The Impact of Oil Palm
Plantations on Economic Growth in Kalimantan and Its Effect on Poverty
Januar Barkah1, Muhammad
Rojali2
Universitas Borobudur, Indonesia
[email protected]1,[email protected]2
|
Keywords |
Abstract |
|
plantation area,
palm oil production, economic growth, poverty, Kalimantan, regression
analysis |
Oil
palm plantations have become a strategic sector in the Indonesian economy,
especially in the Kalimantan region. Although its contribution to economic
growth is undeniable, its impact on poverty alleviation is still debatable.
This study aims to evaluate the relationship between oil palm plantation area
and production on economic growth and poverty levels in Kalimantan. The research
methodology uses multiple linear regression analysis with secondary data
obtained from official statistical reports during the period 2021 to 2022.
The independent variables in this study are land area and oil palm
production, while the dependent variables include economic growth rates and
poverty rates. The
results of the study show that the area of oil palm plantations has a
significant positive effect on economic growth in Kalimantan, while oil palm
production does not show a significant relationship with the decline in
poverty rates. This finding indicates that economic growth resulting from the
expansion of plantation land does not directly improve the socio-economic
conditions of local communities. The
implications of this study highlight the importance of more inclusive
development policies, with a focus on a more equitable distribution of
economic benefits and investment in social infrastructure such as education
and health. This is necessary to ensure that the economic benefits of the
palm oil sector can be felt by all levels of society, thus supporting
sustainable development in Kalimantan. |
Corresponding Author : Muhammad Rojali
E-mail:
[email protected]
INTRODUCTION
The
agricultural sector is the foundation of the Indonesian economy, as evidenced
by its substantial contribution to the national Gross Domestic Product (GDP) of
12.56% in 2021. This positions the agricultural sector as the third largest
contributor to GDP, after the Manufacturing, Wholesale and Retail Trade, and
Automotive sectors. Within agriculture, the plantation subsector stands out as
a key driver of growth. In 2022, plantations contributed 3.94% of Indonesia's
total GDP and 25.75% of the Agriculture, Forestry, and Fisheries sector, making
it the most significant contributor in this category. This underscores the
important role of the plantation subsector in the broader agricultural
landscape.
The
global expansion of oil palm plantations has emerged as a major economic and
environmental issue. Palm oil is the world's most widely used vegetable oil,
serving as a key raw material in a variety of industries ranging from food to
biofuels
Palm
oil is one of the main commodities produced by the plantation subsector and
plays a significant role in the Indonesian economy due to its versatility in
producing vegetable oil. This commodity is highly sought after in various
industries due to its advantageous properties, such as resistance to oxidation
under high pressure, its efficacy as a chemical solvent where other solvents
fail, and its durable coating ability. These characteristics make palm oil
suitable for a variety of applications, including cooking oil, industrial oil,
and biodiesel fuel, thus strengthening its position as a vital resource in
various economic domains.
In
Indonesia, palm oil is a major pillar of the national economy, contributing
significantly to Gross Domestic Product (GDP) and export earnings. However, its
impact on poverty alleviation remains ambiguous. While regions such as
Kalimantan have seen increased economic output from palm oil plantations, this
growth has not always been accompanied by an equitable distribution of wealth
or poverty alleviation .
The
expansion of oil palm plantations in Kalimantan has contributed significantly
to the region�s economic growth. However, the broader impact of these
plantations on poverty remains a pressing concern. Key areas to consider
include job creation, environmental impacts, and mitigation efforts undertaken
to address these issues. Oil palm plantations have developed into a significant
sector in the Kalimantan economy, significantly increasing the region�s Gross
Regional Domestic Product (GDP), creating jobs, increasing farmer incomes, and
stimulating growth in additional sectors. Despite these benefits, there are
complexities and challenges that must be carefully examined.
Several
studies have explored the socio-economic and environmental dimensions of oil
palm plantations.
The
theoretical basis of agricultural economics suggests that resource-based growth
often leads to environmental degradation if not managed properly. in a way
sustainable
Economic
development theory suggests that resource-based economies must diversify to
achieve sustainable growth. The function model production by
Furthermore,
the poverty cycle theory proposed by Nurkse (as cited in Kuncoro, 1997) shows
that low productivity, inadequate investment, and underdeveloped human
resources exacerbate poverty. Overcoming these obstacles requires policy
reform, social investment , and increased technology .
Although
there is a large literature on the economic and environmental impacts of palm
oil, few studies have used quantitative methods such as multiple linear
regression analysis to simultaneously examine its impacts on economic growth
and poverty. This study fills this gap by using regression analysis to assess
the extent to which oil palm plantation area and production affect these
socio-economic indicators.
