Toward a sustainable future:Examining the interconnectedness among Foreign Direct Investment (FDI),urbanization, trade openness, economic growth, and energy usage in Australia

Liton Chnr VOUMIK, M.Hsnur RAHMAN , M.Mznur RAHMAN,Mohmm RIDWAN, Slm AKTER, Asif RAIHAN

a Department of Economics, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh

b Department of Economics, Sheikh Fazilatunnesa Mujib University, Jamalpur, 2000, Bangladesh

c Department of Economics, Comilla University, Cumilla, 3506, Bangladesh

d Institute of Forestry and Environmental Sciences, University of Chittagong, Chittagong, 4331, Bangladesh

Keywords: : Renewable energy Foreign Direct Investment (FDI)Trade openness Urbanization Climate change Marshallian Demand Function

ABSTRACT: The energy demand in Australia is increasing with the industrialization and rapid economic growth.This study analyzed the relationships among the economic growth, Foreign Direct Investment (FDI), trade openness,urbanization, and energy usage in Australia based on the data from World Development Indicators (WDI) from 1972 to 2021.The results indicates that there is a cointegration among economic growth, FDI, trade openness,urbanization, and energy usage, which was traced through the autoregressivedistributed lag (ARDL).The Zivot-Andrews unit root test reveals that energy usage, economic growth, FDI, urbanization, and trade openness show significant structural breaks in 1993, 1996, 1982, 2008, and 1994, respectively.The ARDL model shows that economic growth has a positive and significant effect on energy usage in the long-run (0.814) and short-run (0.809).Moreover,the results also show that FDI (0.028) and trade openness (0.043) have positive impacts on energy usage in the long-run.However, urbanization shows a negative and significant influence on energy usage in the long-run (–0.965).Then, the research demonstrates a unidirectional causation between energy usage and trade openness, with energy usage significantly causing trade openness.The current study endorses energy consumption policies and investment strategies for a paradigm shifting from a reliance on fossil fuels as the primary energy source to renewable energy sources.These findings have profound implications for sustainable energy usage.

1.Introduction

The rapid expansion of the economy and population and the escalating usage of fossil fuels are the primary contributors to the general trend in developing counties that encourage economic growth (Rahman and Majumder,2022).Thus, nations and regions should increase efficiency and decrease CO2emissions throughout the energy usage,acquisition, and distribution channels.In addition, they should switch to renewable energy sources and implement low-carbon technologies to mitigate energy sector emissions and obtain economic growth, sustainable energy supplies, and ecological sustainability (Sohag et al., 2015).The formation of sustainable ecosystem poses an enormous challenge for developed counties in the current century.Using fossil fuels also makes this challenge highly critical (Pattak et al., 2023).The combustion of fossil fuels has a substantial contribution to the levels of greenhouse gas emissions in the atmosphere.Furthermore, renewable energy sources are valuable and significant in mitigating pollution and contributing to the attainment of ecological sustainability (Rahman et al., 2023).Australia has abundant,high-quality, and diversified energy sources, including nonrenewable and renewable energy sources.Hence,Australia’s economy relies on energy usage now and in the future.More than 80% of Australia’s overall energy usage is accounted by the power generation, transportation, and industrial sectors (Kar et al., 2023).The energy demand in Australia is increasing with the industrialization and rapid economic growth.In emerging countries, the main force behind economic growth and productivity improvement is energy (Rahman and Majumder, 2022; Majumder et al.,2023).Energy provides fuels for vital services, enterprises, and industries, allowing them to run smoothly and satisfy the requirements of the people (Addai et al., 2023).A steady and affordable energy supply is essential for the industry,transportation, agriculture, mining, and other industries (Rahman et al., 2021), which support innovation, economic growth, and job creation.Despite having many natural resources, Australia has a high energy requirement.Energy security must be ensured to meet domestic needs and lessen reliance on imported energy sources.A robust and secure energy system benefits from a broad energy structure that includes coal, natural gas, and renewable energy sources.The environment is strongly impacted by the production and consumption of energy, particularly in terms of greenhouse gas emissions and air pollution (Ghosh et al., 2023; Sultana et al., 2023).Australia must reduce its carbon emissions and switch to cleaner energy sources to slow the intensification of climate change.Australia can reduce emissions, protect ecosystems, and support international efforts to address climate change by promoting sustainable energy usage and switching to renewable energy.Energy access is essential for homes and businesses.Low energy costs decrease living expenses and increase economic competitiveness.Australia may aim to provide reliable and inexpensive energy for its people by supporting renewable energy, enhancing energy efficiency, and diversifying energy structure.Energy services that are dependable and reasonably priced improve the standard of living for people.Energy enables necessary processes, such as lighting, heating, cooling, and communication in homes, hospitals,schools, and other public facilities.For isolated and underprivileged communities, having access to energy is particularly crucial because it promotes economic growth and improves people’s living standards.The energy is a center for technical advancement.Innovations in energy storage, smart grids, electric vehicles, and renewable energy technologies present the potential for Australia to take the lead in manufacturing and research and development (R&D)(Rahman, 2023).Adopting renewable energy technologies can improve the development of new markets for exports and high-skilled employments.Australia must be proactive in combating climate change and advancing sustainable energy policies because it is a developed country and a significant energy producer.Australia can support global emission reduction goals by switching to low-carbon energy sources and encouraging other countries to do the same.

