EFFECTS OF MICRO-CREDIT ON CROPS YIELD BY SMALL HOLDER FARMERS IN ORHIONMWON LOCAL GOVERNMENT AREA OF EDO STATE, NIGERIA

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1 EFFECTS OF MICRO-CREDIT ON CROPS YIELD BY SMALL HOLDER FARMERS IN ORHIONMWON LOCAL GOVERNMENT AREA OF EDO STATE, NIGERIA ABSTRACT Orewa 1, S. I., Ekunwe 1, P. A., Egware 1, R. A. and Abulu 2, M. O. 1 Department of Agricultural Economics and Extension Services, Faculty of Agriculture and Agricultural Technology, Benson Idahosa University, Benin City, Edo State, Nigeria. 2 Agricultural and Rural Development Secretariat, Federal Capital Territory Administration, Abuja, Nigeria. This study examined the effects of micro-credit on crop yields in Orhionmwon Local Government Area of Edo State, Nigeria. A sample size of 166 small-scale farmers was randomly selected from the farming communities in Orhionmwon Local Government Area. Ninety two (92) beneficiaries and 74 non-beneficiaries were randomly selected from the study area. A wellstructured questionnaire and scheduled interviews were used to obtain data from the farmers. The data collected were subjected to descriptive statistics such as frequency counts, percentages and mean scores. The mean scores were compared using the student t-test. Results showed that the respondents were almost uniformly distributed gender-wise. The females were however slightly more, both among the beneficiaries (58.7%) and non-beneficiaries (52.7%). The mean years of farming for both the credit beneficiaries and non-beneficiaries were 32 years and 34 years respectively. Most of the farmers had farm holdings less than 2.5 ha. On the average, the yield difference between beneficiaries and non-beneficiaries for maize, yam, cassava and plantain were 0.94, 9.91, 14.74, 6.89 tonnes respectively showing that the beneficiaries had higher yields. The results of the t-test showed that there was a significant difference between yields of beneficiaries and non-beneficiaries and they were all found to be significant at 1% level of significance. Untimely delivery of loan was indicated as the greatest constraint to loan acquisition by the beneficiaries while the non-beneficiaries identified high interest rate charged by the microfinance bank and distance as the greatest reasons for not accessing loans. Keyword: Micro Credit, Crop Yield, Small Holder farmers Edo State, Nigeria. INTRODUCTION Before the spawn of Nigeria s formal microfinance industry in the late 1990s, financial activity was enacted within the context of an extensive informal economy. Throughout the country, traditional group networks served as proprietors of financial exchange (CBN, 2005). They were led by traditional moneylenders who offered limited services and loans at disproportionately high interest rates. Nevertheless, it was documented that as early as 1936, the Nigerian government supported such exchanges, as long as cooperative groups maintained their ordinance of coupling credit with regular and compulsory savings (Eboh, 2008).It was not until the big aid push of the 1950s that the government became an intermediary, funneling large amounts of aid from foreign donors into subsidized rural credit programs (CBN, 2005). In this case, government intervention resulted in indebtedness, high default rates and an inability to reach those at the bottom of the pyramid. This led to the gradual emergence of private sector-led microfinance to fill the void perpetuated by exclusive financial policies and government incapacity (Acha, 2008). The Nigerian Government however tried to maintain a stronghold on financial activities by enacting a number of initiatives dedicated to rural development beginning in the 1970s (Eboh,2008). In particular, the National Agricultural and Cooperative Bank (NACB) and the Rural Banking Scheme (RBS) were founded in order to facilitate financial access to farmers. Subsequently, an Agricultural Credit Scheme Fund was developed to provide a financial cushion for farmers facing risk from natural disasters. Finally, the Export Financing Rediscount Facility was established to formalize and standardize the rural credit markets (Olaitan 2006). As microfinance institutions undergo transformation and commercialization, the founding principle of microfinance which is to reach those most in need of formal financial services becomes more and more obsolete. In Nigeria in particular, the concentration of MFIs in urban centers has directly contributes to a large underserved rural population (Okpara, 2009). In Orhionmwon local government area, the only micro-finance bank giving out soft loans is the Trust Fund Micro Finance Bank. It has been in existence there since Trustfund Microfinance Back is a Limited company which resulted from the transformation of former Alaghodaro Community Bank to Microfinance Bank in July This was in respond to the directive by the Central Bank of Nigeria that all community banks should be recapitalised and change to MFB. The bank was established to reduce poverty in Nigeria by empowering a large number of micro, small and medium enterprises through effective NJAFE VOL. 11 No. 1,

