The Nexus Between Debt Servicing and Foreign Exchange Rate Unification In Nigeria
Description
This study examined the relationship between debt servicing and foreign exchange rate unification in Nigeria from 1995 to 2023, hypothesizing that a unified exchange rate policy would significantly impact the country's debt service-to-revenue ratio. Using annual time series data from sources such as the International Monetary Fund and World Development Indicators, the study employed an Autoregressive Distributed Lag (ARDL) model to analyze the relationship between the debt service-to-revenue ratio and factors including the official foreign exchange rate, GDP growth rate, inflation rate, and oil prices. The findings revealed several notable insights. Exchange rate unification was found to have a significant negative effect on the debt service-to-revenue ratio, suggesting that a unified exchange rate policy could help reduce Nigeria's debt service burden. Both current and lagged inflation rates showed a significant negative impact on the debt service-to-revenue ratio, indicating that higher inflation might be eroding the real value of debt or increasing nominal revenues faster than debt servicing costs. Lagged exchange rates were found to negatively affect the debt service-to-revenue ratio, implying that higher exchange rates in the previous period decrease the current ratio. Oil prices demonstrated mixed effects, with current prices positively impacting the debt service-to-revenue ratio while lagged prices had a negative effect. The study also revealed strong persistence in debt servicing behavior over time, as evidenced by the significant positive correlation between current and previous year's debt service ratios. These results offer significant implications for policymakers. The negative effect of exchange rate unification on the debt service-to-revenue ratio suggests that such a policy could improve efficiency in forex markets and reduce arbitrage opportunities, ultimately helping to reduce the debt service burden. The negative relationship between inflation and the debt service-to-revenue ratio indicates that higher inflation might be beneficial for debt servicing in the short term, though this should be interpreted cautiously given the potential negative consequences of high inflation. The mixed impact of oil prices reflects the complexity of Nigeria's oil-dependent economy, highlighting the need for economic diversification. The strong persistence in debt servicing commitments points to potential structural issues in debt management or lack of fiscal flexibility. Policymakers can use these findings to inform strategies for managing Nigeria's debt burden. The results suggest that pursuing exchange rate unification, carefully managing inflation, diversifying the economy to reduce oil dependence, and improving fiscal discipline could all contribute to better management of debt servicing costs. However, it's crucial to consider the lagged effects of economic variables on debt servicing when formulating long-term fiscal strategies.
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The study's data collection and research methodology were designed to analyze the relationship between debt servicing and foreign exchange rate unification in Nigeria from 1995 to 2023. Annual time series data was gathered from reputable international sources. The International Monetary Fund provided data on total debt service as a percentage of GNI, which was used to calculate the Debt Service-to-Revenue Ratio. The World Development Indicators supplied information on the real effective exchange rate index, GDP growth rate, and inflation rate. Average annual crude oil prices were obtained from the U.S. Energy Information Administration. The research focused on several key variables. The Debt Service-to-Revenue Ratio (DSR) served as the dependent variable, while the independent variables included the Exchange Rate (EXR), GDP Growth Rate (GDPg), Inflation Rate (INF), and Oil Prices (OIL). A dummy variable for Exchange Rate Unification (EXR_UNI) was also introduced, set to 1 for years following 2016 and 0 otherwise, to capture the impact of policy changes. The methodology employed quantitative analysis techniques using econometric tools. The research process began with an Augmented Dickey-Fuller (ADF) unit root test to check for stationarity of the variables, conducted at both level and first difference. This was followed by an Engle-Granger co-integration test to examine long-term equilibrium relationships among the variables. Both these tests were performed using EViews 9.0 software. Based on the results of these preliminary tests, an Autoregressive Distributed Lag (ARDL) model was specified and estimated using first differences of the variables. The model included lagged values of certain variables (DSR, EXR, INF, OIL) to capture dynamic effects. The ARDL model estimation was also carried out using EViews 9.0 software. To ensure the validity of the results, several diagnostic tests were conducted. These included calculating R-squared and Adjusted R-squared to assess model fit, computing the F-statistic to test overall model significance, and using the Durbin-Watson statistic to check for autocorrelation. Also, the Breusch-Godfrey Serial Correlation LM Test was performed to further check for serial correlation, and the Breusch-Pagan-Godfrey test was conducted to check for heteroskedasticity. To reproduce this research, one would need to collect the same data from the specified sources for the period 1995-2023 and use econometric software (preferably EViews 9.0 for exact replication) to conduct the unit root tests, co-integration tests, and estimate the ARDL model. The same diagnostic tests would need to be performed to ensure the validity of the results. It's worth noting that access to the specific datasets used and the exact version of EViews software would be crucial for precise replication. Furthermore, any updates or revisions to historical data by the source organizations could potentially lead to slight variations in results.