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Asian Journal of Business and Management Sciences Vol. 1 No. 9 [01-08]

Microfinance and Small Scale Pig Business in Osun State, Nigeria Idowu, Adewunmi O. (Corresponding Author) Department of Agricultural Economics and Farm Management Olabisi Onabanjo University, Yewa Campus, Ayetoro, Ogun State, Nigeria. E-mail: [email protected] Ambali, Omotuyole I. Department of Agricultural Economics and Farm Management Olabisi Onabanjo University, Yewa Campus, Ayetoro, Ogun State, Nigeria. Otunaiya Abiodun O. Department of Agricultural Economics and Farm Management Olabisi Onabanjo University, Yewa Campus, Ayetoro, Ogun State, Nigeria.

ABSTRACT The study empirically examined the effect of microfinance on piggery business in Osun State, Nigeria. There hundred and twenty (320) pig farmers were sampled from Osun State in a multi-stage sampling process through a structured questionnaire. The data collected were analyzed using descriptive statistics and Tobit regression. This study revealed that majority of the piggery farmers are still in their active age (66% are below 50 years), married and educated (26% had first degree). Also, majority of the farmers sourced for loan through cooperative society and have stocking of pens as primary motive. The Tobit result revealed that level of education, years of experience in piggery farming and number of pigs had significant positive effect on fund security. Interest rates on loans obtained should be reduced while the quality and quantities of input should increase. As a policy option, financial institutions and cooperative societies need to relax the transaction cost associated with loan procurement. Above all, more funds should be made available to piggery farmers at minimum cost to increase the output of the piggery industry. Keywords:

Piggery, transaction microfinance

cost,

fund

security,

fund

intensity

and

INTRODUCTION Pork is a source of meat which has high nutritional value particularly in the supply of fat that is rich in energy. The piggery industry also provides employment opportunities for the populace, thereby serving as a source of income to the Nigerian people because of the high prolific nature of pig. One of the advantages of the piggery industry is that feed materials are often industrial wastes which are easily obtained at low cost. The industry faced challenges ranging from religion to poor financing.

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Asian Journal of Business and Management Sciences Vol. 1 No. 9 [01-08]

Efforts to deliver formal credit and financial services to the rural poor in developing countries have failed over the years (Adams, 2009). Commercial banks generally do not serve the needs of the rural poor because of the perceived high risk and the high transaction costs associated with small loans and savings deposits. To fill the void, many governments have tried to deliver formal credit to rural areas by setting up special agricultural banks or directing commercial banks to loan to rural borrowers. However, these programs have almost failed because of the political difficulty for governments to enforce loan repayment, and because the relatively wealthy and powerful, rather than the poor, received most of the loans (Adams et al. 1984, Adams and Vogel, 1986). In Nigeria, credit has been recognized as an essential tool for promoting Small and Micro Enterprises (SMEs) (Morduch, 1999; Olaitan, 2001). About 70 percent of the population is engaged in the informal sector or in agricultural production, piggery inclusive. The Federal and State governments in Nigeria have recognized that for sustainable growth and development the financial empowerment of the rural areas is vital, being the repository of the predominantly poor in society and in particular the SMEs (CBN, 2005; Akinbogun, 2008; Ayanda and Adeyemi, 2011). If this growth strategy is adopted and the latent entrepreneurial capabilities of this large segment of the people is sufficiently stimulated and sustained, then positive multiplier effects will be felt in the economy. To give effect to these aspirations various policies have been instituted over time by the Federal Government to improve agricultural production capabilities, positively channel the potential of SMEs to enhance people standard of living and to put the sector in the front burner of Government’s development strategy (Olaitan, 2001; Akinbogun, 2008; Ayanda and Adeyemi, 2011). Microfinance—the provision of financial services such as small loans to the world’s poor—has grown in the past decade, extending billions of dollars in credit to tens of millions of people. The major aim of the microfinance movement is to provide funds for investment in micro businesses, thus lifting people out of poverty and promoting economic growth. Recent experience and the economic history of rich countries, however, suggest that those expectations are unrealistic (Ledgerwood, 1999; Morduch, 1999; Mejeha, et al, 2007). Most people, poor or otherwise, are not entrepreneurs, so there is little reason to think that mass credit would in general lead to viable business start-ups. Today as in the past, business startups in the advanced countries depend predominantly on savings and informal sources of credit; past forms of microcredit never played a role in small business development, and much microcredit is actually used for consumption rather than investment. In the history of today’s rich countries, moreover, economic growth occurred first, and then came credit for the masses. That credit was and is predominantly for consumption rather than investment (Olaitan, 1997; Otero and Rhyne, 1994; Mejeha, et al, 2007). Microfinance activities come in many shapes, but generally focus on savings and credit, although some institutions also provide insurance and payment services as well as social intermediation services (Adjei et al, 2009). Access to credit is probably the most common type of microfinance services and Micro finance consists of short-term, small-scale loans and the providers are generally NGOs, credit unions, savings and loan cooperatives, government or commercial banks, or non-bank financial institutions (Mejeha, et al, 2007). Microfinance nevertheless has the potential of reaching both urban and rural areas to a greater extent than any macroeconomic development strategy generally does on its own. Clients are usually selfemployed, low-income entrepreneurs such as small-scale farmers, traders, street vendors or small-scale producers. Microfinance can also be part of a strategy to ensure that development aid actually reaches the entire community, this by targeting poor and often marginalized households who engaged in one form of small business or the other (Mejeha, et al, 2007; Adjei et al, 2009). Piggery business is important in this respect because it is both small-scale business (practice in urban and rural area) and commercialized business. This necessitates this study to examine the socio-economic characteristics of the small-scale pig business owners as well as the determinants of micro-financing among the piggery farmers.

