Time-Varying Smooth Transition Autoregressive Models
研究时变平滑转换自回归模型，用于同时描述非线性和结构变化，并开发两种建模策略，通过蒙特卡洛模拟和美国宏观经济数据比较其优劣。
AbstractNonlinear regime-switching behavior and structural change are often perceived as competing alternatives to linearity. In this article we study the so-called time-varying smooth transition autoregressive (TV-STAR) model, which can be used both for describing simultaneous nonlinearity and structural change and for distinguishing between these features. Two modeling strategies for empirical specification of TV-STAR models are developed. Monte Carlo simulations show that neither of the two strategies dominates the other. A specific-to-general-to-specific procedure is best suited for obtaining a first impression of the importance of nonlinearity and/or structural change for a particular time series. A specific-to-general procedure is most useful in careful specification of a model with nonlinear and/or time-varying properties. An empirical application to a large dataset of U.S. macroeconomic time series illustrates the relative merits of both modeling strategies.KEY WORDS: NonlinearityStructural changeTime series model specification