67 © 2022 by the authors; licensee Asian Online Journal Publishing Group Asian Journal of Economics and Empirical Research Vol. 9, No. 2, 67-72, 2022 ISSN(E) 2409-2622 / ISSN(P) 2518-010X DOI: 10.20448/ajeer.v9i2.4055 © 2022 by the authors; licensee Asian Online Journal Publishing Group Do Interest Rate and Inflation Matter for Exchange Rate Fluctuation in Bangladesh? An ARDL Approach Mamun Chowdhury Department of Economics, Jagannath University, Dhaka, Bangladesh. Email: mamun@eco.jnu.ac.bd Abstract This research explores the effects of inflation and interest rate on the nominal exchange rate in Bangladesh using data from 1980 to 2021. The Augmented Dicky-Fuller (ADF) test is used to find the order of integration whereas the ARDL approach has been used to determine the causality and cointegration among the variables. The ARDL bounds testing approach revealed a stable and statistically significant long-run relationship between Interest Rate (IR), Inflation (INF) and Exchange Rate (ER). The long-run ARDL model advocates that an increase in the lending interest rate leads to a significant appreciation of Bangladeshi currency in terms of USD. At the same time, the inflation has a positive but insignificant impact on the exchange rate at 5% level of significance. In the short-run, the effects of the interest rate on the exchange rate are positive and significant but the inflationary effect on the exchange rate is not statistically significant. Hence, the study recommends an efficient management of interest rate and inflation in Bangladesh to keep balance in the exchange rate. Keywords: Exchange rate, Inflation, Interest rate, ARDL model, Foreign exchange earnings, Bangladesh. JEL Classification: C12; C32; C87; F41; E50. Citation | Mamun Chowdhury (2022). Do Interest Rate and Inflation Matter for Exchange Rate Fluctuation in Bangladesh? An ARDL Approach. Asian Journal of Economics and Empirical Research, 9(2): 67-72. History: Received: 10 February 2022 Revised: 23 March 2022 Accepted: 7 April 2022 Published: 18 July 2022 Licensed: This work is licensed under a Creative Commons Attribution 4.0 License Publisher: Asian Online Journal Publishing Group Funding: This study received no specific financial support. Competing Interests: The author declares that there are no conflicts of interests regarding the publication of this paper. Transparency: The author confirms that the manuscript is an honest, accurate, and transparent account of the study; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. Ethical: This study followed all ethical practices during writing. Contents 1. Introduction ...................................................................................................................................................................................... 68 2. Literature Review ............................................................................................................................................................................ 69 3. Data and Methodology ................................................................................................................................................................... 70 4. Results and Discussion ................................................................................................................................................................... 70 5. Conclusion and Policy Recommendations .................................................................................................................................. 71 References .............................................................................................................................................................................................. 72 mailto:mamun@eco.jnu.ac.bd https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/ https://www.doi.org/10.20448/ajeer.v9i2.4055 https://orcid.org/0000-0002-5181-1466 Asian Journal of Economics and Empirical Research, 2022, 9(2): 67-72 68 © 2022 by the authors; licensee Asian Online Journal Publishing Group Contribution of this paper to the literature This study contributes to existing literature by exploring whether the two key macroeconomic variables such as interest rate and inflation can be crucial factors to unstable the nominal exchange rate in a developing country like Bangladesh. 