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International Journal of Trend in Scientific Research and Development (IJTSRD)
Volume 5 Issue 5, July-August 2021 Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470
@ IJTSRD | Unique Paper ID – IJTSRD45009 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 957
Access to Agricultural Credit and Cassava Production:
A Study of Selected Cooperative Farmers in Anambra State
Nwafor, Grace Obiageli; Umebali, Emmanuel E. PhD
Department of Cooperative Economics and Management, Nnamdi Azikiwe University (NAU), Awka, Nigeria
ABSTRACT
This study examined access to agricultural credit and cassava
production: A study of selected cooperative farmers in Anambra
State, Nigeria. This study adopted a descriptive survey research
design that aimed to determine the relationship between the
independent variables and dependent variable in a population. The
population of this study was made up of 2978 members of selected
thirty six cooperative societies in Anambra State. A sample of 353
was determined for the study using Taro Yamani formula. A
structured questionnaire was administered to 353 respondents only
348 responded to the questionnaire. The data collected using the
questionnaire was analyzed using descriptive statistics like
frequency, mean and standard deviation; and also inferential statistics
such as regression analysis and t-test statistics. All analysis was
conducted using SPSS version 23. Findings show that all the five
coefficients (cost of cooperative credit, amount of credit borrowed,
loan repayment period, interest paid and loan repayment
performance) significantly influence cassava production in Anambra
State. In general, the joint effect of the explanatory variables-
independent variables-in the model account for 0.883 or 88.3% of the
variations in the influence of cooperative credit on cassava
production in Anambra State, Nigeria. This implies that 88.3% of the
variations in the cassava production are being accounted for or
explained by the variations in the explanatory variables. While other
independent variables not captured in the model explain just 11.7%
of the variations in cassava production. The study therefore
recommends that credit institutions should supervise and spread the
repayment period for credit obtained in such a way that the cost will
not be heavy. Adequate credit facilities should be provided for
farmers to enable them increase their production capacity. The loan
repayment period for the farmers should be well spread to enhance
their productivity among others. Low interest rate should be charged
farmer to enable them reduce their rate of defaulting repayment.
KEYWORDS: Cost of credit, Amount of Credit Borrowed, Loan
repayment period, Interest Paid Financial Intermediation
How to cite this paper: Nwafor, Grace
Obiageli | Umebali, Emmanuel E.
"Access to Agricultural Credit and
Cassava Production: A Study of
Selected Cooperative Farmers in
Anambra State"
Published in
International Journal
of Trend in
Scientific Research
and Development
(ijtsrd), ISSN: 2456-
6470, Volume-5 |
Issue-5, August 2021, pp.957-962, URL:
www.ijtsrd.com/papers/ijtsrd45009.pdf
Copyright © 2021 by author (s) and
International Journal of Trend in
Scientific Research and Development
Journal. This is an
Open Access article
distributed under the
terms of the Creative Commons
Attribution License (CC BY 4.0)
(http://creativecommons.org/licenses/by/4.0)
1. INTRODUCTION
Agricultural credit has remained a critical input in
agricultural production, thus it is has been describe as
a very significant farm input and has also contributed
a great deal in improving the income of farmers
particularly in developing countries (Linh, Long, Chi,
Tam & Lebailly, 2019). Agricultural credit is a vital
factor in improving agricultural productivity.
Therefore, access to agricultural credit enables
farmers increase their production as well as
guarantees the nations with sustainable food security.
In the process of agricultural development access to
credit is deemed to have positive impact on
productivity since it provides farmers with resources
needed to start the production process. Thus, greater
access to credit can induce agricultural production
and support government program for food security
(Awotide, Abdoulaye, Alene & Manyong, 2015)
IJTSRD45009
International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD45009 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 958
Access to farm credit possess a veryserious challenge
to farmers in Nigeria. Yet, it has been described to be
a critical farm input that enhances productivity of
farmer if adequately supplied (Ukwuaba, Owutuamor
& Ogbu, 2020). In developing countries where the
majority of farmers are resource-poor rural dwellers,
rural credit markets are essential for agricultural
growth and development (Awotide, Abdoulaye,
Alene & Manyong, 2015). However, a number of
factors contain farmers from accessing adequate farm
credit where it is even available. Among the factors
include cost of credit, amount of credit borrowed,
repayment period, interest paid and loan repayment
performance. These challenges are occasioned by
seasonal pattern of farming activities and the various
uncertainties farmers encounter (Aladejebi,
Omolehin, Ajiniran & Ajakpovi (2018). One of the
groups of farmers that encounter the challenge of
access to credit are the cassava farmers and which are
the focus of this study. Adeyemo, Amaza, Okoruwa,
Akinyosoye, Salman and Adebayo (2019) describe
cassava as a food security crop with a potential to
provide off-season calories even on low-nutrient soils
in many developing countries. Consequently, the
important nature of cassava to the growth and
development of Africa and Nigeria in particular
demands that adequate financing and funding of
cassava production is imperative.
