Trends of Carbon Emissions and Foreign Direct Investment: Accounting for Ecological Footprints, Renewable Energy, Globalization and Technological Innovations in BRICS

doi:10.21203/rs.3.rs-2951731/v1

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Trends of Carbon Emissions and Foreign Direct Investment: Accounting for Ecological Footprints, Renewable Energy, Globalization and Technological Innovations in BRICS

https://doi.org/10.21203/rs.3.rs-2951731/v1

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published 22 Dec, 2023

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This paper explores the relationship between carbon emission (CE) and foreign direct investment (FDI) keeping the ecological footprint, renewable energy, globalization, and technological innovations as exogenous variables. We employ the system of equations in the form of simultaneous equations for the panel of BRICS countries to fully capture the proposed association. This study highlights the importance of ecological footprints for the determination of CE and FDI along with some exogenous and instrument variables. Our empirical findings of explaining CE assert that FDI, technological innovations, and renewable energy significantly help to curtail carbon emissions in selected countries. However, the ecological footprints are causing CE positively which yields an alarming situation in two ways, firstly a high of rate environmental degradation, and secondly the pressure of humans on land is increasing and that is causing to increase in the EF in BRICS. The equation of FDI is presenting the curtailing impact of CE and RER whereas globalization is increasing the investment rate in BRICS. Mineral mining should be controlled and regulated since it has the potential to have a number of negative effects, including soil pollution, acid mine drainage, erosion, biodiversity loss, considerable water resource usage, and problems with wastewater disposal. Nonetheless, recycling mining waste, employing environmentally friendly equipment, stopping illegal mining, and enhancing mining sustainability may all help to lessen the effects of mining on the environment.

Carbon Emissions

Foreign Direct Investment

Ecological Footprint

Renewable Energy

Globalization

Technological Innovations

The global economy has been witnessing exponential growth and progress in the past two decades. The developing nation’s role has been extremely crucial in accomplishing a shared global economic goal. The different economies of the world are now facing the liberalized flow of financial funds and investments frequently. However, foreign direct investment (FDI) and market capitalization effectiveness differ from one country to another. A sufficient amount of literature is available regarding the financial development’s role in growth optimization returns from FDI in countries receiving FDI. The smooth flow of capital depends on the efficiency of the financial system. Therefore, the focus should not only be on enhancing net capital inflows but also rather on developing financial systems simultaneously. The evidence of the crucial role of financial development in economic development is present in both theoretical and empirical research (Hanif et al. 2019). However, it was the innovative research work of McKinnon (1973) and Shaw (1973) which started the debate about the interrelation between growth and institutions of financial development. It is after this research that this topic gained academic attention among research scholars. It was until the 1990s that the correlation shared between growth and financial development was not very clear since it is mainly dependent on financial liberalization policies. Therefore, it can be harmful to the process of economic development in some cases. Nonetheless, a very positive picture has been shown by research studies that are based on the role economic growth plays in the nexus between FDI and financial development (Wang et al. 2021; Usman & Hammar, 2021).

Therefore, the growth of the country which is related to FDI is not only dependent on the investment’s volume. A massive threat was posed to economic development due to 2008’s financial crisis. The aftermath of the crisis is still being faced by many economies all around the world, both developing and developed. It is imperative to understand the financial system’s role so that the risk can be minimized, and capital can be exploited efficiently. Although many different studies are available that address the spill-over effect of FDI however, the role of FDI in the correlation between growth and economic independence is difficult to find. Therefore, it is considered important to explore the growth-financial development nexus and FDI and capitalization’s role (Wang et al. 2021).

A very crucial role is played by FDI and capital formation in enhancing infrastructure, technology, and industrial progress. However, it has been highlighted by various researchers that financial development of the advanced stage is needed for optimizing the growth which is resulting from FDI. Moreover, the interrelation between financial and economic growth is dependent upon efficiency (Hanif et al. 2019).

It is therefore essential to understand the complex relationship among environmental quality, inward FDI, and economic development which should be the base for developing economically viable policies. It has been observed through literature research that the causal relation existing between environmental quality, inward FDI, and fiscal stability has crucial policy implications which are essentially based on four factors as discussed here (Shao, 2018). Firstly, if there is a bidirectional relation between inward FDI, environmental degradation, and economic growth then inward FDI will be a source of promoting economic stability in the host country. This signifies that FDI will help in increasing the funds of a financial system. Consequently, these funds enable the financial markets to develop which also translates into the promotion of economic development. Subsequently, this results in attracting more FDI thereby acting as a vicious cycle. Secondly, economic growth and CO2 emissions’ bidirectional correlation signifies that more CO2 levels will negatively affect economic development and vice versa. Therefore, as countries start developing, the level of environmental degradation also increases however, environmental degradation tends to minimize if a specific level of income is attained, in accordance with the Environmental Kuznets Curve (EKC) theory (Abdouli & Hammami, 2020).

