Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing1
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Mixed Causal–Noncausal Autoregressions : Bimodality Issues in Estimation and Unit Root Testing1. / Bec, Frédérique; Nielsen, Heino Bohn; Saïdi, Sarra.
I: Oxford Bulletin of Economics and Statistics, Bind 82, Nr. 6, 12.2021, s. 1413-1428.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Mixed Causal–Noncausal Autoregressions
T2 - Bimodality Issues in Estimation and Unit Root Testing1
AU - Bec, Frédérique
AU - Nielsen, Heino Bohn
AU - Saïdi, Sarra
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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.
U2 - 10.1111/obes.12372
DO - 10.1111/obes.12372
M3 - Journal article
AN - SCOPUS:85087726684
VL - 82
SP - 1413
EP - 1428
JO - Oxford Bulletin of Economics and Statistics
JF - Oxford Bulletin of Economics and Statistics
SN - 0305-9049
IS - 6
ER -
ID: 255049744