Japan energy mix and economic growth nexus: Focus on natural gas consumption

Abstract

Japan's recent enunciation of a “Free and Open Indo-Pacific” policy aims to promote principles such as free trade, freedom of navigation, and encouraging economic prosperity with building commitment to stability and peace connecting the economic hub of Asia to Africa (MFA, 2019). Natural gas use continues to dominate Japan's energy mix despite efforts to improve environmental protection and attain the Sustainable Development Goals (SDGs). Also, increasing production and investment typically leads to a better quality of life and more disposable income for the populace, which promotes economic growth. To this end, the study investigates the relationship between economic growth, trade openness, and natural gas consumption, as well as gross fixed capital formation and carbon dioxide emissions to overcome omitted variable problems to explore the natural gas-economic growth hypothesis in Japan over the period 1980–2020. Empirical results reveal a long-run relationship among the variables under consideration. By applying the Toda and Yamamoto approach to Granger causality testing, a two-sided causality running from CO₂ and economic growth was revealed, while a one-sided causality from economic growth to natural gas consumption. This outcome suggests that the natural gas-economic growth hypothesis is not valid for Japan. According to these outcomes, policymakers in the energy sector should consciously diversify their energy portfolio in line with the Sustainable Development Goals (SDGs) for Japan. Also, it is recommended that there should be a provision of access to skilled labor to increase productivity and export finished products to boost a nation's economy.

Keywords

Japan natural gas carbon emissions energy mix economic growth autoregressive distributed lag (ARDL)Toda Yamamoto (TY) granger causality

Introduction

Energy is generally considered a driving force for many economic activities and socio-economic development across the globe enhancing rapid industrialization.^1–3 Renewable and non-renewable energy are classified as energy sources. Fossil fuel (non-renewable) sources like natural gas, coal, uranium, and crude oil, could be referred to as one of the major sources of energy which is primarily comprised of carbon,^4–7 while alternative cleaner energy otherwise known as renewable energy sources which are replenishable includes solar energy directly from the sun, biomass (biofuels), geothermal (hot springs), wind power (wind), and tides (tidal power).^8–10 Fossil fuel-based energy sources, on the other hand, are recognized to emit carbon dioxide emissions (CO2), therefore contributing to environmental degradation. Akadiri et al.¹¹ regarded natural gas (NG) as a significant fossil fuel that has the potential to enhance the economic activity of all nations, regardless of whether the country is regarded as emerging, developing, or industrialized.

A large number of countries around the globe are now becoming more curious about the possibility of utilizing natural gas as a potential substitute due to the reduction in oil deposits in the majority of oil-producing countries. Due to such a circumstance, it is necessary to investigate the causal link among macroeconomic indicators. The health and environmental risks associated with using fossil fuels have sparked big phenomena as well as debate. As a result, there could be a possible contradiction between the efficiency with environmental sustainability in energy-dependent countries.¹² Owusu and Asumadu-Sarkodie,¹² affirmed that the processing, extracting, transporting, and combustion of fossil fuels is a key contributor to greenhouse gas emissions and could harm human health causing (hormones disruptions, adverse cognitive effects among others) and climate change (deteriorating the air quality). Thus, reflecting on the above effect, environmental energy economists agree to implement policies and energy strategies to curb the consequences.

According to energy scholars,^13–16 natural gas has been viewed as a prospective alternate source of energy. Natural gas has emerged as a fresh focus across the energy industry in the world, mainly to its tremendous expansion in consumption.^16–18 Natural gas could help clean up the world's energy system, however, it confronts its own set of issues, such as maintaining price competitiveness in growing sectors while lowering carbon pollution along the natural gas supply chain.¹⁹ Although there exist three fundamental bases why natural gas should be considered as just a potential alternative form of energy. First, it emits fewer carbon emissions (CO2) than other non-renewable energy such as coal and oil. Second, natural gas provides a less divisive form of energy, unlike nuclear power. Lastly, there has been a shift in the general understanding of natural gas accessibility.²⁰ Natural gas might be viewed as a “footbridge” in the transitional stage from a carbon-intensive energy system to a balanced as well as environmentally friendly system. As a result, it is no shock that an economy such as Japan is expanding its natural gas usage. As this phenomenon gathers momentum, worldwide natural gas consumption is fast increasing.^5,6 Hence, as this practice continues to gain traction, worldwide natural gas consumption is quickly increasing,²¹ with a yearly increase predicted to reach 10% between 2007 and 2035.

Following Russia, Iran has the second-largest natural gas (NG) reserves (24.3%, and 17.3% respectively) in the world. An intriguing economy to research in terms of natural gas (NG) production and consumption is Iran, a net exporter of hydrocarbon commodities. Total gas reserves in Japan are less than even a single year of gas consumption, rendering the country extremely reliant on natural gas imports to maintain consumption levels. Iran's natural gas reserves make up around 16% of all global deposits, as reported by the Iran Petroleum Ministry; over 33% of these reserves are related to natural gas and 67% are not. Interestingly, domestic demand for the bulk of the nation's natural gas consumption has increased about 12% yearly on average during the past 20 years. Global natural gas consumption is predicted to fall marginally in 2022 and then gradually increase within the next three years as Russia-Ukraine drives up prices and increases worries of more supply interruptions.²² Natural gas is estimated as over one-fourth of global energy consumption, although new progress/advancement in drilling and production also allowed drastic improvements in gas supply.²³

Japan aspires to attain net-zero carbon dioxide emissions (CO2) by 2050, however, the country's energy alternatives are limited due to its seismically active archipelago. In 2020, energy sources (Fossil fuels) accounted for approximately 75% of Japan's energy mix, with renewables accounting for 19.8% and nuclear energy accounting for 3.9%. The nation's energy independence rate of 1% is the lowest in the G-7. Japan imports 99.7% of its oil, 97.8% of its gas, as well as 99.6% of its coal. These data have rarely improved over decades (see Fig. 1).^19,24,25

Japan's economy acts as a motivating influence to other economies across the globe due to its outstanding automobile and electronics production structure. With this, it appears to be an inspiring country of study, specifically in the context of the consumption of natural gas (NG). As of January 2020, Japan's estimated NG reserves amounted to 738 billion cubic feet (Bcf), though, is one of the world's biggest consumers of natural gas and has little domestic production, the country depends on importation to satisfy virtually all of its NG needs, except for coal, the country does not have large indigenous deposits of fossil energy which placed the country on the global ranking, the world's 5^th leading energy consumer in 2019, and 2^nd in Eastern Asia in 2020, its production was 99,835,505 million cubic feet (mcf) which crowned the country as the world's 59th largest NG producer, Therefore, NGC and production are critical to a country's economic growth and development.^21,26 Despite the fall in energy demand, the country's GDP increased by 9% over this period.²⁷ The country lacks crucial natural resources and depends largely on imported energy to provide a consistent supply of energy. For instance, in 2018, Japan's reliance on the importation of oil was 99.7%, liquefied natural gas (LNG) accounts for 97.5%, and coal reliance was 99.3%.²⁵ On the other hand, it has recently been discovered in Japan that natural gas and trade openness are highly dependent on the economy's energy intensity and population. Natural gas is anticipated to overtake coal as the world's leading significant energy source in the year 2040, attaining 4.9 trillion cubic meters and contributing to 26.9% of the total primary energy supply. Also, the IEA perceives natural gas as a fossil fuel for Japan's economy, allowing for a possible energy transition to a more sustainable route.²⁸

The influence of NG on growth has increasingly earned more interest among scholars; nevertheless, there appear to be few studies on the issue with contradictory policy recommendations. The reason for different results is that past studies on natural gas-economic growth has shown a contradictory relationship in which bivariate modeling is used to assess the existence of a dynamic causal relationship between the variables measured. Lütkepohl²⁹ affirmed that the bivariate model produced unpredictable and even unfair estimates due to some important factors that might impact the natural gas consumption-growth connection were not included. The absence of significant variables in the previous studies makes policy implications generated from such outcomes spurious. Using major macroeconomic indicators or variables in a multivariate model with a good and more accurate econometrics methodology would yield consistent empirical outcomes. As a result, the most recent research^6,16,30 used more regressors such as labor (l), trade (t), capital (k), and import (m) for their respective analysis.

This paper adds to the current body of knowledge on the relationship between natural gas consumption and economic growth in diverse ways: First, it investigates the consumption of natural gas, gross fixed capital formation, CO2, trade openness, and economic growth in Japan by using Autoregressive distributed lag (ARDL) and Toda Yamamoto Granger causality test models. Studies related to Japan NG-EG are limited to the study of Magazzino et al.,³¹ which examines the D2C-causal direction from the dependency algorithm with the connection of NGC-EG between the periods of 1970 to 2018. The logic attributing to the variables selection of the study was traced back to the United Nations Sustainable Development Goals.³² Where natural gas represents SDG 7, Economic growth (RDGP) SDG 8, Gross fixed capital formation SDG 9, Carbon dioxide emissions (CO2) SDG 13, and trade Openness SDG 12 respectively.³ Therefore, based on our knowledge, there has been no specific research for Japan that has explored the influence of NGC, TO, GFCF, and CO2 on EG in a consistent framework employing the ARDL and Toda Yamamoto Granger causality approach for co-integration. This forms the gap in the study, which this research aims to fill.