Use of natural resources drives gross domestic product (GDP) per capita growth of Australia, for instance,compressed natural gas, polished metal, crude oil, brown coal, black coal, and iron (Shahiduzzaman and Alom, 2014).In Australia, these natural resources are most significant export sources of revenue.Australia was the sixth largest energy producer in the world during 2021–2022, with net energy exports accounting for 81% of the total energy output.In Australia, 54% of energy is produced using coal.However, Australia was also a net importer of crude oil and petroleum-based products during 2020–2021, accounting for 36% of the total oil consumption (World Bank,2022).Australia imports energy from other countries and produces some of its own.Australia’s energy usage ranked the 19thglobally, and its GDP per capita ranked the 10thin 2021.Australia exports significant energy, including coal and gas, accounting for more than two-thirds of national production.During 2020–2021, approximately 90% of the energy produced from black coal was exported, along with approximately 75% of domestic natural gas output and 83% of crude oil production.Exports of compressed natural gas have decreased by 2% from 2020 to 2021 but increased by 15% annually on average over the last decade.Oil and refined petroleum products account for most of Australia’s energy imports.Almost two-thirds of the fuels used by domestic refineries come from abroad, and imports also satisfy 63% of the demand for refined fuels in Australia (ABS, 2022).Australia is fortunate to have various renewable and nonrenewable energy sources, such as wind energy and fossil fuels.The abundance of the country’s energy resources is a significant reason for its economic growth.The continuous growth of economy and population has led to an increase in energy usage in this country.Despite the growing significance of energy sources, energyrelated research is still insufficient in the Australia-specific literature.Hence, the factors impacting energy usage should be addressed and comprehended.Economic growth, Foreign Direct Investment (FDI), and trade openness impact domestic energy usage through several aspects, including cost advantage, compound impacts of production variables, and technology consequences (Shahbaz et al., 2014; Wan et al., 2015; Popescu et al., 2019).For example,increased export demand expands the size of economic activity, which raises domestic energy usage (Cole, 2006;Popescu et al., 2018).Australia’s solid resource base, high capital demand, and low population size help to reduce the disparity between the country’s savings and investments each year.Over the last several decades, Australia’s national investment and saving gap have generally been approximately 4% of the GDP (Department of Foreign and Trade Affairs, Australian Government, 2022).Typically, local savings and FDI operate together to finance the total investment.However, Australia has switched from a net borrower to a net lender abroad.At the end of 2021, net investment flow was 4.97×1011USD, with a national savings of 5.71×1011and 7.40×1010USD for FDI (ABS, 2022).With the expansion of foreign investment and trade, domestic energy demand is also increasing.Therefore, the linkage between FDI and energy usage in Australia should be determined.

