impact of retail banking in agricultural production (2)
TRANSCRIPT
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ABSTRACT
Despite the economic importance of the agricultural sector in national
development, Nigeria has performed poorly relative to other developing
countries. More-so, agricultural production is still highly dominated by the
small holder farming system. This system has, in the time past, suffered
from limited access to credit facilities, modern technology farm inputs and
inefficient use of resources. Credit requirements of the farming sector
have increased rapidly over the past few decades resulting from the rise in
use of fertiliser, biocides, improved seeds, and hike in their prices.
Quantitative and Qualitative research was applied in this study, and data
was gotten from both primary (survey) and secondary (online articles,
journals etc) sources, while Stratified-Cluster sampling was used to select
the respondents. This resulted in a total of sixty (60) farmers/farm owners
generally. Frequency distribution tables, percentage and relevant charts
were used to describe the sample, while a regression model was
developed to determine the effect of small and medium enterprises on
poverty.
The results indicated that Employment Density (measured in proxy as
number of employees), Productivity (measured in proxy as monthly turn-
over), and Level of Education had significant impact on poverty. Each of
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these variables impact/affect poverty by a factor of 0.95, 1.04, and 0.71
respectively per unit increase.
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and development efforts, while technical efficiency with which new
technology is adopted and used more rationally is affected by the
flow of information, better infrastructure, and availability of funds and
farmers’ managerial capabilities. Higher use and better mix of inputs
also requires funds at the disposal of farmers. These funds could
come either from farmers’ own savings or through borrowings.
Nigeria’s agricultural potentials are enormous, including an arable
land area of 72 million hectares of which only 50 per cent is currently
under cultivation. A large expanse of land can therefore still be
brought under cultivation. The country is endowed with a wide range
of ecological zones – from the Sahel, Sudan and Guinea Savannah of
the North to the Southern Rain Forest – that makes it possible to
produce many varieties of crops and livestock. The climatic
conditions are suitable for the production of cocoa, coffee, rubber,
sugar cane, yam, cassava, maize, millet, rice, banana, palm fruit,
orange, etc. Livestock farming also offers major attraction. Nigeria’s
ample waters provide great potentials for fishing and other aqua-
cultural activities. On the whole, agricultural production currently
accounts for over 40 per cent of the country’s gross national product.
More-so, in Nigeria, agricultural production is still highly dominated
by the small holder farming system. The farms are dominated by
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research system in Nigeria should be diversified to include public,
private, and beneficiary sources.
Competitive funds for agricultural production need to be established.
This fund would be used to finance some high-priority national
research activities, especially upstream research, and research within
innovative partnerships among national agricultural research
institutions, universities, and the private sector. The new Agricultural
Research Council of Nigeria should mobilize and coordinate the
funding for agricultural research and production. It is also important
to explore agricultural sector funding under the auspices of the New
Partnership for African Development (NEPAD). Another could be
levies on the exports of agricultural produce such as cocoa, rubber,
oil palm, cotton, cashew, and gum Arabic. Service users (for example
through producer associations) can be encouraged to provide funds
for research and extension priorities defined by them. This will create
a demand-driven hold research and extension by which service users
(farmers) can hold research and extension systems more
accountable for services provided.
Existing government agricultural financing institutions have a crucial
role to play. These institutions exist to correct the imbalance of
finance and credit suffered by agriculture vis-à-vis other economic
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sectors. They are designed to compensate for inadequate amounts of
credit and capital which the formal financial markets allocate to
agriculture and agro-allied investments. These institutions include
the Nigerian Agricultural Cooperative and Rural Development Bank
(NACRDB), the Nigerian Agricultural Insurance Company (NAIC), the
newly-established Commodity Marketing and Development
Companies, the Agricultural Credit Guarantee Scheme Fund (ACGSF).
Presently the outreach and impact of the ACGSF is limited and need
to be enhanced through enlightenment, increased transparency of
procedures and minimal administrative red-tape
1.2 STATEMENT OF THE PROBLEM
Inadequate funding hampers the ability of research institutes to
respond to poor farmers’ needs. For example, the federal and state
governments have not funded the Agricultural Development
Programmes (ADP) at sustainable levels. Although the ADPs have had
some positive impact on Nigeria’s rural sector, they have been
plagued by shortages of financial resources, especially after the
closure of the World Bank loans in early 1990s for reasons including a
lack of counterpart funds from the government. ADPs’ outreach
services to poor farmers by inadequate operating funds, thereby
putting significant limits on the effectiveness of the ADPs
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Availability of credit has been identified as a major constraint to
agricultural development in peasant economies. Small-scale farmers
dominate the agricultural sectors of these countries. Whilst there are
often considerable opportunities to increase production and farm
incomes by adopting new technology this potential can only be
realized if farmers can gain access to funds to finance the additional
inputs that are invariably required. All too frequently small-scale
farmers have insufficient savings to finance the investment in
additional inputs.
Under these circumstances the obvious solution for farmers is to
borrow against the improved returns they expect to achieve by
adopting improved technology. Unfortunately, the desired credit is
not available. This is largely because institutional lenders are
reluctant to advance credit to a sector where historically there is a
high incidence of default. In part this can be attributed to the
dependence of agricultural production on nature and the high
covariance of risk from adverse weather and the incidence of disease
between producers in any given location.
To this end, this study seeks to evaluate how effective retail banking
has been in financing and also aiding agricultural growth in Ifelodun
local government area of Kwara state.
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1.3 RESEARCH QUESTIONS
Based on the statement of the problem, this study aims at answering
the following research questions.
1. What are the factors influencing the agricultural output/yield?
2. Do banks have operational schemes/programmes that will aid
agricultural production?
3. What kind of effect/impact does the availability of credit
facilities (in form of loans) have on agricultural production?
4. What are the factors leading to the non-payment of credit
facilities acquired by the local farmers from the banks?
