Is India Financing Its Emissions Through External Debt?

The main aim of this study is to analyze the effect of external debt on different types of emissions in India as carbon dioxide emissions, methane emissions, emissions from liquid fuel consumption, emissions from solid fuel consumption, and emissions from gaseous fuel consumption. India has a fast growing in external debt especially after 2008 world financial crisis. India has a similar situation to China and Turkey which also started to increase external debt significantly after 2008 world crisis. This study aims to fill the gap in the literature by analyzing the effect of external debt on emissions. This study is the first study in the literature for India. The second aim of the study is to investigate whether inverted U relationship exists between economic development, and carbon oxide emissions, methane emissions, methane emissions, emissions from liquid fuel consumption, emissions from solid fuel consumption, and emissions from gaseous fuel consumption. This study confirmed inverted-U relationship between methane gas emissions and economic development, and emissions from gaseous fuel consumption and economic development. The positive and significant effect of external debt on carbon dioxide emissions, methane emissions, emissions from gaseous fuel consumption and emissions from solid fuel consumption is confirmed by this study. The analysis is important since after 2008 crisis many countries such as China and Turkey besides India started to borrow external debt heavily to create government investments to boost employment market which collapsed due to global economic crisis. This study carries importance since global greenhouse gas emissions may be financed through external debt in India. Since sustainability is the main issue in current world and reduction of emissions is one of the highest priorities of humanity, necessary measures should be taken into account to reduce financing of emissions through external debt in India. This study recommends further analysis to be done with updated intervals.


INTRODUCTION
This study investigated the effect of external debt (EX) on greenhouse gas emissions which are carbon dioxide emissions (CE), methane emissions (MN), emissions from solid fuel consumption (SFCO), emissions from gaseous fuel consumption (GFCO), and emissions from liquid fuel consumption (LFCO) for India for the period 1971 to 2012. This is the first study in the literature that investigates the effect of external debt on greenhouse gas emissions for India. In this study, CE, MN, EX, GFCO, SFCO and LFCO are chosen to be investigated by Autoregressive Distributed Lag Model by Pesaran et al. (2001). World Bank website is used to gather the data analyzed in this study.
Data used in this study are gathered from World Bank database. CE are emissions from manufacturing of cement and burning of fossil fuels. CE are in kilo tons term. MTHN are emissions from industrial methane production and agriculture. MN are in kilo tons of CE equivalent. SFCO are in kilo tons term. SOFC are emissions from mainly of coal use as energy source. LFCO are in kilo tons term. LFCO are emissions from mainly of petroleum derived fuels as energy source. GFCO are in kilo tons term. GFCO are emissions from mainly of natural gas use as energy source. EX is in current US dollars term. EX is the total external debt which includes long-term debt and short-term debt. Economic development ( The main aim of this study is to investigate the effect of EX on emissions so to answer the question whether India is financing its emissions through EX. Although the main of the study is to investigate the effect of EX on emissions, the Kuznets curve relationship is also investigated as second aim of this study in India. There is a gap in the literature for the investigation of the effect of external debt on emissions for India. This study aims to fill this gap by performing this study.   Second part discusses literature for the EKC hypothesis and external debt. Third part discusses the methodology used in this study. Fourth part discusses results and discussion of this study. Fifth and final part is conclusion.

