Time Series Analysis of Exchange Rate Fluctuations and Their Effect on Import Prices in Nigeria

Exchange rate volatility in Nigeria has profound implications for import-dependent businesses and consumer prices, making time series modelling of exchange rate behaviour an important practical data science application. This study analysed monthly naira-to-dollar exchange rate data and corresponding import price index values published by the Central Bank of Nigeria for the period January 2015 to December 2022. Time series decomposition, autocorrelation function analysis, and ARIMA modelling were applied to examine exchange rate trends, seasonality, and forecasting accuracy. The ARIMA(1,1,1) model produced the best fit according to the Akaike Information Criterion, achieving a mean absolute percentage error of 3.7 percent on a held-out test set. Strong positive serial correlation was identified at lags of three and six months, suggesting inertia in exchange rate adjustment. Granger causality tests confirmed that exchange rate changes significantly preceded import price changes by two to three months. A one percent depreciation of the naira was associated with a 0.62 percent increase in the composite import price index within a quarter. The 2016 and 2020 policy devaluation episodes were clearly identified as structural breaks requiring intervention model components. The study concludes that exchange rate movements are a leading indicator of import price inflation in Nigeria. Policymakers are advised to use exchange rate projections to anticipate inflationary pressures, while businesses should adopt forward contracts based on ARIMA forecasts to hedge import costs effectively.

Keywords: time series analysis, exchange rate, import prices, ARIMA, Nigeria