Investigate the Impact of Carbon Dioxide Emissions on Total Fertility
Rate in Taiwan: Human Development Index as Mediator
TZU-KUANG HSU1, KUN-HUNG PAN2,*
1Department of Business Administration,
Chung Hua University,
Hsinchu,
TAIWAN, R.O.C.
2Ph.D. Program of Management,
Chung Hua University,
Hsinchu,
TAIWAN, R.O.C.
*Corresponding Author
Abstract: - This study is to investigate the dynamic relationships among carbon dioxide (CO2) emissions, the
Human Development Index (HDI), and the Total Fertility Rate (TFR) in Taiwan from 1992 to 2021 by using an
innovative method, called quantile mediation analysis. Our findings show that CO2 emissions negatively directly
affect TFR. We also find that HDI, which measures the overall development of a country, has a partly mediation
effect at the distribution of TFR within 0.2 to 0.6 quantiles. Moreover, the results reveal that there exists a
U-shaped relationship between CO2 emissions and TFR, and between CO2 emissions and HDI at the higher 0.8
quantile level. According to these results, we suggest that the Taiwanese government continue investing in
education, healthcare, and gender equality as critical human development sectors. Such investments can mitigate
the negative impact of CO2 emissions on TFR, and balance environmental factors and demographic outcomes.
These policy implications are crucial for policymakers and researchers in environmental science, public health,
and social policy.
Key-Words: - Carbon Dioxide Emissions (CO2); Economic Growth; Environmental Kuznets Curve (EKC);
Human Development Index (HDI); Quantile Mediation Analysis; Total Fertility Rate (TFR).
1 Introduction
There exists a critical issue in the interaction between
carbon dioxide (CO2) emissions and the total fertility
rate (TFR) because it illustrates the complex
relationship between environmental factors and
population dynamics. CO2 emissions are a significant
trigger of climate change, which significantly affects
human health, economic development, and the
natural environment. These effects can impact on
reproductive behaviors and decisions, even affecting
TFR, [1]. Studies by authors [1] and [2] have
demonstrated that CO2 emissions negatively affect
TFR. However, extensive research, including the
works in Bangladesh [3], China [4], and Saudi
Arabia [5], has established a causative link between
CO2 emissions and the Human Development Index
(HDI). Population dynamics must be fully
considered when formulating climate change
mitigation strategies.
Focusing on population dynamics, we use the
Total Fertility Rate (TFR) as the key indicator. It
measures the average number of children a woman is
expected to have during her reproductive years. As
the author [6] pointed out, environmental and
demographic factors must be considered when
making population policies. This is important
because fertility rates are influenced by social,
economic, and cultural factors, all of which are tied
to environmental changes and how resources are
used. Recent research has indicated that the link
between TFR and the Human Development Index
(HDI) would change at different stages of economic
development, [7]. This highlights how important it is
to consider these factors at various stages of
economic development and shows how complex and
non-linear the relationship between TFR and HDI is.
In addition, the Human Development Index
(HDI) covers critical aspects like health, education,
Received: April 19, 2024. Revised: September 11, 2024. Accepted: October 13, 2024. Published: November 18, 2024.
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2024.20.56
Tzu-Kuang Hsu, Kun-Hung Pan
E-ISSN: 2224-3496
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Volume 20, 2024
and the economy, and shows direct and indirect links
with the Total Fertility Rate (TFR). For example, the
author [8] investigated the dynamic interactions
among HDI, TFR, and mortality rates. According to
author [9], explored how a decreasing TFR affects
economic growth. These researches indicated that the
TFR was linked to broader human development and
economic status. In most countries, an increase in
health, education, and economic development levels,
or an improvement in HDI, typically corresponds to a
decrease in the average number of children born per
woman. This trend is observed in numerous studies
and is widely acknowledged, [10]. However,
research by authors [11] reveals an intriguing
phenomenon: in some highly developed countries,
fertility rates may increase as HDI rises further,
suggesting a potential reversal in the TFR-HDI
relationship in these advanced nations. This
organizational framework is designed to
meticulously investigate the interaction between CO2
emissions and the TFR through the mediator of HDI
for Taiwan's economic and environmental
policymaking. Therefore, the main goal of this
study is to investigate the dynamic relationship
among carbon dioxide (CO2) emissions, the Human
Development Index (HDI), and the Total Fertility
Rate (TFR) in Taiwan. Moreover, we examine the
mediating role of the Human Development Index
(HDI) by using quantile mediation analysis. In other
words, we aim to analyze how CO2 emissions affect
TFR across different economic development stages,
providing valuable insights for policymakers.