REVIEW OF LITERATURE
In this part, most recent studies in the literature are discussed. Overall summary of this part is given in Table 1. Saxena and Shanker (2017) confirmed negative relationship between external debt and economic development for India for the period 1991 to 2016. Although a negative relationship is found, up to a certain level of external debt, external debt positively affects economic development. Nath (2020) examined the relationship between external debt, export and economic development in India for the period 1970-2018. Nath confirmed that the effect of external debt on economic growth is positive in India. Irfan et al., (2020) analyzed the moderating effect of capital formation for external debt an stock market performance for Pakistan, Sri Lanka, Bangladesh and India for the period 1992-2017. Irfan, Rao, Akbar, and Younis confirmed that capital formation has a positive effect for external debt and stock performance and external debt has negative effect on economic development. Chisti and Shabir (2019) analyzed the effect of external debt on economic development, government spending, revenue, inflation and exports in India for the period 2007-2017 on quarterly data. Chisti and Shabir confirmed that there is no significant relationship  Main findings Saxena and Shanker (2017) Confirmed negative relationship between EX and economic development Nath (2020) Confirmed the positive effect of EX on economic development Irfan et al., (2020) Confirmed the negative effect of EX on economic development Chisti and Shabir (2019) Confirmed no significant relationship between EX and economic development Pahwa (2018) Confirmed the negative effect of EX on economic development Joy and Panda (2019) Confirmed EX negatively affected non-developmental expenditure and positively affected inflation Sinha and Bhatt (2017) Confirmed N-shaped relationship between emissions and economic development Sultan et al., (2021) Confirmed the EKC hypothesis in India Murthy and Gambhir (2018) Confirmed N-shaped relationship between emissions and economic development Khan et al. (2020) Confirmed the EKC hypothesis for panel countries of India, China, and Pakistan Alam and Adil (2019) Did not confirm the EKC hypothesis in India Katircioglu and Celebi (2018) Did not confirm the effect of EX on emissions  Confirmed the effect of EX on emissions Beşe et al., (2020) Confirmed the coal Kuznets curve Magazzino et al., (2020) Confirmed the coal Kuznets curve Qiao et al., (2019) Confirmed the coal Kuznets curve Shahbaz and Sinha (2019) Recommended new methodologies to be used to investigate the EKC hypothesis Purcel (2020) Recommended new methodologies to be used to investigate the EKC hypothesis between external debt and economic development, external debt and export, external debt and revenue, and external debt and government spending. They found that external debt causes increase in inflation. Pahwa (2018) examined the relationships between external debt, internal debt, population, investment and trade openness for India for the period 1980-2014. Pahwa confirmed that external debt and internal debt affect economic growth significantly and negatively.
Joy and Panda (2019) analyzed the relationship between external debt, external debt servicing, gross domestic capital formation, gross domestic savings, developmental expenditure, nondevelopmental expenditure, export, inflation and foreign direct investment for India. Joy and Panda confirmed the long run relationship between the variables. Joy and Panda confirmed that external debt postively affected inflation but negatively affected non-developmental expenditure.
Sinha and Bhatt (2017)  For the effect of external debt on emissions, the most recent studies are belong to Katircioglu and Celebi (2018) and . Katircioglu and Celebi (2018) analyzed the case in Turkey and  analyzed the case in China. While Katircioglu and Celebi (2018) did not find any evidence for the effect of EX on emissions in Turkey,  confirmed the effect of EX on emissions in China.
Since this study analyzed the emissions from coal consumption, the most recent studies for coal consumption and economic development are belong to Beşe et al., (2020), Magazzino et al., (2020) and Qiao et al., (2019).
For literature review studies for the EKC hypothesis, the most recent studies are belong to Shahbaz and Sinha (2019) and Purcel (2020). Both literature reviews stated that new methodologies should be included for the investigation of the EKC hypothesis.
Literature review shows that the general tendency in the literature is to analyze the relationship between external debt and economic development. There is a gap in the literature for the analysis of the effect of external debt on emissions for India.

Data
The variables used in this study are as follows. CE are emissions from manufacturing of cement and burning of fossil fuels. CE are in kilo tons term. MTHN are emissions from industrial methane production and agriculture. MN are in kilo tons of CE equivalent. SFCO are in kilo tons term. SOFC are emissions from mainly of coal use as energy source. LFCO are in kilo tons term. LFCO are emissions from mainly of petroleum derived fuels as energy source. GFCO are in kilo tons term. GFCO are emissions from mainly of natural gas use as energy source. EX is in current US dollars term. EX is the total external debt which includes long-term debt and short-term debt. Economic development (GD) which is gross domestic per capita are in terms of constant 2010 US$. GD2 is the square of GD. Energy consumption (ECM) is in terms of kg of oil equivalent per capita.
Data used in this study are retrieved from world bank website. Data used in this study range between 1971 and 2012 since the data in world bank website is limited till 2016 for used variables in this study. Range is determined till 2012 for the analyzed variables to provide the stability for established models.

