Impact of CO₂ Emissions, Exchange Rate Regimes, and Political Stability on Currency Crises: Evidence from South Asian Countries

Abstract

This study uses the panel probit model to investigate and evaluate the relationship between exchange rate regimes, political stability, and carbon dioxide during currency crises. To understand currency crisis times, we study a panel dataset of seven South Asian nations that contain annual observations from 1996 to 2020. Furthermore, we created the EMPI exchange market pressure indicator to detect crises. Our results strongly suggested that fixed exchange rate is negatively associated with currency crises, with good regulatory quality and better effective governments. Simultaneously, the floating exchange rate is positively related to the currency crises in those countries where the rule of law has less adequately flowed. However, CO₂, exports, and interest rates are buoyantly associated with crises. The floating exchange rate, the rule of law, exports, and interest rate are associated positively and contribute more prone to the crisis episodes. Negatively associated variables contributed less amid crises episodes: fixed exchange rate regime, government effectiveness, and regulatory quality. Meanwhile, CO₂ has a positive relationship with a currency crisis and contributes more likelihood to the probability of a currency crisis. Countries that adopted the fixed exchange rates with effective governments and regulatory quality faced more minor currency crises.

1. Introduction

The capital market has become increasingly integrated in recent years. The choice of exchange rate regime and currency crises is a crucial and central subject in international economics that has been debated around the world over the past decade. Currency crises accelerated in the 1990s, with notable incidents including the European Monetary System (EMS) crisis (1992–1993), the Mexican crisis (1994–1995), and the Asian crisis (1995–1996). (1997 to 1998). Using various methodologies, such as regression analysis, some scholars have attempted to discover the links between currency crises and exchange rate regimes (Bubula & Robe, 2003; Saka, 2010; Haile & Pozo, 2006). Ghosh et al. (2015) used the IMF de-jure classification dataset from 1972 to 1999 to assess the probability and danger of currency crises under alternative exchange rate regimes. They discovered that countries with variable exchange rates are more vulnerable to currency crises.

Bubula and Robe (2003) used logit models to investigate the link between currency crises and exchange rate regimes, utilizing a dataset of de-facto classifications from 1990 to 2001 that included IMF member nations. They discovered that the bipolar view of exchange rate regimes puts intermediate regimes at a higher risk of currency crises than fixed and floating exchange rate regimes. Haile and Pozo (2006) analyzed that exchange rate regimes affect the occurrence of currency crises on selected 18 developed economies based on IMF classification. Saka (2010) investigated the exchange rate regimes with the currency crisis in 84 economies and used the de facto Reinhart and Rogoff (2004) classification. He found that the fixed exchange rate regimes are significantly lesser than the currency crisis episodes compared with floating exchange rate regimes The languages, cultures, macroeconomic structures, and political systems of South Asian countries are all unique. Because of the vast population, there is a lot of consumption, which indicates how well the economy is doing. The financial crisis of 2008 had a short-term influence on carbon dioxide emissions. Constant CO₂ emission rise, and maybe even much higher growth in the future, has raised many concerns about meeting the global warming target of less than 2 CO₂ (Friedlingstein et al., 2014; Rozenberg et al., 2015).

The foregoing research yielded conflicting results when it came to analyzing, measuring, and examining the impact of exchange rate regimes on the risk of the currency crisis. As a result, it’s critical to look into the various forms of exchange rates and determine which are more vulnerable to currency crises and which are useful in avoiding speculative attacks on currency crises. Furthermore, the effects of CO₂ on currency crises are often disregarded in South Asian literature. As a result, the study’s impact on CO₂ is another contribution.

Our findings imply that fixed exchange rates are negatively associated with currency crises in nations with high regulatory quality and efficient governments. Similarly, the floating exchange rate is positively associated with currency crises in countries where the rule of law has not flowed as freely as it could. Furthermore, CO₂, exports, and interest rates are all strongly linked to crises. The floating exchange rate, the rule of law, CO₂, exports, and interest rates all play a role in the occurrence of crises. Fixed exchange rate, government effectiveness, and regulatory quality were negatively related and contributed less during crises events. Meanwhile, CO₂ has a positive relationship with currency crises and contributes to the likelihood of a currency crisis.

2. Literature Review and Hypotheses

2.1. Exchange Rate Regimes and Currency Crises

The relationship between the probability of currency crisis occurrence, exchange rate regimes, political stability, and CO₂ has been the subject of considerable debate in recent years. It is of great interest to assess how exchange rate arrangement CO₂ and political stability will affect the probability of a currency crisis? The literature is not clear on these issues and provides mixed results.

