关键词: 平滑转移自回归模型, 非线性平稳性检验, 伪检验, 蒙特卡洛仿真

Abstract: This paper addresses whether stationary test including nonlinear ESTAR, LSTAR and linear DF methods can draw right conclusions when the chosen test statistics are inconsistent with DGP(data generating process) through theoretical analysis and Monte Carlo simulation. The results show that the second-order LSTAR can use the same test method as ESTAR model but it has stronger nonlinearity. When DGP is nonlinear ESTAR, second-order LSTAR or linear AR, DF or ESTAR method can generally achieve right results, but LSTAR fails completely. Stronger nonlinearity of DGP brings ESTAR higher power than DF, and stronger linearity brings DF higher power than ESTAR. When is big, leading to big approximation error of first-order Talyor Expansion or if is nonzero in transition function , the standard ESTAR and LSTAR will fail to satisfy the applicable conditions. If is big or is far from 0, DGP will have more linear components, therefore linear DF test can achieve better results.

Key words: Smooth Transition Autoregressive Model, Nonlinear Stationary Test, Spurious Test, Monte Carlo Simulations