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Global Sustainability Research                                ISSN: 2833-986X                                                 
https://doi.org/10.56556/gssr.v2i2.315 

                                                                  
 
 

Global Scientific Research    12 

 

Investigating the nexus between energy consumption, industrialization, urbanization, 
economic growth, and Carbon dioxide emission: Panel data analysis from the Belt and 
Road Initiative countries 

Hayat Khan1, Robeena bibi2, Sumaira3, Le Thi Kim Oanh4, Itbar Khan5* 
 
1School of Economics and Management, Zhejiang University of Science and Technology, Hangzhou China 
2School of Public Administration, Hohai University, Nanjing China 
3College of Economics and Management, Zhejiang Normal University, China 
4College of International Education, Guangxi University for Nationalities, Nanning, Guangxi, China 
4Business school of Guangxi University, Nanning, Guangxi, China  

5College of Economics, Shenzhen University, Shenzhen, China 
 
Corresponding Author: Itbar Khan, Khanitbar321321@gmail.com  
Received: 04 October, 2022, Accepted: 01 December, 2022, Published: 14 April, 2023 

 

Abstract 

An increase in urbanization rises the use of energy in urban areas which leads to high carbon dioxide discharge and worsen 

environmental quality. Industrialization and economic growth are also linked with environmental quality and thus need to 

investigate the effect of these factors on environmental quality. This study uses panel data from 1976 to 2019 and investigate 

the nexus between urbanization, industrialization, economic growth, energy consumption and carbon dioxide emissions in 

the belt and road initiative countries using static and dynamic panel models. The findings reveals that the effect of 

urbanization, energy consumption, industrialization and economic growth on carbon dioxide emission is positive and it 

reduce environmental quality however, international trade significantly reduce carbon dioxide emission. This study further 

confirms the existence of a U-shape link between urbanization and carbon dioxide while the square term of economic growth 

doesn’t validate the Environmental Kuznets curve hypothesis. The findings of this study have considerable policy 

suggestions regarding carbon emission mitigation in term of urbanization, energy use, industrialization and economic growth. 

 

Keywords: Urbanization; Carbon dioxide emission; Nonlinear relationship; Environmental Kuznets Curve 

 

 

 

Introduction 

 

Same as other factors, urbanization also affects 

environmental quality where some studies in the prevailing 

literature indicate that a rise in long term economic growth 

rises environmental quality while a rise in urban population 

increases environmental degradation Adem, Solomon et al. 

(2020). An increase in urbanization rise the use of energy in 

urban areas which leads to high carbon dioxide discharge 

and worsen environmental quality Khoshnevis Yazdi and 

Golestani Dariani (2019).  A study confirms the statement 

that urbanization level raises carbon dioxide emission and 

worsens the quality of the environment Sadorsky (2014) 

while opposite findings are also obtained that low density of 

population makes inefficient public transfer and 

infrastructure and thus carbon emission reduces Chen, 

Colombo et al. (2008). Likewise, the lowest carbon footprint 

in urban areas has been indicated by Muñoz, Zwick et al. 

(2020) while on the other hand, urbanization in an economy 

has been considered concerning scale effect and the driving 

factor of development with the use of energy from 

environmentally friendly Zhang, Wang et al. (2020). 

Urbanization has been considered that effect carbon 

emission positively and unreasonably Poumanyvong and 

Kaneko (2010). Urbanization  above the unity level effects 

the income groups carbon emission differently Martínez-

Zarzoso and Maruotti (2011). On the other hand, the nexus 

between urbanization and carbon emission is found U-

shaped Kong, Wang et al. (2021).  Urbanization effect 

national carbon dioxide emission in variables ways in 

different regions Jorgenson, Auerbach et al. (2014). 

Uncontrol urbanization level leads to environmental 

degradation and other related problems such as air pollution, 

waste disposal and land insecurity Ikumapayi (2020). 

Newly industrialized countries produce high carbon 

emission due to high amount of energy use Khoshnevis 

Yazdi and Golestani Dariani (2019). Countries are 

increasing production in order to rise economic growth to 

enhance living standard. 

The use of energy and carbon dioxide enhance economic 

growth while on the other hand, energy consumption 

degrade environmental quality Kahouli, Miled et al. (2022). 

