help - ecm

[ANDROO1988]

Hello,

I want do vecm. I have 5 I(1) series.


How do I construct an error-correction model? i want u]ecm(-1) or coefficients for speed of adjustment of variables.[/u]

I read this page:
http://forums.eviews.com/viewtopic.php?f=4&t=8508 and this:

http://www.google.com/url?sa=t&rct=j&q= ... 2593,d.b2I

but i need help again.
Thank you in advance :)
this is vecm estimation results:
Vector Error Correction Estimates
Date: 09/06/14 Time: 13:00
Sample (adjusted): 2000M06 2013M12
Included observations: 158 after adjustments
Standard errors in ( ) & t-statistics in [ ]

Cointegrating Eq: CointEq1

Y(-1) 1.000000

X1(-1) -1.397010
(0.36344)
[-3.84390]

X2(-1) -7.016740
(0.66521)
[-10.5482]

X3(-1) 2.078240
(0.83357)
[ 2.49318]

X4(-1) 4.650890
(0.41055)
[ 11.3285]

C -44.64200

Error Correction: D(Y) D(X1) D(X2) D(X3) D(X4)

CointEq1 -0.002069 0.010549 0.000849 -0.003118 -0.054578
(0.00370) (0.00747) (0.00077) (0.00372) (0.00513)
[-0.55940] [ 1.41129] [ 1.10461] [-0.83851] [-10.6440]

D(Y(-1)) 0.614644 0.315297 -0.003015 -0.149740 -0.058028
(0.08309) (0.16795) (0.01728) (0.08354) (0.11521)
[ 7.39766] [ 1.87732] [-0.17451] [-1.79246] [-0.50367]

D(Y(-2)) -0.169307 -0.085108 0.002706 0.043827 -0.100256
(0.08225) (0.16625) (0.01710) (0.08270) (0.11405)
[-2.05851] [-0.51191] [ 0.15822] [ 0.52997] [-0.87908]

D(X1(-1)) 0.030470 0.223991 0.005502 0.021697 0.018647
(0.04006) (0.08098) (0.00833) (0.04028) (0.05555)
[ 0.76058] [ 2.76593] [ 0.66044] [ 0.53864] [ 0.33566]

D(X1(-2)) 0.024109 0.012772 0.004107 0.023406 -0.027465
(0.03937) (0.07958) (0.00819) (0.03958) (0.05459)
[ 0.61237] [ 0.16049] [ 0.50169] [ 0.59129] [-0.50308]

D(X2(-1)) 0.821741 -0.497838 0.437746 0.108007 -0.648769
(0.40438) (0.81740) (0.08408) (0.40658) (0.56072)
[ 2.03212] [-0.60905] [ 5.20614] [ 0.26565] [-1.15702]

D(X2(-2)) -0.222444 -1.046274 0.128941 0.873494 -0.088592
(0.41049) (0.82976) (0.08535) (0.41273) (0.56920)
[-0.54190] [-1.26094] [ 1.51067] [ 2.11641] [-0.15564]

D(X3(-1)) -0.018127 0.258855 0.011447 -0.031560 -0.008566
(0.08090) (0.16353) (0.01682) (0.08134) (0.11218)
[-0.22407] [ 1.58293] [ 0.68050] [-0.38800] [-0.07636]

D(X3(-2)) 0.050773 0.081767 0.014264 -0.032122 -0.053014
(0.08128) (0.16430) (0.01690) (0.08172) (0.11270)
[ 0.62468] [ 0.49768] [ 0.84402] [-0.39306] [-0.47039]

D(X4(-1)) 0.001433 0.094360 0.006981 -0.033711 -0.390975
(0.04948) (0.10003) (0.01029) (0.04975) (0.06862)
[ 0.02895] [ 0.94333] [ 0.67844] [-0.67755] [-5.69786]

D(X4(-2)) -0.023560 -0.011909 0.009596 -0.012173 -0.154534
(0.05168) (0.10447) (0.01075) (0.05196) (0.07166)
[-0.45587] [-0.11399] [ 0.89292] [-0.23426] [-2.15634]

C 0.004734 0.020649 0.005240 -0.009734 0.062481
(0.00774) (0.01565) (0.00161) (0.00779) (0.01074)
[ 0.61133] [ 1.31924] [ 3.25474] [-1.25033] [ 5.81924]

R-squared 0.360335 0.133437 0.276194 0.061167 0.508854
Adj. R-squared 0.312141 0.068148 0.221661 -0.009567 0.471850
Sum sq. resids 0.266517 1.089000 0.011523 0.269431 0.512452
S.E. equation 0.042725 0.086365 0.008884 0.042958 0.059245
F-statistic 7.476778 2.043795 5.064695 0.864740 13.75127
Log likelihood 280.2157 169.0172 528.3617 279.3568 228.5680
Akaike AIC -3.395135 -1.987559 -6.536224 -3.384263 -2.741367
Schwarz SC -3.162533 -1.754957 -6.303622 -3.151661 -2.508765
Mean dependent 0.022832 0.009732 0.013582 0.000000 0.030678
S.D. dependent 0.051515 0.089467 0.010070 0.042754 0.081521

Determinant resid covariance (dof adj.) 6.08E-15
Determinant resid covariance 4.10E-15
Log likelihood 1496.183
Akaike information criterion -18.11624
Schwarz criterion -16.85631

[ANDROO1988]

plz help me.......................