Do Pegged Currencies Support Growth? Insights from Mali’s Experience with the CFA Franc

Do Pegged Currencies Support Growth? 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Insights from Mali’s Experience with the CFA Franc Boubacar Amadou CISSE, Tahirou TANGARA, Boubacar MOUNKORO, Abdoulaye ARAMA, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6866535/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper investigates the relationship between economic growth and exchange rate volatility in Mali, a member of the West African Economic and Monetary Union (WAEMU) with a fixed exchange rate regime by way of the CFA Franc (XOF) peg to the Euro (EUR). In accordance with the Mundell-Fleming model, Purchasing Power Parity (PPP) theory, and balance of payments-constrained growth, the study examines how deviations of the XOF/USD exchange rate—used as a proxy for EUR/USD changes—affect significant macroeconomic variables like GDP, inflation, exports, and imports. Based on annual time series data covering 1967 to 2023, the study uses the Autoregressive Distributed Lag (ARDL) model to examine short-run behavior and long-run equilibrium relationships. The findings reinforce the existence of cointegration between the variables and establish that exchange rate volatility has a major impact on Mali's macroeconomic performance. The fixed peg delivers nominal stability but is restrictive on policy independence and increases vulnerability to external shocks. The findings add novel insights, which are country-specific, to the general discourse on currency regimes in sub-Saharan Africa and provide policy lessons for increasing resilience and sustainable growth under limited monetary regimes. JEL : E31, F31, F33, F41, O55 International Economics Finance Other Economics Exchange Rate CFA Franc Economic Growth ARDL Currency Regime Figures Figure 1 1. Introduction The effect of exchange rates on economic growth has been the center of important debate worldwide. From the gold standard period (1879–1914) to globalization, exchange regimes for currencies have fluctuated as symbols of national identity and utilitarian instruments of economic policy. The choice between the exchange rate regime—fixed, floating, or hybrid—has been essential for nations looking for financial stability, trade competitiveness, and long-run growth. Countries have experimented with different monetary frameworks over the years, weighing their advantages and disadvantages to develop the optimum economic and fiscal policies. One of the most contested exchange rate regimes is the West African Economic and Monetary Union (WAEMU), whose shared currency, the West African CFA franc (XOF), is pegged to the euro (EUR). Along with its counterpart in the Economic and Monetary Community of Central Africa (CEMAC), the Central African CFA franc (XAF), the currency has been politically and economically divisive on numerous occasions. One major source of divisiveness surrounds its derivation from a colonial history. It was initially named Franc of the French Colonies in Africa ( Franc des Colonies Françaises d'Afrique ), and then it was renamed African Financial Community Franc (Franc de la Communauté Financière Africaine ) for WAEMU and Financial Cooperation Franc in Central Africa (Franc de la Coopération Financière en Afrique Centrale ) for the Economic and Monetary Community of Central African States (CEMAC). While its supporters argue that the CFA franc promotes stability and regional trade ease, others view it as a constraint on monetary sovereignty and economic flexibility. Fourteen African nations currently use the CFA franc: Benin, Burkina Faso, Côte d'Ivoire, Guinea-Bissau, Mali, Niger, Senegal, and Togo in WAEMU, and Cameroon, Central African Republic, Republic of Congo, Gabon, Equatorial Guinea, and Chad in CEMAC. Economic challenges these nations face have seen the fixed rate against the euro continue to shape their trade flows, inflationary trends, and macroeconomic performances. This research focuses on the Republic of Mali and the application of the XOF in its economy, examining the impact of the fixed exchange rate of the XOF against the euro on economic development. Because the USD remains a dominant currency in international trade as well as financial transactions, the research uses the USD/XOF exchange rate as a proxy in establishing the impact of EUR/USD volatility on the Malian economy. While significant research exists on exchange rate regimes in Africa, relatively few studies have specifically analyzed Mali’s exchange rate and its broader macroeconomic implications. Thus, this research aims to fill that gap by: Assessing the impact of the USD/XOF exchange rate on Mali’s GDP, inflation, and trade balance. Examining whether the stability of the euro peg is beneficial or detrimental to Mali’s long-term economic performance. This study's responses to these questions add to the ongoing debate regarding the relationship between exchange rate policies and economic growth in developing economies. 2. Literature review Exchange rates affect the economic path of developing nations, especially those with serious reliance on international trade, commodity exports, and foreign direct investment (FDI). As the Franc CFA (XOF), the currency of the WAEMU—of which Mali is a member—is pegged to the European Euro (EUR), its exchange rate fluctuations against both the USD and EUR may have particular relevance to economic performances of the countries union. The Purchasing Power Parity (PPP) theory suggests that exchange rate fluctuations should, in theory, equate the purchasing power of different currencies in the long run. In developing nations like Mali, structural inefficiencies, inflationary pressures, and market distortions typically lead to PPP deviations. Rogoff ( 1996 ) identifies that PPP holds weakly in the short run but stronger in the long run for commodity-exporting economies. In addition, the Mundell-Fleming model (Mundell, 1963 ; Fleming, 1962 ) derives the impact of exchange rate regimes on macroeconomic outcomes under an open economy. Since the fixed exchange rate regime supported by Mali (XOF pegged to the EUR), discretionary monetary policy is not possible, hence fiscal policy stands out as the primary tool of economic management. The Balassa-Samuelson Effect hypothesis (Balassa and Samuelson, 1964 ) suggests that increased productivity in non-tradable sectors of developing economies leads to systematic undervaluation of the exchange rate. Agricultural productivity growth, gold mining productivity growth, and trade productivity growth for Mali can affect its real exchange rate equilibrium as well as follow-up GDP growth. N'Diaye (2021) highlighted that financial development, as indicated by bank deposits, loans, and money supply in Mali, negatively affects economic growth. However, trade openness and public spending have beneficial impacts on economic growth, particularly in the long term. Rapetti ( 2020 ) surveyed new research on the contribution of real exchange rates (RER) to growth and concluded that there existed a positive relationship between the levels of RER and growth, particularly in developing countries. There exist some research works that have concluded exchange rate policies have an impact on economic growth. Guzman, Ocampo, and Stiglitz ( 2017 ) argue that the policy of having a stable and competitive real exchange rate has the potential to reverse market failures, increase learning spillovers, and spur economic growth. Additionally, they assert that the policy, accompanied by industrial policies, must incorporate capital flow control as well as intervention in the foreign exchange market. Ribeiro, McCombie, and Lima ( 2020 ) estimated the relationship between growth in emerging economies and real exchange rate misalignment, considering technological ability and income distribution. They found that undervaluation indirectly influences growth, and it slows down growth through technological innovation and income distribution. Razmi, Rapetti, and Skott ( 2012 ) developed a formal model of the link between competitive exchange rates and economic development in developing economies with a focus on concealed unemployment as a source of endogenous growth. Empirical research on fixed versus floating exchange rate systems comparison shows mixed findings. A study by Ghosh et al. ( 1997 ) mentioned that fixed exchange rate systems often accompany low inflation but lead to overvaluation and trade deficits sometimes. This can be observed within the WAEMU region, as inflation is moderate in comparison with the surrounding countries whose currencies float. Since Mali has a dependence on EUR-pegged XOF, trade balances may be disturbed if the peg is not determined by fundamental economic conditions. A fixed peg of XOF against the EUR maintains inflation control at the expense of Mali's scope to devalue its currency competitively to export more. A study by Sy ( 2019 ) on the WAEMU region highlights that while the peg ensures monetary stability, it can be counterproductive to long-term growth if it is not synchronized with trade conditions. Others argue that the peg reduces currency risk, encourages investment, and facilitates trade relations in WAEMU. Onwuka and Obi ( 2015 ) carried out research on the relationship between G-3 (USA, Japan, and Germany/Eurozone) exchange rate volatility and economic development in African developing countries. They found that while, from 1980 to 2001, G-3 exchange rate volatility contributed positively to growth, it contributed negatively to overall growth in developing economies. Fofanah ( 2022 ) researched 13 West African countries and found that economic growth is affected negatively by exchange rate volatility. He also noted that financial sector development can act as a shock absorber to this adverse effect. He advised governments to invest in building their financial sectors. Also, in their study on Bangladesh, Razzaque et al. ( 2017 ) found that a 10% real exchange rate depreciation in the country results in an increase of 3.2% in aggregate output in the long run and a reduction of 0.5% in GDP in the short run. Barguellil, Ben-Salha & Zmami ( 2018 ) found that exchange rate volatility negatively impacts economic growth, especially in financially open and flexible exchange rate nations. Morina et al. ( 2020 ), from a set of empirical research, stated that exchange rate volatility negatively impacted Central and Eastern European economic development; examination of data from 2002 to 2018 confirms exchange rate stabilization as a means of supporting growth to policymakers. Dornbusch ( 1980 ) suggests in a study that exchange rate volatility stimulates or deters exports depending on market adaptability. For Mali, whose exports are dominated by gold and agricultural products, fluctuations in exchange rates against the USD can have a material impact on export revenues. Studies of West African economies (Bleaney & Greenaway, 2001 ) show that currency pegs are stable but can also undermine competitiveness if not tied to market conditions. Exchange rate stability is likely to attract foreign direct investment (FDI). A study by Asongu ( 2014 ) of WAEMU countries found that stability in exchange rates positively contributes to FDI inflows, particularly in natural resource-based economies. In view of Mali's gold sector, exchange rate volatility and investment flows have a close connection. This may be attributed to the usage of stable exchange rates by foreign investors to repatriate capital to their domestic economies. Moreover, Fisher ( 1993 ) clarifies that currency depreciation often results in inflationary pressures, particularly in high-import-dependent economies. The fact that Mali is import-dependent makes it vulnerable to inflationary effects when the USD appreciates compared to the EUR, thus impacting the real value of the XOF. Mali exports are dominated by gold (over 70% of the total exports), followed by animals and cotton (World Bank, 2022). Mali's major trading partners are China, Switzerland, and India, and most of these transactions are done in USD. Thus, the XOF/USD exchange rate is very critical to revenue stability. Even when the XOF is stable against the EUR peg, Mali remains exposed to external shocks like the volatility of gold prices, variation in global demand, and inflationary pressures from trade partners. 