Review of Economics and Development Studies, Vol. 8 (2) 2022, 97 - 109 97 Does Institutional Quality Improve Environmental Quality? New Evidence from NARDL Approach Muhammad Yasin Abid a, Muhammad Tasnim Khan b, Hafeez ur Rehman c a Ph.D. Scholar, Department of Economics and Statistics (HSM), University of Management Technology, Lahore, Pakistan Email: f2021330007@umt.edu.pk b Ph.D. Scholar, Management Sciences, Dr. Hasan Murad School of Management, University of Management Technology, Lahore, Pakistan Email: tasnim.khan@umt.edu.pk c Professor, Department of Economics and Statistics (HSM), University of Management Technology, Lahore, Pakistan Email: hafeez.rehman@umt.edu.pk ARTICLE DETAILS ABSTRACT History: Accepted 28 April 2022 Available Online June 2022 The current research intends to look at the asymmetrical influence of institutional quality (IQ) on carbon emissions (𝐢𝑂2e) by incorporating additional variables i.e., trade openness (TO), population growth (PG), and energy use (E) over the period 1980-2020. The current study used nonlinear ARDL to demonstrate the nonlinear influence of IQ on 𝐢𝑂2e. The empirical finding suggests that positive fluctuation in institutional quality considerably improves the environmental quality in Pakistan in the short and long run. At the same time, the outcomes show that negative fluctuations in IQ lead to considerably contributed to 𝐢𝑂2e in long run. GDP and E are positively connected with 𝐢𝑂2e. The policy makers could need to enhance the institutional quality leads to attaining the long-term ecological objectives. Β© 2022 The authors. Published by SPCRD Global Publishing. This is an open access article under the Creative Commons Attribution- NonCommercial 4.0 Keywords: Institutional Quality, Carbon Emissions, Energy Use, NARDL, Pakistan JEL Classification: B52, Q53 DOI: 10.47067/reads.v8i2.439 Corresponding author’s email address: hafeez.rehman@umt.edu.pk 1. Introduction The institutional economics research undoubtedly recognized that institutional quality (IQ) is one of the most considerable elements affecting OG as the founding works of Williamson (1989) and North (2018). Institutions develop regulatory norms and policies in public by enacting appropriate restrictions. In general, IQ is connected to domestic institutions' policies that form the legal and cultural framework within which socioeconomic activity occurs. Consequently, it demonstrates the Review of Economics and Development Studies, Vol. 8 (2) 2022, 97 - 109 98 government's capacity to develop and enact policies and regulations that stimulate the private sector, enhance contract execution quality, safeguard property rights, maintain a strict rule of law, and shield institutions from political interference. On the other hand, weak governance supports the private sector, resulting in bribery, inefficient bureaucracy, and low environmental restrictions. Furthermore, institutions may have an influence on the environment by enacting policies such as carbon taxes, feed-in tariffs, and the abolition of financial support in EC. (Ellis, 2010; Wong et al.,2010). Thus, a country's institutional quality influences its energy demand by influencing its level of energy efficiency. It could be accomplished precisely vie reducing energy consumption (EC) or indirectly through green technological advancement. Further, the study by Shah et al. (2020) observed that IQ is a necessity for ensuring ecological preservation. This study indicates that a gradual switch to green energy, accompanied by better strategies and high-tech, is essential for long- term development without jeopardizing developing countries' financial well-being. Institutional quality also significantly impacts regional energy inequalities through the efficient financial market system (Yao et al., 2020). Reduced energy inequities between and within regions contribute to environmental quality since nations are cross-sectionally reliant on various social, economic, and cultural aspects. Consequently, accounting for cross-sectional dependency and variability among nations is crucial. As a result, institutional quality is critical in energy transition and energy efficiency, which influence energy consumption on GHG emissions, notably CO2 emissions, which account for 76% of total GHGs (Hsu et al., 2017). Hence, developing countries like Pakistan face numerous challenges in boosting output growth (OG). Expanding economic activity necessitates increased EC, and less developed economies have consumed a huge