Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 475 Can Financial Development Help in Raising Sustainable Economic Growth and Reduce Environmental Pollution in Pakistan? Evidence from Non Linear ARDL Model Muhammad Asif Amjad a , Nabila Asghar b , Hafeez Ur Rehman c a Phd Scholar, Department of Economics and Statistics (HSM), University of Management and Technology Lahore, Pakistan Email: m.asifamjad22@gmail.com b Associate Professor, Department of Economics and Business Administration, Division of Management and Administrative Science, University of Education Lahore, Pakistan Email: nabeela.asghar@ue.edu.pk c Professor/ Chairman, Department of Economics and Statistics (HSM), University of Management and Technology Lahore, Pakistan Email: hafeez.rehman@umt.edu.pk ARTICLE DETAILS ABSTRACT History: Accepted 25 October 2021 Available Online December 2021 It is a global challenge to reduce environmental pollution and enhance sustainable economic growth. This study explores the role of financial development as an instrument in reducing environmental pollution and enhancing sustainable economic development in Pakistan for the period 1980-2020. The Non-linear Autoregressive Distributed Lag (NARDL) econometrics technique has been utilized to find the association between environmental pollution, economic growth, and financial development. The results show that positive shocks of financial development increase economic growth and reduce environmental pollution. While the negative shocks of financial development increase both economic growth and environmental pollution. Globalization has negative impact on economic growth and the use of energy increases economic growth and environmental pollution. The study suggests that the State Bank of Pakistan and other financial institutions should formulate and implement soft loan policies to induce the private investors to use low carbon emission technologies. © 2021 The authors. Published by SPCRD Global Publishing. This is an open access article under the Creative Commons Attribution- NonCommercial 4.0 Keywords: Sustainable Economic Growth, Environmental Pollution, Financial Development, NARDL, KOF Index JEL Classification: Q01, P27 DOI: 10.47067/reads.v7i4.406 Corresponding author’s email address: hafeez.rehman@umt.edu.pk 1. Introduction Now a days it is a big challenge for policymakers to control environmental pollution and increase sustainable economic development. Several decades ago, the policymakers only focus on economic growth and ignore environmental changes. Fossil fuels have been ruthlessly consumed to boost economic growth which greatly increased the carbon dioxide (CO2) emission in the atmosphere. Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 476 Nowadays, the most challenging issue faced by the world is global warming. According to National Oceanic and Atmospheric Administration, NOAA (2020), the average temperature increased by 0.13 o F per decade since 1980, but in 1981 it increased more than twice (0.32 o F). World Meteorological Organization, WMO (2020) declared the last decade as the warmest decade on record. A continuous increase in global temperature is responsible for climate change which cause floods, heat, droughts, fires, tropical cyclones, and storms. These incidents pose a threat to global economic growth. Swissre (2021) predicated if no mitigation is taken place and global temperature could increase by more than 3 o C then global GDP may shrink by 18% in the next 30 years. Asian economies would be severely affected by the loss of GDP. It is a quite difficult task to reduce CO2 emissions because industry, agriculture and transport sectors in most of the countries realize heavily dependent upon gas, coal, and oil consumption. These sectors provide employment and produce goods which increase economic growth (Khan et al., 2020). Since a decrease in fossil energy consumption may adversely affect economic growth. So, the developing countries are reluctant to reduce fossil fuel consumption and a continuous increase in environmental pollution may be observed over time. The industrial, agricultural and transportation sectors are closely associated with financial system and efficient financial system promotes economic growth (Jiang et al. 2019). Before the 1970s most of the developing countries were financially repressed due to various discriminatory taxes and policies like high reserve requirements, credit controls, low interest rates, and high inflation rates that had exerted a bad impact on the financing decisions. After the 1990s most of the countries of the world have introduced financial reforms which has increased the desire to achieve rapid pace of economic development. This increases the demand and consumption of energy that are responsible for climate change. This study tries to access the way in which environmental pollution can be reduced and how economic growth can be enhanced by using Pakistan’s financial development indicators. Pakistan is among top ten countries which are mostly affected by climate change in the last 20 years as it faced 152 extreme weather events during 1999-2018 and lost 0.53 % per unit GDP and economic loss worth US$3792.52 million (Global climate risk Index, 2021). In the last decade Pakistan’s per capita CO2 emission has increased 3% annually (WDI, 2021). Figure 1 shows the details of CO2 emission metric ton per capita for the period 1990-2020. In the last five years, an average of 1.07 metric tons of CO2 emission have increased which is an alarming situation for Pakistan. Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 477 After the 1990 financial reforms, the financial sector of Pakistan has been developed. According to the Bloomberg (2016) report, Pakistan's financial sector have grown rapidly and have shown promising signs of persistent increase in economic growth. In Pakistan, the financial sector plays an important role in industrial development, a well-organized baking system, agricultural development, government policies, exchange rate stability, political stability, well-founded education sector, monetary and fiscal policy, etc. These factors helped in enhancing economic growth through attracting foreign direct investment. There is mixed evidence regarding the relationship betweeen financial development on CO2 emissions in Pakistan. Some studies argued that financial development has increased CO2 emission in Pakistan (Khan, et al. 2020; Majeed et al., 2020; Ahmad et al., 2020; Raza & Shah, 2018; Shahzad et al., 2017; Siddique, 2017; Javid & Sharif, 2016; Muhammad & Ghulam, 2013; Zhang, 2011). These studies argue that the financial development help the consumers to get loans easily who prefer to buy refrigerators, motorbikes, cars, air-conditioners that emit CO2 emissions. On the other hand, the foreign and domestic investors invest in those projects which have less transaction cost without caring about CO2 emissions which ultimately enhance pollution. While on the other side, a few studies have pointed out that financial development has decreased CO2 emission in Pakistan (Godil, et al., 2020; Ali, et al., 2015; Shahzad, et al., 2014). These studies argued that the developed financial sector attracts most of the investment from developed countries and also developed countries prefer to invest in those projects which are environment friendly. After 9/11 Pakistan have received a lot of foreign direct investment, loans, and aid from developed countries. It helped the country to invest in high-tech projects which resulted in low carbon emissions. This is the reason that Pakistan is declared as a low CO2 emission country in the region. Apart from this Pakistan have imposed an environment friendly policy to reduce environmental pollution. Now-a-days each country of the world has a desire to achieve sustainable economic development without environmental loss. This study is an attempt to have a deep insight into the role of financial development in achieving sustainable economic growth without environmental loss in Pakistan. The study will stress on the aspect that does an increase in the financial development depict an asymmetric relationship with economic growth and carbon emissions? If not what is the optimal composition of financial development with economic growth and carbon emissions? Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 478 The significance of the study stems from the fact that it analyzes the role of financial development as the key tool to achieve sustainable economic development and diminish the environmental losses in Pakistan. Furthermore, this study is not limiting itself from the previous studies conducted in Pakistan (Javid et al. 2016; Shahzad et al., 2017; Raza & Shah, 2018; Chen, et al., 2019; Khan, et al. 2020) but it extends its application to asymmetric impacts on economic growth and environmental pollution. Not many studies are available on Pakistan economy in which non-linear analysis has been carried out to explore the nexus between financial development with sustainable economic growth and environmental pollution. 2. Review of Literature This section reviews previous literature related to the nexus between financial development, economic growth, and environmental pollution. Several studies are available in literature that have examined the linear association between the financial development with economic growth and environmental pollution ( see for example: Khan et al., 2020; Yang, 2019; Asteriou & Spanos, 2019; Bist, 2018; Cetin et al. 2018). There are only a few studies have pointed out that financial development also had a non-linear association with economic growth and carbon emissions (Chen et al. 2020; Nenbee & Danielle, 2021; Maneejuk & Yamaka, 2021; Shahbaz et al. 2017). Shahbaz et al. (2017) investigated the asymmetric analysis between financial development and economic growth for the period 1960Q1 to 2015Q4 in India. The NARDL approach was used to find the causal relationship between the concerned variables. The results of the study reveal that any positive shocks in financial development decreases economic growth while the negative shock increases economic growth. Qamruzzaman and Jianguo (2018) explored the asymmetric association between banking sector development, financial innovation, and economic growth in selected Asian countries during 1974Q1- 2016Q4. The study concluded that in the long run, Pakistan had a significant and positive asymmetric association between economic growth and domestic credit to the financial sector. Chen et al. (2020) analyzed the asymmetric impact of the financial development index on economic growth during 1972-2017 in Kenya. The results of the study show that positive partial shock of financial development index was insignificant in the long run while the negative partial shock of financial development index was statistically significant which increases economic growth. Aigheyisi and Edore (2019) examined the asymmetric effect of broad money supply on economic growth in Nigeria from 1981 to 2016. The results show that broad money supply had a statistically insignificant positive effect on economic growth while the negative change in broad money supply is statistically significant and had positive effect on economic growth in the long run.. The literature show mixed evidence between asymmetric impact of financial development on environmental pollution. Ling et al. (2021) pointed out that the positive shocks in financial development significantly increase carbon emissions while the negative shocks insignificantly increase carbon emissions. In Pakistan