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A new nonlinear asymmetric cointegration approach using error correction models
Jönköping University, Jönköping International Business School, JIBS, Statistics.ORCID iD: 0000-0002-3416-5896
Jönköping University, Jönköping International Business School, JIBS, Statistics.ORCID iD: 0000-0003-3144-2218
Jönköping University, Jönköping International Business School, JIBS, Statistics.ORCID iD: 0000-0002-4535-3630
2017 (English)In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 46, no 2, p. 1661-1668Article in journal (Refereed) Published
Abstract [en]

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 test—which is based on the original ideas of Kanioura and Turner—is 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.

Place, publisher, year, edition, pages
Taylor & Francis, 2017. Vol. 46, no 2, p. 1661-1668
Keywords [en]
Cointegration, Error Correction Models, Monte Carlo Simulations, Nonlinear Asymmetric Price Transmissions, Nordpool
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:hj:diva-37800DOI: 10.1080/03610918.2014.999087ISI: 000395194600054Scopus ID: 2-s2.0-84994172746OAI: oai:DiVA.org:hj-37800DiVA, id: diva2:1153201
Available from: 2017-10-28 Created: 2017-10-28 Last updated: 2018-02-05Bibliographically approved

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Shukur, GhaziSjölander, PärMånsson, Kristofer

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