amount of fossil fuels. It is rapidly draining, and their rates are volatile. Also, the price fluctuations hurt developing countries and are confronted with the issue of IQ (Bellakhal et al., 2019). To enhance social and economic conditions, the government must respond to the populace's needs (Shah et al., 2020). Additionally, EC boosts in countries with higher institutional quality (Adams et al., 2016). As a result, OG infers a different impact on 𝐢𝑂2 e emissions in the developing and developed worlds. Besides, the role of IQ in economic development as well as ecological problems is still being debated, and it requires serious consideration. To conclude, this study intends to scrutinize the asymmetric effect of IQon 𝐢𝑂2efrom 1984- 2020 in Pakistan. Besides, the influence of the rule of law on the tipping point at which economic development enhances environmental quality. The primary contribution will be to highlight the relevance of the rule of law in controlling ecological degradation by examining this institution's direct and indirect consequences. Our results emphasize the relevance of institutional enforcement for environmental protection and contribute to establishing strategies for sustainable development in Pakistan. The remaining sections are organized as follows: "Literature survey" discussed in the ahead section, "Data, Methodology and econometric technique" have been elaborated in section 3, "Empirical results and discussions" Findings and results in the discussion β€œdescribed in section 4. And the final section explores the Concluding remark and policy recommendation. 2. Literature Survey We would look at two techniques for experimentally exploring the association between𝐢𝑂2e and OG in the first strand of inquiry. Like an outcome, this method focuses on inferring the existence of the Review of Economics and Development Studies, Vol. 8 (2) 2022, 97 - 109 99 Environmental Kuznets Curve (EKC) theory. It is contended that the relationship between output growth per capita and𝐢𝑂2e shows a bell-shaped curvature. Besides, the result indicates that output growth and𝐢𝑂2e rise in the initial phase. Beyond a certain point, it becomes a decline in carbon emissions against the rise in OG (Grossman and Krueger, 1991, 1995). The empirical findings of testing this concept have always been debatable. However, solid environmental regulations are formed as the economy progresses, and pollution-free technology improves ecological quality. Several cross-national and country-specific research has previously been conducted to investigate this notion. For example, Ahmad et al. (2017) used the autoregressive distributive lag technique to investigate the non-linear relationship between output growth per capita and 𝐢𝑂2e. Furthermore, Panayotou, (1993) found similar results that verified the bell-shaped EKC hypothesis. The findings verify the occurrence of EKC in Croatia. A few empirical past studies were conducted to study the role of IQ in the OG -𝐢𝑂2e. Solarin et al. (2017) verified the EKC theory in India and China. Their results validated the EKC hypothesis in the nations analyzed. Tamazian and Rao (2010), for example, investigated the impact of IQ on environmental protection in 24 transition nations from 1993 to 2004 using the GMM estimating approach. The empirical turns out of this research indicated the relevance of IQ in enhancing environmental quality in the nations studied. Furthermore, another study by Lau et al. (2014) evaluated the influence of IQ in the OG-𝐢𝑂2e nexus from1984-2008 in the Malaysian economy. The out comes from the ARDL bound test indicated that unbiased and competent internal organizations are fundamental for reducing 𝐢𝑂2e throughout OG. Further, A few institutional experts argue that countries' institutions are not uniform, resulting in economic development divergence. North (1992) Menard and Shirley (2008) argue in their scholarly papers that countries governed by different European nationals owned multiple sets of institutions from their colonial rulers. This is theoretically supported by actual evidence. The implication is that nations that inherited different institutions from their colonial rulers saw diverse degrees of post- colonial economic growth. Countries dominated by the British, for example, received British institutions, but Frenchex-colonies acquired French institutions; consequently, economic development and IQ in British and French ex-colonies varied. (North,1989; Grier,1999; Bertocchi &Canova, 2002). There is