Majeed et al. (2020) examined the asymmetric impact of financial development on carbon emissions from 1972 to 2018. The NARDL approach validated that positive shocks in financial development are statistically insignificant which increase carbon emissions while the negative shocks in financial development is statistically significant which decrease carbon emissions. Ahmad et al. (2018) tried to find the asymmetric effect of financial development on carbon Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 479 emission from 1980 to 2014 using NARDL approach. The results show that in the long run positive shocks of financial development increases carbon emissions significantly while negative shocks have an insignificant impact on carbon emission. Ahmad et al. (2020) constructed financial development index (FD) by incorporating money supply, liquid liabilities and domestic credit to the banking sector during 1996-2018 for Pakistan. The study concluded that financial development had an asymmetric effect on carbon emission. The positive and negative shocks of financial development both decrease the carbon emissions in Pakistan. Some studies linked the financial development variables with ecological footprints. Ahmed et al. (2021) linked financial development with ecological footprints during 1971-2016 in Japan. The study analyzed the asymmetric relationship between financial development and ecological footprints and concluded that an increase and decrease in financial development lead to an increase the ecological footprints in the long run. Omoke et al. (2020) investigated the asymmetric effect of the financial development index on ecological footprints of non-carbon and carbon in Nigeria during 1971-2014. The study concluded that a positive increase in the financial development index statistically and significantly decline carbon ecological footprints while a negative decline in the financial development index statistically and significantly increase the carbon ecological footprints. The review of literature mentioned above that not many studies are available on the asymmetric relationship between financial development, economic growth and environmental pollution. Furthermore, the results related to the above mentioned relationship between the variables are not clear which calls for the need to deeply examine the asymmetric association between financial development, economic growth and environmental pollution. This study uses NARDL approach for estimating the relationship between the variables in the context of Pakistan economy. 3. Conceptual framework and Methodology Financial sector is considered as an important segment of Pakistan's economy which faces both positive and negative shocks frequently. Therefore, these shocks cannot be ignored to capture their impact on economic growth and environmental pollution. This study is conducted in the light of research work by Shin et al. (2014) in which they decomposed the variable in the positive and negative partial sums. Usually, the positive shocks in financial development increase economic growth and environmental up-gradation while the negative shocks decrease economic growth and environmental degradations (Chen et al.,2020; Ling et al., 2021; Aigheyisi & Edore, 2019; Karasoy et al., 2019; Ahmad et al., 2018). Figure 2 demonstrate the theoretical frame work of this study. Financial development Positive shocks Increase Economic growth Decrease Economic growth Negative shocks Environm ental up- gradation Environme ntal de- gradations Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 480 In the present study financial development is measured in terms of domestic credit to banks (DCB). Economic growth is measured in terms of gross domestic product (GDP) and environmental pollution is measured by CO2 emissions in metric tons. The data has been collected from WDI for the period 1980-2020. The description of the variables is presented in Table 1. Table 1 Description of the Variables Symbols Indicator Units Source GDP Gross domestic product Constant LCU WDI-2021 CO2 CO2 emissions metric tons per capita WDI-2021 DCB Domestic credit to Banks % of GDP WDI-2021 EDU Primary education enrollment % of gross WDI-2021 KOF Globalization Index Swiss economic institute EU Energy use kg of oil equivalent per capita WDI-2021 URPOP Urban population % of total population WDI-2021 This study has derived the empirical model from the Cobb-Douglas production function and carbon emissions written as; (1) (2) Where FD means financial development which is measured in terms of credit to banks (DCB), EDU means primary education, KOF shows the globalization, EU means energy use, URPOP stands for urban population while GDP and CO2 show economic growth and carbon emissions. In the light of equation 1 and 2 the following econometric models are formulated: + (3) + (4) Model 3 and 4 have been applied to bring up the above mentioned relationship between variables in the context of Pakistan economy. These models seems to be inappropriate for Pakistan as it’s financial development sector did not remain stable during 1980-2020 due to many ups and downs as shown in figure 3. Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 481 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 1980 1985 1990 1995 2000 2005 2010 2015 2020 LNDCB 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 1980 1985 1990 1995 2000 2005 2010 2015 2020 LNDCP Figure 3 Graphs of financial development variables The present study uses NARDL approach that is extended version of ARDL. The asymmetric relationship between financial development, economic growth and environmental pollution can be written as (5) (6) The asymmetric effect of financial development is a combination of both positive change as LNFD + and negative changes as LNFD - . The positive and negative series of LNFD can be summarized in the partial sum process as follows: ∑ ∑ & ∑ ∑ (7) For the NARDL setting, the dynamic of the long run and short coefficients are incorporated in the equation as: ∑ ∑ ∑ ∑ ∑ ∑ ∑ (8) ∑ ∑ ∑ ∑ ∑ ∑ ∑ (9) Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 482 In equations 8 and 9, , and , show the short term impact of LNFD on LNGDP and LNFD on LNCO2 respectively. After incorporating the Error Correction Term the short-run dynamics of the model are calculated below: ∑ ∑ ∑ ∑ ∑ ∑ ∑ (10) ∑ ∑ ∑ ∑ ∑ ∑ ∑ (11) In these equation ⁄ s and ⁄ are long-term coefficients of LNFD on LNGDP while ⁄ and ⁄ are the long term coefficients of LNFD on LNCO2.The variables∑ , ∑ , ∑ , and ∑ are short run adjustment variables of LNFD on LNGDP and LNFD on LNCO2 respectively. While shows the difference operators.. The implementation of equations 10-11 yields F- statistics bound value to test the null hypothesis with lower and upper critical values (Pesaran et al. 2001; Narayan, 2005; Omoke et al., 2021). The long-run asymmetries of financial development are obtained by the Wald test. The long run asymmetries of LNFD on LNGDP and LNFD on CO2 show that and respectively. Furthermore, the asymmetric cumulative multiplier effect on LNGDP for one percent change in LNFD + and LNFD - is formulated as: ∑ ∑ In the same way, the asymmetric cumulative multiplier effect of LNCO2 for unit change in LNFD + and LNFD - is formulated as: ∑ ∑ If then and are the asymmetric long run coefficients. Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 483 4. Results and Discussion Descriptive statistics are presented in Table 2. There is no pre condition of NARDL whether the series is I(0) or I(1). Table 2 Descriptive statistics LNCO2 LNGDP LNDCB LNEDU LNEU LNKOF LNURPOP Mean -0.40 29.43 3.10 4.25 6.05 3.80 17.62 Median -0.38 29.43 3.16 4.26 6.09 3.83 17.66 Maximum -0.02 30.22 3.39 4.57 6.22 4.01 18.22 Minimum -0.89 28.43 2.73 3.90 5.76 3.50 16.90 Std. Dev. 0.23 0.52 0.19 0.20 0.12 0.19 0.39 Skewness -0.41 -0.19 -0.51 -0.10 -0.94 -0.39 -0.22 Kurtosis 2.35 1.97 2.15 1.83 2.75 1.64 1.86 Jarque-Bera 1.89 2.06 3.00 2.38 6.19 4.22 2.56 Probability 0.39 0.36 0.22 0.30 0.05 0.12 0.28 Observations 41 41 41 41 41 41 41 Note: *, **, *** show level of significance at 1%, 5% and 10% . The financial sector of Pakistan shows fluctuations due to 1990 oil shocks, 9/11 incident in 2001, 2008 financial crises, and most recent Covd-19 also paralyzed the whole economy (Amjad et al. 2021). According to Perron (1990) in the presence of structural breaks in data the traditional unit rot test may be misleading. The present study uses Zivot and Andrews (2002) unit root test to confirm the order of integration. Table 3 shows the results of Zivot and Andrews unit roots and reports that all variables are stationary either I(0) or I(1). The result of the unit root test are reported in Table 3. Note: *, **, *** show level of significance at 1%, 5% and 10% . All the variables are I(0) or I(1). Table 4 presents the results of the long-run co-integration test. The values of F- statistic are higher than upper bound test at all given significance levels which means long rum co-integration exists among the variables. Table 4 Bounds testing of Linear ARDL Models F- statistic I(0) 10% I(1) 10% (LNGDP LNDCB + , LNDCB - , LNEDU, LNKOF, LNEU, LNURPOP) 4.61 2.12 3.23 (LNCO2 LNDCB + , LNDCB - , LNEDU, LNKOF, LNEU, LNURPOP) 4.48 1.75 2.87 Table 3 Zivot and Andrews Unit root with Break test Level 1st difference t-statistic year of break t-statistic year of break LNCO2 -2.709 2014 -5.68* 2007 LNGDP -7.72** 2003 -4.29*** 1992 LNDCB -4.56** 2008 -4.98* 2004 LNEU -4.48** 1986 -6.99* 2007 LNEDU 1.90 2013 -8.60* 2011 LNURPOP -1.62 2000 -7.04* 1998 LNKOF -4.93** 1988 -7.18* 1989 Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 484 The long run coefficients of NARDL are reported in Table 5. In model 1, the study captured the impact of domestic credit to banks (LNDCB) proxy of financial development on economic growth. LNDCB is decomposed into positive series LNDCB + and negative series LNDCB - . A one percent increase in the LNDCB + significantly increases LNGDP on average of 0.29% respectively (Qamruzzaman & Jianguo, 2018). One percent decline in LNDCB - significantly increases LNGDP on average of 0.45% (Shahbaz et al., 2017). In simple words, the positive and negative shocks of LNDCB both increase economic growth in Pakistan. The Wald test presented in table 6 indicates that the LNDCB has asymmetric behavior. In Pakistan after 1990 the privatization and liberalization of the banking sector improved the financial sector which helped in increasing economic growth. In model 2 the LNDCB is used as a proxy of financial development which is decomposed into positive series as LNDCB + and negative series as LNDCB - . One percent increase in LNDCB+ insignificantly reduces carbon emissions on average of 0.17% CO2 emission. (Ahmad et al., 2020; Lahiani, 2020; Odugbesan & Adebayo, 2020; Omoke et al., 2020). Similarly one percent decline in LNDCB - significantly increase on average carbon emission an average of 0.58% (Ahmad et al., 2021; Jakada et al., 2020; Karasoy et al., 2019). It implies that positive shocks in LNDCB decline CO2 emissions while the negative shocks of LNDCB increases CO2 emissions in Pakistan. Therefore, the null hypothesis is rejected and it is concluded that financial development has asymmetric behavior of economic growth and CO2 emissions. Figure 3 shows the dynamic multiplier effects of LNDCB. In Pakistan, foreign aid and debts are the major sources which contribute in improving financial sector. Pakistan has received heavy doses of foreign aid from World Bank to control environmental pollution during 2014-2017. These loans increased the financial development