Econometric Assessment of Institutional Quality in Mitigating Global Climate-Change Risk

: Background: Environmental deterioration is the alarming situation that results from rapid urbanization and development. The rising temperature and climate volatility are accounted for by the massive carbon dioxide (CO 2 ) emissions. The research on climate-change mitigation is trying to curtail the situations before they become irreversible and unmanageable. This study explores the role of institutions in mitigating climate change by moderating the impact of environmental quality on climate change risk. Methodology: Global data sets have been collected from world big data depositories like the World Economic Forum (WEF), the World Development Indicators (WDI), and the International Country Risk Guide (ICRG). Countries that are listed in WEF were used as the sample of the study. An analysis was based on 114 countries that are based on the availability of data. For estimation, descriptive statistics, correlation analysis, change effects, and a Panel Feasible Generalized Least Squares (FGLS) model were used for estimating the results. Results: The global assessment indicates that CO 2 emissions increase the climate risk, but its impact can be reduced by increasing the quality of institutions. Additionally, an increase in renewable energy consumption and economic growth reduces the climate risk. Implications: It is an instrumental study that empirically investigated the role of institutions in reducing climate risk by moderating CO 2 emissions. The results of this study will help policymakers to formulate policies regarding environmental protection.


Introduction
Climate presents as a "hazard" and a "resource." "Climate resource" is the characteristics of climate that put constraints or allow activity. For example, seasonal temperature cycles affect the heating/cooling demand of energy, and rainfall patterns affect the production of crops. Where this resource is excessively used, the occurrence of some discrete events present itself as hazardous consequences. These events are drought, windstorms, floods, hot and cold spells discussed in terms of magnitude, frequency, duration, likelihood timing, spatial extent and variability [1].
Environmental deterioration is an alarming situation that results from rapid growth. Human exploration of things and non-regulated activities resulted in abrupt changes in the but also increases political instability. A 1 • C increase in the temperature in a year will decrease the economic growth in these countries by 1.1% points on average [16]. The World Bank launched the Economics of Adaptation to Climate Change (EACC) in 2009 to study the adaptation cost of climate change for developing countries. The adaptation cost to stabilize the temperature at 2 • C by 2050 was USD 70 to 100 billion per year for the years 2010-2050 [17].
Many countries are paying attention to the quality of the environment. For this purpose, the USA, the EU, and China are focusing on reducing CO 2 emissions. They have formulated their policies with environmental protection by reducing carbon emissions. Due to abrupt climate changes, many nations have added the objective to raise renewable energy as part of their policies [18]. The efforts to stabilize the global temperature at 2 • C with 0.66 probability require that cumulative carbon emissions 2000 to 2500 should not exceed the median estimate of 590 pentagrams of carbon (PgC) (200-950 PgC range). If a temperature target of 2 • C is to be achieved with a probability of 0.9, then allowable cumulative carbon emissions are 170 PgC (−220-700 PgC range) [19].
Renewable energy consumption reduces environmental pollution. Renewable energy is derived from natural resources that are repetitively renewed. Different renewable energy sources are solar, hydropower, biothermal, and wind [20]. The literature has revealed the positive role of renewable-energy consumption in mitigating climate change [18,21]. Regulatory authorities play an essential role in the mitigation of climate change. Different institutions set various standards and codes to reduce environmental pollution [22].
The problem of global warming cannot be resolved without government regulations and policies to protect the environment. Government's costly policies rely on the public that supports government spending to protect the environment. This relationship is dependent on the quality of government where institutions are fair, non-corrupt, and effective [23]. Climate-change policies, projects, and programs either control the greenhouse gases and carbon emissions to mitigate the impact of climate change or create necessary conditions for people to adapt to climate risk and variability [24]. Public policies play an essential role in mitigation or adaptation to climate change [25].
First, to investigate the role of institutions in reducing climate risk by controlling carbon emissions, institutions play an essential role in the mitigation of climate risk. This study highlights the importance of institutions in reducing the environmental pollution that brings abrupt climate changes. For this purpose, this study used the panel-data FGLS method, and the sample comprised 114 countries at risk of climate change. The generalized estimates will be a stepping stone in developing a cross-national strategy to mitigate the climate-change risks.
The structure of the article is organized as follows. The literature of the previous studies is discussed in Section 2. Section 3 will cover the theoretical framework and methodology of the study. The results of the estimated models are presented in Section 4, while Section 5 will cover the conclusion and policy recommendation of the study.

