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American Journal of   Environmental
Economics (AJEE)

Investigating the Environmental Impacts of  Economic and Tourism Activity
Kinjal Kaondal1*, Sanjeet Singh1

Volume 4 Issue 1, Year 2025
ISSN: 2833-7905 (Online)

DOI: https://doi.org/10.54536/ajee.v4i1.5745
https://journals.e-palli.com/home/index.php/ajee

Article Information ABSTRACT

Received: July 12, 2025

Accepted: August 18, 2025

Published: September 11, 2025

One of  the serious problems that the world faces today is environmental degradation and 
there is a dire need to find the extent of  this degradation due to macroeconomic activities, 
as almost every country aims for rapid economic growth, so this present study throws light 
on the interrelationship among these variables. This study aims to analyse the effects of  
economic growth, energy usage and tourism activity on environmental degradation in Asian 
Emerging and Developing Economies from 1995 to 2022. The study employed the fixed 
effect, random effect models, along with the FGLS model. The existing literature does not 
reach a consensus on how different macroeconomic variables affect the environment, hence 
it’s necessary to have a deeper understanding of  how these variables interact. The empirical 
analysis indicates negative significant effects of  economic expansion and tourism, while 
energy consumption positively influenced the environmental indicator. These findings could 
be utilised for drafting regulatory measures in the selected countries, taking into account the 
fragile balance between economic prosperity and the environment.

Keywords

Economic Growth, Environmental 
Degradation, FGLS Model, 
Tourism 

1 Department of  Economics, Central University of  Himachal Pradesh, India
* Corresponding author’s e-mail: kinjalkaondal16@gmail.com

INTRODUCTION
Environmental concerns are among the main problems 
that the world is facing currently. Asian Emerging nations 
are the most populated and swiftest-moving nations, 
emitting the highest amount of  greenhouse gases, 
releasing over half  of  global carbon dioxide emissions   
(International Monetary Fund [IMF], 2021). The present 
study has undertaken these nations because the next 
decade belongs to Asia, the steps taken by Asian nations 
in response to climate change will decide the future of  
our planet to a large extent.
In recent years, significant attention has been drawn from 
researchers, policymakers and environmental advocates 
in the context of  the link between environmental 
deterioration and economic expansion. As countries 
grow, the requirement for resources rises and many times 
this results in a surge in pollution and environmental 
harm. This trade-off  between economic development 
and ecological sustainability has led to continuous 
discussions: while economic growth can strengthen living 
standards and mitigate poverty, it might also risk natural 
ecosystems if  growth is supported by practices that 
damage the environment. Assessing this nexus is essential 
to determine policies that can maintain the environment 
while balancing economic progress, directing initiatives 
towards growth that is sustainable, which considers the 
long-term economic and environmental well-being.
The most frequently recognised greenhouse gases 
(GHGs) include carbon dioxide (CO2), released when 
fossil fuels are burned, nitrogen dioxide (NO2), largely 
originating from particular manufacturing procedures, 
burning fossil fuels and applying nitrogen fertilisers, 

methane (CH4), largely generated from raising cattle. 
The report from the World Meteorological Organization 
(WMO) 2020 claims that the atmospheric concentration 
of  CO2 hit a new peak. This took place despite pollutants 
released via fossil fuels dropping in the midst of  the 
COVID-19 outbreak. Significantly, in 2020, the airborne 
CO2 levels attained 413 parts per million (ppm), which 
shows 149% rise from levels before the beginning of  
large-scale manufacturing. It’s the need of  the hour to 
address the issue of  global warming, which is mainly due 
to the emissions of  greenhouse gases.
It is notable that a critical aspect of  this environmental 
damage is ascribed to a selected group of  nations. 
For example, China is liable for about 30% of  world 
emissions, whereas the United States is accountable for 
around 14%.
Tourism has recently become a viable alternative for 
environmental and economic development, but it has 
drawbacks. When there is a lack of  essential actions 
to safeguard the environment, the deterioration of  the 
environment is the opportunity cost of  tourism. 
Considering the fact that tourism contributes a major 
role in the host economy, it is currently among the most 
significant and rapidly growing economic sectors in the 
world. One of  the sectors with the quickest rate of  growth 
is tourism and it particularly affects employment, income 
production and advancement of  the host country’s 
culture as a whole.
The countries, including India, China, Indonesia 
and Vietnam, are undergoing fast urbanization and 
industrialization, leading to unusual economic growth 
and improved standards of  living. Though this growth 



