A comparison of the forecast performance of Markov‐switching and threshold autoregressive models of US GNP
比较了自激励门限自回归和马尔可夫转换自回归两种非线性模型在预测美国战后GNP时的表现，通过实证预测精度比较和蒙特卡洛研究两种方法进行分析。
While there has been a great deal of interest in the modelling of non-linearities in economic time series, there is no clear consensus regarding the forecasting abilities of non-linear time series models. We evaluate the performance of two leading non-linear models in forecasting post-war US GNP, the self-exciting threshold autoregressive model and the Markov-switching autoregressive model. Two methods of analysis are employed: an empirical forecast accuracy comparison of the two models, and a Monte Carlo study. The latter allows us to control for factors that may otherwise undermine the performance of the non-linear models. 1 Introduction In recent years there has been a great deal of interest in the modelling of non-linearities in economic time series. While the usefulness of linear time-series models in the tradition of Box and Jenkins (1970) is usually gauged by their predictive ability, there does not appear to be a clear consensus as to whether allowing for non-linearities has l...