3. Theoretical Framework Understanding the link between exchange rates and economic growth is based on an open economy macroeconomic theory foundation. This study draws upon three broad strands of theory: the Purchasing Power Parity hypothesis, the Mundell-Fleming model, and the Balance of Payments constrained growth model, augmented by insights from the Balassa-Samuelson effect. These theories help explain how changes in foreign currencies potentially impact macroeconomic performance in a small open economy like Mali. 3.1 Purchasing Power Parity (PPP) PPP Theory postulates that exchange rates would alter to equate a country's price of identical goods and services across countries (Cassel, 1918 ). Under this theory, in the long run: $$\:\varvec{S}\:=\:\frac{\varvec{P}}{{\varvec{P}}^{\varvec{*}}}$$ 1 Where: S is the nominal exchange rate (domestic currency per unit of foreign currency), P is the domestic price level, P * is the foreign price level. PPP deviations can indicate misalignment in the exchange rate, and they can have real effects on trade competitiveness and inflation. Although PPP weakly holds in the short run (Rogoff, 1996 ), it is a good benchmarking for evaluating the implications of fixed exchange rates on domestic price stability. 3.2. Mundell-Fleming Model (IS-LM-BP) For a small open economy with a fixed exchange rate and complete capital mobility–characteristics of WAEMU economies—the Mundell-Fleming model demonstrates the borders of monetary policy (Mundell, 1963 ; Flemming, 1962). The model shows that, under fixed exchange rate: Monetary policy is irrelevant because any effort to change the domestic money supply is offset by capital flows that maintain the exchange rate. Fiscal policy is then the principal device for regulating output. The aggregate demand function in this case can be expressed as: $$\:\varvec{Y}\:=\:\varvec{C}(\varvec{Y}-\varvec{T})\:+\:\varvec{I}\left(\varvec{r}\right)\:+\:\varvec{G}\:+\:\varvec{N}\varvec{X}(\varvec{e},\:\varvec{Y},\:{\varvec{Y}}^{\varvec{*}})$$ 2 Where: Y is national income, C is consumption, I is investment, r is the interest rate (determined externally), G is government spending, NX is net exports, dependent on the real exchange rate e, domestic income Y, and foreign income Y*. The aggregate demand function in this case can be expressed as: $$\:\varvec{e}\:=\:\varvec{S}\:\frac{{\varvec{P}}^{\varvec{*}}}{\varvec{P}}$$ 3 It has been demonstrated that even with a fixed nominal exchange rate, inflation or changes in foreign prices affect the real exchange rate, the trade balances, and therefore the output. 3.3. Balance of Payments Constrained Growth Model Thirlwall's Law (1979) supposes that the long-run growth rate for an open economy is determined by its ability to finance imports from exports. This directly applies to Mali, which is heavily commodity-export dependent (mainly gold and cotton). The balance-of-payments-compatible growth rate is given as: $$\:g\:=\:\frac{\epsilon\:}{\pi\:}\:.\:{g}^{*}$$ 4 Where: g is the domestic growth rate, g∗ is the growth rate of world income, ε is the income elasticity of demand for exports, π is the income elasticity of demand for imports A misaligned or overvalued exchange rate—common in fixed regimes is reducing competitiveness, thus worsening export performance and restraining growth through BOP bottlenecks. 3.4 Balassa-Samuelson Effect The Balassa-Samuelson hypothesis explains real exchange appreciation in fast-growing economies due to higher productivity in tradable versus on-tradable sectors (Balassa, 1964 ; Samuelson, 1964 ). The real exchange rate (e) for this case is calculated based on productivity differentials: $$\:\varvec{e}\:=\:\int\:({\varvec{A}}_{\varvec{T}}\:-\:{\varvec{A}}_{\varvec{N}})$$ 5 Where: A T ​ is productivity in the tradable sector, A N ​ is productivity in the non-tradable sector. In Mali, low productivity in non-tradable sectors (e.g., services, subsistence agriculture) can generate pressures for long-run undervaluation or overvaluation, even in the presence of a fixed nominal exchange rate, impacting inflation, consumption, and export dynamics. 4. Methodology The study is carried out with annual data from 1967 to 2023. The GDP, and the dependent variable, alongside six (6) independent variables, were chosen; they are Exchange Rate, Inflation, Export, Import, and Gold Price (see Table 1 ). Table 1 Variables Variable Code Source Gross Domestic Product GDP World Bank Exchange Rate EXR World Bank Inflation INF World Bank Export EXP World Bank Import IMP World Bank Gold Price GLD World Gold Council Source : Authors’ Construct The USD/XOF exchange rate is used as a proxy for USD/EUR to observe this latter’s effect on Mali’s economy. The Autoregressive Distributed Lag (ARL) and the Bounds Test for cointegration were conducted to establish the relationships (long and short) among the variables. Later, the Error Correction Model (ECM) was specified to determine the Error Correction Term (ECT) that adjusts the model. The proposed Autoregressive Distributed Lag (ARDL) Model is as follows: $$\:{GDP}_{t}\:=\:\alpha\:\:+\:\sum\:{\beta\:}_{1}{EXR}_{t}\:+\:\sum\:{\gamma\:}_{1}{INF}_{t}\:+\:\sum\:{\delta\:}_{1}{GLD}_{t}\:+\:\sum\:{\theta\:}_{1}{EXP}_{t}+\:\sum\:{\lambda\:}_{1}{IMP}_{t}+\:{\epsilon\:}_{t}$$ 6 The Error Correction Model (ECM) that shows how quickly GDP adjusts to changes in the exchange rate and the other variables after a shock (and whether the system returns to equilibrium) is as follows: $$\:\varDelta\:{GDP}_{t}\:=\:\alpha\:\:+\:\beta\:\varDelta\:{EXR}_{t}\:+\:\gamma\:{\varDelta\:INF}_{t}\:+\:\delta\:{\varDelta\:GLD}_{t}\:+\:\theta\:\varDelta\:{EXP}_{t}\:+\:\lambda\:\varDelta\:{IMP}_{t}\:+\:\mu\:{ECT}_{t}\:+\:{\epsilon\:}_{t}$$ 7 Where: \(\:{\Delta\:}\) represents changes (differences), ECT is the Error Correction term (the lagged residuals from the cointegration equation). 4. Findings The information criteria on lag length selection were determined and are displayed in Table 2 . Table 2 Lag Structure Criteria Selection Lag LogL LR FPE (e-16) AIC SC HQ 0 485.16 — 5.66 -18.08 -17.86 -18 1 * 752.76 464.52 9.14 -26.82 -25.26 -26.22 2 784.74 48.28 11.2 -26.67 -23.77 -25.55 3 807.24 28.86 21.4 -26.16 -21.92 -24.53 4 833.85 28.13 40.7 -25.81 -20.23 -23.66 Source : Authors’ Construct The Akaike (AIC) and Schwarz (SC) criteria selected lag 1 as optimal. This implies short-term dynamics are sufficiently captured with one lag. Later, data stationarity was tested through the Augmented Dickey-Fuller unit root test. The result is displayed in Table 3 . Table 3 Unit Root Test (ADF) Results Variable Level First Difference Order of Integration GDP -1.38 (0.588) -7.40 * (0.000)** I(1) EXR -1.35 (0.601) -6.69 * (0.000)** I(1) EXP -0.85 (0.797) -8.36 * (0.000)** I(1) GLD -5.52 * (0.000)** -9.71*** (0.000) I(0) IMP -0.58 (0.864) -0.1584 I(1) INF -5.93 * (0.000)** -5.42 * (0.000)** I(0)/I(1) Source : Authors’ Construct As per the unit root test, it can be observed that the variables are both I(0) and I(1). This justifies using first-differenced variables in short-run models (e.g., ECM) and testing for cointegration. The Bounds Test for cointegration is more adequate for exploring the long-run relationship between the variables. Also, an Autoregressive Distributed Lag (ARDL) is necessary to determine the short-term dynamics among the variables. The ARDL model identifies significant relationships between the exchange rate (USD/XOF) and GDP (Table 4 ). Table 4 ARDL Model Results Variable Coefficient Std. Error t-Statistic p-value GDP(-1) 0.922*** 0.063 14.65 0.000 EXR -0.741*** 0.089 -8.29 0.000 EXR(-1) 0.836*** 0.086 9.67 0.000 EXP -0.176* 0.093 -1.89 0.065 GLD 40.412 51.722 0.78 0.438 IMP 0.082 0.054 1.53 0.133 INF 0.699*** 0.234 2.99 0.004 CONSTANT -118.838 152.313 -0.78 0.439 Source : Authors’ Construct Model Fit : R2 = 0.998; Adj. R2 = 0.998; AIC = -2.68 The exchange rate coefficient is -0.741316 (significant at 1%). This negative relationship suggests that depreciation in USD/XOF adversely affects Mali's GDP growth in the short run. The lagged exchange rate (EXR(-1)) coefficient is positive (0.835629), and it indicates that past exchange rate movements have a compensatory effect on GDP growth. Inflation positively affects GDP (coefficient = 0.699114), suggesting moderate inflation may stimulate economic activity. Other variables like exports and imports show weaker significance levels. The Bounds test was later performed to identify if there is a long-run relationship between the variables. The test result, depicted in Table 5 , indicates an F-statistic of 4.458, which exceeds the critical value at the 10% significance level (I(0): 2.26; I(1): 3.35). This suggests a long-term cointegration relationship between GDP and the explanatory variables (exchange rate, exports, gold price, imports, and inflation). Cointegration implies that changes in these variables have a lasting impact on Mali's GDP. Table 5 Bounds Test for Cointegration Test Statistic Value Critical Values (I(0)/I(1)) F-statistic 4.458 10%: 2.26 / 3.35 5%: 2.62 / 3.79 1%: 3.41 / 4.68 Source : Authors’ Construct The existence of a long-term relation between GDP and the other variables implies the utilization of ECM. The ECM regression confirms the long-term adjustment mechanism. CointEq(-1) , which is the error correction term (-0.07756), is significant at 1%; this indicates that deviations from long-term equilibrium are corrected at a speed of approximately 7.8% per year. The exchange rate (\(\:{\Delta\:}\text{EXR}\)) has a significant adverse short-term effect on GDP (-0.741316), reinforcing findings from the ARDL model. The ECM is represented in Table 6: Table 6 Error Correction Model (ECM) Variable Coefficient Std. Error t-Statistic p-value CointEq(-1) -0.078*** 0.014 -5.43 0 Δ(EXR) -0.741*** 0.058 -12.82 0 CONSTANT -118.838*** 21.883 -5.43 0 Adjustment Speed: 7.8% of disequilibrium corrected annually. Source: Authors’ Construct The diagnostic tests were conducted, and the results are displayed in Table 7 . The diagnostic shows that the model does not have a serial correlation problem among the variables and is homoscedastic, as per the Harvey Test for heteroskedasticity. It is worth noting that this latter regresses the logs of the squared residuals on the original regressors by default. Table 7 Diagnostic Tests Breusch-Godfrey Serial Correlation LM Test: Null hypothesis: No serial correlation at up to 1 lag F-statistic 0.07949 Prob. F(1,47) 0.7792 Obs*R-squared 0.094551 Prob. Chi-Square(1) 0.7585 Heteroskedasticity Test: Harvey Null hypothesis: Homoskedasticity F-statistic 0.637536 Prob. F(7,48) 0.7226 Obs*R-squared 4.763647 Prob. Chi-Square(7) 0.6888 Scaled explained SS 9.12468 Prob. Chi-Square(7) 0.2438 Source : Authors’ Construct The Granger causality test was performed to determine the direction of the relationship among the variables. The exchange rate significantly Granger-causes GDP ( \(\:p=0.0324\) ), highlighting