Foreign Direct Investment and CO2, CH4, N2O, Greenhouse Gas Emissions: A Cross Country Study

To investigate the effects of foreign direct investment on CO2, CH4, N2O, and other greenhouse gas emission the study was conducted. The panel data from 200 countries were collected for the period of 1990 to 2018. Ordinary least square (OLS), pooled ordinary least square (POLS), Driscoll-Kraay (DK), Second stage least square (2SLS), generalized methods of moments (GMM) model has been performed. The findings showed that foreign direct investment has positive impact on CO2 in all the models. The study also showed that FDI had negative impact on CH4 emission and positive impact on N2O emissions in all models except GMM model. Finally, FDI had mixed impact on greenhouse gas emission but the results were statistically insignificant except OLS model.


INTRODUCTION
The environmental impacts of FDI (foreign direct investment); sustainability of FDI and its effect on the environment; and cross-border environmental implications are the areas of debate in which the FDI-Environment Relationship considers its status for study. The literature has progressed to the point that no clear or conclusive consensus on the meaning has been reached (Cole et al., 2017;Pazienza, 2014), which is particularly true in the first vein of the sentence, for which it is commonly argued that further research is required (Shao, 2018;Zheng and Sheng, 2017;Seker et al., 2015;McAusland, 2010;OECD, 2002a). It has been noted that there has been a greater focus on the relationship between FDI and the atmosphere in this specific thematic area. The majority of the work has been completed, and continues to be done, using various aggregated FDI statistics (e.g. Bakhsh et al., 2017;Shahbaz et al., 2015Shahbaz et al., , 2011Liang, 2006). worth debating more. The Pollution Haven Theory states that FDI reduces emissions in high-income countries while increasing emissions in middle-income countries. However, middle-income countries' willingness to absorb technology will become crucial in the long run. Environmental policy has a major impact on trade in middle-income countries. Our mission is to comprehend the transfer of emissions from polluting industries, which is why we conducted a thorough examination of the industrial sector's total green house gas pollution. It has also been discovered that policymakers do not pay enough attention to how innovation contributes to environmental degradation. This paper has five sections. Section two discusses the review of the literature. Section three is the methods. Section four is about the findings and discussion and finally section five of this paper give some recommendations and conclusion.

LITERATURE REVIEW
While panel data analyses using aggregated data, such as those conducted by Hoffmann et al. (2005), Sadorsky (2010), Pao and Tsai (2011), and Kim and Adilov (2012), have been unable to confirm a near relationship between energy intensity and FDI or emission and FDI, firm level analyses conducted by Blackman and Wu (1999) and Fisher-Vanden et al. (2004) have shown that FDI has a reduced impact on energy intensity. Furthermore, Hoffmann et al. (2005) discover that the causal relationship transfers to country groups that were identified by the Granger Causality Approach screen as having high per capita income. In addition, Eskeland and Harrison (2003), Merican et al. (2007), Lee (2009), Tang (2009), and Chang (2012 have identified a transformation in bilateral relations using time series analyses. Panel data analyses produce more reliable and statistically powerful results than cross-section and time series analyses since the sample size is larger. There may be some variation in the estimated parameters for each particular panel, however (country). Furthermore, the topic of heterogeneity will influence bias estimation. Furthermore, cross-sectional dependence may lead to erroneous conclusions. The chosen panel data approach should then take into account variability and cross-sectional dependency concerns. Adams (2009) revealed that FDI had an initial negative influence on DI and subsequent positive effect in later periods for the panel of countries investigated. The sign and size of the present and delayed FDI coefficients imply a net crowding out impact. The study's findings and analysis of the literature show that the continent need a tailored strategy to FDI, increased absorption capacity of local companies, and government-MNE cooperation to achieve mutual benefit. Azomahou et al. (2005) used a panel of 100 nations to look at the empirical relationship between CO 2 emissions per capita and GDP per capita from 1960 to 1996. They discovered evidence of the relationship's structural integrity. They then design a countryspecific nonparametric panel data model. The findings of the estimation reveal that the connection is upward sloping.
Another concern in the literature is the conflicting findings on the relationship of FDI-energy power and FDI-pollution. For example, Eskeland and Harrison (2003) found that FDI helps Mexico save electricity. Cole and Elliott's (2005) findings supported the carbon haven hypothesis for the aforementioned countries. Several studies, including Blackman and Wu (1999), Hübler and Keller (2010), Sadorsky (2010), and Herrerias et al. (2013), have assumed that if FDI had contributed to energy production, per capita emissions would have decreased. Variations in processes, time intervals, or factors may have caused conflicting results in various experiments. As a consequence, the two lines of literature should be reviewed together in order to achieve reliable data. If there are contrary results, reducing emissions by energy savings enhanced by inward FDI cannot be obvious. Muhammad and Khan (2019) contributed to factors that help Asian countries grow economically, with an emphasis on often-forgotten bilateral FDI, electricity use, CO 2 emissions, and a central position in the economy. In their study, they used the Generalized Approach of Moments (GMM), OLS regression, Fixed Effect and Random Effect Estimates. Between 2001 and 2012, data was gathered from 34 Asian host countries and 115 source countries. The study found that oil use, FDI inflows and outflows, CO 2 emissions, and other services all play a significant role in Asia's economic growth. The current study shows that improved energy use strategies, such as the use of appropriate and innovative energy technologies, as well as attracting international investors both in and out of the countries, are being implemented in Asian countries, resulting in increased economic growth as the global economy grows due to both inflows and outflows of FDI, oil use, and CO 2 emissions. Fauzel (2017) looked at the long-and short-term effects of FDI on CO 2 emissions in Mauritius (disaggregated into manufacturing and non-manufacturing sectors). In this study, the bounds checking approach to co-integration is used. For time series data from 1980 to 2012, the autoregressive distributed lag (ARDL) model is used. The study's main findings show that foreign investment in the manufacturing industry is adverse to the environment, while FDI in non-manufacturing sectors is not. Furthermore, an increase in demand is thought to result in an increase in CO 2 emissions. Energy consumption in the world has already been found to result in an increase in CO 2 emissions. The results also affirm the stability of the model for the small island economy in Mauritius. (2019) focused on long-term growth and carbon emissions, as well as their effect on the environment. They tried to gather all available information on the topic and discovered that, in the present scenario, the problem is gaining high priority due to the growing pace of development in developing countries. Many of the study supported Kuznets' environmental curve theory, and they discovered a wide body of literature advocating for cleaner FDI as a way to reduce the negative environmental effects of economic growth.