Efforts by the present and previous government
including donor agencies to improve agricultural
production and cassava in particular have not yielded
the desired result. Ogbuabor and Nwosu (2017) noted
that "some of the policies include the Nigerian
Agricultural and Co-operative Bank which was
established in the year 1973 as part of government
efforts to inject oil wealth into the agricultural sector
through the provision of credit facilities to support
agriculture and agro-allied industries. Also the Rural
Credit Scheme was introduced in 1977 by the Central
Bank of Nigeria, whereby commercial banks were
required to open rural branches. The Agricultural
Credit Scheme was also set up in 1977 with the
primary aim of inducing banks to increase and sustain
lending to agriculture. There are other policies which
were set up by the federal government and linked up
with commercial banks for the purpose of
encouraging the farmers to produce more food such
as National Food Security Programme, Special
Programme on Food Security Programme and
Fadama which are introduced to diversify agricultural
products into other uses. Another great measure for
improving the flow of credit to the agricultural sector
was an attempt to improve the credit mix by lending
in the form of cash and in kind to farmers".
Despite these measures by the government that is
expected to grow agricultural sector through cassava
production and enable the country feed its growing
population, generate employment, earn foreign
exchange and provide raw materials for industries,
there is still a serious food demand and supply gap.
The country still suffer serious hunger and poverty.
But there is a serious need to address the perceived
serious hunger and poverty challenges in the country
through adequate financing of cassava production in
the country. The cooperative particularly the
agricultural cooperative has been touted by the
government as a vehicle for improving agricultural
production in Nigeria. This is coroborated by Ekwere
(2016) who stated that organization of cassava
cooperative farmers has in recent years become one
of the most important pre-conditions for effective
mobilization of production resources as well as,
accelerates farmer’s progress. It is therefore
imperative to analyze the influence of cooperative
credit on cassava production in Nigeria.
Statement of the Problem
This study was informed by the perceived inability of
the smallholder cassava farmers to easily assess
agricultural credit and also obtain credit at subsidized
rates. This perceived farmers outcry has been a
serious problem militating against viable approaches
to promote worthwhile agricultural-oriented
programmes that will enhance cassava production and
processing in Nigeria. Presently, the problem of food
security and the fight against hunger and starvation
have been a topical issue as most of the developing
countries including Nigeria is struggling to be
liberated from the grip of hunger and starvation. A
number of studies on the importance and influence of
credit on agricultural production have been carried
out by scholars in an attempt to lose grip from the
scorge of poverty (Gbigbi & Achoja, 2019; Chandio,
Jiang, Wei & Guangshun, 2018; Ayegba & Ikani,
2013; Medugu, Musa & Abalis, 2019) but there
seems to be a paucity of research that is carried out on
the platform of cooperative. Again, a critical
evaluation from extant literature revealed that there
are component of credits that can be used as
regressors and regressand (independent variables and
dependent variables) in evaluating the influence of
credit in agricultural production which is lacking in
most of the studies. Some of these variables include:
cost of credit, amount of credit borrowed, repayment
period, interest paid and loan repayment performance.
Considering the importance of cassava to food
security and fight against hunger and poverty; and
also the limited empirical literature on influence of
cooperative credit on cassava production particularly
in Anambra state, this study is therefore vital to
International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD45009 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 959
bridge the literature and knowledge gap, thus
warranting an empirical investigation to analyze
access to agricultural credit and cassava production:
A study of selected cooperative farmers in Anambra
State, Nigeria.
Objectives of the Study
The broad objective of this study is to analyze access
to agricultural credit and cassava production: A study
of selected cooperative farmers in Anambra State,
Nigeria. The specific objectives of the study are to:
A. evaluate the extent to which cost of credit has
influenced cassava production in Anambra State,
Nigeria.
B. examine the extent to which amount of credit
borrowed has influenced cassava production in
Anambra State, Nigeria.
C. determine the extent to which repayment period
has influenced has influenced cassava production
in Anambra State, Nigeria.
D. assess the extent to interest paid has influenced
cassava production in Anambra State, Nigeria.
E. ascertain the extent to which loan repayment
performance has influenced cassava production in
Anambra State, Nigeria.
2. METHODOLOGY
Research Design
This study adopts a descriptive survey research
design that involves asking questions, collecting and
analyzing data from a supposedly representative
members of the population at a single point in time
with a view to determine the current situation of that
population with respect to one or more variable under
investigation (Okeke, Olise & Eze, 2008). Descriptive
survey research design can be quantitative or
qualitative, but this study is quantitative in nature.
According to Micheal, Oparaku and Oparaku (2012),
in a quantitative survey research design, the
researcher's aim is to determine the relationship
between the independent variables and dependent
variable in a population. Quantitative research design
is either descriptive (variables usuallymeasured once)
or experimental (variables measured before and after
a treatment). The questions asked are to elicit
responses that will answer the research questions and
address the objectives of the research.
Population of the Study
The population of the study consist of all the
Members of Farmers Multipurpose Cooperative
societies in Anambra state. Which include Onitsha
North, Onitsha south, Oyi, Ogbaru, Agbaru East,
Anambra West, and Ayamelum for Anambra North,
Ihiala, Nnewi North, Nnewi south, Orumba South,
Orumba North, Aguata and Ekwusigo for Anambra
South, Anaocha, Dunukofia, Njikoka, Idemili South,
Idemili North, Awka North and Awka south for
Anambra Central. Puting the members at 3,557 found
in 214 viable societies. Therefore the population of
this study is 3,557 members in 214 cooperative
societies.