Many economists believe that a fixed exchange rate is more likely to cause a currency crisis, while others believe that a floating exchange rate is better at predicting currency crises. The relationship between the exchange rate regime and the likelihood of a currency crisis has been empirically studied by several researchers. According to Ghosh et al. (2015), when hard fixed exchange rates are used instead of floating exchange rates, macroeconomic vulnerability is dramatically increased. According to Hsing (2017), 80% of economies are skewed toward a fixed exchange rate. He also discovered that 40% of countries use limited fixed exchange rates to satisfy their deficit and inflation targets. Over the course of the financial crisis, Levy-Yeyati and Sturzenegger (2016) analyzed how the number of floating regimes expanded. Pegged exchange rates are one of the better options for low-income nations, but fixed exchange rate regimes are also recommended. Most IMF economies are classed as fixed exchange rate regimes with realignment, whereas those designated as floating exchange rate regimes intervene in the exchange market as usual. Shambaugh (2004) employed a dataset of 27 years and a sample of 100 developing and industrial economies; he used de facto coding to split the countries into pegs and non-pegs. Most governments that announce floating currency rates are implemented, according to him, while some economies mislead regimes.

Many academics argue that fixed exchange rate regimes have lower exchange rate volatility and are more likely to increase trade. The floating exchange rate regime, according to Mussa (1986), is more related to real exchange rate volatility, whereas the fixed exchange rate regime is less volatile in the real exchange rate regime. According to Kenen and Rodrik (1986), a stable exchange rate system encourages commerce, while exchange rate volatility discourages it. Aristotelous (2001) disagreed with these findings, claiming that the country’s trade policy has no impact on exports. Bacchetta and Van Wincoop (2000) proposed a novel strategy, arguing that establishing a fixed exchange rate regime does not guarantee increased commerce; it depends on how the exchange rate regime is administered.

Some of the countries affected by the 1997 financial crisis adopted floating exchange rate regimes to accomplish inflation targeting. Those countries targeting inflation as a monetary policy framework, according to Mishkin (2004), are targeting inflation and intervening in the foreign currency rate market to sustain the regime, which is in opposition to the targeting inflation model.

The pegged exchange rate regime to the US dollar is a better strategy for attracting international investors since it allows them to swiftly assess their return on investment due to less fluctuation. Furthermore, for those with a large amount of foreign funds, pegging the exchange rate is a fantastic question. Local inflation pressures can be reduced by tying exchange rates to low-inflation currencies.

Using extreme value theory tools, Haile and Pozo (2006) looked at a dataset of 35 nations to see how the exchange rate regimes selected by countries affect the chance of a currency crisis. The relationship between trade and currency unions is investigated by Persson (2001). Lin and Ye (2007) looked at inflation targets and policy evaluation, while Glick et al. (2006) looked at the link between capital account openness and currency crises. Faiz et al. (2021) examine the exchange rate misalignment from 1991 to 2020 find that the mean and variance of each regime are highly significant and show that undervaluation episodes have low mean and high volatility while overvaluation have a high mean and low volatility. Purwono et al., (2018) examine the condition of deficit which happen in imports and exports, manufacture goods and oil industries, they focus on the impact of exchange rate volatility on current account deficit, they find that the depreciation increase the surpuls to current account deficit. Comelli (2014) demonstrated that a parametric (EWS) early warning system utilizing a probit model is far superior to a non-parametric (EWS) early warning system following the Kaminsky, Lizondo, and Reinhart (KLR) technique in comparative research on currency crisis forecasting.

2.2. Political Stability and Currency Crises

Poor economic and financial policies are more likely to be adopted when political stability is weak and unstable. These explanations include not only the fact that a weak political system increases the likelihood of currency crises but also the extra effect that unstable political systems have on the relationship between exchange rate regimes and currency crisis occurrences. Meanwhile, we should avoid including measures of political stability in our models when testing currency crises and confirming the interaction affects between political stability and exchange rate regimes. There is well-established evidence that reduced political stability and poor government institutions make currency crises more likely. In general, less stable political governments create a toxic environment in which to discuss government goals and policies. Officials were thought to be unable to implement policy adjustments that would reduce market uncertainty, causing economic volatility.