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Asian Journal of Business and Management Sciences Vol. 1 No. 9 [01-08]

METHODOLOGY The Study Area Osun State was carved out of Oyo State on 27th August, 1991 with Osogbo as the state capital. The state shares interstate boundaries with Kwara State in the North, Ogun state in the south, Oyo state in the west and Ondo state in the east. The state has a landmass of about 9,251 km². It is currently made up of 30 Local Government Areas (LGAs) spread across six main zones – Osogbo, Ede, lwo, lkirun, llesha and lle-ife. These zones were further divided into 3 agricultural zones by Osun State Agricultural Development Project (OSSADEP) viz Osogbo, Iwo and Ife/Ijesha. Estimates in the recently released provisional figures of the 2005 census put Osun State human population at 4.137627million (NBS, 2006) as at March 2005. Osun State is located in the heartland of the Yoruba people and shares the distinctive high urbanization attributes of most parts of Yoruba land with Yoruba as the main dialect. The state exhibits the typical tropical climate with prominent wet and dry seasons with fertile soil which encourages the production of crops and livestock. The rainy season generally occur between April and October while the dry season occurs between November and March. The mean annual temperature for the state varies between 21.1c and 31.1c. The mean temperatures are highest at the end of the harmattan, which is from the middle of January to the onset of the rains. Rainfall figures over the state vary from an average of 1000mm in the derived savannah agroecology to 1200mm in the rain forest at the onset of heavy rains to 1600mm at its peak in the rain forest part of the state. Sampling Technique Multistage sampling method was adopted to select 320 pig farmers used for the study. The first stage involved the selection of two (2) agricultural development zones from the State (shown in figure 1). The zones selected include Iwo and Ife/Ijesha. The second stage involved the selection of four (4) blocks from each of the zones selected in stage one. The blocks selected include Olaoluwa, Iwo, Aiyedire and Aiyedaade in Iwo zone and Obokun, Ilesha East, Ife East and Atakumosa East in the Ife/Ijesha zone. The third stage involved the selection of two (2) cells from each of the blocks selected in stage two. In the last stage, 10 pig farmers were randomly selected from each of the cells giving a total of 320 pig farmers used for the study. Out of the 320 questionnaires collected, 300 of them were found useful for analysis while the remaining 20 were discarded due to incomplete information. Information was sought on the socioeconomic characteristics of the piggery farmers, their sources and level of access to micro-finance. Analytical Procedure Data collected was analysed using descriptive statistical tools such as frequency and percentage. This was used for the socio-economic characteristics of piggery farmers. Tobit regression model was used to identify the determinants of micro-finance among the piggery farmers. The Tobit Regression Model Following McDonald and Moffit (1980) as adapted by Adesina and Baidu-Forson (1995) and Akanni (2007), the Tobit regression model is implicitly specified as: MFi = βi Xi + εi

(1)

Where: MFi = Probability of adequate micro-financing or volume of financing (Fund Security Index), for Gi ≥ Z; MFi = is continuous if MFi ≥MFo; MFi= 0 if MFi ≤ MFo; MFo = the nonobservable threshold level. Xi = Vector of explanatory variables; βi = Vector of respective parameters; εi = independently distributed error term.