1.4 OBJECTIVE OF THE STUDY
In light of the foregoing, this study seeks to evaluate whether retail
banking services has any effect in agricultural production, especially
in the area of advancing credit/loan facilities to local farmers in
Ifelodun local government area of Kwara state. Other objectives are
as follow:
i. To identify the factors affecting higher agricultural output/yield.
ii. To identify operational schemes/programmes of banks in aiding
agricultural production
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iii. To determine the impact of the availability of credit facilities (in
form of loans) on agricultural production.
iv. To identify factors leading to the non-payment of credit facilities
acquired by the local farmers from the banks.
1.5 SIGNIFICANCE OF THE STUDY
The emergence of a strong and dynamic banking sector is regarded
as a good sign by key stakeholders in both the agricultural and
banking sectors. This is so because major players in the nation’s
agricultural sector will immensely benefit from the newly emerged
banks’ robust financial base and lending policies.
Evidently, this study will be of significant importance to economic
technocrats, policy makers, and the nation at large in the following
the ways:
• Create awareness on the need to take further advantages of
banking programs/schemes available in the country.
• Bring to consciousness the existing potential in the agricultural
sector of our nation and also how it can boost economic
growth
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• Assist policy makers, executives and other practitioners in the
industry to monitor, evaluate and adjust to the on-going
trends in the agriculture.
1.6 RESEARCH METHOOLOGY
This study requires both qualitative and quantitative research
approach, while the data type required is basically ordinal and
measurement data. The sample area i.e Ifelodun LGA, will be grouped
into existing communities/wards by means of cluster sampling
technique. After the clusters are identified, the target farmers will be
administered the questionnaires. Due to financial and time
constraints, and also the proximity of each cluster from the other, a
total of twenty (20) farmers per community/ward will be surveyed.
The survey data will be evaluated using descriptive statistics such as
means, standard deviations, and percentages. To this end, a
frequency distribution table will be constructed. Further analysis
carried out on the survey data entails the development of a
production model where agricultural production/output is the
explained variable i.e Y. Also, credit/loan facilities (measured in naira)
will form a part of the explanatory variables alongside other factors.
These other factors will be selected based on the output of a principal
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component analysis (pca) to be carried out on the items highlighted
on the questionnaire.
1.7 SCOPE OF THE STUDY
This study involves local farm owners and farmers from the individual
communities in Ifelodun LGA. Although, there are many other factors
that could impact agricultural production, this study covers only the
effect of credit/loan facilities on agricultural production, and the role
of retail banks in facilitating such facilities. Also the variables of age,
sex, marital status, educational background, ethnicity, religion, and
economic status among others were used for this study.
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CHAPTER TWO
LITERATURE REVIEW
2.1 THE NIGERIAN AGRICULTURAL SECTOR
During Nigeria’s political independence in 1960, agriculture was the
mainstay of the nation’s economy, providing food to feed the
population and fetching the bulk of the nation’s foreign exchange
earnings. However, the emergence of crude oil since the early 1970s
has changed the nation’s economic profile, marginalizing agriculture
in favour of the petroleum industry. In order to enhance the nation’s
economic growth, it is necessary to diversify the economy into non-
traditional exports. There-by reducing vulnerability to price instability
associated with the crude oil markets. In the agricultural sectors,
diversification could be horizontal or vertical. These require
processing primary agricultural commodities into intermediate and
finished products, with considerable value-added. This process is
expected to fetch higher export earnings with such commodities as
cocoa, cotton, palm produce, rubber, etc. Also, export diversification
into non-traditional agricultural commodities can become a veritable
source of foreign exchange earnings. This may include exportation of
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cut flowers, fruits, vegetables, herbs and several sea foods. These
agricultural commodities have a high dynamic potential because of
their high unit value and high elasticity demand. Therefore,
successful diversification into such products generally requires
introduction of new technologies. If these are put in place, positive
linkages may be created with domestic industry in food, beverages
and tobacco sector which are likely to spur export orientation, as well
as the emergence of domestic firms processing agricultural
commodities that may eventually become large enough to compete
in international markets (UNCTAD, 1998). Despite agriculture’s
crucial position in the national economy, it has remained below its
production potential, particularly in the past three decades. This
negative trend is reflected in the under-capitalization, which accounts
for its lack of competitiveness in the global markets. However, this
unenviable position can be reversed by injecting additional resources
into the agricultural sector from the windfall earnings that accrue to
the petroleum industry from time to time. For example, in the
aftermath of the recent crisis in the Middle East, where American-led
coalition forces invaded Iraq in 2003, oil prices have reacted sharply,
rising in recent times beyond $40 (USD) per barrel to the current
price of $83 (USD) per barrel in September 2007. Additional
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resources generated from the windfall can provide the nation’s
agricultural sector with the support it needs to tackle food insecurity,
and foster export diversification.
New resources for the nation’s agricultural sector can be tailored to
assist smallscale farmers and their organizations through the
following schemes:
(a) Micro-credit programmes, (b) Provision of agricultural inputs with
subsidies where necessary, (c) Additional funding to assist the
nation’s agricultural research institutes to generate novel agricultural
technologies, (d) Capacity building for both private and public
extension agencies to disseminate sustainable agricultural
techniques, (e) Fostering enduring partnerships between farmers’
organizations, governmental bodies and international development
agencies, (f) Developing, export markets for the nation’s primary and
processed agricultural commodities and (g) Upgrading social and
physical infrastructure, particularly in rural areas, where they are in
dismal conditions.
2.1.1 Major Sources of Agricultural Productivity
A. A. Komolafe (2001) stated that there is great potential in
developing economies to resuscitate and expand production of
traditional agricultural exports as well as new ones given the current
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wide range of traditional grains such as sorghum, maize, beans and
oil seeds. Indeed, our land resources are one that can guaranty that
the nation is self-sufficient in the production of a wide variety of food
crops and livestock. The greatest supply side challenge would
therefore to strive to raise productivity through technological change
(use of intensive chemicals, fertilizers, integration of livestock into
farming systems, better irrigation methods, hand-tools and storage
methods and improved animal and crop husbandry.