This study evaluated the interaction among Australia’s economic growth, FDI, trade openness, urbanization and energy usage.The objectives of this study are to determine the effects of economic growth, FDI, trade openness,urbanization on energy usage in Australia and explore the causal linkages among these variables.In particular, the article contributed in the following ways.Firstly, the autoregressive-distributed lag (ARDL) model was utilized for the first time to evaluate the relationships among economic growth, FDI, trade openness, urbanization and energy usage.Secondly, we tested the robustness of the ARDL model by using fully modified ordinary least squares(FMOLS), dynamic ordinary least squares (DOLS), and canonical cointegrating regression (CCR), which are absent in the existing literature.Thirdly, this study discussed the feasibility of energy usage program based on fossil fuels in Australia.Finally, the research would help policy-makers in Australia and other nations or regions create a sustainable energy strategy that considers the intricate linkages among these variables.

2.Literature review

In this section, we evaluated the prevailing literature and identified the significance, uniqueness, and contribution of our research to the body of existing literature.However, in-depth analyses mainly focused on the linkage between energy usage and economic growth.For example, Leal et al.(2018) explored how CO2emissions, renewable energy sources, and fossil fuels influenced economic growth in Australia between 1965 and 2015, and implemented the ARDL model to monitor the link among these variables in the long-run and short-run.The results demonstrated that further economic growth would encourage additional spending on sustainable energy sources.With the growth of GDP, spending on fossil fuels, such as oil and coal, has decreased compared with renewable energy sources.Churchill and Ivanovski (2020) examined the linkage between economic growth and energy usage in seven Australian states between 1990 and 2015.They demonstrated that economic growth and energy usage are causally related.Similar research was conducted by Kahouli (2019) to observe the interaction between energy usage and economic growth in Organization for Economic Co-operation and Development (OECD) economies between 1990 and 2015, including Australia.In doing so, the study employed a generalized method of moment estimators to observe the relationship.The outcomes exhibited a causal linkage between economic growth and energy usage.The dynamic estimator implied that economic growth accelerates energy usage.Furthermore, using the nonlinear ARDL model, Munir and Riaz(2020) found that rapid economic growth leads to high energy usage in China, the USA, and Australia.Moreover,Gyimah et al.(2022) implemented the Granger causality test to scrutinize the connection between sustainable energy utilization and economic growth in Ghana from 1990 to 2015, and observed that renewable energy indirectly and directly influences Ghana’s economic growth.In addition, Voumik et al.(2022) investigated the environmental Kuznets curve (EKC) hypothesis for the European Union (EU) with renewable energy and nuclear energy.The study determined that the EKC hypothesis exists in the EU and renewable and nuclear energy contributes significantly to lowering environmental pollution.The study also covered how rapid economic growth in the EU gives governments great resources to spend on infrastructure, research, and development projects related to renewable energy.The EU nations have established several measures, including feed-in tariffs, tax incentives, and renewable energy objectives,to promote the adoption and growth of renewable energy sources.Economic growth enables governments to spend on renewable energy projects and encourages private investment.Additionally, Polcyn et al.(2023) used the crosssectional ARDL (CS-ARDL) model to explore how energy usage and environmental pollutants affect Asian life expectancy, and discovered that using renewable energy increases life expectancy and decreases environmental pollutions.The research covered how urbanization, growing living standards, trade openness, infrastructure development, and demographic considerations contribute to high energy usage in the Asian area.Industries need energy for production processes, whereas cities need energy for infrastructure and transportation.Consumption habits change as earnings growth, favoring products and services with the renewable energy.Transport is essential for international trade openness, and infrastructure inadequacies encourage investments in energy-intensive industries.Haldar and Sethi (2023) examined the potential for climate change mitigation and economic development in seven chosen rising Asian countries including China, India, Indonesia, South Korea, Malaysia, the Philippines, and Thailand from 2000 to 2018.According to the ARDL model and three stage least squares (3SLS) estimates, they discovered that using renewable energy is beneficial to economy and environment.By contrast, trade openness, insufficient innovation, and the use of nonrenewable energy sources have led to environmental deterioration in these economies.Moreover, Haldar et al.(2023) analyzed the influence of information and communication technologies (ICT),electricity consumption, and the use of renewable energy on economic growth in 16 emerging economies.The study discovered that ICT and innovation have a positive correlation with economic growth.The study also emphasized the use of renewable energy to attain sustainable economic development.Behera et al.(2023) looked at the role of green technology and renewable energy in reaching the goal of carbon neutrality for 18 rising nations between 1990 and 2018, and revealed that using green technologies and renewable energy can significantly reduce environmental pollution.