2 services and to be a leading microfinance institution in Nigeria, delivering effective services in a mutually beneficial relationship to all stakeholders (TMFB, 2012) This study therefore seeks to answer the following research questions: how have microfinance banks faired in the provision of agricultural credit to small-holder farmers? What are the effects of such volume of loan on the production of small holder farmers and what are the constraints to securing loans from MFB? The objectives of this study were to examine the socio-economic characteristics of the small holder farmers in the study area, compare the yield of credit beneficiaries and non beneficiaries and then identify the constraints faced by beneficiaries and non-beneficiaries in accessing credit facilities. MATERIALS AND METHODS Area and scope of study The study was carried out in Orhionmwon Local Government Area of Edo State with headquarters at Abudu. The State is located in the rainforest belt of Nigeria between Longitudes 5 o E and 6 o 42 I and Latitudes 5 o 45 I N and 35 o N. It is bounded by Kogi State to the North, Delta State to the South, Ondo State to the West and again Kogi State to the East. Edo State occupies a total land mass of 17,820 km 2 and has a population of 3,218,332 by the 2006 population census figure (EDSG, 2012). Orhionmwon local government area is one of the oldest and largest among the 18 Local Government Areas in the State. It has a landmass of approximately 41,319 square km. The population is predominantly Bini speaking people and their major economic activity includes hunting, craftwork, petty trading and artisanship. Majority (over 70%) of the people engage in subsistence agriculture. The land is known to be very fertile and the people cultivate crops such as yam, cassava, maize, coco-yam, and plantain to mention but a few. They also engage in the rearing of livestock including goats, pig, poultry and rabbits.the scope of the study focused on small-scale arable farmers, who cultivate maize, cassava, yam and plantain in the study area. TrustFund Microfinance Bank is the only microcredit institution in the area that is servicing the credit needs of the small scale crop farmers in the study area. Data collection and sampling techniques Primary and secondary data were utilized for the study. Primary data were collected using a structured questionnaire and interview schedules (for non-illiterate respondents). Secondary data consisting of list of credit beneficiaries as well as amount were obtained from the disbursing Microfinance institution. Primary data were collected from July 2013 to November A sample size of two hundred (200) small-scale farmers was randomly selected from the farming communities in Orhionmwon Local Government Area. One hundred (100) credit beneficiaries and one hundred (100) non-beneficiaries were randomly selected from the study area. Data list consisting of three hundred (300) credit beneficiaries from the study area was obtained from TrustFund microfinance bank which is the only microfinance institution in the study area. Through a process of random sampling, they were assigned numbers each from one (1) to three hundred (300) in a sheet of paper which were placed in a box where one hundred beneficiaries were drawn at random without replacement to make up the list of the researcher s sample size for the beneficiaries. To get the required number of sample size (100) of the non-beneficiaries, the study area was demarcated into five farming communities and twenty (20) non-beneficiary farmers were drawn from among the non-beneficiary farmers that were presented in each community. The non-beneficiaries were identified by scheduled meetings with the farmers either as individuals or as group living within the same locality as the beneficiaries. This made a total sample size of two hundred (200) consisting of one hundred (100) beneficiaries and one hundred (100) nonbeneficiaries. However, eight copies of the questionnaire and 26 copies of the questionnaire administered to the beneficiaries and non-beneficiaries respectively were discarded since they were found to be unsuitable at the data analysis stage. Thus, 92 copies and 74 copies were analysed for the beneficiaries and non-beneficiaries respectively. This gave a response rate of 83%. Analytical techniques The data collected were subjected to descriptive statistics. The descriptive statistics used were frequency counts, percentages and mean scores. The mean scores were compared using the student t-test. The inferential statistics used were pooled variance and the t-test of differences between sample means. Pooled variance was used to obtain estimated standard error of the difference between the means. Explicitly, the pooled variance formula can be represented as: Where: (1) NJAFE VOL. 11 No. 1,

