Determinants of Informal Agricultural Financing: Evidence from Rural Economy of Kwara State, Nigeria

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1 The Journal of World Economic Review; Vol. 6 No. 2 (July-December 2011) pp Determinants of Informal Agricultural Financing: Evidence from Rural Economy of Kwara State, Nigeria A. A. Aderinto *, W. A. Lawal *# & I. B. Abdullahi * * Department of Accounting and Finance, Faculty of Business and Social Sciences, University of Ilorin, Pmb 1515, Ilorin, Nigeria, (FCIB, doklawal@yahoo.com & doklawal@gmail.com) # ABSTRACT The rural farmers who constitute a large percentage of food producers in Nigeria have problem of accessibility to financial resources from the formal financial institutions because of the institutions stringent conditions and their location. In effect, most of the rural farmers have to rely mainly on the informal financial institutions for funding. The objective of this study was to examine the determinants of informal agricultural financing in the rural economy of Kwara State, Nigeria. The source of data for this study was mainly from primary that was collected through the use of structured questionnaire from sampled farmers who were participating in three informal financing schemes namely: (i) periodic savings; (ii) money lending; and (iii) rotating savings in nine Local Government Areas covering the three senatorial districts of Kwara State, Nigeria. Using a multi-stage random sampling method, a total of 1350 farmers were selected for the study. The returned 1249 copies of questionnaires were then processed using Ordinary Least Square method of regression analysis. The findings indicated that membership size was the only functional variable that had positive and significant t-value. This shows that membership size is an important determinant of the sustainability and performance of the informal agricultural financing institutions. Based on the results, the study recommended that membership drive should be further intensified by the institutions. 1. INTRODUCTION The financial systems of most developing countries including Nigeria are made of two sectors: the formal and informal financial sectors that operate side by side. The formal sector, also known as the organized sector is made up of the Central Bank, Commercial Banks, Development Banks, Building Societies, Insurance Companies etc. These institutions are mostly found in the urban and semi-urban setting. On the other hand, the informal financial sector also known as un-organized sector consists of individuals such as money lenders, relatives, friends, neighbours, landlords, traders and group of individuals that operates mainly in the rural setting, (Mehrteab 2005). While the formal financial sector is an inheritance from the colonial times or a legacy of foreign systems and the activities are being regulated by the Government, the informal financial sector is an age-long one, an ancient one, that dates back at least to the 16 th century and the activities predate those of the formal financial system and are not subjected to Government regulation, (Iganiga et al., 2008; Siebel and Damachi 1982). Aryeety and Udry (1995) discussed the type of informal financial units in Africa. Accordingly there are three types of informal units. These according to them include (i) savings mobilisation that do little or no lending, that is, periodic savings; (ii) lending units that seldom engage in savings mobilisation (money lenders); and (iii) units that combine deposit mobilisation with

2 102 THE JOURNAL OF WORLD ECONOMIC REVIEW amounts of lending, albeit to members of distinct associations or groups, that is, rotating savings. They went on to describe the first units which are available in virtually all countries of West Africa as savings collectors. They do not engage in lending and the member merely collects what he or she saved at the end of the agreed period. The second category of informal financial units include money lenders which include relations, friends, landlords and neighbours who seldom engage in savings mobilisation, but, in lending money while the third units of the informal market include savings and credit associations and credit unions that take deposits and so lend in various forms to members only. Mehrteab (2005) also reported that in a number of countries like Nigeria, Ghana, Liberia, Togo, Cameroon and Senegal, there are also other financial institutions such as Savings and Credit Cooperatives and Credit Unions which are generally classified as semi-formal financial institutions because they are neither controlled by the countries banking laws nor by Central Bank regulations. For instance, they are not meant to comply with the reserve requirement regulations prescribed by Central Banks even though they are attached to the formal financial sector through legal regulations under the commercial laws of countries. The semi-formal financial institutions are outside the scope of this paper. As stated earlier, the informal financial institutions are more prominent in the rural settings and as such the rural populace including the rural farmers therefore mostly depend on the services of these informal financial institutions for funding. A vast majority of the rural populace depend on agriculture for their livelihood, (Ezengo,1998, cited in Henri-Ukoha 2011). The objective of this paper therefore is to examine the determinants of these informal financial institutions in the provision of finance for the rural farmers in Kwara State, Nigeria. 2. CONCEPTUAL CLARIFICATION AND REVIEW OF LITERATURE: AGRICULTURAL DEVELOPMENT AND DETERMINANTS OF INFORMAL AGRICULTURAL FINANCING 2.1 Agricultural Development in Nigeria Agriculture has been defined as the production of food and livestock and the purposeful tendering of plants and animals, (Ahmed, 1993). He stated further that agriculture is the mainstay of many economics and it is fundamental to the socio-economic development of a nation because it is a major element and factor in national development. In the same view, Okolo, (2004) describe agricultural sector as the most important sector of the economy which holds a lot of potentials for the future economic development of the nation as it had done in the past. Before the discovery of oil in Nigeria, agriculture accounted for over 60% of its Gross Domestic Product (GDP). It provided food and employment for the teeming population and raw materials for the growing industries. In the early 1960s, agriculture was the country s major source of foreign exchange earnings. Ogen (2007) stated that from the standpoint of occupational distribution and contribution to the GDP, agriculture was the leading sector in the 1960s. Also, the Nigerian economy, like that of Brazil, could reasonably be described as an agricultural economy during the first decade after independence. This is because agriculture served as the engine of growth of the overall economy of the two countries. During the period of 1960s, Nigeria was the world s second largest producer of cocoa, the largest exporter of palm kernel

