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非线性平滑转换误差修正模型中的协整检验AI 解读

This paper proposes a new testing procedure to detect the presence of a cointegrating relationship that follows a globally stationary smooth transition process. In the context of nonlinear smooth transition error correction models (ECMs) we provide two simple operational versions of the tests. First, we obtain the associated nonlinear ECM-based tests. Second, we derive the nonlinear analogue of the residual-based test for cointegration in linear models. We derive the…

异质面板平稳性的均值组检验AI 解读

This paper proposes a panel-based mean group test for the null of stationarity against the alternative of unit roots in the presence of both heterogeneity across cross-section units and serial correlation across time periods. Using both sequential and joint asymptotic analyses the proposed test statistic is shown to be distributed as standard normal under the null for large N (number of groups) and large T (number of time periods). Monte Carlo results support the use of…

非线性 STAR 框架下的单位根检验AI 解读

In this paper, we propose a simple testing procedure to detect the presence of nonstationarity against nonlinear but globally stationary exponential smooth transition autoregressive processes. We provide an advance over the existing literature in three senses. First, we derive the limiting nonstandard distribution of the proposed tests. Second, we find via Monte Carlo simulation exercises that under the alternative of a globally stationary ESTAR process, our proposed test…

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