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Asian Journal of Business and Management Sciences Vol. 1 No. 9 [01-08]

MF= Volume of financing/funding (Naira) Z = Fund Insecurity line Gi = Intensity of Micro-financing which is defined as: (Wi - Yi) / Wi and, Wi = Optimum funding level (Naira) Yi = Mean Piggery farm per capital expenditure (N). To be fund secure, a piggery farm (small scale) required about N 1.0 million per annum. This takes care of daily upkeep, purchase of vaccines, feeds, piglets and settlement of overhead costs. Any farm operating below this line was therefore categorized as operating below the fund secure line. The set of explanatory variables which describe the effect of the use of micro finance on the output of piggery farms are: X1 = Age (years); X2 = Educational Status (years); X3 = Piggery Farming Experience (Years); X4 = household Size (No); X5 = Interest rate (%); X6 = Number of Pigs (No); X7 = Total Annual Expenditure (Naira); X8 = Gender of Piggery Farmers (1for Male and 0 if otherwise); X9 = Value of Inputs e.g. feeds, drugs, water etc (Naira). RESULTS AND DISCUSSION Socio-economic Characteristics of Piggery Farmers This section explains the socio-economic characteristics of piggery farmers as these variables are believed to have direct and indirect effects on production activities of the piggery farmers. Table 1 reveals the socio-economic characteristics of piggery farmers in the study area. The age of the farmers is an important factor that affects the roles played by microfinance on level of productivity and overall coping ability in pig business. Age is also believed to influence the level of physical work and the willingness to take risk. Majority of the respondent (43.0%) were aged between 30-50 years while 23% were below 30 years of age. This implies that majority of the respondents are still in their active labour age to cope with the drudgery nature of pig production and easily adopt innovation that would enhance production. Eighty percent of the piggery owners were male showing that pig production in the study area was dominated by men. Table 1: Distribution of sampled piggery farmers by personal characteristics Socio-economic Variables Frequency Percentage (%) Age of the Piggery Farmers Below 30 69 23.0 30 – 50 129 43.0 51 – 70 99 33.0 Above 70 3 1.0 Total 300 100.0 Gender of the Piggery Farmers Male 240 80.0 Female 60 20.0 Total 300 100.0 Family size of the Piggery Farmers 1-5 228 76.0 6-10 72 24.0 Total 300 100.0 Farming experience of the Piggery Farmers Below 5 153 51.0 6 – 10 54 18.0 11 – 15 57 19.0

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Asian Journal of Business and Management Sciences Vol. 1 No. 9 [01-08]

16 – 20 27 Above 20 9 Total 300 Marital status of the Piggery Farmers Married 243 Single 30 Divorced 27 Total 300 Education level of the Piggery Farmers No formal education 36 Primary education 42 Secondary education 69 NCE/ND 54 Bsc/HND 78 Post Graduate 21 Total 300 Sources of fund for the Piggery Farms Micro finance bank 102 Cooperative Societies 156 Friends and Relatives 18 Money lenders 21 Others 3 Total 300 Reasons for borrowing money among piggery farmers Stocking of pen 135 Feeding 108 Expansion of pen 45 Others 12 Total 300 Source: Computed from Survey Data, 2010

9.0 3.0 100.0 81.0 10.0 9.0 100.0 12.0 14.0 23.0 18.0 26.0 7.0 100.0 34.0 52.0 6.0 7.0 1.0 100.0 45.0 36.0 15.0 4.0 100.0

