JOURNAL OF SUSTAINABLE DEVELOPMENT
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·Factors Influencing, job PerformanCe by Staff of the National Agricultural Research Institutes (NARIS)
TOkula M.H. Unamma, RP.A and Ek1:!mankama, O. O. . o
. Credit Utilisation among Rice Farmers in Oyo State, Nigeria
Oladokun, Y. O. M. and Adenegan, K. O.
, Evaluation of Three Okro Varieties in Okra/Sweet Potato Intercrop on a Typic Palenduct
.' NjOku S.C., C.O. Muoneke and DA'Okpara G>
Indigenous Methods of Storing Sweet Potato in Bauchi, Nigeria
Dantata, I. J. e
Risks and Management Strategies in Poultry Production in Oke-Ogun Area of OyoState, Nigeria
. Salau, M. A, Eniola, P.O., Siyanbola, M. F.
" e
Germination and Seedling GroWth of Parkia Bico/or (A. Cheu) as Influenced by Various Nursery Techniques
Okunomo, K. " .
Profitability Analysis of Fish Farming: An Antidote to Economic Meltdown
Williams, S. B.; R. O. Kareem; N. M. Eneh
Response of Uvinigstone Potato (Plectranthus Esculentus) to Different NPK 15: 15:15 Fertilizer Rates
" Akinpelu, A. 0., Asumugha, G. N., Omonona, B. l;Olojede, A. O. (§)
The Effect of Fungicides on the,NQdulation of Cowpea (Vigna Unguiculata L. Walp)
Uthman 10.;A. O. Awosanya; A. O. S. Ayanwaleand 1 G. Ayinde €>
Structure, Causality and PriceTransmissi()n Tests in the Marketing of Irvingia Seed (Ogbono)
P.C.lke. .- -(9
Overview of the Challenges to Agricultural Extension Practice, Research and Technology Development
lssa, F. O. e
Impact Of Foreign Direct Investment On Nigeria Economy (1980-2008)
Kareem, R. 0; Ad~niji, 1R; and Ayan~ale, A. O. S. . (!j)
Nutrient Intake of WAD Sheep Fed Boiled Cocoa Seed Testa and
Sorghum Malt Dust-Based Diets
E~u, R. 0., Onwuka, C. F. I., Arigbede, O. A. and Isah, O. A.
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UNIVERSITY OF IBADAN LIBRARY
Journal of Sustainable Development Vol. 7. No.1, March 2010
CREDIT UTILISATION k~MONGRICE FARMERS IN OYO STATE, NIGERIA
OLADOKUN, Y. O. M. AND ADENEGAN, K. O.
Deparbnent of Agricultural Economics, University of Ibadan, Nigeria
Email: yetdele@yahoo.com.bumkem@yahoo.com
ABSTRACT
This paper examined the effect that access to credit facilities at reasonable costs has on rice
production activities in three Local Government Areas of Oyo State. Probability to size
sampling technique was adopted to select and collect data from one hundred and twenty
(120) rice farmers with the aid of questionnaires. The analytical tools employed include
descriptive statistics, normalised profit function and Spearman rho correlation. The result
showed that 78.3% and 73.7% of credit users and non credit users respectively are between 30
and 59 years old. About half (50.5%) of credit users and all non credit users are male. Most
(68.3%) of the credit users and all the non credit users can at least read or write. Majority
(75.3%, 68.4% of credit users and non credit users respectively) have household sizes of
between 4 and 9 persons. Sixty-four percent of credit users and all the non credit users have 2
to 3.99 hectares of farmland. The results of normalized profit function reveal that the
coefficients of normalized fertilizer use have negative sign in the profit equation while the
coefficients of land and the other variable inputs of production have positive signs, which
occur at relatively low levels of output that are characteristic of small scale farming. The R2
value is 0.594. Use of credit facilities and shortage of labour have negative correlation while
insufficient agricultural inputs, shortage of land and lack of enough agricultural information
have positive correlation. It was recommended that enlightenment program should be
intensified by introducing illiterate farmers to modern techniques of farming and awareness
of all fields of agriculture, while the bureaucracies for obtaining credit should be reviewed so
that more farmers will benefit from the credit facilities.
Keywords: Farmers, Microcredit, Nigeria, Normalised Profit function, Rice production
INTRODUCTION annually over US$300 million on rice
imports alone.