3 DETERMINANTS OF INFORMAL AGRICULTURAL FINANCING: 103 and the largest producer and exporter of palm oil. It was also a leading exporter of other major commodities such as cotton, groundnut, rubber, as well as hides and skins (Alkali, 1997; Lawal, 1997). Despite the reliance of Nigerian peasant farmers on traditional tools and indigenous farming methods, these farmers produced 70% of Nigeria s exports and 95% of its food needs. The agricultural sector however suffered neglect during the hey-days of the oil boom in the 1970s. Ogen (2007) stated that agricultural sector accounted for less than 5% of Nigeria s GDP in Ever since then, Nigeria has been facing serious poverty challenges and the insufficiency of basic food needs (NEEDS, 2004). It is further stated in the NEEDS Policy Paper, 2004 that it is estimated that two-thirds of Nigerians live below the poverty line of US$1 per day, most of them in the rural areas, a figure that is up from 43% in 1985 (NEEDS, 2004). The root of this crisis lies in the neglect of agriculture and the increased dependency on mono cultural economy based on oil. 2.2 Determinants of Informal Agricultural Financing and Review of Literature The determinants in the context of this study are the variables or factors that determine the sustainability and performance of the informal agricultural financing institutions. Several studies have dwelled into the determinants of informal financial institutions especially in Nigeria and other part of Africa like Dakar, Senegal. The focus of this study is to determine the determinants of informal financial institutions in the development of agriculture in the rural economy of Kwara State, Nigeria. For example, Fadiga and Fadiga-Stewart (2004) conducted a study on Collective Action and Informal Financial Institutions: An Empirical Analysis of Rotating and Savings Credit Associations (ROSCAs) in Dakar, Senegal. The study analysed how Rotating Savings and Credit Associations in Senegal were able to overcome collective action dilemma, maintain institutional performance and remain sustainable over time. It was reported that in the informal financial institutions, members cooperate to provide collective benefits that each member receives in turn. They affirmed that social capital such as shared norms, network of relationship and trust are important factors that explain how these informal financial institutions have been able to remain sustainable. They further reported that larger groups are better able to provide collective goods because they have more resources available. The result of the study showed that individual contribution levels of members, the availability or the timing of loanable funds made available to members are important factors that determine the performance and sustainability of the informal financial institutions. Oloyede (2005) also conducted a study on the Informal Financial Institutions and Savings Mobilization Strategies in Ekiti State, Nigeria. It was observed that the reputation of the leader or the collector of funds is an important consideration in forming the rotating savings group. The study also revealed that in the daily contribution scheme, the organizer or the collector of funds usually collects commission from members which are equivalent to a day s commission deducted from members contribution as an incentive to the organizer. It was the view of Oloyede (2005) that the moneylenders perform some economic functions at least to the extent that they render some financial services that satisfy the demand of some sections of the community for loanable funds. Thus they charge interest on such funds as a reflection of risk premium. Olaiya (2005) also reported that the volume and availability of loanable funds depend on the ability of individual members to contribute funds.