Again, Dimgba F. O (2001), emphasized that large domestic markets
provided by agro-allied industries especially the food and beverage
industries offer opportunity to add value to traditional non-export
grains such as sorghum and cassava mainly to target ECOWAS
market. This, he opined, would represent a major dividend of the
current regional integration effort. Opportunities also exist to
substitute traditional grains for imported ones by industries such as
sorghum and maize for malted barley in the brewery industry,
cassava and other grains in the flour and feed industry instead of
wheat and a host of others. These are immense opportunities for
resuscitating and inducing agro-allied exports.
Adeleke T. O (2003), in his publication “Economics of Farm
Production and Marketing” clearly emphasized that there is also
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great potential for piggery and other livestock production targeted
mainly at export markets. He also stated that “One area of
comparative advantage that has been relatively unexploited is
cultivation of fresh fruits, vegetables and horticulture for export, and
that almost all flora and fauna can grow in Nigeria with very little
effort.”
2.1.2 Constraints to Increasing Agricultural Productivity.
(a) Sector-wide Constraints
Available research results and literature have identified a number of
sector-wide constraints to increasing agricultural productivity in
Nigeria. According to Fakunle, J. O (2001), these include: poor
agricultural pricing policies, low fertilizer use, low access to
agricultural credit, land tenure insecurity, land degradation, poverty
and gender issues, low and unstable investment in agricultural
research, and poor market access and marketing efficiency.
Poor Agricultural Pricing and Low Fertilizer Use
Fertilizer use is promoted mainly by the fertilizer subsidy policy in
Nigeria. Input subsidies have been a part of Nigeria’s agricultural
price policy since independence, and in spite of economic reforms in
Nigeria, fertilizer subsidies have remained (Fakunle, J. O, 2001).
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In addition, Ajuonuma O.O, (1999) reiterated that under these
sustained and high input subsidy programs, investments in core
public goods such as research and extension, which also aim to boost
productivity, are limited. Ajuonuma O.O (1999) further stated that
although improved crop varieties exist, low fertilizer use is a serious
constraint to agricultural productivity growth, averaging 10 to15
kilograms per hectare. An important factor is low and unstable
domestic production. There has been no domestic production of
fertilizer since the early 2000s, because NAFCON, the dominant
fertilizer producer in Nigeria, has been shut down. Other issues which
affect domestic supply of fertilizers include high transport costs from
port to inland destinations, poor distribution infrastructure, the
absence of capital for private sector participation in distribution,
significant business risks facing fertilizer importers, and
inconsistencies in government policies.
Low Access to Agricultural Credit
Access to agricultural credit has been positively linked to agricultural
productivity in several studies. Yet this vital input has eluded
smallholder farmers in Nigeria.
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Fakunle, J. O, and Imeh O, F (2001), opined that Banks with large loan
funds are generally difficult for smallholder farmers to access.
Problems with collateral and high interest rates appear to frequently
screen out most potential rural smallholder beneficiaries. In addition,
agricultural loans are often short-term with fixed repayment periods,
a loan structure that is not suitable for annual cropping or livestock
production.
Land Tenure Insecurity and Land Degradation
According to Dimgba F. O, (2001), an important institutional
constraint is the absence of a clear title to land. Group ownership of
land in Nigeria has been associated with such problems as limited
tenure security, restrictions on farmers’ mobility, and the inevitable
fragmentation of holdings among future heirs. Dimgba F. O, (2001)
also stated that it may also limit access to formal credit, since the
farmer cannot use land as collateral which reduces incentives to
invest in land quality maintenance or improvement. Kolawole B. F,
(1999) clearly noted that because poor farmers cannot afford
alternative farmlands, and do not have customary access to lands not
inherited, they remain on depleted lands and further degrade these
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resources. Thus, poverty and custom may constrain farmers’ ability
and willingness to mitigate land degradation, leading to declining
productivity.
According to the Global Assessment of Soil Degradation (GLASOD),
more than one-fourth of the agricultural land in Nigeria is severely
degraded, with most of this very severely degraded, meaning major
and irreversible losses in productivity. In situations where technology
is affordable, poor knowledge may lead to over use of agrochemicals
such as fertilizers, which may precipitate environmental problems.
But of immediate concern today in Nigeria is under usage of
fertilizers as a result of high costs. Land degradation has been
manifested in soil erosion, especially the southeast zone;
desertification due to deforestation, mainly in the northeast and
northwest zones; and oil spillage, especially in the oil producing
states. In addition, shorter fallow periods, especially around
homesteads, have resulted in low soil fertility.
Low and Unstable Investment in Agricultural Research
When research is poorly funded, agricultural technologies cannot be
improved, and there will be no downstream farm income increase,
rural employment generation, reduction in food prices, establishment
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of agro-based industries, and economic growth. In short, the absence
of new technologies in agriculture will slow the growth of agricultural
productivity and the reduction of rural poverty. (Dele Oladele, 2003,
“Agricultural blue print for rural Nigeria”)
Public research and development (R&D) spending in Nigeria has been
low and unstable since independence, and the government budget
process for funding agricultural research is complex. The time
between the submission of planned budgets by research agencies
and the approval and release of funds is lengthy and often out of
tune with research work plans. The approved amounts and the
disbursement processes very often fall far short of the planned
budgets of the research agencies. Private sector involvement in
agricultural research has remained negligible to date.
