American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 ISSN 2641-4937 E-ISSN 2641-4953 Published by American Center of Science and Education, USA 11 A Study of Monetary Integration in West Africa and Its Implications on Trade on Developing Country (Africa) Rabnawaz Khan School of Finance and Economics Jiangsu University, Zhenjiang Jiangsu, Zhenjiang 212013, People’s Republic of China E-mail: khan.rab@stmail.ujs.edu.cn Jin Xinxin School of Literature art Jiangsu University, Zhenjiang Jiangsu, Zhenjiang 212013, People’s Republic of China E-mail: 1048186766@qq.com Abstract It shows the monetary investigation in west countries the big flow in economy by the gross value change effects, also the value of debt policy with debt management strategies to control the budgetary risk of long-term economy from sustainability. The intellectual policies of inflation, GDP, trade, and services and merchandise trade has affected on the West African country’s monetary policies. The implication of trade by a lag of exchange rate indicators has a positive and significant effect. The estimated results reflect the dynamic implication of trade with liquidity and proper monitoring policies. The GDP, gross value (GVA), debt policies, equity of public administration, trade in service and merchandise trade is positive and significant, all are significant. We suggest the optimum control of liquidity with trade service policy recommendations in different countries. The research method was based on 5 countries from the 16 countries of western African and elaborated by their individual indicators with the least square method. The gross value of debts and public administration controlled the development aim of an entire state with strategic and planned environment for state and reduce the level of inflation in small and enterprise section and the results analyzed the policy makers implement planned in implication of trade with domestic currency and long run endogeneity. The results analyzed the monetary policies affecting the level of growth of an individual country. Keywords: Monetary, West African countries, Trade, Economy. 1. Introduction We have increased the regional interaction the economy by the priority of free trade and growth. According to Negotiating Forum (NF) the Continental Free Trade Area (CFTA) is the path of trade and investment which convened for CFTA. The investment of incorporate of 53 African countries, represent 1 billion people with $3 trillion GDP. The policy of implication of west African countries controlled by regional economic community (REC’s) likewise West Economic and Monetary Union (WAEMU) is the main building block of achievement of free trade and monetary implication.(K. Ahmed, Bhattacharya, Shaikh, Ramzan, & Ozturk, 2017; Aydin, 2019; Kong & Khan, 2019; MengYunet al., 2018) The highest level of intraregional trade in West African countries is low when it compares to the level of a custom union trade in WAEMU and EU’s with 25-60 percent. Fig 1. mailto:khan.rab@stmail.ujs.edu.cn mailto:1048186766@qq.com www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 12 Figure 1: Intra-regional export for WEMU and ASEAN: Sources: UNCTA, 2015 Second the monetary policies and implication of trade is satiability of CFA franc zone in African countries in the term of macroeconomic. (Bekun, Emir, & Sarkodie, 2019; Grossman G, 1995) The important issues some countries unstable and have taking weak attention of historically monetary institutional framework. However, the currencies depreciate in an external environment in the region’s stability and legitimate to achieve the competitiveness of individual policies. Figure 2: Franc stability, Sauce: Hallet, 2008 The global fixed exchange rate has benefited to foreign trade and taxation policies with achieving macroeconomic stability.