In summary, this study contributes to the ongoing knowledge based on its research gap that is; no specific research for Japan has assessed the influence of the above variables on economic growth. Thus; the work analyzes the relationship between natural gas consumption to Japanese growth. Researchers investigate whether an increase or decrease in the consumption of natural gas has a substantial influence on economic growth. The remaining parts of the study are arranged chronologically; the next sections provide a view of the empirical and theoretical literature, a summary of the Japanese economy and its energy dynamics, methodology, discussion and presentation of findings and conclusions, as well as policy implications.

Review of theoretical and empirical literature

This part of the review is subdivided into two segments, which are theoretical review and empirical review. The first section focuses to address the study's theoretical footing of the endogenous and exogenous growth theories,³³ the section also discusses on Energy-led Emission Hypothesis and EKC hypothesis which examines the random nexus between environmental quality (carbon emissions), and economic growth,^{10,16,18,34–36} while the empirical review section focuses on the previous studies on the nexus among natural gas consumption, carbon emissions, trade openness, and gross fixed capital formation.

Economic growth and EKC hypothesis

Endogenous growth theory is used in this study to describe growth because of improving labour force population, human capital, and policy decisions which are classified as the (internal factors) economy. Intellectual capital is another category of endogenous growth established by Grossman and Helpman³⁷; Howitt³⁸ These endogenous growth models emphasized quality-improvement technologies premised on Schumpete's³⁹ creative-destruction theory. According to the Schumpeterian approach, overall production is increased through a continuum of advancements in intermediate products. The assertion is that the increased overall product quality boosts productive efficiency in the manufacture of consumption and capital products over time.⁴⁰ Solow's exogenous growth concept contradicts the above model which argues significant increases in technological capabilities resulting from innovation and studies work outside (external) of the household sector, endogenous growth theorists (e.g.^40,41 assert that technological knowledge is acquired via frequent activity (gaining knowledge via practice). In a real sense, endogenous growth economists believe that improved savings, human capital formation and improved infrastructure development, capital investment in research and innovation, and trade liberalization, among other measures, can result in domestically or internally generated growth. This generally implies that attaining substantial economic growth is possible through investing in the health care system, human capital, research and innovation, education, and infrastructural development by the state authority.

Over a few decades, environmental challenges increasing significantly, and several investigations relating to energy economic theories have been conducted to investigate the validity of the EKC hypothesis. According to the classic environment Kuznets Curve (EKC) hypothesis, the traditional asserted that environmental pollution should be measured based on Emissions of CO2, which is also strongly influenced by real income. Kirikkaleli et al.⁴²; Kirikkaleli and Kalmaz⁴³ affirmed that real income is determined through productivity and therefore that consumption of energy is the major means of livelihood, and energy becomes the subsequent significant part of carbon emissions necessary to evaluate.

The Environmental Kuznets Curve (EKC) was invented by Grossman and Krueger⁴⁰ to address the apparent inverted U-shaped connection involving sustainability in terms of growth, and environmental degradation. Hence, various tests have been conducted to objectively evaluate the hypothesis.^44–47 The EKC conceptualization was used in each of these evaluations to investigate the link between income and environmental deterioration, indicating a nexus between economic growth and protection of the environment, whereas environmental destruction is a rising element of economic development until a critical threshold is attained, beyond which greater income rates contribute.

Review of past literature

Kraft and Kraft ⁴⁷ study contributed a strong sensitivity to the nexus between economic growth, and energy consumption which has been considered to have the most effect in the field of energy economics.^16,42,48 In the field of energy economics research, the scholars became the first to demonstrate the presence of a unidirectional relationship between gross national product (GNP) and energy consumption (using the United States as a case study ranging from 1947 to 1974). Despite the findings of Kraft and Kraft,⁴⁷ other scholars^5,49 (including re-investigated the results by Kraft and Kraft). In their contemporaneous studies, the researchers employed different econometrics techniques and expanded the time series. Findings from their studies supported the denial of a unidirectional nexus between GNP and energy consumption as demonstrated by Kraft and Kraft.⁴⁷

The findings of Samu et al.⁵⁰ employed the Maki cointegration technique showing the existence of long-run nexus between real gross domestic product (RGDP), carbon emissions, and electricity consumption ranging from the period 1971 −2014. Therefore, based on the electricity-led hypothesis, the results braced the causality test, showing a one-way interconnectedness has been investigated from real gross domestic product and electricity consumption. Cetin et al.⁴⁹ findings show the existence of long-run unidirectional nexus across energy consumption, economic growth, financial development, CO2, to trade openness which supports the study by Kraft and Kraft.⁴⁷ Rafindadi and Ozturk⁵ affirmed that in the short run, employing a dataset spanning from 1970–2012 portrays the existence of the response interconnectedness among the variables specified in the study such as economic growth, electricity consumption from Japan, imports and exports were revealed. The finding majorly found that economic growth Granger-cause the consumption of electricity supported by Bekun et al.⁵¹ examined the economic growth and energy consumption relationship between the period of 1960–2016 in South Africa. The Granger causality test demonstrates one-way causation linking energy use to economic growth, hence authenticating its energy-led growth theory. Rafindadi and Ozturk's⁵² findings revealed the existence of a response impact between economic growth and renewable energy use. There exist a bidirectional nexus between the consumption of energy and capital while the same implication was discovered between economic growth and capital. Furthermore, Rafindadi and Mika’Ilu⁵³ employed the ARDL bounds testing technique, Zivot-Andrew, Bayer- Hanck, structural break test including Johansen co-integration method to achieve an economic outcome, used a time series data spanning from 1970–2013. The findings from the study revealed cointegration exists between the variables.

The research, on the contrary, revealed the presence of a bidirectional causal link, indicating how renewable or sustainable energy use might contribute to the robustness of the UK financial sector as well as the country's economic expansion prospects. Gyamfi et al. ⁵⁴ employed different techniques i.e; (PMG-ARDL, OLS, DOLS FMOLS) to assess the reliability and robustness of the conceptual relationship between the variables (Carbondixiode emissions, biomass energy consumption, energy investment) analyzed. From their analysis, empirical evidence indicates that mainstream energy generated from fossil liquid fuels contributes to Carbon dioxide emissions in the E7 nations. Therefore, biomass energy use as well as investment in the energy sector reduce Carbon dioxide emissions.

There seems to be a positive feedback causation link between biomass energy usage and carbon dioxide emission. Likewise, there seems to be evidence of a positive feedback causation link between economic expansion and biomass energy demand validating the studies of Bilgili and Ozturk,⁵⁵ comprising data for the years 1980–2009, which investigated the long-term relationships between biomass energy use and economic performance across G7 economies using homogeneous and heterogeneous variance models. The findings also revealed a long-run interaction between gross domestic product (GDP), biomass energy use, and capital formation. The also results validated the development theory: the usage of biomass energy has benefited the G7 country's economic growth.

Contradictorily, the relationship between energy consumption and pollutants remained robust and positive, showing that primary energy demand is not beneficial to ecological sustainability. The evidence suggests that gross domestic product increased long-term pollution in the G7 environment, supporting the G7 block growth-induced emissions hypothesis. They discover a one-way causal relationship between the following variables analyzed in the study: pollutants, biomass and pollutants and production, biomass and output, biomass and energy consumption, and output and energy consumption.

In addition to the review, Bekun and Alola,¹⁷ ascertained in their study that the availability of renewable energy and addressing climate change challenges are linked to the vision of the seventh and thirteenth Sustainable Development Goals (SDG) stated in vision 2030. ARDL and pooled mean groups were analyzed to explore the elements of non-conventional energy in Sub-Saharan Africa. The findings of the study revealed in the short run that a 1% rise in economic growth improves the consumption of energy (renewable energy) by 0.128%. While economic growth diminishes energy consumption by 0.402% before the examined timeframe in the long run. Considering the causation study utilizing the heterogeneous panel, the overall connection outcome shows a one-way connection flowing between growth to renewable energy use. Researchers discovered a positive feedback causation link between urbanization, clean energy, agricultural quality enhancement, and growth.

The study of Bekun,⁵⁶ focused on the study of an Indian economy examining the influence of both renewable and non-renewable energy, energy investment, and economic growth on carbon emissions. Econometrics techniques such as FMOLS, DOLS, and CCR were utilized to examine the long-run elasticity of the variables under investigation while causality nexus was conducted to identify the trend of the interconnectedness between the variables specified. The Empirical regression indicates an inverse connection between CO2 emissions as well as clean energy. Therefore, in the face of an economic growth curve, clean energy seems to be a solution to sustainability. Furthermore, there was a correlation between CO2 emissions and non-renewable as well as growth. the study observed one-way causation between clean energy usage as well as CO2 emissions, growth, and energy investment in the Granger model. The finding supports the studies such as Mujtaba et al.⁵⁷ However, this novelty encouraged contemporary researchers to adopt diverse analytical techniques including data repositories in the forms of panels and time series to continue their inquiry into the relationship involving energy demand and economic growth.

Numerous past research has investigated the strong nexus between natural gas consumption (NGC) and economic growth (EG) in the literature.⁵⁸ The nexus between natural gas consumption and economic growth has recently become a focal point in energy-growth research. Existing research has revealed various correlations between these subjects of interest Unfortunately, barely a few research have presented a full review of the literature, suggesting techniques for comprehending the underlying nexus.^58,59 Fewer researchers possess extensively discussed literature proving the timeframe researched, their methodologies employed, all countries analyzed, as well as the causal relationship revealed.