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Am. J. Environ Econ. 4(1) 158-162, 2025

frequently comes at a substantial cost to the environment. 
Higher usage of  energy and fossil fuels, deforestation and 
enhanced agricultural practices led to carbon emissions, 
high levels of  water and air pollution and deterioration 
of  habitat. As these nations aspire to prosperity, they 
also confront the dual hurdle of  addressing poverty and 
inequality while dealing with the severe impacts on the 
environment that follow growth.
For Asian emerging economies, the consequences are 
particularly elevated due to their dense populations, 
which worsens the social and environmental effects 
of  unsustainable growth patterns. Consequently, these 
nations are at the focal point of  the international debates 
on sustainable development, looking for approaches 
that permit economic advancement without making 
concessions for ecological balance. The linkage between 
economic expansion and environmental deterioration in 
these areas is complicated, as many ecological challenges 
extend beyond national boundaries and regional 
cooperation is needed to handle them. For this reason, 
comprehending this connection is vital for formulating 
policies that not only lead to economic progress but also 
ascertains that it is in line with the sustainability goals 
of  the environment, like those described in the United 
Nations Sustainable Development Goals (SDGs).
This article intends to explore the consequences on the 
environment of  rapid economic growth within Asian 
emerging countries, evaluate the current environmental 
regulations and explore possible routes for sustainable 
development. By examining the particular difficulties 
and opportunities these countries encounter, this study 
provides a wider exchange on sustainable economic 
models that balance development that safeguards natural 
resources for future generations.

LITERATURE REVIEW
Diverse research has been conducted to find the nexus 
between environmental deterioration and economic 
expansion, resulting in various conclusions.
Ridzuan et al. (2022) explored the EKC hypothesis 
between 1971 and 2019 using ARDL analysis for Malaysia. 
In the short and long term, they observed an inverted and 
direct U-shaped EKC, respectively.
Beton Kalmaz and Adebayo (2023) looked for the EKC 
hypothesis for BRICS countries from 1990 to 2018 
by using FMOLS, DOLS and fixed-effect OLS. They 
validated this hypothesis and therefore observed the 
positive impact of  GDP on CO2.
Tran et al. (2023) examined linkage between economic 
expansion and ecological deterioration for 47 middle-
income countries by using the ARDL model between 
1991 and 2018. They validated the EKC hypothesis, 
therefore observed a positive and an inverse relation in 
the near and distant future, respectively.
Alshehry and Belloumi (2024) looked for the linkages 
between economic expansion and ecological deterioration 
from 1990 to 2020 by employing linear and nonlinear panel 
ARDL models in MENA countries. They validated the 

EKC hypothesis and observed that economic expansion 
results in ecological deterioration in the long term.
Wang et al. (2024) explored the link between economic 
advancement and ecological deterioration between 1995 
and 2018 by using a nonlinear threshold panel model 
in 147 countries. They supported EKC for the selected 
countries. They observed that the extent of  ecological 
deterioration due to economic growth is relatively low 
in low-income nations. Simultaneously, the values of  
coefficients became relatively greater for middle-income 
and high-income nations.
Gulistan et al. (2020) assessed the influence of  increase 
in economic activity and some other variables on 
environmental deterioration in 112 nations from 1995 to 
2017. They used Pooled OLS, fixed and random effect 
models and GLS for estimation. They observed a direct 
relation between CO2 emissions and Energy usage and 
this signified that most of  this energy is non-renewable 
and based on oil.
Usman et al. (2022) explored effect of  utilization of  
energy and other variables on CO2 release between 
1995 and 2017 using FMOLS and discovered that 
non-sustainable energy usage has a direct influence on 
ecological deterioration, whereas the application of  
sustainable means of  energy production can somewhat 
enhance the quality of  the environment in South Asian 
Nations. 
Tran et al. (2024) examined the nexus among carbon 
release, energy usage and economic prosperity in ASEAN 
countries in the previous thirty years by using the panel 
vector autoregressive model, FMOLS and DOLS. They 
observed that carbon release is related to energy usage, 
while sustainable energy consumption reduces carbon 
pollutants. Economic growth leads to higher energy 
consumption, which consequently results in carbon release.
Osman (2024) assessed the effect of  energy usage by 
various sectors on CO2 release in Saudi Arabia from 
1979 to 2022 by using the ARDL technique and found 
that energy usage in the logistics and industrial sectors 
has a direct influence on CO2 release, while energy 
consumption in the agriculture sector negatively affects 
CO2 release.
Rahman et al. (2024) investigated the applicability of  the 
environmental Kuznets Curve (EKC) theory with respect 
to energy usage, human capital index and population 
density by using fixed effects, random effects and dynamic 
panel methodology in five South Asian nations and found 
an inverted U-shaped EKC curve.
Since the existing literature does not reach a consensus 
on how various macroeconomic variables impact the 
environment, the present study seeks to shed further light 
on this relationship.

MATERIALS AND METHODS
Data Sources and Model Formulation
The purpose of  this paper is to look at the influence 
of  economic expansion, energy usage and tourism on 
environmental deterioration between 1995 and 2020 for 



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Am. J. Environ Econ. 4(1) 158-162, 2025

Emerging and Developing Asian Economies. Panel data 
will be used for this purpose. Gross Domestic Product 
per capita and Green House Gas (GHG) emissions per 
capita will be used as the proxy of  economic growth and 
environment degradation, respectively. GDP, Energy 
usage and tourism data were obtained from the World 
Bank, whereas data on GHG emissions were obtained 

from Our World in Data. According to the World 
Economic Outlook (2023), there are thirty emerging and 
developing economies, out of  which twelve economies are 
chosen on the basis of  data availability. All the variables 
are presented in their logarithmic transformation.
Table 1 presents the description of  each variable under 
consideration.