limited information on the environmental effect of institutions. There is, however, a lot of literature on institutions and economic progress. Omri, (2014) contends that institutions impact economic development and the effectiveness of energy programs. Bhattacharya et al. (2017) suggested that institutions that support property rights protection foster voluntary trading and help governments formulate and execute ecological improvement strategies. Consequently, the success of ecological and renewables policies depends on the functioning of institutions, deprived of which government programs would fail to generate the intended effects. Abid’s (2016) empirical results reveal that government efficacy, peace and stability, and corruption control contributed to 𝐢𝑂2e reductions. Furthermore, improved institutions increase energy efficiency and renewable energy uptake, leading to stricter energy and environmental legislation (Stern, 2012; Fredriksson et al., 2004; Cadoret & Padovano, 2016). In Sub-Saharan African countries, however, controlling quality and the state of law do not curb the growth in𝐢𝑂2e. Extending on the previous study, Abid (2017) discovered that in the EU, good governance, rule of law, peace and stability, corrupt practices control, and the limit the growth of 𝐢𝑂2e. However, none of these institutional measures have a meaningful effect on 𝐢𝑂2e in countries in the Middle East and North Africa. Review of Economics and Development Studies, Vol. 8 (2) 2022, 97 - 109 100 3. Methodology and Data Description 3.1 Data Collection To achieve the aim of the study, the data was extracted from the World Development Indicators database (WDI). In our analysis dependent variable is 𝐢𝑂2e and the focus variable is the institutional quality (IQ) is comprising of four indicators i.e., rule of law, corruption, accountability, and government stability, and other independent variables are energy use (E), gross domestic product (GDP), trade openness (TO), population growth (PG). Details descriptions and symbols of variables are reported in table1. Table1 Displays Description and Symbols of Variables Variables Symbol Definition Source Carbon dioxide emissions CO2e Carbon dioxide emissions (Kilotons) WDI Institutional Quality IQ The IQ assesses the rule of law, corruption, WGI Accountability and government stability. Energy use E Energy use (KG of oil equivalent per capita) WDI Trade Openness TO trade openness (calculated as export imports/GDP, constant US$, 2010) WDI Gross domestic product GDP GDP per capita (constant 2010 US$) WDI Population growth PG Population growth (annual %) WDI 3.2 Model Specification and Methodology The key goal of the current research is to look at the nonlinear connection between IQ and 𝐢𝑂2e in Pakistan. Furthermore, this research (Tamazain and Rao, 2010; Lau et al., 2020) included IQ in their model to explore the influence of IQ on 𝐢𝑂2e. The following model created by Salman et al. combines the focal variables as IQ in this investigation. The functional form of the relationship between IQ, TO, GDP, E, and 𝐢𝑂2e is as follows: 𝐢𝑂2,𝑑 = 𝛽0 + 𝛽1𝐼𝑄𝑑 + 𝛽2πΈπ‘ˆπ‘‘ + 𝛽3𝐺𝐷𝑃𝑑 + 𝛽4𝑇𝑂𝑑 + 𝛽5𝑃𝑂𝑃𝑑 + 𝑒𝑑 (1) To obtain long and short estimates, the above equation (1) was reconfigured with an error- correction structure, which is shown below in equation (2) Δ𝐢𝑂2,𝑑 = Ξ²0 + Ξ£π‘˜=1 𝑝 πœƒπ‘˜ Δ𝐢𝑂2,π‘‘βˆ’π‘˜ + Ξ£π‘˜=0 𝑝 πœ‹π‘˜ Ξ”πΌπ‘„π‘‘βˆ’π‘˜ + Ξ£π‘˜=0 𝑝 π›Ώπ‘˜ Ξ”πΈπ‘ˆπ‘‘βˆ’π‘˜ + Ξ£π‘˜=0 𝑝 πœ†π‘˜ Ξ”πΊπ·π‘ƒπ‘‘βˆ’π‘˜ + Ξ£π‘˜=0 𝑝 πœ‚π‘˜ Ξ”π‘‡π‘‚π‘‘βˆ’π‘˜ + Ξ£π‘˜=0 𝑝 πœŒπ‘˜ Ξ”π‘ƒπ‘‚π‘ƒπ‘‘βˆ’π‘˜ + 𝛼1𝐢𝑂2,π‘‘βˆ’1 + 𝛼2𝑇𝑂𝑅 π‘‘βˆ’1 + 𝛼3πΈπ‘ˆ π‘‘βˆ’1 + 𝛼4𝐺𝐷𝑃 π‘‘βˆ’1 + 𝛼5𝑇𝑂 π‘‘βˆ’1 + 𝛼6𝑃𝑂𝑃 π‘‘βˆ’1πœ–π‘‘ (2) Shin et al. (2014) suggested the nonlinear ARDL econometric framework applied in this research (2014). This approach explores the nonlinear influence of the variables under evaluation, which alludes to both positive and negative changes (Mensi et al., 2018). Hence, NARDL has an advanced form of ARDL and better technique as compared to ARDL. Furthermore, some scholars in environmental economics have applied the NARLD approach (Ahmad et al., 2019; Munir and Riaz, 2020). The present research is the first to look at the asymmetric link between IQ and𝐢𝑂2e in Pakistan. The primary purpose of this study is to look at the nonlinear influence on Pakistan. This research focused on the nonlinear effect of IQ on 𝐢𝑂2 e. Besides, NARDL categorizes IQ into two parts: positive and negative. Review of Economics and Development Studies, Vol. 8 (2) 2022, 97 - 109 101 3.3 Econometric