The literature on the currency crisis, both empirical and theoretical, has been reviewed extensively. As an explanatory variable, a subset of the literature on political stability variables was used. Bussire and Mulder (2000) and Bernhard and Leblang (2000) found political events to be primary variables in their research (2002). Eichengreen et al. (1995) found how the political variables relevant to constant macroeconomic fundamentals caused the probability of currency crisis. The dataset consists of 20 industrial economies from 1959 to 1995. They examined the relationship of past and future governments’ wins and losses based on exchange rate episodes. In general, they fail to find out the link between political variables and exchange rate regimes. Klein and Marion (1997) found that speculative attacks may be one of the reasons which caused at the end being peg exchange rate by using political variables. However, the irregular transfers are statistically related to the termination of the peg exchange rate.

Bussire and Mulder (2000) examine four variables of political instability on economic vulnerability and currency crisis. Leblang (2001) studied developing economies found that speculative attacks are rare during elections, and unified governments are positively associated with defending against attacks. Relevant literature suggests that currency crisis is generally related to country risk but in real political risk. Reinhart and Rogoff (2004) studied the relationship between currency crisis and sovereign debt found that sovereign default plays a keen role in sovereign risk rating departments. They confirmed that risk rating is a poor initiative to predict currency crises.

The World Bank indicators were used for government’s effectiveness and technical equality Kurtz and Schrank (2007). Some other investigation was used for the govern- ment’s stabilities. Chiu and Willett (2020) examined 56 countries from 1995 to 2015 found that stable political governments with controls of inflow reduce the likelihood of currency crisis, while unstable political governments with controls on outflow increase the likelihood of currency crisis. According to Zia et al., (2021), fixed exchange rates and capital restrictions in countries with less political stability lessen the risk of currency crises, whereas floating exchange rates and capital controls in countries with political instability raise the risk of currency crises. They also discovered that floating exchange rates combined with sustained political stability lower the risk and probability of currency crises.

2.3. Carbon Dioxide and Currency Crises

For decades, global CO₂ emissions from cement manufacture and fossil-fuel contribution have been increasing as part of worldwide efforts to combat climate change. Previous crises, such as the 1973 oil crisis, the 1979 US loan and savings crisis, and the 1990 fall of the former Soviet Union, reduced the global growth of carbon dioxide emissions for several years. The impact of the 2008 financial crisis on CO₂ emissions was minimal. Constant growths in carbon dioxide emissions, and even much higher growth in the future, have raised numerous concerns about meeting the aim of global warming of fewer than two degrees centigrade (Friedlingstein et al., 2014; Rozenberg et al., 2015). Vu & Huang, (2020) examine the interaction between CO₂, political factors and economic variables in Vietnam since the revolution in 1986; they find that political risk has negative effect on environment, lasting negative environmental effects of economic growth, trade openness and increase electricity consumption.

It’s fascinating to compare the impact of the currency crisis and the impact of continuous global CO₂ emissions after and before the financial crisis. The input and output tables were used in the structural decomposition study Wang et al., (2017). SDA or other variables like energy intensity, production recipe, population growth, and ultimate demand structure can be used to break out changes in CO₂ emissions. The literature argues that more broad use of SDA to determine the pilot force behind increases in carbon dioxide emissions of an area or country should be pursued.

Feng et al. (2015), Yamakawa and Peters (2011), Baiocchi et al. (2010), Arto and Dietzenbacher (2014), Malik and Lan (2016) and Hoekstra et al. (2016). The SDA, which consists of worldwide multi-regional input output tables, can incorporate more than just the driving force behind carbon dioxide emissions increase. Changes in global trade patterns of both final and intermediate items can be found based on emission intensity, final demand, and production recipe (Wiedmann, 2009; Arto & Dietzenbacher, 2014; Malik & Lan, 2016). The increase in carbon dioxide emissions following the financial crisis in 2008–2009 is explored in detail. In other words, in the event of a currency crisis, we should concentrate on carbon dioxide and examine the connecting and connection impacts of political stability and exchange rate regimes. Less stable governments would be more effective at enforcing fixed exchange rates. As a result, we propose the following three theories.

H1: Currency crisis increases the CO2 emission.

H2: Fixed exchange rates reduce the currency crisis risk in a stabilized government.

H3: Less stable government has more risk in floating exchange rates.

3. Data and Methodology

3.1. Data Sources

We use annual data from 1996 to 2020 for South Asian countries. Our primary dependent variable is currency crisis based on EMP Eichengreen et al.’s (1995) approach. For the exchange rate regime, we used the index of Levy-Yeyati and Sturzenegger (2016). Use one-year window threshold standard deviations as is expected in the previous literature. For political stability, we used the World Bank data worldwide governance indicators such as political stability variables, control of corruption, government effectiveness, regulatory quality, rule of law. For macroeconomic variables export, interest rate, and CO₂ we used the World Bank WDI dataset.