Thirdly, the existing interrelation amongst FDI and CO2 emissions signifies that the most vital cause of environmental degradation in the host country is FDI, consequently as CO2 emissions increase it encourages inflows of inward FDI. Lastly, when considering the interrelation between economic growth and carbon footprint, it is observed that more financing is provided by the financial sector at cheaper rates which are also imperative when considering an investment for projects related to the environment. On the contrary, as finical development increases, so does the emissions of CO2. This signifies that prosperous and well-organized financial mediation seems to be more favourable in assisting the expansion of economic output which also means more consumption of energy and buying bigger emission-intensive products such as automobiles, refrigerators, washing machines (Cicea et al. 2020).

Additionally, FDI can play the role of economic growth’s decisive factor at both the macro and micro-economic arena in some countries (Cicea et al., 2019). Generally, there are two ways for measuring economic progress i.e., Gross Domestic Product (GDP) and the quality of life. In 1990 the major source of financial inflows in the developing economies was FDI. The major attributes of FDI are that it has a lesser degree of volatility and behavioral wise it is irregular pro-cyclical. When observed globally, the inflows of FDI have generally increased over time since the 1980s and 1990s and are contributing significantly to the economic development of low-income nations (Simionescu & Naros, 2019). The correlation shared by industrial development, economic growth and environmental sustainability has been studied by many environmentalists, economists and corporate researchers.

2.1 Globalization and environmental footprint

Increased industrial growth and globalization have instigated a debate regarding its pragmatic and negative impacts on environmental quality and CO2 emissions. Previously published studies available on this topic have classified the impact of globalization on the environment in three major classes i.e., scale, composition, and technique impact. Scale effect refers to the concept that globalization promotes increased financial growth, industrial production, and resource consumption. All these processes require high energy usage leading to an increase in the global carbon burden. In this way, the scale effect defines the impact of globalization on environmental pollution (Destek & Sarkodie 2019; Tanveer et al., 2022). According to the consumption impact, the state of industrial development and its dimensions in any country determines the magnitude and degree of impact globalization will likely cast on eco-sustainability (Zaidi et al., 2019; Tanveer et al., 2023). However, typically with the increase in globalization, industrial sectors associated with a limited carbon footprint undergo expansion such as the service industry while those sectors that possess a high CO2 burden begin to contract. In this way, the net carbon footprint of the country reduces thus implying no harmful impact of globalization on environmental performance and vice versa. The third impact mechanism is the technique effect that presents different ways by which globalization affects the levels of CO2 emissions by the commercial, residential and industrial sectors and their influence on ecological degradation. These ways pose diverse impacts on the nature of environmental performance, impact mitigation, and globalization-driven technology modernization or sustainable technology exchange (Lin et al., 2016).

In this regard, the research by Wang et al., (2019) is significant in this reference which argues that global development positively impacts sustainable technology innovation thus reducing the extent of ecological damage. Various other researchers have explored the influence of globalization and industrial development on pollution and have presented contrasting results. For example, in recent research by Saud et al., (2020), the financial development’s role in promoting a sustainable environment in terms of ecological footprint has been researched. The results revealed that globalization reduces adverse environmental impacts considering the case of “One Belt One Road” (OBOR). In addition, the study reported that with the increase in globalization the development and transfer of sustainable technologies is fostered which not only promotes economic development in a country but also results in a significant reduction in the overall carbon footprint of that country (Hussain et al., 2022; Khalid et al., 2021). Consequently, this scenario supports the technique impact of globalization. Similarly, another recent research on the “Generalized Method of Moments” approach, scrutinized the correlation shared by energy usage, globalization, and environmental countries in 97 countries (Yang et al., 2020). According to the results, environmental sustainability is positively impacted by the increase in globalization. The findings have been found to be in accordance with the famous ecological modernization model. Ibrahiem & Hanafy (2020) also focused on investigating the complex nexus between globalization and the selected economic and environmental indicators. These included the per capita income, energy demand, and eco-sustainability in Egypt over a period of more than 40 years from 1971–2014. According to the findings, as energy consumption increases, a rise in CO2 emissions is observed whereas globalization results in decreased carbon emissions. In view of the results of the study by Ulucak et al., (2020), a similar correlation exists between globalization and ecological sustainability in nations undergoing economic development.