The structure of this paper is as follows: Section
2 explores the literature review. Section 3 presents
the research methodology, and section 4 reports on
data collection, scope, and empirical results. Section
5 presents a detailed justification of significant
results. Section 6 provides conclusions and
suggestions for future research in Section 7. Section
8 reports the contributions of this study.
2 Literature Review
Climate change is all about the long-term shifts in
temperature and weather patterns, mainly caused by
human activities. The most apparent signs of climate
change include the rising global average
temperatures and increasing extreme and
unpredictable weather events, which have become
major international issues in recent years. These
changes threaten human well-being [12] and also
impact the survival and reproduction of other species
[13], affecting the sustainability of the entire Earth's
ecosystem. The author [14] found the significant
adverse effects of CO2 emissions on fertility rates in
the Middle East, North Africa (MENA), and the
Economic Community of West African States
(ECOWAS) regions during the period of 1970 to
2019. This emphasizes the urgency of understanding
how CO2 emissions impact the TFR. In other words,
we should find out how climate change affects
socioeconomic development.
According to author [15], pointed out that
compared with low-income countries, high-income
countries have the ability and willingness to invest in
environmental protection once they reach a certain
economic level, aiming to balance economic growth
and environmental sustainability. This theoretical
framework helps us provide a new perspective for
understanding and exploring the relationship
between CO2 emissions and economic development,
especially the impact on the economic aspects of the
Human Development Index (HDI), [16].
When we investigate the relationships among
CO2 emissions, the Human Development Index
(HDI) and the Total Fertility Rate (TFR), many
existing studies only examine the relationship
between two variables, [17], [18], [19], [20], [21],
[22], [23]. This study emphasizes things that other
studies missed. It investigates a dynamic interaction
among carbon dioxide emissions, the total fertility
rate, and the human development index. The study
puts all these variables together to understand how
they affect each other. This may provide new insights
into developing integrated strategies that effectively
address climate change, promote human
development, and control population growth.
This research uses an integrate method called
quantile mediation analysis to study the changing
cause-and-effect relationships between CO2
emissions and the TFR, with the HDI acting as a
mediation factor from 1992 to 2021 in Taiwan. The
study includes HDI as an important demographic
factor to see how it affects the relationship between
CO2 emissions and TFR. Besides, based on studies
by authors [24] and [25] on environmental pollution,
this research further explores whether there exists an
inverted U-shaped Environmental Kuznets Curve
(EKC) relationship between CO2 emissions and TFR,
as well as between CO2 emissions and HDI in
Taiwan.
The EKC is a key framework to understand the
nonlinear relationship between economic growth and
environmental quality when evaluating economic
development and human well-being. Therefore, the
EKC hypothesis suggests that an inverted U-shaped
relationship between economic growth and
environmental degradation. This study is similar to
the EKC hypothesis. It says that the environmental
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conditions worsen as a country's income increases
but improve after reaching a certain income level
because of technological advancements and
increased environmental awareness [26]. This idea
can understand how different stages of economic
development affect the environment [27].
Examining previous studies [28], [29], [30], and [31],
we establish a theoretical hypothesis which guides
the better policies and measures for government to
solve problems.