Poor Market Access and Marketing Efficiency
Agricultural marketing efficiency in Nigeria is dismally low. Transport
costs are high due to poor road conditions, limiting access to inputs,
credit, and output markets, and reducing the transmission of key
market information. (Timothy Fisayo, A, 2000)
(b). Commodity-specific Constraints
Staple Crop Constraints
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Three of the leading staple food crops in Nigeria are cassava, maize
and rice. Several improved varieties of these commodities have been
released through years of on-station and adaptive research. Most of
the varieties released, however, have multiplication problems.
Contract growers (also called outgrowers) are often denied good
prices for the resulting harvests at the end of the growing season,
which in turn discourages future farmer participation. In addition,
while many of the varieties are high yielding, they score low on other
parameters such as resistance to drought, pests, and disease; and
early maturity. On-farm costs of producing these crops are still very
high at the small scale level in Nigeria. Agrochemicals are largely
imported at prohibitive costs. Thus, fertilizers and insecticides are
rarely applied to recommended levels. (Timothy Fisayo, A, Kolade
M.O et al 2000)
Again, Timothy Fisayo, A, Kolade M.O et al (2000) stated that making
food available goes beyond increasing on-farm production to include
year-round storage and processing. Due to a combination of low
productivity and post harvest losses, year-round grain availability is
low in Nigeria. Grains in storage are partially lost to storage pests and
diseases. It has been estimated that 10 percent of the total
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production of grains and 20 percent of the total production of tubers
are lost or wasted annually to poor or non-storage.
According to Adebimpe Lawal (1999), there are also everyday
challenges faced by the various levels of tuber and grain processing.
Medium to large scale processors face problems such as inadequate
equipment and fabricators. Okon F and Adebimpe Lawal (2001) also
insisted that this problems that cut across all processors include
unstable market conditions, unstable government trade policies and
difficulty sustaining the supply of raw materials to processors.
Livestock Production Constraints
Collins Madu (2003) in his publication “The constraints to livestock
production in Nigeria” noted that part of the constraints include
biological limitations of the indigenous breeds of animals,
unavailability of production inputs such as feed, water and good
quality pasture year-round, lack of effective veterinary services, and
unavailability of vaccines and veterinary drugs at reasonable costs.
Collins Madu (2003) further noted that non-grazing livestock depend
on compounded feeds, which are affected by seasonality and the cost
of raw feed materials. The pastoral system relies on natural
rangeland for ruminant feeding. Again he said that the expansion of
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cropping activities has reduced available water and grazing
resources, leading in turn to conflicts among pastoralists, fishermen
and farmers.
With 90 percent of the national livestock herd under traditional
management, genetic factors seriously limit livestock productivity in
Nigeria (Ifelodun M A, 2004). He further stated that the absence of a
grandparent stock and the collapse of the livestock breeding and
multiplication programs have reduced high-quality livestock
production. Public veterinary services have declined and livestock
diseases account for 30 to 40 percent of the productivity losses.
The specific constraints in livestock marketing and processing in
Nigeria include poor packaging facilities for products in the value
chains, lack of cold storage facilities in abattoirs at wholesale and
retail markets, and the absence of standards for meat and other
livestock and poultry products.
2.2 THE CONCEPTUAL DEVELOPMENT OF RETAIL BANKING
Feringthing Kelby (2004) stated in his article “Banking and Banking
style in the twenty-first century” that in years gone by there was no
need for “retailing” in the banking industry simply because only a few
banks were in operation and competition was virtually non-existent.
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According to Trubik and Smith, (2000), arm-chair banking was the
order of the day. The banks expected customers to come from very
distant towns and villages to patronize them. In fact the customers
were at the mercy of the banks and the latter dictated the terms and
conditions of the business. It was indeed a sellers market. The
customers had no say and the banks could afford to do whatsoever
they felt like doing. The customers then bore the brunt of whatever
the situation was no matter how harrowing, bitter or ugly their
experiences were. They had no choice. The customers who were
supposed to be king and the very purpose of the banking business
were considered secondary.
According to Hassan A. T (2001), since the introduction of the
structural adjustment Programme (SAP) on the 29th September 1986;
the story has then changed. Many banks have been issued with
operating licenses and this paved way for keen competition. The
bank customer’s tastes also increased and become varied. This
means that if a bank fails to satisfy its customers, the latter would go
and open accounts with other banks were they may gain satisfaction.
The older banks now stood the risk of loosing their customers to the
new ones.
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According to Ajayi Ibi (1980). Competition was then accentuated in
the banking industry by the general deregulation of the economy
pursued under the Structural Adjustment Programme. In the same
view, Ogwuma Paul (1980) was of the opinion that deregulation
opened up the gates for new banks and other financial institutions
and this development then jolted the existing banks out of their deep
slumber. It dawned on them for the first time that to survive the
heightened competition, they had no alternative than to act swiftly.
They realized that for their financial services to be patronized, they
must be brought to the attention of the potential and target users for
whom they were intended. Many financial services are also offered by
some organisations such as the Bureau de Change Companies and
this mean that banks have to compete with other organization and
not just with one another in the market place. To retain their existing
customers and win more business, it became obvious that they must
adopt a positive marketing approach.
2.2.1 Service Strategy of Nigerian Retail Banks
Garland (2002) observed that retail banks usually operate on a long-
term "cradle-to-grave" customer management strategy. This means
that some customers may be regarded as being unprofitable in the
short terms but become profitable over time. Retail banks in Nigeria
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have typically viewed their primary customers as males between 20
and 55 years old (Ojo, 1994). Usually, males are seen as the primary
wage earners and decision makers for financial planning in their
households (Bartos, 1989). As the rationale goes, these male
individuals offer the maximum profitability since they not only have
the resources but also the necessary focus on increasing their assets
(Hisrich and Ozturk, 1999).
Increased growth from sales of financial services to the male
segment has been the primary strategy of retail banks in Nigeria
(Ojo, 1994). In short, male customers have been viewed as the
golden geese of the financial service marketplace. But as Javalgi,
Belonax and Robinson (1990) remarked, while this strategy may
achieve some growth, the financial services needs of females are
usually unclear.
