The article explores how using certain types of nonlinear models can improve forecasting accuracy. By studying models that account for sudden changes in relationships between variables, researchers found that correctly using these nonlinear models can lead to significant improvements in forecasting, especially when adjustments to long-term equilibrium are strong or when parameter changes are large.