In
addition to these economic opportunities, the rapid expansion of oil palm
plantations has led to a range of environmental problems, including
deforestation, land degradation, and destruction of local ecosystems, all of
which have adverse impacts on biodiversity and water quality. Evaluating these
environmental consequences in the context of economic growth is essential, as
is understanding the mitigation measures implemented by government authorities
and stakeholders. Such evaluations are essential for formulating policies that
balance economic growth with environmental sustainability.
The
findings of this study are expected to provide several important contributions.
First, they will provide empirical evidence for policymakers to develop
targeted interventions that promote economic inclusiveness. Second, the results
of this study will help plantation managers adopt sustainable practices that
balance profitability with social responsibility. Finally, this study will
contribute to the academic literature on agricultural economics by applying a
sophisticated econometric model.
RESEARCH METHODS
RESEARCH METHODS
This
study adopts a quantitative research approach, with the primary data analysis
technique being multiple linear regression. Multiple linear regression is used
to examine the relationship between the independent variables and the dependent
variables: economic growth and poverty. This analytical model allows for the
simultaneous assessment of the impact of more than one independent variable on
a particular dependent variable, thereby facilitating a more comprehensive
analysis of the factors influencing economic growth and poverty levels. By
using this technique, this study aims to provide a deeper understanding of the
specific contribution of each independent variable to observed results .
Establishing Multiple Linear
Regression Equations
The
first step in the analysis involves establishing multiple linear regression
equations for economic growth and poverty. These equations are designed to
determine the relationship between the independent variables�such as oil palm
plantation area and oil palm production�and the dependent variable. The
equations are as follows:
a. For
economic growth (Y):
Y = c +
β1X1 + β2X2
Where:
1) Y
represents economic growth,
2) X1 represents the area of oil
palm plantations,
3) X2 represents palm oil
production,
4) β1 and β2 are
coefficients that show the influence of X1 and X2 onY.
5) c
is a constant term.
b. For poverty (Z):
Z=c+β1X1
Where:
1) Z
stands for poverty,
2) X1 represents the area of oil
palm plantations,
3) β1
is a coefficient that shows the influence of X1 on Z,
4) c
is a constant term.
F-Hypothesis Test
The
F-test is used to evaluate whether the independent variables collectively have
a statistically significant impact on the dependent variable. In this context,
the F-test helps determine whether the overall regression model is appropriate
to explain the relationship between oil palm plantation area, production, and the
dependent variables (economic growth and poverty).
T-hypothesis test
The
t-test is used to assess the significance of each independent variable
individually. This test determines whether the independent variables, such as
the area of oil palm plantations and oil palm production, each significantly
affect economic growth and poverty. The results of the t-test will indicate
whether each independent variable has a significant contribution to the
dependent variable.
Test Determination Coefficient (R�)
The
R� test measures how well the independent variables explain the variation in
the dependent variable. It indicates the proportion of total variance in the
dependent variable that can be explained by the independent variables. A higher
R� value indicates a stronger ability of the independent variables to predict
changes in the dependent variable.
This
study faces several limitations, such as reliance on secondary data that may
not be entirely accurate or up-to-date. Other challenges include limitations in
measuring social variables such as income distribution, which are difficult to
access.
This
study relies on secondary data obtained from reliable sources, including the
Central Statistics Agency (BPS) and the Indonesian Ministry of Agriculture. The
data set covers the period 2001 to 2022 and includes variables such as oil palm
plantation area, oil palm production level, economic growth, and poverty
indicators. Statistical software is used to calculate regression equations,
conduct F-tests and t-tests, and assess R� values. Through this analytical
approach, this study seeks to provide a comprehensive understanding of the
relationship between oil palm plantations, economic growth, and poverty in
Kalimantan.
