Mixed Causal-Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing
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- Frédérique Bec & Heino Bohn Nielsen & Sarra Saïdi, 2020. "Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1413-1428, December.
- Frédérique Bec & Heino Bohn Nielsen & Sarra Saïdi, 2019. "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 r," Working Papers hal-02175760, HAL.
- Frédérique BEC & Heino BOHN NIELSEN & Sarra SAÏDI, 2019. "Mixed Causal-Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing," Working Papers 2019-09, Center for Research in Economics and Statistics.
References listed on IDEAS
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Cited by:
- Alain Hecq & Elisa Voisin, 2019. "Predicting bubble bursts in oil prices during the COVID-19 pandemic with mixed causal-noncausal models," Papers 1911.10916, arXiv.org, revised Mar 2021.
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More about this item
Keywords
Mixed autoregression; non-causal autoregression; maximum likelihood estimation; unit root test; Brent crude oil price.;All these keywords.
JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ENE-2019-09-16 (Energy Economics)
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