1. Introduction Both interest rate and inflation are the key to having an impact on the nominal exchange rate, consistent with many economic theories. The traditional economic theories argue that an increase in the domestic lending interest rate would provide incentives for foreign investors to invest in financial markets. The influx of such foreign capital, would, therefore, appreciate the national currency. On the contrary, a lower domestic interest rate would depreciate currency value and as a result, boost the capital outflow (Mgammal, 2012). As opined by Ogege (2019), the interest rate is the most essential component of the economy because it affects international trade through borrowing costs, savings, and investment. Fisher (1930)also explained the inflationary effect on the exchange rate by concluding that the increase in the inflation rate would depreciate the value of the domestic currency. This is because the higher the rate of inflation, the higher volume of imports which dampens the export performance. The seminal work by Engel (1986), has also pointed out that the negative relationship between the nominal interest rate and exchange rate takes place if the inflation rate of a country increases and the expected inflation rate decreases. The theory of Purchasing Power Parity (PPP) has also attributed a negative relationship between inflation and nominal exchange rate in the same vein. Overall, the impact of interest rate and inflation on the exchange rate is still conflicting as theoretical and empirical literature have failed to provide conclusive evidence about the effects of interest rate and inflation on the exchange rate. Nevertheless, in Bangladesh, the correlation between these three macroeconomic variables may be stronger as they were fluctuating altogether since the 1980s. Refer to Table 1. This volatility may be due to lower levels of output growth, inadequate Foreign Direct Investment (FDI), and the political turmoil between 1980 and 1990. After the 2000s, overwhelming government debts from the banking sector and the massive capital flight have contributed to the worsening liquidity scenario. This leads to an increase in the interest rate and inflation. The trend of the nominal exchange rate also showed a steady devaluation of BDT during this period. This paper has intended to explore whether the changes in the interest rate and inflation have any influence on the devaluation of BDT against the USD. Furthermore, divergences in the findings of some theories were motivation to take up this issue in Bangladesh. However, this study has some significance for Bangladesh's economy as its economic growth is highly sensitive to the changes in the exchange rate. This has exposed the country’s remittance and export sector to greater vulnerability. The excess devaluation of its currency would increase the import cost. On the contrary, its appreciation might have an effect on the export performance and remittance inflow. Hence, the stability in the interest rate and inflation is important for Bangladesh to keep its exchange rate in a steady-state position. Given this context, this paper aims to address the following two issues. First, to investigate whether the nominal exchange rate of BDT(Bangladesh) in terms of USD posits a cointegration relation with interest rate and inflation. Second, to examine the effects of fluctuations in the interest rate and inflation on the long-run and short-run behavior of the nominal exchange rate in Bangladesh. 1.1. Exchange Rate, Interest Rate and Inflation Nexus in Bangladesh The transition of Bangladesh's economy since(to) independence was not smooth. Since then, the country has faced several economic policy shifts. For example, it adopted socialism shortly after the independence and thereby nationalized all its SOEs. The socialistic mode of production, however, did not bring success to the economic growth for which the country had to enter into the privatization-led free-market economy in the early 1980s. The statistics show that the economy was not performing well, even in the realm of a privatization-based free-market economy. The economy was facing several challenges ranging from low GDP growth to ensuring food security. The key macroeconomic variables such as interest rate, inflation and exchange rate showed volatility as the monetary aggregates were not steady. This might be due to the persistent lower export growth, high import cost, low remittance inflow, poor foreign direct investment and high payment of external debt interest. Table 1. Trend of exchange rate, lending