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THE IMPACT OF GROSS DOMESTIC PRODUCT ON CO2 EMISSIONS
(A CASE STUDY OF ASIAN TIGER COUNTRIES).
Boburbek Khakimov
Senior lecturer, Oriental University, Tashkent
Muazzam Khakimova
Student, Uzbekistan State World Languages University
https://doi.org/10.5281/zenodo.15038712
Annotation:
This research examines the impact of Gross Domestic Product
(GDP) on CO2 emissions in four well-developed Asian countries—South Korea,
Singapore, Taiwan, and Hong Kong—over the period from 1960 to 2019. To
analyze the relationships, regression was performed using the Generalized Least
Squares (GLS) method in STATA-14. The results indicate that all regressors are
significant, and to address the issue of autocorrelation in the model, an
Autoregressive Lag model was used. By adding the lag of an independent
variable to the model, the problem of autocorrelation was resolved.
Consequently, the model's goodness-of-fit improved, and the significance levels
of the regressors were confirmed. Based on the research findings, it can be
concluded that the economic growth of these countries leads to an increase in
carbon dioxide emissions into the external environment.
Keywords:
Gross Domestic Product, CO2 emissions, GLS method, STATA14,
correlation, Autoregressive Lag model, coefficient of determination.
1. Introduction.
The reason we chose this specific topic is that today, the
issue of environmental pollution, particularly the problem of carbon dioxide
emissions that have a range of negative and harmful effects on living organisms,
is becoming one of the most pressing concerns. For the analysis, four countries
from Asia, specifically the Asian Tiger countries, were selected. These countries
have both developed and developing economies, and the analyses conducted can
also be applied to Uzbekistan.
The aim of the research presented in the monograph is to evaluate the
impact of economic and environmental policies on the state of the environment
and to develop methods for this assessment. To achieve this goal, the following
tasks were addressed:
1.
Developing the proposed approach, improving the previously
established ones, and creating new mathematical models and methods based on
the identified connections between economic and environmental indicators that
will allow for the assessment of the impact of various factors on environmental
pollution.
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2.
The country analysis demonstrates the relationship between GDP
growth and CO2 emissions in the Asian Tiger countries.
3.
Based on the constructed pollution functions, conducting a
comparative analysis of the impact of economic development on the
environment in these countries and neighboring countries (regions) with similar
natural-climatic conditions and similar economic structures.
Since the works of J. Forrester, M. Mesarovich, and E. Pestel, significant
attention has been given to the environmental consequences of economic
development. Since the late 1980s, ecological economics has developed rapidly,
including the development of specialized mathematical models.
Among the modern studies in the field of ecological and economic
interactions are the works of T. A. Akimova, S. N. Bobylev, I. P. Glazyrina, A. A.
Gusev, V. I. Danilov-Danilyan, M. F. Zamyatina, G. E. Mekush, N. V. Pakhomova, I.
V. Sheravniy, R. I., R. I., and others. Special models are developed to assess the
interaction of economic and ecological processes, which together describe the
behavior of ecological and economic systems and allow for the identification and
quantitative assessment of the main factors influencing changes in the ecological
situation.
At the same time, the impact of significant factors within a single year and
their effect on the environment, as well as their influence on indicators in
subsequent years, has not been sufficiently studied.
2. Methodology
Figure 1. Digital Descriptive Statistics
In the STATA-14 program, the "sum" command is used to view the number
of observations, the arithmetic mean, the quadratic mean deviation, as well as
the minimum and maximum values.
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Figures 2-3. Normal Distribution Analysis
The comparison between statistical indicators and the normal distribution
is illustrated in Figures 2-3, where we can observe that our indicators closely
approximate the normal distribution.
Figure 4. Correlation Analysis.
The results of the correlation analysis show that GDP and CO2 have a strong
positive correlation.
Figure 5.
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The analysis of carbon dioxide emission indicators by country is presented
in Figure 5. Although the patterns may appear different at various scales, the
scatter plots of the countries present nearly the same shape.
Analysis of Results.
The results of the regression analysis on the collected data are presented in
Figure 6.
Figure 6.
The results of our regression analysis show that a 1% increase in GDP leads
to a 9.28% increase in CO2 emissions. The overall coefficient of determination is
92.72%. Our p-value indicates that the result is statistically significant.
It is necessary to check the regression results according to the Gauss-
Markov conditions. The results are presented in Figures 7 and 8.
Figure 7.
Figure 8.
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The Breusch-Pagan heteroscedasticity test is presented in Figure 7.
According to its results, there is no heteroscedasticity problem in our model. The
Breusch-Godfrey test, presented in Figure 8, checks the model for
autocorrelation issues. The test results show that autocorrelation exists even at
the 5th-order lag. Although we do not present it here, we also checked that
autocorrelation causes issues at all existing lags.
To address the autocorrelation issue in the model, we use an
Autoregressive Lag model. By adding the lag of the independent variable to the
model, we resolve the autocorrelation problem in the model.
The results of the Autoregressive Lag model are presented in Figure 9.
According to these results, the model’s coefficient of determination has
improved, and the significance levels of the regressors have been confirmed. A
1% increase in GDP leads to a 0.21% increase in carbon dioxide emissions.
Figure 9.
The results of our research confirmed the views presented in the scientific
literature.
Conclusion.
Based on the conducted research, it can be concluded that the
economic growth of countries leads to an increase in carbon dioxide emissions
into the external environment. This phenomenon negatively impacts the
environment, causes ecological degradation, and leads to the formation of ozone
holes. Therefore, this process should be monitored by governments to maintain
a balance.
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