Introduction
Climate
change in one of the most serious environmental threats facing mankind
worldwide (Anselm and Toafeeq, 2010). They further argued that there is a
general consensus among scientists an policy makers that the entire globe is
facing a real and serious long-term threat from climate change. Climate change
which is attributed to the natural climate cycle and human activities has
adversely affected agricultural production and productivity in Africa. Climate
change in form of extreme temperature, frequent flooding and drought and
increased salinity of water supply used for irrigation has become a recurrent
subject of debate globally (Ajetomobi, Abiodun and Hassan 2010).
Anselm and Taofeeq (2010) further
opined that climate change affects agriculture in several ways, including its
direct impact on food production. Ajetomobi et al (2010) argued that developing
countries are more likely to be negatively affected by climate change than
developed countries. He further claimed that more effort have been made to
quantify the economic impact of climate change on agriculture in developed
countries than developing countries. Thus, for instance he argued there has
been no major research carried out in Nigeria to study the economic effect of
climate change on agriculture.
Objective of the Study
The broad objective of this study is
to analyze effect of climate change on the productivity of rice in Abakaliki
Local government area of Ebonyi State.
The
specific objective is to determine
The relationship between the
socio-economic characteristics of rice farmers and the effect of climate change
on productivity of rice in the study area.
Hypothesis
The null hypothesis tested in this
study was:
Ho: Climate change has no significant effect
on the productivity of rice in the study area.
Analytical Technique
Model specification
The multiple regression analysis was used the specific
objective of the study.
Y = F(X1,
X2, X3, X4,X5X6)
Implicit form
Implicit Function
Y = bo
+ b1 x1+ b2x2 + b3 x3
+ b4x4 + b5x5 + b6x6
et
Explicit form
Where;
Y = Effect
of climate change on rice production
X1 = Age
(years)
X2 = Lender
X3 = Marital
status
X4 = Educational
status
X5 = Farm size (ha)
X6 = Land
Ownership
Et = Error
term
bo = Constant
b1
– b6 = Coefficient of multiple regression
determining
the relationship between the socio-economic characteristics of the respondents
on productivity of rice due to comate change.
The dependent variable Y (rice
productivity) was regressed against the independent variables which include:
gender (X1), Age (X2) marital status (X3),
Educational attainment (X4), farm size (X=5) and land
ownership (X6).
Table
(1): Multiple regression result on relationship between the socio-Economic
characteristics and Effect of rice productivity in the study area.
Variable
|
Variable name
|
Regression coefficient
|
Std error
|
T-value
|
Sign
|
Contant
|
17.533
|
2.269
|
7.728
|
0.000
|
|
X1
|
Age
|
0.039
|
0.036
|
-0.960
|
0.344
|
X2
|
Gender
|
-0.149
|
0.153
|
-0.973
|
0.358
|
X3
|
Marital status
|
0.029
|
0.016
|
0.572
|
0.571
|
X4
|
Educational level
|
-0.022
|
0.041
|
3.535
|
0.596
|
X5
|
Farm size
|
0.168
|
0.052
|
-3.229
|
0.003
|
X6
|
Land ownership
|
0.172
|
0.088
|
-1.969
|
0.057
|
R2 = 0.726
Adjusted
R2 = 0.704
Standard
Error of the estimate = 0.43634
Durbin-Watson = 1.870
Source:
survey, 2013
A
multiple regression model was adopted for the analysis. Base don the analysis
the corefficient of determination(R2)was 0.726. this showed that
about (72%) of the variation in the dependent variable Y (rice productivity)
was influenced by the combined effects of the independent variables, (X1-
X6)
From the result obtained, in table
above, it indicated that gender (X1) was negatively signed and
statistically insignificant. This implies that with male farmers the
productivity of rice increases.
Age (X2) on the other
hand was positively signed and statistically significant at 1%.
This means that with advance in age,
rice productivity tend to increase and can be attributed to the fact that at
advanced age, the farmers is married and with children, thereby increasing the
labour base of the farmer and hence influence his productivity.
The multiple regression coefficient
of marital status (X3) bore positive sign and statistically
significant.
This implies that there is a
positive relationship existing between the marital status and effect of climate
change on rice production in the study area.
Educational attainment (X4)
showed a negative sign but was statistically. In significant, Education is a
significant factor in facilitating certain agricultural activities as high education
tends to improve farmers level and efficiency in agricultural activities. This
is consistent with finding of Idiong (2007) who stated that vice farmers
efficiency will increase with increase in their years in schooling.
The result also indicated the
coefficients of farm size (X5( and land ownership (X6)
bore a positively signed but statistically significant. This implies that rice
productivity will increase depending on the farm size and land ownership of the
farmers in the study area.
Y = 17.533 + 0.039
- 0.149 +
0.029 – 0.022
(2.269) (0.036)
(-0.153) (0.016) (0.041)
+ -.168 +
0.172 + et
(0.088)
(0.052)
testing
of hypothesis
F-cal = R2(N-K)
1-R2(k-1)
where;
R2 = Multiple
regression determination
N = Sample
K = Number
of variables
F-cal = ?
F-cal = 0.726
(40-6)
1-0.726 (6-1)
F-cal = 31.944
1.37
F-cal = 23.32
F-cal = 3.29
Since
if F-cal is greater that F-tal, null hypothesis was rejected while alternative
hypothesis was accepted. This implies that climate change have significant
affect on the productivity of rice in the study area.
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