interest rate and consumer price index in Bangladesh. Year Exchange Rate Interest Rate Consumer price Index 1980 15.45 11.33 17.92 1985 27.99 12 27.80 1990 34.57 16 49.85 1995 40.28 14 63.73 2000 52.14 12.75 80.22 2005 64.33 10.62 102.69 2010 69.65 12.22 163.52 2015 77.95 11.71 227.39 2020 84.87 8.3 282.685 2021 85.08 7.3 298.395 Source: 1) World Development Indicators (WDI), World Bank, 2). World Economic Outlook 2020 (WEO), IMF. From the statistics depicted in Table 1, the BDT had been continuing to have depreciated since the 1980s. From 1983 onwards, the country experienced 89 adjustments in exchange rate. Among which 83 were observed downwards and the remaining were upward (Islam, 2002). On occasion, the government had intentionally kept its currency value lower against the USD aiming to boost its export sector. The practice of an adjustable peg system had made it easier for the government to keep the currency value favorable to international trade. Despite this, during the 1980s and 1990s, the nominal exchange rate of Bangladesh was being further depreciated. The domestic interest rate and inflation were volatile and at the same time, the export earnings and remittances were not strong Asian Journal of Economics and Empirical Research, 2022, 9(2): 67-72 69 © 2022 by the authors; licensee Asian Online Journal Publishing Group enough to prevent BDT from being further depreciated. However, in early 2000, the booming export sector and remittance earnings along with the stability in macroeconomic aggregates have provided Bangladesh with some economic strength to adopt a floating exchange rate system. The statistics as displayed in Table 1 show that the nominal exchange rate of Bangladesh was not steady, even in the realm of floating exchange rate. After 2005, the rate of depreciation of BDT was not less comparing to the previous decades. So why did the exchange rate of BDT depreciate while the country had better export earnings and remittance inflow? The volatility in the interest rate and inflation after 2000 may be the reason for the downturn of BDT values against the USD. The statistics evident in Table 1 have strengthened this possibility as the interest rate was significantly higher after 2000, which reached its peak in 2017 and the consumer price index became parallel to this skyrocketing interest rate. Furthermore, as per the economic theory, the increase in the interest rate and inflation can depreciate currency by rising imports. On the other hand, the increased interest rate can also appreciate the currency by increasing the demand for foreign capital. 1.2. Theoretical Background of the Research Many classical and contemporary economic theories have highlighted the relationship between interest rates, inflation, and exchange rates. Their findings, however, were not similar which has made this a long-debated issue in macroeconomics. Several economic theories such as the international Fisher Effect (IFE), the theory of Purchasing Power Parity (PPP), the views of Keynesian and Chicago schools, etc. have produced the following different conclusions. The International Fisher effect is an extended form of the Fisher effect which postulates a positive correlation between nominal interest rate and expected rate of inflation. According to the theory, as is stated by Dornbush, Fischer, and Startz (2009), the country will tend to experience depreciation in relation to its currency value if it has a higher rate of interest compared to its trading partners. According to the theory of Purchasing Power Parity, the ratio of purchasing power of the two countries is a strong determinant of the nominal exchange rate. The real exchange rate turns out to be less than 1(%) if a country faces higher inflation in comparison with another country. This implies that the country has to depreciate its currency value to make the real exchange rate equal to 1(%). Furthermore, the views of the Chicago school and Keynesian thought can also be some good examples in analyzing the interest rate, inflation and exchange rate relationship. The Chicago school considers the fluctuation in interest rate a prime source for the deviation of the nominal exchange rate. The school believes that the higher cost of production, which is caused by the higher lending interest rate, leads to an increase in the exchange rate of domestic currency because the country now faces inflation and depreciation(Frankle, 1979). Alternatively, the