Literature Review
There are empirical studies available that have focused on the regional antecedents of climate-change risk. Being regional reduces their generalizability for national and international policy makers [26,27]. In order to develop a generalizable model, multicountry macroeconomic determinants must be explored. There are several studies that have introduced the macroeconomic variables against climate change, and the most important of them are discussed in this study [28][29][30][31].

Carbon Emission and Climate Change
Carbon emission is closely related to climate change; it relates to black carbon or the carbon-sink effect. Although these emissions produce pollution in the environment, they are also responsible for global warming, the ecological footprint, and abrupt climate changes. A reduction in greenhouse gases and emissions is the only way to reduce the risk of climate change. Zickfeld et al. [19] set the emissions targets as a way to reduce the climate risk. They adopted the risk-management approach to present the carbon-cycle modelling. Their results indicate that a temperature target of 2 • C can only be achieved if CO 2 emissions are removed from the atmosphere.
Molina et al. [4] discussed the abrupt changes in climate due to CO 2 emissions. They used the Montreal Protocol to reduce the amount of CO 2 emissions, and besides reducing carbon emissions, they proposed the fastest strategy that brings the fastest climate-change response. The implementation time of this strategy was 5-10 years, and this plan will take a decade or earlier to bring a climate response. The literature also points out that an increase in the CO 2 concentration in the economy is highly correlated with global warming [32,33], which is the major driver for climate-related hazards for the ecosystems [34] and standard of living [35,36]. Hence, in developing any model related to climate-change risk, CO 2 content in the environment must be considered as an important indicator.

Institutional Quality and Climate Change
According to Starker [22], regulation plays a vital role in climate mitigation, like codes in different mandatory standards. Abduqayumov et al. [37] investigated the impact of institutional quality on the environment in the 15 post-Soviet countries from 2001 to 2017 by using the Generalized Method of Moments (GMM) approach. The findings of this study indicate a positive impact of institutional quality on the environment quality.
Problems that are related to climate change cannot be solved without the regulation of the government [2,38]. Kulin and Johansson Sevä [23] highlighted the importance of institutions' quality in implementing the government's environmental-protection policies.
Arnell et al. [1] calculated the policy-relevant indicators responsible for changing the climate risk in the UK in the health, transport, water, floods, energy, and agriculture sectors. They adopted the approach that focuses on climate-change changes in risk components by using climate projection UNCP18. The finding of this study indicates that climate risk will increase in the absence of adaptation. Extreme heat will also increase and affect health, productivity, infrastructure, etc. So, in order to incorporate the adaptability effect of institutional quality, it has been used as a moderator to reduce the harmful effects of CO 2 emissions on the economy [39,40].

Renewable Energy and Climate Change
Renewable energy and climate change are interrelated with each other. The literature has revealed the positive impact of renewable energy on the mitigation of climate-change effects. Renewable energy reduces the carbon emissions in the atmosphere and helps increase the standard of living [41,42] and reduce the resource dependency. Therefore, it is used as a policy tool to mitigate climate change, and it plays a very important role in adaptation strategies. Eitan [43] examined whether the policymakers in Israel should focus on renewable energy as a mitigation strategy or an adaptive strategy. The results indicate the minor impact of Israel on the world carbon emissions, so policymakers should promote renewable energy as a mitigation strategy rather than an adaptive strategy.
Mathiesen et al. [18] analyzed the model of 100-percent renewable energy for Denmark by 2050. Its results indicate the positive impact of energy-saving and renewable energy on the mitigation of climate change. In addition, this system will generate employment that has positive socio-economic effects. Lima et al. [21] reviewed the government strategies to promote the use of renewable energy in Brazil to mitigate climate change. Expansion in the use of renewable energy in Brazil reduces greenhouse gases' emission.
Hence, while studying the antecedents of climate change, renewable energy policy plays an important role. The level of renewable energy may define how other policies are abating climate change.