(Abid, 2017; Dong, Wang, & Guo, 2016; J. Du & Zhang, 2018) The research showed the competitiveness challenges of GDP, trade services, and merchandise trade. The region economic communities in west countries have directly infect the economy by different strategic policies. www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 13 The prior research implication based on economic development and south African country’s economic policies and didn’t mention the (Adom & Kwakwa, 2014) strategic policies regarding individual expect of foreign exchange rate, federal economic development trade and effected issues of GDP by CFA.(Adom & Kwakwa, 2014) Therefore, this research is most import issues weighted and determined the strategic policy with CPIA debt policies, inflation, GDP deflator, trade services, trade (GDP),(G. Du, Liu, Lei, & Huang, 2018; Riaz et al., 2018) merchandise trade and merchandise export. We base the second section of this research on the literature. We base the third section of this research on the method. 4th section showed results and analysis and final section held with recommendation and conclusion. 2. Literature We base prior research on implemented policies and strategic changes in sub-Saharan countries and highlighted the issues of economic development with individual effects. The convergence member of countries showed i.e. inflation, growth, per capita and currency union. (Coleman, 2010; Harvey & Cushing, 2015)The common stock of macroeconomic policies more in under developing countries, which makes a common strategic policy for individual states. Several theories in literature is showing the impact of policy regarding the monitoring policies, which created on asset prices, patents, development and growing of economy. The systematical approach of the theories effects on economics variables.(Button, Martini, Scotti, & Volta, 2019; Osabutey & Jackson, 2019) the first view is liquidity approach emphasized the increasing liquidity, asset prices increase, and it acts as a link in the transmission of liquidity assets on the economic activities with the wide range of development skills and determined policies of an individual government.(Bensassi & Jarreau, 2019; Tsao et al., 2019) the other expects of low and stable inflation cause of lack of monitoring policies in stabilizing the high level of investment.(Keho, 2017; Yaya, Ling, Furuoka, Rose Ezeoke, & Jacob, 2019) 2nd the presented a dynamic equilibrium of monitoring policies based on the bubble in asset prices, in addition poor monetary policy design such as rate rules of sustainable long-term inflation. 3rdthe trend survey of effect on money and monetary policy on asset prices including the exchange rate the monetarist theory effects on uncertainty, government policies and economic growth. The high-quality boom of assets price, growth of monetary supply and investment. (Asongu, Folarin, & Biekpe, 2019; Mikayilov, Hasanov, & Galeotti, 2018; Riaz et al., 2018)Therefore, the prior of research implicated the trade in big rule and hold the effect of a portfolio of a financial institution regarding huge investment and development policies. 4th the policies of investment in a different channel by self-crating the huge gap in monetary policies, where the different price channel has tagging different prices level, credit ratio, exchange rate cause of the intellectual policies of inflation, GDP, trade and services and merchandise trade has affected on the west African countries monetary policies. The rate of a channel determined the effects on price and exchange rate (K. Ahmed, Bhattacharya, M., Shaikh, Z., Ramzan, M., & Ozturk, I 2017; Cham, 2016). The exchange rate channel, other asset price channels, and the credit channel. Since the present study surveys the impact of monetary policy on the exchange rate, it determines the level of intensity in financing. (Al-Mulali, Ozturk, & Solarin, 2016; Apergis & Ozturk, 2015) . The countries competitiveness will need to ensure the macroeconomic stability, which improved the business climate of trade, reduce the hard infrastructure stability and technology with transfer infrastructure gap.