in Pakistan and helped in raising the import of environment friendly technologies. Moreover, the improvement in financial development helped the private investors to expand their businesses through the use of modern technology in the production process. Table 5 Long run coefficients of NARDL Model 1 Model 2 LNGDP LNCO2 Variable ARDL(2, 2, 2, 1, 2, 2, 0) ARDL(2, 2, 2, 2, 2, 2, 2) LNDCB + 0.29* (0.08) -0.17 (0.17) LNDCB - -0.45* (0.09) -0.58* (0.14) LNEDU 0.94* (0.26) 3.02* (0.46) LNKOF -0.88 (0.18) -1.56* (0.48) LNEU 1.33* (0.27) 2.46* (0.49) LNURPOP 0.18 (0.22) -1.28* (0.20) C 17.28* (2.09) Note: * show level of significance at 1%, while standard errors are in parenthesis Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 485 Table 6 Results of Wald Test Variables F-statistic(Prob.) Decisions LNDCB 23.51(0.000) An asymmetric relationship exists between LNDCB and LNGDP LNDCB 4.86(0.038) An asymmetric relationship exists between LNDCB and LNCO2 Model 1 0.0 0.2 0.4 0.6 0.8 1.0 1 3 5 7 9 11 13 15 Multiplier for LNDCB(+) Multiplier for LNDCB(-) Asymmetry Plot (with C.I.) Model 2 -.6 -.4 -.2 .0 .2 .4 .6 .8 1 3 5 7 9 11 13 15 Multiplier for LNDCB(+) Multiplier for LNDCB(-) Asymmetry Plot (with C.I.) Figure 3 Dynamic multiplier effects The other variables which are used in both models for finding the asymmetric behavior of the economic growth and carbon emissions include primary education (LNEDU), energy use (LNEU), globalization (KOF), and urban populations (LNURPOP). In model 1, primary education (LNEDU) significantly increases economic growth (Nenbee & Danielle, 2021; Maneejuk & Yamaka, 2021). Globalization inversely impacts economic growth (Shaheer & Butt, 2021). Energy use (LNEDU) positively impacts economic growth (Abbasi et al. 2021). In model 2 primary education (LNEDU) has positive impact on carbon emissions. The people who have primary education niether care about environmental pollutions nor even prefer to use modern eco-friendly technologies. The globalization has negative impact on carbon emissions (Islam et al., 2021; Sharif et al., 2020; Bu et al., 2016). It means that globalization is not harmful to environmental degradation in Pakistan. The trade liberalization after 1980 provided more opportunities to establish different industries in Pakistan which mostly use energy-efficient technologies and helped in declining carbon pollution. Energy use (LNEU) has positive impact on carbon emissions. Pakistan meets most of its energy requirements from fossil fuels which are considered as major contributor to carbon emissions. As far as short run analysis is concerned in both models, the values of error correction terms (ECM) are negative and significant which means a disequilibrium in the models converge towards the Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 486 equilibrium. In both the models values of error correction terms in both models are -0.58 and -0.71 respectively which means model 1, 58% and model 2, 71% converge to long run equilibrium in one period. Table 7 short coefficient of NARDL 1(a) 2(a) Variable LNGDP LNCO2 ECM -0.58* (0.11) -0.71* (0.15) D(LNGDP(-1)) 0.35** (0.17) D(LNCO2(-1)) 0.19 (0.16) D(LNDCB + ) 0.25* (0.06) 0.19 (0.16) D(LNDCB + (-1)) -0.09 (0.06) 0.07 (0.16) D(LNDCB - ) -0.06 (0.04) 0.11 (0.10) D(LNDCB - (-1)) 0.11* (0.04) 0.35* (0.100 D(LNEU) 0.33** (0.14) 1.22* (0.33) D(LNEU(-1)) -0.49** (0.19) -0.70 (0.44) D(LNKOF) -0.41** (0.14) -0.99** (0.38) D(LNKOF(-1)) 0.18 (0.11) -0.12 (0.25) D(LNEDU) 0.34** (0.12) 0.52*** (0.26) D(LNEDU(-1)) -0.84** (0.34) D(LNURPOP) 0.10 (0.14) -9.44 (10.12) D(LNURPOP(-1)) 12.32 (13.82) Note: *, **, *** show level of significance at 1%, 5% and 10% while standard errors are in parenthesis Figure 4 presents the graphs of CUSUM and CUSUMSQ. The trend line lie in between the upper and lower boundary which means that both models are stable. Both the models also passed the diagnostic test. Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 487 Model 1 -15 -10 -5 0 5 10 15 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 CUSUM 5% Significance -0.4 0.0 0.4 0.8 1.2 1.6 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 CUSUM of Squares 5% Significance Model 2 -12 -8 -4 0 4 8 12 2004 2006 2008 2010 2012 2014 2016 2018 2020 CUSUM 5% Significance -0.4 0.0 0.4 0.8 1.2 1.6 2004 2006 2008 2010 2012 2014 2016 2018 2020 CUSUM of Squares 5% Significance 5. Conclusion This study explores the asymmetric relation between financial development, economic growth, and environmental pollution in Pakistan. For this purpose annual time series data has been used from 1980 to 2020. The bound test finds that financial development has a long-run relationship with economic growth (LNGDP) and environmental pollution (LNCO2). The empirical findings of NARDL reveal that financial development exerts asymmetric long-run impact on LNGDP and LNCO2 in both models. An increase or decrease in financial development significantly increase LNGDP (Qamruzzaman & Jianguo, 2018; Shahbaz et al., 2017). Domestic credit to banks and the private sector at soft conditions increase investment which increases economic growth. While on the other hand, positive shocks in financial development decline CO2 emissions and the negative shocks of financial development increase CO2 emissions in Pakistan (Ahmad et al., 2021; Ahmad et al., 2020; Lahiani, 2020; Odugbesan & Adebayo, 2020; Omoke et al., 2020; Jakada et al., 2020; Karasoy et al., 2019). In Pakistan, foreign aid and debts are major sources to improve the financial sector. These loans exerts positive impact on financial development and increase investment through import of environment friendly technologies in Pakistan. Moreover, the improvement in financial development induces private investors to expand their scale of operations for earning more