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JOURNAL OF RESEARCH IN NATIONAL DEVELOPMENT VOLUME 6 NO 2, DECEMBER, 2008

LOAN REPAYMENT AMONG MICROFINANCE COOPERATORS OF THE NIGERIAN AGRICULTURAL COOPERATIVE AND RURAL DEVELOPMENT BANK (NACRDB) IN ANAMBRA STATE
           
C.O.A. Ugwumba and   E.L.C. Nnabuife   
 Faculty of Agriculture, Anambra State University, Igbariam Campus
and
P.C.  Ike
 Department of Agricultural Economics & Extension, Delta State University, Asaba Campus

 

Abstract
This study investigated loan repayment by microfinance cooperators of the Nigerian Agricultural Cooperative and Rural Development Bank (NACRDB) in Anambra State. Descriptive statistics and multiple regression were employed in data analysis. Results showed that majority of the cooperators were 41 years and above, suggesting a strong peer influence in group formation. Mean annual income, expenses and savings were N102,763.00, N101,620.00 and N8,750.00 respectively implying a poor savings culture. Seventy one percent of the cooperators repaid more than 62% of their loans as at when due. Eight variables- amount of loan, borrowed, positive socio-cultural activities, access to business related information and amount spent on business investment were significant and positively correlated to repayment; while distance between dwelling place and bank, number of days between loan application and disbursement and poverty level influenced repayment negatively but were equally significant. The F-value (11.39) was highly significant. Policy issues should be tailored towards: sustaining the group lending strategy, increasing loan sizes, reducing administrative costs as well as time lag between loan application and disbursement among others. The cooperators on their part should scale down on wasteful socio-cultural expenses and embrace savings culture.

Keywords: Microfinance, loan repayment, cooperators, NACRDB


Introduction
Lack of access to credit is generally seen as one of the main reasons why many people in developing economics remain poor. Usually the poor have no access to loans from the banking system because they cannot put up acceptable collaterals and/or because the costs for banks of screening and monitoring the activities of the poor and enforcing their contracts are too high to make lending to this group profitable (Hermes and Lensink, 2004). However, access to financial services as opined by Ehigiamusoe (2005), enables the poor household to move from everyday for survival to planning for the future, investing in better nutrition, children’s education and health and empowering women socially.

Microfinance is acknowledged as one of the prime strategies to achieve the Millennium Development Goals (MDGs) (Iganga, 2007). It involves the supply of loans, savings and other basic financial services to the poor (Ehiagiamusoe, 2005; Iweala, 2005 and Kimotha, 2005). Over the years, in Nigeria, as classified by Olomola (2001); formal and informal institutions have been involved in the provision of micro credit.

One of the formal, government microfinance institutions playing active role in credits provision for poverty alleviation is the NACRDB. The bank is an amalgam of the former Peoples Bank of Nigeria, the Nigerian Agricultural and Cooperative bank (NACB) and the Family Economic Advancement Programme (FEAP). It was set up to finance agriculture as well as small and medium enterprises (Anyanwu, 2004). Since 2003, the bank’s focus has been on funding the development of micro enterprises through joint liability group lending or cooperative societies to increase participation of the poor and enhance repayment rates which may contribute to improving the sustainability of microfinance programmes (Akanyi, 2002; Anyanwu , 2004; Oke et al, 2007; Cassar et al, 2007; Cull et  al, 2007).

Loan repayment is a necessary ingredient for sustaining the microfinance programme. Chiawa (1997) specified a Probit Model to assess the determinants of the

probability of credit repayment among small holders in Malawi. Only five factors (sales of crops, size of group, degree of diversification, income transfer and the quality of information) were consistently significant determinant of agricultural credit repayment. Four independent variables – gender, amount of loan, club experience and household size were not statistically significant in various specifications.

Oni (1999) studied the proportion of loan repayment by small holder farmers in Ogun State. His explanatory variables were: Amount of loan collected, expenditure on farm, interest rate, extent of farmers contact with bank, disbursement lag, cultivated land area and years of experience in farming. The result of linear and log form equations showed that the regression coefficients associated with amount of loan(+), disbursement lag (-) and extent of farmers contact with banks(-) had expected signs and were statistically significant at 5 percent.