(Bo, 2015; Schwerhoff & Sy, 2017; Zhao & Kim, 2009) The investment of trade and strategic policies of economic development such as skills has increased agriculture as well with adept policies, training and extension program and build capabilities of domestic firms.(Acheampong, 2018 Awad & Abugamos, 2017; Harvey & Cushing, 2015) The structural transformation will require leverage of the ICT sector of productivity, financial tie and domestic macroeconomics frameworks. 3. Data, Model and Results We base this research paper research method on liner regression between gross value, CPIA debt policies, public administration with regional trade, GDP per capita, service in trade, trade of an individual,(Harding, 2007; Im, Pesaran, & Shin, 2003; Zhang, Liao, & Hao, 2018) merchandise trade and export of low income economy. It shows the stability of model the strategic policies,, so the results conducted by the regression. In a first step unit root is taking for the stationary and non-stationary level of intimal of 5 countries from the 16 west African countries. www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 14 Table 1. Indicators Indicators (Benin, Burkina Faso, Ghana, Guinea, Guinea- Bissau) Indicator WB Symbol Gross value added at basic prices (GVA) (current US$) NY.GDP.FCST.CD GVA CPIA debt policy rating (1 = low to 6 = high) IQ.CPA.DEBT.XQ CPIAD CPIA quality of public administration rating (1=low to 6=high) IQ.CPA.PADM.XQ CPIAQ Inflation, GDP deflator (annual %) NY.GDP.DEFL.KD. ZG IGD GDP per capita (current US$) NY.GDP.PCAP.CD GDPPC Trade in services (% of GDP) BG.GSR.NFSV.GD.ZS TS Trade (% of GDP) NE.TRD.GNFS.ZS TR Merchandise trade (% of GDP) TG.VAL.TOTL.GD.ZS MTG Merchandise exports to low- and middle-income economies within region (% of total merchandise exports) TX.VAL.MRCH.WR.ZS MEL It indicates Table 1 the gross values of different indicators as per indicator codes. The strategic policies have been transiting with 9 indicators and individually defined with the period of 1960-2018. However, the export level of merchandise. (Perron, 1988; Sinha & Shahbaz, 2018) Results and Analysis The results and analysis were analyzed using the liner method. In 1st stage mean deviation of individual variables have been taking by skewness and Kurtosis, and the deviation analyzed by mean and standard deviation. The mean deviation is greater from the standard deviation. The individual indicator shows a significant effect on each individual variable(Cheng, Ren, Wang, & Yan, 2019; Im et al., 2003; Saqib, Ahmad, & Amezcua-Prieto, 2018; Zhao & Kim, 2009). Table 2. Mean deviation CPIAD CPIAQ GDPPC GVA IGD MEL MTG TR TS Mean 3.25714 3 3.08571 4 422.502 2 4.85E+ 09 13.9884 1 18.4213 7 40.7366 6 49.1624 2 12.7690 1 Median 3.5 3 341.527 5 2.36E+ 09 6.38697 4 12.6578 4 39.5120 5 46.9411 1 12.7851 5 Maximum 4.5 3.5 2378.16 5.98E+ 10 123.061 2 88.2146 8 93.1964 1 132.050 2 27.3494 8 Minimum 1 2 68.4247 5 1.53E+ 08 - 6.34567 7 0.36662 5 4.53936 3 6.32034 3 4.26148 1 Std. Dev. 0.81978 0.40799 356.543 8.64E+ 20.8678 18.5417 15.2425 19.6215 4.24076 www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 15 6 5 3 09 8 1 4 3 4 Skewness - 0.74088 1 - 0.64428 6 2.69987 6 4.18352 1 2.62944 2 1.52885 3 0.39060 3 0.86074 1 0.70782 8 Kurtosis 2.59803 2 2.66245 3 12.4324 8 22.1229 5 10.7893 9 4.85654 2 3.59937 4 4.83443 7 4.13222 3 Jarque- Bera 6.87516 5.17520 3 1274.80 8 4356.94 5 934.830 9 136.494 1 10.4628 6 68.0331 1 22.3174 8 Probability 0.03214 2 0.0752 0 0 0 0 0.00534 6 0 0.00001 4 Sum 228 216 109428. 1 1.16E+ 12 3553.05 6 4715.87 10550.8 12683.9 2081.34 8 Sum Sq. Dev. 46.3714 3 11.4857 1 3279776 9 1.78E+ 22 110173. 