4 104 THE JOURNAL OF WORLD ECONOMIC REVIEW 3. METHODOLOGY 3.1 Data Source A survey aimed at gathering primary data on the Scio-Demographic Characteristics of the respondents and the Determinants of Informal Financial Institutions in rural areas of Kwara State, Nigeria was conducted through distribution of copies of questionnaire on sampled farmers who were participating in the three indentified informal financial schemes in nine Local Governments Areas covering the three Senatorial Districts of the State. Multi-stage random sampling method was used for selecting the respondents, first by selecting 50% of the Local Government Areas in each of the senatorial districts, three (3) rural areas from each Local Government and fifty (50) farmers from each of the rural areas. A total of 1350 farmers were selected for the study but only 1249 farmers or 92% of the farmers satisfactorily completed the copies of the questionnaire which formed the basis for the analysis. The questionnaire was backed with oral interviews to elicit more information from the rural farmers. This study followed the same methodology as Rweyemamu, Kimaro and Urassa (2003). While their study was conducted on the semi-formal financial institutions in Tanzania, this study was conducted on informal financial institutions in Kwara State, Nigeria. 3.2 Data Analysis The analysis was based on inferential statistics using regression analysis. An alpha level of 0.05 was chosen as a-priori as the level of significance. The relationship was estimated using Least Square regression technique Model Specification The determinants of informal agricultural financing were hitherto identified from literature as: (i) individual level of savings; (ii) number of members; (iii) time taken to collect amount of fund saved; (iv) trust among contributors; (v) interest rate; and (vi) commission. In specifying the model, emphasis was first placed on the determinants of informal agricultural finance in the rural areas of Kwara State. Following Rweyemamu, Kimaro and Urassa (2003) method of estimating the determinants of agricultural finance, the model for this study is therefore stated as follows: where IFI a = f (DIFIa, HHc). 3.1 DIFIa = f ( S, NM, TM, Tru, In, Co) 3.2 HHc = f (Loca, Age, HHs, Edu, Ms, Gder) 3.3 When equations (3.2) and (3.3) are substituted into equation (3.1), equation (3.1) becomes IFI a = f (S, NM, TM, Tru, In, Co, Loca, Age, HHs, Edu, Ms, Gder) 3.4 where IFIa = fund made available for agricultural production by the informal agricultural financing institutions, (that is the aggregate of funds received for farming from the three informal financial institutions by the farmers)

5 DETERMINANTS OF INFORMAL AGRICULTURAL FINANCING: 105 HHc = household characteristics S = individual level of savings, NM = number of members, TM = time taken by members to collect amount saved, Tru = trust among contributors In = interest rate Co = commission Loca = location (Local Government) Age = age of respondent HHs = household size Edu = educational background of respondent Ms = marital status of respondent Gder = gender of respondent and U t is stochastic error term or disturbance error term. On transformation, equation 3.4 can be in linear form of the type; IFI a = a 0 + b 1 S + b 2 NM + b 3 TM + b 4 Tru + b 5 In + b 6 Co + b 7 Loca + b 8 Age + b 9 HHs + b 10 Edu + b 11 Ms + b 12 Gder + U t 3.5 A-priori Expectation or the expected patterns of behaviour of the independent variables (S, NM, TM, Tru, In, Co) on the dependent variable (IFIa) in the model are: 4. RESULTS AND DISCUSSIONS b 1 > 0, b 2 > 0, b 3 > 0, b 4 > 0, b 5 > 0, b 6 > 0, b 7 > 0, b 8 > 0, b 9 > 0 b 10 > 0, b 11 > 0, b 12 > Socio-Demographic Characteristics of the Respondents The age, educational status, marital status, household size and the gender of farmers are given in the Table 4.1 above. Majority of the farmers (34.43%) fell within 31 to 40 years of age cohort. Quite negligible proportion of the respondents was younger than 21 years (5.41%). Those above 60 years were equally negligible (0.4%). The result implies that the farmers were in their active productive years. This is expected to impact positively on their productivity. Given sufficient financial mobilization for the farmers, it is expected that their age would not have negative influence on productivity. The educational status of the respondents as shown in Table 4.1 indicates that majority of the farmers had primary (32%) and secondary (24%) education while only 5% had tertiary education. 39% had no formal education. This pattern of distribution is expected because the study area is a rural setting. The distribution of the respondents by marital status shows that most of the farmers (69.74%) were married. This is typical of Nigeria rural setting because family members often serve as a

6 106 THE JOURNAL OF WORLD ECONOMIC REVIEW Table 4.1 Socio-Demographic Characteristics of the Respondents in the Rural Areas of Kwara State S/No. Variables Frequency Percentage (%) 1 Age of the Respondents < > Educational Status of Respondents Informal Primary Secondary Tertiary Marital Status of Respondents Single Married Widow Others House Hold Size of the Respondents > Gender of Respondents Male Female Source: Author s Computation source of additional labour on the one hand, and the cultural value attached to marriage on the other. Next to this category of those married were those that were single (26.26%). The distribution of the respondents by household size shows that more than half of the respondents (54.45%) had between four to six household members. Household in the context of this study refers to total number of people eating from the same pot. The gender distribution of the respondents shows that female farmers (54.12%) were greater in number than male farmers (45.88%) in the study area. It has been discovered that 60% of labour force in agriculture in Nigeria are women (Ajetomobi, Olamide and Ayanwale 2003). 4.2 The Determinants of Informal Agricultural Financing The results of the regression analysis of the determinants of informal agricultural financing institutions in the rural areas of Kwara State are shown in Table 4.2. The determinants in the context of the study and as discussed in the review of literature are the variables or factors that determine the sustainability and performance of the informal agricultural financing which include:(i) group size or association size; (ii) mutual trust among members; (iii) individual savings contribution levels; (iv) time taken to collect funds; (v) interest rate charged by the

