LITERATURE REVIEW
The rising risk of climate change and global warming has drawn global attention to the
connection between GDP growth, use of energy, and carbon dioxide emissions (CO2). There are
many studies on carbon dioxide emissions, economic growth, and energy consumption. Naseem et
al. (2021) investigated the effect of (EC) on ecological dilapidation in BRICS states from 1990 to
2017. The researcher used the (EKC) hypothesis and Autoregressive, Distributed, Lag (ARDL)
approaches. The study's outcomes prove that economic growth (EG) and ecological deprivation in
the long run. ED and (CO2 emissions) are destroyed by constant economic growth. Running of
energy demands and energy disasters is the implementation of environmentally sustainable
policies.
Jun et al. (2021) documented energy consumption, EC, and environmental damage across
several Asian countries between 1985 and 2018. The researcher employed a fully modified ordinary
empirical result, showing that globalization is connected with CO2 emissions. The results also show
that (non-renewable) energy consumption is causing environmental pollution. The empirical
outcomes suggest that the administration should support and promote renewable energy sources to
tackle the problem of environmental degradation.
Chihoho et al. (2020) considered the energy used and the actual profit per capita income on
CO2 in BRICKS countries from 1989 to 2016. These studies include retrospective models, random
and constant research outcomes, energy expenditure results, and integration of character incomes
among brick carbon dioxide nations.
Manta et al. (2020) investigated the nexus among (CO2) emissions, strength use, and FD
and EG. In important ten (CEEC) international nations from 2000 to 2017, the used (FMOLS)
models were used. The result shows that (CO2) significantly affects economic growth, meaning that
CO2 use no longer affects GDP growth. Similarly, Jian et al. (2019) explored the influence of EG
and strength used on (CO2) emissions from 1982 to 2017.
The study conducted by Kahia et al. (2019) utilized panel vector autoregressive, multi-area,
and Granger causality methods to investigate the effect of renewable energy utilization and GDP on
CO2 emissions in MENA (12 nations). Thus, the effects of the economic boom suggest
environmental degradation; renewable energy inflows, global trade, and overseas direct investment
have caused a discount in carbon dioxide emissions (DinhHong and Lin., 2015). Ntanos et al.
(2018) analyzed the connection between renewable energy consumption and economic growth of
25 EC international locations over the duration (2007–2016). The result confirmed that the
monetary intake of nations with a higher GDP is higher than those with a lower GDP. Research
finished using unit root test, cointegration, and cointegration models. Look at Johansen-Fisher and
cointegration models (Baker et al., 2005; Van der Linden, 2017).
Apergis and Payne (2010) examined the association between (economic growth and
renewable energy consumption) for OECD countries from 1985 to 2005. The researcher used EC
(error correction) and cointegration for panel models. The result from cointegration suggests a long-
term correlation linking GDP and renewable electricity utilization, while labour pressure and capital
also have a statistically positive correlation.
Ang (2007) studied CO2 release from energy consumption and yield in France during 1960-
2000. This empirically illustrated the effects by using vector and error-correction cointegration
models. The findings from these models show a positive impact of energy utilization on ED in the
short term and long term, as well as a "bidirectional causality" of energy utilization on production.
Everything is managed at the executive level, from electricity consumption, exchange openness,
and population to CO2 emissions (Peterson, 2017).
Kais and Mbarek (2017) explored the relationship between CO2, used energy, and EG in
three selected African countries from 1980 to 2012. The researcher uses penal cointegration, unit
root, Granger causality, and panels. The result is a short-term unilateral association between
economic growth to energy. The one-way correlation between used EC and CO2 emissions has
been exposed. The results further show that, in the long run, there is a significant link between EC
and EG. The study found that the authorities, who had to formulate comprehensive fiscal, energy
and environmental policies to keep the economy afloat, meant that these three variables could play
a key role in the adjustment process as the system operates on its own (Akadiri et al., 2019; Khobai
et al., 2017; Khan et al., 2019).
Therefore, Rahman (2020) supports a one-way link between energy use and carbon emissions in
which there is no reaction; there is a bilateral business relationship between carbon emissions
(CO2) and economic growth throughout the region. Furthermore, studies suggest that
environmental and energy policies must recognize the nexus between energy consumption and
economic growth to sustain economic growth in the MENA region.