Economic Growth and Climate Change
Climate change causes serious consequences and reduces the growth of countries. At one side, there are several studies that advocate that an increase in economic activity produces friction, which is observed in the form of the carbon footprint and global warming [2,44,45]. At the same time, high growth in countries reduces the climate risk. Fankhauser and Tol [46] used different approaches to investigate the link between climate change and economic growth. They investigated the dynamic effects of saving and the accumulation of capital. Theoretical analysis suggests that net saving will decrease because of climate change that reduces physical capital. With constant saving, reducing output due to climate change will lower future welfare, decreasing investment and economic growth. If saving is endogenous, forward-looking rational agents can change their saving behavior to reduce future climate change.
Some studies revealed the effect of high growth in the mitigation of climate risk. Thus, growth can cushion the negative consequences of climate change. Economic growth is an essential factor that builds the adaptive capacity of people. The adaptive capacity that reduces the adverse impact of climate change depends on the economic status. Developing countries are more vulnerable to climate change than developed countries with high adaptive capacity [47]. Bowen et al. [13] investigated the link between climate change and economic growth. Economic growth decreases the vulnerability of climate change. Different growth policies like access to finance and investment to enhance skills decrease vulnerability to climate change.

Population Density and Climate Change
Samson et al. [48] investigated the relationship between climate change and the human population. For this purpose, they developed a global index of the predicted impact of change in climate on the population. The findings of this study indicate the negative impact of climate on humans in different regions of Africa, Southeast Asia, Central America, the Arabian Peninsula, and Central South America. These regions are away from high-latitude areas where the impact of climate change is high.
Ahmadalipour et al. [49] assessed the drought risk in Africa during three future periods between 2010-2100. The results indicate that drought risk will rise in future, and control of population growth can mitigate the drought risk.
Population density is linked with climate risk. Therefore, it can be used to reduce climate hazards in the future, such as droughts [50]. Baur et al. [51] investigated the 62 cities of Europe to analyze the importance of population density in reducing the CO 2 emissions in the environment and in mitigating climate change. This study indicates that in European urbanities, carbon emission increased with household size and household wealth reduction.
Lastly, empirical studies have underexplored the linear socio-economic determinants of climate-change risk for a data set of 114 countries. This study also interacts the role of institutional quality with CO 2 emissions to assess the regulatory efforts in limiting the CO 2 emissions and its effect on climate-change risk, while controlling for contextual factors like renewable energy, economic growth, and population density. This macroeconomic assessment based on secondary data will provide the guidelines to policymakers to abate climate-change risk.