5 87667.6 8 59942.4 6 98946.1 1 2913.42 Observatio ns 70 70 259 240 254 256 259 258 163 The given results of analysis have interoperated the distribution t-factors within between valuation. www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 16 Table 3. Covariance Covariance Analysis: Ordinary t-Statistic Probability CPIAD CPIAQ GDPPC GVA IGD MEL MTG TR TS CPIAD 0.685562 CPIAQ 0.250355 0.153018 9.670279 ----- GDPPC 80.13973 66.1267 176071 1.881582 3.493724 ----- 0.0645 0.0009 ----- GVA 3.87E+09 3.29E+09 5.63E+12 1.97E+20 2.800963 5.934168 25.77055 ----- 0.0068 0 0 ----- IGD -0.379726 1.222435 1808.744 7.36E+10 289.5489 -0.214 1.482909 2.078473 2.571124 ----- 0.8312 0.1431 0.0417 0.0125 ----- MEL 4.212973 1.085542 1030.478 3.36E+10 -16.18827 302.9732 2.426221 1.281843 1.131174 1.101121 -0.434467 ----- www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 17 0.0181 0.2046 0.2623 0.275 0.6654 ----- MTG 3.394529 1.364002 1517.276 5.06E+10 23.7466 39.62843 136.398 2.975628 2.483048 2.584455 2.575627 0.955278 1.577552 ----- 0.0041 0.0157 0.0121 0.0124 0.3431 0.1197 ----- TR -0.120382 0.812654 2488.352 7.59E+10 63.69064 -17.78276 152.6474 272.7775 -0.069875 1.006384 3.053553 2.748993 1.846842 -0.491921 10.27479 ----- 0.9445 0.3181 0.0033 0.0078 0.0695 0.6245 0 ----- TS 0.717598 0.461766 965.8295 3.52E+10 3.87425 9.645411 14.46673 14.38365 20.8171 1.53567 2.125966 4.637605 5.225046 0.396578 0.971193 2.238991 1.543421 ----- 0.1296 0.0374 0 0 0.693 0.3352 0.0287 0.1277 ----- www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 18 Table 2 The significant relationships analyzed by the probability level of linear value, where the highest mean deviation is directly affecting the monetary integration and implication of trade in African countries. the integration of value has been analyzed by the CPIAD, IGD and TS, where the gross value at the basic rate, inflation of GDP with trade service, merchandise trade, export and the quality of public administration in debt value and interpreted the monetary policies of Africa and implication on trade. Table 3 Figure 3: Mean and covariance Table 4. Equity Test for Equality of Variances Between Series Method df Value Probability Bartlett 8 59193.83 0 Levene (8, 1820) 75.12375 0 Brown-Forsythe (8, 1820) 43.85331 0 Category Statistics Mean Abs. Mean Abs. Variable Count Std. Dev. Mean Diff. Median Diff. CPIAD 70 0.819786 0.706122 0.671429 CPIAQ 70 0.407995 0.331429 0.314286 www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 19 GDPPC 259 356.5433 234.0249 218.1158 GVA 240 8.64E+09 4.52E+09 3.82E+09 IGD 254 20.86788 13.7503 12.14635 MEL 256 18.54171 13.93338 13.22127 MTG 259 15.24254 11.83501 11.81549 TR 258 19.62153 14.58696 14.49539 TS 163 4.240764 3.173404 3.173305 All 1829 3.53E+09 5.93E+08 5.02E+08 Bartlett weighted standard deviation: 3.13e+09 Error! Filename not specified. Figure 4: Least limitation Fig 3 And the highest mean deviation of IGD and TS are indicated the highly effects of domestic trade in private sectors, its mean if the investment of individual countries will rise in private sector so effect on the monitoring policy. Table 4 Table 5.Observation Autocorrelation Partial Correlation AC PAC Q-Stat Prob **| . | **| . | 1 -0.223 -0.223 3.1455 0.076 .*| . | .*| . | 2 -0.116 -0.174 4.0065 0.135 **| . | **| . | 3 -0.224 -0.318 7.2805 0.063 . |*. | . | . | 4 0.17 -0.003 9.195 0.056 . | . | .*| . | 5 -0.052 -0.113 9.376 0.095 . | . | .*| . | 6 -0.002 -0.093 9.3762 0.153 . | . | . | . | 7 -0.008 -0.014 9.3805 0.226 . | . | .