The food sub-sector of Nigerian
agriculture parades a large array of staple Rice is cultivated in virtually all the agro-
crops, made possible by the diversity of ecological zones in Nigeria. Despite this,
agro-ecological production systems. The the area cultivated to rice still appears
major food crops are cereals (sorghum, small. In 2000, out of about 25 million
maize, millet, rice, and wheat), tubers hectares of land cultivated to various food
(yam, cassava), legume (groundnut, crops, only about 6.37% was cultivated to
cowpeas) and others (vegetables). These rice. During this period, the average
are the commodities that are of national yield was 1.47 tons per hectare.
considerable importance for food security, Significant improvement in rice
expenditures and incomes of households. production in Nigeria occurred in 1980
However of all the staple crops, rice has when output increased to 1 million tons
risen to a position of pre-eminence. Since while area cultivated and yield rose to 550
themid-1970s, rice consumption in thousand hectares and 1.98 tons per
Nigeria has risen tremendously, at about hectare respectively. Throughout the
10% per annum due to changing consumer 1980s, rice output and yield increased. But
preferences. Domestic production has in the 1990s, while rice output increased,
never been able to meet the demand, the yield of rice declined, suggesting
leading to considerable imports which extensive rice cultivation.
today stand at about 1,000,000 metric tons
yearly. The imports are procured on the Presently Nigerian agricultural sector is
world market with Nigeria spending characterized by small scale farming.
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Journal of Sustainable Development Vol. 7. No.1, March 2010
Experts have opined that the Nigeria isrevealed by the actual yields of
empowerment of small scale rural rice maj6r crops. The various Governments
farmers should therefore be the focus of intervention targeted at boosting food
any intervention program that is aimed at Production in Nigeria, has not yielded the
improving local production. Specifically, desired results, . while existing
these interventions should involve the medium/large scale farms have equally
provision of agricultural credit. been ascertained as not being able to
sustain the food requirement of the ever
Agricultural credit is the sum total of the increasing population in Nigeria.
arrangement through which cash and kind However, the task of bulk food
inputs are made available to a farmer or production, still lies with rural peasant
producer who repays such inputs in the farmers.
form stated in the repayment schedule
with due interest.(Oshuntogun, 1992). Peasant rice farmers have been
Agric credit which has been identified in acknowledged, as being averse to risk, and
literature as a major catalyst to increase need credit for boosting their agricultural
the productivity of farmers in most production as well as smoothening their
developing country (Okorie and Obeta, family consumption. Despite the role of
1990;Jamal and Kulundu, 1992;Goetz and farmers as the backbone of food
Gupta 1996; Lindvert 2006;etc) and also production in Nigeria, they are faced with
constitute a major platform for poverty many factors limiting their effective
alleviation ( IFAD, 2001; Adongo and participation in achieving food security.
Stork et al 2005; Eswaran et al 1990 and Notable among these are limited access: to
Haddad et al 1997). Moreover there has land and capital, credit, agricultural
been a consensus on the fact that, to inputs, education and appropriate,
increase the level of agricultural technology. The twin challenge is
production and development in Nigeria, therefore, the need to develop appropriate
there is the need to strengthen the credit advancement and utilization
financial capacity of the (rural) mechanism that can produce the desired
agricultural producers, ( Aihonsu, 2001). result on the target farmers. It is obvious
In the same vein, adequate flow of credits that any effective strategy or mechanism
into agriculture has been identified as a must be based on environmental, social,
critical factor in accelerating incremental gender, cultural, economic and other
food production in Nigeria. Dimithe factors characterizing the target farming
(2001),states that the major barrier to the community.
intensification of agriculture in sub-Sahara
Africa is the difficulty that poorly There is, therefore need to study what
capitalised farmers have (faced) in effect, access to credit facilities at
obtaining credit for inputs. The financial reasonable cost will have on rice farmers
services usually available to the (rural) production activities in Oyo state. The
poor, according to Latifee (2003), are following questions need to be answered:
limited in terms of cost, risk and What effects does such credit accessibility
convenience. have on rural farmers' naira value of their
output (i.e. revenue), gross margin and
PROBLEMSTATEMENT profit levels? And what. possible
constraints do rice farmers encounter?