High level or industrialization and a rapid increase in 

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urbanization have effected the urban building which results 

a major effect on energy consumption Gierałtowska, 

Asyngier et al. (2022). Urbanization has different 

independent effects on energy consumption independently 

Shao, Chen et al. (2019). Urbanization convert traditional 

energy consumption to modern types and thus rise intensity 

of energy which reduce pollution such as pollution 

purification and urban transportation Martínez-Zarzoso and 

Maruotti (2011).  Several studies indicates that the 

environmental Kuznets curve in this context is valid. 

According to this phenomenon, urbanization rise carbon 

dioxide emission with a rise in urban land and decrease 

when there is further rise in urban land at the highest level 

of urbanization Li, Wang et al. (2016); Sadik-Zada and 

Gatto (2021).  Complex mechanism has been debated by 

which the effect of urbanization on carbon emission has 

positively or negatively shown Zhou, Wang et al. 

(2019);Yao, Zhu et al. (2021). Beside urbanization, most of 

other activities such as industrialization and production in 

countries are increased in order to rise economic growth 

while increase in these activities increase energy demand 

and rise carbon dioxide emission. 

The belt and road countries are mostly developing and 

emerging countries. These countries need to increase 

industrialization and production to rise economic growth 

while industrialization and production need high amount of 

energy. Thus, a rise in energy consumption and economic 

growth leads to high carbon emission discharge. The rapid 

industrialization in the countries is also observed as 

urbanization also linked with economic growth and thus its 

effect carbon emission. In this study, we believe that the 

specific characteristics of the belt and road countries, the 

effect of urbanization, energy consumption, economic 

growth and industrialization on carbon dioxide can be 

different as a regional difference. Several previous studies 

have conducted studies on the effect of urbanization on 

carbon dioxide emission however industrialization, energy 

consumption and economic growth has not been considered 

while this study considered these closely related factors. The 

nonlinear association between urbanization and carbon 

dioxide emission has not been considered in such kind of 

investigation. This study tests both the nonlinear association 

between carbon emission and urbanization as well testing 

for the environmental Kuznets curve by introducing the 

square term of economic growth per capita. Considering the 

belt and road countries data and its specific characteristics 

and economic level, this study investigates the effect of 

urbanization, energy consumption, industrialization and 

economic growth on carbon dioxide emission from 1976 to 

2019 using dynamic panel models. The findings reveals that 

the effect of urbanization, energy consumption, 

industrialization and economic growth on carbon dioxide 

emission is positive and it reduce environmental quality 

however, international trade significantly reduce carbon 

dioxide emission. This study further confirms the existence 

of a U-shape link between urbanization and carbon dioxide 

while the square term of economic growth doesn’t validate 

the Environmental Kuznets curve hypothesis. 

The rest of the paper is structure as follows; literature review 

is presented in part 2, section 3 is composed of variables and 

method used, part 4 present results and discussions while the 

part 5 conclude the study findings and give policy 

implications. 

 

Literature review 

 

Large number of studies have been examined the nexus 

between different factors with environmental quality proxy 

by carbon dioxide emission such as economic growth, 

energy consumption and urbanization. However, these 

studies have not yet achieved enough conclusions and thus 

this topic still need investigation. For instance, Kong, Wang 

et al. (2021) studied the link between urbanization and 

carbon emissions in China. The results show a U-shaped 

association between urbanization and environmental 

degradation. (Bao & Lin, 2021) Based on provincial data, 

the spatial vector autoregression model was used to explore 

the relationship between economic growth, carbon 

emissions and technological innovation from 2003 to 2017. 

The results of this study indicate that the study variables 

were positively correlated. Pece, Simona et al. (2015) 

examine the relationship on economic growth and 

technology innovations in Central and Eastern European 

countries. Using patents, trademarks, and R&D spending as 

innovation indicators, we found a positive relationship 

between innovation and economic growth. (Pala, 2019) 

examined the impact of technology on economic growth in 

25 developing countries Using a random coefficient model 

and using R&D and researchers, they reveals that R&D 

spending had a significant negative impact on economic 

growth in some countries in the study sample. Mukhtarov, 

Humbatova et al. (2020) examine the association between 

energy and economic growth. The authors used the ARDL 

model and collected the data from 1993 to 2015. The results 

show that economic growth increases renewable energy 

consumption. Financial development was also found that 

rises renewable energy. Another study by Godil, Sharif et al. 

(2020)  studied the nexus between institutions, ICT and 

carbon emission using QARDL and data from 1995 to 2018. 