Finally although some of the previous findings relating to retail bank
choice are consistent with the ethos of Nigerian culture that
emphasises social and family ties there has not been a study devoted
to identifying differences in retail bank choice between male and
female customers especially in an African context.
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3.2 RESEARCH DESIGN
Quantitative and Qualitative research was applied in this study.
These research designs focus on objective means and subjective
experience respectively. Quantitative research “allows” for data that
is collected in some objective and replicable manner: this
methodology provides greater “distance” between the data and
researcher. On the contrary, qualitative research deals with the
collection of data in subjective manner in which the research “goes”
to the subject or respondent in order to get the needed data. In both
instances data is analysed statistically.
3.3 DATA SPECIFICATION
There are about four data types usually considered in the study of
random variables (and research works). Such data are common in
engineering, Agricultural, Medical and Business practices, namely;
• HISTORIC OR CHRONOLOGIC DATA: This is the first type of
data associated with time related observations or
measurements, a case of time series data. Historic data are
subject to being lost if not observed initially.
• FIELD DATA: These are observations or surveys in space such
as water level measurements, responses to interviews or
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questionnaires etc. Apart from economic factors as the
limiting conditions, resurvey of field data is always possible.
• EXPERIMENTAL DATA (LABORATORY): A number of data
belong to this group which is found useful in basic and
applied research. For instance, sample soft soil from farm
lands are analysed in the lale as soil quality tests.
• SIMULTANEOUS MEASUREMENTS OF TWO OR MORE RANDOM
VARIABLES: This is a necessary requirement for developing
regression models amongst such variable.
In line with the overall objective of this study, two types of data will
be required for test of hypothesis; Chronologic data and Field data.
The chronologic data is gotten from secondary sources online, while
the field data is from the survey carried out to get input from
surveyed respondents.
3.4 SAMPLING PROCEDURE
A sample is a representative portion of a target population, whereas
Sampling refers to the process of selecting/choosing a sample. There
are basically two broad classes of sampling; Random sampling
process, and Non-random sampling process.
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Random sampling process refers to the selection process where each
element within the population is has equal opportunity to be selected
as part of the sample. Examples are simple random sampling,
stratified random sampling and cluster sampling. Therefore, the Non-
random sampling refers to the process where the selection process is
influenced by the researcher in some form or the other, hence
leading to a bias selection.
Our study entails the use of Random sampling process/method in the
selection of sample farmers and farm owners across the three
districts of the LGA. Specifically, a kind of random sampling called
Stratified-Cluster sampling was used to select the sample. This
method requires the study population be first grouped into clusters,
and then the element within each cluster is stratified. Therefore, the
LGA was clustered on the basis of its districts; Afon, Owode, and
Orire. Thus three clusters were created. About twenty (20)
farmers/farm owners per cluster were surveyed, which implies that a
total of sixty (60) farmers/farm owners were surveyed generally.
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3.5 METHOD OF DATA COLLECTION:
A questionnaire was designed for the purpose of this study and
serves as the main instrument of data collection. Secondary sources
were equally consulted for information on bank schemes and loans
etc.
The questionnaire administration was carried out by the researcher
and with the aid of a few research assistants. Based on the sampling
technique used in the selection process, the questionnaires were
administered to the farmers in their respective wards/districts.
All administered questionnaires were duly collected from the
respondents and later processed for data analysis.
3.6 TECHNIQUE OF DATA ANALYSIS
Our research requires that key statistical analytical tools be
employed hence core Descriptive and Inferential statistics was used
in the analysis of data related to this work in order to reach some
valid and reliable conclusion.
The data gathered was summarised using the descriptive statistics
like frequency distribution tables, percentage and relevant charts.
This was also be done by ensuring the appropriate measure(s) of
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location and dispersion are applied. Inferential analytic tools was
employed namely regression analysis (multiple).
A regression model was developed to help determine the effect of
small and medium enterprises on poverty. The nature of our study
demands the use of multiple regression analysis. The regression
model broadly divided into two types of variables;
• Response variable i.e Dependent variable denoted as Y
• Predictors i.e Independent variables denoted as b
The procedure for determining formulas to solve multiple regression
analysis co-efficient requires that we establish the formulas to meet
an objective of minimizing the sum of squares error for the model.
Methods of calculus are applied, resulting in k+1 unknowns for
multiple regression analyses with k independent variables. For
multiple regression models with two independent variable, the result
is three simultaneous equations with three unknowns (b0, b1, and b2 )
b0n + b1∑X 1 + b2∑X 2 = ∑Y
b0∑X 1 + b1∑X 12 + b2∑X 1X 2 = ∑ X 1Y
b0∑X 2 + b1∑X 1 X 2 + b2∑X 22
= ∑ X 1Y
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The process involved in solving these equations, mostly when k is
greater than 2 (as in our study k = 3) is tedious and time consuming
hence we employ statistical softwares.
The general model is given as
Y = b0 + b1X 1 + b2X 2 + b3X 3
Where;
Y – Dependent variable
b0 - Constant
b1, b2,…, bn – Coefficients
X1, X2,…, Xn – Independent variables
The model was then subjected to an overall significance test by way
of Analysis of Variance (anova).
A Principal Component Analysis (PCA) was carried out on all variables
covered by the questionnaire so as to determine the most significant
variables for the regression models. This (PCA) transforms the raw
score of the variables into a covariance matrix, and later the Eigen
analysis was carried out on the covariance matrix. Also, the
coefficient of determination and adjusted coefficient of determination
were determined. These values inform us of the percentage of
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variation in the dependent variable that the independent variables
account for.
The derived regression model will thus be subjected to test of
significance using analysis of variance (anova) to determine the level
of significance/relevance of the model.