7 DETERMINANTS OF INFORMAL AGRICULTURAL FINANCING: 107 moneylenders; and (vi) commission received by money collector. In the model, the fund made available for agriculture by the informal agricultural financing institutions is the dependent variable while the factors stated above which are the determinants of the performance of the informal agricultural financing are the independent variables. Table 4.2 Regression Results of the Determinants of Informal Financial Institutions in the Rural Areas of Kwara State Variables Kwara state Kwara Central Kwara North Kwara South Intercept (t) 3.62 (3.03) (10.63) 7.98 (13.74) ( 0.03) S (t) ( 2.37) * 0.13 ( 0.99) ( 0.47) 0.36 (0.099) NM (t) 0.17 (3.38) ** 0.28 (1.36) * (0.57) (1.59) * TM (t) 0.09 ( 0.37) 0.04 ( 1.58) * ( 0.78) 0.04 (1.00) Tru(t) ( 4.15) ** 0.27 ( 3.50) ** (.039) 0.63 ( 4.25) ** In (t) 7.5E-0 ( 0.03) (0.39) (0.29) CO (t) 1.49E (0.10) 0.00 (.41) 6.6E-005 ( 0.67) ( 1.43)* Loca (t) 0.56 (10.52) ** 6.39 ( 19.83) ** (2.63) ** 0.63 (4.03)** Age (t) 0.12 (7.17) ** 0.74 (3.95) ** 0.29 (4.31) ** 0.14 (4.52)** HHs (t) 0.18 ( 4.23) ** 0.05 ( 1.47) * 0.04 ( 2.08) 0.12 ( 1.59)* Edu (t) 0.49 (2.88) ** 0.67 (4.31) ** 0.57 (0.63) 0.29 ( 1.11) Ms (t) 0.61 ( 2.13) * 0.48 ( 1.82) * 0.87 (0.67) 0.03 (0.05) Gder (t) 0.15 (7.60) ** 0.64 ( 2.35) 0.02 (3.98) ** 0.96 ( 2.24) * R 2 adjusted F c F t No. of observations 1, * Statistically significant at 10% level ** Statistically significant at 5% level. Key: S = Ind level of savings, NM = No of members, TM = Time, Tru = Trust, In = Int rate, Co = Commission, F c = Calculated F-Statistic, F t = Table F-Statistic, F c > F t. Source: Author s Computation 2010 Starting with the result of the whole state, the result of the regression analysis of the determinants of informal agricultural financing institutions shows a very low R _ square value of The reason for this low value can be attributed to the house characteristics which on many occasions can be interrelated. Furthermore, since our data is cross sectional, it is a permanent characteristic of such data. This means that only 28% variation in the dependent variable (informal agricultural financing) was explained by the explanatory variables (level of savings, number of members, time taken to collect funds, trust among members, interest rate and commission). The error term of 72% takes care of the variables in the study that cannot be included in the model because of certain qualitative features such as household characteristics, for example, age of the respondent, household size of the respondent, educational background of the respondent, marital status of the respondent, and the gender of the respondent. At 5% level of significance, the F-statistic of shows that the model is useful in determining if any relationship exists between informal agricultural financing and the determinants in Kwara State. As the computed F-Statistic which is is greater than the tabulated F-Statistic valued at 1.98, an implication that the explanatory variables have significant influence on the dependent variable is suggested.

