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MARKOV SWITCHING CAUSALITY AND THE MONEY-OUTPUT RELATIONSHIP

机译:马尔科夫开关因果关系和货币输出关系

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摘要

The causal link between monetary variables and output is one of the most studied issues in macroeconomics. One puzzle from this literature is that the results of causality tests appear to be sensitive with respect to the sample period that one considers. As a way of overcoming this difficulty, we propose a method for analysing Granger causality which is based on a vector autoregressive model with time-varying parameters. We model parameter time-variation so as to reflect changes in Granger causality, and assume that these changes are stochastic and governed by an unobservable Markov chain. When applied to US data, our methodology allows us to reconcile previous puzzling differences in the outcome of conventional tests for money-output causality.
机译:货币变量与产出之间的因果关系是宏观经济学中研究最多的问题之一。该文献的一个困惑是,因果关系检验的结果似乎对一个人所考虑的采样周期很敏感。为了克服这一困难,我们提出了一种基于带有时变参数的矢量自回归模型的格兰杰因果关系分析方法。我们对参数时变建模以反映格兰杰因果关系的变化,并假定这些变化是随机的并且受不可观察的马尔可夫链控制。当应用于美国数据时,我们的方法使我们能够调和以前对于货币产出因果关系的常规检验结果中令人费解的差异。

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