its predictive power for economic growth; GDP does not significantly Granger-causes the exchange rate ( \(\:p=0.0785\) ), implying asymmetry in causality. Bidirectional causality exists between exports ( p = 0.022 ) and GDP ( p = 0.0177 ). Moreover, imports show weaker causality effects on GDP compared to exports. Table 8 represents the Granger causality test result. Table 8 Pairwise Granger Causality Null Hypothesis Obs F-Statistic Prob. Decision (5% sig) EXR does not Granger Cause GDP 56 4.82639 0.0324 Reject GDP does not Granger Cause EXR 3.21874 0.0785 Accept EXP does not Granger Cause GDP 56 5.99597 0.0177 Reject GDP does not Granger Cause EXP 10.3407 0.0022 Reject GLD does not Granger Cause GDP 56 0.52561 0.4716 Accept GDP does not Granger Cause GLD 8.98875 0.0041 Reject IMP does not Granger Cause GDP 56 3.91079 0.0532 Accept GDP does not Granger Cause IMP 5.49784 0.0228 Reject INF does not Granger Cause GDP 56 1.6496 0.2046 Accept GDP does not Granger Cause INF 0.48169 0.4907 Accept EXP does not Granger Cause EXR 56 0.84424 0.3623 Accept EXR does not Granger Cause EXP 4.08306 0.0484 Reject GLD does not Granger Cause EXR 56 2.45981 0.1227 Accept EXR does not Granger Cause GLD 8.99734 0.0041 Reject IMP does not Granger Cause EXR 56 2.89315 0.0948 Accept EXR does not Granger Cause IMP 1.86665 0.1776 Accept INF does not Granger Cause EXR 56 1.01619 0.318 Accept EXR does not Granger Cause INF 0.79796 0.3757 Accept GLD does not Granger Cause EXP 56 5.76784 0.0199 Reject EXP does not Granger Cause GLD 10.2976 0.0023 Reject IMP does not Granger Cause EXP 56 7.29405 0.0093 Reject EXP does not Granger Cause IMP 3.02787 0.0876 Accept INF does not Granger Cause EXP 56 0.12795 0.722 Accept EXP does not Granger Cause INF 0.56805 0.4544 Accept IMP does not Granger Cause GLD 56 8.8861 0.0043 Reject GLD does not Granger Cause IMP 0.27118 0.6047 Accept INF does not Granger Cause GLD 56 0.01626 0.899 Accept GLD does not Granger Cause INF 0.12901 0.7209 Accept INF does not Granger Cause IMP 56 0.21702 0.6432 Accept IMP does not Granger Cause INF 0.43203 0.5138 Accept Source : Authors’ Construct The CUSUM of Squares graph confirms model stability over time, as the blue line remains within the bounds of 5% significance throughout most of the sample period, and that indicates that the model is largely stable. This indicates that the estimated relationships are mostly consistent and reliable. However, a notable rise between 1998 and 2010 suggests some structural shifts in the model, possibly due to economic or policy changes (e.g., the 1994 CFA franc devaluation and the adoption of the Euro currency in 1999). The CUSUM of Squares graph is displayed below in Fig. 2 . 5. Interpretation, Implications, and Recommendations The research highlights the adverse short-term impact of USD/XOF depreciation on GDP growth and shows long-term equilibrium adjustments through cointegration. This suggests that Mali's dependence on foreign exchange rates, particularly the stability of the Euro via the CFA Franc peg, plays a critical role in its economic health; it could be assumed that this is the same for the remaining six countries in the monetary community. Given the recent depreciation of USD/XOF − 628.99 CFA Francs per USD in February 2025 – (The Global Economy, 2025), policymakers must focus on strengthening monetary policy by collaborating closely with the West African Economic and Monetary Union (WAEMU) to ensure stability in the CFA Franc peg system; this will help mitigate external shocks from USD/EUR fluctuations. They must emphasize protecting against external volatility by exploring mechanisms such as foreign exchange reserves or hedging strategies to reduce vulnerability to sudden currency depreciation. Mali’s economy relies heavily on gold and cotton exports, which account for over 80% of total exports (WB, 2025). While depreciation of USD/XOF makes exports cheaper and potentially more competitive globally, this reliance on a narrow export base limits the country’s ability to capitalize on broader trade opportunities. To address this, authorities must promote agricultural productivity by adopting policies that enhance agricultural output and trade facilitation, which could help diversify exports and reduce reliance on gold and cotton. They must also develop manufacturing and value-added sectors; this could be done by expanding into manufacturing or processing industries that could create more resilient export streams that are less dependent on commodity prices. In addition, inflation has been positively correlated with GDP growth in Mali, suggesting that moderate inflation may stimulate economic activity by increasing spending power and attracting investment. However, excessive inflation risks eroding purchasing power and increasing production costs. Policymakers must strive to maintain prices and continue monitoring inflation closely while ensuring it remains within a range conducive to growth. Supporting vulnerable populations by combatting food insecurity and providing subsidies and support programs that could mitigate inflation’s impact on lower-income households. Moreover, Mali faces significant security challenges alongside its neighbors Burkina Faso and Niger, including ongoing conflicts and socio-political instability. These factors exacerbate economic vulnerabilities, limiting foreign investment and increasing fiscal pressures. The government must strengthen governance with transparent political processes and stable leadership, which are essential for fostering investor confidence. The resurgence of protectionist policies under Trump 2.0 in the U.S., including increased tariffs and reduced foreign aid, may indirectly affect many countries through tighter global financial conditions; Mali is no exception. Additionally, volatile commodity prices remain a risk for Mali’s gold exports. To curb these, authorities may diversify Mali’s trade partnerships by strengthening intra-African trade through agreements like the African Continental Free Trade Area (AfCFTA). They should also reduce dependency on aid and focus on domestic resource mobilization. Lastly, climate change poses significant threats to Mali’s agriculture-dependent economy. Erratic weather patterns can disrupt crop yields, exacerbate food insecurity, and hinder GDP growth. To mitigate climate impacts, policymakers should invest in climate resilience and develop strategies, such as irrigation systems, drought-resistant crops, and reforestation initiatives. They should also enhance disaster preparedness by strengthening infrastructure to withstand extreme weather events, which will reduce economic losses. 6. Conclusion The CFA Franc has been a currency of controversy for many years. Nowadays, it is obvious that the fixed conversion with the Euro has started displaying issues, and many echo these. This study supports the general determining influence of exchange rate development on Mali's macroeconomic performance. In the past, the formerly fixed CFA Franc (XOF)—Euro peg has delivered stability, particularly in containing inflation. However, this comes at a cost of reduced monetary policy room for maneuver, reducing Mali's ability to respond successfully to exogenous shocks, most prominently from USD/EUR parity changes and commodity price volatility. The study also indicates that economic growth in Mali remains exchange rate-sensitive due to the country's structural reliance on foreign trade and commodity exports, primarily gold. As a result, exposure to external shocks, including global economic instability, regional security concerns, and inflationary pressure, constrains sustainable growth. Addressing these challenges will require a multi-dimensional approach. Beyond maintaining monetary and fiscal stability, Mali must accelerate efforts towards economic diversification, foster financial sector development, and invest in climate adaptation strategies to safeguard key sectors such as agriculture and mining. Moreover, while the WAEMU exchange rate regime has provided short-term stability, further research is warranted to assess whether its long-term effects are aligned with Mali’s developmental objectives, especially under rapidly changing global conditions. Here, policymakers should consider policies that reduce reliance on foreign currency, like the Euro, tackle structural vulnerabilities, enhance resilience, and ensure inclusive growth. Stability of the exchange rate for overall macroeconomic stability and sustainable development is still a top priority of strategic nature and immediacy for Mali and the other WAEMU member states. Declarations Ethical Approval Statement This research does not involve human participants, their data, or animals. Therefore, no ethical approval was required. All procedures and methods used in the study comply with the relevant institutional and international research guidelines and standards. Availability of data and materials The data of this study were collected from different websites notably those of the World Bank, the IMF and the BRVM. The datasets are available Competing Interests The author has no conflicts of interest to declare. Funding Not applicable References Asongu, S. (2014). Exchange Rate Stability and FDI in West Africa. African Development Review , 26(2), 125-145. Balassa, B. (1964). The Purchasing Power Parity Doctrine: A Reappraisal. Journal of Political Economy , 72(6), 584–596. https://doi.org/10.1086/258965 Barguellil, A., Ben-Salha, O., & Zmami, M. (2018). Exchange Rate Volatility and Economic Growth. Journal of Economic Integration . https://doi.org/10.11130/JEI.2018.33.2.1302 Bleaney, M., & Greenaway, D. (2001). The Impact of Exchange Rate Regimes on Exports in Africa. Journal of African Economies , 10(2), 233-257. Cassel, G. (1918). Abnormal deviations in international exchanges. The Economic Journal, 28(112), 413–415. https://doi.org/10.2307/2223329 Dornbusch, R. (1980). Exchange Rate Economics: Where Do We Stand? Brookings Papers on Economic Activity , 1980(1), 143-185. Fisher, S. (1993). The Role of Macroeconomic Factors in Growth. Journal of Monetary Economics , 32(3), 485-512. Fleming, J. M. (1962). Domestic financial policies under fixed and under floating exchange rates. IMF Staff Papers, 9(3), 369–380. https://doi.org/10.2307/3866091 Fofanah, P. (2022). Effects of Exchange Rate Volatility on Economic Growth: Evidence from West Africa. International Journal of Business and Economics Research . https://doi.org/10.11648/j.ijber.20221101.15 Ghosh, A., Gulde, A., & Wolf, H. (1997). Does the Exchange Rate Regime Matter for Inflation and Growth? IMF Economic Review , 44(3), 381-414. Guzman, M., Ocampo, J., & Stiglitz, J. (2017). Real Exchange Rate Policies for Economic Development. PSN: Exchange Rates & Currency (Comparative) (Topic) . https://doi.org/10.3386/W23868 John, F. (1997). Statistical Methods in Economic Research . Cambridge University Press. Mamadou, N’Diaye. (2021). Financial Development and Economic Growth: Case of Mali. Business, Management and Economics Research . https://doi.org/10.32861/bmer.74.108.119 Mankiw, N. G. (1990). A Quick Refresher Course in Macroeconomics. Journal of Economic Literature , 28(4), 1645-1660. Morina, F., Hysa, E., Ergün, U., Panait, M., & Voica, M. (2020). The Effect of Exchange Rate Volatility on Economic Growth: Case of the CEE Countries. Journal of Risk and Financial Management . https://doi.org/10.3390/jrfm13080177 Mundell, R. (1963). Capital Mobility and Stabilization Policy Under Fixed and Flexible Exchange Rates. Canadian Journal of Economics and Political Science , 29(4), 475-485. Onwuka, K., & Obi, K. (2015). Exchange Rate Volatility and Growth Dynamics: Evidence from Selected Sub-Saharan African Countries. British Journal of Economics, Management and Trade , 6, 61-77. https://doi.org/10.9734/BJEMT/2015/12308 Rapetti, M. (2020). The Real Exchange Rate and Economic Growth: A Survey. Journal of Globalization and Development , 11(2), 20190024. https://doi.org/10.1515/jgd-2019-0024 Razmi, A., Rapetti, M., & Skott, P. (2012). The Real Exchange Rate and Economic Development. Structural Change and Economic Dynamics , 23(2), 151-169. https://doi.org/10.1016/j.strueco.2012.01.002 Razzaque, M., Bidisha, S., & Khondker, B. (2017). Exchange Rate and Economic Growth. Journal of South Asian Development , 12, 42-64. https://doi.org/10.1177/0973174117702712 Ribeiro, R. S., McCombie, J. S., & Lima, G. T. (2020). Does Real Exchange Rate Undervaluation Really Promote Economic Growth? Structural Change and Economic Dynamics , 52, 408-417. https://doi.org/10.1016/j.strueco.2019.02.005 Rogoff, K. (1996). The purchasing power parity puzzle. Journal of Economic Literature, 34(2), 647–668. Samuelson, P. A. (1964). Theoretical notes on trade problems. The Review of Economics and Statistics, 46(2), 145–154. https://doi.org/10.2307/1928178 Sy, A. (2019). The CFA Franc and West Africa’s Economic Future. Brookings Institution Policy Paper . Thirlwall, A. P. (1979). The balance of payments constraint as an explanation of international growth rate differences. Banca Nazionale del Lavoro Quarterly Review, 128, 45–53. Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6866535","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":469472890,"identity":"d6ae52be-91ab-4a80-8e54-34994a24daf3","order_by":0,"name":"Boubacar Amadou CISSE","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAUlEQVRIiWNgGAWjYDACZgiVYMDAwAakbYCYsfEAKVrSQFoa8GthQNVyGMzDq4W/nf3xhw8Mdnnm7AfYHvyoOW+3tv0w0JYam2hcWiQO85hJzmBILrbsSWA37Dl2O3nbmUSglmNpuQ04tBgw87Ax8zAwJ244kMAmwdtwO9nsAFALY8NhPFrYH3/+w1CfuOH8AzbJvw3nks3OPySkhcFAGujrxA03EtikeRsO2JndIGAL2C89BseLLWc8bDeWOZacYHYDaEsCHr/w9x9//OFHRXWeOX/ysYdvauzszc6nP3zwocYGpxao80AEI1hNIphMwKscDdiTongUjIJRMApGBgAA8NpfVZ57bzcAAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0002-0455-3502","institution":"Mohammed Vi Polytechnic University","correspondingAuthor":true,"prefix":"","firstName":"Boubacar","middleName":"Amadou","lastName":"CISSE","suffix":""},{"id":469472891,"identity":"63509cef-1760-43a4-91d9-1eca6330c017","order_by":1,"name":"Tahirou TANGARA","email":"","orcid":"","institution":"Bamako University of Social and Management Sciences","correspondingAuthor":false,"prefix":"","firstName":"Tahirou","middleName":"","lastName":"TANGARA","suffix":""},{"id":469472892,"identity":"234b96f4-f986-4ea4-9758-6cedf4f9a037","order_by":2,"name":"Boubacar MOUNKORO","email":"","orcid":"","institution":"Bamako University of Social and Management Sciences","correspondingAuthor":false,"prefix":"","firstName":"Boubacar","middleName":"","lastName":"MOUNKORO","suffix":""},{"id":469472893,"identity":"d7e96ee4-ac50-46da-a906-ccc3aa7b778f","order_by":3,"name":"Abdoulaye ARAMA","email":"","orcid":"","institution":"Bamako University of Social and Management Sciences","correspondingAuthor":false,"prefix":"","firstName":"Abdoulaye","middleName":"","lastName":"ARAMA","suffix":""},{"id":469472894,"identity":"4e368914-f3c6-4191-a139-94005af8f62f","order_by":4,"name":"Ahmed Baba SINGARE","email":"","orcid":"","institution":"Bamako University of Social and Management Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"Baba","lastName":"SINGARE","suffix":""},{"id":469472895,"identity":"3491a563-19ac-4720-acc1-fb44ee71ffdc","order_by":5,"name":"Moussa DIALLO","email":"","orcid":"","institution":"Bamako University of Social and Management Sciences","correspondingAuthor":false,"prefix":"","firstName":"Moussa","middleName":"","lastName":"DIALLO","suffix":""}],"badges":[],"createdAt":"2025-06-10 23:23:56","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6866535/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6866535/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84443451,"identity":"85971a55-d4d2-4ca9-bc2a-fee112b0e850","added_by":"auto","created_at":"2025-06-12 04:44:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":53109,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 2:\u003c/strong\u003e CUSUM Squares\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSource\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e: Authors’ Construct\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6866535/v1/60de68670cd8a7225b941beb.png"},{"id":84444595,"identity":"8fb0474e-0454-4d22-8e9f-2ef7a12d7c90","added_by":"auto","created_at":"2025-06-12 05:08:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1242103,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6866535/v1/26aec0bf-54fa-494a-ad0a-3f5a9be84cb5.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDo Pegged Currencies Support Growth? Insights from Mali’s Experience with the CFA Franc\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe effect of exchange rates on economic growth has been the center of important debate worldwide. From the gold standard period (1879\u0026ndash;1914) to globalization, exchange regimes for currencies have fluctuated as symbols of national identity and utilitarian instruments of economic policy. The choice between the exchange rate regime\u0026mdash;fixed, floating, or hybrid\u0026mdash;has been essential for nations looking for financial stability, trade competitiveness, and long-run growth. Countries have experimented with different monetary frameworks over the years, weighing their advantages and disadvantages to develop the optimum economic and fiscal policies.\u003c/p\u003e \u003cp\u003eOne of the most contested exchange rate regimes is the West African Economic and Monetary Union (WAEMU), whose shared currency, the West African CFA franc (XOF), is pegged to the euro (EUR). Along with its counterpart in the Economic and Monetary Community of Central Africa (CEMAC), the Central African CFA franc (XAF), the currency has been politically and economically divisive on numerous occasions. One major source of divisiveness surrounds its derivation from a colonial history. It was initially named Franc of the French Colonies in Africa (\u003cem\u003eFranc des Colonies Fran\u0026ccedil;aises d'Afrique\u003c/em\u003e), and then it was renamed African Financial Community Franc (Franc de la \u003cem\u003eCommunaut\u0026eacute; Financi\u0026egrave;re Africaine\u003c/em\u003e) for WAEMU and Financial Cooperation Franc in Central Africa (Franc de la \u003cem\u003eCoop\u0026eacute;ration Financi\u0026egrave;re en Afrique Centrale\u003c/em\u003e) for the Economic and Monetary Community of Central African States (CEMAC). While its supporters argue that the CFA franc promotes stability and regional trade ease, others view it as a constraint on monetary sovereignty and economic flexibility.\u003c/p\u003e \u003cp\u003eFourteen African nations currently use the CFA franc: Benin, Burkina Faso, C\u0026ocirc;te d'Ivoire, Guinea-Bissau, Mali, Niger, Senegal, and Togo in WAEMU, and Cameroon, Central African Republic, Republic of Congo, Gabon, Equatorial Guinea, and Chad in CEMAC. Economic challenges these nations face have seen the fixed rate against the euro continue to shape their trade flows, inflationary trends, and macroeconomic performances.\u003c/p\u003e \u003cp\u003eThis research focuses on the Republic of Mali and the application of the XOF in its economy, examining the impact of the fixed exchange rate of the XOF against the euro on economic development. Because the USD remains a dominant currency in international trade as well as financial transactions, the research uses the USD/XOF exchange rate as a proxy in establishing the impact of EUR/USD volatility on the Malian economy. While significant research exists on exchange rate regimes in Africa, relatively few studies have specifically analyzed Mali\u0026rsquo;s exchange rate and its broader macroeconomic implications. Thus, this research aims to fill that gap by:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eAssessing the impact of the USD/XOF exchange rate on Mali\u0026rsquo;s GDP, inflation, and trade balance.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eExamining whether the stability of the euro peg is beneficial or detrimental to Mali\u0026rsquo;s long-term economic performance.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThis study's responses to these questions add to the ongoing debate regarding the relationship between exchange rate policies and economic growth in developing economies.\u003c/p\u003e"},{"header":"2. Literature review","content":"\u003cp\u003eExchange rates affect the economic path of developing nations, especially those with serious reliance on international trade, commodity exports, and foreign direct investment (FDI). As the Franc CFA (XOF), the currency of the WAEMU\u0026mdash;of which Mali is a member\u0026mdash;is pegged to the European Euro (EUR), its exchange rate fluctuations against both the USD and EUR may have particular relevance to economic performances of the countries union.\u003c/p\u003e \u003cp\u003eThe Purchasing Power Parity (PPP) theory suggests that exchange rate fluctuations should, in theory, equate the purchasing power of different currencies in the long run. In developing nations like Mali, structural inefficiencies, inflationary pressures, and market distortions typically lead to PPP deviations. Rogoff (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) identifies that PPP holds weakly in the short run but stronger in the long run for commodity-exporting economies. In addition, the Mundell-Fleming model (Mundell, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1963\u003c/span\u003e; Fleming, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1962\u003c/span\u003e) derives the impact of exchange rate regimes on macroeconomic outcomes under an open economy. Since the fixed exchange rate regime supported by Mali (XOF pegged to the EUR), discretionary monetary policy is not possible, hence fiscal policy stands out as the primary tool of economic management.\u003c/p\u003e \u003cp\u003eThe Balassa-Samuelson Effect hypothesis (Balassa and Samuelson, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1964\u003c/span\u003e) suggests that increased productivity in non-tradable sectors of developing economies leads to systematic undervaluation of the exchange rate. Agricultural productivity growth, gold mining productivity growth, and trade productivity growth for Mali can affect its real exchange rate equilibrium as well as follow-up GDP growth. N'Diaye (2021) highlighted that financial development, as indicated by bank deposits, loans, and money supply in Mali, negatively affects economic growth. However, trade openness and public spending have beneficial impacts on economic growth, particularly in the long term. Rapetti (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) surveyed new research on the contribution of real exchange rates (RER) to growth and concluded that there existed a positive relationship between the levels of RER and growth, particularly in developing countries.