On contrary, there is ample literature present highlighting the negative impacts of globalization on environmental protection and providing a relevant evidence base for supporting this narrative. Yilanci & Gorus (2020) recently examined globalization and industrial development’s influence on environmental protection in the Middle Eastern and North African countries. The authors collected data from a set of 14 MENA countries from 1981–2016. The results reported that globalization is associated with undermining environmental performance via scale impacts. Similarly, Usman et al., (2020) evaluated the correlation between sustainable power resources, globalization, and ecological footprint and presented that environmental footprint is reduced with the increase in renewable energy utilization. However, environmental pollution is increased with the accelerating globalization rates. This has been attributed to the increased consumption of fossil resources. The study has provided strong evidence in support of the scale effect. In another research, Suki et al., (2020) studied the correlation of globalization and environmental quality in different Malaysian cities over the period of 1970–2018. The results reported a significant positive correlation is found between globalization and environmental degradation. The reason is the reliance of most industrial sectors on conventional pollution-intensive fossil-driven energy resources like natural gas, petroleum, oil, and coal in Malaysia. Le & Ozturk (2020) also presented similar findings and reported that globalization leads to undermined ecological sustainability. The reason for the positive nexus between globalization and CO2 emissions has been explained by the authors in terms of trade openness and poorly formulated and executed environmental laws.

Ansari et al., (2020) studied the correlation between economic progress, energy demand, and globalization on environmental pollution in terms of the EKC model in gulf countries including UAE from 1991–2017. The findings reported that increased energy usage and a high rate of globalization negatively impact environmental quality in the selected countries. The results implied that the EKC hypothesis fails to hold its validity for GCC countries. In the light of all these studies, it can be inferred that there are contrasting opinions in regard to globalization’s impact on the quality of the environment and reaching a consensus is not possible.

2.2 Economic development and environmental pollution

When considering the financial growth and environmental quality nexus, a similar trend is observed where there are two groups of researchers, one in support of the positive nexus while others supporting the negative nexus. According to the group of researchers advocating the influence of increased financial stability in minimizing environmental emissions, economic growth helps in channeling investments in the renewable energy sector. In addition, when a country achieves financial security, it can allocate funds to green businesses, provide subsidies for cleaner production and facilitate the transfer of sustainable business practices and technologies (Kirikkaleli & Adebayo, 2021). On the other hand, there is a great deal of literature reporting the role of economic growth in increasing CO2 emissions and associated ecological deterioration. This is defined in terms of the provision of adequate financial and technological resources at an economical cost for expanding previously established industrial enterprises and fostering the development of new ones. More industries mean more environmental pollution and resource consumption. Similarly, high per capita income equips the population to invest in modern electronic equipment or vehicles which in most cases are energy-intensive goods (Cheng et al., 2021). Therefore, economic stability is often associated with a higher carbon footprint as it increases the energy demand consequently leading towards environmental deterioration.

The extent and direction of the correlation between financial progressiveness and CO2 emissions also depend significantly upon the political, industrial, and regulatory systems of the country (Charfeddine & Kahia 2019). This can be explained in the light of various studies such as Bayar et al., (2020) which employed a regression estimator for observing the economic growth and pollution index correlation. The correlation was observed in 11 countries of the European regions which are currently in the post-transition phase. According to the findings, financial stability is associated with massive energy utilization and increased CO2 pollution confirming a negative correlation between sustainability and economic growth. Similar conclusions have been drawn by Hussain et al., (2020) while examining the contribution of economic prosperity and the high rate of globalization on environmental quality. The environmental quality indicator selected by the study was CO2 emissions. The results reported a positive interrelation between economic growth and carbon footprint. A similar trend was seen between globalization and the selected environmental indicator. This implies that the growing economy is not yielding potential opportunities to shift towards sustainable energy generation and pollution control in the countries under study. Godil et al., (2020) also explored that causality shared by economic stability and eco-footprint in Turkish states over the span of more than 30 years (1986–2018). It has been found that economic development, globalization, and development in the tourism sector negatively impact the environmental quality of the country.

On contrary, in a recent study Lahiani (2020) reported an eco-friendly role of economic stability in the country. The study focused on testing the role of financial growth on the quality of the environment in China and reported that the availability of excess economic resources fosters the provision of funds for carrying out projects for environmental protection. Similarly, the investments in green industries also increase which not only augment the productivity of the country but also minimizes the power usage. According to Saidi & Mbarek (2017), GDP growth and a rise in population income lead to higher environmental pollution. However, the introduction of green economic reforms can invert this correlation. Dogan & Seker (2016) investigated the nexus between financial growth and ecological wellbeing from 1985–2011. The findings presented that an increase in economic prosperity leads to comprised environmental quality when viewed in the long term. Whereas Zaidi et al., (2019), reports that there is an inverse interrelation between economic stability and carbon footprint. This implies the existence of favorable opportunities for development in the eco-sustainability sector by investing in green technologies due to better availability of financial resources. These findings are in accordance with the research of Zafar et al., (2019) when considering the case of OECD nations. Thus, it can be inferred that the literature presented a mix of positive and negative views related to financial development’s impact on the environment.

