[R] Cointegration and ECM in Package {urca}

Pfaff, Bernhard Dr. Bernhard_Pfaff at fra.invesco.com
Tue Dec 16 09:32:51 CET 2008

>Dear R Core Team,
>I am using package {urca} to do cointegration and estimate ECM model,
>but I have the following two problems:
>(1)    I use ca.jo() to do cointegration first and can get the
>cointegration rank, alpha and beta.  The next step is to test some
>restrictions on beta with blrtest(),bh5lrtest(), and bh6lrtest().  But
>none of them can add restrictions on all the cointegration equations at
>the same time if have more than one cointegration rank.  For example,
>there are three cointegration in my case.  I want to add three 
>restrictions on them at the same time.  What can I do?

Dear Christine,

would you be so kind and give a more precise example of what you would
like to achieve? 
The examples in the above mentioned functions are replications of the
results in:

Johansen, S. and Juselius, K. (1990), Maximum Likelihood
     Estimation and Inference on Cointegration - with Applications to
     the Demand for Money, _Oxford Bulletin of Economics and
     Statistics_, *52, 2*, 169-210.

>(2)    What I want to do is to estimate ECM model with imposing
>restriction on beta or on both alpha and beta at the same time.  It
>looks like that command cajo.test() can do this estimation.  
>It shows up
>in the package but there is no example there.  I tried to find some
>examples but I cannot find any even if I have read  the book 
>Analysis of
>Integrated and Cointegrated Time Series with R.  Can you show me how to
>use this command or some examples? 

There is no function cajo.test() contained in the package urca. Have you
meant ablrtest() instead? If so, have a look at the example and the
above given reference as well as:

Johansen, S. (1991), Estimation and Hypothesis Testing of
     Cointegration Vectors in Gaussian Vector Autoregressive Models,
     _Econometrica_, *Vol. 59, No. 6*, 1551-1580.


>Thank you very much in advance.  Best wishes.
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>PLEASE do read the posting guide 
>and provide commented, minimal, self-contained, reproducible code.
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