3 Methodology
3.1 A quantile Regression
This study integrates the mediation analysis method
[32] and the quantile regression method [33]. This
novel method helps us understand how interacts the
relationship between Taiwan's carbon dioxide
emissions, human development index (HDI), and
total fertility rate (TFR) from 1992 to 2021 [34], [35].
Furthermore, quantile regression can offer a
comprehensive insight into their interaction, analyse
the distributional skewness of variables and evaluate
the impact of independent variables on the dependent
variable across various quantiles [36]. According to
the quantile regression, it firstly establishes a
equation (1) to show the relation between the
dependent variable given the independent
variable .
(1)
Then, we define the conditional distribution
function in Equation (2). This formula explains the
likelihood that will be at most , contingent upon
.
) = F ( (2)
To measure the regression issue, we formulate
the subsequent Equation (3). The solution to this
equation is , from which we derive the
conditional quantile
() = X.
(3)
3.2 Mediation Effect on Human
Development Index
The purpose of this study is to investigate the
dynamic association among carbon dioxide
emissions, human development index (HDI) and
total fertility rate (TFR) and examine if it exists the
mediation effect of HDI. Here are important terms
and steps in equations (4) to (6):
Key Terms:
1: The regression coefficient that explains how
CO2 affects TFR.
1: The regression coefficient that explains how
CO2 affects HDI.
1 and 2: The regression coefficient that
explains how CO2 and HDI affect TFR
0, 0, d0: The intercept terms.
1, 2, 3: The error terms.
Equations We Used:
CO2 (4)
CO2 (5)
CO2 (6)
Here are the steps we investigate the mediation
effect of HDI how CO2 emissions affect TFR:
Step 1: Direct Relationship Between CO2 and TFR
If the coefficient 1 is significant in Equation
(4), then CO2 emissions directly related to
TFR. This step is important because it shows
a direct link between CO2 and TFR, which is
essential for mediation analysis.
Step 2: Relationship Between CO2 and HDI
CO2 emissions must be related to HDI,
making c1 in Equation (5) significant. This
step confirms the first part of the mediation
effect.
Step 3: Relationship Between HDI and TFR
HDI should be related to TFR, making d2 in
Equation (6) significant. This confirms that
HDI affects TFR.
Step 4: Mediation Effect of HDI
When accounting for HDI, CO2 should no
longer be significantly related to TFR,
making d1 in Equation (6) insignificant. This
indicates that HDI mediates the full effect of
CO2 on TFR.
If all these steps are met, it shows complete
mediation. If only the first three steps are met and d1
in Equation (6) remains significant but smaller than
b1 in Equation (4), it shows partial mediation.
Figure 1 illustrates our research framework,
which defines the mediating effect of the Human
Development Index (HDI) on the relationship
between CO2 emissions and TFR.
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Fig.1: Research framework on the mediating effect
of human development index
3.3 A Quantile Meditation Analysis
Utilizing the methods proposed by authors [34] and
[35], our methodology now encompasses quantile
mediation analysis. This addition permits the
examination of all conceivable parameters
throughout the quantile range, scrutinizing the
disparities in the dependent variable’s higher and
lower values. This ability to evaluate the full range of
quantiles represents a considerable improvement
over the traditional fixed-parameter regression
models, which are usually limited to a single
coefficient. Moreover, this novel method enhances
our dynamic and thorough comprehension of the
potential effects of CO2 emissions on the total
fertility rate or the absence thereof. In the model, θ
represents different quantiles. By integrating the
prior regression equation (3) into equations (4) to (6),
we can express it as equations (7) to (9), where the
model is operationalized through the aggregation of
weighted positive and negative error terms.