Technique A series of econometric techniques were used in this study to find linear and nonlinear relationships among the considered variables. The first step was to perform a unit root to assess the level of stationary such as the Augmented Dicker–Fuller (ADF) and Phillips–Perron (PP) tests. And in the coming step to detect asymmetric connections between the incorporated variables. This study used nonlinear cointegration tests. Finally, a diagnostic and stability test has performed to ensure that the NARDL models were secure and stable. The asymmetric effects of the explanatory variables are investigated using the NARDL version contingent error correction, which is derived from the ARDL model. Equation (3) has been developed to represent the nonlinear association between these two attributes. Shin et al. (2014) postulated the NARDL for the bound test approach used in this analysis. Δ𝐢𝑂2,𝑑 = Ξ²0 + Ξ£π‘˜=1 𝑝 πœƒπ‘˜ Δ𝐢𝑂2,π‘‘βˆ’π‘˜ + Ξ£π‘˜=0 𝑝 πœ‹π‘˜ Ξ”πΌπ‘„π‘‘βˆ’π‘˜ + + Ξ£π‘˜=0 𝑝 πœ‹π‘˜ Ξ”πΌπ‘„π‘‘βˆ’π‘˜ βˆ’ + Ξ£π‘˜=0 𝑝 π›Ώπ‘˜ Ξ”πΈπ‘ˆπ‘‘βˆ’π‘˜ + Ξ£π‘˜=0 𝑝 πœ†π‘˜ Ξ”πΊπ·π‘ƒπ‘‘βˆ’π‘˜ + Ξ£π‘˜=0 𝑝 πœ‚π‘˜ Ξ”π‘‡π‘‚π‘‘βˆ’π‘˜ + Ξ£π‘˜=0 𝑝 πœŒπ‘˜ Ξ”π‘ƒπ‘‚π‘ƒπ‘‘βˆ’π‘˜ + 𝛼1𝐢𝑂2,π‘‘βˆ’1 + 𝛼2𝑇𝑂𝑅 π‘‘βˆ’1 + 𝛼3πΈπ‘ˆ π‘‘βˆ’1 + 𝛼4𝐺𝐷𝑃 π‘‘βˆ’1 + 𝛼5𝑇𝑂 π‘‘βˆ’1 + 𝛼6𝑃𝑂𝑃 π‘‘βˆ’1πœ–π‘‘ (3) So, in equation (4) 𝐼𝑄+ Signifies the positive fluctuation in IQ. On the other hand, πΌπ‘„βˆ’ infers the negative fluctuating in IQ. Besides the link between IQ and 𝐢𝑂2e is considered the nonlinear in the condition of changes in positive and negative resulting in an inflow of IQ. Further, the F- State-bound test is used to explore the long-run cointegration among the selected variables. Hence, the null hypothesis shows the absence of cointegration while the alternative revealed the presence of cointegration. Also, the Wald testis adopted to assess the nonlinear association between IQ and 𝐢𝑂2e. 𝐼𝑄𝑑 + = 𝛴𝑛=1 𝑑 π›₯𝐼𝑄𝑑 + = 𝛴𝑛=1 𝑑 π‘šπ‘Žπ‘₯(π›₯𝐼𝑄𝑑 +, 0) = (4) 𝐼𝑄𝑑 + = 𝛴𝑛=1 𝑑 π›₯𝐼𝑄𝑑 + = 𝛴𝑛=1 𝑑 π‘šπ‘–π‘›(π›₯𝐼𝑄𝑑 +, 0) = (5) 4. Results and Discussion The time series properties have been examined to determine the integration pattern of the variables using the Augmented Dickey-Fuller (ADF) test and the Phillips–Perron (PP) test (Khan et al., 2021). Besides, the PP and ADF unit root tests specify that the variables have a unit root as their null hypothesis. The nonstationary null hypothesis is generated at the significance levels of 10, 5, and 1%. Table 2 shows the results of unit root tests. The outcomes of the tests show that IQ, TR, and POP are stationary at the level. The results of the ADF tests on the 1stdifference, on the other hand, clearly show that carbon emissions and energy use are stationary after the 1stdifference at the 1, 5, and 10% significance levels, respectively, declining the null hypothesis. As a result, the overall results of the ADF tests describe the mixed order of integration. The results of the ADF test have been verified by adopting the PP unit root tests. Further, the PP test also shows similar results. According to the outcome of the unit root tests, all the considered variables are an integrated series of only order I (0) and I (1). As a result, none of the variables are integrated at I (2), necessitating the use of the NARDL technique. Review of Economics and Development Studies, Vol. 8 (2) 2022, 97 - 109 102 Table 2 Unit Root Test Results Variables ADF (Level) PP(Level) CO2e 0.031 0.031 IQ -0.171*** -0.130*** EU -0.043 -0.043 GDP -0.02 0.029 TR -0.239*** -0.239*** POP -0.007** -0.007** Note: ***, **, and * are significant at the 1%, 5%, and 10% levels, respectively. The null hypothesis for the ADF test is that the attribute does have a unit root. The null hypothesis for the PP test is that the attribute has a unit root. The nonlinear ARDL long-run values of coefficients are extracted in table 3. The turnout illustrates that positive shocks in IQ significantly improve the environmental quality (EQ) in the long run. On the contrary, the negative surprise in IQ stimulates 𝐢𝑂2e. The results highlighted that a 1% increase (decrease) in intuitional quality impacts carbon emissions to about -0.040% (0.033) at the 10% and 5% significance levels in Pakistan in the long run. Additionally, the outcomes infer that EU and GDP are positively associated with 𝐢𝑂2e in the long run. It shows that a 1% rise in EU and OG enhances 𝐢𝑂2e to about 5.532% and 0.463% at a 1% significate level, respectively, in the long run in Pakistan. At the same time, the empirical finding depicts that TOR demonstrates