3.2. Defining Currency Crises

A currency crisis is defined as large fluctuations in exchange market pressure recorded in an index that is the average weight of annual exchange rate changes. We employ a minimum depreciation rate rise of 10% over the previous year and a depreciation rate of less than 10% over the previous year. For crisis episode 1, we utilize binary numbers, and for no crisis 0, we use yearly data analysis observations. Table 1 show how annual data for the exchange rate pressure index was used to identify every annual occurrence of currency crisis for each country using South Asian seven economies as an example.

Table 1: Details Summary of Variables

3.3. Models Specification

Many rounds of probit regression utilizing panel models were used in this study to identify the interactions between the exchange rate regime, political stability, and CO₂ with some macroeconomic factors, as well as the likelihood of a currency crisis.

Our model of study is defined as:

Pr(Crisis_i,t=1) =  β₀ + β₁Float_i,t-1 + β₂PSCC_i,t-1 + β₃PSGE_i,t-1 + β₄PSRQ_i,t-1 + β₅PSRL_i,t-1 + β6CO_2i,t-1 + μi,t         (1)

Pr(Crisis_i,t=1) =  β₀ + β₁Fix_i,t-1 + β₂PSCC_i,t-1 + β₃PSGE_i,t-1 + β₄PSRQ_i,t-1 + β₅PSRL_i,t-1 + β6CO_2i,t-1 + β7EX_i,t-1 + β8IR_i,t-1 + μi,t        (2)

The data used for this study is secondary, and the dataset is derived from different sources. A currency crisis is a dependent variable; independent variables include fixed exchange rate shown in (Fix), political stability (PS), the sum of corruption control (PSCC), and government effectiveness is (PSGE), regulatory quality (PSRQ), and the rule of law (PSRL), carbon dioxide (CO₂) and some macroeconomic variables export (EX) and interest rate (IR).

Pr(Crisis_i,t=1) =  β₀ + β1PSCC_i,t-1 + β₂PSGE_i,t-1 + β₃PSRQ_i,t-1 + β₄PSRL_i,t-1 + β₅CO_2i,t-1 + β6EX_i,t-1 + β7IR_i,t-1 + μi,t ​​​​​​       (3)

​​​​​​​​​​​​​​Pr(Crisis_i,t=1) =  β₀ + β₁Fix_i,t-1 + β₂Float_i,t-1 + β₃PSCC_i,t-1 + β₄PSGE_i,t-1 + β6PSRL_i,t-1 + β7CO_2i,t-1 + β8EX_i,t-1 + β9IR_i,t-1 + μi,t​​​​​​       (4)

The β₀ are coefficients of dependent variables, µ is an error term with a standard distribution, i.e., zero mean and constant variance, i denote cross-section, and t denotes time panel. We have calculated the currency crisis as per the approach of Eichengreen et al., (1995). For exchange rate regimes, we use the index of Levy-Yeyati and Sturzenegger (2016).

Government stability control of corruption (PSCC) is the first variable, followed by Political stability government effectiveness (PSGE), Political stability regulatory qualities (PSRQ), and political stability rule of law (PSRL) (PSRL). When it comes to macroeconomic variables (exports of goods and services (annual percent increase), deposit interest rate (percent), and CO₂ emissions (thousand metric tons). The panel data was collected from the World Development Indicators (WDI) online available on the World Bank’s website for the period 1996–2020.

3.4. Panel Unit Root Test

To eliminate typical error influence concerns, the panel unit root test is utilized for all selected variables in the study; we use Levin- Lin- Chu, Breitung, and Im-Pesaran-Shin for the test. The test verifies that the data is not susceptible to suspicious regress. Because it has more influence and a standard asymptotic distribution, the panel unit root test can solve the problem. The evaluation should make consistent recommendations. Furthermore, the unit root test panel data is more effectively related to the test. Unit root test as first order auto-regression components equation

X_it = ρ_iX_it–1d + Y_it γ_i + ε_it       (5)

Where X_it is used for previous value X_it–1 and Y_it γ_i used for panel specification means in case of fixed effects that is Y_it =1 or Y_it = (1, t), used for liner trend when time trend is specified, or this value finished when test allow for non constant and ε_it symbolize used for the fixed error term.

