Global Journal of Management and Business Research, C: Finance, Volume 19 Issue 6

and Hansen (1990). The preconditions for FMOLS test is the variables should be stationary at first difference and having no co-integrated relationship between variables. LREMIT -0.168211 0.075180 -2.237438 0.0340 LGDPG 0.019098 0.086303 0.221294 0.8266 LINTTRADE 0.254514 0.146977 1.731663 0.0952 C 4.161396 0.328534 12.66657 0.0000 R-squared 0.091675 Mean dependent var 4.768487 Adjusted R-squared -0.013131 S.D. dependent var 0.120696 S.E. of regression 0.121486 Sum squared resid 0.383730 Long-run variance 0.005928 R-squared value indicates about 9.17 % of real effective exchange rate volatility is due to the volatility of independent variable. The strong significant relations is hold when the R-squared value is greater than 60 %. Our calculated value is less than the standard. But we should also think that we used three independent variables excluding all other variables affect the real effective exchange rate. So, we cannot underestimate the result because other 80% of the variation of real effective exchange rate as a results of the other variables such as inflation, interest rate, FDI, monetary and fiscal policy and so on. The t-statistics shows that the remittance have negative effect on real effective exchange rate, as my description in introduction part but other two variables (GDP growth and International trade) have positive effect. VII. C onclusion Our purpose was to investigate the factors affect real effective exchange rate. We used factors that affect real effective exchange rate fluctuations for the 1987-2017 period in Bangladesh. The use of statistical software helps us to show relationship among the dependent and independent variables and significance with one another.ADF and PP test statistics ensured us to go for further analysis. Correlogram test helps us to certify that the variables are non-stationary at level and stationary at 1 st difference. Q-statistics, LM and Heteroscedasticity shows that there is no serial correlations among variables. After fulfilling these conditions we went for analysis to test whether there is any long run relationship or short run relationship with real effective exchange rate. Johansen co-integration test result shows that there is no long run co-integrating relationship at 5% significance level according to trace maximum eigenvalue test. The short run relationship specifies us to use VAR model to determine how much lagged independent variables affect the dependent variables. The VAR model ensued us that there is a combined effect on dependent variables because their adjusted R- squared value is statistically significant. OLS test helps us to detect the variables significantly affect the dependent variable. We saw that real effective exchange rate has its own significance having a constant growth over the years and other independent variables affect it such as international trade, remittance. The joint effect is tested by the Wald test where we saw that “Remittance and international trade, Remittance and GDP growth” have combined effect on real effective exchange rate volatility. Ganger causality test statistics indicates LREMIT (Remittances received) and LINTTRADE (International trade) significantly affect the REER (real effective exchange rate) at 5% significant level. The FMOLS test now tell that the Remittance affects real effective exchange rate negatively. International trade (trade openness) and GDP growth have positive effect on real effective exchange rate volatility. The FMOLS test also certifies the result of correlation matrix having negative correlation with remittance and other two independent variables (GDP growth and International trade) have positive correlations with real effective exchange rate. © 2019 Global Journals 23 Global Journal of Management and Business Research Volume XIX Issue VI Version I Year 2019 ( ) C Factors Influencing Exchange Rate: An Empirical Evidence from Bangladesh R eferences R éférences R eferencias 1. Abbas, Q., Iqbal, J., & Ayaz, L. (2012). Relationship between GDP, inflation and real interest rate with exchange rate fluctuation of African countries. Variable Coefficient Std. Error t-Statistic Prob.

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