a negative impact on 𝐢𝑂2e. The results indicate that a 1% upsurge in TOR declined the 𝐢𝑂2e to about 0.364%, while the coefficient of POP does not show a statistically significant influence on 𝐢𝑂2e. Table 3 NARDL Long Run Estimates DV CO2e Variables Coefficients Std. Error IQ -0.040* 0.021 IQ 0.033** 0.017 EU 5.532*** 2.727 GDP 0.463*** 0.157 TR -0.364* 0.20 POP 0.459 0.39 Note: ***, **, and *are significant at the1%,5%, and10%levels, respectively Table 4 displays the short-run estimates from NARDL. The empirical findings highlight that the results infer that those positive shocks in IQ offer a substantially negative influence on 𝐢𝑂2 e in the short run in Pakistan. In comparison, negative surprise in the short run has an insignificant effect on 𝐢𝑂2e. Thus, the short-run results indicate that EU and GDP accelerate𝐢𝑂2e in the short run meaningfully. On the other hand, the empirical findings confer that TOR and POP are significantly negatively associated with the 𝐢𝑂2e in short in Pakistan. Table 4's bottom panel displays the results of various diagnostic tests. The value of the Lagrange multiplier (LM) test shows an insignificant, indicating that the residuals are autocorrelation-free. Ramsey RESET test, Heteroskedasticity test, and some other diagnostic tests. The RESET test coefficients appear statistically insignificant, showing that the functional forms of our models are suitable. Similarly, the coefficient of the Heteroskedasticity test seems to be statistically insignificant, indicating that Heteroskedasticity does not affect the model. Finally, the stability of the calculated nonlinear ARDL models is evaluated using the CUSUM and CUSUM-squared tests, as illustrated in figs. 1 and 2. Furthermore, in the case of IQ and 𝐢𝑂2e, the ECT Review of Economics and Development Studies, Vol. 8 (2) 2022, 97 - 109 103 term is negative and statistically significant at the 5% level, suggesting the existence of cointegration among variables in the model. The ECT terms offer that IQ (𝐢𝑂2e) readjusts extremely fast to its long- run equilibrium level, at 82 percent per year in the presence of other measurable factors. As a result of the Wald test results, the asymmetry between IQ and 𝐢𝑂2 e seems to be significantly significant in both the long and short term. The asymmetry dynamic multiplier curve has been denoted by a difference between the positive and negative portions of the curves, which reflects the linear mixing of dynamic multipliers associated with positive and negative shocks of IQ on 𝐢𝑂2e, as illustrated in fig.3. Table 4 NARDL Short Run Estimates DV CO2e Variables Coefficients Std. Error βˆ†πΌπ‘„π‘‘ + -0.057*** 0.013 βˆ†πΌπ‘„π‘‘βˆ’1 + -0.018 0.01 βˆ†πΌπ‘„π‘‘ βˆ’ -0.009 0.008 βˆ†πΈπ‘ˆπ‘‘ 1.138*** 0.291 βˆ†πΊπ·π‘ƒπ‘‘βˆ’1 2.398*** 0.527 βˆ†πΊπ·π‘ƒπ‘‘βˆ’1 1.514*** 0.588 βˆ†π‘‡π‘…π‘‘ -0.106 0.087 βˆ†π‘ƒπ‘‚π‘ƒπ‘‘ -4.103*** 0.908 Note: ***, **, and *are significant at the1%,5%, and10%levels, respectively Table 5 Diagnostics Test DV CO2e R-squares 99.081 Adjusted R-squares 91.902 πΈπΆπ‘€π‘‘βˆ’1 0.082*** 0.03 LM test 3.021 F-test 8.416*** RESET test 0.043 Heteroscedasticity test 2.139 Note: The critical values of the RESET, and LM, and at the 10 % level of significance are 2.12 and 3.823 Review of Economics and Development Studies, Vol. 8 (2) 2022, 97 - 109 104 Review of Economics and Development Studies, Vol. 8 (2) 2022, 97 - 109 105 A significant and positive influence of IQ positively affects Pakistan's environmental performance by lowering 𝐢𝑂2e. In contrast, a substantial and negative influence on IQ is expected to harm Pakistan’s environmental performance by increasing 𝐢𝑂2 e. Besides, the nonlinear form between IQ and environment has been proved by differing levels in their coefficients in both periods (long-run and short-run). As a result, a positive influence on Pakistan's IQ may have a meaningful (at 1%) and positive impact on the quality of Pakistan's environment by reducing emissions by 0.040(0.4) in both the long and short run, respectively. In Pakistan, a negative surprise to institutional quality will result in a significant(at1%) and negative change in EQ by increasing 𝐢𝑂2e by 0.033 only in the long run. Thus, the finding revealed that the positive and negative performance of institutional quality on the environment in Pakistan is mainly dependent on long-term changes in the country's institutions. This discovery is related to the quality of Pakistani institutions. This discovery highlights the need for support of useful and competent