The study shows that economic growth along institutions 

raises carbon dioxide while ICT reduce emission. (Chien et 

al., 2021) also conducted such a study using ARDL for the 

period 1980 to 2018. The study country was Pakistan and 

the authors found that economic growth significantly 

increases carbon emissions, and the EKC hypothesis is 

validated. They further show that renewable energy and 

technological innovation can negatively impact carbon 

emissions. Globalization is a significant source of increased 

carbon dioxide emissions in Pakistan. Suki, Suki et al. 

(2022) examine the relationship between renewable energy 

consumption, technological innovation, and carbon 

emissions in Malaysia. Using a bootstrapped ARDL model, 

the findings suggest that using renewable energy can help 

reduce environmental degradation, and technological 

innovation can reduce ecological footprint and carbon 

emissions. Their study also confirmed the EKC hypothesis. 

Khoshnevis Yazdi and Golestani Dariani (2019) used 

Indonesia data from 1971 to 2019 and examine the nexus 

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between urbanization, economic growth and carbon dioxide. 

Using vector error correction model and found the existence 

of pollution haven hypothesis while there was found a 

unidirectional causal relationship from economic growth, 

FDI and economic growth to carbon dioxide emission. 

Other studies have also conduct such investigation such as 

the study of Ponce de Leon Barido and Marshall (2014) 

validate the findings of above study. These authors 

conducted a study to examine the nexus between carbon 

dioxide and urbanization in 80 countries from 1983 to 2005. 

The authors used fixed and random effects models and 

reveals that urbanization rise carbon dioxide.  

Chen, Liu et al.) studied the nexus between urbanization and 

carbon dioxide emission by considering the transformative 

role of government effectives from 1996 to 2018 in OECD 

countries using FGLS and correlated errors models. The 

authors found the existence of U shape association between 

urbanization and carbon dioxide. They further evidence the 

government effectiveness transformative role in this 

association. Some authors also believes that quality 

institutions also effect the nexus between urbanization, 

industrialization and carbon dioxide such as Wu and Madni 

(2021) studied the nexus between institutional quality, 

transportation and industrialization with carbon dioxide 

emission in the belt and road countries from 1996 to 2018. 

The study implemented panel threshold regression and 

found the threshold level of institutional quality in the 

sample countries. Institutional quality above the level, 

carbon dioxide doesn’t destroy the environment while 

below is related to environmental degradation. Most of the 

studies indicates that urbanization increase carbon dioxide 

emission. A study is conducted by Zhang, Song et al. (2021) 

used China data from 2000 to 2012 to examine the nexus 

between urbanization, population and carbon dioxide 

emission. GMM, two stage least square models were 

employed to the data for analysis and the results illustrate 

that temporary residence has a marginal influence on 

urbanization and carbon dioxide emission nexus. Likewise, 

Kahouli, Miled et al. (2022) explore the association of trade, 

urbanization, economic growth and carbon dioxide 

emission. The time period of the study is from 1971 to 2019 

and data sample country is Saudi Arabia. The authors used 

ARDL and VECM models and found that the use of energy 

and carbon dioxide enhance economic growth while on the 

other hand, energy consumption degrade environmental 

quality. Martínez-Zarzoso and Maruotti (2011) used data for 

different countries groups from 1975 to 2015 and explore 

the effect of urbanization on carbon dioxide emission. The 

authors found that urbanization above unity differently 

affects the income groups. Kong, Wang et al. (2021) studied 

urbanization and carbon emissions in China. The results 

show a U-shaped association between urbanization and 

environmental degradation. Energy consumption and 

economic growth is also widely debated and most of the 

previous studies shows that energy consumption drive 

economic growth as well both energy use for production and 

economic growth increase carbon dioxide and leads to 

environmental degradation. A study by Gierałtowska, 

Asyngier et al. (2022) investigate the nexus between 

urbanization, renewable energy and carbon dioxide from 

2000 to 2016 in a sample of 163 countries. The authors 

analyzed the data with GMM model and found U-shape 

association between urbanization and carbon dioxide. The 

author further expresses that the effect of renewable energy 

on carbon dioxide is negative. They also found the existence 

of EKC hypothesis in the sample countries. (Bao & Lin, 

2021) used provincial data and applied the spatial vector 

autoregression model to explore the relationship between 

economic growth, carbon emissions and technological 

innovation from 2003 to 2017. The findings show that 

technological innovation, economic growth and carbon 

dioxide are positively correlated over time. (Pece, Simona 

et al. (2015) examine the relationship between innovation 

and economic growth in Central and Eastern European 

countries. Using patents, trademarks, and R&D spending as 

innovation indicators, we found a positive relationship 

between innovation and economic growth. (Pala, 2019) 