2.3 Overview of the Ecological Footprints of the BRICS countries.

The BRICS cluster is including Brazil, Russia, India, China and South Africa. The BRICS initiative is a continuation of a legacy that was solidly established in April 1955, when nations from Asia and Africa gathered at the historic Bandung Conference to flex their collective muscles during the Cold War and make their presence felt in the global order. Russia was the organization's founder. They convened the first BRICS Ministerial Conference on September 20, 2006. During a UN General Assembly session in New York, Vladimir Putin, the president of Russia, requested this gathering. They were all eager to increase their level of international collaboration. The purpose of the study is also to have a look on the ecological footprint of each nation that is an encouraging element of international collaboration. This section of the study is based on the EF with all its sub-sections. As per the Global Footprint Network, the EF is based on the summation of the Built-up Land, Carbon Cropland, Fishing Grounds, Forest Products and Grazing Land of each country.

The Fig. 1 and table are presenting the story of EF in all countries of panel. The numbers are telling the interesting story about the breakdown. EF is a measurement of the amount of biologically productive land and water needed by a person, population, or activity, while employing current technology and resource management techniques, to produce all the resources they need and to absorb the waste they make. Global hectares are often used to calculate the ecological footprint. Trade is international, therefore a person's or a nation's Footprint includes land and water from all around the globe. The term "Ecological Footprint" without additional qualification often refers to the ecological impact of consumption. Footprint is a common abbreviation for ecological footprint. Ecological footprint is calculated using a complex set of calculations and models that take into account a wide range of factors. For Brazil the total EF is 2.721, Russia it is 5.199, China has EF of 3.054, India among the top ten most polluted countries of the world is having 1.040 that is lower of the panel and south Africa has 3.763. Despite among the most polluted countries of world, India has EF minimum and it is indicating that it has abundant natural resources to bear the pressure of human on its land. Brazil has rich mining natural resources like tin, iron and phosphate in addition to large deposits of diamonds, chromium, copper and many other. Due to heavy mining in Brazil the EF is relatively higher than India. Russia has world largest gas resources, oil and coal reserves. Due to larger export of these resources the highest EF is of Russia among the panel. China is top producer of aluminium, magnesium, talc, cement, coal, gold, graphite, iron, steel, antimony and many more such products. South Africa also having variety of minerals.

Cropland, which includes areas used to cultivate food and fiber for human consumption, feed for animals, oil crops, and rubber, is the most bio productive land-use category. The degree to which farming methods or unsustainable agricultural practices may impact long-term soil deterioration is not yet taken into consideration in current cropland Footprint estimations because to a lack of internationally uniform data sets. Crop products utilized for fiber and material production as well as those used as feed for livestock and aquaculture are all included in the farmland footprint. When the values of cropland are viewed, the percentage of cropland is less than a quarter with second maximum percentage of 23% for Brazil and India has maximum value of 31%. South Africa has lowest for the category of cropland that is only 9%.

Grazing land: Livestock is raised on grazing land to provide meat, dairy, hide, and wool. The quantity of livestock feed available in a nation is compared to the amount of feed needed for all animals during that year, with the remaining feed demand assumed to come from grazing land. This comparison yields the grazing land Footprint. Table 1 reporting the maximum value for the Brazil that is 27% and remaining countries have values in the range of 1–4%.

Two services are provided by forest land: The quantity of timber, pulp, timber products, and fuel wood used by a nation annually is used to determine the forest product Footprint. This component is covering also lower rate of percentage with 19% maximum share for Brazil followed by Russia and India with 12%. The Carbon Footprint, which reflects the carbon dioxide emissions from using fossil fuels, is also taken into account. Embodied carbon in imported items is also taken into account by the carbon footprint. The area required to trap these carbon emissions serves as a metaphor for it. The quantity of forest area required to absorb these carbon dioxide emissions is used to compute the carbon Footprint component of the Ecological Footprint. The major percentage of humanity's Footprint at the moment is made up of carbon. The forest area and carbon footprint shares are opposite to each other. Brazil with maximum forest surface is having carbon percentage 26% that is lowest in the group. China and South Africa are lowest surface of forest therefore they have more percentage of carbon that is 67% and 77% respectively.

Fishing grounds are estimates of the maximum sustainable harvest for a number of fish species are used to assess the Footprint of fishing grounds. Based on the trophic levels of the individual species, these sustainable catch estimates are transformed into an equal mass of primary output. The world's continental shelf areas are then separated by this projection of the greatest primary output that may be harvested. Included are fish collected and added to feed mixtures for aquaculture. The percentage of fishing area is lowest in overall EF of all countries and it ranges from 1–3% only. The built-up land Footprint is computed using the amount of land occupied by human infrastructure, including roads, homes, buildings used for industry, and hydroelectric reservoirs. What would have been farmland might now be developed. Like fishing grounds, it has also small share that ranges from 1–4%.