\u003c/p\u003e \u003cp\u003eThere exist some research works that have concluded exchange rate policies have an impact on economic growth. Guzman, Ocampo, and Stiglitz (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) argue that the policy of having a stable and competitive real exchange rate has the potential to reverse market failures, increase learning spillovers, and spur economic growth. Additionally, they assert that the policy, accompanied by industrial policies, must incorporate capital flow control as well as intervention in the foreign exchange market. Ribeiro, McCombie, and Lima (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) estimated the relationship between growth in emerging economies and real exchange rate misalignment, considering technological ability and income distribution. They found that undervaluation indirectly influences growth, and it slows down growth through technological innovation and income distribution. Razmi, Rapetti, and Skott (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) developed a formal model of the link between competitive exchange rates and economic development in developing economies with a focus on concealed unemployment as a source of endogenous growth.\u003c/p\u003e \u003cp\u003eEmpirical research on fixed versus floating exchange rate systems comparison shows mixed findings. A study by Ghosh et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) mentioned that fixed exchange rate systems often accompany low inflation but lead to overvaluation and trade deficits sometimes. This can be observed within the WAEMU region, as inflation is moderate in comparison with the surrounding countries whose currencies float. Since Mali has a dependence on EUR-pegged XOF, trade balances may be disturbed if the peg is not determined by fundamental economic conditions. A fixed peg of XOF against the EUR maintains inflation control at the expense of Mali's scope to devalue its currency competitively to export more. A study by Sy (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) on the WAEMU region highlights that while the peg ensures monetary stability, it can be counterproductive to long-term growth if it is not synchronized with trade conditions. Others argue that the peg reduces currency risk, encourages investment, and facilitates trade relations in WAEMU.\u003c/p\u003e \u003cp\u003eOnwuka and Obi (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) carried out research on the relationship between G-3 (USA, Japan, and Germany/Eurozone) exchange rate volatility and economic development in African developing countries. They found that while, from 1980 to 2001, G-3 exchange rate volatility contributed positively to growth, it contributed negatively to overall growth in developing economies. Fofanah (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) researched 13 West African countries and found that economic growth is affected negatively by exchange rate volatility. He also noted that financial sector development can act as a shock absorber to this adverse effect. He advised governments to invest in building their financial sectors. Also, in their study on Bangladesh, Razzaque et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) found that a 10% real exchange rate depreciation in the country results in an increase of 3.2% in aggregate output in the long run and a reduction of 0.5% in GDP in the short run.\u003c/p\u003e \u003cp\u003eBarguellil, Ben-Salha \u0026amp; Zmami (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) found that exchange rate volatility negatively impacts economic growth, especially in financially open and flexible exchange rate nations. Morina et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), from a set of empirical research, stated that exchange rate volatility negatively impacted Central and Eastern European economic development; examination of data from 2002 to 2018 confirms exchange rate stabilization as a means of supporting growth to policymakers. Dornbusch (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1980\u003c/span\u003e) suggests in a study that exchange rate volatility stimulates or deters exports depending on market adaptability. For Mali, whose exports are dominated by gold and agricultural products, fluctuations in exchange rates against the USD can have a material impact on export revenues. Studies of West African economies (Bleaney \u0026amp; Greenaway, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) show that currency pegs are stable but can also undermine competitiveness if not tied to market conditions.\u003c/p\u003e \u003cp\u003eExchange rate stability is likely to attract foreign direct investment (FDI). A study by Asongu (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) of WAEMU countries found that stability in exchange rates positively contributes to FDI inflows, particularly in natural resource-based economies. In view of Mali's gold sector, exchange rate volatility and investment flows have a close connection. This may be attributed to the usage of stable exchange rates by foreign investors to repatriate capital to their domestic economies. Moreover, Fisher (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) clarifies that currency depreciation often results in inflationary pressures, particularly in high-import-dependent economies. The fact that Mali is import-dependent makes it vulnerable to inflationary effects when the USD appreciates compared to the EUR, thus impacting the real value of the XOF.\u003c/p\u003e \u003cp\u003eMali exports are dominated by gold (over 70% of the total exports), followed by animals and cotton (World Bank, 2022). Mali's major trading partners are China, Switzerland, and India, and most of these transactions are done in USD. Thus, the XOF/USD exchange rate is very critical to revenue stability. Even when the XOF is stable against the EUR peg, Mali remains exposed to external shocks like the volatility of gold prices, variation in global demand, and inflationary pressures from trade partners.\u003c/p\u003e"},{"header":"3. Theoretical Framework","content":"\u003cp\u003eUnderstanding the link between exchange rates and economic growth is based on an open economy macroeconomic theory foundation. This study draws upon three broad strands of theory: the Purchasing Power Parity hypothesis, the Mundell-Fleming model, and the Balance of Payments constrained growth model, augmented by insights from the Balassa-Samuelson effect. These theories help explain how changes in foreign currencies potentially impact macroeconomic performance in a small open economy like Mali.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Purchasing Power Parity (PPP)\u003c/h2\u003e \u003cp\u003ePPP Theory postulates that exchange rates would alter to equate a country's price of identical goods and services across countries (Cassel, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1918\u003c/span\u003e). Under this theory, in the long run:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{S}\\:=\\:\\frac{\\varvec{P}}{{\\varvec{P}}^{\\varvec{*}}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere:\u003c/p\u003e \u003cp\u003e \u003cem\u003eS\u003c/em\u003e is the nominal exchange rate (domestic currency per unit of foreign currency),\u003c/p\u003e \u003cp\u003e \u003cem\u003eP\u003c/em\u003e is the domestic price level,\u003c/p\u003e \u003cp\u003e \u003cem\u003eP\u003c/em\u003e \u003csup\u003e \u003cem\u003e*\u003c/em\u003e \u003c/sup\u003e is the foreign price level.\u003c/p\u003e \u003cp\u003ePPP deviations can indicate misalignment in the exchange rate, and they can have real effects on trade competitiveness and inflation. Although PPP weakly holds in the short run (Rogoff, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), it is a good benchmarking for evaluating the implications of fixed exchange rates on domestic price stability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Mundell-Fleming Model (IS-LM-BP)\u003c/h2\u003e \u003cp\u003eFor a small open economy with a fixed exchange rate and complete capital mobility\u0026ndash;characteristics of WAEMU economies\u0026mdash;the Mundell-Fleming model demonstrates the borders of monetary policy (Mundell, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1963\u003c/span\u003e; Flemming, 1962). The model shows that, under fixed exchange rate:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eMonetary policy is irrelevant because any effort to change the domestic money supply is offset by capital flows that maintain the exchange rate.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFiscal policy is then the principal device for regulating output.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe aggregate demand function in this case can be expressed as:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{Y}\\:=\\:\\varvec{C}(\\varvec{Y}-\\varvec{T})\\:+\\:\\varvec{I}\\left(\\varvec{r}\\right)\\:+\\:\\varvec{G}\\:+\\:\\varvec{N}\\varvec{X}(\\varvec{e},\\:\\varvec{Y},\\:{\\varvec{Y}}^{\\varvec{*}})$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere:\u003c/p\u003e \u003cp\u003eY is national income,\u003c/p\u003e \u003cp\u003eC is consumption,\u003c/p\u003e \u003cp\u003eI is investment,\u003c/p\u003e \u003cp\u003er is the interest rate (determined externally),\u003c/p\u003e \u003cp\u003eG is government spending,\u003c/p\u003e \u003cp\u003eNX is net exports, dependent on the real exchange rate e, domestic income Y, and foreign income Y*.\u003c/p\u003e \u003cp\u003eThe aggregate demand function in this case can be expressed as:\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{e}\\:=\\:\\varvec{S}\\:\\frac{{\\varvec{P}}^{\\varvec{*}}}{\\varvec{P}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIt has been demonstrated that even with a fixed nominal exchange rate, inflation or changes in foreign prices affect the real exchange rate, the trade balances, and therefore the output.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Balance of Payments Constrained Growth Model\u003c/h2\u003e \u003cp\u003eThirlwall's Law (1979) supposes that the long-run growth rate for an open economy is determined by its ability to finance imports from exports. This directly applies to Mali, which is heavily commodity-export dependent (mainly gold and cotton). The balance-of-payments-compatible growth rate is given as:\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:g\\:=\\:\\frac{\\epsilon\\:}{\\pi\\:}\\:.\\:{g}^{*}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere:\u003c/p\u003e \u003cp\u003eg is the domestic growth rate,\u003c/p\u003e \u003cp\u003eg\u0026lowast; is the growth rate of world income,\u003c/p\u003e \u003cp\u003eε is the income elasticity of demand for exports,\u003c/p\u003e \u003cp\u003eπ is the income elasticity of demand for imports\u003c/p\u003e \u003cp\u003eA misaligned or overvalued exchange rate\u0026mdash;common in fixed regimes is reducing competitiveness, thus worsening export performance and restraining growth through BOP bottlenecks.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Balassa-Samuelson Effect\u003c/h2\u003e \u003cp\u003eThe Balassa-Samuelson hypothesis explains real exchange appreciation in fast-growing economies due to higher productivity in tradable versus on-tradable sectors (Balassa, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1964\u003c/span\u003e; Samuelson, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1964\u003c/span\u003e). The real exchange rate (e) for this case is calculated based on productivity differentials:\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{e}\\:=\\:\\int\\:({\\varvec{A}}_{\\varvec{T}}\\:-\\:{\\varvec{A}}_{\\varvec{N}})$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere:\u003c/p\u003e \u003cp\u003eA\u003csub\u003eT\u003c/sub\u003e​ is productivity in the tradable sector,\u003c/p\u003e \u003cp\u003eA\u003csub\u003eN\u003c/sub\u003e​ is productivity in the non-tradable sector.\u003c/p\u003e \u003cp\u003eIn Mali, low productivity in non-tradable sectors (e.g., services, subsistence agriculture) can generate pressures for long-run undervaluation or overvaluation, even in the presence of a fixed nominal exchange rate, impacting inflation, consumption, and export dynamics.