This research provides gathered literature on widely utilized multivariate model frameworks, variables considered conclusions, policy recommendations regarding natural gas consumption (NGC), and the Economic growth (EG) relationship. For instance, in multinational baseline investigations, Solarin and Shahbaz⁷ for Malaysia, Magazzino et al.³¹ for Germany and Japan, and Rafindadi and Ozturk⁴ for Malaysia. Galadima and Aminu⁶⁰ argued through their research that natural gas usage improves economic growth in Nigeria. Furthermore, researchers used nonlinear estimating methods to verify such assertion as well as determined that the natural gas consumption-economic growth nexus is nonlinear. Galadima and Aminu⁶⁰ found another significant research on Nigeria suggested expanding natural gas utilization seems useful in supporting the country's long-term economic growth.

Likewise, in the context of African countries, According to Awodumi and Adewuyi,⁶¹ the study shows boosting natural gas consumption is not only useful in stimulating economic growth in Gabon but as well as beneficial in alleviating the destruction of the environment. In the context of Nigeria, although, natural gas usage has been claimed to have expansion effects. In the case of Egypt, however, the researchers stated that natural gas use has a minor influence on economic growth. Azam et al.⁶² were unable to show causality between natural gas consumption (NGC) and economic growth (EC) within the context of the global highest CO2-emitting nations.

There have been all-encompassing studies related to the nexus between economic growth and natural gas consumption over the years Akadiri et al.⁸, previous research may be divided into four classifications which are described below:⁸

First, Işik⁶³ and Ziramba⁶⁴ are the first set of scholars who used a bivariate econometrics framework to investigate the claimed connections. In the study of Işik,⁶³ the role of natural gas consumption toward economic growth using the ARDL approach spanning from 1977–2008. The finding revealed a short and long run where he discovered a short and long-run direct nexus between economic growth and natural gas consumption in Turkey. On contrary, Lim and Yoo⁶⁵ adopted periodical frequency data ranging from the timeframe 1991–2008. Two-sided relationships were found between natural gas consumption and economic growth in the case of the Korean economy. In the case of Japan and China, which are known as the two main consumers of natural gas consumption in Asia. Furuoka⁵⁹ used time series between the periods 1980–2012 with an econometric approach (ARDL). The findings revealed that China and Japan exhibit similarities in regards to natural gas consumption - economic growth, and relationships exhibiting long-run cointegration between the variables of interest Regarding Japan's economy, the relationship between the two variables showed two–sided causality while China showed a one-sided relationship between natural gas consumption and economic growth. This is supported by studies such as Etokakpan et al.³; Molele and Ncanywa.⁶⁶

The second category included additional variables such as capital and labour which were distinctly different from the first category. Rafindadi and Ozturk,⁴ examine the relationship between natural gas consumption, economic growth, exports, capital, and labour within the periods 1971–2012 in Malaysia. The findings demonstrated a one-way connection from natural gas consumption to economic growth. Labor, capital, and exports are said to greatly contribute to economic growth with the use of the ARDL bounds technique, Johansen and Bayer-Hanck cointegration, and structural break. The study argued that proper utilization of neutral gas reserves as well as collaborative exertion to improve human capital development in the sampling country.

Apergis and Payne²⁶ used a panel data multivariate method to assess the relationship between domestic investments, economic growth, labour force, and natural gas consumption from 1992 to 2005. Researchers conducted the co-integration approach which revealed a long-run relationship and two-sided causation between economic growth and natural gas consumption. In a multivariate production function research, Alam et al.,⁶⁷ investigate the causal relationship between energy demand and economic growth in Bangladesh spanning 1980 and 2011. Empirically, findings indicated one-sided causation between economic growth and energy consumption, suggesting that overall conservative policy does not constitute the best energy policy instrument for Bangladesh. This is consistent with the studies of Pachiyappan et al.⁶⁸; Chaudhry et al.¹⁵

The third category extensively added extra variables to bridge the literature gaps compared to the previous literature. The studies of Shahbaz, Hye, et al.;⁶⁹ Shahbaz, Khan, et al.;⁷⁰ Shahbaz, Kumar Tiwari, et al.⁷¹ examined the relationships between natural gas consumption, trade (imports and exports), gross fixed capital formation, and economic growth. Researchers revealed a two-sided bidirectional relationship between natural gas consumption, and economic growth for specific countries, as well as labour, export, real capital, and natural gas consumption stimulating growth. This is commensurate with Akadiri et al,⁸ investigation, which looked at the impact of foreign direct investment, trade openness, and capital formation on Malaysian NGC and EC. Ozturk and Al-Mulali⁷² investigate the relationship between natural gas consumption and economic growth in a panel analysis that incorporates trade openness, gross fixed capital formation, and total labour force, as determinants of GDP growth from 1980 to 2012. In the long term, research studies revealed the presence of a cointegration connection between GDP growth and natural gas consumption was found to have a long-run significant effect on GDP growth, with a two-sided causality relationship between natural gas consumption and economic growth. This study was supported by the study of Krarti and Dubey.⁷³

The fourth category of research used a variety of disaggregated types of energy-related variables, including renewable and non-renewable energy, among others. Destek and Okumus⁷⁴ was using the panel bootstrap approach to investigate the disaggregated influence of energy demand which includes oil, coal, and natural gas on economic growth in the Great Seven (7) countries. According to empirical findings, oil consumption indicates growth in Italy, Germany, and United States, whereas growth anticipates oil demand in the United Kingdom and Germany. In the United Kingdom, United States, Japan, and Italy, natural gas consumption was shown to forecast economic growth. Conclusively, Natural gas consumption restricting measures would be detrimental to natural gas consumption-driven economies. This is in agreement with the findings of Rafindadi and Usman ^75,76; Tiba and Omri.⁷⁷ A summary of related studies of the observed variables is shown in Table 1.

Table 1.

Tabular summary of related studies in the literature.