Table 1

Breakdown of EF for BRICS
	Built-up Land	Carbon*	Cropland*	Fishing Grounds*	Forest Products*	Grazing Land*	EF Total
Brazil	0.107	0.709	0.612	0.040	0.521	0.731	2.721
Brazil	4%	26%	23%	1%	19%	27%	100%
Russia	0.034	3.512	0.764	0.171	0.607	0.110	5.199
Russia	1%	67%	15%	3%	12%	2%	100%
India	0.044	0.524	0.318	0.015	0.129	0.008	1.040
India	4%	50%	31%	2%	12%	1%	100%
China	0.099	2.052	0.512	0.074	0.186	0.131	3.054
China	3%	67%	17%	3%	6%	4%	100%
South Africa	0.030	2.914	0.332	0.082	0.270	0.135	3.763
South Africa	1%	77%	9%	2%	7%	4%	100%

Source: World ecological footprint by land. Source: Global Footprint Network 2019 National Footprint Account.

The BRICS countries are our study sample and we took the data from 2000 to 2022. As the topic of the study has considered the ecological footprints, technological innovations, renewable energy, and globalization as important factors of carbon emissions and foreign direct investment, therefore the data is taken from world development indicators and global footprint network for BRICS countries. The authors of the study compiled a panel of five countries and obtain the long-run results to depict the relationship of the variables of the study where carbon emissions (CE) and foreign direct investment (FDI) are explaining each other with some exogenous variables and instrumental variables. The table of the description of variables is following:

Table 2

Description of Variable of Study
Variable Names	Abbreviations	Measurements
Foreign direct Investment	FDI	Foreign direct investment, net outflows (% of GDP)
Ecological Footprints	EF	Ecological Footprint (gha)
Globalization	GLOB	KOF Globalisation Index
Carbon Emissions	CE	CO2 emissions (kt)
Technological Innovation	TI	Research and development expenditure (% of GDP)
Renewable Energy Resources	RER	Renewable energy consumption (% of total final energy consumption)

Table 2 is explaining the units of measurement and abbreviations of the variables. A foreign enterprise or project that receives a foreign direct investment (FDI) from a foreign investor, business, or government. In other words, foreign direct investment is an investment made by a company with its headquarters in another country that takes the form of controlling ownership in a company, in real estate, or in productive assets like factories located in another nation. FDI has the potential to promote and sustain economic development in both the receiving nation and the nation making the investment. On the one hand, developing nations have supported FDI as a way to fund the development of new infrastructure and the creation of employment for their native workforce. However, global corporations gain from FDI by using it to increase their market penetration abroad. However, one drawback of FDI is that it is subject to many governments' inspection and regulation, which raises the political risk.

To put it simply, ecological footprint (EF) is the result of human activity and is determined by the amount of biologically productive land and water needed to create the commodities we use and ingest the garbage we make. Globalization (GLOB) is the process that makes it easier for people and products to go beyond national boundaries. The integration of markets, commerce, and investments with minimal impediments to hinder the flow of goods and services across countries is primarily an economic notion.

Carbon dioxide emissions (CE), often known as CO2 emissions, are those caused by the burning of fossil fuels and the production of cement. They also include gas flaring and carbon dioxide created during the use of solid, liquid, and gas fuels. An expanded definition of innovation is technological innovation (TI). Although innovation is a fairly well-defined notion, many people—especially those in the academic and corporate worlds—understand it to imply different things. A new or enhanced product or procedure with considerably better technical features is referred to as technological innovation. New items (product innovations) or processes (process innovations) that have been commercialized constitute technologically implemented product innovations.

4.1 Description Analysis

The descriptive analysis is estimated as a common sample for each variable and is presented in Table 3. For CE, the descriptive analysis is reported in Table 3. The panel consists of five cross-sections and each cross-section is geographically different in size and population. Table 3 is summarizing the carbon dioxide emissions in the panel. The values reported show that EF has a mean value of 3.16 with a standard deviation of 1.42. Similarly, FDI has a mean value of 0.99 of net outflow which is the percentage of GDP with a dispersion value of 1.01. the values of skewness and kurtosis indicated the normality of panel for all variables. The skewness value is favourable only if it is between 1 and + 1. If the value is higher than 1, it indicates a highly skewed distribution. For the variables of the study, TI is having highly skewed distribution. If the value of skewness is between 1 and ± 0.5, it showed the distribution is moderately skewed like FDI, GLOB and CE. However, if the value is between ± 0.5 then it is symmetric like RER and EF.