Oke et al (2007) examined the factors that influenced micro credit repayment among members of microfinance non-governmental organizations (NGOs) in South Western Nigeria. Ten out of the twenty-three (23) variables that went into the multiple regression model were significant (p = 0.001 or p = 0.05). They are: income, distance between dwelling place and bank, amount of business investment, socio-cultural expenses, amount of loan borrowed, access to business information, penalty for lateness to group meetings, membership of cooperative society, number of days between loan application and disbursement and poverty indicator.

 

This study was undertaken to examine the influence of the ten significant variables mentioned in Oke et al (2007) on micro credit repayment among cooperators of a government owned bank, the NACRDB, in Anambra State.

Methodology
The survey covered the Central Senatorial Zone of Anambra State made up of 7 Local Government Areas. A list of about 95 cooperative societies that obtained facilities from the NACRDB was used for the study. Three cooperative societies and ten cooperators per society were selected from each of the Local Government Areas  by Multistage Stratified Random Sampling.  At least, a total of 210 cooperators emerged. A structured questionnaire tested of validity and reliability was employed to elicit information from the respondents on age, sex, occupation, educational background, family size, income, consumption expenditure (on food, medicare, children education and energy), social expenses (on ceremonies, religious obligations, social clubs, extended family), savings, amount of credit and its uses, micro credit disbursement lag, micro credit repayment and interaction with credit institution.

Descriptive statistics were used to summarize socio-demographic variables of the respondents while multiple regression model adopted by Gujarati (1995) was used to determine the order of influence of the explanatory variables in explaining the variations observed in the dependent variable. The t – test was performed to test the significance of each of the explanatory variables at alpha levels of one, five and ten percent.


The model is specified thus: MRP = 0+  *1IHH + *2DDB +  *3AB1 + *4SCE + *5ALB + *6AB1 + *7PLATE + *8MCB + *9D1SLAG +  *10PI + e
Where,
MRP    =          Proportion of microfinance repaid on the date
when  repayment falls due.
IHH                 =          Income of respondent in 2006 (N)
DDB                =          Distance between the dwelling unit of
respondent and the nearest NACRDB branch office
ABI                  =          Amount of business investment in the
year 2006 (N)
SCE                 =          Socio-cultural expenses (N)
ALB                 =          Amount of loan obtained in year 2006 (N)
QBI                  =          Quality of business information (0 = No/poor
information and 1 = good information).
PLATE =          Amount paid as penalty for lateness (N)
MCS                =          Membership of cooperative society

DISLAG          =          Loan disbursement lag, defined as the number
of days between the submission of loan application and actual loan collection.
PI                     =          Poverty indicator (PI = 1 if expenditure is less
than two-third of mean expenditure and 0 otherwise).
e                      =          Error term
 *0                    =          Intercept
 *i                     =          Coefficient of explanatory variable (i =1,2,…,10)


Results and Discussion
Socio-demographic Background of Selected Cooperators
The study indicated that there were more female cooperators (58%) than the males (42%). Again majority of the cooperators (62%) were 41 years and above. This later fact suggests a very strong peer influence in group formation. Though many respondents attributed the minor participation of younger people to youth migration to the urban centres in search of white collar jobs and better social life.

All the cooperators had one form of formal education or the other meaning that they can readily adopt new technological packages in order to improve their businesses. Seventy percent of them were married with majority (61.7%) having between 0 – 7 children.

Business Enterprises
The cooperators engaged in diverse ventures including farming and non-farming (Table 1). However, farming activities were less patronized (48.0%) than non-farming ventures (52.0%). Notably, men shared a greater percentage of the farming businesses while the females were more than the men in non-farming businesses.


Table I: Business Enterprises of NACRDB Cooperators Business Type


Farming

Percentage

Non-Farming

Percentage

Arable Cropping

17.5

Trading

16.2

Tree cropping

9.2

Food processing

15.2

Vegetable production

1.6

Soap making

1.4

Fishing

4.1

Basket making

4.2

Fish Farming

3.2

Carving

2.2

Poultry

7.3

Transportation

7.2

Other livestock

5.1

Others

7.6

All Farming

48.0

All non-farming

52.0

Source: Field survey


Non-farming businesses of the cooperators ranged from Trading (16.2%), food processing (15.0%) to soap making (1.4%), while farming businesses ranged from Arable cropping (17.5%). Tree cropping (9.2%) to vegetable production (1.6%).