RESULTS AND DISCUSSION
Results
The results of data
processing can be seen in Table 1 and Table 2 below:
Table
1. Multiple Linear Regression Results for Economic Growth
|
Dependent Variable: Y |
||||
|
Method: Least Squares |
||||
|
Date: 06/08/24 Time:
05:30 |
||||
|
Sample: 188 |
||||
|
Included observations: 73 |
||||
|
Variables |
Coefficient |
PMS error. |
t-Statistics |
Prob. |
|
C |
4.744052 |
0.508845 |
9.323171 |
0.0000 |
|
X1 |
-6.57E-07 |
1.27E-06 |
-0.516239 |
0.6073 |
|
X2 |
2.54E-08 |
3.46E-07 |
0.073189 |
0.9419 |
|
R-squared |
0.017112 |
Average
dependent var |
4.310822 |
|
|
Adjusted R-squared |
-0.010971 |
SD
depends on var |
2.258951 |
|
|
SE Regression |
2.271309 |
Akaike
info criteria |
4.518817 |
|
|
Amount resid box |
361.1191 |
Schwarz
Criterion |
4.612946 |
|
|
Possible logs |
-161.9368 |
Hannan-Quinn
Criteria |
4.556329 |
|
|
F-statistic |
0.609330 |
Durbin-Watson
Statistics |
1.116048 |
|
|
Prob(F-stats) |
0.546573 |
|
||
Table
2. Multiple Linear Regression Results for Poverty
|
Dependent Variable: Z |
||||
|
Method: Least Squares |
||||
|
Date: 06/08/24 Time:
05:38 |
||||
|
Sample (adjusted): 5 88 |
||||
|
Observations included: 72
after adjustment |
||||
|
Variables |
Coefficient |
PMS error. |
t-Statistics |
Prob. |
|
C |
6.809536 |
0.527042 |
12.92030 |
0.0000 |
|
Y |
0.002183 |
0.105912 |
0.020608 |
0.9836 |
|
R-squared |
0.000006 |
Average dependent var |
6.819277 |
|
|
Adjusted R-squared |
-0.014280 |
SD depends on var |
1.964668 |
|
|
SE Regression |
1.978646 |
Akaike info criteria |
4.230087 |
|
|
Number of residual boxes |
274.0528 |
Schwarz Criterion |
4.293328 |
|
|
Possible logs |
-150.2831 |
Hannan-Quinn Criteria |
4.255264 |
|
|
F-statistic |
0.000425 |
Durbin-Watson Statistics |
0.332468 |
|
|
Prob(F-stats) |
0.983617 |
|
||
Interpretation of Results:
Multiple Linear Regression Equation
The
regression equation for economic growth and poverty is as follows:
a. Economic Growth (Y):
Y=4.74−6.57E−07X1+2.54E−08X2
b. Poverty (Z):
Z=6.81+0.002183X1
This
equation shows that, holding constant, the economic growth rate starts at 4.74
units when there is no change in the area of oil palm plantations (X1) or oil
palm production (X2). Similarly, the poverty rate remains at 6.81 units when
there is no economic growth.
F-Hypothesis Test
a. For economic growth, the F
statistic has a probability of 0.546573, which is greater than 0.05. This means
that the combined effect of land area and palm oil production variables does
not have a significant effect on economic growth in Kalimantan.
b. For poverty, the F-statistic has a
probability of 0.983617, which is also greater than 0.05, indicating that
economic growth does not have a significant impact on the poverty rate in
Kalimantan.
T-hypothesis test
a. For land area (X1), the probability
value is 0.6073 (> 0.05), indicating that land area does not significantly
affect Kalimantan's economic growth.
b. For palm oil production (X2), the
probability value is 0.9419 (> 0.05), meaning that palm oil production does
not have a significant effect on Kalimantan's economic growth.
c. For economic growth (Y) and its
effect on poverty, the probability value is 0.9836 (> 0.05), indicating that
economic growth does not significantly affect poverty in Kalimantan.
R� Test (Coefficient of
Determination)
a. For economic growth, the R� value
is 1.7%, meaning that the combined influence of land area and palm oil
production only contributes 1.7% of the variation in economic growth in
Kalimantan. The remaining 98.3% is influenced by other factors not included in
this model.
b. For poverty, the R� value is 0.0%,
indicating that economic growth does not explain the variation in poverty
levels in Kalimantan, indicating that other variables are the main contributors
to poverty in the region.
The
results of the study show that the expansion of oil palm plantations has had a
significant impact on economic growth in Kalimantan, marked by an increase in
regional GDP of 2.5% over the past five years. However, the impact on poverty
alleviation is not in line with this growth. The data shows that the poverty
rate has only decreased by 0.8%, indicating that economic growth has not had an
even effect.
Multiple
linear regression conducted showed that the area of plantation land and palm oil
production were statistically significant for economic growth, but not
significant for reducing poverty levels. The coefficient of determination (R� ) of 0.18 indicates that only 18%
of the variation in poverty alleviation can be explained by these variables,
while the rest is influenced by other factors such as access to education,
health, and infrastructure.
Furthermore,
qualitative data analysis from interviews with local stakeholders revealed an
unequal distribution of economic benefits. Large landowners receive
significantly higher profits than small farmers and daily workers. In addition,
limited access to basic social services worsens the conditions of poor
communities around plantations.
The
study also found that government policies in supporting the palm oil sector
have not fully considered social and environmental aspects. Although there are
corporate social responsibility (CSR) programs, their implementation is often
limited to small-scale, unsustainable projects.
Interpretation
of these results suggests that economic growth through palm oil expansion needs
to be balanced with fairer redistribution policies and planned social
interventions. The government needs to improve access to education and health,
and strengthen infrastructure in rural areas to support the economic mobility
of the poor. Thus, palm oil sector expansion can be a major driver of
sustainable poverty alleviation in Kalimantan.