(7)
(8)
(9)
3.4 A Quantile Environmental Kuznets
Curve Model
The author [26] introduced the concept of the
Environmental Kuznets Curve (EKC), a hypothesis
that delineates the relationship between
environmental quality and economic development. It
posits that as an economy grows, indicators of
ecological degradation initially worsen before
improving once per capita income reaches a certain
threshold, forming an inverted U-shaped curve. The
United Nations Development Programme (UNDP),
which incorporates gross national income (GNI) into
the Human Development Index (HDI) assessment,
not only reflects the scale of the economy but also
reveals various characteristics and trends of
economic growth. Therefore, this study integrates the
EKC with quantile regression techniques, employing
the nonlinear models presented in equations (10) and
(11), which are widely recognized simplified
econometric models internationally, [37]. This
approach allows us to analyze whether there's an
inverted U-shaped relationship between carbon
dioxide (CO2) emissions and the Total Fertility Rate
(TFR) or the Human Development Index (HDI).
(10)
(11)
At any quantiles of TFR or HDI, we use
equations (10) and (11) to test the null hypothesis.
This hypothesis asserts that 1 and 1 are greater than
zero and 2 and 2 are less than zero. When the
p-values derived from the t-tests for these equations
are under 0.05, it denotes a statistically significant
inverse U-shaped pattern, which agrees with the
Environmental Kuznets Curve (EKC) concept
suggested by the author, [26].
4 Results
In examining the causal relationships between CO2
emissions and the TFR and the relationship between
CO2 emissions and the HDI in equations (7) and (8),
we present the results of causality tests in Table 1.
The notation x ≠> y indicates that variable x does
not influence variable y. Our research uncovers
critical insights, chiefly through quantile regression
analysis, which establishes a causative nexus
between CO2 emissions and the Total Fertility Rate
(TFR) across the 0.2 to 0.6 quantiles of TFR
distribution (as illustrated in Table 1 and Figure 2). It
HDI
CO2
TFR
c1
b1 / d1
d2
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suggests that within the TFR quantile distribution
below 0.8, an elevation in CO2 emissions is reliably
and significantly linked with a negative shift in TFR.
This outcome sets the stage for the initial segment of
the mediation effect, underscoring a consistent and
impactful relationship of CO2 on TFR for quantiles
below 0.8 in the TFR distribution. Furthermore, in
our analysis, quantile regression techniques have
revealed a substantial causal link between CO2
emissions and the Human Development Index (HDI)
within the 0.2 to 0.8 quantile range. This
demonstrates a steady positive correlation between
the rise in CO2 emissions and the enhancement of
HDI throughout the entire HDI quantile distribution
(refer to Table 1 and Figure 3). To put it differently,
there exists a uniform positive relationship between
the escalation of CO2 emissions and the advancement
of HDI across the quantiles, suggesting a widespread
influence of increased CO2 emissions on the
augmentation of HDI.
Table 1. Results from CO2 to HDI and from CO2 to
TFR at Different Quantiles
CO2 ≠> HDI
CO2 ≠> TFR
Quantile
P-
value
P-
value
0.20
0.016
0.019*
-0.289
0.000*
0.40
0.023
0.002*
-0.315
0.000*
0.50
0.025
0.001*
-0.306
0.000*
0.60
0.027
0.000*
-0.304
0.000*
0.80
0.031
0.000*
-0.507
0.154
* Denotes significance at the 5%
Fig. 2: Variation of the Quantile Regression
Coefficients of TFR concerning CO2
Note: The x-axis represents the carbon dioxide quantiles, while
the y-axis denotes the regression coefficient values for the total
fertility rate. The red dashed lines indicate the 95% confidence
intervals for the quantiles.