profits. In summary, the financial institutions can play an important role to improve environment and achieve rapid economic growth in Pakistan. This study recommends that the State Banks of Pakistan and other international financial organizations should provide loans at zero-interest rate for inducing the private investors to use low carbon emission technologies. It will help to achieve rapid economic growth and reduce carbon emissions in Pakistan References Abbasi, K. R., Shahbaz, M., Jiao, Z., & Tufail, M. (2021). How energy consumption, industrial growth, urbanization, and CO2 emissions affect economic growth in Pakistan? A novel dynamic ARDL simulations approach. Energy, 221, 119 Ahmad, M., Khan, Z., Ur Rahman, Z., & Khan, S. (2018). Does financial development Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 488 asymmetrically affect CO2 emissions in China? An application of the nonlinear autoregressive distributed lag (NARDL) model. Carbon Management, 9(6), 631-644. https://doi.org/10.1080/17583004.2018.1529998. Ahmed, F., Kousar, S., Pervaiz, A., & Ramos-Requena, J. P. (2020). Financial development, institutional quality, and environmental degradation nexus: New evidence from asymmetric ARDL co-integration approach. Sustainability, 12(18), 7812. https://doi.org/10.3390/su12187812. Ahmed, Z., Zhang, B., & Cary, M. (2021). Linking economic globalization, economic growth, financial development, and ecological footprint: Evidence from symmetric and asymmetric ARDL. Ecological Indicators, 121, 107060. https://doi.org/10.1016/j.ecolind.2020.107060. Aigheyisi, O. S., & Edore, J. E. (2019). Asymmetric Effects of Money Supply Growth on Economic Growth in Nigeria: An Empirical Investigation. Kardan Journal of Economics and Management Sciences, 2(3), 27-42. Ali, S., Waqas, H., & Ahmad, N. (2015). Analyzing the dynamics of energy consumption, liberalization, financial development, poverty and carbon emissions in Pakistan. J Appl Environ Biol Sci, 5(4), 166-183. Asteriou, D., & Spanos, K. (2019). The relationship between financial development and economic growth during the recent crisis: Evidence from the EU. Finance Research Letters, 28, 238- 245.https://doi.org/10.1016/j.frl.2018.05.011 Bano, S., Zhao, Y., Ahmad, A., Wang, S., & Liu, Y. (2018). Identifying the impacts of human capital on carbon emissions in Pakistan. Journal of Cleaner Production, 183, 1082-1092. https://doi.org/10.1016/j.jclepro.2018.02.008. Benoit, K. (2011). Linear regression models with logarithmic transformations. London School of Economics, London, 22(1), 23–36. Bist, J. P. (2018). Financial development and economic growth: Evidence from a panel of 16 African and non-African low-income countries. Cogent Economics & Finance, 6(1), 1449780.https://doi.org/10.1080/23322039.2018.1449780 Bloomberg (2016). What’s next for Asia’s best-performing Stock Market. https://www.bloomberg.com/news/articles/2016-06-14/best-performing-asian-stock- market-may-get-extra-boost-from-msci. Bu, M., Lin, C. T., & Zhang, B. (2016). Globalization and climate change: new empirical panel data evidence. Journal of Economic Surveys, 30(3), 577-595.https://doi.org/10.1111/joes.12162. Cetin, M., Ecevit, E., & Yucel, A. G. (2018). The impact of economic growth, energy consumption, trade openness, and financial development on carbon emissions: empirical evidence from Turkey. Environmental Science and Pollution Research, 25(36), 36589- 36603.https://doi.org/10.1007/s11356-018-3526-5. Chen, H., Hongo, D. O., Ssali, M. W., Nyaranga, M. S., & Nderitu, C. W. (2020). The asymmetric influence of financial development on economic growth in Kenya: evidence from NARDL. SAGE Open, 10(1), 2158244019894071. https://doi.org/10.1177/2158244019894071. Chen, S., Saleem, N., & Bari, M. W. (2019). Financial development and its moderating role in environmental Kuznets curve: evidence from Pakistan. Environmental Science and Pollution Research, 26(19), 19305-19319. https://doi.org/10.1007/s11356-019-05290-z. Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association, 74(366a), 427-431. Dreher, A., Gaston, N., & Martens, P. (2008). Consequences of globalization reconsidered: Applying the KOF index. In Measuring Globalization (pp. 75-171). Springer, New York, NY. Global Climate Risk Index (2021).Who suffers most from extreme weathers events? Weather https://doi.org/10.1080/17583004.2018.1529998 https://doi.org/10.3390/su12187812 https://doi.org/10.1016/j.ecolind.2020.107060 https://doi.org/10.1016/j.frl.2018.05.011 https://doi.org/10.1016/j.jclepro.2018.02.008 https://doi.org/10.1080/23322039.2018.1449780 https://www.bloomberg.com/news/articles/2016-06-14/best-performing-asian-stock-market-may-get-extra-boost-from-msci https://www.bloomberg.com/news/articles/2016-06-14/best-performing-asian-stock-market-may-get-extra-boost-from-msci https://doi.org/10.1111/joes.12162 https://doi.org/10.1007/s11356-018-3526-5 https://doi.org/10.1177%2F2158244019894071 https://doi.org/10.1007/s11356-019-05290-z Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 489 related loss events in 2019- and 200-2019. https://germanwatch.org/sites/default/files/Global%20Climate%20Risk%20Index%2020 21_2.pdf. Godil, D. I., Sharif, A., Agha, H., & Jermsittiparsert, K. (2020). The dynamic nonlinear influence of ICT, financial development, and institutional quality on CO2 emission in Pakistan: new insights from QARDL approach. Environmental Science and Pollution Research, 27(19), 24190-24200. Haini, H. (2021). Examining the impact of ICT, human capital and carbon emissions: Evidence from the ASEAN economies. International Economics, 166, 116-125. https://doi.org/10.1016/j.inteco.2021.03.003. Ibrahim, M., & Alagidede, I. P. (2020). Asymmetric effects of financial development on economic growth in Ghana. Journal of Sustainable Finance & Investment, 10(4), 371-387. https://doi.org/10.1080/20430795.2019.1706142. Islam, M. M., Khan, M. K., Tareque, M., Jehan, N., & Dagar, V. (2021). Impact of globalization, foreign direct investment, and energy consumption on CO 2 emissions in Bangladesh: Does institutional quality matter?. Environmental Science and Pollution Research, 1-21. https://doi.org/10.1007/s11356-021-13441-4. Jakada, A. H., Mahmood, S., Ahmad, A. U., Farouq, I. S., & Mustapha, U. A. (2020). Financial development and the quality of the environment in Nigeria: an application of non-linear ARLD approach. Res World Econ, 11, 78-92. Javid, M., & Sharif, F. (2016). Environmental Kuznets curve and financial development in Pakistan. Renewable and Sustainable Energy Reviews, 54, 406-414. https://doi.org/10.1016/j.rser.2015.10.019. Jiang, T., Huang, S., & Yang, J. (2019). Structural carbon emissions from industry and energy systems in China: An input-output analysis. Journal of Cleaner Production, 240, 118116.https://doi.org/10.1016/j.jclepro.2019.118116 Karasoy, A. (2019). Drivers of carbon emissions in Turkey: considering asymmetric impacts. Environmental Science and Pollution Research, 26(9), 9219-9231. https://doi.org/10.1007/s11356-019-04354-4. Kausar, R., & Gull, M. K. B. S. (2020). An Effect of Money Supply on Economic Growth: Evidence from Pakistan. Journal of Contemporary Macroeconomic Issues, 1(1), 34-43. Khan, H., Khan, I., & Binh, T. T. (2020). The heterogeneity of renewable energy consumption, carbon emission and financial development in the globe: a panel quantile regression approach. Energy Reports, 6, 859-867.https://doi.org/10.1016/j.egyr.2020.04.002 Khan, M. I., Teng, J. Z., & Khan, M. K. (2020). The impact of macroeconomic and financial development on carbon dioxide emissions in Pakistan: evidence with a novel dynamic simulated ARDL approach. Environmental Science and Pollution Research, 27(31), 39560- 39571. https://doi.org/10.1007/s11356-020-09304-z. Khan, M. K., Teng, J. Z., Khan, M. I., & Khan, M. O. (2019). Impact of globalization, economic factors and energy consumption on CO2 emissions in Pakistan. Science of the total environment, 688, 424-436. https://doi.org/10.1016/j.scitotenv.2019.06.065. Khan, M. U. H., & Hanif, M. N. (2019). Empirical evaluation of ‘structure-conduct- performance’and ‘efficient-structure’paradigms in banking sector of Pakistan. International Review of Applied Economics, 33(5), 682-696. https://doi.org/10.1080/02692171.2018.1518411 Lahiani, A. (2020). Is financial development good for the environment? An asymmetric analysis with CO 2 emissions in China. Environmental Science and Pollution Research, 27(8), 7901- 7909. https://doi.org/10.1007/s11356-019-07467-y. https://germanwatch.org/sites/default/files/Global%20Climate%20Risk%20Index%202021_2.pdf https://germanwatch.org/sites/default/files/Global%20Climate%20Risk%20Index%202021_2.pdf https://doi.org/10.1016/j.inteco.2021.03.003 https://doi.org/10.1080/20430795.2019.1706142 https://doi.org/10.1007/s11356-021-13441-4 https://doi.org/10.1016/j.rser.2015.10.019 https://doi.org/10.1016/j.jclepro.2019.118116 https://doi.org/10.1007/s11356-019-04354-4 https://doi.org/10.1016/j.egyr.2020.04.002 https://doi.org/10.1007/s11356-020-09304-z https://doi.org/10.1016/j.scitotenv.2019.06.065 https://doi.org/10.1080/02692171.2018.1518411 https://doi.org/10.1007/s11356-019-07467-y Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 490 Ling, G., Razzaq, A., Guo, Y., Fatima, T., & Shahzad, F. (2021). Asymmetric and time-varying linkages between carbon emissions, globalization, natural resources and financial development in China. Environment, Development and Sustainability, 1-29. https://doi.org/10.1007/s10668-021-01724-2. Majeed, M. T., Samreen, I., Tauqir, A., & Mazhar, M. (2020). The asymmetric relationship between financial development and CO 2 emissions: the case of Pakistan. SN Applied Sciences, 2(5), 1-11. https://doi.org/10.1007/s42452-020-2627-1. Maneejuk, P., & Yamaka, W. (2021). The Impact of Higher Education on Economic Growth in ASEAN-5 Countries. Sustainability, 13(2), 520. https://doi.org/10.3390/su13020520. MOCC (2021). Ten billion trees tsunami programme - phase-i up-scaling of green Pakistan programme (revised). http://www.mocc.gov.pk/ProjectDetail/M2QzOWJmMjUtZTU3MC00NmFkLWE4YmMtZDF hMmRlOGU2NGRh. Nassani, A. A., Aldakhil, A. M., & Zaman, K. (2021). Ecological footprints jeopardy for mineral resource extraction: efficient use of energy, financial development and insurance services to conserve natural resources. Resources Policy, 74, 102271. https://doi.org/10.1016/j.resourpol.2021.102271. Nenbee, S. G., & Danielle, I. E. (2021). Primary School Enrolment, Public Spending on Education and Economic Growth in Nigeria. Mediterranean Journal of Social Sciences, 12(5), 103-103. Neog, Y., & Yadava, A. K. (2020). Nexus among CO2 emissions, remittances, and financial development: a NARDL approach for India. Environmental Science and Pollution Research, 27(35), 44470-44481. https://doi.org/10.1007/s11356-020-10198-0. Ng, S., & Perron, P. (1995). Unit root tests in ARMA models with data-dependent methods for the selection of the truncation lag. Journal of the American Statistical Association, 90(429), 268-281. NOAA (2020). Global climate report- annual 2020. https://www.ncdc.noaa.gov/sotc/global/202013. Odugbesan, J. A., & Adebayo, T. S. (2020). The symmetrical and asymmetrical effects of foreign direct investment and financial development on carbon emission: evidence from Nigeria. SN Applied Sciences, 2(12), 1-15. Omoke, P. C., Nwani, C., Effiong, E. L., Evbuomwan, O. O., & Emenekwe, C. C. (2020). The impact of financial development on carbon, non-carbon, and total ecological footprint in Nigeria: new evidence from asymmetric dynamic analysis. Environmental Science and