Mixed Causal-Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing *

Modèles auto-régressifs non-causaux mixtes: Problèmes de bimodalité pour l'estimation et le test de racine unitaire

Frédérique Bec, Heino Bohn Nielsen () and Sarra Saïdi ()
Additional contact information
Heino Bohn Nielsen: Department of Economics [Copenhagen] - Faculty of Social Sciences [Copenhagen] - UCPH - University of Copenhagen = Københavns Universitet
Sarra Saïdi: THEMA - Théorie économique, modélisation et applications - UCP - Université de Cergy Pontoise - Université Paris-Seine - CNRS - Centre National de la Recherche Scientifique

Working Papers from HAL

Abstract: This paper stresses the bimodality of the widely used Student's t likelihood function applied in modelling Mixed causal-noncausal AutoRegressions (MAR). It first shows that a local maximum is very often to be found in addition to the global Maximum Likelihood Estimator (MLE), and that standard estimation algorithms could end up in this local maximum. It then shows that the issue becomes more salient as the causal root of the process approaches unity from below. The consequences are important as the local maximum estimated roots are typically interchanged , attributing the noncausal one to the causal component and vice-versa, which severely changes the interpretation of the results. The properties of unit root tests based on this Student's t MLE of the backward root are obviously affected as well. To circumvent this issues, this paper proposes an estimation strategy which i) increases noticeably the probability to end up in the global MLE and ii) retains the maximum relevant for the unit root test against a MAR stationary alternative. An application to Brent crude oil price illustrates the relevance of the proposed approach. Keywords: Mixed autoregression, non-causal autoregression, maximum likelihood estimation, unit root test, Brent crude oil price.

Date: 2019-07-06
New Economics Papers: this item is included in nep-ecm, nep-ene and nep-ets
Note: View the original document on HAL open archive server: https://hal.science/hal-02175760
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://hal.science/hal-02175760/document (application/pdf)

Related works:
Journal Article: Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing (2020)
Working Paper: Mixed Causal-Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing (2019)
Working Paper: Mixed Causal-Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:wpaper:hal-02175760

Access Statistics for this paper

More papers in Working Papers from HAL
Bibliographic data for series maintained by CCSD ().