Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/195479
Authors: 
Johansen, Søren
Tabor, Morten Nyboe
Year of Publication: 
2017
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 5 [Year:] 2017 [Issue:] 3 [Pages:] 1-46
Abstract: 
A state space model with an unobserved multivariate random walk and a linear observation equation is studied. The purpose is to find out when the extracted trend cointegrates with its estimator, in the sense that a linear combination is asymptotically stationary. It is found that this result holds for the linear combination of the trend that appears in the observation equation. If identifying restrictions are imposed on either the trend or its coefficients in the linear observation equation, it is shown that there is cointegration between the identified trend and its estimator, if and only if the estimators of the coefficients in the observation equations are consistent at a faster rate than the square root of sample size. The same results are found if the observations from the state space model are analysed using a cointegrated vector autoregressive model. The findings are illustrated by a small simulation study.
Subjects: 
cointegration of trends
state space models
cointegrated vector autoregressive models
JEL: 
C32
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

Files in This Item:
File
Size
283.52 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.