Concerns about currency fluctuations are becoming increasingly prominent in both advanced and
emerging countries, including Ghana because they affect imports and exports directly.
The main aim of the study is to assess the impact of the Central Bank intervention on Exchange
rates in Ghana, using Société Générale Ghana as a case study.
This study used secondary data mainly drawn from the Bank of Ghana Data base. The study covers
a time period of 4 years (2014-2018) which captures period in which the Bank of Ghana initiated
new rules to augment and support the free fall of the cedi. To interpret and analyze the data in
relation to the variables under study, Descriptive Statistics, Unit root test such as the Augmented
Dicky Fuller Test was run. Models for the study were the Stock Watson (DOLS) test and the
Granger Causality test. Eviews10 was used in the data analysis.
The results indicate that the data was stationary using the Augmented Dickey Fuller test
The correlation analysis indicates that there exist a positive correlation between interbank rate and
Central Bank Intervention with a correlation coeffiecient of .073. A regression analysis was run to
establish the effect of the central bank intervention on the exchange rate. The coefficient of the
dependent variable at zero level of the explanatory variable was .073 indicating a positive
relationship exist between central bank intervention and the interbank exchange rate despite the
fact that the constant has no significant meaning in the model than reflecting the value of interbank
exchange rate when central bank intervention is held constant. The R2 which is the determinant of
the coefficient measures the proportion of the variance in the dependent variable that can be explained by the independent variable. The coefficient of 0.005 explains only 5 percent of the
variability of the dependent variable.
The F-ratio in the ANOVA table indicates whether the overall regression model is a good fit for
the data. The table indicates that the independent variables do not statistically justify the model to
be a good fit (1,58)=0.308, p>.005. The Null Hypothesis of the Granger Causality states that
Intervention does not Granger Cause Interbank rate. The rule of thumb indicates that the
probability of the F-statistics must be less than 5 percent to show causal relationship. The
probabilities of the causal variables of intervention was 0.712 and interbank rate was 0.111. per
the results obtained, the null hypothesis is rejected and a conclusion drawn that no relationship
exists between central bank intervention and the exchange rate. Conclusions were drawn based on
the findings and recommendations made for policy makers and future research directions.
SSA, R (2021). Impact Of Central Bank Intervention On Exchange Rates. Afribary.com: Retrieved April 15, 2021, from https://afribary.com/works/impact-of-central-bank-intervention-on-exchange-rates
Research, SSA. "Impact Of Central Bank Intervention On Exchange Rates" Afribary.com. Afribary.com, 08 Apr. 2021, https://afribary.com/works/impact-of-central-bank-intervention-on-exchange-rates . Accessed 15 Apr. 2021.
Research, SSA. "Impact Of Central Bank Intervention On Exchange Rates". Afribary.com, Afribary.com, 08 Apr. 2021. Web. 15 Apr. 2021. < https://afribary.com/works/impact-of-central-bank-intervention-on-exchange-rates >.
Research, SSA. "Impact Of Central Bank Intervention On Exchange Rates" Afribary.com (2021). Accessed April 15, 2021. https://afribary.com/works/impact-of-central-bank-intervention-on-exchange-rates