Determination of Sample Size
For various sampling techniques, there are
appropriate sample size determination technique,
which mostly depends on the confidence level, bound
on the error and size of the population. Samples are
meant to represent population when the entire
population cannot be studied. We used a combination
of multi-stage sampling and random sampling
techniques in this work. In multi –stage sampling, the
target population is first divided into first – stage
sampling units. A random sample of these is
thereafter taken. This is in line with Cochran’s (1977)
idea that it is customary to select the first stage
sampling units with the probabilities of selection of
the units proportional to their size and not equal as in
the case of simple random sampling. The first-stage
sampling units, which was selected in this sample, are
then divided into smaller second random sampling
units, which will be sampled again.
Four local governments were randomly selected from
each of the three agricultural zones that make up
Anambra state. The decision to select only four local
governments were largely purposive and for
convenience. The local governments selected include
Dunukofia, Njikoka, Idemili South, and Awka North
from Anambra Central. Ihiala, Nnewi South, Orumba
South and Ekwusigo from Anambra South. Oyi,
Ogbaru, Anambra East and Ayamelum from
Anambra North. From the twelve local governments,
three societies each were selected making a total of
thirty six cooperative societies with membership
strength of 2978. The researcher applied the Taro
Yamani formula to obtain the desired sample size for
the study. The formula is as stated as below:
n = N
1+N (e) 2
Where n is the desired sample size
N= Population
I = Mathematical constant
e= Sampling error (5% in this case).
In this case, n =? (Unknown), N=359, e = 0.05 and I=
constant
Substituting the above values into the formula we
have;
Substituting in the above formula:
International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD45009 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 960
n = 2978
1+2978 (0.05)2
= 2978
1+2978 (0.0025)
= 2978
8.4425
= 352.6
= 353
For the purpose of allocation of sample stratum, the
researcher adopted R. Kumaison's formula. Below is
the R. Kumaisons formula for sample size
distribution:
nh = nNh
N
Where
n = Total sample size
Nh = The number of items in each stratum in the
population
N = Population size
nh = The number of units allocated to each stratum
n = 353
Sources and Method of Data Collection
Survey data were collected from cassava farmers,
who acquire credit or loan from the cooperative
society. The study will make use of both primary and
secondary data. Primary data were collected using
well structured questionnaires to obtain information
from the respondents in the study area and through
oral interview. Secondary data was sourced from
journals, statistical publications, textbooks, articles,
past projects, and the internet.
Description of the Research Instrument
The research instrument used data collection is the
structured questionnaire. It was used to obtain data
from both the cooperative and non cooperative
farmers in the study area. The questionnaire has two
sections: Sections A and Section B. Section A seek
information on the socio-economic background of
respondents while Section B is designed to elicit
information relating to access to cooperative credit,
other sources of credit, cassava output and cassava
revenue, cost of cassava farming and constraints to
cooperative credit access. Out of 353 questionnaires
distributed only 348 were returned.
Method of Data Analysis
Data collected were analyzed using descriptive
statistics (frequencies, percentages, mean, and
standard deviation) and the inferential statistics such
as test statistics and the linear regression model. The
demographic profiles was processed using descriptive
statistics. Thereafter, the seven objectives will be
processed using descriptive statistics (like mean and
standard deviation) and the regression model of the
Ordinary Least Square (OLS). T-test and F-test
statistics was used to test the hypotheses of the study
and the overall fitness of the model. All the analyses
was done using SPSS version 23. Linear regression
model of the Ordinary Least Square (OLS) approach
was used to analyze the objectives in order to
ascertain the influence and also determine the
relationship between the independent variables and
dependent variable in the conceptualized model of the
study. The use of Ordinary Least Square (OLS), is
informed by the fact that under normality assumption
for αi, the Ordinary Least Square (OLS) estimator is
normally distributed and is said to be best, unbiased
linear estimator (Gujarati and Porter, 2008).
Model Specification
The model for this study is anchored on the model
developed by Adofu & Audu (2015) the study
examined the impact of financial deepening (FIND)
proxied by banks credits to agricultural sector
development in Nigeria. By adopting Adofu &
Audu’s type model and modified it to incorporate cost
of credit, amount of credit borrowed, repayment
period, interest paid and loan repayment performance.
Thus, the model for the study is specified as:
Thus, the model of this study, is stated as follows:
The functional form of the model is
CAP = f(COC, AMC, RPC, INP, LRP)..................(1)
The mathematical form of the model is
CAP = β0+β1 COC +β2 AMC +β3 RPC +β4 INP +β5
LRP .......... (2)
The econometric form of the model is
CAP = β0+β1 COC +β2 AMC +β3 RPC +β4 INP +β5
LRP + αi.......... (3)
Where; CAP = Cassava Production (proxied by
farmers' output)
COC = Cost of credit
AMC = Amount of credit borrowed
RPC = Repayment period
INP = Interest paid
LRP = Loan repayment performance
β0 = Intercept of the model
β1 – β5 = Parameters of the model
αi = Stochastic error term
International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD45009 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 961
3. RESULTS AND DISCUSSION
Regression Analysis Result
Table 1: Regression Result on access to agricultural credit and cassava production in Anambra State,
Nigeria
Source: Field Survey, 2020
Dependent Variable: Farmers' output
In order to also determine the influence of cooperative credit on cassava production in Anambra State, Nigeria,
the analysis was also done based on statistical criteria by applying the coefficient of determination (R2
) and the
F-test. In general, the joint effect of the explanatory variables-independent variables-in the model account for
0.883 or 88.3% of the variations in the influence of cooperative credit on cassava production in Anambra State,
Nigeria. This implies that 88.3% of the variations in the cassava production are being accounted for or explained
by the variations in the explanatory variables. While other independent variables not captured in the model
explain just 11.7% of the variations in cassava production. All the six coefficients (Cost of cooperative credit,
Amount of Credit Borrowed, Loan repayment period, Interest Paid and Loan Repayment Performance)
significantly influence cassava production in Anambra State.