Keynesian views find an appreciation of domestic currency value due to the effect of increased nominal interest rate in the domestic financial market. Keynes explains this relationship based on the theory of sticky prices. The theory argued that any increase in nominal interest rate, which might be the result of the tight monetary policy, eventually leads to an increase in real interest rate because there is a sticky price in the goods market. The higher rate of real interest rate would, therefore, bring foreign capital to the country. Hence, following the Keynes view, there would be an appreciation of domestic currency value as the inflow of foreign capital will increase the demand for domestic currency in the foreign exchange market. 2. Literature Review This section explores different types of literature on the nexus between interest rate, inflation, and exchange rate for the different economies. The aim is to understand how the exchange rate of Bangladesh and many other countries respond to the changes in the interest rate and inflation. For example, by using Structural Vector Autoregressive (SVAR) and Cholesky Factorization method (Karim, 2019) found that the increase in domestic interest rate attracts foreign investors and thereby causes the appreciation of Bangladesh Taka against USD. On the other hand, Chowdhury and Hossain (2014) have shown that the increase in interest rate in Bangladesh creates a depreciation of the Taka in terms of USD. Likewise, Amin, Murshed, and Chowdhury (2018) and Hossain and Ahmed (2009) have found a similar result. Now, in the context of the global economy, the work of Carneiro and Rossi (2013) and Shodipe (2018) are good examples to start with. In their seminal work, the authors argued that prudent macroeconomic policy is necessary for the economy to prevent further appreciation of currency value which has been caused by the increase in interest rate. However, a cross-country analysis by Kui SI, Xiao-Lin, Chang, and Lu (2018) has also shown positive co- movement between interest rate and exchange rate for the economy of BRICS countries. On the other hand, (Hacker, H. Kim, & Manson, 2009) showed that the increase in interest rate leads to appreciating the currency value in the short run for selected seven pairs of countries. Yung (2017) has concluded that the interest rate is negatively related to the exchange rate. The work of Khan, Teng, and Khan (2019) has also estimated negative effects of interest rate and inflation on the exchange rate in the Chinese economy. Saraç and Karagöz (2016) in their work, however, interestingly found no evidence that a higher interest rate can cause exchange rate differentials in Turkey’s economy. Hossain (2002) argued that the increase in the consumer price index leads to a higher nominal exchange rate in Bangladesh. Murshed (2018), on the other hand, has found no evidence of Granger causality from inflation to exchange rate in Bangladesh. Ali, Mahmood, and Bashir (2015) have studied the relationship between inflation, interest rate and exchange rate for the Pakistan economy and found bi-direction Granger causality between inflation and exchange rate. Dilmaghani and Tehranchian (2015), on the other hand, alleged that a country with a higher domestic inflation rate faces devaluation of its currency value. The seminal work by Sean, Pastpipatkul, and Boonyakunakorn (2019) demonstrated that the increase in money supply causes inflation in Cambodia and the increased inflation depreciates its currency value in consequence. Similarly, Joof and Jallow (2020) argued that a 1% increase in the inflation rate in the Gambia result from a 0.39% devaluation of domestic currency value against the US dollar. The works by Fetai, Koku, Caushi, and Fetai (2016) have found that the exchange rate volatility is the supreme cause of generating inflationary pressure in Western Balkan countries. Asian Journal of Economics and Empirical Research, 2022, 9(2): 67-72 70 © 2022 by the authors; licensee Asian Online Journal Publishing Group 3. Data and Methodology The entire data set deployed in this research has been collected from two sources, the World Development Indicators (WDI) of the World Bank (WB) and the World Economic Outlook of IMF. However, this study employed the Autoregressive Distributive Lag (ARDL) model developed by Pesaran, Shin, and Smith (2001) to investigate the short-run and long-run relationship between the studied variables. This method was used