Pollution Research, 27(17), 21628-21646. https://doi.org/10.1007/s11356-020-08382-3. Perron, P. (1990). Testing for a unit root in a time series with a changing mean. Journal of Business & Economic Statistics, 8(2), 153-162. DOI: 10.1080/07350015.1990.10509786. Pesaran MH, Shin Y, Smith RJ (2001) Bounds testing approaches to the analysis of level relationships. J Appl Econ 16(3):289–326. https:// doi.org/10.1002/jae.616. Phillips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346. https://doi.org/10.1093/biomet/75.2.335. Qamruzzaman, M., & Jianguo, W. (2018). Investigation of the asymmetric relationship between financial innovation, banking sector development, and economic growth. Quantitative Finance and Economics, 2(4), 952-980. Raggad, B. (2020). Economic development, energy consumption, financial development, and carbon dioxide emissions in Saudi Arabia: new evidence from a nonlinear and asymmetric analysis. Environmental Science and Pollution Research, 27(17), 21872-21891. https://doi.org/10.1007/s11356-020-08390-3. Raza, S. A., & Shah, N. (2018). Impact of financial development, economic growth and energy https://doi.org/10.1007/s10668-021-01724-2 https://doi.org/10.1007/s42452-020-2627-1 https://doi.org/10.3390/su13020520 http://www.mocc.gov.pk/ProjectDetail/M2QzOWJmMjUtZTU3MC00NmFkLWE4YmMtZDFhMmRlOGU2NGRh http://www.mocc.gov.pk/ProjectDetail/M2QzOWJmMjUtZTU3MC00NmFkLWE4YmMtZDFhMmRlOGU2NGRh https://doi.org/10.1016/j.resourpol.2021.102271 https://doi.org/10.1007/s11356-020-10198-0 https://www.ncdc.noaa.gov/sotc/global/202013 https://doi.org/10.1007/s11356-020-08382-3 https://doi.org/10.1080/07350015.1990.10509786 https://doi.org/10.1093/biomet/75.2.335 https://doi.org/10.1007/s11356-020-08390-3 Review of Economics and Development Studies, Vol. 7 (4) 2021, 475 - 491 491 consumption on environmental degradation: evidence from Pakistan. In MPRA paper 87095 University Library of Munich Germany. Shahbaz, M., Van Hoang, T. H., Mahalik, M. K., & Roubaud, D. (2017). Energy consumption, financial development and economic growth in India: New evidence from a nonlinear and asymmetric analysis. Energy Economics, 63, 199-212. https://doi.org/10.1016/j.eneco.2017.01.023 Shaheer, M. & Butt, U. U. (2021). Asymmetric Impact of Globalization on Economic Growth in Pakistan by Using ARDI Model. International Journal of Business, Economics and Finance. http://dx.doi.org/10.2139/ssrn.3860498. Shahzad, S. J. H., Kumar, R. R., Zakaria, M., & Hurr, M. (2017). Carbon emission, energy consumption, trade openness and financial development in Pakistan: a revisit. Renewable and Sustainable Energy Reviews, 70, 185-192. https://doi.org/10.1016/j.rser.2016.11.042. Sharif, A., Godil, D. I., Xu, B., Sinha, A., Khan, S. A. R., & Jermsittiparsert, K. (2020). Revisiting the role of tourism and globalization in environmental degradation in China: Fresh insights from the quantile ARDL approach. Journal of Cleaner Production, 272, 122906.. https://doi.org/10.1016/j.jclepro.2020.122906 Shin, Y., & Schmidt, P. (1992). The KPSS stationarity test as a unit root test. Economics Letters, 38(4), 387-392. 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. Siddique, H. M. A. (2017). Impact of financial development and energy consumption on CO2 emissions: evidence from Pakistan. Bulletin of Business and Economics, 6 (2), 68-73. Svirydzenka, K. (2016). Introducing a new broad-based index of financial development. International Monetary Fund. Swissre (2021) . Climate and natural catastrophe risk. https://www.swissre.com/institute/research/topics-and-risk-dialogues/climate-and- natural-catastrophe-risk.html. WMO (2020). The state of the global climate 2020. https://public.wmo.int/en/our- mandate/climate/wmo-statement-state-of-global-climate. World Bank (2020). Pollution management and environmental health program. https://www.worldbank.org/en/programs/pollution-management-and-environmental- health-program. Worldometer (2016).Carbon Dioxide (CO2) Emissions by Country .https://www.worldometers.info/co2-emissions/co2-emissions-by-country/. Yang, F. (2019). The impact of financial development on economic growth in middle-income countries. Journal of International Financial Markets, Institutions and Money, 59, 74- 89..https://doi.org/10.1016/j.intfin.2018.11.008 . Yao, X., Kou, D., Shao, S., Li, X., Wang, W., & Zhang, C. (2018). Can urbanization process and carbon emission abatement be harmonious? New evidence from China. Environmental Impact Assessment Review, 71, 70-83. https://doi.org/10.1016/j.eiar.2018.04.005. Zhang, Y. J. (2011). The impact of financial development on carbon emissions: An empirical analysis in China. Energy policy, 39(4), 2197-2203. https://doi.org/10.1016/j.enpol.2011.02.026. Zivot, E., & Andrews, D. W. K. (2002). Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of business & economic statistics, 20(1), 25-44. https://doi.org/10.1016/j.eneco.2017.01.023 https://dx.doi.org/10.2139/ssrn.3860498 https://doi.org/10.1016/j.rser.2016.11.042 https://doi.org/10.1016/j.jclepro.2020.122906 https://www.swissre.com/institute/research/topics-and-risk-dialogues/climate-and-natural-catastrophe-risk.html https://www.swissre.com/institute/research/topics-and-risk-dialogues/climate-and-natural-catastrophe-risk.html https://public.wmo.int/en/our-mandate/climate/wmo-statement-state-of-global-climate https://public.wmo.int/en/our-mandate/climate/wmo-statement-state-of-global-climate https://www.worldbank.org/en/programs/pollution-management-and-environmental-health-program https://www.worldbank.org/en/programs/pollution-management-and-environmental-health-program https://www.worldometers.info/co2-emissions/co2-emissions-by-country/ https://doi.org/10.1016/j.intfin.2018.11.008 https://doi.org/10.1016/j.eiar.2018.04.005 https://doi.org/10.1016/j.enpol.2011.02.026