4. CONCLUSION AND
RECOMMENDATIONS
Cost of cooperative credit has a negative relationship
with cassava production. This implies that the cost of
cooperative credit and cassava production increase in
the opposite direction. That is to say that cost of
cooperative credit has a inverse relationship with
cassava production. In other words, 1% increase in
cost of cooperative credit will bring about 13.6%
decrease in cassava production. Amount of credit
borrowed has a negative relationship with cassava
production. In other words, 1% increase in amount of
credit borrowed will bring about 16.0% reduction in
cassava production. Loan repayment period has a
direct and positive relationship with cassava
production. As the loan repayment period grows, it
increases the cassava production. In other words, 1%
increase in loan repayment period will bring about
51.6% increases in cassava production. Interest paid
also have direct and positive relationship with cassava
production. Therefore, 1% increase in interest paid
will bring about 44.9% increase in cassava
production. Loan Repayment Performance have direct
and positive relationship with cassava production.
This implies that loan repayment performance move
in the same direction with cassava production. It has a
positive influence on cassava production. As loan
repayment performance, cassava production also
increases.
Based on the findings of this study, the following
recommendations are made:
A. In order to address the challenge of cost of
cooperative credit, credit institutions should
supervise and spread the repayment period for
credit obtained in such a way that the cost will not
be heavy.
B. Adequate credit facilities should be provided for
farmers to enable them increase their production
capacity.
C. The loan repayment period for the farmers should
be well spread to enhance their productivity
D. Low interest rate should be charged farmer to
enable them reduce their rate of defaulting
repayment.
E. For improved loan repayment performance
farmers should be well supervised to ensure that
the credit obtained is well utilized. The farmers
should plan for a large farm so that the expected
income will improve their capacity to repay farm
credit.
Model B Std. error T Sig.
Constant(C) 0. 155 0.034 4.579 0.000
Cost of cooperative credit -0.136 0.061 -8.749 0.000
Amount of Credit Borrowed 0.160 0.066 -6.991 0.003
Loan repayment period 0.516 0.128 4.046 0.006
Interest Paid -0.449 0.143 3.143 0.005
Loan Repayment Performance 0.364 0.112 3.254 0.047
R 0.903
R2
0.883
Adj. R2
0.850
F-statistic 78.63 0.000
International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD45009 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 962
REFERENCES
[1] Adeyemo, T., Amaza, P., Okoruwa, V.,
Akinyosoye, V., Salman, K. & Adebayo, A.
(2019). Determinants of intensity of biomass
utilization: evidence from
cassava smallholders in Nigeria. Sustainability,
11(2516), 1-16. doi:10. 3390/su11092516
[2] Aladejebi, O. J., Omolehin, R. A., Ajiniran, M.
E. & Ajakpovi, A. P. (2018). Determinants of
Credit Acquisition and Utilization among
Household farmers in the Drive towards
Sustainable Output in Ekiti State, Nigeria.
International Journal of Sustainable
Development, 11(9), 26-36.
[3] Awotide, B. A., Abdoulaye, T., Alene, A. &
Manyong, V. M. (2015). Impact of Access to
Credit on Agricultural Productivity: Evidence
from Smallholder Cassava Farmers in Nigeria.
A Contributed paper Prepared for Oral
Presentation at the International Conference of
Agricultural Economists (ICAE) Milan, Italy
August 9-14, 2015.
[4] Ayegba, O. & Ikani, D. I. B. (2013). An impact
assessment of agricultural credit on rural
farmers in Nigeria. Research Journal of
Finance and Accounting, 4(18), 80-89.
[5] Chandio, A. A., Jiang, Y. & Rehman, A.
(2018). Credit margin of investment in the
agricultural sector and credit fungibility: the
case of smallholders of district Shikarpur,
Sindh, Pakistan. Financial Innovation, 4(27), 2-
10.
[6] Ekwere, G. E. & Edem, I. D. (2014).
Evaluation of agricultural credit facility in
agricultural production and rural development.
Global Journal of Human-Social Science: B,
14(3), 18-26.
[7] Gbigbi, T. M. & Achoja, F. O. (2019).
Cooperative financing and the growth of catfish
aquaculture value chain in Nigeria. Croatian
Journal of Fisheries, 77: 263-270.
[8] Linh, T. N., Long, H. T., Chi, L. V., Tam, L. T.
& Lebailly, P. (2019). Access to Rural Credit
Markets in Developing Countries, the Case of
Vietnam: A Literature Review. Sustainability,
11 (1468) 1-18. ; doi:10. 3390/su11051468
[9] Medugu, P. Z., Musa, I. & Abalis, E. P. (2019).
Commercial banks' credit and agricultural
output in Nigeria: 1980 -2018. International
Journal of Research and Innovation in Social
Science, III (VI), 244-251.