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Methodology","content":"\u003cp\u003eThe study is carried out with annual data from 1967 to 2023. The GDP, and the dependent variable, alongside six (6) independent variables, were chosen; they are Exchange Rate, Inflation, Export, Import, and Gold Price (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCode\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGross Domestic Product\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWorld Bank\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExchange Rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEXR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWorld Bank\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInflation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eINF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWorld Bank\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExport\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEXP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWorld Bank\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImport\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWorld Bank\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGold Price\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWorld Gold Council\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eSource\u003c/b\u003e: Authors\u0026rsquo; Construct\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe USD/XOF exchange rate is used as a proxy for USD/EUR to observe this latter\u0026rsquo;s effect on Mali\u0026rsquo;s economy.\u003c/p\u003e \u003cp\u003eThe Autoregressive Distributed Lag (ARL) and the Bounds Test for cointegration were conducted to establish the relationships (long and short) among the variables. Later, the Error Correction Model (ECM) was specified to determine the Error Correction Term (ECT) that adjusts the model. The proposed Autoregressive Distributed Lag (ARDL) Model is as follows:\u003cdiv id=\"Equ6\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ6\" name=\"EquationSource\"\u003e\n$$\\:{GDP}_{t}\\:=\\:\\alpha\\:\\:+\\:\\sum\\:{\\beta\\:}_{1}{EXR}_{t}\\:+\\:\\sum\\:{\\gamma\\:}_{1}{INF}_{t}\\:+\\:\\sum\\:{\\delta\\:}_{1}{GLD}_{t}\\:+\\:\\sum\\:{\\theta\\:}_{1}{EXP}_{t}+\\:\\sum\\:{\\lambda\\:}_{1}{IMP}_{t}+\\:{\\epsilon\\:}_{t}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e6\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe Error Correction Model (ECM) that shows how quickly GDP adjusts to changes in the exchange rate and the other variables after a shock (and whether the system returns to equilibrium) is as follows:\u003cdiv id=\"Equ7\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ7\" name=\"EquationSource\"\u003e\n$$\\:\\varDelta\\:{GDP}_{t}\\:=\\:\\alpha\\:\\:+\\:\\beta\\:\\varDelta\\:{EXR}_{t}\\:+\\:\\gamma\\:{\\varDelta\\:INF}_{t}\\:+\\:\\delta\\:{\\varDelta\\:GLD}_{t}\\:+\\:\\theta\\:\\varDelta\\:{EXP}_{t}\\:+\\:\\lambda\\:\\varDelta\\:{IMP}_{t}\\:+\\:\\mu\\:{ECT}_{t}\\:+\\:{\\epsilon\\:}_{t}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e7\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:{\\Delta\\:}\\)\u003c/span\u003e \u003c/span\u003e represents changes (differences), ECT is the Error Correction term (the lagged residuals from the cointegration equation).\u003c/p\u003e"},{"header":"4. Findings","content":"\u003cp\u003eThe information criteria on lag length selection were determined and are displayed in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLag Structure Criteria Selection\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLag\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLogL\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFPE (e-16)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAIC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHQ\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e485.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-18.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-17.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e752.76\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e464.52\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e9.14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e-26.82\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e-25.26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e-26.22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e784.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-26.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-23.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-25.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e807.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-26.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-21.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-24.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e833.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-25.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-20.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-23.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\u003cstrong\u003eSource\u003c/strong\u003e: \u003cem\u003eAuthors\u0026rsquo; Construct\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe Akaike (AIC) and Schwarz (SC) criteria selected lag 1 as optimal. This implies short-term dynamics are sufficiently captured with one lag.\u003c/p\u003e\n\u003cp\u003eLater, data stationarity was tested through the Augmented Dickey-Fuller unit root test. The result is displayed in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eUnit Root Test (ADF) Results\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLevel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFirst Difference\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOrder of Integration\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.38 (0.588)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e-7.40\u003c/strong\u003e* (0.000)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEXR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.35 (0.601)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e-6.69\u003c/strong\u003e* (0.000)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEXP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.85 (0.797)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e-8.36\u003c/strong\u003e* (0.000)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGLD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e-5.52\u003c/strong\u003e* (0.000)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-9.71*** (0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.58 (0.864)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.1584\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eINF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e-5.93\u003c/strong\u003e* (0.000)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e-5.42\u003c/strong\u003e* (0.000)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI(0)/I(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\u003cstrong\u003eSource\u003c/strong\u003e: \u003cem\u003eAuthors\u0026rsquo; Construct\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAs per the unit root test, it can be observed that the variables are both I(0) and I(1). This justifies using first-differenced variables in short-run models (e.g., ECM) and testing for cointegration. The Bounds Test for cointegration is more adequate for exploring the long-run relationship between the variables. Also, an Autoregressive Distributed Lag (ARDL) is necessary to determine the short-term dynamics among the variables.\u003c/p\u003e\n\u003cp\u003eThe ARDL model identifies significant relationships between the exchange rate (USD/XOF) and GDP (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eARDL Model Results\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCoefficient\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003et-Statistic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGDP(-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.922***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEXR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.741***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-8.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEXR(-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.836***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEXP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.176*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGLD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.438\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eINF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.699***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCONSTANT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-118.838\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e152.313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.439\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003cstrong\u003eSource\u003c/strong\u003e: \u003cem\u003eAuthors\u0026rsquo; Construct\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eModel Fit\u003c/strong\u003e: \u003cem\u003eR2\u0026thinsp;=\u0026thinsp;0.998; Adj. R2\u0026thinsp;=\u0026thinsp;0.998; AIC = -2.68\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe exchange rate coefficient is -0.741316 (significant at 1%). This negative relationship suggests that depreciation in USD/XOF adversely affects Mali\u0026apos;s GDP growth in the short run. The lagged exchange rate (EXR(-1)) coefficient is positive (0.835629), and it indicates that past exchange rate movements have a compensatory effect on GDP growth. Inflation positively affects GDP (coefficient\u0026thinsp;=\u0026thinsp;0.699114), suggesting moderate inflation may stimulate economic activity. Other variables like exports and imports show weaker significance levels.\u003c/p\u003e\n\u003cp\u003eThe Bounds test was later performed to identify if there is a long-run relationship between the variables. The test result, depicted in Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, indicates an F-statistic of 4.458, which exceeds the critical value at the 10% significance level (I(0): 2.26; I(1): 3.35). This suggests a\u0026nbsp;\u003cstrong\u003elong-term cointegration relationship\u003c/strong\u003e between GDP and the explanatory variables (exchange rate, exports, gold price, imports, and inflation). Cointegration implies that changes in these variables have a lasting impact on Mali\u0026apos;s GDP.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBounds Test for Cointegration\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTest Statistic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCritical Values (I(0)/I(1))\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF-statistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10%: 2.26 / 3.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5%: 2.62 / 3.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1%: 3.41 / 4.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003cstrong\u003eSource\u003c/strong\u003e: \u003cem\u003eAuthors\u0026rsquo; Construct\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe existence of a long-term relation between GDP and the other variables implies the utilization of ECM. The ECM regression confirms the long-term adjustment mechanism.