| الملخص: | When breaks occur, equilibrium-correction models (EqCMs) based on cointegration face forecasting problems. We investigate approaches to alleviate forecast failure following a location shift, including updating, intercept corrections, differencing, and estimating the future impact of an 'internal' break during its progress. Although updating can lead to a loss of cointegration when an EqCM suffers an equilibrium-mean shift, we show that updating can help when collinearities are changed by an 'external' break and the EqCM itself remains constant. Both mechanistic corrections help compared to just retaining a pre-break estimated model, but an estimated model of the break process could outperform. Throughout, we apply the approaches to the much-studied example of EqCMs for UK M1, and compare with updating a learning function as the break evolves.
|
|---|