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CHAPTER FOUR
4.0 DATA ANALYSIS AND PRESENTATION OF RESULTS
4.1 INTRODUCTION
The study is conceptually focussed on the impact of retail banking on
agricultural production specifically as it concerns the availability of
loans to farmers for agricultural purposes. Questionnaires were
administered to total of eighty (80) farmers in Ifelodun LGA of Kwara
state. The results are presented in three sections.
The analysis shows the background details of the farmers specifically
as regards their demographic profiles i.e age, sex, marital status,
household size etc. This was done by means of frequency distribution
tables. t-test analysis was conducted to evaluate hypotheses 1 and 2,
while a regression model was developed to determine the impact of
bank credit facilities, among others, on agricultural production.
Microsoft Excel 2007 and Statistical Package for Social Sciences
(SPSS) version 17 were used for the analyses.
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4.2 EVALUATION OF THE PROFILE OF SURVEYED
HOUSEHOLDS
Table 4.1: Demographic profile of households surveyed
CHARACTERISTICS N PERCENTAGE
SEX
male 58 72.5
female 22 27.5AGE
21 - 30 21 26.25
31 - 40 35 43.75
41 - 50 13 16.25
51 - 60 8 10
61 above 3 3.75
MARITAL STATUSsingle 21 26.25
married 36 45
widowed 12 15
divorced 9 11.25
others 2 2.5
TYPE OF FAMILY
mono 29 36.25poly 51 63.75
LEVEL OF EDUCATION
non formal 11 13.75
primary 32 40
secondary 26 32.5
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Age of Household Head
Table 4.1 reveals that about 35 of the farmers are aged 31 to 40
years, while 13 of the farmers surveyed are aged 41 to 50 years. This
accounts for 43.75% and 16.25% respectively. Also, about 8 of the
farmers are aged 51 to 60 years, accounting for about 3.75% of the
entire farmers surveyed.
Furthermore, about 21 of the farmers are aged 21 to 30 years, while
3 of the farmers are aged 61 years and above. This accounts for
about 26.25% and 3.75% respectively.
Marital Status
Results in table 4.1 indicates that 36 of the total 80 farmers are
married and they make up about 45% of the entire farmers surveyed,
while about 12 of the respondents are widowed, accounting for about
15% of the entire farmers surveyed. Also, 9 of the farmers are
divorced, thus accounting for about 11.25% of the entire farmers
surveyed.
Furthermore, 21 of the respondents are singles, while 2 of the
respondents are classified as “others”. This account for 26.25% and
2.5% respectively of the entire farmers surveyed. These figures
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Religion
Table 4.1 shows that 48 of the farmers surveyed profess Christianity
accounting for about 60%, while 32 of the respondents profess Islam
which accounts for about 40% of the respondents surveyed.
Household Size
Table 4.1 reveals that 37 of the farmers surveyed have about 6 to 10
members which accounts for 46.25%, while 22 of the farmers
surveyed have about 11 to 15 members which account for 27.50%.
Furthermore 19 farmers have about 1 to 5 members, while 2 of the
households have at least 16 members which accounts for 2.5% of the
farmers surveyed.
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4.3 TEST OF HYPOTHESES.
The analysis was to determine the correlation between Agricultural
Production, and the Demographic characteristics of the respondents
(Age, Marital status, Level of Education, and Household size). The
correlation co-efficient (r) values were calculated using Karl Pearson
Product Moment Correlation analysis, while the significance level (α)
was set at 0.05. The correlation co-efficient values (r) are deemed
significant when the respective p-values (i.e probability values of the
correlation co-efficient) are less than the significance level of 0.05.
Hypothesis 1:
There is no significant relationship between the Age, Marital status,
Level of Education, and Household size of farmers, and Agricultural
production
Table 4.2: Relationship between Age, Marital status, Education level,
and Household size of farmers, and Agricultural production
Variable N R p
Age 80 0.042 0.150
Marital status 80 0.002 0.935
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Level of
Education 80 0.037 0.200
Household size 80 -0.056 0.063
**α= 0.05
**Correlation is significant at p< 0.05 level
Agricultural production and Age
Evaluation of the relationship between Agricultural production and
Age of farmer shows a correlation co-efficient (r) of 0.042, and a p-
value of 0.150, which is not significant since p-value is greater than
0.05. This implies that there is no significant relationship between
Agricultural production and Age of farmer.
Agricultural production and Marital Status
According to table 4.2, the relationship between Agricultural
production and the marital status of farmers shows a correlation co-
efficient (r) of 0.002, with a p-value of 0.935, which is not significant
since p-value is greater than 0.05. This implies that there is no
significant relationship between Agricultural production and the
marital status of farmers.
Agricultural production and Level of Education
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According to table 4.2, the relationship between Agricultural
production and the level of education of farmers shows a correlation
co-efficient (r) of 0.037, with a p-value of 0.200, which is not
significant since p-value is greater than 0.05. This implies that there
is no significant relationship between Agricultural production and the
level of education of farmers.
Agricultural production and Household size
An examination of table 4.2, the relationship between Agricultural
production and the household size of farmers shows a correlation co-
efficient (r) of -0.056, with a p-value of 0.063, which is not significant
since p-value is greater than 0.05. This implies that there is no
significant relationship between the behavioural pattern of
adolescents and outburst of anger at-risk behavior.
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Hypothesis 2:
There is no significant difference in agricultural production output
between bank credit facilities and other sources of credit facilities
Table 4.3: t-test analysis on difference in agricultural production
output based on bank credit facilities and other sources of credit
facilities
Primary sources of
credit N Mean df t p value
Bank 21 5880 78 -0.291 0.707
Other sources 59 5940
*significant at p < 0.05, where α = 0.05
The t-test analysis for the difference in agricultural production output
between bank credit facilities and other sources of credit facilities
reveals a mean score of 5880 for farmers having bank credit
facilities, and 5940 for farmers having other sources of credit
facilities. The analysis yielded t-value of -0.29 at 78 degrees of
freedom which was deemed not significant at p=0.77, hence
hypothesis 1 is not rejected. This implies that there is no significant
difference in agricultural production output between bank credit
facilities and other sources of credit facilities.