examined the impact of technology on economic growth in 

25 developing countries Using a random coefficient model 

and using R&D and researchers, they found that R&D 

spending had a significant negative impact on economic 

growth in some countries in the study sample. Mukhtarov, 

Humbatova et al. (2020) examine the association between 

energy and economic growth. The authors used the ARDL 

model and collected the data from 1993 to 2015. The results 

show that economic growth increases renewable energy 

consumption. Financial development was also found that 

rises renewable energy. Another study by Godil, Sharif et 

al. (2020)  studied the nexus between institutions, ICT and 

carbon emission using QARDL and data from 1995 to 2018. 

The study shows that economic growth along institutions 

raises carbon dioxide while ICT reduce emission. (Chien et 

al., 2021) also conducted such a study using ARDL for the 

period 1980 to 2018. The study country was Pakistan and 

the authors found that economic growth significantly 

increases carbon emissions, and the EKC hypothesis is 

validated. They further show that renewable energy and 

technological innovation can negatively impact carbon 

emissions. Globalization is a significant source of increased 

carbon dioxide emissions in Pakistan. Suki, Suki et al. 

(2022) examine the relationship between renewable energy 

consumption, technological innovation, and carbon 

emissions in Malaysia. Using a bootstrapped ARDL model, 

the findings suggest that using renewable energy can help 

reduce environmental degradation, and technological 

innovation can reduce ecological footprint and carbon 

emissions. Their study also confirmed the EKC hypothesis. 

 

Methodology 

 

This study uses panel data from 1976 to 2019 for the belt 

and road initiative countries and investigate the nexus 

between urbanization, economic growth, industrialization, 

energy consumption and carbon dioxide emission. The 

study uses both static and dynamic panel models to examine 

this association. The models include ordinary least square, 

fixed effect model, two step difference GMM and two step 

system GMM. However, before the formal analysis, this 

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study first implemented a panel unit root test to test the 

stationarity of the data. After performing these preliminary 

tests, we further conduct formal analysis using static and 

dynamic panel models. These estimators include OLS, 

fixed-effects models, two-step differencing, and two-step 

systematic generalized method of moments (GMM). The 

GMM model was proposed by (Arellano & Bond, 1991) and 

is considered a recent application of the topic, and most 

studies have focused on this estimator when dealing with 

panel data. First, the study uses static models, OLS, and 

fixed effects to deal with heterogeneity. These static 

estimators were used to compare the results of the current 

study with previous studies and to compare the results with 

dynamic model results. By using a GMM model, it will deal 

with endogeneity issues related to study variables 

Kinyondo, Pelizzo et al. (2021). The system GMM model 

handles grouping equation differences s at the horizontal 

level. The instrument specified in the model is the variable 

delay value of the level in the difference equation. The 

variables also studied are the horizontal equation and the 

first difference mean. Monte Carlo simulations by (Blundell 

and Bond, 1998) show that the SGMM model is most 

effective at estimating this dilemma. The over descriptive 

constraint test was replaced by the Sargan test with the 

Hansen test, and Arellano and Bond's serial correlation test 

was also used. Most of the results of these tests confirmed 

our study expectations. Hansen test values give recognition 

and show the effectiveness of the instrument. The baseline 

empirical models are presented below in form of generalized 

method of moments. The first equation shows the direct 

effect of urbanization and economic growth along other 

explanatory variables while empirical model in equation 2 

presented the nonlinear association between the study 

variables.  

 

𝐶𝑂2𝑖𝑡 = 𝛽0 + 𝛽1𝐶𝑂2𝑖𝑡−1 + 𝛽2𝑈𝑅𝐵𝑖𝑡 + 𝛽3𝐸𝐶𝐺𝑖𝑡

+ 𝛽4𝐼𝑁𝐷𝑖𝑡+𝛽5𝐸𝑁𝑅𝑖𝑡 + 𝛽6𝑇𝑅𝑖𝑡

+ ɛ𝑖𝑡                                    (1) 

 

𝐶𝑂2𝑖𝑡 = 𝛽0 + 𝛽1𝐶𝑂2𝑖𝑡−1 + 𝛽2𝑈𝑅𝐵𝑖𝑡 + 𝛽3(𝑈𝑅𝐵)𝑖𝑡
2

+ 𝛽4𝐸𝐶𝐺𝑖𝑡 + 𝛽5(𝐸𝐶𝐺)𝑖𝑡
2

+ 𝛽6𝐼𝑁𝐷𝑖𝑡+𝛽7𝐸𝑁𝑅𝑖𝑡 + 𝛽8𝑇𝑅𝑖𝑡

+ ɛ𝑖𝑡                    (2) 