3 S b 2 = variance for the credit beneficiaries S nb 2 = variance for the non-beneficiaries N b = number of observations of credit beneficiaries N nb = number of observations of non-beneficiaries The standard error of the difference of the means is represented as: Where = estimated standard error of the difference of the means The Test of Difference between Sample Means: The test of difference between the two categories of small-scale farmers sampled (credit beneficiaries and nonbeneficiaries) was done using the t-test statistics. It is represented as: Where: = calculated t-value = the mean of credit beneficiaries = the mean of non-beneficiaries = estimated standard error of the difference of the means (2) (3) RESULTS AND DISCUSSION Socio-economic characteristics of respondents The results of the socioeconomic characteristics of the respondents are presented in Table 1. Results showed that the respondents in the study area were fairly uniformly distributed gender-wise. The females were however slightly more, both among the beneficiaries (58.7%) and non-beneficiaries (52.7%). This indicates that though both males and females were involved in farming, the females appear to be more involved in providing food security. This is supported by the findings of Adisa and Okunade (2005) who reported that women contribute 60 per cent of the labour force, produce 80 percent of the nation s food, earn 10 percent of the money income but own only 1percent of the farm assets. Moreover, about 81.5 percent of beneficiaries were married while 56.8 percent of the non-beneficiaries were married. Onemolease (2001) in his study suggested that a possible explanation for the dominance of married farmers amongst respondents is to care for their families. It is also believed that a married person is more responsible and stable than the unmarried. The age distribution among the respondents ranged between less than 30 and 70 years. Although there was a wide variation in age among the respondents; the average age was 45 years and 42 years for the credit beneficiaries and non-beneficiaries respectively. Only about 16% of the respondents were above 60 years of age while about 42% and 54% of the credit beneficiaries and non-beneficiaries respectively were 40 years of age and below. This implies that more youths were involved in arable crop farming in the study area. The result from the survey further shows that only 24% of the credit beneficiaries had no formal education while illiteracy level among the non-beneficiaries was as high as 40.5%. This fact is in line with a similar study on microfinance Scheme in Western Nigeria by Oke et. al., (2007) in which they reported that 81 percent of the respondents had formal education. That study concluded that the high level of literacy was likely to afford respondents better managerial skills in handling their businesses. The relatively high level of illiteracy among the non-beneficiaries in this study may be partly the reason why they could not access credit since they had less access to information. This fact is in line with the study of Asiabaka (2002) who reported that the resultant effect of lack of formal and informal education is acute resistance to change especially in the spread of information. The result also indicated that the respondents had farming experience of 40 years and above for both groups. These farmers can rightly be classified as "professionals" in farming business because of their long involvement in the farming business. The mean years of farming for both the credit beneficiaries and non-beneficiaries were 32 years and 34 years respectively. The household size is the number of persons belonging to one household. This could include extended family members or other persons putting up with the family. The study revealed that most of the respondents had NJAFE VOL. 11 No. 1,

4 Table 1: Socio-economic characteristics of respondents Characteristics Categories Beneficiary (n = 92) Non beneficiary (n = 74) Freq % Mean Freq % Mean Sex Male Female Marital status Single Married Divorced Widowed Separated Age range 30 years & below >60 years Education No formal education Primary education Secondary education Tertiary education Farming status Part-time Farming experience range Full time > Household size range above Farm size range (ha) 0.5 and below Above Source: Field survey, household sizes of between five to nine persons per household for both the credit beneficiaries (52.2%) and nonbeneficiaries (54.1%) respectively. The mean household size was however eight persons per household for the beneficiaries while that of the non-beneficiaries was five persons per household. The large household size among beneficiaries may be a result of their increased labour need for their expanded farming operations. Dipeolu, et. al., (2000) was of the view that a larger household may serve as an important source of farm labour supply and consequently increased productivity. The study further shows that 72.8 % of beneficiaries and 89.2 % of nonbeneficiaries had farm sizes of less than 2.5 hectares, which is in line with the report of Akangbe et. al.,(2012) which posits that close to 50 percent of Nigerian farmers cultivate between 1-5 hectares farmland and that they are generally small holder farmers. NJAFE VOL. 11 No. 1,

