ANALYZING STRUCTURAL BREAKS AND NONLINEAR VOLATILITY IN NIGERIAN QUASI-MONEY USING SMOOTH TRANSITION AUTOREGRESSIVE-GARCH MODELS

This study examines the behavior of Nigeria’s quasi-money, focusing on its nonlinear dynamics and volatility from January 1994 to December 2024. By utilizing nonlinear GARCH-type models, specifically the smooth transition autoregressive-GARCH models (LSTAR-GARCH and ESTAR-GARCH), the study indicates notable conditional heteroskedasticity, volatility clustering, and nonlinearity in the series of monetary aggregates. Diagnostic tests such as Chow and BDS highlight the existence of structural breaks and behavior dependent on different regimes, emphasizing the drawbacks of conventional linear models. Among the various models, the LSTAR-GARCH shows better statistical results and is more reactive to abrupt changes in economic or policy conditions. These results stress the essential role of using nonlinear and regime-switching volatility models to analyze quasi-money in developing countries, equipping policymakers with improved methods for forecasting and handling liquidity during structural shifts. The results indicate that those in charge of monetary policy should use nonlinear and regime-switching volatility models, especially the LSTAR-GARCH model, in their analysis to enhance effective prediction of the changes in Nigeria’s quasi-money. Moreover, it is advised to frequently check for structural breaks for timely policy updates. Financial analysts, too, should focus on models that can capture both nonlinearity and changing volatility to achieve better forecasts and a clearer understanding of monetary trends. Received: January 7, 2026Accepted: February 12, 2026