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Between cointegration and multicointegration: Modelling time series dynamics by cumulative error correction models

机译:在协整和多重协整之间:通过累积误差校正模型对时间序列动力学建模

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This study proposes a cumulative error correction model where the summing weights follow a geometrically decreasing function of prior deviations from the equilibrium and are estimated from the data. It is shown that this approach nests both the traditional error correction model - where no weight is given to deviations from the steady state prior to the most recent period - and the error correction model based on the idea of multicointegration. The form of accumulation presented here does not change the order of integration of the series, as is the case in the multicointegration approach of Granger and Lee (1989). Furthermore, it is very parsimonious as only one or two parameters more have to be estimated. The assumption of geometrically decreasing weights can be tested by estimating the model in its unrestricted form. Based on this new model type, the relationship between private consumption and real disposable income of private households in the US is estimated. The short-term forces which set off the most recent period's deviations are much smaller than would be suggested by a VEC and a conventional single equation ECM, and the income elasticity is lower as well. The proposed model outperforms the other two with respect to its forecasting power.
机译:这项研究提出了一个累积误差校正模型,其中总和权重遵循与平衡先验偏差的几何递减函数,并根据数据进行估算。结果表明,这种方法既嵌套了传统的纠错模型(基于最近的周期之前的稳态误差没有权重),也嵌套了基于多协整思想的纠错模型。这里展示的累积形式不会改变该系列的积分顺序,就像Granger和Lee(1989)的多重协积分方法一样。此外,这非常简单,因为仅需要估计一个或两个以上的参数。可以通过估计模型的无限制形式来检验权重几何递减的假设。基于这种新模型类型,可以估算美国私人消费与私人家庭实际可支配收入之间的关系。引起最近期偏差的短期力量要比VEC和传统的单方程ECM所建议的要小得多,收入弹性也较低。就其预测能力而言,所提出的模型优于其他两个模型。

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