Nigeria has not been able to attain self-
sufficiency in food crop production, LITERATURE REVIEW\CONCEPTUAL
despite increasing hectares being put into FRAMEWORK
production annually. According to Amaza
and Olayemi (2002),the constraint to rapid Credit is essential in rural economies in a
growth of food production is due to low variety of ways. It is required to finance
crop yields and resource productivity. In working capital and to invest in fixed
1993, the Minister of Agriculture stated capital partly among farmers too poor to
that low agricultural productivity in accumulate much savings (Ghosh et. aI.
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Journal of Sustainable Development Vol. 7. No.1, March 2010
2000). The importance of credit facilities to empowerment that can enhance farmers'
small land holders in less developed self-confidence and status within the
countries has been underlined by several family and their community.
authors (Adams and Graham, 1981).
Sapovadia et al (2006) concluded that Moreover, credit use will give farmers the
micro credit has wrought local revolutions opportunity to invest in the purchase of
in access to credit in poor communities improved agricultural inputs such as
around the world. Access to credit seeds, fertilizers and pesticides and will
enhances the adoption of new, more risky have a multiplying effect that will help to
technologies and enables the household to increase crop and animal production. This
expand agricultural and non-agricultural will in turn enhance the household's
micro enterprises that will improve the capacity to send their children to school
level of farm household income and and to improve the family's welfare. In
therefore, alleviating their poverty. The addition, no production, no matter how
expected increase in income will simple the technology, can take place
contribute to formation of human and without the use of capital. Therefore,
physical capital (Feder et. al., 1985; Zeller provision of financial support through
et. al. 1997). There have been several cases credit and savings for their acquisition of
on how financial institutions in some capital goods is crucial for their economic
selected developing countries in Asia have development, the aim of which is to
designed programmes to specifically increase their equity and sustainable well
target the poor in the society to enhance being. The expected increase in income
access to credit for productive activities will contribute to formation of human and
and improvement in their economic well- physical capital (Feder et. al. 1985 and
being. Many of the poor, especially those Zeller et. al. 1997).
living in the rural areas, have been left out
of this scheme contributing to growing
inequality, declined access to credit, and MATERIALS, METHOD AND
rapidly growing urban areas (Park et. al., ANALYTICAL MODEL
2003).
The primary data was sourced through the
According to Jama and Kulundu (1992), administration of well structured
access to credit would enable small-scale questionnaires among one hundred and
farmers to use improved farm inputs such twenty (120) rural rice farmers
as fertilizer and seeds as well as to Proportion to size sampling procedure
improve tillage and husbandry practices. was employed. Three Local Governments
This goes along with what Goetz and Areas were selected in Oyo state namely
Gupta (1996) and Lindvert (2006) Akinyele, Ogo-Oluwa and Igbo-Ora.
concluded on in their studies that; credit Thirty respondents were selected each
delivers a range of particular benefits from Akinyele and Ogo-Oluwa local
when targeted to low income women. It governments while sixty respondents
seems as a critical input for increasing were selected from Igbo-Ora local
women's employment in small-scale government.
enterprises and it is expected to encourage
adoption of improved agricultural Analytical Tools and Models
technologies that can enhance the This study will employ a number of
productivity of farming households, analytical tools based on the objectives of
income-generating and expenditure- the study. The tools include, descriptive
saving work. An increase in household statistics, Normalised profit function and
income can facilitate and improve the Spearmen rho correlation.
livelihood enhancing tasks farmers
perform for their households such as Descriptive Statistics
health, nutrition, and education of the The use of percentages was adopted to
household members, It is argued that describe the socio economic characteristics
credit represents a form of economic
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Journal of Sustainable Development Vol. 7. No.1, March 2010
of rice farmers such as age, sex, marital
status, etc. RESULTSAND DISCUSSION
1 Normalised profit function: Table 1 shows' the summary of
H* = G (rj rm, zi zn) (3) characteristics of rice farmers in Oyo State.
Implicit form The summary shows that 82.2% of the
TI* =A'L\ riJ.u ",'\L Z ij(3", (4) farmers are young and middle aged with
Explicit Non-linearised Cobb-Douglas the potential to sustain rice production for
form of normalised profit function, many years. Majority of the farmers 50.5%
This will be linearised by taking natural are male. This is probably because
logarithm of equation (4) above, thus majority of the women in the area are into
becoming: the production of other food crops like
Inn = IrtA, + aj .'..)..,' lnr«1) + Iff] .5•••'• maize and vegetables. Most of the farmers
ZI) (5) (89.1%) are married. This will help to
Explicit linearised form of normalised boast their production as their wives and
profit function. children will help on the farm. Thus less
money will be used to hire Labour and
Where: more money will go to other aspects of
TI* =Normalised profit production. 68.3% of farmers can at least
variable (actual) profit (In) read and write. This shows that there is a
reasonable level of literacy among the
Average Output price (Lp) farmers and hence they might be willing
rij=Normalised price of variable inputs to take more productive risks and it may
used = Total input price (Lpj) enhance the adoption of new technological.
