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st: VECM model using vec command
From
Talal <[email protected]>
To
[email protected]
Subject
st: VECM model using vec command
Date
Sat, 25 Sep 2010 17:17:00 -0700 (PDT)
Hi all
For whom using vec model regularily
1. I am trying to estimate a VECM model for demand (ln_qt) as dependent variable; and (ln_VKM , lnincome , Lnf ] as three independent variables.
2- After testing the number of cointegrating relation using "vecrank"
the results shows that I have multiple cointegrating vectors (2).
3. the number of lags decided using VAR and lag length criteria before doing the cointegration test for my VECM model (Lag no.=3)
4- based on above
I belive my VECM model specification should be:
Δyt = λ1 + λ2 Δxt − γ1 (yt−1 − xt−1) + γ2 (yt−1 − xt−1)+ πxt−1 + ηt
where y is the dependent variable and X is a vector of Independent variables
I have used a "vec" comand as follws:
vec ln_qt ln_VKM lnincome Lnf , lag(3) rank (2)
My question are:
A- did I specified the VECM equation and vec command correctl?
B- the vec outputs is very confusing (it seems specified 4 models where each variable i have used was specified as dependend variable in one of the four models).
I am only intersted to estimate a demand (ln_qt) model.
Also the outputs in STATA are not well organised and I find it dificult to
interpret th paramaters. Any help in the interpretation will be appreciated.
Rgards
Talal
Vector error-correction model
Sample: 1983 - 2008 No. of obs = 26
AIC = -18.18355
Log likelihood = 284.3861 HQIC = -17.51471
Det(Sigma_ml) = 3.71e-15 SBIC = -15.86091
Equation Parms RMSE R-sq chi2 P>chi2
----------------------------------------------------------------
D_ln_qt 11 .031182 0.6703 28.46039 0.0028
D_lnvkm 11 .020371 0.7712 47.19024 0.0000
D_lnincome 11 .011182 0.9033 130.7283 0.0000
D_lnf 11 .039259 0.7739 47.90836 0.0000
----------------------------------------------------------------
------------------------------------------------------------------------------
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
D_ln_qt |
_ce1 |
L1. | .2503267 .7070148 0.35 0.723 -1.135397 1.63605
|
_ce2 |
L1. | -.0519306 .2854071 -0.18 0.856 -.6113183 .507457
|
ln_qt |
LD. | -.3892408 .5782202 -0.67 0.501 -1.522532 .74405
L2D. | -.210528 .3547468 -0.59 0.553 -.9058189 .484763
|
lnvkm |
LD. | .0952668 .3173674 0.30 0.764 -.526762 .7172955
L2D. | -.1789577 .3448023 -0.52 0.604 -.8547577 .4968424
|
lnincome |
LD. | 1.39124 .6996217 1.99 0.047 .0200066 2.762473
L2D. | .0910786 1.043868 0.09 0.930 -1.954865 2.137022
|
lnf |
LD. | -.4656339 .4380534 -1.06 0.288 -1.324203 .3929351
L2D. | -.1438649 .2447154 -0.59 0.557 -.6234983 .3357685
|
_cons | .0007162 .0172881 0.04 0.967 -.0331677 .0346002
-------------+----------------------------------------------------------------
D_lnvkm |
_ce1 |
L1. | -1.285009 .4618835 -2.78 0.005 -2.190284 -.3797342
|
_ce2 |
L1. | -.5471533 .1864527 -2.93 0.003 -.9125939 -.1817128
|
ln_qt |
LD. | .1844832 .3777436 0.49 0.625 -.5558807 .9248472
L2D. | .3597803 .2317514 1.55 0.121 -.0944441 .8140047
|
lnvkm |
LD. | .5725982 .207332 2.76 0.006 .166235 .9789614
L2D. | .2093582 .2252548 0.93 0.353 -.2321331 .6508495
|
lnincome |
LD. | .9908236 .4570537 2.17 0.030 .0950149 1.886632
L2D. | .0802654 .681945 0.12 0.906 -1.256322 1.416853
|
lnf |
LD. | .4226623 .2861745 1.48 0.140 -.1382295 .9835541
L2D. | .2055419 .1598694 1.29 0.199 -.1077963 .5188801
|
_cons | -.0008924 .0112941 -0.08 0.937 -.0230283 .0212436
-------------+----------------------------------------------------------------
D_lnincome |
_ce1 |
L1. | -.2725985 .2535389 -1.08 0.282 -.7695257 .2243286
|
_ce2 |
L1. | -.0681478 .1023484 -0.67 0.506 -.2687469 .1324513
|
ln_qt |
LD. | .2758531 .2073526 1.33 0.183 -.1305504 .6822567
L2D. | -.1959344 .1272139 -1.54 0.124 -.4452691 .0534003
|
lnvkm |
LD. | .0957609 .1138095 0.84 0.400 -.1273016 .3188234
L2D. | .0480082 .1236478 0.39 0.698 -.194337 .2903534
|
lnincome |
LD. | .0166749 .2508877 0.07 0.947 -.4750561 .5084058
L2D. | -.0643503 .374336 -0.17 0.864 -.7980354 .6693348
|
lnf |
LD. | .1221691 .1570881 0.78 0.437 -.1857179 .4300561
L2D. | -.0698057 .0877561 -0.80 0.426 -.2418046 .1021932
|
_cons | .0096477 .0061996 1.56 0.120 -.0025032 .0217987
-------------+----------------------------------------------------------------
D_lnf |
_ce1 |
L1. | -1.398677 .8901514 -1.57 0.116 -3.143341 .345988
|
_ce2 |
L1. | -.2213953 .3593355 -0.62 0.538 -.92568 .4828894
|
ln_qt |
LD. | .5618666 .7279954 0.77 0.440 -.8649782 1.988711
L2D. | .6363211 .4466361 1.42 0.154 -.2390697 1.511712
|
lnvkm |
LD. | .0969903 .3995745 0.24 0.808 -.6861613 .8801418
L2D. | -.2930602 .4341157 -0.68 0.500 -1.143911 .557791
|
lnincome |
LD. | -2.956396 .8808433 -3.36 0.001 -4.682817 -1.229975
L2D. | -1.461442 1.314259 -1.11 0.266 -4.037342 1.114458
|
lnf |
LD. | .813693 .5515215 1.48 0.140 -.2672694 1.894655
L2D. | .426378 .3081035 1.38 0.166 -.1774939 1.03025
|
_cons | -.0009323 .0217661 -0.04 0.966 -.0435931 .0417286
------------------------------------------------------------------------------
Cointegrating equations
Equation Parms chi2 P>chi2
-------------------------------------------
_ce1 2 414.1233 0.0000
_ce2 2 21.02513 0.0000
-------------------------------------------
Identification: beta is exactly identified
Johansen normalization restrictions imposed
------------------------------------------------------------------------------
beta | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_ce1 |
ln_qt | 1 . . . . .
lnvkm | 5.55e-17 . . . . .
lnincome | -.8126088 .2787991 -2.91 0.004 -1.359045 -.2661725
lnf | 2.232979 .3353644 6.66 0.000 1.575677 2.890281
_cons | 4.198856 . . . . .
-------------+----------------------------------------------------------------
_ce2 |
ln_qt | (omitted)
lnvkm | 1 . . . . .
lnincome | 3.087591 .7286725 4.24 0.000 1.659419 4.515763
lnf | -3.936948 .876512 -4.49 0.000 -5.65488 -2.219016
_cons | -35.40865 . . . . .
------------------------------------------------------------------------------
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