Greetings. I want to report an issue I've discover when estimating a VECM model with trend option, looks like when estimating the trend, the serial correlation test and the normality test cannot be estimate.
I thought this would be a one time error, however i've tested it on 3 different time series data bases, and the conclusions is that after a VECM with trend, the commands of vecmarl and vecnorm, jbera cannot estimate the results of the test.
The error is general for what i've been testing, other VECM estimations with (restricted constant, no constant, drift) have no troubles.
I'll leave an example of what the error looks like.
I thought this would be a one time error, however i've tested it on 3 different time series data bases, and the conclusions is that after a VECM with trend, the commands of vecmarl and vecnorm, jbera cannot estimate the results of the test.
The error is general for what i've been testing, other VECM estimations with (restricted constant, no constant, drift) have no troubles.
I'll leave an example of what the error looks like.
Code:
vec log_PIB_r log_Military_S_r, lag(3) trend(trend)
Vector error-correction model
Sample: 1953 - 2014 Number of obs = 62
AIC = -5.013312
Log likelihood = 170.4127 HQIC = -4.811255
Det(Sigma_ml) = .000014 SBIC = -4.498682
Equation Parms RMSE R-sq chi2 P>chi2
----------------------------------------------------------------
D_log_PIB_r 7 .029485 0.7528 167.4535 0.0000
D_log_Military~r 7 .145817 0.3055 24.19635 0.0011
----------------------------------------------------------------
------------------------------------------------------------------------------------
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------------+----------------------------------------------------------------
D_log_PIB_r |
_ce1 |
L1. | -.0369507 .0182902 -2.02 0.043 -.0727988 -.0011026
|
log_PIB_r |
LD. | .4199505 .1275807 3.29 0.001 .1698969 .6700041
L2D. | .2141882 .1306261 1.64 0.101 -.0418343 .4702107
|
log_Military_S_r |
LD. | .0265396 .0272462 0.97 0.330 -.026862 .0799411
L2D. | .0391178 .0261992 1.49 0.135 -.0122317 .0904674
|
_trend | -.0000329 .0002105 -0.16 0.876 -.0004455 .0003797
_cons | .0150881 .0099484 1.52 0.129 -.0044104 .0345866
-------------------+----------------------------------------------------------------
D_log_Military_S_r |
_ce1 |
L1. | -.2698643 .0904541 -2.98 0.003 -.4471511 -.0925775
|
log_PIB_r |
LD. | .3414482 .63095 0.54 0.588 -.8951912 1.578088
L2D. | .6698477 .6460111 1.04 0.300 -.5963108 1.936006
|
log_Military_S_r |
LD. | -.0068011 .1347459 -0.05 0.960 -.2708983 .257296
L2D. | -.1033091 .1295682 -0.80 0.425 -.3572581 .1506399
|
_trend | 4.51e-06 .0010411 0.00 0.997 -.002036 .002045
_cons | .0265753 .0491999 0.54 0.589 -.0698546 .1230053
------------------------------------------------------------------------------------
Cointegrating equations
Equation Parms chi2 P>chi2
-------------------------------------------
_ce1 1 13.45587 0.0002
-------------------------------------------
Identification: beta is exactly identified
Johansen normalization restriction imposed
----------------------------------------------------------------------------------
beta | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
_ce1 |
log_PIB_r | 1 . . . . .
log_Military_S_r | 1.284193 .3500859 3.67 0.000 .5980377 1.970349
_trend | -.1041789 . . . . .
_cons | -19.4083 . . . . .
----------------------------------------------------------------------------------
. veclmar, mlag(2)
error computing temporary var estimates
r(111);
. vecnorm, jbera
error computing temporary var estimates
r(111);