Methodology
t t ln CE = r +r ln GD + r ln GD + r ln ECM t t ln MN = r +r ln GD + r ln GD + r ln ECM 10 11 t t t t 12 t t ln GFCO = r +r ln GD + r ln GD + r ln ECM t t ln LFCO = r +r ln GD + r ln GD + r ln ECM + r ln EX + e (4) t t ln SFCO = r +r ln GD + r ln GD + r ln ECM + r ln EX + e Relationship between GD, square of GD, ECM and EX, with CE, MN, GFCO, LFCO and SFCO are modelled above in equation 1-5.
For the equation 6 below, v 0 , v 1 , v 2 , v 3 , v 4 are coefficients for the examined variables which are GD, square of GD, EM and EX and b t is for error term. EM is for emissions which are CE, MN, GFCO, LFCO and SFCO.
The ARDL model which is used as to investigate the relationship between the variables is mentioned as below in equation 7.
In the model below, M coefficients are long run coefficients. N coefficients are short run coefficients. b t is for white noise residuals.
( ) Equation 8 is to determine the long-run coefficients of ARDL model and equation 9 is to determine the short-run coefficients of ARDL model. Error correction model is specified in equation 10. (1992)

Analysis of CE-EX Relationship
Bounds test results show that F-statistics value is 6.69 and it is above I1 value of 1% which is 5.06. Long-run relationship between the analyzed variables is confirmed. For further analysis, ARDL-ECM model is applied to calculate short-run and long-run coefficients for each variable. 1997 is used as structural break in the analysis. Further analysis show that inverted U relationship is not confirmed between CE and GD, and EX has positive and significant effect on CE ( Table 3). The long-run relationship between the variables is confirmed with negative coefficient of cointegration equation with significance of 1%. RRAT, BPGODT, HTAHT, HTWT, BDGODLMT and NMTT shows that the model satisfies the criteria for stability ( Table 2). Further stability tests are carried out by CTU and CTUSQ tests and the model satisfies the criteria for stability for these tests as well (Figures 4 and 5). This analysis confirms the main aim of the study that EX has positive and significant effect on CE.

Analysis of MN-EX Relationship
Bounds test results show that F-statistics value is 13.17 and it is above I1 value of 1% which is 5.06. Long-run relationship between the analyzed variables is confirmed. For further analysis, ARDL-ECM model is applied to calculate short-run and long-run coefficients for each variable. 1990 is used as structural break in the analysis. Further analysis show that inverted U relationship is confirmed between MN and GD, and EX has positive and significant effect on MN ( Table 5). The long-run relationship between the variables is confirmed with negative coefficient of    (Table 4). Further stability tests are carried out by CTU and CTUSQ tests and the model satisfies the criteria for stability for these tests as well (Figures 6 and 7). The analysis shows that there is inverted U relationship between MN and economic growth for India for the period 1971-2012. This analysis confirms the main aim of the study that EX has positive and significant effect on MN.

Analysis of GFCO-EX Relationship
Bounds test results show that F-statistics value is 13.48 and it is above I1 value of 1% which is 5.06. Long-run relationship between the analyzed variables is confirmed. For further analysis, ARDL-ECM model is applied to calculate short-run and long-run coefficients for each variable. 1991 is used as structural break in the analysis (Table 6). Further analysis show that inverted U relationship is confirmed between GFCO and GP, and EX has    Table 7). The long-run relationship between the variables is confirmed with negative coefficient of cointegration equation with significance of 1%. RRAT, BPGODT, HTAHT, HTWT, BDGODLMT and NMTT shows that the model satisfies the criteria for stability (Table 5).