In equations 1 and 2, CO2 is carbon dioxide emission taken 

as metric tons per capita, URB is urban population, ECG is 

economic growth taken as GDP per capita, IND is 

industrialization, ENR is energy consumption while TR is 

international trade. Likewise, the square of urbanization is 

taken to examine the nonlinear association and also the 

square of economic growth is taken to test for the 

Environmental Kuznets Curve. The data for all selected 

variables were downloaded from the world bank database 

world development indicator.  Table 1 present the variables 

explanation and table 2 shows the variables statistics. 

Likewise, the correlation is given in table 3. It is believed by 

large number of researchers that  an increase in urban 

population is also related to an increase in carbon dioxide 

emission  Li, Fang et al. (2019); Khan, Han et al. (2021). 

Urbanization transfers a rural to urban transition and moves 

an agricultural economy to an industrial economy 

(Muhammad, Long et al. (2020). When there is an increase 

in urbanization, the emission level will increase as 

inhabitant production and improvement in living standards 

as well as industrialization. However, it's also been argued 

that agglomeration in population due to the rise in 

urbanization enhances the energy use effectiveness and 

contributes to achieving economy of scale Solarin and Lean 

(2016). Several studies in preceding literature show that a 

rise in urbanization leads to a high level of production and 

raise carbon emission Ghisellini and Ulgiati (2020); 

Nguyen, Nguyen et al. (2018); Canh (2019);Khan, Weili et 

al. (2022). Carbon emissions are expressed as metric tons 

per capita in terms of environmental quality or degradation. 

This proxy has been used recently by Ibrahim D. Raheem 

(2019) and Khan, Weili et al. (2021). Similarly, it is 

generally accepted that the independent variable for 

considering its impact on carbon emissions is urbanization. 

Economic growth is measured as per capita GDP Aritenang 

(2021);  Bouchoucha (2021, Hamdaoui, Ayouni et al. 

(2021); Khan, Weili et al. (2021). Previous studies claim 

that carbon emission is increased and the environment is 

polluted by the higher economic growth (Danish et 

al.,2018c; Ozcan and Apergis (2018). Likewise, it's been 

argued in previous research that a rise in economic growth 

rise carbon emission and degrade environmental quality. 

Krueger and Grossman (1995) ; Apergis and Li (2016); Bai, 

Feng et al. (2020) indicate that per capita income is a vital 

factor that affects the level of carbon emission. Several 

studies in the preceding literature used the square terms of 

GDP per capita to testify to the Environmental Kuznets 

Curve Stern (2004); Mader (2018). The environmental 

Kuznets Curve indicates that in the initial stage of growth 

rise carbon dioxide while when the country reaches a certain 

level of development, the emission level goes down. Based 

on the preceding studies, this study also adds the quadratic 

function of economic growth to test the non-linear effect of 

per capita growth on carbon dioxide emission. 

 

Table 1. Variables description 

Variables description  Symbols 

carbon dioxide emissions (metric tons per 

capita) 

CO2 

Urbanization taken as total population  URB 

Per capita gross domestic product  GDP 

Industrialization  IND 

Energy consumption  ENR 

Trade  TR 

 

Table 2. Descriptive statistics  

Variable Mean Std. Dev. Min Max 

CO2 4.325272 4.150806 0 26.89927 

URB 51.15108 18.30245 6.668 92.501 

GDP 2.940403 5.59511 -45.32511 24.97367 

IND 30.62608 8.436977 12.17161 64.00978 

ENR 1822.165 1299.566 105.4537 6232.732 

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TR 82.0442 39.42683 8.384615 220.4068 

 

Table 3. Correlation matrix 

 CO2 URB GDP IND ENR TR 

CO2 1.0000      

URB 0.7289 1.0000     

GDP -0.0893 -0.0814 1.0000    

IND 0.1557 -0.0247 -0.0134 1.0000   

ENR 0.9569 0.7480 -0.0814 0.1047 1.0000  

TR 0.2726 0.2540 0.0615 -0.0430 0.3429 1.0000 

 

 

Results and discussions 

 

Panel unit root tests 

 

Before the formal analysis using static and dynamic panel 

models, the stationarity of the variables was firstly checked 

employing CADF and CIPS unit root tests. These are second 

generation tests where its is assumed that each time series in 

the panel is distributed across each cross sections.  