Author(s) and Year	Country/Region	Coverage	Methodology	Variables	Findings/Decision
Adebayo et al.⁷⁸	Argentina	1980–2017.	ARDL, FMOLS, and DOLS;	CO2, GDP FD, REN GLO	Pollution-driven economic growth trajectory in Argentina with high dependence on fossil fuels.
Akadiri et al.⁸	Saudi Arabia	1968–2016	ARDL, Cointegration, Toda and Yamamoto	NGC, TT, Real GDP	Natural gas conservation policies will reduce demands for energy (Natural gas), impede overall trade, and therefore slow domestic productivity.
Akadiri et al.⁷⁹	Tourism island states:	1995–2016	Panel Co-integration and Panel Granger Causality	CO2, GLO, RGDP TA	The findings showed a two-way relationship between GLO and CO2, and one -way relationship between IT and CO2 in the long run
Bekun⁵⁶	Indian	1990–2016	DOLS, CCR, FMOLS	CO2, REC, NREC, GDP, IEC	Empirical regression indicates an inverse relationship between CO2 emissions as well as clean energy.
Bekun and Alola¹⁷	Sub-Sahara African	Not specified	ARDL-PMG	ELE,URB, RGDP, AG, REC	The study discovered a feedback direct causal link across urbanization, clean energy, agricultural value addition, and real GDP
Bekun, Agboola, et al.¹⁴	Nigeria	1971–2015	ADF, PP, ARDL	CO2, RGDP	The dynamic analysis verifies the EKC concept in the Nigerian situation.
Bekun, Alola, et al.³⁵	European Union (EU) member states	1990–2017	Panel unit roots, GC	CEM, GDPC, GDPCsq, and EINTENSITY	The findings attest to the presence of EKC facts relating to growth at expense of environmental quality.
Asongu et al.⁴⁸	Africa	1980–2014.	ARDL-PMG, GC,	CO2, URB, ELE, NEC GDPC	There is a bidirectional relationship between pollutant emissions, energy usage, and real GDP but there is a unidirectional relationship between total natural resource rent and pollutant emissions.
Bekun, Gyamfi, et al.³⁶	E7:Economies China, India, Brazil, Mexico, Russia, Indonesia, and Turkey,	1995–2016.	Augmented Mean Group, Common analysis.	CO2, EG, I, NR, and R	Clean energy is generally viewed as a cure for reducing pollution emissions since it has a negative and statistical connection with CO2 emissions during the observed timeframe.
Cetin et al.⁴⁹	Turkey	1960-2013	CO2, TR, FD, EN, GDP	VECM Granger causality	The results, therefore, demonstrate that the EKC application or hypothesis is appropriate for Turkey in both the long and short run.
Rafindadi⁸⁰	Japan	1961- 2012	C, Y, EX, IM	ARDL, GC	The findings showed that energy demand is the leading cause of environmental pollution in Japan and that although exports reduce CO2 emissions, imports contribute to environmental deterioration.
Rafindadi and Mika’Ilu⁵³	United Kingdom	1970–2013	EC, Y, F	UECM, ARDL	According to the study, economic growth has a considerable impact on sustainable energy use, but the capital formation is strongly related to energy consumption.
Rafindadi and Ozturk⁴	Malaysia	1971–2012	G, Y, EX, K, L	Bayer–Hanck cointegration, ARDL bounds tests	The findings of this study indicate that economic expansion does not influence gas consumption in Malaysia.
Rafindadi and Ozturk⁶	South Africa	1970-2011	E, FD, Y, TR,	Bayer–Hanck cointegration, ARDL bounds tests	The findings suggest that financial growth drives South African energy use; wealth is directly associated with demand, and trade openness significantly raises energy consumption.
Rafindadi and Ozturk⁵²	Germany	1971Q1 to 2013QIV	Y, RE, K, L	ARDL bounds tests, VECM	Findings suggest that the consumption of renewable energy in Germany strengthens the country's economic growth prospects
Rafindadi and Usman⁷⁶	Brazil	1971M: 01 - 2014M	EC, GDP, GI, FPT	Nonlinear ARDL model.	The results show that the effects of economic growth, globalization, and ecological footprint on electricity consumption are asymmetric.
Rafindadi et al.⁸¹	Cooperation Council GCC	1990 to 2014	C02, FDI,DI, EC	Pooled Mean Group (PMG)	The research also showed how increased discretionary income and FDI aid in the improvement of environmental quality in the GCC.
Chaudhry et al.¹⁵	Pakistan	1990–2017	GDP, REC, CC, OC, NGC, CO2	ARDL approach	Following the findings, Pakistan should pursue several initiatives to reduce its reliance on non-renewable energy sources, which hurts growth.
Gyamfi et al.⁵⁴	E7 countries	1995–2018	CO2, GDP, REC	PMG-ARDL estimator and heterogeneous causality	Although clean energy and nonrenewable energy have a substantial and positive connection with Carbon dioxide emission, short-run findings indicate no substantial connection between economic growth, clean energy, nonrenewable energy, and CO2 emissions.
Işik⁶³	Turkey	1977–2008	ARDL model	NGC ↔ EG	Feedback
Apergis and Payne²⁶	A panel of 67 Countries	1992–2005	Pedroni Co-integration	NGC↔ EG	Feedback
Shahbaz, Lean, et al.⁸²	Pakistan	1972–2010	ARDL bounds test	EC→ EG	Conservative
Solarin and Shahbaz⁸⁴	Malaysia	1971–2012	VECM, ARDL, BH	NGC ↔EG	Feedback
Shahbaz et al.⁸³	Pakistan	1972QI and 2011QIV	ARDL bound testing	NGC ↔EG	Feedback
Solarin and Ozturk⁸⁰	12 OPEC member countries	1980–2012	Panel Granger causality	NGC ↔EG	Feedback
Etokakpan et al.²	Malaysia	1980–2014	ADF, ZA, BH, ARDL, Granger causality	NGC ↔EG	Feedback
Lim and Yoo⁶⁵	Korea	1991–2008	CGC, VECM	NGC ↔EG	Feedback
Etokakpan et al.³	China	1971–2018	ARDL bound testing and EKC	NGC←EG	Growth
Farhani et al.⁸⁵	Tunisia	1980–2010	ARDL, TY, JJ	NGC → EG; EG x NGC	Feedback
Kum et al.⁸⁶	G-7 countries	1970-2008	GC, Bootstrap, TY	EG←NG	Growth; Neutrality
Akadiri et al.⁸	Saudi Arabia	1968–2016	ARDL, TY, GC	NGC → EG; EG x NGC	Feedback
Okoye et al.³³	Nigeria	1981–2017	ARDL, DT, ECM	EC→ EG	Growth
Magazzino et al.³¹	Japan and Germany	1970–2018	D2C Algorithm	NGC ↔ EG	Feedback
Elgharbawy and Sayed⁸⁷	Europe, Asia, and Africa.	2014–2020	Descriptive and Graphical Plots	NGC ↔ EG	Growth; Neutrality
Dantama et al.⁸⁸	Nigeria	1980-2010	ARDL bound test	NGC → EG	Growth
Heidari et al.⁸⁹	Iran	1972–2007	Descriptive stats, Graphs, Bound test	EC → EG	Feedback
Arora and Shi⁹⁰	United State	[1973Q1–2014Q1	GC	EC → EG	Conservative
Farhani and Rahman⁹¹	France	1990 to 2014	VECM, ARDL, GC	EC → EG	Feedback

Note: (ARDL -PMG) Autoregressive distributive lag methodology, Pesaran's Panel Pooled Mean Group, (GC)Granger causality, (CO2)carbon emissions, (GLO)Globalization, (ELE)Electricity consumption, (CCR)Canonical cointegration regression, (EG)Economic Globalization (I) institutional quality, (NR and R) Energy consumption, (C) CO2 emissions per capita, (EX)real exports per capita, (IM) real imports per capita, (F) financial market, (UECM) unconditional error correction model, (RE)renewable energy consumption per capita, (K) real capital per capita, (L) labor force per capita, (FDI) foreign direct investment.

A summary of the Japanese economy and its energy dynamics

Japan is an island nation in Eastern Asia that has a distinct geographical element with a total land area of 377,975 km², situated in the northwest Pacific Ocean. The population of Japan is 126,476,461 million as of September 2021. The population density in Japan is expected to be 347 per Km² (899 people per mi²). Similar to Britain and Canada's system of government, Japan runs a parliamentary system. Japan is a monarchy system of government focused on the division of powers. It is a unified state comprising 47 administrative districts and the Monarch as its Constitutional monarch.

It is surrounded by countries such as South Korea, Russia, and Republic of China, North Korea, and the Philippines. Japan's economy is endowed with natural resources not restricted to copper, gold, coal, silver, sulfur, iron ore, limestone, etc. Japan's economy progressively evolved and remains an agricultural country from agricultural and commodity production to a worldwide participant in manufacturing and services, particularly in the exporting of cars, textiles, electronic equipment, and steel. Over the years, the energy sector has been gaining huge recognition as becoming a lifesaver for the Japanese economy.

The energy sector in Japan plays a substantial part in the country's growth and development. 3.7 million barrels per day (b/d) was estimated in 2019 for Japan's oil consumption placing it as the 5th largest petroleum consumer globally trailing China, Russia, India, United States.¹ As of the fiscal year 2018, coal accounted for 32% of power capacity in Japan, trailing only natural gas (38%). The Ministry of Economy, Trade, and Industry (METI) intends to decrease thermal coal power to 27% by 2030 and increase renewable energy to 22–24%, creating electricity that produces no greenhouse gases from fossil fuels and lowers some form of air pollution, diversifying energy production and decreasing reliance on imported fuels and creating employment in manufacturing, installation, and other industries. The industry generates income for the Japanese government via dividends and taxation while the major activities or industries are manufacturing, agriculture, fishing, tourism, etc.

The Japanese economy is dominated by the consumption of natural gas.¹⁹ 634,654 TJ to 1,395,179 TJ in between. Over the same period, the demand for natural gas in Japan increased. Japan grew heavily reliant on fossil fuels due to the enormous importation of around 95% of the gas they consume due to insufficient domestic fuel resources. On the other hand, it has recently been proven that the population and country's level of energy intensity has a significant impact on the consumption and import-export of natural gas companies. Natural gas is anticipated to surpass coal as the dominant energy source on a global scale by 2040, reaching 4.9 trillion cubic meters and accou/nting for 26.9% of the total primary energy supply. To ensure a feasible energy transition towards a sustainable path, Japan's economy also views natural gas as a bridge fuel. However, despite strong encouragement for renewable energy to take a significant share soon, the majority of the country's electricity still comes from nuclear power, despite recent events eroding this energy pattern. A historical pause has been caused by the prompt shutdown of operating power plants in Japan due to security concerns. The Japanese government is committed to implementing a comprehensive energy reform to diversify its energy mix over the long term, even though some of them have just been restarted after passing safety regulations.²³

Description of variables and sources of data

This section emphasizes data description, economic model, econometric estimations, data source, and unit of measurement of the study. The interconnections between natural gas consumption and Japanese growth are examined in this study. Improving the previous studies^2,7,8,26,63 among others. The researchers investigated the existence of relationships between natural gas consumption (NGC) and economic growth (EG), but this study incorporated the inclusion of Trade Openness (TO), Carbon dioxide emissions (CO2), Gross fixed gross capital formation (GFCF) as an explanatory and control variables to enhance the robustness of the study, and to eliminate the limitations of the previous studies.

The logic underlying the variables’ choices can be attributed to the United Nations Sustainable Development Goals (UNSDG) of which Japan serves as a member of the United Nations. The variables of interest can be traced to sustainable development goals such as; (SDG 7) which emphasized Natural gas (NG): Planned endeavors for using cleaner energy to offer electricity availability remain part of the long-term aims that would boost growth while protecting the environment. Real GDP is used as a proxy of economic growth which focuses on a substantial production level needed to reach full employment across the economy. As a result, SDG 8 aims that encourage innovators/ businessmen who influence the process to generate quality employment for the huge jobless population who already are willing and capable of working. These would aid in attaining long-term economic growth.

SDG 9 explains gross fixed capital formation (GFCF) which is used as a proxy for physical capital. The funding required to construct infrastructure will be determined by wealth creation with industrial as well as productivity increases. An overall aggregate of these will raise investment, which will be advantageous in improving infrastructure facilities, hence increasing the manufacturing contribution to growth. As a result, it promotes equitable, efficient industrialization, and fosters creativity including development.