Saini and Sighania
Carbon pollution and foreign direct investment have a negative relationship, according to Yüksel et al. (2020). As a result, a comparison analysis is conducted for all E7 and G7 countries. The analysis framework incorporates Pedroni panel co-integration (PPC), Kao panel co-integration (KPC), and Dumitrescu Hurlin panel causality (DHPC) analyses. Gas emissions have a detrimental impact on foreign direct investment for all countries, according to the findings. This bond, on the other hand, is stronger with the G7 economies. There is also no evidence of a causal relationship between these factors. Countries should follow ambitious policies to reduce carbon emissions, according to the experts. In this way, a new tax might be imposed on businesses that emit a lot of pollution. Policymakers, on the other hand, may be willing to support policies that aim to reduce carbon emissions. In this scenario, lowering the tax rate and increasing the supply of technical assistance are examples. Li and Liu (2011) used absolute and comparative metrics representing the volume of CO 2 released from 30 Chinese provinces from 2000 to 2008 to divide the entire county into eastern and western regions based on economic and geographical factors. The thesis investigates the effect of foreign direct investment on CO 2 emissions across a technical channel. According to the findings, FDI's effect on CO 2 emissions in China is erratic. FDI in the east has a significant positive impact on local CO 2 emissions; the role of FDI in the central region is unclear; and FDI in the west of the country had a negative impact on CO 2 emissions.
The effect of international trade and foreign direct investment (FDI) on CO 2 emissions in Turkey was investigated by Haug and Ucal (2019). They looked at both linear and non-linear ARDL models and discovered that exports, imports, and FDI have a significant asymmetrical effect on per capita CO 2 emissions. FDI, on the other hand, has no statistically significant long-term effects. The reduction in exports reduces per capita CO 2 emissions in the long run, but the increase in exports has no statistically meaningful effect. Imports increase CO 2 emissions per capita, while reductions in imports have no long-term effects. Exports and imports, on the other hand, have little effect on CO 2 power, which measures CO 2 emissions per unit of oil. Instead, financial development and urbanization are aided. They also discovered that the Kuznets environmental curve is current for both CO 2 indices, implying that increases in actual per capita GDP have led to lower CO 2 emissions for at least the last decade, after accounting for other competing causes. Furthermore, in two of the four markets, the sectoral share of CO 2 emissions in total CO 2 emissions asymmetrically changes with foreign trade, with export growth leading to a lower share of CO 2 and imports having the opposite impact. Fereidouni (2013) indicated that actual FDI states do not add to emissions of CO 2 . Consumption of energy, urbanization and economic growth has also been described as significant determinants of CO 2 emissions. Mugableh (2013) and Borhan et al. (2012) studied the association between CO 2 emissions and economic growth in Malaysia in separate ways, but the results were similar: an increase in the economy causes CO 2 emissions. To re-analyse CO 2 pollution, Mugableh (2013) used a self-regressive lag strategy. From 1971 to 2012, data was collected. The results show that economic development is dependent on energy demand, but that this can be harmful to the environment because it can result in CO 2 emissions. Borhan et al. (2012) used FDI to conduct their research. From 1965 to 2010, they used a larger number of comments in the study. Revenue, FDI, population, exports and imports were included as parts of their CO 2 feature. The non-linear model has been used and the findings suggest that a rise in FDI implies a rise of CO 2 in the atmosphere.
For 15 years, Maddison and Rehdanz (2008) looked at the relationship between GDP and carbon emissions in 134 countries (1990 to 2005). When variability is ignored, CO 2 emissions in North America, Asia, and Oceania are not compared to GDP. Han and Lee (2013) used a hierarchical panel data model to study the directional relationship between pollution and economic growth in OECD countries from 1981 to 2009. The connection between economic growth and pollution implies the need for technological advancement in order to achieve economic growth with minimal pollution, which supports Kuznets' environmental curve hypothesis.

