New research reveals key insights into forecasting non-stationary time series.
The article discusses three main topics: estimating models with I(2) variables, forecasting, and structural models with short-term behavior driven by expectations. The researchers found that the concept of order of integration and cointegration is not always exact in real-world data. Time series data from developed economies can show various behaviors, from stationary to requiring differencing to become stationary. Some series may even need multiple differencing, indicating they are of order I(2) or higher. The discussion in the chapter focuses on processes up to I(2).