The linkage between FDI and energy usage is now a worldwide concern.Caetano et al.(2022) used the ARDL model to evaluate the role of FDI on energy transition and pollution in 15 OECD economies, including Australia,from 2005 to 2015.The findings revealed that FDI may increase pollution by elevating the overall energy usage.Accordingly, Amoako and Insaidoo (2021) explored the impacts of FDI on energy usage, utilizing data from 1981 to 2014 in Ghana.They used the Johansen multivariate test, FMOLS, and CCR to observe the long-run correlations among the variables, and revealed that a high inflow of FDI and rapid industrialization increase energy demand.Similarly, Zaharia et al.(2019) examined panel and bibliometric data to determine the elements that affect energy usage.Following the findings of this study, FDI and economic growth have a favorable link with energy usage.Moreover, Doytch and Narayan (2016) investigated whether FDI influences the use of sustainable and nonrenewable energy in 74 countries from 1985 to 2012.The study utilized a Blundell–Bond dynamic panel estimator to account for omitted variable biases and endogeneity, and observed that in lower-, low-, middle-, and high-income countries,the overall FDI enhances the development methods of green energy and reduces the use of nonrenewable energy.If these countries value the impact of energy usage on the environment, they will tend to use green or renewable energy.Voumik and Ridwan (2023) applied the Johansen cointegration test and the ARDL model to examine the influence of FDI, industrialization, and education on the environment in Argentina.The study found that FDI and industrialization are responsible for Argentina’s significant environmental degradation.The study also highlighted how FDI causes manufacturing factories to be built or expanded, which increases energy usage.Such factories depend extensively on energy-intensive procedures to operate their equipment and provide lighting, heating, and cooling.Hence, the FDI-fueled expansion of industrial activity raises the need for energy.The increased energy demand is mostly satisfied by nonrenewable energy, which consequently leads to the destruction of the environment.

The existing research has studied the dynamic relationship between trade openness and renewable and nonrenewable energy.In this context, Topcu and Payne (2018) explored the connection between trade openness and energy usage from 1990 to 2015 in OECD nations, including Australia.The findings observed the impact of trade openness on energy usage with an inverted U-shaped pattern relationship.Islam et al.(2013) explored the interaction among Australia’s energy use, trade openness, and economic progress, and showed a two-way causal relationship between energy usage and trade openness.According to Akbar et al.(2021), trade openness favors the use of nonrenewable and renewable energy.Similarly, Hdom and Fuinhas (2020) demonstrated a causal relationship between trade openness and energy usage in the case of Brazil and recommended using renewable energy owing to its efficiency in lowering CO2emissions.

In sum, the researches above indicate three gaps.Firstly, research on the effect of economic growth on energy usage in Australia is necessary.Secondly, no study in Australia simultaneously examines the relationship among energy usage, economic growth and FDI.Thirdly, a significant gap in the present research is the implementation of the ARDL, DOLS, and FMOLS models in studying the effects of independent variables on dependent variable by considering structural break analysis.

3.Methodology

3.1.Theoretical framework

The Marshallian Demand Function reveals the link among energy usage, economic growth, and energy costs in a country, which can be used to represent the energy demand function at timetgiven the equilibrium situation in the market for energy, where the energy demand is equal to the energy usage.

where ENERt,Yt, andPetstand for energy usage (kg/people), income (USD), and the cost of energy (USD) at timet,respectively.

Equation 2 expresses the effects of economic growth, FDI, trade openness, and urbanization on energy usage.

where GDP stands for economic growth (USD/people); FDI indicates Foreign Direct Investment (USD); TO means trade openness (%); and URBA indicates urbanization calculated by urban population (people).

The income elasticity of energy is positive, whereas price elasticity is negative, according to the conventional Marshallian Demand Function.However, as energy costs are subsidized in Australia, this research does not consider energy costs as independent determinants.Haldar and Sethi (2022) identified that innovation and trade openness are essential to promoting economic development by increasing productivity and ensuring energy efficiency.In this analysis, we controlled other factors to determine whether trade openness can contribute to reducing energy usage.