Table 3

Descriptive Analysis
	EF	FDI	GLOB	RER	TI	CE
Mean	3.16	0.99	63.66	22.75	1.08	14.06
Median	3.18	0.76	63.89	14.77	1.03	14.26
Maximum	5.79	3.77	72.15	48.92	2.43	16.28
Minimum	0.80	-2.60	46.31	3.11	0.62	12.56
Std. Dev.	1.42	1.01	5.38	16.46	0.43	1.13
Skewness	-0.03	0.61	-0.66	0.32	1.48	0.48
Kurtosis	2.05	2.54	1.46	1.48	2.70	2.11
Jarque-Bera	4.31	7.37	9.35	8.04	5.60	8.21
Probability	0.44	0.65	0.15	0.86	0.47	0.38
Observations	115.00	115.00	115.00	115.00	115.00	115
Note: Table 3 is reporting the descriptive statistics of the panel as a whole. All variables of the study are pooled country-wise and then measures of locations (mean, median and mode) are calculated considering a panel. Skewness and kurtosis also a part of the descriptive analysis that is indicating the distribution of each variable. For the robustness, the normality of residuals is estimated for the possibility of misspecification of model through monitoring the residuals of regression equations. All variables are showing the acceptance of null hypothesis that is validating the normality of residuals and no misspecification in the model.

4.2 Correlation Matrix

A balanced panel is created from the data for the chosen nations (Luo & Ma, 2021). By using a linear trend, the missing data are extrapolated and interpolated. The correlation matrix was acquired for the research in order to understand the dependency of the variables. The correlation matrix was created with the aid of the EVIEWS program (Agung, 2011), and the results are shown in Table 4.

Table 4

Correlation Matrix
	CE	EF	FDI	GLOB	RER	TI
CE	1
EF	0.62	1.00
FDI	0.64	0.53	1.00
GLOB	-0.04	0.68	0.45	1.00
RER	-0.27	-0.79	-0.41	-0.68	1.00
TI	0.85	0.24	0.16	0.08	-0.17	1
Note: Table 4’s results show that there is no correlation between the variables, and the multicollinearity is not severe enough to have an impact on the empirical results. For any variable, the estimated relationships' directions won't be reversed.

4.3 Simultaneous Equation Model

The main variables of the study CE and FDI are explaining each other along with some other variables. As both variables are indigenously behaving therefore the model of the study is presented as follows:

$CE=f\left(FDI, EF, TI, RER\right)$ ……………… Eq. (1)

$FDI=f(CE, EF, GLOB, RER)$ ………………… Eq. (2)

Both equations are showing that CE and FDI are dependent variables of the model and technological innovations, renewable energy and globalization are exogenous variables whereas ecological footprints and renewable energy are present in both models as independent variables. According to the above set of equations, the number of equations (G) are two and we have to check this set of equations for the identification problem first. As per Hall & Asteriou (2016), as each equation has one missing variable (M) and as per the identification problem:

$$G-1=M$$

$$G=2 \& M=1$$

So we can say about the model that it is exactly identified and we can proceed further by formulating the equations.

$CE={C}_{1}+{\delta }_{1}FDI+{\delta }_{2}EF+{\delta }_{3}TI+{\delta }_{4}RER$ …….. Eq. (3)

$FDI={C}_{2}+{\delta }_{5}EF+{\delta }_{6}CE+{\delta }_{7}GLOB+{\delta }_{8}RER$ ……. Eq. (4)

Here in both equations C is representing the constant term and subscripts 1 and 2 is telling the equations. $\delta$ is representing the coefficients of the exogenous and indigenous variables. For the estimation, Eviews statistical software is used for system of equations. In system of equations, each equation is written manually according to simultaneous equation model

and the results for each equation is reported below in Table 3 and 4.

Table 5

Results of first equation$CE={C}_{1}+{\delta }_{1}FDI+{\delta }_{2}EF+{\delta }_{3}TI+{\delta }_{4}RER$
Variables	Coefficients	Std. Err	t-ratio	Prob.
FDI	-0.272	0.051	5.319	0.000
EF	0.842	0.350	2.407	0.000
TI	-1.890	0.476	-3.968	0.000
RER	-0.065	0.024	-2.732	0.000
${C}_{1}$	15.865	3.261	4.865	0.000
Note: Table 5 reflects the results of Eq. 3 where CE is indigenous variable with a set of exogenous variables. The table indicating the estimated coefficients values in second column, std. error, t-ratios in next two columns and probability values in the last column. The probability value is used for indication of significance of the estimated coefficients and prob. values are declaring all variables statistically effective and significant. The estimated signs of the coefficients are explaining the direction of relationship of exogenous variables with dependent one.

In the Table 5, we showed the results of our first equation of the analysis and set of equations. The results show that an inverse and significant prediction of relationship between CE and FDI. The per-unit increase in FDI will lead a decrease of CE showing the increasing quality of environment (Ren et al. 2021; Latief et al. 2021; Apergis et al. 2023; Nasim et al., 2023). The reason behind this positive correlation of FDI and environment quality is mainly from the developed countries which intended to allows only such sources of investment that are eco-friendly. Next variable of the system is EF that also presenting a direct relation with CE (Ansari, 2022; Ansari et al. 2022; Alola et al, 2022). As ecological footprint is accounting the measures the demand on and supply of nature. It measures the biologically productive area that need to provide the people demand from nature (GF Network, 2019; Rees, 2018). The more addition in EF will decrease the environment quality when CE increases. The inverse relationship between TI and CE depicting that TI is able to contribute in the environmental quality of the selected panel with a decrease in CE (Chen et al, 2023; Dong et al. 2022; Irandoust, 2016; Ali et al, 2016). The lower rate of association might be due to India as it is fifth most polluted country of the world. The empirical relationship of RER and CE is also negative that is quite clear. More and more renewable energy will decrease the CE and boost the environment (Saidi, & Mbarek, 2016; Sebri, & Ben-Salha, 2014; Mirza & Kanwal, 2017).