administration of Pakistan by govt representatives through its regulatory agencies and institutions. Therefore, for the scenario to continue, the country's institutions must be determined and free of corruption to deliver effective and efficient policy implementation and intensive care. As a result, the occurrences may necessitate regulatory requirements to combat market participants' excesses in electricity, and effluence-concentrated consumption; however, this may be accomplished if the country's governing strategies are prioritized over individual requirements and pursued without favor or discrimination. This finding is consistent with the author's expectations for 𝐢𝑂2 control in accomplishing carbon neutrality and improving EQ through the channel of efficient institutional mechanism the outcome is consistent with the results (Uzar, 2020; Aron, 2000; Panayotou, 1997; Vogel (1997; Abid,2016). They believe that IQ is an effective tool for reversing environmental degradation. On the other hand, Wawrzyniak and Dory's (2020) study effect IQ on 𝐢𝑂2e between authority efficacy and handling exploitation of power. They discovered that government effectiveness positively affects the 𝐢𝑂2e, whereas corruption control has the opposite effect. Moreover, the finding suggests that the rise in the EU has a meaningful effect on 𝐢𝑂2einPakistan. The outcomes are Review of Economics and Development Studies, Vol. 8 (2) 2022, 97 - 109 106 consistent with past studies such as those (Saidi and Hammami, 2015; Nilritetal. (2017). These studies suggest that spikes in energy consumption significantly contributed to carbon emissions. 5. Conclusion and Policy Implications This research looks in to the factors that have helped Pakistan to maintain a consistent improvement in its environmental performance by reducing carbon emissions. The real goal provides perspective on Pakistan's accomplishing carbon neutrality and conceivably offers suggestions for some other states to develop. Hence, it would undoubtedly spark a concerted effort to reduce the climate crisis via individual action in slowing down the rate of global emissions. To achieve the study's goal effectively, the present study utilized nonlinear ARDL to inspect the asymmetric effect of IQ on carbon emissions in Pakistan over the period 1980-2020.This study also employed additional variables, i.e., GDP, energy use, TO, and population. The emphasis on the effect of IQ and TO in determining environmental performance. This is the effectiveness of policies in controlling negative phenomena, for instance, 𝐢𝑂2e. The efficiency and competency in policies that are implemented to attain their targeted outcomes are directly related to the quality and capabilities of the existing institutions entrusted with a task. Also, TO has been used in many studies to test environmental performance. The turns out infer a (positive and negative) TO impacting negatively on the environment of developing countries due to laxity in policies of those countries. It is not enough to generalize that institutions’ rooted policies positively control the negative phenomenon without research. Bearing in mind Pakistan’s positive trend of handling 𝐢𝑂2e, the present paper hypothesized that Pakistan’s government’s institutional quality positively impacts the environment quality. The outcomes from the NARDL indicate a positive component of IQ, assisting EQ certainly causes the reduction in 𝐢𝑂2e.TOR has also been used in numerous studies to assess environmental performance. It shows a mixed finding (positive and negative) that TO is hurting the environment of less developed economies with the ineffectiveness of policies in the countries. Without research, that is not enough to generalize that institutionally deeply ingrained initiative favorably handle the negative occurrence. Given Pakistan's positive trend in reducing carbon emissions, the current paper hypothesized that the government's institutional quality positively impacts environmental quality. The NARDL findings indicate that IQ has a positive component that benefits the environment by lowering carbon emissions. The outcome infers that the EU and OG evoke the carbon emissions in Pakistan. In contrast, the higher the level of TOR is negatively connected with carbon emissions. It infers that the TOR level increases the environmental quality by decreasing carbon emissions in Pakistan. The following strategies have been endorsed: the outcomes confirm the potency of handling 𝐢𝑂2ethrough IQ, the primary