[10] Ogbuabor, J. E. & Nwosu, C. A. (2017). The
Impact of Deposit Money Bank’s Agricultural
Credit on Agricultural Productivity in Nigeria:
Evidence from an Error Correction Model.
International Journal of Economics and
Financial Issues, 7(2), 513-517.
[11] Ukwuaba, I. C., Owutuamor, Z. B. & Ogbu, C.
C. (2020). Assessment of agricultural credit
sources and accessibility in Nigeria. Review of
Agricultural and Applied Economics, 23(2), 3-
11.

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Access to Agricultural Credit and Cassava Production A Study of Selected Cooperative Farmers in Anambra State

  • 1. International Journal of Trend in Scientific Research and Development (IJTSRD) Volume 5 Issue 5, July-August 2021 Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470 @ IJTSRD | Unique Paper ID – IJTSRD45009 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 957 Access to Agricultural Credit and Cassava Production: A Study of Selected Cooperative Farmers in Anambra State Nwafor, Grace Obiageli; Umebali, Emmanuel E. PhD Department of Cooperative Economics and Management, Nnamdi Azikiwe University (NAU), Awka, Nigeria ABSTRACT This study examined access to agricultural credit and cassava production: A study of selected cooperative farmers in Anambra State, Nigeria. This study adopted a descriptive survey research design that aimed to determine the relationship between the independent variables and dependent variable in a population. The population of this study was made up of 2978 members of selected thirty six cooperative societies in Anambra State. A sample of 353 was determined for the study using Taro Yamani formula. A structured questionnaire was administered to 353 respondents only 348 responded to the questionnaire. The data collected using the questionnaire was analyzed using descriptive statistics like frequency, mean and standard deviation; and also inferential statistics such as regression analysis and t-test statistics. All analysis was conducted using SPSS version 23. Findings show that all the five coefficients (cost of cooperative credit, amount of credit borrowed, loan repayment period, interest paid and loan repayment performance) significantly influence cassava production in Anambra State. In general, the joint effect of the explanatory variables- independent variables-in the model account for 0.883 or 88.3% of the variations in the influence of cooperative credit on cassava production in Anambra State, Nigeria. This implies that 88.3% of the variations in the cassava production are being accounted for or explained by the variations in the explanatory variables. While other independent variables not captured in the model explain just 11.7% of the variations in cassava production. The study therefore recommends that credit institutions should supervise and spread the repayment period for credit obtained in such a way that the cost will not be heavy. Adequate credit facilities should be provided for farmers to enable them increase their production capacity. The loan repayment period for the farmers should be well spread to enhance their productivity among others. Low interest rate should be charged farmer to enable them reduce their rate of defaulting repayment. KEYWORDS: Cost of credit, Amount of Credit Borrowed, Loan repayment period, Interest Paid Financial Intermediation How to cite this paper: Nwafor, Grace Obiageli | Umebali, Emmanuel E. "Access to Agricultural Credit and Cassava Production: A Study of Selected Cooperative Farmers in Anambra State" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456- 6470, Volume-5 | Issue-5, August 2021, pp.957-962, URL: www.ijtsrd.com/papers/ijtsrd45009.pdf Copyright © 2021 by author (s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0) 1. INTRODUCTION Agricultural credit has remained a critical input in agricultural production, thus it is has been describe as a very significant farm input and has also contributed a great deal in improving the income of farmers particularly in developing countries (Linh, Long, Chi, Tam & Lebailly, 2019). Agricultural credit is a vital factor in improving agricultural productivity. Therefore, access to agricultural credit enables farmers increase their production as well as guarantees the nations with sustainable food security. In the process of agricultural development access to credit is deemed to have positive impact on productivity since it provides farmers with resources needed to start the production process. Thus, greater access to credit can induce agricultural production and support government program for food security (Awotide, Abdoulaye, Alene & Manyong, 2015) IJTSRD45009
  • 2. International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID – IJTSRD45009 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 958 Access to farm credit possess a veryserious challenge to farmers in Nigeria. Yet, it has been described to be a critical farm input that enhances productivity of farmer if adequately supplied (Ukwuaba, Owutuamor & Ogbu, 2020). In developing countries where the majority of farmers are resource-poor rural dwellers, rural credit markets are essential for agricultural growth and development (Awotide, Abdoulaye, Alene & Manyong, 2015). However, a number of factors contain farmers from accessing adequate farm credit where it is even available. Among the factors include cost of credit, amount of credit borrowed, repayment period, interest paid and loan repayment performance. These challenges are occasioned by seasonal pattern of farming activities and the various uncertainties farmers encounter (Aladejebi, Omolehin, Ajiniran & Ajakpovi (2018). One of the groups of farmers that encounter the challenge of access to credit are the cassava farmers and which are the focus of this study. Adeyemo, Amaza, Okoruwa, Akinyosoye, Salman and Adebayo (2019) describe cassava as a food security crop with a potential to provide off-season calories even on low-nutrient soils in many developing countries. Consequently, the important nature of cassava to the growth and development of Africa and Nigeria in particular demands that adequate financing and funding of cassava production is imperative. Efforts by the present and previous government including donor agencies to improve agricultural production and cassava in particular have not yielded the