Loan Disbursement to Cooperators in 2006
The focus of NACRDB from 2006 was to fund the development of micro enterprises through joint liability group lending or cooperative societies to increase participation of the poor. Individuals belonging to the various groups draw from the joint account opened with the bank to execute their specific projects. Table 2 below shows the different ranges of micro finance borrowed by the cooperators in 2006.


Table 2: Borrowings of Cooperators


Amount borrowed in 2006

Frequency

%

1 – 10,000

32

16

10,001 – 50,000

102

51

50,001 – 100,000

50

25

100,001 – 250,000

14

7

250,001 +

.2

1

 

 

 

Total

200

100

Minimum

10,000

 

Maximum

250,000

 

Mean

51,900

 

Median

48,000

 

Standard Deviation

49,070

 

Coefficient of variation

94.5

 

Source: Field survey


Members borrowed between N10,000.00 and N250,000.00 with majority (51%) falling within the range of N10,000.00 and N50,000.00 and only two applicants accessed N250,000.00 probably for livestock business.

Business Investment, Annual Income, Savings
The cooperators realized annual income as returns from business investment and other sources as presented in Table 3. The poorest member earned N32,240.00 while the richest earned N496,600.00 meaning that the cooperators embraced enterprise diversification as insurance against business failure. Greater percentage of the members (76.5%) earned below N150,000.00 while the mean income was N102,763.00.


 

Table 3: Annual Income of NACRDB Cooperators


Income (N)

Frequency

%

1 – 50,000

32

16.10

50,001 – 100,000

71

35.50

100,001 – 150,000

50

25.0

150,001 – 200,000

27

13.5

200,001 – 250,000

14

7.0

Above 250,000

11

5.5

Total

200

100

Minimum

32,240

 

Maximum

496,600

 

Mean

102,763

 

Median

72,136

 

Standard Deviation

71,567

 

Coefficient of Variation

69.64

 

Source: Field survey


Members invested between N12,500.00 and N250,000.00 with about 31% investing more than N50,000.00 in their businesses. This suggests that there was a low level of investment which Zeller, et al (2001) and Oke et al (207) identified as characterizing the rural economy.

The cooperators had no good saving culture as reflected in the mean saving figure of N8,750.00. This figure is too low compared to an average member’s investment of N31,000.00. On the other hand, consumption expenditure was high, averaging N101,620.00. A reflection of the increasing cost of living in the society. Low savings figure recorded by the cooperators could equally be attributed to high socio-cultural expenses with mean value of N24,650.00.

Microfinance Repayment of the Cooperators and Regression Results
Empirical analysis of data collected showed that 71% of the cooperators repaid more than 62% of their micro credit as at when due. These figures are lower than the 88% and 70% respective values recorded by Oke et al (2007) meaning that there were higher rates of default by cooperators of the government bank (NACRDB) than what obtained in the NGO’s where better methods of enforcing repayment probably exist.


Table 4: Regression Output of Micro credit Repayment Model


Variable

Client’s Model

Constant

76.58 (8.27) ***

IHH

4.98 (2.35) ***

DDB

-1.04 (-3.11) ***

ABI

2.63 (3.12) ***

SCE

1.04 (2.48)**

ALB

1.24 (2.38)***

QBI

24.48 (.4.67) ***

MCS

0.18 (1.65) **

DISLAG

-0.92 (-2.99 ***

PI

-0.40 (-2.01) **

PLATE

- 0.22 (-1.82)**

R2

0.32

Adjusted R2

0.28

F – value

11.39

 


Results of the multiple regression analysis are shown in Table 4. The F – value was highly significant implying that the model is a good fit. The adjusted R2, 0.28, indicated that the variables in the model were able to explain 28 percent of the variability in percentage loan repayment (MRP). This R2 was lower than the 0.26 reported by Oke et al (2007) for loan repayment among members of microfinance NGOs in South Western Nigeria.

Eight out of the ten variables were statistically significant. They are: Income (1HH), amount of loan borrowed (ALB), distance between dwelling place and bank (DDB), amount of business investment (ABI), socio-cultural expenses (SCE), quality of business information (QBI), loan disbursement lag (DISLAG) and poverty indicator (PI). IHH is positively correlated with repayment implying that a N100,000.00 increment in income will increase repayment rate by 4.98%. Amount of loan borrowed (ALB) was positive and significant meaning that an additional naira of loan obtained will raise repayment rate by 1.24%. Thus, making more credits available to the cooperators will increase their productivity and consequently their income and repayment capacity.