 

Table 4. Second Generation Panel unit root results 
 CIPS CADF 

Variables I(0) I(1) I(0) I(1) 

CO2 -1.667 -3.575 *** -0.284 -3.831*** 

URB -1.629 -2.402*** -2.547*** -2.110** 

GDP -3.641*** -5.167 *** -3.064*** -4.299*** 

IND -2.308 -5.070 ***    -2.049 -3.723*** 

ENR -1.310 -4.093*** -0.891 -3.130*** 

TR 
-1.793 -4.813***   -1.834 -3.931*** 

Note: **, *** shows significance level at 5 percent and 1 percent 

respectively  

 

 

Pesaran (2007) proposed second generation tests based on 

average lag and first difference of single series to enhance 

ADF regression. Thus, the single common factor is filtered 

out. There is a unit root in the panel in each country and thus 

it is tested alternatively the countries differences. The results 

are presented in table 4. All the variables are stationarity in 

first difference and in level. 

After checking the stationarity of data, this study 

further forward to the formal econometric analysis 

using static and dynamic panel model. Table 5 present 

the direct effect of urbanization on carbon dioxide 

emission. The results indicates that the lagged 

dependent variable carbon dioxide is positive 

significant and the AR1, AR2 and Sargan test also 

fulfil the model requirements. 

The findings shows that the sample countries 

urbanization leads to high carbon dioxide emission and 

worsen environmental quality. Considering the two-

step system GMM results, a rise in the level of 

urbanization in the belt and road countries increase 

carbon dioxide emission by 0.004 percent if 

urbanization goes upward by one percent. The findings 

of this study are similar to Al-Mulali, Solarin et al. 

(2016); Khoshnevis Yazdi and Golestani Dariani (2019) 

regarding the effect of urbanization on carbon dioxide.  

The findings shows that the sample countries 

economic growth also leads to high carbon dioxide 

emission and worsen environmental quality. 

Considering the two-step system GMM results, a rise 

in the level of economic growth in the belt and road 

countries increase carbon dioxide emission by 0.027 

percent if there is a one percent increase in economic 

growth. Adebayo, Adedoyin et al. (2021) found similar 

results. 

The findings shows that the estimated coefficient of 

industrialization is positive and significant that’s leads 

to high carbon dioxide emission and worsen 

environmental quality. Considering the two-step 

system GMM results, a rise in the level of 

industrialization in the belt and road countries increase 

carbon dioxide emission by 0.006 percent with a one 

percent increase in industrialization in the belt and 

road countries. Khoshnevis Yazdi and Golestani 

Dariani (2019) also found that industrialization leads 

to carbon emission discharge. 

Energy consumption is significant and positive. The 

estimated coefficient values indicate that a rise in the 

use of energy in the belt and road countries increase 

carbon dioxide emission. The findings further shows 

that when there is increase in carbon dioxide emission 

with the use of high amount energy worsen 

environmental quality. More specifically, 0.004 

percent increase will occur in carbon dioxide if the use 

of energy increase by one percent. The findings 

confirm that energy use in the belt and road countries 

harms environmental quality by producing pollution. 

International trade variables produce positive and 

significant coefficient. Thus the coefficient indicate 

that it reduce carbon emission and rise environmental 

quality. The findings shows that if there is increase in 

international trade in the sample countries will support 

the environmental quality enhancement. Specifically, 

taking the two-step system GMM model results, if a 

percent increase in the belt and road countries 

international trade occur, the environmental quality 

will be risen and the carbon emission will be reduced 

by 0.001 percent. Khoshnevis Yazdi and Golestani 

Dariani (2019) found opposite results for Asian 

countries. 

