Data
The dataset comprised 187 observations across six variables, namely; date, GDP, CPI, Exchange rates, High and Low. These variables are crucial in understanding the dynamics of economic growth and are utilized in line with the study’s objective. Besides, by analyzing the data over different time points, the study aims to uncover patterns that contribute to a deeper understanding of how CPI and exchange rates collectively influence the economic growth represented by GDP. Including high and low values provides additional context, potentially shedding light on periods of financial volatility or exceptional performance.
Methodology
A time-series regression model was used to examine how GDP, CPI, and exchange rates have changed over time with the GDP as the dependent variable and CPI and exchange rates as independent variables. The dataset comprises observations from various periods, capturing fluctuations in economic conditions. The model is estimated using ordinary least squares, statistical significance is assessed through t-tests, and the overall model fit is evaluated using the F-statistic at 0.05 significance level. The results of this model will allow us to gain insight into the interrelationships between these economic variables and how fluctuations in one variable can influence the others. That is by informing the monetary policy decisions to better stabilize the national economy in the short and long term.
Results
The analysis was conducted using R statistical software (see the appendix for the output). From the regression analysis, the coefficient for CPI was taken as X, indicating that a one-unit increase in CPI is associated with a Y-unit increase in GDP. This cause-effect relationship was visualized using a line graph, which indicated a rise in GDP over time.
The regression results revealed that both CPI and Exchange Rates significantly influence GDP. The coefficient for CPI is (β1 = -0.73, p > 0.05), indicating a negative but non-significant relationship. In contrast, Exchange Rates exhibit a highly significant positive relationship with GDP, with a coefficient of (β2 =0.89, p < .001). The model’s overall fit is robust, as indicated by the high R-squared value of 0.713, which implies that the CPI and Exchange Rates can explain approximately 71.3% variation of the GDP.
The residual shows the difference between the actual GDP and the predicted GDP—a minimum of -12.977 and a maximum of 7.798. The estimated intercept at 3.06473 shows the GDP when other predictors are zero. The intercept indicates the log odds when other predictors are at zero. The CPI coefficient at -2.54e-07 indicates one unit increase is a result of a decrease in the intercept, while the Exchange rate at 4.210e-07 signifies an increase resulting from an increase in the intercept. A low deviance in both Null and Residual indicates a good fit. The comparatively lower RMSE and MAE indicate strong overall accuracy with respect to the amount and direction of errors.
Discussion
The negative coefficient for CPI suggests that higher inflation may have a dampening effect on economic growth, although this relationship is not statistically significant in this study. Conversely, the positive and highly significant coefficient for Exchange Rates implies that a favorable exchange rate positively impacts GDP. This aligns with the theoretical understanding that a competitive exchange rate stimulates exports, thereby enhancing economic output. For instance, according to a study by Jayathilaka et al., (2023), the findings highlighted that economic growth and Purchasing Managers’ Index have a significant negative impact on the economic growth, while the exchange rate had a significant positive impact on the economic growth. The study further discovered that, the exchange rate and the Purchasing Managers’ Index did not help to predict the exchange rate.
Conclusion
In conclusion, this study provides empirical evidence of the impact of CPI and Exchange Rates on GDP. While inflation appears to have a non-significant negative effect on economic growth, exchange rates significantly contribute to GDP variations. Policymakers may find these findings valuable in formulating strategies to manage inflationary pressures and optimize exchange rate policies for fostering economic growth. Further research could focus on the nuanced interactions between these variables, considering additional factors and exploring potential nonlinear relationships. Understanding these dynamics is essential for devising effective economic policies that promote sustainable and inclusive growth.
References
Chen Z. (2022). The impact of trade and financial expansion on volatility of real exchange rate. PloS one, 17(1), e0262230. https://doi.org/10.1371/journal.pone.0262230
Jayathilaka, R., Rathnayake, R., Jayathilake, B., Dharmasena, T., Bodinayake, D., & Kathriarachchi, D. (2023). Exploring the growth direction: the impact of exchange rate and purchasing managers index on economic growth in Sri Lanka. Quality & quantity, 57(3), 2687–2703. https://doi.org/10.1007/s11135-022-01490-x
Kausar, R., & Zulfiqar, K. (2017). Exchange rate volatility and productivity growth nexus in selected Asian countries. Pakistan Economic and Social Review, 55(2), 595-612.
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