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This further implies that credit facilities issued by the banks, and that
issued through other sources have similar effect on the output of
farmers. This could be due to the fact that there could be other
factors responsible for variance in agricultural production beyond
availability of credit facilities.
4.4 EVALUATION OF THE IMPACT OF SMEs ON POVERTY.
This section critically looks at the impact of Bank credit facilities (and
other sources of credit facility), employment density (measured in
proxy as number of employees), and selected demographic variables
(such as marital status, household size, level of education, and age)
on Agricultural productivity. To this end, a regression model was
developed using the following variables;
• Bank credit facility – denoted as BNK
• Other sources of credit facilities – denoted as OTR
• Employment density– denoted as EMP
• Age– denoted as AGE
• Education– denoted as EDU
• Marital status– denoted as MST
• Household size– denoted as HSZ
The result of the analysis follows;
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Table 4.4 : Multiple regression coefficients for impact of SMEs on
Poverty
Predictor Coefficient SE
Coefficient
t p
Constant
(b0)
1.5443 0.118 2.63 0.000
AGE 0.087 0.018 -1.12 0.082
OTR 0.952 0.021 3.44 0.024
BNK 1.042 0.017 4.76 0.001
EMP 0.714 0.022 2.44 0.016
MST -0.159 0.025 -1.19 0.132
HSZ -0.177 0.025 -1.16 0.219
EDU 0.091 0.041 1.09 0.226
S = 0.3385 R-Sq = 61.1% R-Sq (adj) = 56.4%
Table 4.4 shows the coefficient of each explanatory variable and their
respective significance in the model.
Each variable is subjected to a test of significance to determine if it’s
suitable for the model, hence the following hypothesis;
H0: bi=0 (the co-efficient is not significantly different from zero)
Ha: bi≠0 (the co-efficient is significantly different from zero)
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The calculated t and P values respectively show that at an alpha level
of 0.05 (level of significance), the co-efficient of OTR, BNK and EMP
are significantly different from zero; while the co-efficient of AGE,
MST, EDU and HSZ are not significantly different from zero.
The value of the co-efficient tells us of the level of impact made to
agricultural production by each respective variable. This implies that
for every increase in BNK (bank credit facility) the amount in
agricultural production will be positively affected by a factor of 1.042,
while for every increase in OTR (other sources of credit facility) the
amount in agricultural production will be positively affected by a
factor of 0.952. Again, for every increase in EMP (employment
density) the amount in agricultural production will be positively
affected by a factor of 0.714.
This signifies that agricultural production will be positively affected
by bank credit facility (BNK), other sources of credit facility (OTR),
and the employment density (EMP) i.e number of employee. Hence,
these variables have will greatly influence agricultural activities
provided they are available to farmers.
The other variables do not make any significant impact on
agricultural production, this is shown by their t and p values
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respectively. Thus, agricultural production will not be
impacted/effected by these selected demographic variables – Age,
Marital status, Household size, and Level of Education.
Lastly, the R-sq (adj) value reveals that about 56.4% of the variation
in agricultural production is accounted for/ influenced by bank credit
facility (BNK), other sources of credit facility (OTR), and the
employment density (EMP).
Based on table 4.4, the regression model is stated as:
Agricultural production = 1.54 + 1.04 BNK + 0.71 EMP + 0.950 OTR
The overall significance of the model was tested using analysis of
variance (ANOVA), thus the following hypothesis;
H0: b1= b2 = b3 =0 (the model is not significant)
Ha: at least one of the coefficients is not equal to zero (the model is
significant)
Table 4.5: ANOVA output for multiple regression model
Source DF SS MS F P
Model 7 18.57 2.65 2.574 0.048
Residu
al 72 74.21 1.03
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Total 79 17.78
α = 0.05
Table 4.5 shows the regression yielded an F-value of 2.574, and p
value of 0.048 which is significant since p<0.05, thus the null
hypothesis is rejected. Therefore the model is significant. This implies
that the model developed is fit for determining agricultural
production.
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4.5 SUMMARY OF FINDINGS
The results, as presented in tables 1 and 2 above, indicated the
following;
That about 72.5% of the farmers are male, while about 27.5% of the
farmers are females-which is likely due to their tedious nature of
farming
Farmers aged 31 to 40 years account for 43.75%, while farmers aged
41 to 50 years account for about 16.25% of those surveyed. Also
farmers aged 61 years and above account for 3%
Married farmers make up about 45%, while farmers that are single
account for about 26.25% of the entire households surveyed
Farmers practicing polygamy account for 63.75%, while farmers
practicing monogamy account for about 36.25% of the entire farmers
surveyed
Also, about 40% of farmers obtained only a primary education,
13.75% obtained non-formal education, while about 5% obtained
tertiary education
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Farmers professing Christianity account for about 60%, while about
40% profess Islam.
46.25% of farmers have about 6 to 10 members in their household,
while 2.5% of the farmers have at least 16 members in their
household.
Also, the model developed indicated that employment density
(measured in proxy as number of employees), productivity
(measured in proxy as monthly turn-over), and level of education had
significant impact on poverty. Each of these variables impact/affect
poverty by a factor of 0.95, 1.04, and 0.71 respectively per unit
increase.
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CHAPTER FIVE
5.0 SUMMARY, CONCLUSSION, AND RECOMMENDATION
5.1 SUMMARY
This study primarily evaluated the basic characteristics of sampled
households and SMEs in Asa local government area of kwara state.
