Hi all,

I just ran a VEC with 2 endogenous and 5 exogenous variables. Now I wonder how I should interpret the numbers for my exogenous variables (not the standard error or t-statistics)? What does the minus sign stand for? How big should the number be to be considered significant? Below are the results. Thank you in advance!

Vector Error Correction Estimates

Date: 06/03/09 Time: 10:27

Sample (adjusted): 1994 2007

Included observations: 14 after adjustments

Standard errors in ( ) & t-statistics in [ ]

Cointegrating Eq: CointEq1

GDPGROWTH(-1) 1.000000

DEXPGDP(-1) -1.682983

(0.22172)

[-7.59050]

C 0.174989

Error Correction: D(GDPGROWTH) D(DEXPGDP)

CointEq1 0.197145 1.053958

(0.28769) (0.19525)

[ 0.68526] [ 5.39793]

C -0.097634 0.160050

(0.39213) (0.26613)

[-0.24899] [ 0.60140]

EXRATE 0.006276 -0.005289

(0.00584) (0.00396)

[ 1.07489] [-1.33461]

HDI 0.302065 -0.085976

(0.56237) (0.38167)

[ 0.53713] [-0.22526]

INFLATION 0.084941 0.671529

(0.45613) (0.30957)

[ 0.18622] [ 2.16925]

INVESTMENTS -0.640612 -0.635130

(0.29657) (0.20128)

[-2.16008] [-3.15552]

SAVINGS 0.088283 0.185195

(0.08645) (0.05867)

[ 1.02122] [ 3.15649]

R-squared 0.536183 0.828988

Adj. R-squared 0.138626 0.682406

Sum sq. resids 0.002865 0.001320

S.E. equation 0.020230 0.013730

F-statistic 1.348696 5.655452

Log likelihood 39.59491 45.02132

Akaike AIC -4.656416 -5.431618

Schwarz SC -4.336887 -5.112089

Mean dependent 0.003207 -0.000614

S.D. dependent 0.021798 0.024363

Determinant resid covariance (dof adj.) 4.01E-08

Determinant resid covariance 1.00E-08

Log likelihood 89.20401

Akaike information criterion -10.45772

Schwarz criterion -9.727364

## Help with interpreting VEC results

**Moderators:** EViews Gareth, EViews Moderator

### Re: Help with interpreting VEC results

You have to consider "standard error or t-statistics" if you are really interested in the significance. Assuming that you have basic knowledge on VEC models, the following link might be helpful: viewtopic.php?f=18&t=855. Moreover, your sample is too small compared to size of your model.

### Re: Help with interpreting VEC results

Dear Jopo,

What trubador said is true. Your estimation sample size is small and not suitable for cases of 2 endogenous and 5 exogenous variables. Regarding the interpretation of exogenous variables, it is similar to the interpretation of normal regression result, but we only emphasise that this is the short run relationship. “How big should the number to be considered significant?” This is depends on the significant level you choose, you should refer to the student t-table Critical values to make a decision.

Thank you,

Regards,

CF Tang

What trubador said is true. Your estimation sample size is small and not suitable for cases of 2 endogenous and 5 exogenous variables. Regarding the interpretation of exogenous variables, it is similar to the interpretation of normal regression result, but we only emphasise that this is the short run relationship. “How big should the number to be considered significant?” This is depends on the significant level you choose, you should refer to the student t-table Critical values to make a decision.

Thank you,

Regards,

CF Tang

### Re: Help with interpreting VEC results

trubador wrote:You have to consider "standard error or t-statistics" if you are really interested in the significance. Assuming that you have basic knowledge on VEC models, the following link might be helpful: viewtopic.php?f=18&t=855. Moreover, your sample is too small compared to size of your model.

hi trubador - if the t stat is less than the standard error does this imply the coeeficent in the VEC is significant or insignificant?

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