Comparative Analysis of Stochastics Approaches in Forecasting Nigeria’s Key Macroeconomic Indicators
Dariyem Naandi Kruslat *
National Institute for Policy and Strategic Studies, Kuru, Nigeria and Department of Statistics, Nasarawa State University, Keffi, Nigeria.
Waheed B. Yahya
Department of Statistics, University of Ilorin, Kwara State, Nigeria.
Msugh Moses Kembe
Department of Mathematics and Computer Science, Benue State University, Makurdi, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
The Nigerian economy faces significant volatility in key macroeconomic variables, posing challenges to economic stability and growth. This study compares the performance of ARIMA, GARCH, and VAR models in forecasting GDP, exchange rates, interest rates, inflation, and unemployment, using annual data from 1981-2023. Results show that while ARIMA and GARCH models capture certain dynamics, the VAR model consistently delivers the highest forecast accuracy across all variables. These findings offer valuable insights for policymakers seeking data-driven strategies to stabilize the economy and manage macroeconomic uncertainty.
Keywords: Stochastic modeling, vector autoregression (VAR), generalized autoregressive conditional heteroskedasticity (GARCH), autoregressive integrated moving average (ARIMA)