\u0026nbsp;\u003cstrong\u003eCointEq(-1)\u003c/strong\u003e, which is the error correction term (-0.07756), is significant at 1%; this indicates that deviations from long-term equilibrium are corrected at a speed of approximately 7.8% per year. The exchange rate (\\(\\:{\\Delta\\:}\\text{EXR}\\)) has a significant adverse short-term effect on GDP (-0.741316), reinforcing findings from the ARDL model. The ECM is represented in Table 6:\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eError Correction Model (ECM)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCoefficient\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003et-Statistic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCointEq(-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.078***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026Delta;(EXR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.741***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-12.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCONSTANT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-118.838***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjustment Speed: 7.8% of disequilibrium corrected annually.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eSource: Authors\u0026rsquo; Construct\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe diagnostic tests were conducted, and the results are displayed in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e. The diagnostic shows that the model does not have a serial correlation problem among the variables and is homoscedastic, as per the Harvey Test for heteroskedasticity. It is worth noting that this latter regresses the logs of the squared residuals on the original regressors by default.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDiagnostic Tests\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eBreusch-Godfrey Serial Correlation LM Test:\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eNull hypothesis: No serial correlation at up to 1 lag\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF-statistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProb. F(1,47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7792\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObs*R-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.094551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProb. Chi-Square(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7585\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeteroskedasticity Test: Harvey\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eNull hypothesis: Homoskedasticity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF-statistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.637536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProb. F(7,48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7226\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObs*R-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.763647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProb. Chi-Square(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6888\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eScaled explained SS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.12468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProb. Chi-Square(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2438\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003cstrong\u003eSource\u003c/strong\u003e: Authors\u0026rsquo; Construct\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe Granger causality test was performed to determine the direction of the relationship among the variables. The exchange rate significantly Granger-causes GDP (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:p=0.0324\\)\u003c/span\u003e\u003c/span\u003e), highlighting its predictive power for economic growth; GDP does not significantly Granger-causes the exchange rate (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:p=0.0785\\)\u003c/span\u003e\u003c/span\u003e), implying asymmetry in causality. Bidirectional causality exists between exports (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.022\u003c/em\u003e) and GDP (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0177\u003c/em\u003e). Moreover, imports show weaker causality effects on GDP compared to exports. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e represents the Granger causality test result.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePairwise Granger Causality\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNull Hypothesis\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eObs\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eF-Statistic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProb.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDecision (5% sig)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEXR does not Granger Cause GDP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.82639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReject\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGDP does not Granger Cause EXR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.21874\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEXP does not Granger Cause GDP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.99597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReject\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGDP does not Granger Cause EXP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.3407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReject\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGLD does not Granger Cause GDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.52561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGDP does not Granger Cause GLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.98875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReject\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIMP does not Granger Cause GDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.91079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGDP does not Granger Cause IMP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.49784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReject\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eINF does not Granger Cause GDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGDP does not Granger Cause INF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.48169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEXP does not Granger Cause EXR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.84424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEXR does not Granger Cause EXP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.08306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReject\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGLD does not Granger Cause EXR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.45981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEXR does not Granger Cause GLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.99734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReject\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIMP does not Granger Cause EXR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.89315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEXR does not Granger Cause IMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.86665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eINF does not Granger Cause EXR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEXR does not Granger Cause INF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.79796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3757\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGLD does not Granger Cause EXP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.76784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReject\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEXP does not Granger Cause GLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.2976\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReject\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIMP does not Granger Cause EXP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.29405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReject\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEXP does not Granger Cause IMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.02787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eINF does not Granger Cause EXP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEXP does not Granger Cause INF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.56805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIMP does not Granger Cause GLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.8861\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReject\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGLD does not Granger Cause IMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.27118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eINF does not Granger Cause GLD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01626\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGLD does not Granger Cause INF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12901\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eINF does not Granger Cause IMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIMP does not Granger Cause INF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccept\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003cstrong\u003eSource\u003c/strong\u003e: \u003cem\u003eAuthors\u0026rsquo; Construct\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe CUSUM of Squares graph confirms model stability over time, as the blue line remains within the bounds of 5% significance throughout most of the sample period, and that indicates that the model is largely stable. This indicates that the estimated relationships are mostly consistent and reliable. However, a notable rise between 1998 and 2010 suggests some structural shifts in the model, possibly due to economic or policy changes (e.g., the 1994 CFA franc devaluation and the adoption of the Euro currency in 1999). The CUSUM of Squares graph is displayed below in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e"},{"header":"5. Interpretation, Implications, and Recommendations","content":"\u003cp\u003eThe research highlights the adverse short-term impact of USD/XOF depreciation on GDP growth and shows long-term equilibrium adjustments through cointegration. This suggests that Mali's dependence on foreign exchange rates, particularly the stability of the Euro via the CFA Franc peg, plays a critical role in its economic health; it could be assumed that this is the same for the remaining six countries in the monetary community. Given the recent depreciation of USD/XOF \u0026minus;\u0026thinsp;628.99 CFA Francs per USD in February 2025 \u0026ndash; (The Global Economy, 2025), policymakers must focus on strengthening monetary policy by collaborating closely with the West African Economic and Monetary Union (WAEMU) to ensure stability in the CFA Franc peg system; this will help mitigate external shocks from USD/EUR fluctuations. They must emphasize protecting against external volatility by exploring mechanisms such as foreign exchange reserves or hedging strategies to reduce vulnerability to sudden currency depreciation.\u003c/p\u003e \u003cp\u003eMali\u0026rsquo;s economy relies heavily on gold and cotton exports, which account for over 80% of total exports (WB, 2025). While depreciation of USD/XOF makes exports cheaper and potentially more competitive globally, this reliance on a narrow export base limits the country\u0026rsquo;s ability to capitalize on broader trade opportunities. To address this, authorities must promote agricultural productivity by adopting policies that enhance agricultural output and trade facilitation, which could help diversify exports and reduce reliance on gold and cotton. They must also develop manufacturing and value-added sectors; this could be done by expanding into manufacturing or processing industries that could create more resilient export streams that are less dependent on commodity prices.