concern, and increased interest in IQ to maintain good environmental performance. Further, OG may be supported with help of long- and short-term policies. For this purpose, special interest is paid to the use of green energy and also ensures the relaxation of carbon-intensive economic activities; thus, it effectively reduces carbon emissions. Besides, it will aid in advocating energy decentralization and the steady transition away from fossil fuels and toward green energy sources such as solar and hydro. Furthermore, with responsible consumption and production as one of the Sustainable Development Goals (SDG-12) targets, a policy that will help to moderate the country's consumption and production patterns is critical. It could impose a tax on the manufacturing sectors if the target is not met. The institution's instrument should be directed toward regulating the activities of foreign Review of Economics and Development Studies, Vol. 8 (2) 2022, 97 - 109 107 investors and assigning the investor the task of adhering to the energy transition agenda. Further, the study is helpful for policy debates about Pakistan and South Asian economies and global economic development. Furthermore, the results of a specific analysis can be used to develop specific recommendations for that region. It is also beneficial to establish the channels through which these institutional qualities improve the quality of the environment. The research will also help determine the primary role of institutional quality in developing a Pakistani economy. References Abid, M. (2016). Impact of economic, financial, and institutional factors on CO2 emissions: evidence from sub-Saharan Africa economies. Utilities Policy, 41, 85-94. Abid, M. (2017). Does economic, financial, and institutional developments matter for environmental quality? A comparative analysis of EU and MEA countries. Journal of environmental management, 188, 183-194. Adams, S., & Klobodu, E. K. M. (2017). Urbanization, democracy, bureaucratic quality, and environmental degradation. Journal of Policy Modeling, 39(6), 1035-1051. Ahmad, M., Ul Haq, Z., Khan, Z., Khattak, S. I., Ur Rahman, Z., & Khan, S. (2019). Does the inflow of remittances cause environmental degradation? Empirical evidence from China. Economic research-EkonomskaistraΕΎivanja, 32(1), 2099-2121. Ahmad, N., Du, L., Lu, J., Wang, J., Li, H. Z., & Hashmi, M. Z. (2017). Modeling the CO2 emissions and economic growth in Croatia: is there any environmental Kuznets curve? Energy, 123, 164-172. Aron, J. (2000). Growth and institutions: a review of the evidence. The world bank research observer, 15(1), 99-135. Bellakhal, R., Kheder, S. B., & Haffoudhi, H. (2019). Governance and renewable energy investment in MENA countries: How does trade matter? Energy Economics, 84, 104541. Bertocchi, G., & Canova, F. (2002). Did colonization matter for growth? An empirical exploration into the historical causes of Africa's underdevelopment. European economic review, 46(10), 1851-1871. Bhattacharya, M., Churchill, S. A., & Paramati, S. R. (2017). The dynamic impact of renewable energy and institutions on economic output and CO2 emissions across regions. Renewable Energy, 111, 157-167. Cadoret, I., & Padovano, F. (2016). The political drivers of renewable energies policies. Energy Economics, 56, 261-269. Ellis, J. (2010). The Effects of Fossil-Fuel Subsidy Reform: A review of modeling and empirical studies. Available at SSRN 1572397. Fredriksson, P. G., Vollebergh, H. R., & Dijkgraaf, E. (2004). Corruption and energy efficiency in OECD countries: theory and evidence. Journal of Environmental Economics and Management, 47(2), 207-231. Grier, R. M. (1999). Colonial legacies and economic growth. Public Choice, 98(3), 317-335. Grossman, G. M., & Krueger, A. B. (1991). Environmental impacts of a North American free-trade agreement. Grossman, G. M., & Krueger, A. B. (1995). Economic growth and the environment. The quarterly journal of economics, 110(2), 353-377. Hsu, A., Rosengarten, C., Weinfurter, A., Xie, Y., Musolino, E., & Murdock, H. E. (2017). Renewable energy and energy efficiency in developing countries: contributions to reducing global emissions-third report. Review of Economics and Development Studies, Vol. 8 (2) 2022, 97 - 109 108 Khan, M. T., Anwar, M. M., & Husnain, M. (2021). The relationship between corporate diversification and tax avoidance: empirical evidence from the emerging economy of Pakistan. Journal of Accounting and Finance in Emerging Economies, 7(1), 35-52. La