desired result. Ogbuabor and Nwosu (2017) noted that "some of the policies include the Nigerian Agricultural and Co-operative Bank which was established in the year 1973 as part of government efforts to inject oil wealth into the agricultural sector through the provision of credit facilities to support agriculture and agro-allied industries. Also the Rural Credit Scheme was introduced in 1977 by the Central Bank of Nigeria, whereby commercial banks were required to open rural branches. The Agricultural Credit Scheme was also set up in 1977 with the primary aim of inducing banks to increase and sustain lending to agriculture. There are other policies which were set up by the federal government and linked up with commercial banks for the purpose of encouraging the farmers to produce more food such as National Food Security Programme, Special Programme on Food Security Programme and Fadama which are introduced to diversify agricultural products into other uses. Another great measure for improving the flow of credit to the agricultural sector was an attempt to improve the credit mix by lending in the form of cash and in kind to farmers". Despite these measures by the government that is expected to grow agricultural sector through cassava production and enable the country feed its growing population, generate employment, earn foreign exchange and provide raw materials for industries, there is still a serious food demand and supply gap. The country still suffer serious hunger and poverty. But there is a serious need to address the perceived serious hunger and poverty challenges in the country through adequate financing of cassava production in the country. The cooperative particularly the agricultural cooperative has been touted by the government as a vehicle for improving agricultural production in Nigeria. This is coroborated by Ekwere (2016) who stated that organization of cassava cooperative farmers has in recent years become one of the most important pre-conditions for effective mobilization of production resources as well as, accelerates farmer’s progress. It is therefore imperative to analyze the influence of cooperative credit on cassava production in Nigeria. Statement of the Problem This study was informed by the perceived inability of the smallholder cassava farmers to easily assess agricultural credit and also obtain credit at subsidized rates. This perceived farmers outcry has been a serious problem militating against viable approaches to promote worthwhile agricultural-oriented programmes that will enhance cassava production and processing in Nigeria. Presently, the problem of food security and the fight against hunger and starvation have been a topical issue as most of the developing countries including Nigeria is struggling to be liberated from the grip of hunger and starvation. A number of studies on the importance and influence of credit on agricultural production have been carried out by scholars in an attempt to lose grip from the scorge of poverty (Gbigbi & Achoja, 2019; Chandio, Jiang, Wei & Guangshun, 2018; Ayegba & Ikani, 2013; Medugu, Musa & Abalis, 2019) but there seems to be a paucity of research that is carried out on the platform of cooperative. Again, a critical evaluation from extant literature revealed that there are component of credits that can be used as regressors and regressand (independent variables and dependent variables) in evaluating the influence of credit in agricultural production which is lacking in most of the studies. Some of these variables include: cost of credit, amount of credit borrowed, repayment period, interest paid and loan repayment performance. Considering the importance of cassava to food security and fight against hunger and poverty; and also the limited empirical literature on influence of cooperative credit on cassava production particularly in Anambra state, this study is therefore vital to
  • 3. International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID – IJTSRD45009 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 959 bridge the literature and knowledge gap, thus warranting an empirical investigation to analyze access to agricultural credit and cassava production: A study of selected cooperative farmers in Anambra State, Nigeria. Objectives of the Study The broad objective of this study is to analyze access to agricultural credit and cassava production: A study of selected cooperative farmers in Anambra State, Nigeria. The specific objectives of the study are to: A. evaluate the extent to which cost of credit has influenced cassava production in Anambra State, Nigeria. B. examine the extent to which amount of credit borrowed has influenced cassava production in Anambra State, Nigeria. C. determine the extent to which repayment period has influenced has influenced cassava production in Anambra State, Nigeria. D. assess the extent to interest paid has influenced cassava production in Anambra State, Nigeria. E. ascertain the extent to which loan repayment performance has influenced cassava production in Anambra State, Nigeria. 2. METHODOLOGY Research Design This study adopts a descriptive survey research design that involves asking questions, collecting and analyzing data from a supposedly representative members of the population at a single point in time with a view to determine the current situation of that population with respect to one or more variable under investigation (Okeke, Olise & Eze, 2008). Descriptive survey research design can be quantitative or qualitative, but this study is quantitative in nature. According to Micheal, Oparaku and Oparaku (2012), in a quantitative survey research design, the researcher's aim is to determine the relationship between the independent variables and dependent variable in a population. Quantitative research design is either descriptive (variables usuallymeasured once) or experimental (variables measured before and after a treatment). The questions asked are to elicit responses that will answer the research questions and address the objectives of the research. Population of the Study The population of the study consist of all the Members of Farmers Multipurpose Cooperative societies in Anambra state. Which include Onitsha North, Onitsha south, Oyi, Ogbaru, Agbaru East, Anambra West, and Ayamelum for Anambra North, Ihiala, Nnewi North, Nnewi