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# st: Interpreting VEC output

 From Talal To statalist@hsphsun2.harvard.edu Subject st: Interpreting VEC output Date Tue, 21 Sep 2010 15:35:03 -0700 (PDT)

```Hi,

I have tested for a cointegrating relationship and one exists, so I've estimated a VECM with four variables [ ln_qt , ln_VKM , lnincome , Lnf ]. There are enough observations. I'm just wondering how exactly to rewrite the STATA output into equations, in particular the first equation as it is the modelling of demand (Ln_qt) that I am most interested in.

So what I want to know is: how do I rewrite the output (see below please) and what is the best approach in interpreting the results for demand (Ln_qt) modelling?

Thank you.

. vec  ln_qt lnvkm lnincome lnf,

Vector error-correction model

Sample:  1981 - 2008                               No. of obs      =	28
AIC             =	-17.34228
Log likelihood =   253.792                         HQIC            =	-17.18228
Det(Sigma_ml)  =  1.57e-13                         SBIC            =	-16.81892

Equation           Parms      RMSE     R-sq      chi2     P>chi2

D_ln_qt               2     .037116   0.2983   11.05193   0.0040
D_lnvkm               2     .031551   0.1127   3.303018   0.1918
D_lnincome            2     .014566   0.7176   66.06712   0.0000
D_lnf                 2     .050123   0.3709   15.32712   0.0005

Coef.   Std. Err.      z    P>z     [95% Conf.	Interval]

D_ln_qt
_ce1
L1.   -.0866026    .241569    -0.36   0.720    -.5600691	.3868639

_cons   -.0244341  .007835    -3.12   0.002    -.0397905	-.0090777

D_lnvkm
_ce1
L1.   -.3730333   .2053474    -1.82   0.069    -.7755069	.0294403

_cons   -.0050647   .0066602    -0.76   0.447    -.0181185	.0079892

D_lnincome
_ce1
L1.   -.2016308   .0948057    -2.13   0.033    -.3874465	-.015815

_cons    .0186817   .0030749     6.08   0.000      .012655	.0247085

D_lnf
_ce1
L1.   -1.140481   .3262244    -3.50   0.000    -1.779869	-.5010932

_cons    .0002092   .0105808     0.02   0.984    -.0205287	.0209471

Cointegrating equations

Equation           Parms    chi2     P>chi2

_ce1                  3   4320.164   0.0000

Identification:  beta is exactly identified

Johansen normalization restriction imposed

beta       Coef.   Std. Err.      z    P>z     [95% Conf.	Interval]

_ce1
ln_qt       1          .        .       .            .	           .
lnvkm    .3143633   .0472589     6.65   0.000     .2217376	.406989
lnincome .3286365   .0542557     6.06   0.000     .2222974	.4349756
lnf    .7688382   .0583292    13.18   0.000     .6545151	.8831614
_cons   -8.684245      .        .       .            .	           .

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```