Porta, R., Lopez-de-Silanes, F., & Shleifer, A. (2008). The economic consequences of legal origins. Journal of economic literature, 46(2), 285-332. Lau, L. S., Choong, C. K., &Eng, Y. K. (2014). Carbon dioxide emission, institutional quality, and economic growth: empirical evidence in Malaysia. Renewable energy, 68, 276- 281. MΓ©nard, C., & Shirley, M. M. (Eds.). (2005). Handbook of new institutional economics (Vol. 9). Dordrecht: Springer. Mensi, Walid, Syed Jawad Hussain Shahzad, Shawkat Hammoudeh, and Khamis Hamed Al- Yahyaee. "Asymmetric impacts of public and private investments on the non-oil GDP of Saudi Arabia." International Economics 156 (2018): 15-30. Munir, K., & Riaz, N. (2020). Asymmetric impact of energy consumption on environmental degradation: evidence from Australia, China, and the USA. Environmental Science and Pollution Research, 1-11. Nilrit, S., Sampanpanish, P., &Bualert, S. (2017). Comparison of CO2 emissions from vehicles in Thailand. Applied Environmental Research, 39(1), 65-74. North, D. C. (1989). Institutions and economic growth: An historical introduction. World Development, 17(9), 1319-1332. North, D. C. (2018). Institutional change: a framework of analysis. In Social Rules (pp. 189- 201). Routledge. North, D. C., & North, D. C. (1992). Transaction costs, institutions, and economic performance (pp. 13-15). San Francisco, CA: Ics Press. Omri, A. (2014). An international literature survey on energy-economic growth nexus: Evidence from country-specific studies. Renewable and Sustainable Energy Reviews, 38, 951- 959. Panayotou, T. (1993). Empirical tests and policy analysis of environmental degradation at different stages of economic development (No. 992927783402676). International Labour Organization. Vogel, D. (1997). Trading up and governing across: transnational governance and environmental protection. Journal of European public policy, 4(4), 556-571. Panayotou, T. (1997). Demystifying the environmental Kuznets curve: turning a black box into a policy tool. Environment and development economics, 2(4), 465-484. Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of applied econometrics, 16(3), 289-326 Saidi, K., &Hammami, S. (2015). The impact of energy consumption and CO2 emissions on economic growth: Fresh evidence from dynamic simultaneous-equations models. Sustainable Cities and Society, 14, 178-186. Shah, S. Z., Chughtai, S., & Simonetti, B. (2020). Renewable energy, institutional stability, environment and economic growth nexus of D-8 countries. Energy Strategy Reviews, 29, 100484. Shah, S. Z., Chughtai, S., & Simonetti, B. (2020). Renewable energy, institutional stability, environment and economic growth nexus of D-8 countries. Energy Strategy Reviews, 29, 100484. Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In Festschrift in honor of Peter Schmidt (pp. 281-314). Springer, New York, NY. Solarin, S. A., Al-Mulali, U., & Ozturk, I. (2017). Validating the environmental Kuznets curve hypothesis in India and China: The role of hydroelectricity consumption. Renewable and Review of Economics and Development Studies, Vol. 8 (2) 2022, 97 - 109 109 Sustainable Energy Reviews, 80, 1578-1587. Stern, D. I. (2012). Modeling international trends in energy efficiency. Energy Economics, 34(6), 2200-2208. Tamazian, A., & Rao, B. B. (2010). Do economic, financial and institutional developments matter for environmental degradation? Evidence from transitional economies. Energy economics, 32(1), 137-145. Uzar, U. (2020). Political economy of renewable energy: does institutional quality make a difference in renewable energy consumption? Renewable Energy, 155, 591-603. Williamson, O. E. (1989). Transaction cost economics. Handbook of industrial organization, 1, 135- 182. Wong, S., Bhattacharya, K., & Fuller, J. D. (2010). Long-term effects of feed-in tariffs and carbon taxes on distribution systems. IEEE Transactions on Power Systems, 25(3), 1241-1253. World Bank, (2022). World development indicators. Retrieved fromhttps://databank.worldbank.org/source/world-development-indicators World Governance, (2022). World Governance indicators. Retrieved from https://databank.worldbank.org/source/worldwide-governance-indicators. Yao, X., Yasmeen, R., Padda, I. U. H., Shah, W. U. H., & Kamal, M. A. (2020). Inequalities by energy sources: an assessment of environmental quality. PloS one, 15(3), e0230503. https://databank.worldbank.org/source/world-development-indicators https://databank.worldbank.org/source/worldwide-governance-indicators