8 108 THE JOURNAL OF WORLD ECONOMIC REVIEW Keeping the vectors of household characteristics constant, the co-efficient and associated t-values of the determinants show that level of savings, time taken to collect funds, trust among members and interest charged by moneylenders fell short of our expectations while number of members and commission received by money collector fulfilled our a-priori expectations. This is an indication that only number of members and commission received by money collector has significant influence on the performance of informal financial institutions in financing agriculture in the whole state. Statistically, only the number of members is significant at 5% level. The results of the regression analysis of the determinants of informal agricultural financing conducted at 5% level of significance in each of the three senatorial districts of Kwara State are also presented in the same Table 4.2. This is to further confirm the determinants of informal agricultural financing in each of the senatorial districts. From the result, the regression analysis of the determinant of informal agricultural financing shows that Kwara Central, Kwara North and Kwara South senatorial districts have R-square of 0.07, 0.15 and 0.31 respectively. This shows that it was only in Kwara South senatorial district that about 31% variation in the dependent variable (informal agricultural financing) was explained by the explanatory variables (level of savings, number of members, time taken to collect funds, trust among members, interest rate charged by moneylender and commission received by money collector. Other senatorial districts have less than 30% variation of the variables in the dependent variable that was explained by the explanatory variables. At 5% level of significant, the F-statistic in the three senatorial districts shows that the models are useful in determining if any relationship exists between the dependent variable (informal agricultural financing by the informal financial institutions) and the independent variables. As indicated in Table 4.2, the F-statistic which are 78.2, 3.67 and 6.67 for Kwara Central, Kwara North and Kwara South senatorial districts respectively are greater than the tabulated F-statistic valued at This is also an indication that the explanatory variables have significant influence on the dependent variable. Keeping the vectors of household characteristics constant, the co-efficient and associated t-values of the determinants show that level of savings and time fell short of our a-priori expectation in both Kwara Central and Kwara North senatorial districts. Trust also felt short of our a-priori expectation in Kwara Central and Kwara South senatorial districts. The number of members fulfilled our expectations in the three senatorial districts. Interest rate charged by the moneylender also fulfilled our expectations in Kwara North and Kwara South senatorial districts. Savings fulfilled our a-priori expectation only in Kwara South senatorial district. 4.3 Discussion of the Results of the Regression Analysis of the Determinants of Informal Agricultural Financing The result of the regression analysis on the determinants of informal agricultural financing in Table 4.2 showed that only membership size had significant influence on the performance of informal agricultural financing institutions at the state level and across the three senatorial districts of the state. This is expected since the more the members who join the institutions, the more other variables, for example, interest rate received by the money collector in the periodic savings scheme and the individual level of savings contributed by members will increase and will

9 DETERMINANTS OF INFORMAL AGRICULTURAL FINANCING: 109 positively influence the sustainability and performance of the institutions in further financing of agriculture in the study area. The findings of the study thus conform to the views of Olaiya (2005), Oloyede (2005) and Fadiga and Fadiga-Stewart (2004) under the review of literature for this study. They asserted that the larger the size of the group or association, the better the institution is able to provide collective goods because they would have more resources available. They concluded that membership size is an important factor to the sustainability and performance of the institution. Further this result conforms to the oral submission during interview with some of the rural dwellers that the institutions depended on their members not only to be in existence but to be able to function and provide financial services to members. Oral interview with the respondents also revealed that the low level of savings as a determinant of the institutions was as a result of low level of economic activities in the rural economy which was also due to poor infrastructural facilities. 5. CONCLUSION AND RECOMMENDATION This study examined the determinants of informal agricultural financing in the rural economy of Kwara State, Nigeria. Three units of the informal financial institution, namely, periodic contribution, moneylender, and rotating savings were the focus of the study. The study covered the rural areas of the three Senatorial Districts in nine Local Governments Area of the State. A total of 1350 copies of questionnaire were administered on randomly selected farmers who were participating in the three informal financial schemes. Only 1249 of the copies of the questionnaire were returned which formed the basis for the analysis. The analysis was based on inferential statistics using regression analysis. The findings indicated that as a determinant of the sustainability and performance of the informal financial institutions in the study area, membership size was the most important variable being statistically significant at 5% level with a t-value of Savings as a determinant fell short of our expectation with a t-value of This, as revealed by oral interview was due to low economic activities in the rural areas which was a result of poor infrastructural facilities in the rural areas. Based on the findings this study, it was recommended that: (i) membership drive be further intensified since the result revealed that membership is an important determinant of the sustenance and performance of the institutions. This will lead to higher participation and increased mobilization of funds, (ii) Government at all levels should improve infrastructure in the rural areas to boost economic activities as more money in the hands of the rural farmers will improve their propensity to save and enhance the informal financial institutions performance in further financing of agriculture in the study area. In this way, the activities of informal agricultural financing will be further enhanced. References Ahmed Y. O., (1993), Bank of the North Pamphlets on Agricultural Financing, Various Circulars and Policy Guidelines on Agricultural Financing in Bank of the North Limited, A Paper Delivered at Seminars at Bank of the North Human Resources and Development Centre by (Agric. Officer, Bank of the North Limited).

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