SDG 13 is focused on decreasing the risks and consequences of climate change. The harmful impact of anthropogenic environmental pollution on human life and the environment requires immediate attention, especially as CO2 accounts for a large share of greenhouse gas (GHG). The 17 SDGs address a wide range of issues, including poverty, health, sustainable development, including environmental protection. Trade has no particular SDG target because it is not an end in itself, however, it is acknowledged as a significant way to achieve it. However, SDG 17 recognizes trade as a means of application and implementation for the 2030 Agenda. Annual time series arranged from 1980–2020 for Japan were gathered from the Energy Information Administration (EIA) and the World Bank Development Indicator (WDI). Table 2 describes the unit of measurement and their corresponding sources.

Table 2.

Description of variables.

S/N	Variables	Symbol	Unit of Measurement	Source
1	Real GDP	RGDP	Constant 2010 dollars ($)	WDI
2	Carbon-dioxide emission	CO2	Kiloton (kt)	WDI
3	Natural gas	NG	Measured in dry NG in billion Cubic meter	EIA
4	Trade Openness	TO	Sum of imports and exports	WDI
5	Gross fixed capital formation	GFCF	Constant 2010 dollars ($)	WDI

Author's computation.

Research methodology

The research adopts the following test processes sequentially; (i) Testing of unit root for stationary between the variables of interest through Augmented Dickey-Fuller (ADF) propounded in 1981,⁹² (ii) Investigating the long-run equilibrium nexus among the variables using bounds test co-integration, while the Autoregressive Distributed Lag Model (ARDL) approach of Pesaran et al.⁹³) was also examined to test the long-run robustness nexus (iii) Toda Yamamoto Granger causality test was adopted to determine the trend of connectedness between the variables.

Model specification

Explicitly, the study modifies the Akadiri et al.⁸ research model which is given below as equation (1).

R G D P_{t} = f (N G C_{t}, T r a d e_{t})

(1)

The above variables include trade which represents the aggregate trade acquired by summing total import and total export, economic growth denotes RGDP as proxy measures in constant 2010 billion US$, and Natural gas consumption (NGC) measured dry natural gas in billion cubic- meters. The functional form of this study model modifies equation (1), incorporating gross fixed capital formation (GFCF), and carbon dioxide emission (CO2), to achieve enhanced robustness of the results.

R G D P_{t} = f (N G C_{t}, T O_{t}, G F C F_{t}, C O 2_{t})

(2)

In a linear logarithm transformation;

I n R G D P_{t} = α_{0} + α_{1} I n N G C_{t} + α_{2} I n T O_{t} + α_{3} I n G F C F_{t} + α_{4} I n C O 2_{t} + u_{t}

(3)

Where: α₀ = Intercept; α₁… α₅ = slope of the parameters; u_t = stochastic variable or disturbance variable and the apriori expectations is expected to be α₁ > 0; α₂ > 0; α₃ > 0; α₄ > 0

Eq. (3) represents a linear specification for the study where InRGDP_t denotes the natural log of the real gross domestic product measured in constant 2010 billion US$, InNGC_t represents the logarithm of Natural gas consumption measured by dry natural gas in billion cubic meters, InTO_t indicate the log of trade openness as the total of a country's exports and imports as a percentage of its gross domestic product (GDP) specifically in (%), InGFCF_t denotes the log of Gross fixed capital formation measure in constant 2010 billion which includes capital spending on infrastructure, equipment, machinery and housing among others and InCO2_t represent the log of Carbon dioxide emission measured in kiloton (kt).

Stationarity test

From an econometrics perspective, testing for stationarity is an important step to ascertain the order of variable integration. Variables are revealed to be stationary at a level that denotes I(0) while at first differencing denotes I(1) before carrying out a test for co-integration and causality test towards avoiding inaccurate policy implications and spurious analyses. Dickey-Fuller's (DF) 1979, the technique is considered one of the weakest methods for the presence of unit root, simply because it only comprises the AR (1) for the time series. With the failure of the method, approaches such as parametric known as a superior parametric test-Augmented Dickey-Fuller⁹⁴ and non-parametric Phillips and Perron's⁹² stationarity tests are for solving the problems of series autocorrelation and heteroscedasticity of a model. The unit root equation is shown as below;

Δ Y_{t} = b_{0} + β t + δ Y_{t - 1} + \sum b_{j} Δ Y_{t - j} + u_{t}

(4)

The error term (

u_{t}

) in the ADF equation indicates the disturbance variable,

b_{0}

stands for the intercept, and subscript “t” shows the time in the equation. If time trend is not necessary, the model also run without

t

_. To mitigate the issue of serial correlation between our error terms, we empirically measure the number of lagged differences. It is done to avoid a misleading or biased analysis of δ. Greene⁹⁵ affirms that the quality of the ADF method permits the higher-order autoregressive process. H_o: δ = 0 signifies (not stationary) the null hypothesis regarding the ADF method which means that the time series has a unit root while H₁: δ < 0 indicates the stationarity of a time series which denotes the alternative hypothesis.

Autoregressive distributed lag method

ARDL method is used to examine the co-integration relationship between natural gas consumption and economic growth by controlling other selected variables such as carbon dioxide emissions, gross fixed capital formation, and trade openness. This method ensures coherent estimates, particularly whenever the population size is small and finite in comparison to other conventional co-integration methods. It is commendable that this technique can present the long-run and short-run patterns of fitted regression, as well as the error correction term (ECT).⁹³ Aside from the benefits mentioned above, it is therefore important for its use in the context of uncertain order of stationarity such as I(0) or I(1), but surely not I(2). It is often computed in the context of unconstrained error correction, with variables considered to be endogenous. The use of this method is consistent with previous research (Akadiri et al.,⁸) using single-equation models to evaluate long- and short-run impacts. The model carried out an estimation of the short-run and long-run influence on the predictor variables like natural gas consumption, CO2, gross fixed capital formation, and trade openness on the economic growth of Japan. Hence, since the bounds test of the variables showed the existence of co-integration, the ECM model for the short run and the long run is given below;

\begin{aligned} Δ I n R G D P_{t} = & α_{0} + α_{1} I n R G D P_{t} + α_{2} I n N G_{t - 1} + α_{3} I n G F C F_{t - 1} + α_{4} I n C O_{2, t - 1} + α_{5} I n T O_{t - 1} \\ + \sum_{i = 1}^{q} β_{i} Δ I n R G D P_{t - i} + \sum_{i = 1}^{p} θ_{1, i} Δ I n N G_{t - i} + \sum_{i = 1}^{p} θ_{2, i} Δ I n G F C F_{t - i} + \sum_{i = 1}^{p} θ_{3, i} Δ I n C O_{2, t - i} \\ + \sum_{i = 1}^{p} θ_{4, i} Δ I n T O_{t - i} + ε_{t} \end{aligned}

(5)

Where:

Δ is difference operator; $ε_{t}$ stands for the residual term of the normal distribution; p and q are the optimal lag orders. The long-run coefficients of the model are obtained from the first part of the equation (5). The parameters $α_{1}, \dots, α_{5}$ are the long-run effects of all the independent variables on economic growth. The short-run equation of ARDL estimates the ECT which is the error correction term showing the speed of adjustment of the model to long-run equilibrium convergence. Thus, we estimate the error correction model given as

\begin{aligned} Δ I n R G D P_{t} = & α_{0} + \sum_{i = 1}^{q} β_{i} Δ I n R G D P_{t - i} + \sum_{i = 1}^{p} θ_{1, i} Δ I n N G_{t - i} + \sum_{i = 1}^{p} θ_{2, i} Δ I n G F C F_{t - i} \\ + \sum_{i = 1}^{p} θ_{3, i} Δ I n C O_{2, t - i} + \sum_{i = 1}^{p} θ_{4, i} Δ I n T O_{t - i} + λ E C T_{t - 1} + ε_{t} \end{aligned}

(6)

Where the speed of adjustment is captured by

E C T_{t - 1}

λ

denotes ECM coefficients, which should be negative and statistically significant.

Toda Yamamoto (TY) causality test

Kraft and Kraft⁴⁷ affirmed that traditional regression does not show a relationship; therefore, For the policy recommendations which could be drawn from such estimates, a causality test is required. In this study, the Toda and Yamamoto⁹⁶ causality testing were adopted. The Toda and Yamamoto (TY)⁹⁶ test is an improved version of the Wald test that outperforms traditional Granger causality. Even in the presence of heterogeneous cointegration, the TY technique produces reliable and accurate estimates. The TY model is conducted in vector autoregressive framework VAR (k + d_max), where k depicts the optimal order of the VAR model and d_max is the maximum integration order. The VAR (k + d_max) can be expressed as; (see Appendix I). The variables LNRGDP, LNCO2, LNG, LNTO, and LNGFCF have already been expounded in part 4.5 above. Moreover, ε_1t, ε_2t, ε_3t, ε_4t, and ε_5t, indicate the disturbance terms of the estimated models respectively. ∑ signifies summations whereas α, β, and φ are the constant terms. k signifies the optimal lag, order as mentioned by the AIC. By using the standard Chi-square statistics, Wald tests are adopted to the first k coefficient matrices

Discussions and empirical results

This part of the study encompasses empirical and preliminary interpretations of the results estimated, linking and comparing the findings to the previous studies in the literature. To ascertain a good picture of the variables used, Fig. 2 reveals the graphical presentations of the estimated variables specified in the study, showing their movements or trends. Table 3 and Table 4 show descriptive statistics, and a correlation matrix respectively. The graphs of trade openness, carbon dioxide emissions, and gross fixed capital formation show the most inconsistent variables over time. However, it also suggests that the trajectory of economic growth (LNRGDP) in Japan is impacted by the activities of carbon emissions (LNCO2), gross fixed capital formation (LNGFCF), natural gas consumption (LNNGC), and trade openness (LNTO). However, the graph depicts the case of carbon emissions, Trade Openness, and gross fixed capital formation indicating a high-pitched break experienced in Japan causing a reduction in their CO2 emissions and failure in trade including capital formation with a rise in their natural gas consumption and economic growth. This suggests that natural gas consumption is environmentally friendly reducing carbon emissions (CO2), becoming cleaner energy than other traditional fuels, and promoting the Japanese economy towards increasing the consumption of non-renewable energy which in turn mitigates the carbon emissions (CO2) in Japan. According to the Center for Liquefied Natural Gas, natural gas emits fewer. This is consistent with the studies of Gyamfi et al.⁹⁷ and Rafindadi et al.⁹⁸

Table 3.

