UNIT ROOT TEST IN A THRESHOLD AUTOREGRESSION: ASYMPTOTIC THEORY AND RESIDUAL-BASED BLOCK BOOTSTRAP
针对阈值自回归模型，提出了检验单位根原假设的方法，推导了非标准渐近分布，并用基于残差的块状自助法计算p值，蒙特卡洛模拟显示该方法比忽略阈值效应的ADF检验有更高的检验功效。
This paper develops a test of the unit root null hypothesis against a stationary threshold process. This testing problem is nonstandard and complicated because a parameter is unidentified and the process is nonstationary under the null hypothesis. We derive an asymptotic distribution for the test, which is not pivotal without simplifying assumptions. A residual-based block bootstrap is proposed to calculate the asymptotic p -values. The asymptotic validity of the bootstrap is established, and a set of Monte Carlo simulations demonstrates its finite-sample performance. In particular, the test exhibits considerable power gains over the augmented Dickey–Fuller (ADF) test, which neglects threshold effects.