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Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing1

Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing1

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_crossref_primary_10_1111_obes_12372

Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing1

About this item

Full title

Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing1

Journal title

Oxford bulletin of economics and statistics, 2021-12, Vol.82 (6), p.1413-1428

Language

English

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Scope and Contents

Contents

This paper stresses the bimodality of the likelihood function of the Mixed causal–noncausal AutoRegressions (MAR), and it is shown that the bimodality issue becomes more salient as the causal root approaches unity from below. The consequences are important as the roots of the local maxima are typically interchanged, attributing the noncausal compon...

Alternative Titles

Full title

Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing1

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_crossref_primary_10_1111_obes_12372

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_crossref_primary_10_1111_obes_12372

Other Identifiers

ISSN

0305-9049

E-ISSN

1468-0084

DOI

10.1111/obes.12372

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