Fig. 3: Variation of the Quantile Regression
Coefficients of HDI concerning CO2
Note: The x-axis represents the carbon dioxide quantiles, while
the y-axis denotes the values of the human development
coefficients. The red dashed lines indicate the 95% confidence
intervals for the quantiles
Table 2 and Figure 4 demonstrate that at any
quantile distribution of TFR, the coefficient in
equation (9) is significant, indicating a correlation
between the mediator variable HDI and the
dependent variable TFR. This finding establishes the
second stage of the mediation effect. Furthermore,
when accounting for the mediating influence of the
Human Development Index (HDI), significant
correlations are observed between carbon dioxide
(CO2) emissions and the dependent variable, Total
Fertility Rate (TFR). This results in the coefficient
being statistically significant, less than the
coefficient b1 in equation (4) within the 0.2 to 0.6
quantile range of TFR. This suggests that when the
mediation effect transmitted through HDI is
considered, the initially examined relationship
between CO2 and TFR vanishes. This outcome
demonstrates partial mediation, as it does not satisfy
all four steps outlined in equations (4) through (6).
Table 2. Results from CO2 and HDI to TFR at
different quantiles
CO2 ≠> TFR
HDI ≠> TFR
Quantile
P-
value
P-
value
0.20
-0.309
0.000*
0.837
0.000*
0.40
-0.321
0.000*
0.829
0.000*
0.50
-0.328
0.000*
0.811
0.000*
0.60
-0.322
0.000*
0.812
0.000*
0.80
-0.297
0.000*
0.811
0.000*
* Denotes significance at the 5%
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Fig. 4: Variation of the Quantile Regression
Coefficients of TFR concerning CO2 and HDI
Note: The x-axis represents the Total Fertility Rate quantiles,
while the y-axis denotes the human development coefficients and
carbon dioxide values. The red dashed lines indicate the 95%
confidence intervals for the quantiles
In examining the Environmental Kuznets Curve
(EKC) at designated quantiles of carbon dioxide
emissions, we posited the following null hypotheses.
Given the relationship between the Human
Development Index (HDI) and carbon dioxide (CO2)
emissions, we test that α1 > 0 and α2 ≤ 0. Given the
relationship between the Total Fertility Rate (TFR)
and CO2, we test that β1 > 0 and β2 ≤ 0. If the
p-values for these coefficients are less than 0.05, it
impliesthat there is a significant inverted U-shaped
relationship at that quantile, supporting Krueger’s
EKC theory. The EKC theory suggests that
environmental degradation increases in the early
stages of economic growth but eventually decreases
as income rises, due to better environmental
awareness and technological progress. This pattern
has been validated by empirical studies in various
countries, including China and India.
Table 3 reveals that at the 0.8 quantile of the
Total Fertility Rate (TFR), we find α1 < 0 and α2 ≧ 0
with p-value < 0.05, which indicates a U-shaped
relationship between them. Consequently, this
illustrates that the association between the Human
Development Index (HDI) and carbon dioxide (CO2)
emissions at the 0.8 quantile of HDI is not supported
by the Environmental Kuznets Curve (EKC)
hypothesis.
Table 3. Results from CO2 and Squared CO2 to TFR
at Different Quantiles of TFR
CO2 ≠> TFR
CO22 ≠> TFR
Quantile
P-
value
P-
value
0.20
-0.290
0.001*
-0.003
0.966
0.40
-0.347
0.000*
-0.050
0.500
0.50
-0.319
0.000*
-0.015
0.849
0.60
-0.297
0.000*
0.011
0.901
0.80
-0.825
0.000*
0.608
0.000*
Note: *p<0.05
Table 4. Results from CO2 and Squared CO2 to HDI
at Different Quantiles of HDI
CO2 ≠> HDI
CO22 ≠> HDI
Quantile
P-
Value
P-
value
0.20
0.008
0.513
-0.006
0.613
0.40
0.018
0.075
-0.004
0.641
0.50
0.020
0.030*
-0.004
0.682
0.60
0.027
0.003*
-0.000
0.991
0.80
-0.607
0.002*
0.762
0.000*
Note: *p<0.051
In Table 4, the associations between the Human
Development Index (HDI) and carbon dioxide (CO2)
emissions at the 0.80 quantiles of HDI are
characterized erize < 0 and ≧ 0 with p-values
below 0.05. This signifies notable U-shaped
relationships at the 0.8 quantiles. Such findings
diverge from the Environmental Kuznets Curve
(EKC) theory, suggesting that at the 0.8 HDI
quantiles, an increase in CO2 initially leads to a
decrease in HDI, followed by a rise.