\u003c/p\u003e \u003cp\u003eIn addition, inflation has been positively correlated with GDP growth in Mali, suggesting that moderate inflation may stimulate economic activity by increasing spending power and attracting investment. However, excessive inflation risks eroding purchasing power and increasing production costs. Policymakers must strive to maintain prices and continue monitoring inflation closely while ensuring it remains within a range conducive to growth. Supporting vulnerable populations by combatting food insecurity and providing subsidies and support programs that could mitigate inflation\u0026rsquo;s impact on lower-income households.\u003c/p\u003e \u003cp\u003eMoreover, Mali faces significant security challenges alongside its neighbors Burkina Faso and Niger, including ongoing conflicts and socio-political instability. These factors exacerbate economic vulnerabilities, limiting foreign investment and increasing fiscal pressures. The government must strengthen governance with transparent political processes and stable leadership, which are essential for fostering investor confidence.\u003c/p\u003e \u003cp\u003eThe resurgence of protectionist policies under Trump 2.0 in the U.S., including increased tariffs and reduced foreign aid, may indirectly affect many countries through tighter global financial conditions; Mali is no exception. Additionally, volatile commodity prices remain a risk for Mali\u0026rsquo;s gold exports. To curb these, authorities may diversify Mali\u0026rsquo;s trade partnerships by strengthening intra-African trade through agreements like the African Continental Free Trade Area (AfCFTA). They should also reduce dependency on aid and focus on domestic resource mobilization.\u003c/p\u003e \u003cp\u003eLastly, climate change poses significant threats to Mali\u0026rsquo;s agriculture-dependent economy. Erratic weather patterns can disrupt crop yields, exacerbate food insecurity, and hinder GDP growth. To mitigate climate impacts, policymakers should invest in climate resilience and develop strategies, such as irrigation systems, drought-resistant crops, and reforestation initiatives. They should also enhance disaster preparedness by strengthening infrastructure to withstand extreme weather events, which will reduce economic losses.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThe CFA Franc has been a currency of controversy for many years. Nowadays, it is obvious that the fixed conversion with the Euro has started displaying issues, and many echo these. This study supports the general determining influence of exchange rate development on Mali's macroeconomic performance. In the past, the formerly fixed CFA Franc (XOF)\u0026mdash;Euro peg has delivered stability, particularly in containing inflation. However, this comes at a cost of reduced monetary policy room for maneuver, reducing Mali's ability to respond successfully to exogenous shocks, most prominently from USD/EUR parity changes and commodity price volatility.\u003c/p\u003e \u003cp\u003eThe study also indicates that economic growth in Mali remains exchange rate-sensitive due to the country's structural reliance on foreign trade and commodity exports, primarily gold. As a result, exposure to external shocks, including global economic instability, regional security concerns, and inflationary pressure, constrains sustainable growth. Addressing these challenges will require a multi-dimensional approach.\u003c/p\u003e \u003cp\u003eBeyond maintaining monetary and fiscal stability, Mali must accelerate efforts towards economic diversification, foster financial sector development, and invest in climate adaptation strategies to safeguard key sectors such as agriculture and mining. Moreover, while the WAEMU exchange rate regime has provided short-term stability, further research is warranted to assess whether its long-term effects are aligned with Mali\u0026rsquo;s developmental objectives, especially under rapidly changing global conditions.\u003c/p\u003e \u003cp\u003eHere, policymakers should consider policies that reduce reliance on foreign currency, like the Euro, tackle structural vulnerabilities, enhance resilience, and ensure inclusive growth. Stability of the exchange rate for overall macroeconomic stability and sustainable development is still a top priority of strategic nature and immediacy for Mali and the other WAEMU member states.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research does not involve human participants, their data, or animals. Therefore, no ethical approval was required. All procedures and methods used in the study comply with the relevant institutional and international research guidelines and standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data of this study were collected from different websites notably those of the World Bank, the IMF and the BRVM. The datasets are available\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author has no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAsongu, S. (2014). Exchange Rate Stability and FDI in West Africa. \u003cem\u003eAfrican Development Review\u003c/em\u003e, 26(2), 125-145.\u003c/li\u003e\n\u003cli\u003eBalassa, B. (1964). The Purchasing Power Parity Doctrine: A Reappraisal. \u003cem\u003eJournal of Political Economy\u003c/em\u003e, 72(6), 584\u0026ndash;596. https://doi.org/10.1086/258965\u003c/li\u003e\n\u003cli\u003eBarguellil, A., Ben-Salha, O., \u0026amp; Zmami, M. (2018). 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Domestic financial policies under fixed and under floating exchange rates. IMF Staff Papers, 9(3), 369\u0026ndash;380. https://doi.org/10.2307/3866091\u003c/li\u003e\n\u003cli\u003eFofanah, P. (2022). Effects of Exchange Rate Volatility on Economic Growth: Evidence from West Africa. \u003cem\u003eInternational Journal of Business and Economics Research\u003c/em\u003e. https://doi.org/10.11648/j.ijber.20221101.15\u003c/li\u003e\n\u003cli\u003eGhosh, A., Gulde, A., \u0026amp; Wolf, H. (1997). Does the Exchange Rate Regime Matter for Inflation and Growth? \u003cem\u003eIMF Economic Review\u003c/em\u003e, 44(3), 381-414.\u003c/li\u003e\n\u003cli\u003eGuzman, M., Ocampo, J., \u0026amp; Stiglitz, J. (2017). Real Exchange Rate Policies for Economic Development. \u003cem\u003ePSN: Exchange Rates \u0026amp; Currency (Comparative) (Topic)\u003c/em\u003e. https://doi.org/10.3386/W23868\u003c/li\u003e\n\u003cli\u003eJohn, F. (1997). \u003cem\u003eStatistical Methods in Economic Research\u003c/em\u003e. Cambridge University Press.\u003c/li\u003e\n\u003cli\u003eMamadou, N\u0026rsquo;Diaye. (2021). Financial Development and Economic Growth: Case of Mali. \u003cem\u003eBusiness, Management and Economics Research\u003c/em\u003e. https://doi.org/10.32861/bmer.74.108.119\u003c/li\u003e\n\u003cli\u003eMankiw, N. G. (1990). A Quick Refresher Course in Macroeconomics. \u003cem\u003eJournal of Economic Literature\u003c/em\u003e, 28(4), 1645-1660.\u003c/li\u003e\n\u003cli\u003eMorina, F., Hysa, E., Erg\u0026uuml;n, U., Panait, M., \u0026amp; Voica, M. (2020). The Effect of Exchange Rate Volatility on Economic Growth: Case of the CEE Countries. \u003cem\u003eJournal of Risk and Financial Management\u003c/em\u003e. https://doi.org/10.3390/jrfm13080177\u003c/li\u003e\n\u003cli\u003eMundell, R. (1963). 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The Real Exchange Rate and Economic Development. \u003cem\u003eStructural Change and Economic Dynamics\u003c/em\u003e, 23(2), 151-169. https://doi.org/10.1016/j.strueco.2012.01.002\u003c/li\u003e\n\u003cli\u003eRazzaque, M., Bidisha, S., \u0026amp; Khondker, B. (2017). Exchange Rate and Economic Growth. \u003cem\u003eJournal of South Asian Development\u003c/em\u003e, 12, 42-64. https://doi.org/10.1177/0973174117702712\u003c/li\u003e\n\u003cli\u003eRibeiro, R. S., McCombie, J. S., \u0026amp; Lima, G. T. (2020). Does Real Exchange Rate Undervaluation Really Promote Economic Growth? \u003cem\u003eStructural Change and Economic Dynamics\u003c/em\u003e, 52, 408-417. https://doi.org/10.1016/j.strueco.2019.02.005\u003c/li\u003e\n\u003cli\u003eRogoff, K. (1996). The purchasing power parity puzzle. Journal of Economic Literature, 34(2), 647\u0026ndash;668.\u003c/li\u003e\n\u003cli\u003eSamuelson, P. A. (1964). Theoretical notes on trade problems. The Review of Economics and Statistics, 46(2), 145\u0026ndash;154. https://doi.org/10.2307/1928178 \u003c/li\u003e\n\u003cli\u003eSy, A. (2019). The CFA Franc and West Africa\u0026rsquo;s Economic Future. \u003cem\u003eBrookings Institution Policy Paper\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eThirlwall, A. P. (1979). The balance of payments constraint as an explanation of international growth rate differences. Banca Nazionale del Lavoro Quarterly Review, 128, 45\u0026ndash;53.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Exchange Rate, CFA Franc, Economic Growth, ARDL, Currency Regime","lastPublishedDoi":"10.21203/rs.3.rs-6866535/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6866535/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper investigates the relationship between economic growth and exchange rate volatility in Mali, a member of the West African Economic and Monetary Union (WAEMU) with a fixed exchange rate regime by way of the CFA Franc (XOF) peg to the Euro (EUR). In accordance with the Mundell-Fleming model, Purchasing Power Parity (PPP) theory, and balance of payments-constrained growth, the study examines how deviations of the XOF/USD exchange rate—used as a proxy for EUR/USD changes—affect significant macroeconomic variables like GDP, inflation, exports, and imports. Based on annual time series data covering 1967 to 2023, the study uses the Autoregressive Distributed Lag (ARDL) model to examine short-run behavior and long-run equilibrium relationships. The findings reinforce the existence of cointegration between the variables and establish that exchange rate volatility has a major impact on Mali's macroeconomic performance. The fixed peg delivers nominal stability but is restrictive on policy independence and increases vulnerability to external shocks. The findings add novel insights, which are country-specific, to the general discourse on currency regimes in sub-Saharan Africa and provide policy lessons for increasing resilience and sustainable growth under limited monetary regimes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJEL\u003c/strong\u003e: E31, F31, F33, F41, O55\u003c/p\u003e","manuscriptTitle":"Do Pegged Currencies Support Growth? Insights from Mali’s Experience with the CFA Franc","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-12 04:44:19","doi":"10.21203/rs.3.rs-6866535/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"50d771f9-965d-40fa-ac30-906906da50b7","owner":[],"postedDate":"June 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":49847116,"name":"International Economics"},{"id":49847117,"name":"Finance"},{"id":49847118,"name":"Other Economics"}],"tags":[],"updatedAt":"2025-06-12T04:44:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-12 04:44:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6866535","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6866535","identity":"rs-6866535","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}