Table 6

Results of second equation:${F}{D}{I}={{C}}_{2}+{{\delta }}_{5}{E}{F}+{{\delta }}_{6}{C}{E}+{{\delta }}_{7}{G}{L}{O}{B}+{{\delta }}_{8}{R}{E}{R}$
Variables	Coefficients	Std. Err	t-ratio	Prob.
EF	-0.470	0.113	4.166	0.000
CE	-0.264	0.083	3.164	0.002
GLOB	0.031	0.024	1.296	0.196
RER	-0.020	0.009	2.067	0.040
${C}_{2}$	6.627	2.196	-3.017	0.003
Note: Table 6 reflects the results of Eq. 4 where FDI is indigenous variable with a set of exogenous variables. The table indicating the estimated coefficients values in second column, std. error, t-ratios in next two columns and probability values in the last column. The probability value is used for indication of significance of the estimated coefficients and prob. values are declaring all variables statistically effective and significant. The estimated signs of the coefficients are explaining the direction of relationship of exogenous variables with dependent one.

The second equation of the system is estimated and reported in Table 6. The negative relation of EF and FDI showed that the lower rate of EF will demotivate and discourage the foreign investment. In addition, the FDI with more CE are not welcome in the selected nations in order to keep the environment clean. The reason behind this notion is simple, natural resources are the main attraction for large investment companies especially when their production is attached with certain natural asset. When the level of such assets becomes smaller than the attraction for such companies may be lower (Chishti, 2023; Udemba, 2021; Ponce et al. 2023). CE and FDI also move in opposite direction as per the results of the study. High rate of pollution leads to lower rate FDI (Kayani et al. 2023) and investors are not willing to invest in polluted and degraded environment and that is also validated by our empirics. GLOB is a boosting factor for FDI as more and more globally integrated an economy would be an attraction for the rest of the world. However, the estimated score here is not statistically significant at a very lower rate of acceptance. To increase the FDI in the context of GLOB, it is a requirement to alter the foreign policies and make the FDI more friendly (Aluko et al. 2021; Akadiri & Ajmi, 2020; Tiba & Belaid, 2020). RER is a discouraging factor for FDI due to the nature of the foreign investment. If a country leads to increase the use of renewable energy, then it will act like a restriction on the investors that might base on traditional sources of energy (Ben et al. 2019; Ekwueme et al. 2021). The constant term of the equation is representing the value of autonomous FDI that is not effected by any of the factor of the study. The value of constant is telling that 6.67 units of FDI are independent of any factor and this value is statistically significant at 0.3% level.

The study intended to investigate the relationship between CE and FDI in such a way that both are explaining factors for each other keeping in view the EF as one of the main exogenous variable along with TI, GLOB and RER. To obtain the empirical results of the study, simultaneous equation has used with two equations and indigenous variables. The set of the equations tested for possible identification and our model become exactly identified model. By using statistical software EVIEWS, the equations estimated and reported results showed that EF is having the major and positive impact on CE and FDI that is statistically significant as well. The equation for CE is having FDI as a negative determinant along with RER indicating the need of green finance (Khan et al., 2022). The FDI may deteriorate the environment if the investment is not based on the eco-friendly means of productions. Similarly, RER is also pushing the CE downward and improving the environmental quality. Technological innovation is still increasing the production of CE due to presence of India in the panel. India is 5th most polluted country in the world.

The second equation of the study is projecting the impact of CE, GLOB and RER on FDI along with EF. The results are not surprising for this equation, as CE and RER are empirically validated as discouraging factor for FDI and GLOB is behaving inversely. Higher rate of EF also pushing the FDI down and depicting the importance of natural resources for any economy.

The feasibility of achieving carbon emissions in the economic and environmental performance of the BRICS nations was investigated, as the study's title implies. Indicators were carefully chosen depending on their applicability to the study's goal. Given the complexity of the study and the ecological footprint's comprehensiveness, which includes six (6) environmental components, it was decided to use it as an indicator of environmental performance (quality of the environment). Other than ecological footprint, globalization, technical advancement, foreign direct investment, and renewable energy were thought significant to the goal of this study. The policy emphasis should instead be on improving environmental quality and FDI after taking a serious look at the existing status of the BRICS environment and the huge EF effect. This should be accomplished through raising public awareness of the need of reducing carbon emissions. Several projects have been launched due to technology advancements, and the globe is currently focused on new green construction laws that should be promoted to lower CE. The diversification of energy sources to include more renewable sources is the goal of these programs. Also, a policy should be put into place to mandate the use of energy-efficient items, which are mostly utilized in the housing sector. By providing provisions for expanding accessibility of public mass transit systems like metro and light rail, the transportation sector should be strengthened. The rate of automobile use by the general public, who will favour the mass transit system, will be impacted by this. The rate of fuel and petrol consumption among the families would be affected equally by this.

