.png){kind=icon}
Return
EFFICIENT INFERENCE ON COINTEGRATION PARAMETERS IN STRUCTURAL ERROR-CORRECTION MODELS
.png){kind=icon}
OA
AI
DOI：10.1016/0304-4076(94)01665-M.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper proposes inferential procedures for error correction models in structural form. Particular attention is paid to the issues of exogeneity of conditioning variables and identification of cointegration parameters as well as short-run parameters. The model leads to two classes of estimators and associated test statistics, depending on the exogeneity status of the conditioning variables. A Monte Carlo experiment shows how their asymptotic properties are reflected in finite sample behaviour.
Keywords:
COINTEGRATION
ERROR CORRECTION MODELS
EXOGENEITY
IDENTIFICATION
STRUCTURAL MODELS
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4
Papers:
5.2K
Citations:
3.0W
Organization
No organization information available
Cited Papers
ShareSaveSOME EXACT DISTRIBUTION-THEORY FOR MAXIMUM-LIKELIHOOD ESTIMATORS OF COINTEGRATING COEFFICIENTS IN ERROR-CORRECTION MODELS.png)
ECONOMETRICA
ECONOMETRICAIF7.1
PREAI
ShareSaveShareSaveShareSaveResearch and Development of Rare Earth-Transition Metal Alloys as Permanent-Magnet Materials
IF0
PREAI
ShareSaveShareSaveTESTING STRUCTURAL HYPOTHESES IN A MULTIVARIATE COINTEGRATION ANALYSIS OF THE PPP AND THE UIP FOR UK
PREAI
ShareSave
View more