RE: st: F test on VECM

[DE SOUZA Eric <eric.de_souza@coleurope.eu>]

There is a typo in your command: bconstrainsts instead of bconstraints

The error message I got is produced below. It is
 there are at least as many constraints as parameters

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Charles Koss
Sent: 08 April 2011 13:21
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: F test on VECM

I have run this code:

clear
webuse rdinc
constraint 1 [_ce1]ln_ne = -1
constraint 2 [_ce1]ln_se =  1
vec ln_ne ln_se, bconstrainsts(1/2)

and got error message too: option bconstrainsts() not allowed

Is this the error message that you are refering to?

Charles


--
Charles Koss
http://charlesonnet.blogspot.com

On Fri, Apr 8, 2011 at 3:45 AM, DE SOUZA Eric <eric.de_souza@coleurope.eu> wrote:
> I forgot to add that in the second case with three variables one can test the restrictions in question:
> constraint 1 [_ce1]ln_se = -1
> constraint 2 [_ce1]ln_ne = 1
> It is only in the first case with two variables that the eror message 
> occurs
>
> Eric
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of DE SOUZA 
> Eric
> Sent: 08 April 2011 10:15
> To: statalist@hsphsun2.harvard.edu
> Subject: RE: st: F test on VECM
>
> Normally the following should work (but it does not in this case, see below why):
> webuse rdinc
> vec ln_ne ln_se
> constraint 1 [_ce1]ln_se = -1
> constraint 2 [_ce1]ln_ne = 1
> vec ln_ne ln_se, bconstraints(1/2)
> vec ln_ne ln_se ln_sw
> vec ln_ne ln_se ln_sw, bconstraints(1 2)
>
> The errror message one gets is the following:
> there are at least as many constraints as parameters
>
> This is a weakness of the program: it should go ahead and estimate and produce the likelihood ratio test.
>
> Remember that without constraints, the beta coefficients are not identified. -vecrank- automatically imposes identification restrictions in order to able to estimate the model, what it calls the Johansen restrictions.
>
> If the restrictions you wish to test are not constraining, then the maximum value of the likelihood function will be the same for both models. In this case, you cannot test the restrictions.
>
> If the restrictions are constraining, you should always get a likelhood ratio test of the restrictions.
>
> The following is the output (edited for length) from PcGive 
> (OxMetrics) The last line gives you the likelihood ratio test. The 
> null is not rejected
>
> SYS( 2) Cointegrated VAR (using rdinc.xls)
>        The estimation sample is: 1950 - 2002
>
> Cointegrated VAR (2) in:
> [0] = ln_ne
> [1] = ln_se
> [2] = ln_sw
> Unrestricted variables:
> [0] = Constant
> Number of lags used in the analysis: 2
>
> beta
> ln_ne        1.0000
> ln_se      -0.98233
> ln_sw      0.037982
>
> alpha
> ln_ne      -0.44735
> ln_se      -0.36762
> ln_sw      -0.35322
>
> . . . .
>
> log-likelihood     465.501631  -
>
> beta is not identified
> No restrictions imposed
>
> SYS( 3) Cointegrated VAR (using rdinc.xls)
>        The estimation sample is: 1950 - 2002
>
> Cointegrated VAR (2) in:
> [0] = ln_ne
> [1] = ln_se
> [2] = ln_sw
> Unrestricted variables:
> [0] = Constant
> Number of lags used in the analysis: 2
>
> General cointegration restrictions:
> &3=1;
> &4=-1;
>
>
> beta
> ln_ne        1.0000
> ln_se       -1.0000
> ln_sw      0.056902
>
> . . .
>
> log-likelihood     465.500467
> no. long-run restrictions   1
> beta is identified
>
> LR test of restrictions: Chi^2(1) =0.0023272 [0.9615]
>
> In fact, this is a bad example because there is no cointegration, but 
> it suffices for the purpose here
>
> Eric de Souza
> College of Europe
> Brugge (Bruges), Belgium
> http://www.coleurope.eu
>
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nat 
> Tharnpanich
> Sent: 07 April 2011 23:08
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: F test on VECM
>
> Thanks so much Charles. However, I am afraid that this is not what I 
> wanted. I want to do the F test on the cointegrating vector itself. 
> For example, based on your online data, I want to test whether the 
> estimated coefficient of ln_se which takes a value of -0.94 when ln_ne 
> is constrained to be 1 is statistically different from, say, -1. Do 
> you happen to know how to do that? Nat
>
> On Apr 7 2011, Charles Koss wrote:
>
>>you may try this:
>>
>>clear
>>webuse rdinc
>>vec ln_ne ln_se
>>test [D_ln_se]L._ce1 == 0
>>
>>test [reference to the equation name ].{reference to the parameter} ==
>>0
>>
>>did it work?
>>
>>Charles
>>
>>
>
> --
> Nat Tharnpanich
> Downing College and Department of Land Economy University of Cambridge
> CB2 1DQ
> nt289@cam.ac.uk
>
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