innovations such as improved farming
Total output price (Lp)') practices and the use of agrochemicals on
Zij=Quantity of fixed input used the farm. Most of the farmers are well
rl=Normalised planting material price experienced in farming activities, as they
(Naira) fell within the range of 6 - >15 years of
r-=Normalised fertilizer price (Naira) experience (96.1%). This is in line with
r3=Normalised agro-chemical price (Naira) Tijani (1993) and Olomola et al (1999)
r4=Normalised hired labour wages (Naira) submission that, the number of years of
zr=Cultivated farm size this year (Ha) farming (farming experience) a farmer
zo=Cost of fixed input used (Naira) (as a serves as an indication of the practical
proxy for quantity of fixed input used) knowledge he has acquired through trial
A*ja & f3*j = parameters and error would likely have positive*j
j=I=4 i=I-2 impact on productions
Four functional forms will be considered This result also shows that (67.4%)have 2-
and estimated, namely: Linear, 3.99 hectares of land which implies that
Exponential, Semi-log and Double-log. majority of them still practice subsistence
2 Spearman Rho Correlation. farming. This has implication for the
This will be used to rank the problems technology employed and the scale of
facing rice farmers in the area. It is also production. Majority of the farmers access
called Spearman's rank correlation. The their credit from the formal sources, which
formula is as: is represented by 45% against 26.7% that
=1-6 I D2 accessed it from informal sources. ThisIs
N(NLl) perfectly agrees with the submission of
D - Denotes the differences between the Diagne and Zeller (2001) that, informal
ranks of corresponding Xand Y loan sizes are significantly lower than the
N- Number of pairs of values (X, Y) in the corresponding loans sizes from formal
data. source. This according to Zeller et al (2001)
is because informal sources, especially
friends and relatives, are more constrained
for funds and are not in position to risk
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Journal of Sustainable Development Vol. 7. No.1, March 2010
giving large sums of funds. They further significantly short term loan than the
submitted that, informal sector provides formal sector.
Table 1. Some socio-economic characteristics of rice farmers (credit users and non credit
users)
Variable/ Category Credit users n=101 Non-credit users n=19
Frequency Percentage Frequency Percentage
Age group (years)
Less than 30 - 59 83 82.20 14 73.7
Above 60 18 17.8 9 26.3
Gender
Male 51 50.5 19 100.0
Female 50 49.5 0 0.0
Marital status
Single 5 5.0 0 0.0
Married 90 89.1 19 100.0
Widowed 6 5.9 0 0.0
Household size (persons)
Less than 4-6 24 23.7 8 42.1
7-9 55 54.5 7 36.8
Above 10 22 21.8 4 21.1
Educational status
No formal education 32 31.7 0 0.0
Primary 52 51.5 7 36.8
Secondary 9 8.9 12 63.2
Tertiary 8 7.9 0 0.0
Years of experience in rice farming
1-5 4 3.9 0 0.0
6-10 14 13.9 13 68.9
11-15 12 11.9 6 31.6
Above 15 71 70.3 0 0.0
Rice farm size (hectares)
2.0-4.99 74 73.3 19 100.0
5.0-6.99 27 26.8 0 0.0
Normalized profit function All the coefficients of the variable and
Double log was chosen as the lead fixed inputs have the expected signs and
equation for both credit users and non- those that are statistically significant at the
credit users, from the four functional 1 percent level are shown. In the profit
farms estimated. The selection was based function, fixed input, normalized planting
on a prior expectation (sign of material, normalized fertilizer and
coefficients), statistics (no of significant normalized storage chemical coefficients
variables, t value) econometric (coefficient are not significant. The coefficients of
of multiple determination) R square and normalized fertilizer have negative sign in
adjusted R2) and F - value. This concurs the profit equation because they are part
with Yotopolous and Lau (1979) that the of the costs incurred in the production of
lead equation for normalized profits study rice while the coefficients of land and the
is Double log. Table 2 shows the other variable inputs have positive signs,
normalized profit functions for rice implying that an increase in land and
production in the study Areas during the the other variable inputs in the production
2008/2009 cropping season. of rice would increase the profit level and
vice versa.( Lau and Yotopolous, 1979).