METHODS
A analysis using a composite model was carried out. Using STATA 15, describe the relationship between FDI and emission-related variables. The OLS (ordinary least squares) model was used. STATA 15 was used to describe the relationship between FDI and emission variables using the Pooled Ordinary Least Squares (POLS model). Using STATA 15, the Drisc/Kraay (DK) model was used to determine the relationship between FDI and emission variables. The two stage least square model (2SLS) was used to describe the relationship between FDI and variables related to emissions using STATA 15. Finally, using STATA 15, a Generalized Method of Moments (GMM) model was used to define important explanatory variables that can describe the reasons for the interaction between FDI and emission variables.

Pair Wise Correlation Matrix
First, we'll look at the associations among the variables we found in the literature and see whether there's a connection between FDI and different types of emissions. The variables are reported in a combined correlation matrix shown in Table 2.

Econometric Models
Multiple regression models have been run with the dependent (LnFDI) and independent variables (LnCO 2 EKT, LnCO 2 EMTPC, LnCH 4 E, LnN 2 OE and LnTGHGE). In the following section the results of those models are presented and interpreted below.
CO 2 emissions (both kt and metric ton per capita) have a strong positive association with FDI, as seen in Table 3. The higher a country's foreign direct investment, the higher its CO 2 emissions. On the contrary CH 4 emissions has significant negative relationship with the FDI which indicates that a country having high more FDI does not significantly affect the CH 4 emission of a country. N2O emissions and total greenhouse gas emissions have a substantial positive relationship with FDI, indicating that more FDI produces more N2O and total greenhouse gas emissions in a region.
CO 2 emissions (both kt and metric ton per capita) and nitrous oxide emissions (both kt and metric ton per capita) have a strong positive relationship with FDI, as seen in Table 4. The higher a country's foreign direct investment, the higher its CO 2 and N 2 O emissions.
On the contrary methane emissions has significant negative relationship with the FDI which indicates that a country having high more FDI does not significantly affect the CH 4 emission of a country. Total greenhouse gas emissions have a negative relationship with FDI, but the relationship is insignificant, even though the overall model is significant at the 10% stage.
CO 2 emissions (kt) and nitrous oxide emissions (kt) have a significant beneficial association with FDI, as seen in Table 5.
The higher a country's foreign direct investment, the higher its CO 2 and nitrous oxide emissions. Methane emissions, on the other hand, have a substantial negative association with FDI, indicating that a nation with a high level of FDI has no impact on its CH4 emissions. CO 2 emissions (metric ton per capita and gross greenhouse gas emissions) have a favorable relationship with FDI, but the relationship is negligible, despite the overall model   being important at the 10% stage. The next model is presented to improve the findings' robustness.
CO 2 emissions (both kt and metric ton per capita) have a strong positive association with FDI, as seen in Table 6. The higher a    country's foreign direct investment, the higher its CO 2 emissions. On the other hand, CH4 emissions have a major negative association with FDI, indicating that a nation with a high level of FDI has no impact on its CH 4 emissions. N 2 O emissions and total greenhouse gas emissions have a significant beneficial association with FDI, implying that more FDI causes more N2O emissions and total greenhouse gas emissions. The next model is run to ensure that the findings are more reliable. Table 7 reveals a significant positive association between CO 2 emissions (kt), CO 2 emissions (metric ton per capita), and CH4 emissions and FDI. The higher a country's foreign direct investment, the higher its CO 2 and methane emissions. In the other hand, N2O emissions have a major negative association with FDI, indicating that a nation with a high level of FDI has no impact on its N2O emissions. Total greenhouse gas emissions have a favorable relationship with FDI, but the relationship is negligible, despite the overall model being meaningful at the 10% stage.

CONCLUSION
To investigate the effects of foreign direct investment on CO 2 , CH 4 , N 2 O and total greenhouse gas emission this study is conducted. Panel data for 200 countries over a period of 29 years  has been used as the sources of information. Ordinary Least Square (OLS), Pooled Ordinary Least Square (POLS), Driscoll-Kraay (DK), Second Stage Least square (2SLS), Generalized Methods of Moments (GMM) models have been performed and the result shows that there is a positive relationship between FDI and different types of green house gas emission. With economical advancement the emission green house gases (CO 2 , CH 4 , N 2 O and others) increase simultaneously. The findings are very important in case of formulating environmental policies. Therefore, the developing country should find alternative sources of energy to ensure that there is no harmful effect on environment as there is an increase rate of energy consumption with economic growth. The use of natural gas, biomass, green technology etc. may be some important way to reduce CO 2 emission.
Data were collected only from 200 countries because there is a lack of data availability from remaining countries of the world. Data more than 29 years would have led us to a better conclusion. Data conversion during analysis may lead to some discrepancy. Besides these emissions many other variables remained untouched in this research that may help us on finding out other important determinants of FDI.