Theoretical Framework
Carbon emissions and greenhouse gases cause pollution in the environment, but these emissions are also responsible for high temperatures and unpredictable changes in the climate. Abrupt climate changes cause extreme events and climate-change risks (link shown in Figure 1).
Carbon emissions and greenhouse gases cause pollution in the environment, but these emissions are also responsible for high temperatures and unpredictable changes in the climate. Abrupt climate changes cause extreme events and climate-change risks (link shown in Figure 1). Climate change causes negative consequences on the economic growth of the countries. In addition, climate change has a severe impact on the productivity of labor. There are two main reasons for the reduction in productivity. One is through the health issues of labor caused by climate change, and the second is the direct effect of climate on productivity due to abrupt changes in weather, i.e., hot and cold weather [15].
Economic growth reduces the negative impact of climate change and its risk. However, it depends on the adaptive capacity of the people to deal with climate change. The adaptive capacity of people can only be increased by economic growth because it is linked with the development indicators like education, income, and quality of institutions [13]. The literature revealed that countries that mainly rely on such activities directly affected by climate change suffer due to climate risk. Renewable energy is used as a policy tool in the mitigation of climate change and adaptation capacity. The promotion of renewable energy can mitigate the impact of climate change [43].
Densely populated areas of low-income countries are affected mainly by a change in the climate. The impact can be reduced by developing the infrastructure in those areas. At the same time, the experience of middle-and high-income countries shows that highly urbanized populations and the structure of production can be developed with lesser climate risk [52]. Population density is associated with climate risk. Population density reduces the climate risk, i.e., droughts that affect nutrition and create health issues [50]. Climate change harms humans in the regions where the population primarily relies on the climate [48]. Figure 2 presents the connection between variables that are interlinked with each other and cause climate risk.  Climate change causes negative consequences on the economic growth of the countries. In addition, climate change has a severe impact on the productivity of labor. There are two main reasons for the reduction in productivity. One is through the health issues of labor caused by climate change, and the second is the direct effect of climate on productivity due to abrupt changes in weather, i.e., hot and cold weather [15].
Economic growth reduces the negative impact of climate change and its risk. However, it depends on the adaptive capacity of the people to deal with climate change. The adaptive capacity of people can only be increased by economic growth because it is linked with the development indicators like education, income, and quality of institutions [13]. The literature revealed that countries that mainly rely on such activities directly affected by climate change suffer due to climate risk. Renewable energy is used as a policy tool in the mitigation of climate change and adaptation capacity. The promotion of renewable energy can mitigate the impact of climate change [43].
Densely populated areas of low-income countries are affected mainly by a change in the climate. The impact can be reduced by developing the infrastructure in those areas. At the same time, the experience of middle-and high-income countries shows that highly urbanized populations and the structure of production can be developed with lesser climate risk [52]. Population density is associated with climate risk. Population density reduces the climate risk, i.e., droughts that affect nutrition and create health issues [50]. Climate change harms humans in the regions where the population primarily relies on the climate [48]. Figure 2 presents the connection between variables that are interlinked with each other and cause climate risk. these emissions are also responsible for high temperatures and unpredictable changes the climate. Abrupt climate changes cause extreme events and climate-change risks (li shown in Figure 1). Climate change causes negative consequences on the economic growth of the cou tries. In addition, climate change has a severe impact on the productivity of labor. The are two main reasons for the reduction in productivity. One is through the health issu of labor caused by climate change, and the second is the direct effect of climate on produ tivity due to abrupt changes in weather, i.e., hot and cold weather [15].
Economic growth reduces the negative impact of climate change and its risk. Ho ever, it depends on the adaptive capacity of the people to deal with climate change. T adaptive capacity of people can only be increased by economic growth because it is link with the development indicators like education, income, and quality of institutions [1 The literature revealed that countries that mainly rely on such activities directly affect by climate change suffer due to climate risk. Renewable energy is used as a policy tool the mitigation of climate change and adaptation capacity. The promotion of renewab energy can mitigate the impact of climate change [43].
Densely populated areas of low-income countries are affected mainly by a change the climate. The impact can be reduced by developing the infrastructure in those areas. the same time, the experience of middle-and high-income countries shows that high urbanized populations and the structure of production can be developed with lesser c mate risk [52]. Population density is associated with climate risk. Population density duces the climate risk, i.e., droughts that affect nutrition and create health issues [50]. C mate change harms humans in the regions where the population primarily relies on t climate [48]. Figure 2 presents the connection between variables that are interlinked w each other and cause climate risk.  Regulations can control extreme events. Institutional quality plays an important role to mitigate the impact of climate change. The literature revealed that the better institutions respond quickly to the problem as it arises. This quick mitigating response results in reducing the damage of output arising from climate shocks. These institutions also increase the adaptive capacity of people to deal with climate risk [13,16].

Model Specification
To investigate the role of institutions in reducing climate risk by controlling CO 2 emissions, a linear-panel-data model with moderation was utilized. This model conducts a spatial temporal assessment of empirical patterns of selected independent and depen-Sustainability 2022, 14, 669 7 of 13 dent variables to provide its marginal effects. Here, the climate-risk index was used as a dependent variable in the model, and CO 2 emissions, institutions, renewable-energy consumption, population density, and GDP per capita were used as explanatory variables in the model. The interaction term of CO 2 emissions and institutions was used to assess the moderating role of institutions. Although CO 2 emissions increase the risk of climate, institutions can mitigate its impact by controlling CO 2 emissions. Renewable-energy consumption, population density, and GDP per capita are transformed into natural-logarithm form.
The following is the parameterized equation, which linearly estimates the effect of independent variables on the climate-risk index for the selected empirical data.

