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A new nonlinear asymmetric cointegration approach using error correction models

机译:一种新的使用误差校正模型的非线性非对称协整方法

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In this article, two new powerful tests for cointegration are proposed. The general idea is based on an intuitively appealing extension of the traditional, rather restrictive cointegration concept. In this article, we allow for a nonlinear, but most importantly a different, asymmetric convergence process to account for negative and positive changes in our cointegration approach. Using Monte Carlo simulations we verify, that the estimated size of the first test depends on the unknown value of a signal-to-noise ratio q. However, our second testwhich is based on the original ideas of Kanioura and Turneris more successful and robust in the sense that it works in all of the different evaluated situations. Furthermore it is shown to be more powerful than the traditional residual based Enders and Siklos method. The new optimal test is also applied in an empirical example in order to test for potential nonlinear asymmetric price transmission effects on the Swedish power market. We find that there is a higher propensity for power retailers to rapidly and systematically increase their retail electricity prices subsequent to increases in Nordpool's wholesale prices, than there is for them to reduce their prices subsequent to a drop in wholesale spot prices.
机译:在本文中,提出了两个新的强大的协整测试。总的思想是基于对传统的,限制性的协整概念的直观吸引人的扩展。在本文中,我们允许采用非线性方法,但最重要的是采用不同的非对称收敛过程,以解决我们的协整方法中的负面和正面变化。使用蒙特卡洛模拟,我们验证了第一次测试的估计大小取决于信噪比q的未知值。但是,我们的第二项测试基于Kanioura和Turneris的原始思想,在可以在所有不同的评估情况下都有效的意义上,更加成功和强大。此外,它显示出比传统的基于残差的Enders和Siklos方法更强大。新的最佳检验还用于一个经验示例,以检验对瑞典电力市场的潜在非线性非对称价格传导效应。我们发现,电力零售商在诺德普尔批发价格上涨之后迅速而系统地提高其零售电价的可能性高于在批发现货价格下降之后降低其价格的倾向。

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