And also a regression model depicting the impact of employment
density (measured in proxy as number of employees), productivity
(measured in proxy as monthly turnover), and other demographic
variables on poverty was developed.
Availability of credit has been identified as a major constraint to
agricultural development in peasant economies. Small-scale farmers
dominate the agricultural sectors of these countries. Whilst there are
often considerable opportunities to increase production and farm
incomes by adopting new technology this potential can only be
realized if farmers can gain access to funds to finance the additional
inputs that are invariably required.
This study was deemed to be of significant importance to economic
technocrats, policy makers, and the nation at large since it will create
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awareness on the need to take further advantages of banking
programs/schemes available in the country; bring to consciousness
the existing potential in the agricultural sector of our nation and also
how it can boost economic growth; and assist policy makers,
executives and other practitioners in the industry to monitor,
evaluate and adjust to the on-going trends in the agricultural sector.
The study also identified some existing constraints to Agricultural
Productivity in the following aspects;
(a) Sector-wide Constraints: Poor Agricultural Pricing and Low
Fertilizer Use, Low Access to Agricultural Credit, Land Tenure
Insecurity and Land Degradation, Low and Unstable
Investment in Agricultural Research, Poor Market Access and
Marketing Efficiency
(b) Commodity-specific Constraints: Staple Crop Constraints,
Livestock Production Constraints
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5.2 CONCLUSION
In Nigeria, it has been shown that agriculture is the dominant
economic activity in term of employment and linkages with the rest
of the economy. About 75% of Nigeria land is arable of which about
40% is cultivated. It is because of the importance of agriculture as
well as the fact that significant improvement in rural welfare depends
upon its development that the governments (Federal, State and
Local) over the years have pursued policies and programmes aimed
at the expansion and modernization of agriculture. These
programmes and policies all have the bottom line of trying to unlock
the agricultural and rural development potentials by enhancing the
capacity of the rural dwellers, making agriculture more profitable,
providing infrastructural facilities and hereby raising the rural people
standard of living.
Therefore, it is important to note that though agriculture has not
made the desired impact on the Nigerian economy in spite of all the
efforts and supports of succeeding administrations and governments
gives a cause for concern. This underscores the fact that there exist
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fundamental issues or problems which confront farmers and
stakeholders which hitherto have either not been addressed at all or
have not been tackled wholesomely.
Owing to the above, Obadan (1997) opines that the main factors that
cause low agricultural output include; inadequate access to credit
facilities, inadequate physical assets such as land and capital and
minimal access by the poor to credit even on a small scale,
inadequate access to markets (where the poor can sell goods and
services), and low endowment of human capital
It is also worthy of note that, according to Pandey,(2000 ), there is no
single ideal way to financing agricultural enterprises, each business
has individual circumstances which makes its requirement unique;
the markets in which it operates, its age and the stage of its life cycle
which it has reached, its ownership, rate at which its owners hush to
expand etc. He further identified two main channels that have been
used as credit for agricultural enterprises as Formal and Informal
sources. He identified the formal sources to include commercial
banks, merchant banks, saving, banks insurance companies, and
development banks, also government loan agencies and cooperative
credit societies. Also, the informal sources were identified as Owners
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savings, Retained earnings, Friends and relations, Clubs, ‘Esusu’ and
Money-lenders among others.
Obitayo (1991) noted that some of the major problems affecting
agricultural production stem from their nature and characteristics. He
identified some of these problems as uneven competition arising
from import tariffs which at times favour imported finished product,
lack of access to appropriate technology, weak demand for products
arising from low and dwindling consumers purchasing power
aggravated by lack of patronage of locally produced goods by the
general public as well as those in authority.
Obitayo (1991) further opined that absence of long term finance to
fund capital assets and equipment under project finance for agro-
firms could equally hamper agricultural production
Finally, Biggs and Shah (1998), using panel data from enterprise
surveys in five countries in Sub-Saharan Africa, report that large
agro-firms (>100 employees) over a three year period in the early
1990s emerged as the dominant source of net job creation. These
agro firms contributed about 56 percent of net job creation in Ghana,
74 percent in Kenya, 76 percent in Zimbabwe, and 66 percent in
Tanzania.
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5.3 RECOMMENDATION
Based on findings and the conclusions reached on the issues raised
by this study, the following are the recommendations of the
researcher;
1. There arises a cogent need for measures that’ll lead to
mobilizing and allocating financial resources to farmers. This will
further boost the agro-firms in building and consolidation
process. The government’s efforts should also be geared
towards improving the enabling environment, which will help to
reduce agency problems and transaction costs and mitigate
problems of access.
2. Furthermore, agro-firms will have to figure out different kinds of
strategies and structures, and develop core technical
capabilities to respond appropriately to the new market and
institutional conditions they face. The need to readjust in the
areas of Financial capital flow, Strategy, Core technical
capabilities will involve considerable cost to the agro-firm and
requires access to an array of “dynamic learning mechanisms,”
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which facilitate and shape the evolution of strategies, structure,
and capabilities (Teece, and Shuen 1990; Nelson 1991).
3. Government at all levels should create an enabling “financial
environment” that’ll help facilitate availability of credit facilities.
Some instances could be the formulation of policies that
guarantee easy access to loans/credit facilities from banks and
other formal sources of funding. Equally of importance in such
policies will be the need to put in place measures that’ll
guarantee the security of such loans given out to farmers/agro-
firms. This stems from complaints by banks/other formal sources
of funding that loans advanced to the farmers are usually not
returned as at when due, and in most instances, the repayment
periods actually drag.
4. Finally, the need to put in place a fair competitive market
environment that encourage locally produced crops. This has
been a major concern for the farmers since they are faced with
uneven competition arising from import tariffs which at times
favour imported finished product, and therefore leads to
dwindling consumers purchasing power aggravated by lack of
patronage of locally produced goods by the general public as
well as those in authority.
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