4. Empirical Results and Discussion

Table 2 describes the details of the descriptive statistics. It describes the mean, standard deviation, minimum and maximum values of dependent, independent, and control variables and observations. The mean of crisis is 0.662: minimum value is 0: and the maximum value is 1: for exchange rate regime mean 2.01 min 1: max 3: political stability control of corruption mean is –0.351: min –1.49: max 2.25: while, political stability government effectiveness mean –0.278: min –1.61: max 0.982: (PSRQ) mean –0.471: min –1.31: max 1.02: political stability rule of law mean –0.292: min –1.04: max 0.742: carbon dioxide mean 251634: min 582777: max value is 2700000: export mean –18.8: min value –367: max value is 85.6: and last variable interest rate mean value is 6.34: min value is 1.63: max value is 11.7.

Table 2: Descriptive Statistics

Table 3 shows the results of the punitive unit root test; three tests are used to determine the level of stationary and non-stationary variables. Three tests are used: Breitung, LLC, and IPS. Political stability and corruption control are non-stationery at LLC and IPS, but stationery at Breitung. Similarly, at is non-stationary, but LLC and IPS, CO₂ is non-stationary, but LLC and Breitung are.

Table 3: Unit-Root Test Results

Significance levels: * 10%, **5%, ***1%.

Table 4 shows the regression findings for the South Asian nation’s dataset from 1996 to 2020, using panel data. For this study, we employed four models; the floating exchange rate is statistically significant and positively associated with a currency crisis in model one. Stability in politics Currency crises has a significant and negative relationship with government effectiveness and regulatory quality. Political stability, on the other hand, has a statistically significant and positive relationship with crises. Similarly, in model one, CO₂ has a significant and positive relationship with currency crises; our H₁ shows that carbon dioxide emissions contribute more during a currency crisis.

Table 4: Regression Estimation

Note: Standard errors are presented in columns (1) to (4) in parentheses robustness check by probit model. Significance levels: * 10%, **5%, ***1%.

Fix exchange rate regime is statistically significant in model 2 and is connected with a currency crisis in a negative way. Control of corruption by political stability variables has a negative relationship, but it is statistically insignificant. Stability in politics A currency crisis has a significant and negative association with government effectiveness. Similar to (PSRQ), there is a statistically significant and negative link between crises and (PSRQ). Political stability, on the other hand, is statistically significant and positively connected with currency crises. CO₂ is positively connected with a monetary crisis and is significant in model 2. While export is statistically significant and positively associated with macroeconomic variables, H₂ suggests that a fixed exchange rate combined with political stability contributes less to currency crises.

Similarly, the interest rate is a crucial factor in the currency crisis and is positively related to it. The political stability variables (PSCC) are adversely associated with the crisis in model 3, although the relationship is not significant. Other political stability variables (PSRQ) regulatory quality and (PSGE) government effectiveness, on the other hand, are statistically significant and adversely related to currency crises. Political stability and rule of law (PSRL) are, on the other hand, positively associated with a currency crisis. The currency crisis is statistically significant and positively related to CO₂, export, and interest rate. The fixed exchange rate has a significant and negative relationship with currency crises in model 4. The floating exchange rate system is statistically significant, and it has a positive correlation with crises. In the meantime, political stability factors (PSCC) have a negative but not statistically significant link with currency crises.

Government effectiveness is statistically significant and inversely connected with political stability. The currency crisis has a negative relationship with PSRQ, which has a significant value. Political stability, on the other hand, H₃ clearly shows that a floating exchange rate with less stability adds more to the currency crisis; rule of law is statistically significant and positively connected with a currency crisis. As a result, our research proved all three hypotheses. The link between CO₂ and currency crises is positive and important. While both export and interest rates are positively related to a currency crisis, neither is statistically significant. South Asian countries with seven economies were included in this study. Model one has a chi2 test of 37, model two has a chi2 test of 47, model three has a chi2 test of 45, and model four has a chi2 test of 59.

5. Conclusion

This investigation focuses on the exchange rate regime, political stability, and CO₂ influencing the currency crisis, especially in South Asian countries; data from 1996 to 2020 annual observations. We used the Eichengreen et al. (1995) model to identify the currency crisis in South Asian countries. We adopted the panel probit model to identify crises for analyzing currency crisis periods. Countries that adopt a fixed exchange rate with political stability variables Government effectiveness and Regulatory quality have less likelihood of a currency crisis. While floating exchange rate and political stability Rule of law and CO₂ have more likelihood of a currency crisis. Our key findings imply that variables such as the floating exchange rate are the most important causes and vulnerabilities to currency crises. The key variables in the currency crises are rule of law, CO₂, export, and interest rate. Fixing the exchange rate, ensuring government effectiveness, and ensuring political stability Currency crises are less likely in countries with high regulatory quality. Future research will focus on energy usage and capital controls for probable political economics reasons that are also worth investigating.