*| . | 8 -0.006 -0.079 9.3832 0.311 . | . | . | . | 9 -0.003 -0.039 9.3838 0.403 . | . | . | . | 10 0.001 -0.028 9.3838 0.496 . | . | . | . | 11 -0.003 -0.048 9.3847 0.586 www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 20 Table 5-6 is indicated the actual effects of fitted and residual effect by the level of actual intensity. The foreign trade computed by the debt policies and quality of public administration which is the part of monitoring policies. The trade service and merchandise trade with in economic growth with exports. Table 7 is indicated the indicators different policies with sources of inflation and GDP per capita, the highlighted part of Trade service and investment, likewise, foreign investment under the stated law implement the rules and policies of CPIA quality and debit policies. Fig 4 Table 6. Indicated observation CPIAD,CPIAQ(-i) CPIAD,CPIAQ(+i) i lag lead . |******** | . |******** | 0 0.7564 0.7564 . |******* | . |******* | 1 0.6706 0.7213 . |****** | . |******* | 2 0.581 0.6862 . |***** | . |******* | 3 0.5078 0.6511 . |**** | . |****** | 4 0.4219 0.625 . |*** | . |****** | 5 0.3469 0.5988 . |*** | . |****** | 6 0.2846 0.5637 . |** | . |***** | 7 0.2368 0.5305 . |** | . |***** | 8 0.1927 0.5044 . |** | . |***** | 9 0.1576 0.4637 . |*. | . |**** | 10 0.1315 0.3886 . |*. | . |*** | 11 0.1053 0.292 . |*. | . |** | 12 0.0702 0.2079 . | . | . |*. | 13 0.0351 0.0967 . | . | . | . | 14 0 0 . | . | . | . | 15 0 0 . | . | . | . | 16 0 0 . | . | . | . | 17 0 0 . | . | . | . | 18 0 0 . | . | . | . | 19 0 0 . | . | . | . | 20 0 0 . | . | . | . | 21 0 0 www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 21 . | . | . | . | 22 0 0 . | . | . | . | 23 0 0 . | . | . | . | 24 0 0 . | . | . | . | 25 0 0 . | . | . | . | 26 0 0 . | . | . | . | 27 0 0 . | . | . | . | 28 0 0 . | . | . | . | 29 0 0 . | . | . | . | 30 0 0 . | . | . | . | 31 0 0 . | . | . | . | 32 0 0 Table 4 is indicated the covariance of indicator and their relationship of individual indicators. likewise, GVA, CPIAD, GDPPC and TR with MTG have shown the significant effect on investment and implemented policies. So therefore, the relationship of IGD and TS the implanted policies and its implication of trade in Africa. Table 7. Maximum factors Factor Method: Maximum Likelihood F1 Communality Uniqueness CPIAD 0.332776 0.11074 0.88926 CPIAQ 0.598787 0.358546 0.641454 GDPPC 0.955697 0.913357 0.086643 GVA 1 1 0 IGD 0.308166 0.094966 0.905034 MEL 0.137412 0.018882 0.981118 MTG 0.308655 0.095268 0.904732 TR 0.327268 0.107104 0.892896 TS 0.549849 0.302334 0.697666 Factor Variance Cumulative Difference Proportion Cumulative F1 3.001197 3.001197 --- 1 1 www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 22 Total 3.001197 3.001197 1 Model Independence Saturated Discrepancy 3.877421 7.577025 0 Chi-square statistic 248.155 484.9296 --- Chi-square prob. 0 0 --- Bartlett chi-square 230.7066 455.8843 --- Bartlett probability 0 0 --- Parameters 18 9 45 Degrees-of-freedom 27 36 --- Warning: Heywood solution (uniqueness estimates are non-positive). Results should be interpreted with caution. Table 8 shows the padroni test of individual indicators of CPIAD and IGD with GVA within 6-1 ranking, the computed results is indicated the stationary issue in nonstationary level. The probability of test is indicated the turn over period 1960-2018. Table 9 www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 23 Table 8. Correlate CPIAD CPIAQ GDPPC GVA IGD MEL MTG TR TS CPIAD -3.22E-15 0.573707104 -0.087368372 -2.83E-15 -0.129501948 0.246595646 0.248323602 -0.117709958 0.006977153 CPIAQ 0.573707104 -4.66E-15 -0.169391678 -2.78E-15 -0.000874664 0.077150599 0.113747569 -0.070178457 -0.070515985 GDPPC -0.087368372 -0.169391678 2.90E-09 3.33E-16 -0.041192064 0.009764396 0.014630985 0.046287995 -0.021006338 GVA -2.83E-15 -2.78E-15 3.33E-16 -4.44E-16 3.89E-16 -5.55E-17 0 7.22E-16 1.11E-15 IGD -0.129501948 -0.000874664 -0.041192064 3.89E-16 4.44E-16 -0.097001772 0.024374437 0.12577333 -0.119543142 MEL 0.246595646 0.077150599 0.009764396 -5.55E-17 -0.097001772 -1.11E-16 0.152526961 -0.106828207 0.045897037 MTG 0.248323602 0.113747569 0.014630985 0 0.024374437 0.152526961 -2.00E-15 0.690359979 0.101778013 TR -0.117709958 -0.070178457 0.046287995 7.22E-16 0.12577333 -0.106828207 0.690359979 -6.66E-16 0.010929393 TS 0.006977153 -0.070515985 -0.021006338 1.11E-15 -0.119543142 0.045897037 0.101778013 0.010929393 1.55E-15 www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 