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From |
Charles Koss <[email protected]> |

To |
[email protected] |

Subject |
Re: st: F test on VECM |

Date |
Fri, 8 Apr 2011 06:21:27 -0500 |

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 <[email protected]> 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: [email protected] [mailto:[email protected]] On Behalf Of DE SOUZA Eric > Sent: 08 April 2011 10:15 > To: [email protected] > 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: [email protected] [mailto:[email protected]] On Behalf Of Nat Tharnpanich > Sent: 07 April 2011 23:08 > To: [email protected] > 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 > [email protected] > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: st: F test on VECM***From:*DE SOUZA Eric <[email protected]>

**Re: st: F test on VECM***From:*Nat Tharnpanich <[email protected]>

**Re: st: F test on VECM***From:*Nick Cox <[email protected]>

**References**:**st: rolling regression and hypothesis testing***From:*Nat Tharnpanich <[email protected]>

**st: RE: rolling regression and hypothesis testing***From:*Nick Cox <[email protected]>

**Re: st: RE: rolling regression and hypothesis testing***From:*Nat Tharnpanich <[email protected]>

**st: F test on VECM***From:*Nat Tharnpanich <[email protected]>

**Re: st: F test on VECM***From:*Charles Koss <[email protected]>

**Re: st: F test on VECM***From:*Nat Tharnpanich <[email protected]>

**RE: st: F test on VECM***From:*DE SOUZA Eric <[email protected]>

**RE: st: F test on VECM***From:*DE SOUZA Eric <[email protected]>

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