5 Comparison of crop yields between loan beneficiaries and non-beneficiaries Yield difference in farm size per hectare is presented in table 2a. It indicates that the beneficiaries obtained higher yields than the non-beneficiaries for maize production. However, the yield difference between the beneficiaries and non-beneficiaries were significant for the hectares and hectares farm size ranges. This is indicated by their of and which were lower than the tabulated of and respectively. For yam production, the table 2b indicates that the beneficiaries obtained significantly higher yields than the non-beneficiaries in all the different farm sizes. This is indicated by the for each farm size ranges greater than their tabulated or critical t- values respectively. It was also observed that the beneficiaries obtained the highest yield per hectare in the hectares of farm size ranges while the lowest yield was obtained in the hectares for farm size ranges. Results obtained for cassava as presented Table 2c indicates a similarity with what was obtained for yam production in Table 2b. Table 2a: Yield Difference between beneficiaries and non beneficiaries for maize Farm size range (ha) Maize (tonnes) Beneficiaries Non-beneficiaries Yield Difference Calculated Critical < ** ** ** ** ** Difference is significant at 5% level. Table 2b: Yield Difference between beneficiaries and non beneficiaries for yam Farm size range Yam (tonnes) Yield Difference Calculated Critical (ha) Beneficiaries Non-beneficiaries 0.5 &below ** ** ** ** ** Above ** ** Difference is significant at 5% level. Table 2c: Yield difference between beneficiaries and non beneficiaries for cassava Farm size range Cassava (tonnes) Yield Difference Calculated t- Critical (ha) Beneficiaries Non-beneficiaries values 0.5 &below ** ** ** ** ** ** ** Difference is significant at 5 level. Beneficiaries obtained significantly higher and greater yield than the beneficiaries for all the different farm size ranges as shown by significant higher than the critical values for all farm size ranges. The greatest yield difference of tonnes was obtained in the hectare farm size range while the lowest yield difference of tonnes was obtained in the farm size range. Results of yield per hectare for plantain as shown in Table 2d indicates that although there was greater yields for plantain production by the beneficiaries than the nonbeneficiaries in all the different farm sizes, the yield differences were not significant only for the and farm size ranges. NJAFE VOL. 11 No. 1,

6 Table 2d: Yield Difference between beneficiaries and non beneficiaries for plantain Farm size range Plantain (tonnes) Yield Difference Calculated Critical (ha) Beneficiaries Non-beneficiaries 0.5 &below * * * * ** Difference is significant at 5% level. This is indicated by the values of greater than the tabulated or critical t values for all the different farm size ranges except for the hectares and hectares farm size ranges. The highest yield difference of 8.05 tonnes was obtained in the hectare farm size ranges while the lowest yield difference of 2.56 tonnes between the beneficiaries and non-beneficiaries was obtained in the hectares farm size range. Test of Differences of Crop Yields between Beneficiaries and Non-Beneficiaries The mean output per hectare for maize for the beneficiaries was 3.68 tonnes while that for the non-beneficiaries was 2.74 tonnes. The mean difference of 0.94 tonne was significant at 1% level (Table 3). Table 3: Test of differences of crop yields between beneficiaries and non-beneficiaries of credit Crop Beneficiary Non beneficiary Difference t value Mean/ha Mean/ha Maize *** Yam *** Cassava *** Plantain *** ***Difference is significant at the 1% level (critical t =2.609) Source: Field Survey, 2013 This indicates that the credit obtained by the beneficiaries tremendously improved their production of maize. The mean output per hectare for yam produced by the beneficiaries and non-beneficiaries were tonnes and 22.7 tonnes respectively. The difference in the mean was 9.91 tonnes. The t-test value comparing the mean value of the output of the beneficiaries and that of the non-beneficiaries was and was significant at 1% (Table 3). This indicates that the provision of credit to the beneficiaries brought about a significant increase in the yield of yam. Provision of credits by the Trust Fund Micro Finance Bank to small holder farmers in the study area had great impact on the production of