 

 

 

 

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Table 5. Urbanization and carbon dioxide emission  

Variables  OLS Fixed effect 2Steps Difference GMM 2Steps System GMM 

Urbanization  0.009*** 0.009*** 0.003 0.004** 

 (0.003) (0.003) (0.011) (0.004) 

Economic growth  -0.006*** 0.006*** 0.003*** 0.027*** 

 (0.002) (0.002) (0.000) (0.000) 

Industrialization  0.029*** 0.029*** 0.015*** 0.006*** 

 (0.002) (0.002) (0.002) (0.001) 

Energy consumption  0.002*** 0.002*** 0.001*** 0.0004*** 

 (4.320) (4.430) (4.370) (3.365) 

International trade  -0.003*** -0.003*** -0.002*** -0.001* 

 (0.000) (0.000) (0.0003) (0.0002) 

𝐶𝑂2𝑖𝑡−1   0.250*** 0.804*** 

   (0.005) (0.012) 

Constant -1.195*** -1.171***  0.001 

 (0.228) (0.148)  (0.002) 

     

Observations 936 936 886 925 

R-squared  0.903   

Number of id 37 37 37 37 

AR1   -2.01 -2.22   

   (0.045) (0.027) 

AR2   -1.42   -0.92   

   (0.154) (0.357) 

Sargan test    1733.32   1377.01   

   (0.020) (0.121) 

Note: Standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1 

 

 

The findings shows that the sample countries 

urbanization leads to high carbon dioxide emission and 

worsen environmental quality. Considering the two-

step system GMM results, a rise in the level of 

urbanization in the belt and road countries increase 

carbon dioxide emission by 0.081 percent if 

urbanization goes upward by one percent. 

As the effect of urbanization is positive and rise carbon 

dioxide emission however the estimated coefficient of 

the square term of urbanization shows that this 

coefficient give significant but negative sign thus 

indicates that urbanization will significantly reduce 

carbon dioxide emission when its reach a certain level 

in the belt and road countries. Thus, the findings 

confirm that there exist a U-shape association of 

urbanization and carbon dioxide emission. 

The findings shows that the sample countries 

economic growth also leads to high carbon dioxide 

emission and worsen environmental quality. 

Considering the two-step system GMM results, a rise 

in the level of economic growth in the belt and road 

countries increase carbon dioxide emission by 0.027 

percent if there is a one percent increase in economic 

growth. Consistent with findings from Zoundi (2017); (H. 

Khan, Weili & Khan, 2021b); economic growth increases 

emissions, further evidence from more researchers (Chien et 

al., 2021); Adebayo, Adedoyin et al. (2021). Economic 

growth reduces environmental quality. (Usman, Alola, and 

Sarkodie, 2020) also claim that economic growth puts 

upward pressure on the ecological footprint. Khoshnevis 

Yazdi and Shakouri (2017) obtained the opposite result. As 

the economic growth is positive and significant 

increase carbon dioxide however this study also tests 

the environmental Kuznets curve by taking the square 

of economic growth per capita. By checking the EKC 

hypothesis whether economic growth still increase or 

reduce emission when the countries reach a certain 

level of development, the results did not validate this 

hypothesis as the square term coefficient gives positive 

and insignificant results. 

The findings shows that the estimated coefficient of 

industrialization is positive and significant that’s leads 

to high carbon dioxide emission and worsen 

environmental quality. Considering the two-step 

system GMM results, a rise in the level of 

industrialization in the belt and road countries increase 

carbon dioxide emission by 0.001 percent with a one 

percent increase in industrialization in the belt and 

road countries. 

The effect of energy consumption on carbon dioxide 

shown positively by the coefficients. Thus, a rise in 

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energy use increase carbon dioxide. The findings 

further shows that when there is increase in carbon 

dioxide emission with the use of high amount energy 

worsen environmental quality. More specifically, 

0.004 percent increase will occur in carbon dioxide if 

the use of energy increase by one percent. The findings 

confirm that energy use in the belt and road countries 

harms environmental quality by producing pollution. 

 

 

Table 6. Nonlinear association between urbanization and carbon dioxide 
Variables  OLS Fixed effect 2Steps Difference 

GMM 

2Steps System GMM 

Urbanization  0.041*** 0.043*** 0.0572 0.081*** 

 (0.009) (0.009) (0.0488) (0.085) 

Urbanization Square -0.000*** -0.000*** -0.000*** -0.000*** 

 (9.320) (9.480) (0.000) (0.0006) 

Economic Growth  -0.005** -0.005** 0.004*** 0.027*** 

 (0.002) (0.002) (0.000) (0.000) 

ECG Square 7.110 7.080 1.940 1.490 

 (0.000) (0.000) (7.020) (8.960) 

Industrialization  0.026*** 0.026*** 0.016*** 0.001*** 

 (0.002) (0.002) (0.002) (0.002) 

Energy consumption  0.002*** 0.002*** 0.001*** 0.0004*** 

 (4.350) (4.460) (3.230) (2.390) 

International trade -0.004*** -0.004*** -0.002*** -0.000** 

 (0.000) (0.000) (0.000) (0.0003) 