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Journal of Sustainable Development Vol. 7. No.1, March 2010
Table 2: Normalized Profit Function for Credit Users
Variable Linear Exponential Semi log Doublelog
Constant 1.624 1.457 174.642 1.287
t-ratio 0.093 2.673 -3.229 0.765
P[ITI>t] 0.926 0.089 0.002 0.446
Fixed Input 0.119 -0.313 9.444 -0.404
t- ratio 2.486 -0.210 2.329 -0.321
P(ITI>t] 0.015 0.834 0.022 0.749
Farm size 17.289 0.279 61.549 1.080
t-ratio 7.357 3.820 9.736 5.491
P [ITI] > t] 0.000 0.000 0.000 0.000*
Normalized Planting material -5.549 -0.593 -15.766 0.940
t- ratio -2.986 -0.103 -3.3350 0.064
P[ITI> t] 0.004 0.918 0.00 0.949
Normalized Fertilizer -484.564 -7.571 -23.535 -0.412
t-ratio -1.528 -0.768 -1.909 -1.074
P [ITI >t] -0.130 0.444 0.059 0.286
Normalised Herbicide 0.654 0.506 3.738 0.170
t-ratio 0.597 1.487 1.962 2.868
P[ITI>t] 0.552 0.140 0.053 0.0051*
Normalized Storage chemical 0.625 -0.493 0.334 0.111
t-ratio 0.009 -0.22 0.084 0.089
P [ITI>t) 0.993 0.825 0.934 0.929-
Normalized wage 10.834 1.299 13.246 1.540
t- ratio 1.056 4.073 1.208 4.512
P tlTI>t] 0.294 0.00 0.230 0.000*
R2 0.608 0.532 0.712 0.594
AdjR2 0.642 0.497 0.690 0.563
F- value 26.72 15.14 32.85 19.43
N 101 101 101 101
* = 1% level of significance **= 5% level of significance ***= 10% level of significance
Estimated Normalized profit function for This means increasing returns to scale.
credit users This case of increasing returns is not very
In TTcu = 1.287 - 0.404z1 +1.079z2 + 0.939xl common in agriculture, but when such
-0.412 x2 + 0.169 x3+0.111 x 4 + 1.539x5 cases are observed, they occur at relatively
(0.765> (-0.321) (5.491) low levels of output that are characteristic
(0.064>- (-1.074> (2.868) (0.089)'" of small scale (peasant) farming. Thus is
(4.512) given as
n 101 I al + PI > 1 = Increasing refurns to scale
R2 0.594 (Olayide and Heady, 1982).
R-2 0.563
Fvalue = 19.43 The R2 value is high at 0.594 signifying an
explanation of 59.4 percent of the variation
in the profit by the explanatory variables.
Since the normalized profit function was The F value is highly significant at 1
patterned after Cobb Douglas production percent level
function, the sum of a and P parameters,
which represent return to scale was 3.025.
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Journal of Sustainable Development Vol. 7. No.1, March 2010
Problems affecting rice production Insufficient agricultural inputs have a
As shown in Table 3, credit facilities have positive correlation coefficient of 0.333 at
a negative correlation coefficient of 0.367 1percent level of significance this means
at 1 percent level of significance. This that as the problem of agricultural inputs
means that as the problem of credit reduces production will decrease.
reduces the .level of production will Shortage of land has a positive correlation
increase. It implies that credit has a great coefficient of 0.184 at 5 percent level of
effect on farmers' level of production. significance. This implies that as the
Shortage of labour has a negative problem of land reduces level of
correlation of 0.290 at 1 percent level of production will decrease. Lack of enough
significance. This implies that as the agricultural information has a positive
problem of labour reduces the level of correlation of 0.05 at 1 percent level of
production will increase. significance. Showing that as the problem
of agricultural information reduces the
level of production will decrease.
Table 3:Results of correlation analysis (Dependent variable-level of production)
Variable Correlation Coefficient
Shortage of labour -0.290*
Shortage of land 0.184**
Insufficient agricultural inputs 0.333*
Lack of credit facilities -0.367*
Lack of enough agricultural information 0.05*
* - 1%level of significance ** = 5%level of significance *** = 10%level of significance
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