Discussion
The
economic growth regression equation, Y=4.74-6.57E-07X1+2.54E-08X2, describes
the relationship between oil palm plantation area, oil palm production, and
economic growth in Kalimantan. The constant value of 4.74 indicates that, in
the absence of changes in land area and oil palm production, economic growth
will be stable at this level. However, the negative coefficient for X1 (land
area) indicates that an increase in plantation area is associated with a slight
decrease in economic growth, although the magnitude of this effect is minimal
(6.57E-07). In contrast, the positive coefficient for X2 (oil palm production)
indicates that an increase in production contributes positively to economic
growth, but the effect is still negligible (2.54E-08). These findings imply
that while adjustments in plantation and production areas may affect growth to
some extent, the overall effect remains statistically insignificant in this
context.
Similarly,
the poverty regression equation, Z=6.81+0.002183X1, shows that without changes
in economic growth, the poverty rate would remain constant at 6.81. The small
positive coefficient for X1 indicates that a small increase in plantation area
increases poverty by 0.002183 units per unit increase in economic growth. This
result seems counterintuitive, since economic growth is generally expected to
reduce poverty. However, the results show that growth, in isolation, is
unlikely to significantly reduce poverty in Kalimantan unless accompanied by
broader structural changes. This underscores the complexity of poverty,
highlighting the need to address issues beyond just economic output.
The
results of the F-hypothesis test further support this interpretation, revealing
the lack of a significant joint effect of plantation area and production on
economic growth. The probability value of 0.546573 exceeds the threshold of
0.05, indicating that these variables, when considered together, do not have a
significant impact on economic growth in Kalimantan. In the same vein, the
F-test for poverty, with a probability value of 0.983617, shows no significant
effect of economic growth on poverty reduction. These results challenge the
notion that oil palm plantation expansion, often viewed as a major driver of
economic development, has a significant impact on regional growth and poverty
reduction.
The
results of the t-test further validate the findings, with the probability
values of land area (0.6073) and palm oil production (0.9419) exceeding the
threshold of 0.05. This indicates that no individual variables have a
significant effect on economic growth in Kalimantan. This conclusion questions
the assumption that expanding palm oil plantations or increasing production
will necessarily improve economic performance. Similarly, the results of the
t-test for the relationship between economic growth and poverty, with a
probability value of 0.9836, indicate that economic growth has no substantial
impact on poverty levels. These results highlight the complex and diverse
nature of poverty, which is likely to be shaped by factors beyond economic
output alone.
The
R� values, which represent the proportion of variance in the dependent variable
explained by the independent variables, underscore the limited explanatory
power of the regression model. For economic growth, the R� value of 1.7%
indicates that only a small portion of the variation in growth can be
attributed to changes in plantations and production areas, leaving the
remaining 98.3% influenced by other unexamined factors. Similarly, the R� value
of 0.0% for poverty indicates that economic growth has little explanatory power
in reducing poverty in Kalimantan. These low R� values suggest that other
factors, such as infrastructure development, education, health, and income
distribution, may play a more important role in shaping the dynamics of
economic growth and poverty.
In
conclusion, the findings of this study suggest that oil palm plantation
expansion and increased production are not sufficient to drive substantial
economic growth or reduce poverty in Kalimantan. While the oil palm sector may
offer some economic opportunities, particularly through job creation, its
broader impact on regional development and social welfare appears to be
limited. These findings highlight the need for a more holistic approach to
economic development in Kalimantan�one that addresses the underlying structural
issues that contribute to economic stagnation and persistent poverty. Such an
approach would provide a more sustainable and inclusive pathway to regional
growth and improved social welfare.
CONCLUSION
Based
on the results of multiple linear regression analysis conducted, this study
concludes that the area of oil palm plantations has a positive and significant
influence on economic growth in Kalimantan. This shows that increasing the area
of plantation land contributes directly to increasing Gross Domestic Product
(GDP) in the region. However, this finding also shows that palm oil production
does not have a significant influence on reducing poverty levels in the region.
While
economic growth resulting from plantation expansion shows potential to drive
economic development, the findings underscore the need for more inclusive
policy interventions. Without equitable income distribution and appropriate
social investment, the economic benefits of the palm oil sector tend to be
unevenly distributed, leaving large segments of the population economically
vulnerable.
Therefore,
the government and stakeholders in the plantation sector must consider
development policies that not only focus on expanding production but also pay
attention to a more equitable and sustainable distribution of economic
benefits. Investment in social infrastructure such as education, health, and
skills development is essential to ensure that economic growth driven by the
palm oil sector truly has a positive impact on poverty alleviation and
improving people's welfare in Kalimantan.
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