This study measured FDI as the net inflow of FDI (balance of payment current USD) following the study of Mohanty and Sethi (2022).Trade openness was also included in empirical model in this study.The effect of trade openness on energy usage could be either positive or negative.

However, the negative elasticity of trade openness to energy usage suggests that trade openness brings technology from highly technologically advanced nations into the local sector, which decreases energy usage (Haldar and Sethi,2022).From another aspect, the positive elasticity of trade openness to energy usage indicates an increase in energy usage related to trade openness.Numerous studies previously conducted have used the Stochastic Regression on population, affluence, and technology model to examine topics such as energy usage, FDI, trade openness, economic growth, and environmental quality (Sahoo and Sethi, 2021; Behera and Sethi, 2022; Dash et al., 2022; Esquivias et al., 2022).The Marshallian Demand Function was utilized in this research, which concentrated on some variables influencing Australia’s energy usage.

Equations 3 and 4 are the econometric formats of the equations mentioned above.

whereLmeans calculating logarithm;γ0is the intercept;γ1,γ2,γ3, andγ4indicate coefficients of variables; andεtis the error term.

3.2.Data description

Table 1 summarizes the description and sources of the data during the period of 1972–2021 in Australia that were collected from the World Development Indicators (WDI) dataset (World Bank, 2022).

Table 2 presents statistics for the variables utilized in this study.Moreover, summary statistics such as mean,standard deviation, maximum and minimum values show the strength of the dataset to determine the econometric model.

Table 1Description of selected variables.

Table 2Summary statistics of the selected variables.

3.3.Empirical framework and method of estimation

In this study, diagnostic tests included the ARDL model, structural break analysis, causality test, and unit root tests.Preventing the possibility of misleading regression requires the use of unit root tests.Thus, the data are stationary before using stationary methods to assess the regression model.Empirical evidence suggests that the integration technique should be prepared before examining the issue of cointegration.Numerous studies have advised conducting multiple stationarity tests because the efficiency of these tests varies based on the sample size when determining the sequence integration classification.This study employed Im, Pesaran and Shin (IPS) (Im et al., 2003), Phillips–Perron(PP) (Phillips and Perron, 1988), and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) unit root tests (Kwiatkowski et al., 1992) to check stationarity.However, the stationarity assumption is the basis for applying time series forecasting and analysis, which assumes that the mean, variance, and trend remain constant over time.If at least one of those factors changed at some time, or if the break period occurred during the sample period, then a structural break is assumed to happen.A structural break in econometrics is an unanticipated change in the time series data.This case can result in significant forecasting errors and conceptual model instability.This study employed the Zivot-Andrews unit root test to observe the structural break, and also utilized the ARDL model established by Pesaran et al.(2001),as an efficient estimating tool to reveal the long-run and short-run interactions among the variables.Compared with earlier cointegration approaches, this technique provides several benefits.However, unlike earlier cointegration processes that require analyzing a series of integration properties before use, this model does not need any such preparatory testing.The ARDL model can be used to study endogeneity by considering the lag duration of variables.In addition, this model is helpful in any case involving the integration of investigative series.Finally, despite limited observations, the ARDL model retains its validity.The ARDL model may be developed by utilizing the econometric technique provided in Equations 3 and 4.After establishing the long-run linkage between the variables, the short-run relationship needs to be retrieved.We thus evaluated the error correction model and determined the short-run and long-run linkages between the variables, as shown in Equations 5 and 6, respectively.

wherewrepresents the series’ lag length; Δ means the first difference operator;α0is the intercept;α1,α2,α3,α4, andα5indicate coefficients of variables;imeans the individual lag order; ECT means error correction term; andθis the coefficient of ECT.

We also used FMOLS, DOLS, and CCR to examine how various variables throughout time impact energy usage and to assess the model’s robustness.Two key considerations drove the requirement to use these techniques.Before using FMOLS, DOLS, or CCR, the cointegration requirement for the I(1) (the first-differencing) parameters must been met.These techniques also addressed serial correlation biases and endogeneity resulting from the cointegration interaction.Therefore, results with asymptotic efficiency were produced (Rahman and Majumder, 2022).