5 Detailed Justification of Significant
Results
When examining the Environmental Kuznets Curve
(EKC) at specific quantiles of CO2 emissions, we set
up the following hypotheses: Given the relationship
between the Human Development Index (HDI) and
CO2 emissions, we should find out that 1 > 0 and 2
≤ 0; Given the relationship between the Total
Fertility Rate (TFR) and CO2, we also should find out
that 1 > 0 and 2 ≤ 0. If the p-values for these
coefficients are less than 0.05, it indicates that there
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is a significant inverted U-shaped relationship at that
quantile, which aligns with Krueger’s EKC theory.
The EKC theory suggests that environmental
degradation increases to a certain point as an
economy grows. After reaching this point, as income
rises, ecological quality improves. This inverted
U-shaped relationship means that in the early stages
of economic development, environmental quality
gets worse. Still, it improves as economic growth
leads to more environmental awareness and cleaner
technologies.
Our study found some significant results in Table
3. At the 0.8 quantiles of TFR, we found out that
there exists a U-shaped relationship, which means an
increase in CO2 emissions first leads to a drop in TFR
but increase after reaching a certain level at higher
TFR quantiles. This finding is similar to Krueger’s
EKC theory, which explains the negative impact of
CO2 emissions on fertility rates at first, then reaching
a certain level reverses at higher development levels.
In addition, Table 4 shows a clear U-shaped
relationship at the 0.80 quantiles of HDI, with 1 < 0
and 1 ≥ 0 and p-values below 0.05. This finding is
different from what the EKC theory says. It shows
that when people live better (high HDI), more CO2
emissions first makes their lives worse (HDI goes
down). Then CO2 emissions reach a certain level,
people get better again (HDI goes up). This happens
because of many things working together, like new
rules to help the environment, better technology, and
changes in the economy as the country grows.
Our findings show that we need to think about
how CO2 emissions, how well people live HDI, and
how many babies are born TFR are connected in
complicated ways. This means that when we make
policies and measures to reduce CO2 emissions, we
need to consider how these connections change as a
country grows. Our novel quantile mediation
analysis gives significant proof of these complex
connections, supporting the hypothesis of the EKC
and providing useful advice for policymakers.
6 Conclusions
Many previous researches found that a causal
relationship between carbon dioxide (CO2) emissions
and total fertility rate (TFR). These researches
mostly used ordinary least squares methods and
indicated a negative effect of CO2 emissions on total
fertility. However, our study uses an integrate and
advanced method that combines mediation analysis
with quantile regression. This method provides a
dynamic and comprehensive explanation of the
conditional distribution of the total fertility rate
(TFR), instead of focusing on its conditional mean.
In other words, this method can investigate a broad
view how the impact of CO2 emissions on TFR in
Taiwan from 1992 to 2021.
Our study found that there exists the EKC
hypothesis in Taiwan. This finding indicated that a
significant U-shaped relation between CO2 emissions
and Total Fertility Rate (TFR) and between CO2
emissions and Human Development Index (HDI) at
the higher quantile distribution of the dependent
variable. This suggests that we should use more
sustainable energy sources to help the environment.
The hypothesis of Environmental Kuznets Curve
(EKC) indicates that environmental degradation rises
at the beginning of economic growth, but improves
once over a certain income level. Our study
demonstrates this hypothesis that there exists a
U-shaped relationship between CO2 emissions and
the Total Fertility Rate (TFR), and between CO2
emissions and the Human Development Index (HDI)
at higher quantiles distribution of dependent variable.