Short-run coefficients
Further stability tests are carried out by CMM and CMMSQ tests and the model satisfies the criteria for stability for these tests as well (Figures 8 and 9). The analysis shows that there is inverted U relationship between GFCO and economic growth for India for the period 1971-2012. This analysis confirms the main aim of the study that EX has positive and significant effect on GFCO.

Analysis of LFCO-EX Relationship
Bounds test results show that F-statistics value is 10.84 and it is above I1 value of 1% which is 5.06. Long-run relationship between the analyzed variables is confirmed. For further analysis, ARDL-ECM model is applied to calculate short-run and long-run coefficients for each variable. 2001 is used as structural break in the analysis. Further analysis show that inverted U relationship is not confirmed between LFCO and GP, and EX has positive and insignificant effect on LFCO ( Table 9). The long-run relationship between the variables is confirmed with negative coefficient of cointegration equation with significance of 5%. RRAT, BPGODT, HTAHT, HTWT, BDGODLMT and NMTT shows that the model satisfies the criteria for stability (Table 8). Further stability tests are carried out by CTU and CTUSQ tests and the model satisfies the criteria for stability for these tests as well (Figures 10 and 11).

Analysis of SFCO-EX Relationship
Bounds test results show that F-statistics value is 4.46 and it is above I1 value of 5% which is 4.01. Long-run relationship        Table 11). The long-run relationship between the variables is confirmed with negative coefficient of cointegration equation with significance of 1%. RRAT, BPGODT, HTAHT, HTWT, BDGODLMT and NMTT shows that the model satisfies the criteria for stability (Table 10). Further stability tests are carried out by CTU and CTUSQ tests and the model satisfies the criteria for stability for these tests as well (Figures 12 and  13). This analysis confirms the main aim of the study that EX has positive and significant effect on SFCO.

CONCLUSION
Main findings of this study are as below.

No inverted U relationship between CE and GD (Hypothesis 2)
2. EX has significant and positive effect on CE (Hypothesis 1) 3. Inverted U relationship between MN and GD (Hypothesis 4) 4. EX has significant and positive effect on MN (Hypothesis 3) 5. Inverted U relationship between GFCO and GD (Hypothesis 10) 6. EX has significant and positive effect on GFCO (Hypothesis 9) 7. No Inverted U relationship between LFCO and GD (Hypothesis 8) 8. EX has insignificant and positive effect on LFCO (Hypothesis 7) 9. No inverted U relationship between SFCO and GD (Hypothesis 6) 10. EX has significant and positive effect on SFCO (Hypothesis 5).
Time period of this study for India is from 1971 to 2012. Period is chosen according to the availability of data on energy consumption side. India's external debt continued to rise after 2012 till today. The results of this study confirmed hypothesis 1, 3, 4, 5, 9 and 10. The results of this study did not confirm hypothesis 2, 6, 7 and 8. MN Kuznets curve and GFCO Kuznets curve are confirmed by this study. The main aim of this study is to prove the effect of EX on emissions. According to study results, EX has significant and positive effect on SFCO, GFCO, MN and CE. The results of this study confirm that India finances its emissions through external debt. As stated above, although the study period covers from 1971 to 2012, India's external debt continued to increase after 2012. It is highly likely India continued to finance its emissions through external debt after 2012 till today. Since sustainability is the main issue in current world and reduction of emissions is one of the highest priorities of humanity, necessary measures should be taken into account to reduce financing of emissions through external debt in India.
Although this study did not confirm inverted U relationship between SFCO and GD, we recommend further studies to investigate coal Kuznets curve for India which is another gap in the literature and coal is one of the major contributors to greenhouse gas emissions. Beşe et al., (2020), Magazzino et al., (2020) and Qiao et al., (2019) are the most recent studies in the literature that confirmed coal Kuznets curve.
The time period analyzed and the country of the study which is India are the limits of this study. This study recommends further policies to be taken to control the use of external debt for creating environmental pollution in India. For future research direction, further studies need to be carried out to analyze the effect of external debt on emissions for developing countries.