria Publisher, Owerri, Imo State, has implication for a social re-orientation to enhance the Nigeria. 2004. productivity of rural women. Perhaps the step taken by Enugu [16] R.O. Babatunde, O.A.Adedeji and B.F Segun. Income and Caloric State Government in enacting a law, which empowers women Intake among Faming Households in Rural Nigeria: Results of Parametric and Nonparametric Analysis. Journal of Agricultural and redresses social and cultural bottlenecks that inhibit the Science, 2(2):135-146. 2010. freedom of women, should provide a guide in this direction. [17] R. Dixon. Population Policy and Women’s Rights: Transforming Government should guarantee rural women output prices. In Reproductive Choice. Westport, Conn: Praeger.1993. this direction, the re-introduction of the defunct produce board [18] N. Egbeogu. Comparative analysis of saving and borrowing behaviours between male-headed and female-headed farm households in the rural is hereby canvassed. This board should be re-organized and communities of Abia State, Nigeria. M.Sc Dissertation, Department of made functional in order to be able to guarantee stability in the Agricultrual Economics and Extension, Abia State University, Nigeria. output price of crops by these rural women. This will act as 2011. motivating factors to these rural women to produce. Another [19] C. O. Anyiro and B. N. Oriaku. Access to and Investment of Formal important policy issue is that women farm income would Micro Credit by Small Holder Farmers in Abia State, Nigeria. A case study of ABSU Micro Finance Bank, Uturu. The Journal of enhance their decision-making status. There is need to Agricultural Sciences, Faculty of Agricultural Sciences of the mainstream gender targeting in poverty eradication if women Sabaragamuwa University of Sri Lanka, 6(2):69-76. 2011. household decision status is to be enhanced. To achieve this there should be improved women’s education and access to gainful employment in higher income generating sectors.

REFERENCES [1] World Bank. Rural households and their pathways out of poverty. A powerful rational for land access policies. World Development Report 2008. Page 72. [2] H. Gladwin. ―Targeting Women Farmers to Increase Food Production in Africa‖. Proceeding of Women in Agriculture, University of Cape Coast, Ghana. 2000. [3] G. Margaret. Beyond the Policy Table Gender Agricultural and African Rural Household, Proceedings of the Workshop of Agriculture Intensification and Household Food Security Held at the Sabakawa Center, University of Cape Coast, Ghana, June 2000. [4] C. Ohuegbe, C. ―Women in Agriculture Programme in Imo State‖. A Paper Presented at the World Bank Workshop on Agric Extension, Ibadan, Nigeria. 1989. [5] A. Iman. ―Households and Crises in Africa‖. A Paper Presented to the A.A. World Seminar. The African Crises and Women’s Vision of the Wayout, Dakar, Senegal. 1988. [6] K. A. Oyediran and A. F. Odusola. Poverty and the Dynamics of Women’s Participation . African Population Studies Supplement A to Vol. 19: Pp. 115-139. 2006. [7] (NPC) National Population Commission. The Population Census of the Federal Republic of Nigeria Analytical report at the National Population Commission- Abuja. 2006. [8] D.N. Gujarati. Basic Econometrics. Tata McGraw-Hill Edition, New York. 2003. [9] F. Onyenucheya and O. O. Ukoha. Loan Repayment and Credit Worthiness of Farmers Participation in Household Decision-Making in Nigeria. 2007. [10] C.K. Osondu. Performance of Informal Micro-financing on Poverty Level of Women Farmers in Abia State, Nigeria. M.Sc Dissertation. Department of Agricultural Economics and Extension, Faculty of Agriculture, Abia State University. Nigeria. 2014. [11] C. K. Osondu and J. C. jioma. Analysis of Profitability and Production Determinants of Fish Farming in Umuahia Capital Territory of Abia State, Nigeria. World Journal of Agricultural Sciences. 2 (7): 168-176. December 2014. [12] O.E. Okolo. Economic analysis of broiler production in Jos, Plateau State. B.Sc. Project. Department of Agricultural Economics, ATBU Bauchi, Bauchi State, Nigeria. 2007

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