Forecasting Interest Rates in Pakistan's Economy Using the ARIMA Model: An Analytical Approach

This study employs the AutoRegressive Integrated Moving Average (ARIMA) model to forecast interest rates in Pakistan from 2004 to 2023. Using a time series dataset, the research investigates the dynamic relationships between interest rates and key macroeconomic variables. The ARIMA model is estimated. The optimal ARIMA model (p, d, q) is identified, and out-of-sample forecasts are generated. The results show the fluctuation between the years but after forecasted intrest rate the results show there is steadily increase in intrest rate over the next seven years . Starting from 2.86832% in 2024, the rate rises incrementally,reaching 2.98156% in 2025, 3.08603% in 2026, 3.18242% in 2027, 3.27136% in 2028, 3.35342% in 2029, and finally 3.42913% in 2030.This upward trend suggests a conservative and gradual tightening of monetary policy, potentially reflecting expectations of stable economic growth and inflation management. The Results also indicate that the ARIMA model accurately captures interest rate fluctuations, providing reliable predictions for policymakers and stakeholders, to exploring the dynamic relationships between interest rates, macroeconomic variables, and policy interventions.The analysis reveals significant correlations and optimal model specifications. Results provide valuable insights for policymakers, highlighting the need for coordinated monetary and fiscal strategies to promote economic growth and stability.The study contributes to the understanding of interest rate dynamics in Pakistan, offering valuable insights for monetary policy decisions and economic planning.