2007
DOI: 10.1016/j.jeconom.2005.10.005
|View full text |Cite
|
Sign up to set email alerts
|

Marginal likelihood and unit roots

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
22
0

Year Published

2009
2009
2013
2013

Publication Types

Select...
7

Relationship

3
4

Authors

Journals

citations
Cited by 13 publications
(22 citation statements)
references
References 43 publications
0
22
0
Order By: Relevance
“…Small sample evidence for time‐series models is provided by Shephard (1993). The marginal likelihood is for a (transformed) random variable and therefore its score vector has expectation zero; see, for example, Shephard (1993), Rahman and King (1997) and Francke and de Vos (2007).…”
Section: Introductionmentioning
confidence: 99%
“…Small sample evidence for time‐series models is provided by Shephard (1993). The marginal likelihood is for a (transformed) random variable and therefore its score vector has expectation zero; see, for example, Shephard (1993), Rahman and King (1997) and Francke and de Vos (2007).…”
Section: Introductionmentioning
confidence: 99%
“…The marginal likelihood is well-defined for −1 < ρ ≤ 1 where the profile likelihood is zero when ρ = 1. Francke and de Vos (2007) show that unit root tests based on the marginal likelihood ratio outperform other well-known tests in the literature. This result holds specifically for small samples.…”
Section: Nonstationary Time Series Modelsmentioning
confidence: 87%
“…Among others, Cooper and Thompson (1977) and Tunnicliffe-Wilson (1989) argue that the marginal likelihood is superior to the profile likelihood for the inference of nuisance parameters collected in vector θ. The marginal likelihood is for a (transformed) random variable and therefore its score vector has expectation zero, see, for example, Shephard (1993), Rahman and King (1997) and Francke and de Vos (2007).…”
Section: Introductionmentioning
confidence: 99%
“…For a detailed discussion of the properties of the marginal likelihood and the likelihood of the 'differenced data' in the regression model with first order autoregressive disturbances, see Francke and De Vos (2007).…”
Section: Discussionmentioning
confidence: 99%