Table 1: Description of  Variables
Variable Types Name Notation Units
Explained Variable Green House Gas Emissions GHG GHG per capita, CO2 equivalents
Explanatory Variable Gross Domestic Product GDP GDP per capita, constant 2015 US$
Explanatory Variable Energy Consumption EC kWh per person
Explanatory Variable Tourism Tourism Number of  arrivals

Table 2: Descriptive Statistics
Variables lnGHG lnGDP lnEC lnTourism
Mean 1.411316 7.604194 8.584625 14.84214 
Standard Deviation .8081339 .8531185 1.134581 1.866396
Maximum .0862168 5.349685 5.937852 11.11095
Minimum 3.466943 9.316011 10.54069 18.90642
Observations 312 312 312 312

Table 2, shows that mean GHG emissions for Asian 
Emerging and Developing Economies are 1.411316 
CO2 eq. from 1995 to 2020. Per capita GDP is on 
average equal to 7.604194 US$ whereas mean energy 
consumption is equal to 8.584625 kWh per person and 
on average around 14.84214 tourists arrived from 1995 to 
2020 in the selected area. 

Econometric Methodology
The following basic model will be used:

lnGHGi,t = γ+ϴ1lnGDPi,t+ϴ2lnECi,t+ϴ3lnTourismi,t+ φi,t
where γ is the intercept term, ϴ1, ϴ2 and ϴ3 are slope 
coefficients, φ is the error term, i is cross cross-section 
and t is time period.

RESULTS AND DISCUSSION
Initially, the Fixed Effects and Random Effects models 
were used, along with the Hausman test, to figure out the 
best-suited methodology for further analysis. The results 
propose that the Fixed Effect model will be applied. 

Table 3: Panel Data Regression Results
Variable OLS Fixed Effects                                    Random Effects                                                                                                  
GDP -.3681877*** .3060402*** .2752862***

(0.00) (0.000) (0.00)
EC .8572978*** .1208867 .1630829**

(0.00) (0.39) (0.04)
Tourism -.0449811 -.067599** -.0654784**

(0.16) (0.03) (0.03)
Constant -2.480877 -.9503251 -1.110179
Observations 312 312 312
Hausman test p – value    0.0078

*** significant at 1%,  ** significant at 5%,  * significant at 10%

Table 4: Pesaran’s test of  cross-sectional independence
Statistic 0.692 P-value 0.4891

*** significant at 1%,  ** significant at 5%,  * significant at 10%

Table 2 shows summary statistics based on 312 observations.



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The above results reflect that the value of  test statistic 
is 0.692 and p- value is 0.4891, that exceeds 0.05, so 
null hypothesis cannot be rejected and hence there is no 

cross-sectional dependence in our model.

Multicollinearity Testing

It is employed to check the model for multicollinearity. 
As a general norm, the VIF score needs to be below 10. 
Therefore, multicollinearity is not a problem.
Heteroscedasticity Test: Lagrange Multiplier, Likelihood 

Ratio and Wald Test are conducted in order to examine 
the panel groupwise heteroscedasticity with :

Ho: Panel Homoscedasticity                             
Ha: Panel Groupwise Heteroscedaticity                                                                                    

Table 5: Variance Inflation Factors (VIF)
Variable Random Effects                                                                                                  
GDP 4.84
Tourism 4.55
EC 1.80

Source: Author’s calculation

Table 6: Heteroscedasticity Test
Wald Test LM Test LR Test

Chi2 value 2045.0794 124.5087 165.7499
P value 0.00 0.00 0.00

The outcomes give enough evidence to reject the null 
hypothesis; there persists the issue of  heteroscedasticity, 

so FGLS model will be applied.
The outcomes of  FGLS regression are illustrated in the 

Table 7: Cross-sectional time-series FGLS regression
Variable                                                                         Coefficient    P-value
GDP -.3681877                                                           0.00***
Tourism    -.0449811                                                            0.015**
EC .8572978                                                              0.00***
Constant -2.480877                                                            0.00***

*** significant at 1%,  ** significant at 5%,  * significant at 10%

above table, according to which GDP, Tourism have a 
significant statistical negative effect on carbon release 
of  the chosen Asian countries. The results signify 
that economic prosperity and tourism activity may be 
related to environmental improvement. But, Energy 
consumption appears as a significant and positive 
determinant, reflecting that enhanced energy usage 
amplifies environmental impact. Further, the constant 
term is also substantial, which strengthens the robustness 
of  the model.  
Simultaneously, FGLS methodology eliminated the issue 
of  heteroscedasticity and the results thus acquired are 
reliable. 

CONCLUSION 
Asian Emerging Economies are on the path of  
development with the aim of  high economic growth, 
but at the same time, their environmental repercussions 
need to be addressed. As is evident from the data, GDP, 
which is a proxy of  economic growth, leads to reduced 
environmental pressure. Tourism also contributes to 
environmental sustainabilitywhereas Energy Usage 

remains a key environmental pressure. Therefore, these 
economies should encourage green economic growth 
along with sustainable tourism and work in the area to 
adopt clean energy technologies.

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Asymmetric Impacts of  Energy Consumption and 
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