cassava. The mean output per hectare for the non-beneficiaries was tonnes while that for the beneficiaries was 35.6 tonnes (Table 3). The mean difference for cassava yield per hectare of tonnes was found to be significant at 1%. The output of plantain obtained by credit beneficiaries and nonbeneficiaries in the study area is shown in Table 3. The t test value of was found to be positive and significant at 1%. This implies that the credit beneficiaries in the study area produced significantly more plantain than the non-beneficiaries. Constraints to Loan by Beneficiaries The untimely delivery of loan constituted the greatest constraint as reported by all respondents. This is represented on Table 4. The second major constraint was high interest charged as indicated by 71% of the respondents. In that order, the third constraint which was not as significant accounting for 37% of respondents was insufficient loan volume approved. Other factors that were indicated by respondents include administrative bottle necks in terms of too many forms to fill (15.2%), unfriendly attitude of trust fund workers (13%), high cost of processing loan (10.7%), distance (8.7%), and lack of collateral/guarantor (5.4%). Reasons for not accessing loan by non beneficiaries The non-beneficiaries identified high interest rate and distance as the greatest constraints to acquiring loans; this is seen on Table 5. Distance could pose as a major constraint to loan acquisition to the non-beneficiaries since the Trust Fund Micro Finance Bank was too far for most of them. Next, was untimely delivery of loans (77%) and could lead to delay in loan acquisition. NJAFE VOL. 11 No. 1,

7 Table 4: Constraints to Loan by Beneficiaries Constraints of Respondents Respondents Percentage Untimely delivery of loan High interest rate charged Insufficient loan approval Administrative bottle necks(too many forms to fill) Unfriendly attitude of trust fund workers High cost of processing loan Distance Lack of collateral/guarantor Source: Field Survey, Note: All the respondents were involved in multiple application loan application Table 5: Reasons for not accessing loan by non beneficiaries Constraints of Respondents Respondents Percentage High interest rate % Distance % Untimely delivery of loan 57 77% Insufficient loan approval % Unfriendly attitude of trust fund workers % Too many forms to fill (Administrative bottleneck) % Lack of collateral/guarantor % High cost of processing loan 5 6.8% Source: Field Survey, Note: All the respondents were involved in multiple application loan application This delay ultimately affects production. Emerole (1995) identified untimely release of fund, cumbersome loan procedure etc as constraints that reduce the ability of clients to repay loans. This conformed to the finding of Olomola (2001) that delay in credit disbursement increases delinquency in borrows. Oke et al. (2007) proved that a day delay in micro credit disbursement will eventually reduce loan repayment rate by 0.98 percent. Furthermore, Emerole (1995) recommended that it is ideal for loan to be disbursed to farmer before the on-set of the farming period. Other constraints identified include insufficient loan approval, unfriendly attitude of Trust Fund workers, administrative bottle necks, lack of collateral/guarantor and high cost of processing loan. CONCLUSION This study showed that there is significant impact of Trust Fund credits on the crop production. The loans accessed were found to play significant roles in increasing the yields of the farmers. From the research findings, it is recommended that a reduction in the interest rate of 36% will encourage the farmers to access loan and repayment will be easy for them. This could be achieved if the government introduces a regulatory interest rate. Also, government should ensure the steady release of loan facilities to Micro Finance Banks to enable them release enough funds to farmers whenever needed. Also, loan should be disbursed to farmers before the onset of the farming season to address the issue of untimeliness in the disbursement of TrustFund Microfinance loan. REFERENCES Adisa. B. And Okunade, E. O Women in agricultural Extension. In Adedoyin, S.F (ed.) Agricultural Extension in Nigeria. Ilorin: Agricultural Extension. Society of Nigeria.pp Acha, I. A Borrowing Cycle: Alternative Micro financing Model for Nigeria. African Journal of Entrepreneurship, 1(3), Akpan, I Fundamentals of Finance (3 rd ed.) Uyo: Abaam Publishing Co. pp Akangbe, J. A., Ogunyinka, W., Ayanda, I. F., Achem, B. and Adisa, R. S An Assessment of Effects of Fadama II Project on Livelihood of Farmers in Orire Local Government Area of Oyo State, Nigeria. Nigerian Journal of Agriculture, food and Environment, 8(1) Asiabaka, C. C Agricultural Extension: A Hand book for Development practitioners. Omoku, Molsyfem United Services. NJAFE VOL. 11 No. 1,

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