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

B-Tier
Journal: Oxford Bulletin of Economics and Statistics
Year: 2020
Volume: 82
Issue: 6
Pages: 1413-1428

Authors (3)

Frédérique Bec (Université de Cergy-Pontoise) Heino Bohn Nielsen (not in RePEc) Sarra Saïdi (not in RePEc)

Score contribution per author:

0.670 = (α=2.01 / 3 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

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 component to the causal one and vice‐versa. This severely changes the interpretation of the results, and the properties of unit root tests of the backward root are adversely affected. To circumvent the bimodality issue, this paper proposes an estimation strategy which (i) increases noticeably the probability of attaining the global MLE; and (ii) selects carefully the maximum used for the unit root test against a MAR stationary alternative.

Technical Details

RePEc Handle
repec:bla:obuest:v:82:y:2020:i:6:p:1413-1428
Journal Field
General
Author Count
3
Added to Database
2026-01-24