Descriptive statistics.

	LNRGDP	LNNG	LNCO2	LNTO	LNGFCF
Mean	10.592	7.820	13.917	3.191	27.927
Median	10.649	7.949	13.960	3.202	27.983
Maximum	10.799	8.385	14.047	3.625	28.127
Minimum	10.160	6.800	13.692	2.773	27.567
Std. Dev.	0.179	0.462	0.105	0.275	0.158
Skewness	−1.057	−0.768	−0.983	0.052	−1.069
Kurtosis	3.023	2.614	2.563	1.574	2.947
Jarque-Bera	7.646	4.293	6.933	3.491	7.815
Observations	41	41	41	41	41

Table 4.

Correlation matrix.

Variables	LNRGDP_t	LNNG_t	LNCO2_t	LNGFCF_t	LNTO_t
LNRGDP	1
LNNG	0.974	1
	(0.0000)
LNCO2	0.892	0.879	1
	(0.0000)	(0.0000)
LNGCF	0.757	0.623	0.752	1
	(0.0000)	(0.0000)	(0.0000)
LNTO	0.350	0.445	0.208	0.203	1
	(0.024)	(0.003)	(0.191)	(0.202)

Source: Researchers’ compilation.

Table 3 shows the descriptive statistics such as the mean, median, and Standard. dev., skewness, and kurtosis, minimum and maximum. Comparatively, the observations are limited to 41 and the standard deviations in the analysis are significantly lower than the mean and median values. Mean values of real GDP_t, CO2_t, and GFCF_t are less than their median values which affirm that the variables are negatively skewed, while TO_t is greater than the median and only considered as positively skewed. Jargue-Bera's decision rule aligns with the probability which indicates that natural gas consumption and trade openness was normally distributed within the years 1980−2020 since the probabilities for such variables remain insignificant, while real GDP_t, GFCF_t, and CO2_t were not abnormally distributed. Table 4 depicts the correlation matrix of the response and explanatory variables generated to gain a basic understanding of the direction of the connection among the variables. The table indicates the correlation of Real GDP with NGC_t has a coefficient of 0.974, with a p-value of 0.000 which means that an increase in natural gas consumption will increase economic growth in Japan and it is statically significant. This is consistent with the empirical findings.^2,4,8,10 Similarly, there is an existence of correlation with CO2_t which has a coefficient of 0.892 with a p-value of 0.000 which simply means that the coefficient depicts a significant level because increasing productivity and economic growth entails increasing emissions levels. Higher output demands increased input, which necessitates the use of additional natural resources and a spike in pollutant emissions. Carbon emissions are expected to rise in proportion to economic growth. The result is consistent with the study of Bekun⁵⁶; Cosmas et al.⁹⁹; Rafindadi.¹⁶ GFCF_t has a coefficient of 0.757 and is statistically significant. The higher the GFCF_t, the higher the economic growth. In essence, the more a country's capital formation, the quicker it may increase its overall revenue. Trade openness also is statistically significant at 0.024. This implies that trade has a significant impact on growth. That is, trade openness enables countries to increase output, boosting returns to scale and the economics of specialization.⁸ Thus, caution must be used when analyzing the correlation matrix since it cannot offer a good indication of the relationship in a way that accounts for other regressors, necessitating the application of appropriate robustness tests. Once the analysis of pre-estimation diagnostics and graphical plots of the series were utilized, it is important to carry out the stationarity of the data.

The Augmented Dickey-Fuller⁹⁴ and Phillips-Perron⁹² unit root testing were adopted to validate the series and determine the order of integration of the variables of interest in Table 5. At levels, the table reveals that all the sampled variables were not stationary except the NG_t and RGDP_t which showed stationarity but become stationary at first differencing. after estimating the ADF approach. Thus, the analysis shows that the variables are integrated in the order of I(1) at a 10% level of significance. Philip-Perron results from the table show that the same variables such as NG_t and RGDP_t variables are non-stationary at level but stationary at first difference showing a 10% level of significance and integrated in order of I(1) and therefore useful for co-integration approach.

Table 5.

Unit root test.

Method	Forms	InCO2_t	InGCF_t	InNG_t	InRGDP_t	InTO_t
ADF (t_U)	Level	−1.5501	−2.3416	−4.0638***	−4.2686*** −0.7963
		(0.4983)	(0.1646)	(0.0031)	(0.0017)	(0.8093)
1st Diff.	Δ	−5.4687***	−4.0026***	−4.266***	−4.037***	−5.5565***
		(0.0001)	(0.0035)	(0.0018)	(0.0032)	(0.0000)
	level	1.0454	−2.1054	−1.9207	−2.1857	−2.2149
ADF (t_t)		(0.9257)	(0.5268)	(0.6242)	(0.4843)	(0.4688)
	Δ	−5.6443	−4.0941	−5.9997	−4.8771	−5.7584
1st Diff.		(0.0002)***	(0.0134)***	(0.0001)***	(0.0017)***	(0.0001)***
Order of Integration		I(1)	I(1)	I(1)	I(1)	I(1)
PP (t_u)	level	−1.566	−2.117	−9.5227***	−4.0107***	−0.885
		(0.4903)	(0.2393)	(0.0000)	(0.000)	(0.7828)
1^st Diff.	Δ	−5.4416***	−4.0307***	−4.3401***	−4.0058***	−5.5232***
		(0.0001)	(0.0033)	(0.0014)	(0.0035)	(0.0000)
	level	−1.1434	−1.7407	−0.4835	−2.1434	−2.1391
PP (t_t)		(0.9084)	(0.7142)	(0.9803)	(0.5068)	(0.5091)
	Δ	−5.9763***	−4.0868**	−8.7606***	−4.8771***	−5.8513***
1^st Diff.		(0.0001)	(0.0137)	(0.0000)	(0.0017)	(0.0001)
Order of Integration		I(1)	I(1)	I(1)	I(1)	I(1)

Note: The asterisks (^*,** and ***) indicate a rejection of the null hypothesis at 1%, 5%, and 10% significance levels respectively.

Table 6 shows the different lags of the model. The most appropriate and maximum VAR lag selection criteria were selected which were derived from the unrestricted vector autoregressive model. It shows the most suitable lag length criteria selection is SIC lag length of 1 which is capable to accommodate trivial size which is fit for this study. Since the unit root depicts stationarity and integration of order I(1), Pesaran et al.⁹³ bounds test cointegration was performed to determine the robustness using the ARDL bounds approach in Table 7 to confirm the cointegration between the sampled variables. The table indicates that the F-statistic value (11.03) is greater than the upper bound at 1%, 5%, and 10% levels of significance. Therefore, it shows the presence of long-run cointegration relation among the real GDP, Natural gas consumption, Carbon dioxide emission, Gross fixed capital formation, and Trade openness in Japan.

Table 6.

Lag selection criteria.

Lag	LogL	LR	FPE	AIC	SC	HQ
0	196.1850	NA	3.80e-11	-9.80436	-9.59108	-9.72784
1	437.2222	407.9092	5.94e-16	-20.8832	-19.60353*	-20.42406*
2	463.7796	38.13363*	5.86e-16*	-20.96305*	-18.617	-20.1213

Table 7.

ARDL bound test result.

Test Statistic	Value	Signif.	I(0)	I(1)
F-statistic	11.03736	10%	2.45	3.52
K	4	5%	2.86	4.01
		2.5%	3.25	4.49
		1%	3.74	5.06

Source: Authors’ Compilation.

The result of ECM-ARDL for the above-estimated model are reported in Table 8. The outcome of all variables both in the long-run and short-run does not associate with the trend of each other. In the short-run analysis, the coefficient of CO2 showed a substantial positive nexus with Real GDP. Such an increase permits a trade-off between environmental quality and economic growth. Although faster improvements in output are possible due to more intense energy usage by current technology, capacity grows and also CO₂ emissions. Consequently, environmentally sustainable and modernized energy sources were supported, particularly in light of a worldwide transition to greener forms of energy pioneered by other countries. This result supports the findings of Emir and Bekun¹⁰⁰; Kasperowicz¹⁰¹ for gulf cooperation council countries, Akadiri et al.⁸ for Saudi Arabia, and Caporale et al.¹⁰² for China. On a contrary, the study of Salahuddin and Gow¹⁰³ shows that there is no nexus between pollution and economic growth. The result in the short-run and long-run showed negative nexus between NG and economic growth. A percent rise in natural gas consumption does not lead to a rise in economic productivity in Japan. This depicts that energy consumption such as natural gas alone does not lead to an increase in the Japanese economy.