because it provides some advantages compared to other traditional methods like (Engle & Granger, 1987) two-step procedures and Johansen and Juselius (1990). For example, the ARDL model is likely to be more efficient, even with a small sample size, whereas the Johansen Juselius test requires a relatively large sample size to obtain valid results (Ghatak & Siddiki, 2001). An additional advantage of this model is that it can determine the level of relationship between the variables even if the regressors are integrated at different orders such as I(0) and I(1). On the contrary, the Johansen Juselius test provides results if the variables are integrated at I (1). Furthermore, the ARDL model is successful to address the endogeneity problem. This is because it allows satisfactory lags that can provide unbiased long-run estimates and valid t-statistics even when the time series are not integrated at the same level. Moreover, this approach can also provide the simultaneous assessment of the long-run and short-run effects of one variable on another. The following model shows the long-run relationship of the time series. ΔERt = ɑ1+ β1ERt-i + β2IRt-i+ β3INFt-i + ∑ θ p i=1 i∆ERt-i +∑ λ p i=1 i∆NIRt-I+ ∑ ψ p i=1 i∆NINFt-i+ε1t(1) ΔIRt = ɑ2+ β1IRt-i + β2ERt-i + β3INFt-i + ∑ θ p i=1 i∆ERt-i +∑ λ p i=1 i∆NIRt-I+ ∑ ψ p i=1 i∆NINFt-i+ ε2t(2) ΔINFt = ɑ3+β1INFt-i + β2ERt-i+ β3IRt-i + ∑ θ p i=1 i∆ERt-i +∑ λ p i=1 i∆NIRt-I+ ∑ ψ p i=1 i∆NINFt-i + ε3t (3) Where, Δ stands for the first difference operator, ɑi (i= 1....3) is the constant term, βi (i=1...3) represents coefficients of the lagged levels, θi, λi, and 𝛙i (i= 1-p) signifies the coefficients of lagged variables and εit (i= 1...3) implies the error terms which is assumed to be serially uncorrelated. The lag length is denoted by p which is determined by the minimum value of Schwartz Information Criteria (SIC). However, the equation can be divided into two parts. The first portion which is denoted by βi represents the long-run relationship. On the contrary, the portion with the summation sign would provide the short-run dynamics of error correction. The ARDL bound test provides the Wald test (F-statistics) that estimates the long-run cointegration among variables. The lagged level variables are restricted to zero to form a null hypothesis. Pesaran et al. (2001) have argued that the calculated F-statistics need to be compared with upper bound and lower bound critical values for the estimation of the relationship. According to the model, the null hypothesis would be rejected if the value of calculated F-statistics goes above the value of the upper bound. On the other hand, if the calculated F-statistic value is found below the lower bound critical value, the null hypothesis cannot be rejected. However, the inference remains inconclusive if the value of F-statistics is positioned within these two bounds. If cointegration exists, the model would look into the estimation of long-run coefficients and short-run parameters along with Error Correction. Therefore, the ARDL model with error correction term is presented below to estimate the long-run and short-run coefficients. ΔERt= ɑ1+ β1ERt-i+ β2IRt-i+ β3INFt-i+ ∑ θ p i=1 i∆ERt-i +∑ λ p i=1 i∆NIRt-I + ∑ ψ p i=1 i∆NINFt-i+δ1 ECTti+ε1t (4) ΔIRt= ɑ2 + β1IRt-i + β2ERt-i+ β3INFt-i + ∑ θ p i=1 i∆ERt-i +∑ λ p i=1 i∆NIRt-I + ∑ ψ p i=1 i∆NINFt-i + δ2 ECTt-i+ε2t(5) ΔINFt= ɑ3+ β1INFt-i+ β2ERt-i+ β3IRt-i+ ∑ θ p i=1 i∆ERt-i+∑ λ p i=1 i∆NIRt-I + ∑ ψ p i=1 i∆NINFt-i + δ3 ECTti+ε3t(6) Equation 4 presents the target model of this research which estimates the effects of inflation and interest rate on the exchange rate with the error correction term. In the same vein, Equation 5 and 6 postulates the effects of corresponding explanatory variables in the equations when interest rate (ΔIR) and inflation (ΔINF) at time t appear as dependent variables. The error correction term in the equation stands for the long-run equilibrium speed of adjustment. However, the convergence to the long-run equilibrium would occur if the sign of the error correction term is found negative and the coefficient of the term is significant. 