Ghosh et al. (2014) results show that energy consumption positively and significantly impacts
economic growth. However, carbon emissions have a negative and insignificant effect on economic
growth, so Bangladesh can be realized without demeaning the environment. Kais and Mbarek
(2017) revealed that, in the long run, there is an interdependence between GDP growth and the EU.
Koengkan (2017) showed a positive link between GDP, energy, and consumption in the Caribbean
and Latin American countries, while a uni-directional relationship exists between energy usage,
development, and growth. Sinha's (2017) result indicates that non-renewable energy is indirectly
associated with GDP. In the long run, renewable energy uses directly and significantly affect GDP
growth. Ajide (2018) described a significant role of (EC) and (CO2 emission) in economic progress
has been determined by empirical study, yet the direction is opposite (Dogan, 2018). Bhat (2018)
explored BRICS countries, including Brazil, Russia, China, India, and South Africa; researchers
looked at the link between GDP growth, disaggregated energy use, and (CO2) emissions.
Ahmad et al.'s (2019) outcome indicates that non-renewable energy was positively
associated with carbon dioxide emissions, but renewable energy was found to be negatively related.
Zaidi (2019) and Khan (2019) examined the association between the EU and EG and ecological
degradation in Sub-Saharan nations. The results support Rahman's(2020) study, "bi-directional
causality between energy consumption and economic growth, as well as a bi-directional relationship
between electricity consumption and energy consumption; nonetheless, all variables highlighted
pollution's detrimental influence on electricity consumption". Philip et al. (2020) investigated
the fifteen economies and the asymmetric association between economic growth, energy
consumption, and carbon dioxide emission. Therefore, the results indicated nonlinear co-integration
between variables in the research.
On the other hand, Osobajo et al. (2020) results of both the pooled OLS and fixed
approaches demonstrated that economic growth and energy consumption had a largely beneficial
influence on CO2 emissions. Chukwunonso Bosah et al. (2020) shows a nonlinear relationship
between variables. Dabachi et al. (2020) examined the causal association between energy
consumption, economic growth, energy intensity, carbon emission, and energy prices in OPEC
African economies. The period covered in this study is from 1970-2018. Aydin (2019) examined
the association between biomass energy usage and GDP growth for low- and middle-income
countries. The panel data was applied in this study. The period covered in this study is from 1971-
2013. The econometric approach of the Konya panel causality test was used. Parallel study support
results of this study such as Soava et al. (2018), Hanif (2018), Matthew (2019), Wang et al. (2018)
and Gozgor et al. (2020) result revealed that the degree of causality between GDP growth and bio-
mass energy use differed according to the nation's dimensions and period.
Tong et al.'s (2020) study revealed no correlation between economic growth and CO2
emissions in China, Indonesia, Turkey, Mexico, Brazil, India, and Russia. CO2 outflows in the
output and EC are the explanatory variables—co-integration found in Russia and India. Islam et al.
(2017) studied the impact of economic growth, energy use, population, poverty, and (CO2)
emissions (Mikayilov et al., 2018; Aye & Edoja, 2017). These studies also support the results of
Sulaiman and Rahim (2017), Khan et al. (2019), and Khan et al. (2020).
Zahonogo's (2016) findings revealed that trade openness occurs under the surface and that
more trade openness positively influences GDP growth. The results are in line with trade
liberalization changes and electoral model parameters. Balanika (2017) revealed that trade
liberalization positively and negatively affected GDP. However, exchange in Sub-Saharan Africa is
characterized by high common borders and a reliance on essential goods. Insufficient overland
connectivity to far-flung major markets may explain why more trade openness does not lead to
increased economic growth (Manteli, 2015; Keho, 2017; Khalid, 2016)
The primary purpose of this research is to analyze the association between economic
development, environmental degradation, and energy consumption. We will use the latest panel
data and methods to achieve these objectives. Moreover, all the previous studies were conducted
from different perspectives. This research will contribute to formulating policies based on research
findings in the four South Asian countries (Pakistan, Bangladesh, Sri. Lanka and India).
