The effect of parameter uncertainty on forecast variances and confidence intervals for unit root and trend stationary time‐series models
研究了参数不确定性如何影响单位根和趋势平稳时间序列模型的预测方差随预测期增长的方式，发现参数不确定性使两种模型的预测方差均以预测期的平方增长，远快于无参数不确定性时的线性或有界增长。
Abstract In this paper I describe the effect of parameter uncertainty on the way conditional forecast variances grow as the forecast horizon increases. Without parameter uncertainty, forecast variances for the unit root model grow linearly with the forecast horizon while with the trend stationary model they are bounded. With parameter uncertainty, however, I find that for both the unit root and the trend stationary models, forecast variances grow with the square of the forecast horizon so that uncertainty grows at a much faster rate than without parameter uncertainty.