𝐶𝑂2𝑖𝑡−1   0.247*** 0.811*** 

   (0.0053) (0.010) 

Constant -1.810*** -1.822***  0.001 

 (0.286) (0.225)  (0.001) 

     

Observations 936 936 886 925 

R-squared  0.905   

Number of id 37 37 37 37 

AR1   -1.97   -2.25   

   (0.049) (0.024) 

AR2   -1.43   -0.89   

   (0.154) (0.375) 

Sargan test   1723.62   1380.07   

   (0.000) (0.000) 

   Note: Standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1

Conclusion  

 

The current study examines the linear and nonlinear effect 

of urbanization on carbon dioxide emission by including 

industrialization, energy consumption and economic growth 

in this association. The belt and road countries data for the 

period of 1976 to 2019 have been collected from the world 

development indicator and employed generalized method of 

moments estimator for analysis. The findings shows that 

urbanization, industrialization, economic growth and energy 

use increase carbon dioxide emission and degrade 

environmental quality however the effect of international 

trade on carbon dioxide emission is negative thus shows that 

international trade significantly reduce carbon emission and 

leads to environmental quality. The study further found the 

U-shape association between urbanization and carbon 

dioxide emission however the Environmental Kuznets curve 

is not validated in this study shown by the square term of per 

capita GDP.  

From the findings, this study concludes that there is high 

level of urbanization in the belt and road countries and 

migration from rural areas to urban areas. This migration to 

cities effects the environment in the belt and road countries 

in several ways as the urban population increase, there will 

be increased air pollution, waste materials in cities and high 

population which worsen environmental quality. This 

urbanization in the belt and road countries can rise economic 

activities in cities however there is worsen environmental 

consequences. However, this urbanization in the sample 

countries increase pollution and worsen environmental 

quality in the initial stage while its will rise environmental 

quality when the urbanization reach a peak level. likewise, 

energy consumption for production and industrialization 

rise carbon dioxide emission in the belt and road countries 

as these sample countries are still developing or emerging 

countries that need to rise economic growth and living 

standard. Thus, increase energy use increase economic 

growth while both economic growth and energy rise carbon 

dioxide emission and degrade environmental quality. The 

environmental Kuznets curve isn’t validated so thus it’s a 

challenge for the belt and road countries to considered the 

environmental consequences while rising economic growth 

through production and industrialization that require high 

amount of energy. The solution maybe that the countries 

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Global Sustainability Research 

 

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need to invest in renewable energy to rise its use in 

production and industrialization so thus environmental 

degradation can be decreased as energy consumption, 

industrialization and economic growth all positively effect 

carbon dioxide in this study. 

The countries are suggested to reduce the rapid growth of 

urbanization in order to control the rapid deterioration of 

environmental quality in urban areas. Likewise, the 

countries need to adopt strategies to use renewable energy 

in production and industrialization process to thus can 

minimize environmental consequences and well can attain 

economic growth. In case on the effect of industrialization 

on carbon emission, the countries should not fully be 

focused on increased industrialization in the initial stage to 

boost economic growth. alternatives should be investigated 

to keep economic growth increasing and to protect 

environmental quality. The international trade should be 

more advantageous to rise economic growth as well to 

increase renewable energy which can be the solution to 

economic growth and environmental problems. The 

findings concludes that most of variables in this study leads 

to high carbon dioxide emission except international trade 

and thus need proper attention. However, urbanization is 

beneficial for economic growth and the U-shape association 

between urbanization and carbon emission is also found thus 

indicates that its can rise environmental quality in later 

stages when its reach a higher level. while on the other hand, 

the economic growth EKC hypothesis is not validated thus 

the countries need special attention to economic activities. 

This study is limited to the variables used. Future study may 

include institutional quality indicators and governance 

which may give important suggestion regarding economic 

growth activities such as the role of governance and 

institutions in conducting environmental regulation and 

economic activities rules to control the harmful effects of 

these factors on environmental quality. 

 

 

Acknowledgment  

 

The authors are thankful to the journal editor and 

anonymous reviewers for their useful comments that 

improved the quality of this work 

 

Funding: No financial support was received for the 

research, authorship, and/or publication of this article  

 

Competing Interests: The authors declared no potential 

conflicts of interest concerning the research, authorship, 

and/or publication of this article  

 

Availability of data and materials: Data used in the 

analysis are available upon reasonable request from the 

corresponding author   

 

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