However, the pairwise Granger causality test assesses he combined values of past and present of independent variable (X) and dependent variable (Y).The same is true for the causal relationship ofYandX; if the results diverge from zero, then causation exists on both sides (Rahman and Majumder, 2022).The study utilized the pairwise Granger causality test to explore whether the variables have a causal relationship.The following equations show the causal relationship betweenXtandYt.

whereδ0is the intercept;γz,λz,δz, andψzare the coefficients of variables;kis the total number of timet;zindicates specific time; andμtis the residual term.

Finally, this study employed several diagnostic tests to ensure the validity of the findings.The study also used the Breush–Pagan–Godfrey test for detecting heteroscedasticity, the Durbin Watson test for autocorrelation, the Ramsey Reset test for specification error, the Jarque-Bera test for normality, and the cumulative sum test (CUSUM) and the cumulative sum test square (CUSUMsq) test for finding out the stability of the predicted model.

4.Results and discussion

Table 3 displays the outcomes of the IPS, PP, and KPSS unit root tests and provides the validity of using the ARDL model.The findings of the stationarity test show that variables have a mixed order of integration, making the ARDL model preferable to conventional cointegration approaches.Three unit root test results indicate that energy usage,FDI, economic growth, and trade openness are stationary at the first-difference I(1), and urbanization is stationary at the level I(0) (Table 3).The results also exhibit that energy usage, economic growth, FDI, urbanization, and trade openness showed significant structural breaks in 1993, 1996, 1982, 2008, and 1994, respectively (Table 4).

Table 3Results of Im, Pesaran and Shin (IPS), Phillips–Perron (PP), and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) unit root tests.

Table 4Identifications of structural breaks by using the Zivot-Andrews unit root test.

From Table 5 we can see that no cointegration exists among the variables assumed as the null hypothesis, which is rejected at the 1% significance level.The variables in the ARDL model have specific cointegration linkages.The long-run driving variables in this study are economic growth, FDI, trade openness, and urbanization.These variables move first if a shared stochastic shock is introduced to the system.From the previous observation, changes in these variables are followed by variations in energy usage.The ARDL model was adopted to examine the long-run effects of economic growth, FDI, trade openness, and urbanization on energy usage in Australia after establishing cointegration among the variables.Table 6 shows that long-run coefficient of economic growth is significant at the 5% level, with a positive sign when all other variables are held constant, indicating that economic growth will result in an increase in energy usage.As economic growth accelerates, further energy usage is necessary.People still consume energy in their everyday lives, and fortunately, many people will have access to advanced appliances in the future.With the expansion of economies and the operation of businesses, energy will always be needed (Rahman and Majumder, 2022).The positive relationship between economic growth and energy usage is supported by several studies, such as Ajisafe et al.(2006), Pan et al.(2019), and Novak et al.(2022).

Table 5Cointegration test results of the autoregressive-distributed lag (ARDL) model.

Additionally, the long-run coefficient of urbanization is significant at the 1% level with a negative value, indicating that increasing urbanization reduces energy usage in the long-run.Thus, urbanization has a negative and statistically meaningful long-run effect on energy usage, and the findings are similar to the researches of Johnson and Nica (2021)and Nica (2021).Urbanization makes producing commodities in large quantities easier, thereby reducing energy usage.However, urbanization also needs perfect infrastructures to move people, food, and products into and out of cities, which increases energy usage.Urbanization presents a means of enhancing sustainable development for economic growth.The inverse relationship between urbanization and energy usage is in line with several studies(Rana, 2011; Sadorsky, 2014; Popescu et al., 2016; Nica et al., 2020; Novak et al., 2022; Warsame, 2022).In addition,the results presented in Table 6 demonstrate that FDI (0.028) has a positive but insignificant impact on energy usage in Australia and trade openness (0.043) has a positive and significant (at the 1% level) impact on energy usage in Australia.Economic growth significantly impacts energy usage in Australia in the short-run.These findings are supported by Rahman and Majumder (2022) for Next-11 countries, Nica et al.(2023) for South Asian Association For Regional Cooperation (SAARC) countries, Popescu et al.(2014) for Eastern Europe, Nahrin et al.(2023) for Mexico, Colombia, and Venezuela (G-3 countries), and Voumik et al.(2023) for the top 10 tourist countries.Additionally, the results show that FDI and urbanization have a negative and insignificant impact on energy usage in the short-run.Furthermore, the short-run result of the ARDL model shows that trade openness has a positive but insignificant relationship with energy usage in Australia.