Earlier studies (Matlon, 1998; Olayode et.al 2005) stated that household is a unit of decision making that consists of people who feed from the same pot. Majority (76%) of the respondents were having household size of 1-5 while 24 % were having household size between 6-10 family members. This implies that the labour requirements of pig business can be easily obtained from family source, if so required. The farming experience of a farmer can be a useful guide in the use of inputs and in taking farm management decision. Majority (51%) of the respondents had below 5 years farming experience in pig rearing or livestock, showing that pig production in the area is still gaining momentum, while 3% of the respondents had over 20 years of experience. Education is an important factor in the recognition and utilization of investment opportunities (Islam and Choe, 2009; Stampini and Davis, 2009). The study revealed that most of the pig farmers were found to have some form of formal education. Seventy four percent of the pig farmers had secondary education and above while 12 % possessed no formal education, implying that the pig farmers would have greater tendency of adopting new innovations for farm growth. Majority (81%) of the farmers were married with medium household size. This may urge them to opt for financial assistance in order to keep the farm and family responsibility which will make them to enhance the level of their pig business. As shown in the above table, 52% of the pig farmers sourced for fund from cooperative society while 34% got fund from micro finance banks, for different pig farming purposes ranging from stocking of pen (45%), for feeding the pigs (36%) and for expansion of the pens (15%).

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Asian Journal of Business and Management Sciences Vol. 1 No. 9 [01-08]

Determinants of the use of microfinance Following Akanni (2007), the Tobit regression model was used to identify the determinants of the use of microfinance by the piggery farmers (Table 2). It measured the parameters of the conditional probability of having access to the required level of funds and the marginal changes in explanatory variables on the micro finance status of the piggery units. The finance classification of the piggery farms followed the method used by Akanni (2007), the piggery farms were classified into adequately financed (MFi) and inadequately financed (MF0) group using the fund insecurity line measure (Z). Table 2: Tobit Regression Result on the Determinants of Micro-credit Use among Piggery Farmers Variable/Parameter Coefficient Standard Prob. of Fund Intensity of error Security micro-financing Constant -0.034*** 0.011 0.087 0.0098 Age -0.045** 0.022 0.003 0.0121 Educational level 0.061* 0.032 0.065 0.0043 Piggery farming experience 0.059** 0.025 0.048 0.0027 Household size -0.0098*** 0.0021 0.670 - 0.054 Interest rate -0.067** 0.032 0.069 0.037 Number of pigs 0.132** 0.052 0.091 0.009 Total annual expenditure 0.411 0.398 0.112 0.043 Gender of piggery farmers 0.087 0.069 0.099 0.0016 Value of inputs 0.231 0.199 0.118 0.161 Sigma 0.116 Log- Likelihood -441.123 LR chi2 52.47*** *,**,*** indicate significant level at 10, 5, 1 % respectively. Dependent Variable: Fund security index. Source: Computed from Survey Data, 2010 The regression parameters and diagnostic statistics were estimated using the maximum likelihood estimation (MLE) method (Table 2).The results showed that six dependent variables had significant influence on the fund insecurity status of the piggery farms. The sigma (σ) value was 0.116 and log likelihood function of -441.123, while the LR chi square was 52.47. The significant variables are age, educational level, years of experience in piggery farming, household size, interest rate on loans and number of pigs. Positive sign on a parameter indicated that higher values of the variables tend to reduce the likelihood of fund insecurity. Also, a negative value of a co-efficient implied that higher values of the variables would increase the likelihood of fund insecurity. Observing the variables individually, age of the farmer, household size and interest rate with negative signs agreed with the a priori expectations. Other variables like the education level, experience in poultry keeping, number of pigs and total annual expenditure had positive coefficient and thus agreed with the a priori expectations. While the age, piggery farming experience, interest on loan and number of pigs are significant at 5 percent, education and household size are significant at 10 percent and 1 percent, respectively. The fund security was highest for household size (0.67) and least for age (0.003). This implies that increasing the family labour in piggery production was the best option. Intensity of financing was highest for input usage (0.161) and least for gender (0.0016). The implication of this is that input procurement and usage attracted highest funding in the piggery business.

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Asian Journal of Business and Management Sciences Vol. 1 No. 9 [01-08]