Data Source
In order to investigate the impact of CO 2 emissions on climate risk, the climate-risk index was used as a dependent variable in the model. Its data were taken from Germanwatch. The data of explanatory variables, i.e., CO 2 emissions, renewable-energy consumption, population density, and GDP per capita were taken from WDI. The data source of institutional quality was ICRG. Countries that are listed in WEF were used as the sample of the study. An analysis was based on 114 countries. These countries were selected based on the availability of data. Table 1 presents the representation and transformation of variables.

Estimation Method
Different steps were adopted to obtain the empirical results of the study. Initially, descriptive statistics were estimated to check the mean and standard deviation of the variables. Then, the normality of the variables was checked by using the skewness and kurtosis test of normality. The correlation matrix and variance inflation factor were estimated in the next step to check the multicollinearity of the data.
This study resorted to the panel-data models, which have an inherit ability to account for the contemporaneous effects of estimates in the one cross section to other. The model that is being discussed asks for the data setup to allow the effects of one country to spillover to another. Such a setup was missing in past studies, which have focused on regional assessment. A commonly random or fixed-effect model were used in panel data, but they fail to account for the differences across countries. Finally, the panel FGLS method was used to find the empirical results of the study. It solves the heteroscedasticity problem in the data [53]. There are several studies that have used the generalization approach of panel data and then explored the country-specific estimates with the help of moderators [54][55][56][57]. This model was also used in assessing the vulnerability to climate change for 73 countries between 1998 to 2013 [58]. Further, Pedroni [59] states that the dynamic-panel data are only used if the data are more than 20 years per cross section. Table 2 is the first step to start any empirical investigation. It provides information about the variables mean, standard, median, and maximum and minimum values, etc. The values of Kurtosis and skewness show that most variables were non-normal. All the mean values of data except the mean value of CO 2 were greater than their standard deviation, which means that these variables were under-disbursed and CO 2 emission was over-disbursed.  Table 3 provides the results of a correlation matrix. None of the variables showed a very high correlation with other variables. The high correlation was 0.71, which was between GDP and Institutions. The multicollinearity of the data was checked through a variance-inflating factor. As the VIF of all the variables was less than 10, there was no multicollinearity problem in the data [60]. Its results are presented in Table 4.  Table 5 presents the results of the panel FGLS method. This model climate-risk index was used as a dependent variable. In contrast, CO 2 emissions, institutions, renewable-energy consumption, population density, and GDP per capita were used as explanatory variables in the model. In addition, the interaction term of CO 2 emissions and institutions was used in the analysis with the view that CO 2 emissions increase the climate risk. Still, institutional quality plays an essential role in mitigating the effect of CO 2 emissions and reducing climate risk. Standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

Estimation of descriptive statistics reported in
The empirical results show a positive association between carbon emissions and climate risk. These results indicate that a 1 unit increase in CO 2 emissions will increase the climate risk by 3.29 units. A 1-unit increase in institutions will increase the climate risk by 13.65 units.

Discussion
This study included the moderating role of institutions in abating the climate-change risk. The interaction terms of CO 2 emissions and institutions showed that an increase in CO 2 emissions and the quality of institutions will decrease the climate risk by 0.93 units. CO 2 pollution increases the climate risk, and institutional quality mitigation is supported in the literature [19,37,58]. Hence, when there is an increase in the institutional quality, it places a higher cost of CO 2 emissions in the society; hence, the economy resorts to other carbon-saving production measures. Second, a 1-percent increase in renewable-energy consumption will decrease the climate risk by 3.37 units. The inverse relationship of renewable energy with climate change is empirically supported because if its sustainability effects [18,21]. Third, a 1 percent-increase in GDP per capita will decrease the climate risk by 1.5 units. Economic growth decreases the vulnerability of climate change, as the developed countries have done by financing climate-resilient and sustainable systems [13]. All the variables were statistically significant. Figure 3 presents the relationship between CO 2 emissions and climate risk in the presence of institutional quality. Figure 3 indicates that when institutional quality is low, CO 2 emissions increase the climate risk, but high institutional quality decreases the climate risk by controlling CO 2 emissions. the variables were statistically significant. Figure 3 presents the relationship between CO2 emissions and climate risk in the presence of institutional quality. Figure 3 indicates that when institutional quality is low, CO2 emissions increase the climate risk, but high institutional quality decreases the climate risk by controlling CO2 emissions.