4. Results and Discussion Although the ARDL bound testing approach can accommodate variables in any order such as I(0), I(1), or their mixture, it cannot be employed in any of the variables integrated at order 2 that is I(2). Therefore, the ARDL approach requires testing the stochastic properties of the time series to be confirmed that none of the variables are I(2). The widely used Augmented Dickey-Fuller test is employed in this research to make sure the stochastic properties of the variables. Table 2. Unit root test (ADF) for the period of 1980 to 2021. Intercept With Trend and Intercept Series at Level First Difference Series at level First Difference Variables Test Statistic Test Statistics Test Statistics Test Statistics LN ER -5.28 (0) * -3.91(0)* -4.07(0)* -6.42(1)* LN IR -0.27(1) -3.75(0)* -1.35(1) -4.22(0)* LN INF -1.51(1) -7.29(1)* 5.86(0)* -7.22(1)* Notes: * denotes rejection of null hypothesis at a 5% level of significance. The figure in parenthesis indicates the optimal lag length determined by Schwartz Information Criteria (SIC). The results depicted in Table 2 indicate some mixed integrations. For example, while the variable LNER is confirmed stationary at I(0), the variable like LNIR exhibits stationary at I(1). This dichotomy continues for LNINF as well. The variable LNINF is found stationary at I(1) with intercept but if we check its unit root in the case of with trend and intercept it does not need the first difference to be stationary. Hence, Table 2 indicates that the order of integration of the series is a mixture of I(0) and I(1) and none of the series are I(2). Thus, the unit root results indicate that the paper needs to employ the ARDL approach the order of integration is a mixture of I(0) and I(1) and none of them are I(2). Asian Journal of Economics and Empirical Research, 2022, 9(2): 67-72 71 © 2022 by the authors; licensee Asian Online Journal Publishing Group The ARDL bounds testing method will check co-integration for equations (4), (5) and (6) where each variable appears LHS simultaneously. This method provides F-statistics at a 5% level of significance as presented in Table 3. Table 3. ARDL bound test for co integration. Functions Value of F Statistics Critical Values at a 5% level of significance Inferences I(0) I(1) F(LNER/LNIR, LNINF) 27.2* 3.1 3.87 Cointegrated F(LNIR/LNER, LNINF) 2.45 3.1 3.87 Not cointegrated F(LNINF/LNER, LNIR) 9.12* 3.1 3.87 Cointegrated Note: 1: * indicates the rejection of the Null Hypothesis at a 5% level of Significance. This method determines co-integration among variables if the F-statistics value is greater than the upper bound value produced at a 1% or 5% or 10% level of significance (Pesaran et al., 2001). According to the results, the long-run cointegration relationship is evident among the variables when LNER and LNINF appear as dependent variables as the values of calculated F-statistics of these functions are greater than the 5% upper bound value. The estimated results show there is a stable long-run relationship between interest rate, inflation, and exchange rate in Bangladesh. On the contrary, the changes in the nominal exchange rate and inflation do not have any long-term effects on the interest rate when the interest rate appears as a dependent variable. However, in this research, my target model is (4) where the exchange rate appears as a dependent variable and the bound test result confirms the long-run relationship among the variables of this model. That being said, we need the long-run estimators of the model to measure the effects of regressors on the dependent variable. The optimal lag length is determined by the Schwartz Information Criteria (SIC) criterion which selects ARDL (1, 1, 0) model. The results of long-run coefficients are presented in Table 4. Table 4. ARDL long run and short run approach with LNER as dependent variable. Function Coefficient Std. Error t-Statistic Probability LNIR -1.05 0.39 -2.69 0.01 LNINF 0.18 0.10 1.69 0.09 C 0.62 0.12 5.18 0.00 D(LIR) 0.11 0.07 1.46 0.15 CointEq(-1)* -0.10 0.01 -10.9 0.00 Note: * indicates ECM value is negative and Significant. The long-run approach provides the long-run coefficients of regressors and probability value of t-statistics. The coefficient of LNIR is estimated at -1.058382 and the probability of t-statistics suggests this result is highly significant. This long-run estimator advocates the negative relationship between interest rate and exchange rate. The nominal exchange rate in Bangladesh decreases by 105% per annum if the nominal lending interest rate rises by 1% in the long run. This finding goes parallel to the Keynesian thought which postulates that a unit increase in interest rate appreciates the currency value to a greater extent. On the contrary, inflation (LNINF) in Bangladesh is positive, but