Table 8.

Long-run and short-run outcome.

Variables	Coefficient	Std error	t-statistics	Prob.
Short-run result
ECT(−1)*	−0.063227	0.007979	−7.924567	0.0000*
Δ(InCO2 _t )	0.136145	0.032457	4.194606	0.0002*
Δ(InNG _t )	−0.019053	0.024477	−0.778412	0.4424
Δ(InGCF _t )	0.294334	0.020696	14.22203	0.0000*
Δ(InTO _t )	0.030644	0.010125	3.026586	0.0051*
Constant	−1.071664	0.136755	−7.836387	0.0000*
Long run result
InNG _t	−0.259931	0.557521	−0.466227	0.6444
InGCF _t	0.354147	0.184633	1.918107	0.0647***
InCO2 _t	1.222393	1.432455	0.853355	0.4002
InTO _t	0.33052	0.279207	1.183779	0.2458
Constant	−1.110631	0.63567	−1.747181	0.0908***

Source: Author's compilation.

Note: Asterisk (*, ***) denotes 1% and 10% levels of significance respectively.

Furthermore, evidence showed that fossil fuels influenced growth, but it revealed that over 88% of crude oil contributes largely to economic growth and development while little amount accounts for Liquified natural gas (LNG). This outcome contradicts the research carried out by Rafindadi and Ozturk⁴ for Malaysia; Solarin and Ozturk⁸⁴ for OPEC members; Sinaga¹⁰⁴ for Indonesia, Etokakpan et al.² for Malaysia; Etokakpan et al.³ for China. Also in the short run, trade openness has a positive relationship with Real GDP at (P < 0.01) level of significance. The result indicates that trade openness has an insignificant impact on economic growth in the long run. This outcome reverberates with the results of Akadiri et al.⁸; Saudi Arabi, Farhani et al.⁸⁵ for Tunisia; Lim and Yoo⁶⁵ for Korea. Similarly, gross fixed capital formation is positively and statistically significant in both the short-run and long-run with a p-value of 1% and 10% significant levels. This reveals the positive nexus perceived between gross fixed capital formation and economic growth in Japan. The outcome resonates with the findings of Etokakpan et al.³ The error correction term ECT(−1)* shows the speed of adjustment of short-run change of Real GDP to its long-run model equilibrium following a shock. This implies that the deviation from the long-run equilibrium path of Real GDP in one year is modified by 6.3% per unit time or yearly. Since the variables showed the order of integration I(1), stationary at first differencing and the residual ECT_t−1 is stationary at level, it shows the presence of co-integration or long-run equilibrium nexus between the variables of interest.

Moreover, the diagnostic time series tests described in Table 9 shows to assess the model's competency for policy, strategic direction, and guidance. There is no violation of an assumption in the fitted model of the classical linear regression model (CLRM) such as the heteroscedasticity test: ARCH and Breusch-Godfrey Serial Correlation LM. No problem with heteroscedasticity if the null hypothesis is accepted given a probability value less than 5% and reject if it is greater than a 0.05 level of significance. This demonstrates that the model is free of the auto-correlation problem. Fig. 3 depicts the recursive estimates of the fitted model's stability is diagnosed using the cumulative sum (CUSUM) and cumulative sum of squares (CUSUMsq) tests. Based on the study by Brown et al.¹⁰⁵ the model stability is considered short- and long-term changes through the residuals. The model stability is considered short and long-term changes through the residuals. Since the blue plotted line is within the critical values and less than of 5% significance level, this means that the estimated model is stable.

Table 9.

Diagnostic tests.

Test	F-statistic	Obs*R-squared	Chi(χ2)	Prob.
Heteroskedasticity Test: ARCH	0.086509	0.187332	0.9106	0.9173
Breusch-Godfrey Serial Correlation LM Test:	0.252064	0.714838	0.6995	0.779

Source: Authors’ Compilation.

The Toda-Yamamoto Granger causality analysis was performed to determine the direction of the Granger causal relationship between the variables. The Granger causality results are used to determine whether one variable has predictability power on another by taking into account the co-existence term and its historic realization among the emphasized variables namely; Real GDP, natural gas consumption, CO2 emissions, and gross fixed capital formation. Such knowledge contributes to the expansion of suitable energy strategies for long-term economic growth. From Table 10, the results indicated the trend of interconnections between variables of interest gross fixed capital formation. Specifically, there is a feedback effect between CO2 emissions and real GDP. It means that the past values of CO2 emissions and real GDP can be used to estimate the future value of each other.

Table 10.

Toda-Yamamota granger causality test result.

Null Hypothesis:	Chi square Stat.	Prob.	Decision
LNCO2 ≠>LNRGDP	27.024	0.000*	Reject
LNRGDP ≠>LNCO2	12.045	0.002*	Reject
LNGFCF≠>LNRGDP	7.245	0.027**	Reject
LNRGDP≠>LNGFCF	0.935	0.627	Fail to Reject
LNNG ≠>LNRGDP	0.677	0.713	Fail to Reject
LNRGDP≠>LNNG	12.185	0.002*	Reject
LNTO ≠>LNRGDP	1.134	0.567	Fail to Reject
LNRGDP≠>LNTO	0.147	0.929	Fail to Reject

Note: The symbol “≠>” denotes “does not Granger cause.” Asterisk(s) *, **, *** represent(s) rejection of the null hypothesis at 1%, 5% and 10% significance level, respectively.

Also, there is Granger causality running from gross fixed capital formation to real GDP. This result shows that the past values of gross fixed capital formation are a good predictor of economic growth. Additionally, uni-direction Granger causality is found from real GDP to natural gas consumption and hence we can validate the conservative hypothesis for Japan. This outcome is in line with the study of Etokakpan et al.²

Conclusion and policy implications

Conclusion

Natural gas seems to have the least detrimental effect on the environment when compared to coal and oil because it has the lowest carbon intensity. The Japanese economic development has improved because of this discovery, however, very few studies have examined the natural gas-driven economy, especially in Japan. Inspired by the fact that natural gas is increasingly becoming an important fuel source in Japan ¹ and the 7th sustainable development goal, this study examined the long-run cointegration and causal impact of natural gas consumption in economic growth by incorporating trade openness, carbon dioxide emissions, and gross fixed capital formation in Japan. This study used data spanning from 1980 to 2020 and employed econometric techniques including the Johansen cointegration test, ARDL method, and Toda-Yamomato Granger causality test.

The empirical results indicated that a 1% increase in natural gas consumption reduces economic growth by 0.02% and 0.26% in the short- and long-run respectively, which indicates that natural gas consumption does not help in achieving Japanese economic well-being. Furthermore, a 1% increase in trade openness leads to a 0.03% in the short-run and a 0.33% in the long run, which indicates that in Japan, trade openness will increase economies of specialization, returns to scale, and poverty reduction. The study further found a short-run and short-run gross fixed capital formation-led growth of 0.29% and 0.35% respectively. Carbon dioxide emissions were also found to increase economic growth as a 1% increase in carbon dioxide emission leads to 0.13% and 1.22% in the short- and long-run respectively. This implies that environmental policies aimed at reducing carbon dioxide emissions will hurt Japan's economic growth, however structural policies directed at increasing the country's economic growth will improve the environment. The study also found that there is a unidirectional causality running from economic growth to trade openness, natural gas consumption to trade openness, and trade openness to gross fixed capital formation but a bidirectional causality between trade openness and carbon dioxide emissions.

Policy recommendation

The following policy recommendations are made based on empirical findings:

As shown in the Granger causality analysis, the growth induces natural gas consumption which means that other sources of energy such as coal are still being used in Japan International Energy Agency.²³ Therefore, a much more aggressive strategy in using alternative sources of energy would aid in keeping the country's economic momentum. From a policy standpoint, the study confirms that Japan is heavily dependent on non-renewable energy sources. Investments in and use of renewable energy sources (e.g. solar, geothermal, wind, etc.) could help to lessen the detrimental effects of the growing environment. The long-term growth of Japan will be aided by the development and implementation of efficient policies to regulate activities in the energy and industrial sectors in the country. Government-imposed CO₂ emission limits on manufacturing firms and industries will aid in lowering the nation's CO₂ emissions. Environmental degradation will be prevented by the prospective imposition of severe fines or high fees on those who violate this law. To encourage energy conservation, alternative (renewable) energy sources including oceanic, hydropower, and wind energy sources should be developed. The policies described above will help Japan sustain its strong economic growth and enhance environmental sustainability. Similarly, several academics have advocated for the introduction of technology, such as Clean Coal Technology (CCTs), in coal energy systems to lower GHG emissions and increase efficiency, which Japan's current plan relies heavily upon. Also, considering that one of Japan's largest coal-consuming sectors is the transport sector and also one of the nation's top export products (vehicles), it is imperative that to achieve green growth, reduce CO2 emissions, and sustain development, increasing research and development activities will be crucial in the development and deployment of new technologies for coal use.

To mitigate the effects of carbon emissions on the Japanese environment, the research reflects that even as energy is a major element of the production, and signifies the stimulation of economic growth, a malfunctioning energy system is associated with such a wrongheaded or dysfunctional national planning process, which could, in essence, be associated with risky economic growth and development. As a result, the research illustrates that the more rapid rate of economic growth in Japan, the more energy demand in form of natural gas, and as a result, the larger the carbon intensity. To create a balance whereby optimal energy use for long-term growth does not adversely impact the environment, this study recommends that Japanese energy regulators engage extensively in cleaner energy and innovations.