The variable (DDB) was inversely related to repayment and as such 1km increase between dwelling place and bank will reduce repayment by 1.04%. The variables, SSE, QBI and ABI were significant and positively related to repayment meaning that spending on positive socio-cultural activities, having access to business related information and increasing the amount spent on business investment will increase repayment rate by 1.04%, 24.48% and 2.63% respectively.

Another two variables, DISLAG and PI had negative relationship with repayment though the negative sign of DISLAG did not conform to theoretical expectations. Consequently, an increase in the number of days between loan application and disbursement will reduce repayment. Likewise the poorer the cooperators, the more difficult it is to repay.

Conclusion and Recommendation
The study on Loan Repayment among Cooperators of the NACRDB in Anambra State identified that there were more female cooperators (58%) than males (42%). Majority of the cooperators were 41 years and above suggesting a strong peer influence in group formation. The cooperators had some form of formal education.

The cooperators invested their loans in various businesses, both farming (48%) and non-farming (52%). Membership of a society was a condition for bank’s approval of micro credit. Mean annual income, expenses and savings were N102,763.00, N101,620.00 and N8,750.00 respectively implying a poor savings culture. Seventy one percent of the cooperators repaid more than 67% of their loans as at when due.

Amount of loan borrowed was positively related to repayment such that a unit increase will increase repayment by 1.24%. similarly, a unit increase in income will increase repayment by 4.98%. Again, spending on positive socio-cultural activities, access to

business related information and membership of cooperative society will positively influence repayment. However, repayment was negatively influenced by distance between dwelling place and bank, increase in the number of days between loan application and disbursement as well as poverty level.

In order to improve the repayment rate of cooperators, the NACRDB should: continue to implement the group lending strategy which has been proved to enhance repayment and increase participation of the poor and vulnerable; improve on the loan sizes approved for cooperators to enable them to increase investment, income and thus savings; reduce administrative costs as well as time lag between loan application and disbursement; and improve on the provision of quality business information to the cooperators. On the other hand, the cooperators should scale down on deceitful socio-cultural expenses and embrace savings culture.

References

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Anyanwu, C.M. (2004). Microfinance Institutions in Nigeria: Policy,Practice and Potentials. Paper presented at the G24 Workshop on Constraints to Growth in Sub-Saharan Africa. Pretoria, South Africa, No. 29 – 30.

Cassar, A.; Crowley, L. and Wydlick, B. (2007).  The  Effect  of Social Capital on Group Loan Repayment: Evidence from field experiments. Economic Journal, Vol. 117 pp: 85 – 106.

Chiawa, E. A. (1997). An Economic Analysis of Determinant of Agricultural Credit Payment in Malawi, African Review of Money, Finance and Banking Vol. 1 -2: 107 – 122.

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Hermes, N.; Lensink, R. and Melitenb, H.J. (2005). Peer Monitoring, Social ties and Moral Hazard in Group Lending Programme. Evidence from Eritrea. World Development, Vol. 33 (1), pp: 149 – 169.

Iganga, B.O. (2007). An Evaluation of Microfinance Policies and Institutions in Nigeria. Department of Economics, Delta State University, Abraka.

Kimotha, M. (2005). National Microfinance Policy Framework and Expected Impact on the Microfinance Market in Nigeria. Proceedings of Seminar on Microfinance Policy, Regulatory and Supervisory Framework for Nigeria.

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Okonjo – Iweala, N. (2005). The Role of Government in Microfinance Development in Nigeria. Proceedings of Seminar on Microfinance Policy, Regulatory and Supervisory Framework for Nigeria.

Olomola, A.S. (2001). The Nature and Developments of Rural Loan Repayment Performance in Nigeria: The case of FADU’s  Microcredit Programme. NISER Monograph series No. 3, NISER, Ibadan pp. 57.

 

Oni. T.K. (1999). Bank Credit Facilities for Smallholder Farmers: Implications for Food Security in Nigeria. In Fabiyi, Y.L. and E.O. Idowu (eds) Poverty Alleviation and Food Security in Nigeria, Ibadan, N.A.A.E, pp: 342.

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