Conclusions and Policy Recommendation
Rapid development and human exploration of new things have deteriorated the alarming environment for the whole world [2]. Furthermore, rapid changes in the environment and discrete events like drought, rising sea levels, high atmospheric temperature, floods, etc. have worsened the situation. A high temperature lowers economic growth in developing countries as compared to developed countries. It causes severe consequences by lowering the productivity of the agriculture and industrial sector. Besides these effects, it reduces investment in poor developing countries and increases political instability [16]. CO2 emissions and greenhouse gases are responsible for these changes. If these emissions are not controlled properly, they can bring even worse situations that will be irreversible and unmanageable.
The current study highlights the importance of renewable energy, economic activity, and institutions in mitigating climate change. The estimated model provides guidelines in controlling global warming and, most importantly, the risks associated with climate change. Many countries have formulated policies regarding environmental protection, but there was a lack of studies providing a macroeconomic framework for them to follow. Hence, because of this, developing countries suffer more due to climate change because agriculture is a major profession in these nations and directly depends on climate change [13,14], and they have lower ability to mitigate the adverse conditions.
To investigate the role of institutions in moderating the impact of CO2 emissions on climate change, this study used the panel FGLS method as an estimation technique. This moderator setup in the panel data helps to explore the cross-country heterogeneities within the overall model with respect to the differences in the institutional quality. A sample is comprised of countries that are listed in the WEF. One-hundred fourteen countries Low CO2 High CO2 Climate Risk

CO 2 Emissions
Low Institutional Quality

Conclusions and Policy Recommendation
Rapid development and human exploration of new things have deteriorated the alarming environment for the whole world [2]. Furthermore, rapid changes in the environment and discrete events like drought, rising sea levels, high atmospheric temperature, floods, etc. have worsened the situation. A high temperature lowers economic growth in developing countries as compared to developed countries. It causes severe consequences by lowering the productivity of the agriculture and industrial sector. Besides these effects, it reduces investment in poor developing countries and increases political instability [16]. CO 2 emissions and greenhouse gases are responsible for these changes. If these emissions are not controlled properly, they can bring even worse situations that will be irreversible and unmanageable.
The current study highlights the importance of renewable energy, economic activity, and institutions in mitigating climate change. The estimated model provides guidelines in controlling global warming and, most importantly, the risks associated with climate change. Many countries have formulated policies regarding environmental protection, but there was a lack of studies providing a macroeconomic framework for them to follow. Hence, because of this, developing countries suffer more due to climate change because agriculture is a major profession in these nations and directly depends on climate change [13,14], and they have lower ability to mitigate the adverse conditions.
To investigate the role of institutions in moderating the impact of CO 2 emissions on climate change, this study used the panel FGLS method as an estimation technique. This moderator setup in the panel data helps to explore the cross-country heterogeneities within the overall model with respect to the differences in the institutional quality. A sample is comprised of countries that are listed in the WEF. One-hundred fourteen countries were selected based on the availability of the data. Its results indicate that CO 2 emissions increase the climate risk, but its impact can be reduced by increasing the quality of institutions. Here, the direct effect of institution was positive, but the moderating effect was negative; this shows that with the increase in institutions, it creates ease an of doing business that increases global warming-but with the formation of regulations, the economic activities are transformed to be environment friendly, thus reducing climate-change risk. Other results of this study indicate that an increase in renewable-energy consumption and economic growth reduces the climate risk. All the variables were significant, and its outcomes were complied with the literature.
This study proposed that countries listed in the WEF should focus on the quality of institutions, improve the adaptive capacity, and encourage the use of renewable energy. Coupled together, they will help in regulating the economic activity by using environment-friendly energy in order to engage in a combined effort in reducing the climate-change risk.
This study provided estimates that are valid for the selected countries and the selected time period; hence, estimation in extended data must also suffice for the linear-regression assumptions. Future studies should also explore different sub-dimensions of climate-change risk and institutional quality and split the sample into countries in terms of similar climate-change extreme events and hazards to see the effectiveness of institutional quality in mitigating climate-change risk.