insignificant long-run effects on the nominal exchange rate. The exchange rate of BDT depreciates by 17.6% per annum against USD for a 1% increase in the general price level in Bangladesh. The short-run effect of the interest rate is not similar to the long-run effect. The effects of the interest rate on the exchange rate are positive in the short run. As shown by the results, the increase in interest rate by 1% point depreciates the currency value of BDT by 10.6% in the short run. These short-run effects are also statistically insignificant as the P-value of t-statistics is greater than 5%. However, the error correction term is statistically significant. The negative sign before it implies that the long-run disequilibrium will turn back to a steady-state by any external shock imposed on the economy. The lower value (-0.0101283) of the error correction term is indicating that it will take a longer period to make the adjustment process. 5. Conclusion and Policy Recommendations The stability in the exchange rate regime is crucial for Bangladesh's economy due to its recent economic growth relying heavily on foreign exchange earnings. Its export earnings and remittance inflow would significantly increase cost if there is unsteadiness in the exchange rate. The economy would cost the payment of import bills and external debt as well if the exchange rate cannot be kept under control. However, it is a challenge for Bangladesh to keep the exchange rate under control in the floating exchange rate system. Except for the RMG export and the remittances, the country has not any significant economic strength that can make the BDT stronger against the USD. On the contrary, the amount of money outgoing from Bangladesh is increasing rapidly. Hence, the stability in the interest rate and inflation is crucial for Bangladesh as these two have direct impacts on both the inflow and outflow of money. The empirical results of this study have been found by using the ARDL method are statistically significant as the coefficient of the cointegrating equation has been found negative and the probability value of t-statistics is less than 5%. In the long run, the impact of inflation and interest rate on the exchange rate is not similar. The exchange rate appreciated by 105.8% for a 1% increase in interest rate. On the other hand, the exchange rate depreciated by 17.6% if the inflation rate goes up by 1%. In the short run, however, the increase in the interest rate causes a little depreciation of BDT. Moreover, the value of the error correction term is found very low which is only at 1.01%. The slower adjustment indicates that the economy will take a longer time to correct any disequilibrium in the interest rate and inflation to get the exchange rate into a steady-state situation. The monetary policy is therefore requiring efficient management of interest rate and inflation as the exchange rate in Bangladesh is found highly elastic to the interest rate which can impact badly on the foreign exchange earnings. Paradoxically, an increased interest rate can be an effective strategy for Bangladesh, while the exchange rate depreciates sharply. However, the monetary authority in Bangladesh should also consider the slow adjustment Asian Journal of Economics and Empirical Research, 2022, 9(2): 67-72 72 © 2022 by the authors; licensee Asian Online Journal Publishing Group process toward the long-run equilibrium in the exchange rate. The value of the speed of adjustment is found extremely low which would entail higher associated costs if the monetary authority fails to keep interest rate and inflation stable. References Ali, T. M., Mahmood, M. T., & Bashir, T. (2015). Impact of interest rate, inflation and money supply on exchange rate volatility in Pakistan. World Applied Sciences Journal, 33(4), 620-630. Amin, S., Murshed, M., & Chowdhury, M. T. (2018). Examining the exchange rate overshooting hypothesis in Bangladesh: A cointegration and causality analysis. World Journal of Social Sciences, 8(3), 69-83. Carneiro, R., & Rossi, P. (2013). The Brazilian experience in maintaining interest-exchange rate nexus. Berlin Working Paper On Money, Finance, Trade and Development, No, 02/2013. Chowdhury, M., & Hossain, M. (2014). Determinants of exchange rate in Bangladesh: A case study. Journal of Economics and Sustainable Development, 5(1), 78-81. Dilmaghani, K. A., & Tehranchian, A. M. (2015). The impact of monetary policies on the exchange rate: A GMM approach. Iranian Economic Review, 19(2), 177-191. Dornbush, R., Fischer, S., & Startz, R. (2009). Macro economics (9th ed.). New York: McGraw-Hill, 121 Avenue of the Americas. Engel, C. M. (1986). On the correlation of exchange rates and interest rates. Journal of International Money and Finance, 5(12), 125-128. Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251-276. Fetai, B., Koku, P. S., Caushi, A., & Fetai, A. (2016). The relationship between exchange rate and inflation: The case of Western Balkans countries. Journal of Business Economics and Finance, 5(4), 360-364.Available at: https://doi.org/10.17261/pressacademia.2017.358. Fisher, I. (1930). The theory of interest (Vol. 43). New York: The Macmillan Company. Frankle, J. A. (1979). A Theory of floating exchange rates based on real interest differentials. The American Economic Review, 69(4), 610-622. Ghatak, S., & Siddiki, J. U. (2001). The use of the ARDL approach in estimating virtual exchange rates in India. Journal of Applied Statistics, 28(5), 573-583.Available at: https://doi.org/10.1080/02664760120047906. Hacker, R. S., H. Kim, H., & Manson, K. (2009). The relationship between exchange rates and interest rates differentials: A wavelet approach. CESIS Electronics Working Paper Series, No: 217, 1-23. Hossain, A. (2002). Exchange rate responses to inflation in Bangladesh. IMF Working Paper, No. WP/02/166, 1-33. Hossain, M., & Ahmed, M. (2009). An assessment of exchange rate policy under floating regime in Bangladesh. The Bangladesh Development Studies, 33(4), 35-67. Islam, M. A. (2002). Exchange rate policy of Bangladesh-not floating does not mean sinking. Asia-Pacific Development Journal, 9(2), 1-15. Johansen, S., & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration with application to the demand for money. Oxford Bulletin of Economic and Statistics, 52(2), 169-210. Joof, F., & Jallow, O. (2020). The impact of interest rate and inflation on the exchange rate of the Gambia. International Journal of Economics, Commerce and Management, 8(1), 340-348. Karim, M. S. (2019). An empirical evaluation of monetary and f fiscal effects in Bangladesh. ADB South Asia Working Paper Series, No. 66, August 2019, Asian Development Bank, 1-40. Khan, M. K., Teng, J.-Z., & Khan, M. I. (2019). Cointegration between macroeconomic factors and the exchange rate USD/CNY. Financial Innovation, 5(1), 1-15.Available at: https://doi.org/10.1186/s40854-018-0117-x. Kui SI, D., Xiao-Lin, L., Chang, T., & Lu, B. (2018). Co-movement and causality between nominal exchange rates and interest rate differentials in BRICS countries: A wavelet analysis. ESPERA, 21(1), 5-19. Mgammal, M. H. H. (2012). The effect of inflation, interest rates and exchange rates on stock prices comparative study among two GCC countries. International Journal of Finance and Accounting, 1(6), 179-189. Murshed, M. (2018). An empirical assessment of the nexus between terms of trade and inflation in Bangladesh. The Bangladesh Development Studies, 41(1), 89-105. Ogege, S. (2019). Analysis of the impact of inflation, interest eate and exchange rate on economic development. International Journal of Commerce and Finance, 5(1), 121-132. Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326.Available at: https://doi.org/10.1002/jae.616. Saraç, T. B., & Karagöz, K. (2016). Impact of short-term interest rate on exchange rate: The case of Turkey. Procedia Economics and Finance, 38, 195-202.Available at: https://doi.org/10.1016/s2212-5671(16)30190-3. Sean, M., Pastpipatkul, P., & Boonyakunakorn, P. (2019). Money supply, inflation and exchange rate movement: the case of Cambodia by Bayesian VAR approach. Journal of Management, Economics, and Industrial Organization, 3(1), 63-81.Available at: https://doi.org/10.31039/jomeino.2019.3.1.5. Shodipe, T. (2018). The impact of real interest rate on real exchange rate: Evidence from Japan, 2018 Awards for Excellence in Student Research and Creative Activity – Documents. 5. Retrieved from: https://thekeep.eiu.edu/lib_awards_2018_docs/5. Yung, J. (2017). Can interest rate factors explain exchange rate fluctuations? Globalization and Monetary Policy Institute, Federal Reserve Bank of Dallas, Working Paper No. 207, 1-37. Asian Online Journal Publishing Group is not responsible or answerable for any loss, damage or liability, etc. caused in relation to/arising out of the use of the content. Any queries should be directed to the corresponding author of the article.