south, Orumba South, Orumba North, Aguata and Ekwusigo for Anambra South, Anaocha, Dunukofia, Njikoka, Idemili South, Idemili North, Awka North and Awka south for Anambra Central. Puting the members at 3,557 found in 214 viable societies. Therefore the population of this study is 3,557 members in 214 cooperative societies. Determination of Sample Size For various sampling techniques, there are appropriate sample size determination technique, which mostly depends on the confidence level, bound on the error and size of the population. Samples are meant to represent population when the entire population cannot be studied. We used a combination of multi-stage sampling and random sampling techniques in this work. In multi –stage sampling, the target population is first divided into first – stage sampling units. A random sample of these is thereafter taken. This is in line with Cochran’s (1977) idea that it is customary to select the first stage sampling units with the probabilities of selection of the units proportional to their size and not equal as in the case of simple random sampling. The first-stage sampling units, which was selected in this sample, are then divided into smaller second random sampling units, which will be sampled again. Four local governments were randomly selected from each of the three agricultural zones that make up Anambra state. The decision to select only four local governments were largely purposive and for convenience. The local governments selected include Dunukofia, Njikoka, Idemili South, and Awka North from Anambra Central. Ihiala, Nnewi South, Orumba South and Ekwusigo from Anambra South. Oyi, Ogbaru, Anambra East and Ayamelum from Anambra North. From the twelve local governments, three societies each were selected making a total of thirty six cooperative societies with membership strength of 2978. The researcher applied the Taro Yamani formula to obtain the desired sample size for the study. The formula is as stated as below: n = N 1+N (e) 2 Where n is the desired sample size N= Population I = Mathematical constant e= Sampling error (5% in this case). In this case, n =? (Unknown), N=359, e = 0.05 and I= constant Substituting the above values into the formula we have; Substituting in the above formula:
  • 4. International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID – IJTSRD45009 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 960 n = 2978 1+2978 (0.05)2 = 2978 1+2978 (0.0025) = 2978 8.4425 = 352.6 = 353 For the purpose of allocation of sample stratum, the researcher adopted R. Kumaison's formula. Below is the R. Kumaisons formula for sample size distribution: nh = nNh N Where n = Total sample size Nh = The number of items in each stratum in the population N = Population size nh = The number of units allocated to each stratum n = 353 Sources and Method of Data Collection Survey data were collected from cassava farmers, who acquire credit or loan from the cooperative society. The study will make use of both primary and secondary data. Primary data were collected using well structured questionnaires to obtain information from the respondents in the study area and through oral interview. Secondary data was sourced from journals, statistical publications, textbooks, articles, past projects, and the internet. Description of the Research Instrument The research instrument used data collection is the structured questionnaire. It was used to obtain data from both the cooperative and non cooperative farmers in the study area. The questionnaire has two sections: Sections A and Section B. Section A seek information on the socio-economic background of respondents while Section B is designed to elicit information relating to access to cooperative credit, other sources of credit, cassava output and cassava revenue, cost of cassava farming and constraints to cooperative credit access. Out of 353 questionnaires distributed only 348 were returned. Method of Data Analysis Data collected were analyzed using descriptive statistics (frequencies, percentages, mean, and standard deviation) and the inferential statistics such as test statistics and the linear regression model. The demographic profiles was processed using descriptive statistics. Thereafter, the seven objectives will be processed using descriptive statistics (like mean and standard deviation) and the regression model of the Ordinary Least Square (OLS). T-test and F-test statistics was used to test the hypotheses of the study and the overall fitness of the model. All the analyses was done using SPSS version 23. Linear regression model of the Ordinary Least Square (OLS) approach was used to analyze the objectives in order to ascertain the influence and also determine the relationship between the independent variables and dependent variable in the conceptualized model of the study. The use of Ordinary Least Square (OLS), is informed by the fact that under normality assumption for αi, the Ordinary Least Square (OLS) estimator is normally distributed and is said to be best, unbiased linear estimator (Gujarati and Porter, 2008). Model Specification The model for this study is anchored on the model developed by Adofu & Audu (2015) the study examined the impact of financial deepening (FIND) proxied by banks credits to agricultural sector development in Nigeria. By adopting Adofu & Audu’s type model and modified it to incorporate cost of credit, amount of credit borrowed, repayment period, interest paid and loan repayment performance. Thus, the model for the study is specified as: Thus, the model of this study, is stated as follows: The functional form of the model is CAP = f(COC, AMC, RPC, INP, LRP)..................(1) The mathematical form of the model is CAP = β0+β1 COC +β2 AMC +β3 RPC +β4 INP +β5 LRP .......... (2) The econometric form of the model is CAP = β0+β1 COC +β2 AMC +β3 RPC +β4 INP +β5 LRP + αi.......... (3) Where; CAP = Cassava Production (proxied by farmers' output) COC = Cost of credit AMC = Amount of credit borrowed RPC = Repayment period INP = Interest paid LRP = Loan repayment performance β0 = Intercept of the model β1 – β5 = Parameters of the model αi = Stochastic error term