Checking the reliability and validity of the ARDL model is essential.Hence, this research applied FMOLS, DOLS,and CCR to check the validity of the ARDL model.The results show that economic growth has a significant positive association with energy usage (Table 7).Thus, the findings of FMOLS, DOLS, and CCR are consistent with the estimation results of the ARDL model.Additionally, the DOLS estimation results reveal that urbanization has a significant and negative effect on energy usage, and these findings support the calculation result of the ARDL model.Therefore, economic growth raises energy usage, whereas increasing urbanization lowers energy usage in Australia.Finally, the pairwise Granger causality test demonstrates a unidirectional causation between energy usage and trade openness, with energy usage significantly causing trade openness (Table 8).Similarly, urbanization increases energy usage.No other causal relationship exist among the variables in this analysis apart from these two.However, the final concern is the goodness of fit of error correction in the ARDL model.Several stability and diagnostic tests were conducted to test the validity of the ARDL model.Heteroscedasticity, homoscedasticity, serial correlation, and model specifications were all examined by diagnostic tests.According to the findings in Table 9, there were no heteroscedasticity, specification error, or autocorrelation in the ARDL model.Hence, the findings of this investigation can be used to draw reliable conclusions.The model is found to be stable at the 5% significance level according to the results of the CUSUM and CUSUMsq stability tests.

Table 7Robustness check results of fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS),and canonical cointegrating regression (CCR).

Table 8Estimations of pairwise Granger causality test results.

Table 9Diagnostic for the ARDL model adequacy.

A country needs a smooth energy supply to maintain sustainable economic growth.Increasing GDP motivates citizens to buy large houses and new products, travel, and consume.Moreover, rising GDP is directly related to largescale consumption and production.Continuous energy supply is the main driver of production.According to Rahman et al.(2021), energy usage promotes economic growth and industrialization.In Australia, vast new projects are created, and large-scale construction is conducted everywhere.All economic activities require enormous amounts of energy.In addition, FDI also increases energy usage, although the impact is insignificant.When FDI enters a country,new industries and large jobs are created.This result is similar to the investigations of Majumder et al.(2022) and Rahman (2023).FDI also creates new superstructures and large construction projects in a country.Moreover, the findings show that urbanization is inversely related to energy usage, although traditional research Majumder and Rahman (2023) has noted that urbanization positively impacts energy usage.In urban areas, many people live in very congested areas.The per capita electricity demand of the urban population has decreased.Moreover, trade openness is positively related to energy usage and is vital for Australia (a very trade-dominant country).

5.Conclusions

This study analyzed the impacts of economic growth, FDI, trade openness, and urbanization on energy usage in Australia using data from 1972 to 2021.This research employed methods such as IPS, PP, and KPSS unit root tests to find out the stationary feature within the dataset.The findings of those tests demonstrate that variables show mixedorder integration.The findings of Zivot–Andrewes unit root test shows significant structural breaks within the sample period.The investigation employed FMOLS, DOLS, and CCR estimators in addition to the ARDL model to ensure the reliability of the findings.According to long-run estimation results of the ARDL model, economic growth leads to the increasing of energy usage but urbanization lowers energy usage in the long-run.FMOLS, DOLS, and CCR estimation results also validate these outcomes.Other variables used in this study, such as trade openness and FDI,have an impact on energy usage in Australia in the long-run.The overall findings show that Australia will need additional energy supply in the future.The expanding GDP, increasing FDI size, and large trade volumes push energy usage in Australia.The primary purpose of this research is not to mitigate energy usage but to determine which factors are most responsible for energy usage and then suggest several energy sources and recommend optimal energy usage.Energy is the main wheel of any economy.Therefore, minimizing energy usage is not the solution but finding alternative energy sources and optimizing current energy usage.Economic growth, FDI, urbanization, and trade openness are the four giant pillars of the Australian economy.Among these four factors, three (economic growth,FDI, and trade openness) are directly related to increased energy usage.