24 Table 9. Fitness summary Goodness-of-fit Summary Factor: Untitled Model Independence Saturated Parameters 18 9 45 Degrees-of-freedom 27 36 --- Parsimony ratio 0.75 1 --- Absolute Fit Indices Model Independence Saturated Discrepancy 3.877421 7.577025 0 Chi-square statistic 248.155 484.9296 --- Chi-square probability 0 0 --- Bartlett chi-square statistic 230.7066 455.8843 --- Bartlett probability 0 0 --- Root mean sq. reside. (RMSR) 0.176065 0.362026 0 Akaike criterion 2.986999 6.352763 0 Schwarz criterion 2.083792 5.148487 0 Hannan-Quinn criterion 2.630626 5.877599 0 Expected cross-validation (ECVI) 4.439921 7.858275 1.40625 Generalized fit index (GFI) 0.672501 0.488161 1 Adjusted GFI 0.454168 0.146935 --- Non-centrality parameter 221.155 448.9296 --- Gamma Hat 0.126405 0.066538 --- McDonald Non-centrally 0.17768 0.029979 --- Root MSE approximation 0.357747 0.441416 --- www.acseusa.org/journal/index.php/aijbms American International Journal of Business and Management Studies Vol. 2, No. 2; 2020 25 Incremental Fit Indices Model Bollen Relative (RFI) 0.317688 Bentler-Bonnet Normed (NFI) 0.488266 Tucker-Lewis Non-Normed (NNFI) 0.343164 Bollen Incremental (IFI) 0.517055 Bentler Comparative (CFI) 0.507373 4. Conclusion The above research is proved that investment in these western African countries not only to develop the individual region or society, it creating effect on the entire African state with huge monitoring polices. The gross value of debts and public administration is controlled the development objective of entire state with strategic and planned environment for state and reduce the level of inflation in small and enterprise section. The monitoring policies in developing countries is one of the important issues and influence factor in each individual state. Therefore, the impact of monetary policies on GDP per capita reflect the exchange rate in developing countries and generalized method of covariance by the probability level of linear value, where the highest mean deviation is directly affecting the monetary integration and implication of trade in African countries. The integration of value has been analyzed by the CPIAD, IGD and TS. The above results estimated the coefficient of all indicators with 95% confidence interval. In addition, Wald test confirm the validity of the instrument by absence of serial autocorrelation in 1st order. The estimation shows the monetary integration in African states. Therefore, the functioning of the foreign exchange and their implication in trade constantly shows the significant effects on proxy monitoring policies. The results reflect the debt policies, public administration with regional trade, GDP per capita, service in trade, trade of individual, merchandise trade, and export of low income economy. The stability of model is indicated the strategic policies so the results is conducting by the regression. It has necessary for the individual state to reduce the economy dependency in export and oil sources, to prevent the equity of public administration, trade in service and merchandise trade. The fluctuation of monetary policies and implication review the sector of currency policies in trade and investment. Furthermore, the above per-capita results are heighted the trade services and merchandise trade with different level of GDP. The gross development product need strategic techniques for development and entire export so therefore the one corner has been solving with monitoring policies and premeditated planed. References 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. doi:https://doi.org/10.1016/j.jenvman.2016.12.007 Acheampong, A. O. (2018). Economic growth, CO2 emissions and energy consumption: What causes what and where? Energy Economics, 74, 677-692. doi:https://doi.org/10.1016/j.eneco.2018.07.022 Adom, P. K., & Kwakwa, P. A. (2014). 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