Do real exchange rates really follow threshold autoregressive or exponential smooth transition autoregressive models
Do real exchange rates really follow threshold autoregressive or exponential smooth transition autoregressive models
复制标题
实际汇率是否真的遵循阈值自回归或指数平滑过渡自回归模型
DOI：
10.1016/j.econmod.2009.11.015
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Gawon Yoon
中科院分区：
文献类型：
--
作者：
Gawon Yoon
非线性模型，特别是门限自回归模型（TAR）和指数平滑过渡自回归模型（ESTAR），被广泛应用于真实的汇率模型，以检验购买力平价（PPP）的有效性。尽管非线性模型在理论上是合理的，但最近的一些研究结果使人怀疑它们与真实的汇率的相关性。特别是，非线性模型不一定比线性模型产生更好的样本外预测，并且在解决有据可查的购买力平价难题方面几乎没有增加价值。利用格兰杰等人（2004）提出的非参数熵测度，我们发现四个主要国家的真实的汇率具有很强的非线性序列相关性，而线性自回归模型无法复制。此外，非线性TAR和ESTAR模型估计的真实的汇率也有一些困难，产生显着的序列相关结构，实际观察到的数据。总体而言，其他非线性模型比目前受理TAR和ESTAR应考虑研究动态的真实的汇率。
Nonlinear models, especially threshold autoregressive [TAR] and exponential smooth transition autoregressive [ESTAR] classes, are widely applied for modeling real exchange rates in order to examine the validity of purchasing power parity [PPP]. Even though the nonlinear models are theoretically well-motivated, some of the recent findings cast doubts on their relevance for real exchange rates. In particular, the nonlinear models do not necessarily yield improved out-of-sample forecasts over linear models and add little value in resolving the well-documented PPP puzzle. Utilizing a nonparametric entropy measure of dependence proposed by Granger et al. (2004), we show, in this study, that the real exchange rates from four major countries had exhibited quite strong nonlinear serial dependence, which linear autoregressive models fail to replicate. Furthermore, the nonlinear TAR and ESTAR models estimated for the real exchange rates also have some difficulty in generating significant serial dependence structure actually observed in the data. Overall, other nonlinear models than the currently entertained TAR and ESTAR should be considered to study the dynamics of the real exchange rates.
使用三态 TAR 模型测试单位根：功效比较和一些应用
DOI：
--
发表时间：
2007
期刊：
Econometric Reviews (in press)(未定)
影响因子：
--
作者：
Takimoto;T.;Daiki Maki;Daiki Maki;Daiki Maki
通讯作者：
Daiki Maki