6.Policy recommendations and limitations

Australia will need abundant energy supplies in the future.Increasing GDP size, trade openness, and FDI indicate that energy usage will be skyrocketing in Australia.Australia should further invest in renewable energy because there are considerable solar, wind, and geothermal energy resources.Private investors should be encouraged to invest in renewable energy projects by providing incentives, including tax rebates, grants, and low-interest loans.This study will help reduce greenhouse gas emissions, decrease reliance on fossil fuels, accelerate the transition to clean energy,implement stringent renewable energy objectives, and establish goals for renewable energy production.Clear rules and laws that encourage the development of renewable energy technology and infrastructure should go along with these aims.Energy efficiency should be encouraged and supported across all sectors, including residential,commercial, and industrial sectors.Energy-saving behaviors must be encouraged by providing financial incentives and instructional initiatives, such as installing energy-efficient equipment, enhancing insulation, and implementing energy management systems.Australia should increase the use of electric vehicles and public transportation and invest in the infrastructure of public transportation to encourage the adoption of electric cars and lessen the dependency on private vehicles.Incentives for buying electric vehicles, such as tax breaks and the creation of charging infrastructure, should be offered to hasten their adoption and cut down on emissions from the transportation industry.However, fundings for R&D of renewable energy technologies should be enhanced.Moreover, academic institutions,research facilities and private companies should be supported because they can create cutting-edge technology,including improved solar panels, smart grids, and energy storage systems.Therefore, technology will develop and new business prospects will appear.Companies can be persuaded to adopt the concepts of the circular economy by lowering waste, reusing products, and recycling materials.Businesses should be supported in developing environmentally friendly manufacturing techniques and opening up markets for recycled materials.Moreover, they should also invest in the training of a workforce with the necessary skills for the green economy and offer educational opportunities and training programs with focuses on green jobs, clean technologies, and sustainable energy.Hence,prospects for employment and a smooth transition to a sustainable economy will increase.A carbon pricing scheme should be implemented, such as a carbon tax or a cap-and-trade program, to reward firms for investing in clean technology and reducing emissions.The money made from these methods can be invested in renewable energy initiatives or used to help transitionally vulnerable populations.Other nations, groups, and professionals should work together to exchange information, ideas, and the best methods to promote sustainable energy usage and economic development.They should also take part in global projects and accords, such as the Paris Agreement, to combat climate change and work towards a sustainable future.The people should know the significance of sustainable energy and its advantages for markets, environment, and public health.Australia should also launch educational campaigns and work with the media to advance sustainable practices and increase public involvement.Moreover, Australia needs to develop new energy sources.Energy sources derived from fossil fuels are not sustainable or friendly for the environment.The solution to sustainable development and environmental security is renewable energy.Australia needs to look into alternative energy sources.Australia has numerous energy sources and is a very warm and sunny place.Thus, gathering solar energy is simple, including setting up solar panels in deserts and empty spaces.Nuclear energy has recently emerged as a complete alternative to renewable energy.Australia is a sizable nation with a very low population density and a sizable quantity of uninhabited terrain.Australia may then concentrate on nuclear energy and can significantly advance sustainable energy and economic growth while supporting international efforts to mitigate climate change by putting these proposals into practice.

Future studies may bring environmental effects and sustainability into their studies in light of rising public awareness of these issues.Understanding how the connections among economic growth, FDI, urbanization, trade openness, and energy usage vary depending on locations would benefit from cross-national or regional studies.Future research may investigate the short-run and long-run dynamics and isolate any lagging effects or feedback processes between the variables by performing dynamic analysis.

Authorship contribution statement

Liton Chandra VOUMIK: conceptualization, formal analysis, and writing - review & editing; Md.Hasanur RAHMAN: methodology and writing - review & editing; Mohammad RIDWAN and Salma AKTER: writing -original draft; and Maznur RAHMAN and Asif RAIHAN: writing - review & editing and writing - original draft.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.