Submodel estimation of a structural vector error correction model under cointegration

William C. Horrace

doi:10.1016/s0165-1765(98)00033-0

Submodel estimation of a structural vector error correction model under cointegration

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper we derive the concentrated likelihood function of a mutually independent subsystem (submodel) of equations from a p-dimensional vector error component model under cointegration. The structural estimates of the subsystem parameters are identified by exclusion restrictions. The maximum likelihood estimates may be useful for counterfactual policy analysis.

Original language	English (US)
Pages (from-to)	23-29
Number of pages	7
Journal	Economics Letters
Volume	59
Issue number	1
DOIs	https://doi.org/10.1016/s0165-1765(98)00033-0
State	Published - Apr 1 1998
Externally published	Yes

Keywords

C32
Cointegration
Counterfactual policy analysis
Limited information maximum likelihood
Vector error correction model

ASJC Scopus subject areas

Finance
Economics and Econometrics

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10.1016/s0165-1765(98)00033-0

Cite this

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abstract = "In this paper we derive the concentrated likelihood function of a mutually independent subsystem (submodel) of equations from a p-dimensional vector error component model under cointegration. The structural estimates of the subsystem parameters are identified by exclusion restrictions. The maximum likelihood estimates may be useful for counterfactual policy analysis.",

keywords = "C32, Cointegration, Counterfactual policy analysis, Limited information maximum likelihood, Vector error correction model",

author = "Horrace, {William C.}",

note = "Funding Information: I would like to thank Peter Schmidt and Robert Rasche for comments on an earlier version of the paper. Portions of this research were supported by the National Science Foundation and the Ford Foundation. ",

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PY - 1998/4/1

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N2 - In this paper we derive the concentrated likelihood function of a mutually independent subsystem (submodel) of equations from a p-dimensional vector error component model under cointegration. The structural estimates of the subsystem parameters are identified by exclusion restrictions. The maximum likelihood estimates may be useful for counterfactual policy analysis.

AB - In this paper we derive the concentrated likelihood function of a mutually independent subsystem (submodel) of equations from a p-dimensional vector error component model under cointegration. The structural estimates of the subsystem parameters are identified by exclusion restrictions. The maximum likelihood estimates may be useful for counterfactual policy analysis.

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KW - Cointegration

KW - Counterfactual policy analysis

KW - Limited information maximum likelihood

KW - Vector error correction model

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ER -

Submodel estimation of a structural vector error correction model under cointegration

Abstract

Keywords

ASJC Scopus subject areas

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