In our study, at 0.8 quantile distribution, it exists
CO2 emissions initially lead to a decrease in TFR,
following an increase in TFR. Figure 4 shows a
similar result that there exists a U-shaped
relationship between CO2 emissions and the Human
Development Index (HDI). These results indicate
that it exists the complex interactions among
economic growth, environmental quality, and
demographic variables. Moreover, it offers
significant insights for policymakers to establish
more effective strategies and measures.
Since this study provides valuable insights on the
interact between environmental factors and
population dynamics, the government should
establish an effective and sustainable policy. For
Example, the government should focus on the impact
of carbon dioxide emissions on the total fertility rate
at the different quantiles, especially given the effects
of environmental factors on fertility during the
demographic transition at higher quantile of total
fertility rate. This measure can decrease CO2
emissions and maintain human development
standards.
In this study, we only examine the data of
Taiwan, it may lead to the limit application of the
findings. Therefore, we could include comparative
studies in different countries or regions to understand
these relationships better in the future research.
Moreover, we include economic conditions,
education, and health in our study, it could provide a
comprehensive understanding of their effects on the
relationship between CO2 emissions and total
fertility rates.
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7 Future Research Directions
From the findings we found in this study, there are a
few things we can further study in the future. One
thing is to compare different countries or regions to
understand whether it exists the same relationships.
Applying new quantile mediation analysis
techniques will significantly improve our
understanding and validate research results in diverse
socioeconomic and environmental contexts. 2.
Although this study mainly focused on the Human
Development Index (HDI) as a mediating variable,
future research could consider other potential
mediating variables. These variables could include
measures of economic growth, education levels, or
health status. Including these indicators would allow
for a more thorough analysis of the various factors
that influence these relationships. 3. It is vital to
undertake long-term studies to track how CO2
emissions influence changes in the Total Fertility
Rate (TFR) and the Human Development Index
(HDI) over time. 4. Incorporating qualitative
research methods like interviews or case studies can
enhance quantitative research results and provide a
deeper understanding of the factors influencing the
relationship between CO2 emissions, total fertility
rate, and the Human Development Index. This
mixed-methods approach adds valuable depth and
detail to exploring these complex interactions.
8 Contributions of This Study
This study provides multiple academic contributions:
1. Innovative analysis methods: through integration
Interaction between CO2 emissions, TFR and HDI In
a single framework, our study provides more Get a
complete understanding of these developments
relation. In other research, they only examined the
relationship between CO2 emissions and TFR or
between CO2 emissions and HDI.
2. Methodological Innovation: Our quantile
mediation analysis provides strong evidence
supporting the EKC theory, highlighting the varying
impacts of CO2 emissions across different quantiles
of TFR and HDI. This methodological innovation
offers valuable insights for policymakers, suggesting
that targeted interventions at specific quantiles can
more effectively mitigate the negative impacts of
CO2 emissions.
3. New Insights: Our research confirms some
established relationships and uncovers new insights
into HDI's mediating role compared to other studies.
By highlighting HDI's partial mediation effect, this
study provides a more nuanced understanding of how
CO2 emissions influence demographic and
development outcomes.
Overall, this study underscores the importance of
considering the complex and non-linear relationships
among environmental, demographic, and
development variables. The findings offer practical
implications for policymakers aiming to design
effective and sustainable strategies to address the
multifaceted challenges of climate change.
Declaration of Generative AI and AI-assisted
Technologies in the Writing Process
During the preparation of this work the authors used
Grammarly in order to improve the readability and
language of the manuscript. After using this tool, the
authors reviewed and edited the content as needed
and takes full responsibility for the content of the
publication.
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Tzu-Kuang Hsu, Kun-Hung Pan
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
- Tzu-Kuang Hsu provides the idea of the method,
establishes the framework, and revises the paper.
- Kun-Hung Pan performed the data analysis and
wrote the paper.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
No funding was received for conducting this study.
Conflict of Interest
The authors have no conflicts of interest to declare.
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