CONCLUSION AND RECOMMENDATION Inadequate finance has been identified as a bane to agricultural development. This study revealed that majority of the piggery farmers are still in their active age, married and educated. Most of the farmers sourced for loan through cooperative society and have stocking of pens as primary motive. For the piggery farmers to be fund secured there is need for improvement on level of education, years of experience in piggery farming and number of pigs. Interest rates on loans obtained should be moderate and affordable while the quality and quantities of input facilities should increase. As a policy option, financial institutions and cooperative societies need to relax the transaction cost associated with loan procurement. Above all, more funds should be made available to piggery farmers at minimum cost to increase the output of the piggery industry. REFERENCES Adams, D. and Vogel, R. (1986): Rural Financial Markets in Low Income Countries: Recent Controversies and Lessons. World Development, 14(4): 477-487. Adams, D. (2009): Easing Poverty through Thrift. Savings and Development 33(1): 1–13. Adams, Dale, Douglas, H. and Von Pischke, J.D. (1984): Undermining Rural Development with Cheap Credit. Boulder, Co: Westview Press. Adesina, A. A. and Baidu-Forson, J. (1995): Farmers’ perception and adoption of New agricultural technology: evidence from analysis in Burkina Faso and Guinea, West Africa. The Journal of International Association of Agricultural Economics, 13(1):1-9. Adjei, J.K., Arun, T and Hossain F. (2009): The Role of Microfinance in Asset-Building and Poverty Reduction: The Case of Sinapi Aba Trust of Ghana. BWPI Working Paper 87; University of Manchester. Akanni, K.A. (2007): Effect of micro-finance on small scale poultry business in South Western Nigeria. Emir Journal of Food Agriculture, 19 (2): 38-47. Akinbogun T.L. (2008): The Impact of Nigerian Business Environment on the Survival of Small Scale Ceramic Industries: A case Study of South-western Nigeria. Journal of Asian and African Studies, 43(6): 663-679. Ayanda A.M and Adeyemi T.L. (2011): Small and Medium Scale Enterprises as a Survival Strategy for Employment Generation in Nigeria. Journal of Sustainable Development, 4(1): 200-206 CBN (2005): Central Bank of Nigeria Annual Reports and Statement of Accounts. Federal Government of Nigeria (1998): Agricultural Credit Guarantee Scheme Decree No. 20, 1998: Agricultural Credit Guarantee Scheme (Amendment Decree No.18 of 1998). Islam, A. and Choe, C. (2009): Child Labour and Schooling Responses to Access to Microcredit in Rural Bangladesh. Department of Economics working paper 5, Monash University, Australia. Ledgerwood, J. (1999): Microfinance Handbook: An Institutional and Financial Perspective. Sustainable Micro-credit Summit Report 1997 Matlon, P. (1998): The ICRISAT Burkina Faso Farm level studies; Survey Methods and data files. Economics Group, VLS and Miscellaneous Paper Series. ICRISAT, Hyderabad, India. Mejeha, R.O., Iheke O.R. and Afonne, G (2007): Effect of Microfinance Service on Savings, Investment and Output in Abia State of Nigeria. Pakistan Journal of Social Sciences 4(4): 559-564. Morduch, J. (1999): The role of subsidies in microfinance: evidence from the Grameen Bank National Bureau of Statistics- NBS (2006): 2006 Population Census. National Bureau of Statistics: Federal Republic of Nigeria, Abuja. Okoli, E. (1991): The State of livestock industry in Nigeria. EK-OVET Magazine of Nigerian Veterinary Medical Association (NVMA), Lagos State Branch, 6(1):30-32. Olaitan, M. A. (1997): Factors Influencing Repayment Patterns under the ACGS in Ogun State, Nigeria. Unpublished Ph.D Dissertation, University of Ibadan, Ibadan, Nigeria. Olaitan, M.A. (2001): Emerging Issues on Micro and Rural Financing in Nigeria. Bullion, 25(1): 64-71 January/March.

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Otero, M., and E. Rhyne, eds. (1994): The New World of Microenterprise Finance: Building Healthy Stampini, M. and Davis, B. (2009): Does non-agricultural labour relax farmers’ credit constraints? Evidence from longitudinal data for Vietnam. Agricultural Economics, 40(2): 177- 188.

Olorunda

Ila

Odo-Otin Ifelodun

Ifedayo

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Boripe Egbedore

Ola-Oluwa

Obokun

Osogbo

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Aiyedire

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Ife Central Iwo Agricultural Zone

Ife North Irewole

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Isokan

Aiyedaade

Ife South

20

Atakumosa East

Ife/Ijesha Agricultural Zone

Ife/Ijesha Agricultural Zone Iwo Agricultural Zone Osun State

0

20 Kilometers

Figure 1: Map of Osun state showing the sampled Agricultural Blocks in Iwo and Ife/ Ijesha Agricultural zones

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