  • 5. International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID – IJTSRD45009 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 961 3. RESULTS AND DISCUSSION Regression Analysis Result Table 1: Regression Result on access to agricultural credit and cassava production in Anambra State, Nigeria Source: Field Survey, 2020 Dependent Variable: Farmers' output In order to also determine the influence of cooperative credit on cassava production in Anambra State, Nigeria, the analysis was also done based on statistical criteria by applying the coefficient of determination (R2 ) and the F-test. In general, the joint effect of the explanatory variables-independent variables-in the model account for 0.883 or 88.3% of the variations in the influence of cooperative credit on cassava production in Anambra State, Nigeria. This implies that 88.3% of the variations in the cassava production are being accounted for or explained by the variations in the explanatory variables. While other independent variables not captured in the model explain just 11.7% of the variations in cassava production. All the six coefficients (Cost of cooperative credit, Amount of Credit Borrowed, Loan repayment period, Interest Paid and Loan Repayment Performance) significantly influence cassava production in Anambra State. 4. CONCLUSION AND RECOMMENDATIONS Cost of cooperative credit has a negative relationship with cassava production. This implies that the cost of cooperative credit and cassava production increase in the opposite direction. That is to say that cost of cooperative credit has a inverse relationship with cassava production. In other words, 1% increase in cost of cooperative credit will bring about 13.6% decrease in cassava production. Amount of credit borrowed has a negative relationship with cassava production. In other words, 1% increase in amount of credit borrowed will bring about 16.0% reduction in cassava production. Loan repayment period has a direct and positive relationship with cassava production. As the loan repayment period grows, it increases the cassava production. In other words, 1% increase in loan repayment period will bring about 51.6% increases in cassava production. Interest paid also have direct and positive relationship with cassava production. Therefore, 1% increase in interest paid will bring about 44.9% increase in cassava production. Loan Repayment Performance have direct and positive relationship with cassava production. This implies that loan repayment performance move in the same direction with cassava production. It has a positive influence on cassava production. As loan repayment performance, cassava production also increases. Based on the findings of this study, the following recommendations are made: A. In order to address the challenge of cost of cooperative credit, credit institutions should supervise and spread the repayment period for credit obtained in such a way that the cost will not be heavy. B. Adequate credit facilities should be provided for farmers to enable them increase their production capacity. C. The loan repayment period for the farmers should be well spread to enhance their productivity D. Low interest rate should be charged farmer to enable them reduce their rate of defaulting repayment. E. For improved loan repayment performance farmers should be well supervised to ensure that the credit obtained is well utilized. The farmers should plan for a large farm so that the expected income will improve their capacity to repay farm credit. Model B Std. error T Sig. Constant(C) 0. 155 0.034 4.579 0.000 Cost of cooperative credit -0.136 0.061 -8.749 0.000 Amount of Credit Borrowed 0.160 0.066 -6.991 0.003 Loan repayment period 0.516 0.128 4.046 0.006 Interest Paid -0.449 0.143 3.143 0.005 Loan Repayment Performance 0.364 0.112 3.254 0.047 R 0.903 R2 0.883 Adj. R2 0.850 F-statistic 78.63 0.000
  • 6. International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID – IJTSRD45009 | Volume – 5 | Issue – 5 | Jul-Aug 2021 Page 962 REFERENCES [1] Adeyemo, T., Amaza, P., Okoruwa, V., Akinyosoye, V., Salman, K. & Adebayo, A. (2019). Determinants of intensity of biomass utilization: evidence from cassava smallholders in Nigeria. Sustainability, 11(2516), 1-16. doi:10. 3390/su11092516 [2] Aladejebi, O. J., Omolehin, R. A., Ajiniran, M. E. & Ajakpovi, A. P. (2018). Determinants of Credit Acquisition and Utilization among Household farmers in the Drive towards Sustainable Output in Ekiti State, Nigeria. International Journal of Sustainable Development, 11(9), 26-36. [3] Awotide, B. A., Abdoulaye, T., Alene, A. & Manyong, V. M. (2015). Impact of Access to Credit on Agricultural Productivity: Evidence from Smallholder Cassava Farmers in Nigeria. A Contributed paper Prepared for Oral Presentation at the International Conference of Agricultural Economists (ICAE) Milan, Italy August 9-14, 2015. [4] Ayegba, O. & Ikani, D. I. B. (2013). An impact assessment of agricultural credit on rural farmers in Nigeria. Research Journal of Finance and Accounting, 4(18), 80-89. [5] Chandio, A. A., Jiang, Y. & Rehman, A. (2018). Credit margin of investment in the agricultural sector and credit fungibility: the case of smallholders of district Shikarpur, Sindh, Pakistan. Financial Innovation, 4(27), 2- 10. [6] Ekwere, G. E. & Edem, I. D. (2014). Evaluation of agricultural credit facility in agricultural production and rural development. Global Journal of Human-Social Science: B, 14(3), 18-26. [7] Gbigbi, T. M. & Achoja, F. O. (2019). Cooperative financing and the growth of catfish aquaculture value chain in Nigeria. Croatian Journal of Fisheries, 77: 263-270. [8] Linh, T. N., Long, H. T., Chi, L. V., Tam, L. T. & Lebailly, P. (2019). Access to Rural Credit Markets in Developing Countries, the Case of Vietnam: A Literature Review. Sustainability, 11 (1468) 1-18. ; doi:10. 3390/su11051468 [9] Medugu, P. Z., Musa, I. & Abalis, E. P. (2019). Commercial banks' credit and agricultural output in Nigeria: 1980 -2018. International Journal of Research and Innovation in Social Science, III (VI), 244-251. [10] Ogbuabor, J. E. & Nwosu, C. A. (2017). The Impact of Deposit Money Bank’s Agricultural Credit on Agricultural Productivity in Nigeria: Evidence from an Error Correction Model. International Journal of Economics and Financial Issues, 7(2), 513-517. [11] Ukwuaba, I. C., Owutuamor, Z. B. & Ogbu, C. C. (2020). Assessment of agricultural credit sources and accessibility in Nigeria. Review of Agricultural and Applied Economics, 23(2), 3- 11.