The BRICS countries must take another step, which they must create and execute in a realistic amount of time with seriousness towards the FDI pattern, which shows that the chosen countries will get more polluted as CE increases. Nonetheless, it is clear that FDI is critical to environmental performance and that nations with more environmental deterioration may choose to use it. This is made feasible by FDI, which introduces favorable technology from wealthy nations. So, in order to preserve this encouraging trend towards sustainable growth, certain restrictions that are preventative in character against FDI should be relaxed.

The BRICS nations should also concentrate on the supply chain of energy consumption to make it effective and clean, which will convert their impact to negation on the quality of the environment and to lower the ecological footprint and carbon emissions, as suggested by Dincer (2000) and sustainability criteria for renewable energy (Popp et al. 2014). Since BRICS will be the largest provider to global renewable capacity, the BRICS nations also need to reconfigure their energy policies in accordance with their present geographic, economic, sociological, and environmental values to address environmental challenges (Pathak and Shah 2019). Moreover, strict environmental regulations assist BRICS nations reduce their ecological footprint; as a result, these nations should maintain strict environmental regulations. The BRICS nations may also increase environmental institution quality, as indicated by Hassan et al. (2020), who claimed that high institutional quality results in the more effective implementation of environmental rules. There should be control and regulation on the mining of minerals as its higher rates can result in erosion, loss of biodiversity, significant use of water resources, wastewater disposal issues, acid mine drainage and contamination of soil, and ground water can be affected by chemicals emitted from mining process. However, the environmental impacts of mining can be reduced by reusing mining waste, use of eco-friendly equipment, shutting down the illegal mining and improving the sustainability of mining.

Also, the BRICS nations should implement a green development strategy and advance technology to reduce economic and environmental quality, as China's industrial sector's environmental performance grew by 58% between 1998 and 2009, mostly as a result of technical advancement (Meng et al. 2013). Also, the BRICS nations should be concerned with the industry sector's efficiency and treatment procedures since some evidence suggests that China's industrial systems are generally ineffective, particularly with regard to the manufacturing process and pollution removal procedures (Li et al. 2018). After addressing these concerns, it will assist BRICS nations in achieving economic development that increases industrial sector and energy sector efficiency in order to fulfil the SDGs and Paris Agreement objectives and to boost BRICS nations' soft power in global governance (Petrone 2019). It is recommended that further study be done to expand the independent variables, which include the ecological footprint, globalization, technological innovation, and renewable energy characteristics. This study technique may be used to various environmental studies topics such the connections between health and the environment, tourism and the environment, and innovation and the environment, among others.

-Ethical Approval

Not applicable.

-Consent to Participate

Not applicable.

-Consent to Publish

All authors have consented to publish this work.

Competing interests

The authors declare no competing interests.

-Authors Contributions

Contributions

Umar Nawaz Kayani: conceptualization, supervision problem definition and description, investigation, writing — part of the original draft, original draft compilation, project administration review and editing and revision.

Ismat Nasim: conceptualization, supervision problem definition and description, investigation, writing — part of the original draft, original draft compilation, project administration review and editing and revision.

Ahmet Faruk Aysan: conceptualization, supervision problem definition and description, investigation, writing — part of the original draft, project administration review and editing and revision.

Farrukh Bashir: conceptualization, supervision problem definition and description, investigation, writing — part of the original draft, original draft compilation, project administration review and editing and revision.

Umer Iqbal: conceptualization, supervision problem definition and description, investigation, writing — part of the original draft, original draft compilation, project administration review and editing and revision.

Corresponding author

Correspondence to Ahmet Faruk Aysan.

-Funding

No funding is received

-Competing Interests

The authors declare no competing interests.

-Availability of data and materials

Available up on request

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Trends of Carbon Emissions and Foreign Direct Investment: Accounting for Ecological Footprints, Renewable Energy, Globalization and Technological Innovations in BRICS

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Abstract

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1. Introduction

2. Literature Review

2.1 Globalization and environmental footprint

2.2 Economic development and environmental pollution

2.3 Overview of the Ecological Footprints of the BRICS countries.

3. Methodology

4. Research Results

4.1 Description Analysis

4.2 Correlation Matrix

4.3 Simultaneous Equation Model

5. Conclusion and Policy Suggestions

Declarations

References

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Journal Publication

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