Results of the study also confirmed a positive relationship between trade openness and economic growth, which implies that the economic expansion of Japan is external. Income growth should be encouraged because it promotes trade openness. Therefore, the Japanese government needs to further reduce trade barriers by simplifying and reducing trade controls and procedures. Also, to expedite Japan's economic growth and increase trade openness, macro policies should be taken into consideration. The implementation of measures to increase exports, employment, exports, and domestic consumption—all of which support the expansion of economies—is necessary to accomplish this mission.

Trade openness causes carbon dioxide emissions; therefore, trade liberalization policies should encourage the transfer of eco-friendly technologies and innovation that will promote environmental conservation so that the country can achieve its ambition of carbon neutrality by 2050. To achieve the carbon neutrality goals, the trade structure will need to be modified. More specifically, tax incentives should be used by the government to discourage the trade of high-carbon goods and promote the trade of low-carbon products.

Trade openness also causes gross fixed capital formation; since GFCF is designed to improve economic growth and employment, therefore policymakers should increase investment promotions to trade openness and capital formation by promoting sustainable and inclusive innovation and industrialization. The role of gross fixed capital formation in economic growth is substantial to the Japanese economic well-being; therefore, policymakers are encouraged to aggrandize their efforts to increase human and physical capital accumulation in the country.

The study suggests that the Japanese government/policy makers must aim to develop economic reforms and policies that would improve the country's trade, especially exports ensuring the most appropriate energy mix to support the country's ongoing increase in energy consumption.

Limitation and future recommendations

Although this study significantly contributes to economic growth literature, especially in Japan and similar Asian countries, the study is not without limitations. The limitation is in the use of only Japan; therefore, future studies can use panel data to provide more understanding across different economies, considering classification based on national income levels. Considering that Japan is among the first five natural gas consumers and the highest carbon emitter, future studies can carry out a comparative study of the top and least natural gas consumers and carbon emitters. Also, other economic growth drivers such as population, taxes on trade, exchange rate, labor force, and technology advancement can be considered.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Gizem Uzuner

Taiwo Temitope Lasisi

Babatunde S Eweade is currently a PhD student at the Faculty of Business and Economics, Eastern Mediterranean University in (EMU), Turkish Republic of Northern Cyprus (TRNC). He obtained a bachelor's degree (Economics Education, Nigeria), and a Master's degree in (Energy Economics and Finance, North Cyprus). His research interests include energy and environmental economics, Health economics, Tourism economics, and econometrics. His research studies were submitted to top-tier journals such as energy economics and tourism economics.

Gizem Uzuner holds MSc in Economics and earned a PhD degree in Economics from Eastern Mediterranean University and served as a research assistant in the Department of Economics during her master and doctorate program. He is currently serves as an assistant professor at Istanbul Gelisim University in Turkey. Her research interests include economic growth, macroeconomic theory, macroeconomic policy, housing market, tourism and energy economics. Her works have appeared in top-tier journals including Sustainable Cities and Society, International Journal of Finance & Economics, Current Issues in Tourism, Environmental Science and Pollution Research, more recently International Review of Economics & Finance and Journal of Public Affairs, among others.

Ada Chigozie Akadiri currently serves as an Assistant professor at Cyprus West University, Turkish Republic of Northern Cyprus. Her research interests are in the areas of energy economics, environmental sustainability, economic growth, poverty and inequality, Development economics and labour economics. Her publications have appeared in top-tier journals including Energy Policy Journal, Science of the Total Environment, Environmental Science and Pollution Research, Current Issues in Tourism, International Journal of Finance & Economics, and Journal of Hospitality and Tourism Management to mention a few. She could further be contacted via this email: a.akadiri@cwu.edu.tr or ada.akadiri@emu.edu.tr.

Taiwo Temitope Lasisi holds a PhD in Tourism Management at Eastern Mediterranean University, and served as assistant in the Faculty of Tourism Eastern Mediterranean University, Turkey during her doctorate program. Her research interest includes organization behaviour, human resource management, creative working environment, environmental sustainability, economic modelling and policies. She is currently serving as post-doctoral researcher at Southern Federal University, Russia, and as a senior researcher at Dean's Office of the Faculty of Informatics and Management, University of Hradec Králové.

Appendix I

Toda Yamamoto (TY) Causality Testing (8)

\begin{aligned} InRGD P_{t} = & α_{0} + \sum_{i = 1}^{k} α_{1 i} InRGD P_{t - i} + \sum_{j = k + 1}^{dmax} α_{j} InRGD P_{t - j} + \sum_{i = 1}^{k} β_{1 i} InC O_{2, t - i} + \sum_{j = k + 1}^{dmax} β_{2 j} l n C O_{2, t - j} \\ + \sum_{i = 1}^{k} Υ_{1 i} InT O_{t - i} + \sum_{j = k + 1}^{dmax} γ_{2 j} InT O_{t - j} + \sum_{i = 1}^{k} δ_{1 i} InN G_{t - i} + \sum_{j = k + 1}^{dmax} δ_{2 j} InN G_{t - j} \\ + \sum_{i = 1}^{k} ϕ_{1 i} InGFC F_{t - i} + \sum_{j = k + 1}^{dmax} ϕ_{2 j} InGFC F_{t - j} + ε_{1 t} \end{aligned}

(9)

\begin{aligned} InN G_{t} = & δ_{0} + \sum_{i = 1}^{k} δ_{1 i} InN G_{t - i} + \sum_{j = k + 1}^{dmax} δ_{2 j} InN G_{t - j} + \sum_{i = 1}^{k} α_{1 i} InRGD P_{t - i +} \sum_{j = k + 1}^{dmax} α_{2 j} InRGD P_{t - j} \\ + \sum_{i = 1}^{k} β_{1 i} InC O_{2, t - i} + \sum_{j = k + 1}^{dmax} β_{2 j} InC O_{2, t - j} + \sum_{i = 1}^{k} γ_{1 i} InT O_{t - i +} \sum_{j = k + 1}^{dmax} γ_{2 j} InT O_{t - j} \\ + & \sum_{i = 1}^{k} ϕ_{1 i} InGFC F_{t - i} + \sum_{j = k + 1}^{dmax} ϕ_{2 j} InGFC F_{t - j} + ε_{2 t} \end{aligned}

(10)

\begin{aligned} InC O_{2, t} = & β_{0} + \sum_{i = 1}^{k} β_{1 i} InCO 2_{t - i} + \sum_{j = k + 1}^{dmax} β_{2 j} InC O_{2, t - j} + \sum_{i = 1}^{k} δ_{1 i} InRGD P_{t - i} + \sum_{j = k + 1}^{dmax} δ_{2 j} InRGD P_{t - j} \\ + \sum_{i = 1}^{k} γ_{1 i} InT O_{t - i +} \sum_{j = k + 1}^{dmax} γ_{2 j} InT O_{t - j} + \sum_{i = 1}^{k} α_{1 i} InN G_{t - i +} \sum_{j = k + 1}^{dmax} α_{2 j} InN G_{2 t - j} + \sum_{i = 1}^{k} ϕ_{1 i} \\ InGFC F_{t - i} + \sum_{j = k + 1}^{dmax} ϕ_{2 j} InGFC F_{2 t - j} + ε_{3 t} \end{aligned}

(11)

\begin{aligned} InT O_{t} = & γ_{0} + \sum_{i = 1}^{k} γ_{1 i} InT O_{t - i} + \sum_{j = k + 1}^{dmax} γ_{2 j} InT O_{t - j} + \sum_{i = 1}^{k} δ_{1 i} InRGD P_{t - i +} \sum_{j = k + 1}^{dmax} δ_{2 j} InRGD P_{t - j} \\ + \sum_{i = 1}^{k} α_{1 i} InN G_{t - i +} \sum_{j = k + 1}^{dmax} α_{2 j} InN G_{t - j} + \sum_{i = 1}^{k} ϕ_{1 i} InGFC F_{t - i} + \sum_{j = k + 1}^{dmax} ϕ_{2 j} InGFC F_{t - j} \\ + \sum_{i = 1}^{k} β_{1 i} InC O_{2, t - i} + \sum_{j = k + 1}^{dmax} β_{2 j} InC O_{2, t - j} + ε_{4 t} \end{aligned}

(12)

\begin{aligned} InGFCF = & ϕ_{0} + \sum_{i = 1}^{k} ϕ_{1 i} InGFC F_{t - i} + \sum_{j = k + 1}^{dmax} ϕ_{2 j} InGFC F_{t - j} + \sum_{i = 1}^{k} δ_{1 i} InRGD P_{t - i +} \sum_{j = k + 1}^{dmax} δ_{2 j} \\ InRGD P_{t - j} + \sum_{i = 1}^{k} α_{1 i} InN G_{t - i +} \sum_{j = k + 1}^{dmax} α_{2 j} InN G_{t - j} + \sum_{i = 1}^{k} β_{1 i} InC O_{2, t - i} + \sum_{j = k + 1}^{dmax} β_{2 j} InC O_{2, t - j} \\ + \sum_{i = 1}^{k} γ_{1 i} InT O_{t - i} + \sum_{j = k + 1}^{dmax} γ_{2 j} InT O_{t - j} + ε_{5 t} \end{aligned}

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