VECM and forecasting
Posted: Mon Apr 06, 2015 7:20 am
Hi,
I have arrived at an equation via the cointegration test process and eliminating insignificant variables:
D(LN_NBP) = C(1)*( LN_NBP(-1) - 0.860929243883*LN_BRENT(-1) +
0.266786377636 ) + C(4)*D(LN_BRENT(-1)) + C(6)
When trying to forecast EViews only forecasts one step forward (I have data jan2000-dec2014 and it only forecasts Jan2015).
Is it something wrong with the equation obtained through the VECM or am I choosing a wrong type of forecast.
LN_NBP is gas price
LN_Brent is oil, and I am trying to forecast the cointegrated future prices.
Output from equation:
-----------
Dependent Variable: D(LN_NBP)
Method: Least Squares
Date: 04/06/15 Time: 16:18
Sample (adjusted): 2000M03 2014M12
Included observations: 178 after adjustments
D(LN_NBP) = C(1)*( LN_NBP(-1) - 0.860929243883*LN_BRENT(-1) +
0.266786377636 ) + C(4)*D(LN_BRENT(-1)) + C(6)
Coefficient Std. Error t-Statistic Prob.
C(1) -0.355109 0.053506 -6.636756 0.0000
C(4) -0.500458 0.170152 -2.941237 0.0037
C(6) 0.009789 0.016654 0.587764 0.5574
R-squared 0.210504 Mean dependent var 0.007435
Adjusted R-squared 0.201481 S.D. dependent var 0.248215
S.E. of regression 0.221805 Akaike info criterion -0.157328
Sum squared resid 8.609538 Schwarz criterion -0.103702
Log likelihood 17.00219 Hannan-Quinn criter. -0.135581
F-statistic 23.33024 Durbin-Watson stat 2.238876
Prob(F-statistic) 0.000000
----------
Please help and thank you very much!
I have arrived at an equation via the cointegration test process and eliminating insignificant variables:
D(LN_NBP) = C(1)*( LN_NBP(-1) - 0.860929243883*LN_BRENT(-1) +
0.266786377636 ) + C(4)*D(LN_BRENT(-1)) + C(6)
When trying to forecast EViews only forecasts one step forward (I have data jan2000-dec2014 and it only forecasts Jan2015).
Is it something wrong with the equation obtained through the VECM or am I choosing a wrong type of forecast.
LN_NBP is gas price
LN_Brent is oil, and I am trying to forecast the cointegrated future prices.
Output from equation:
-----------
Dependent Variable: D(LN_NBP)
Method: Least Squares
Date: 04/06/15 Time: 16:18
Sample (adjusted): 2000M03 2014M12
Included observations: 178 after adjustments
D(LN_NBP) = C(1)*( LN_NBP(-1) - 0.860929243883*LN_BRENT(-1) +
0.266786377636 ) + C(4)*D(LN_BRENT(-1)) + C(6)
Coefficient Std. Error t-Statistic Prob.
C(1) -0.355109 0.053506 -6.636756 0.0000
C(4) -0.500458 0.170152 -2.941237 0.0037
C(6) 0.009789 0.016654 0.587764 0.5574
R-squared 0.210504 Mean dependent var 0.007435
Adjusted R-squared 0.201481 S.D. dependent var 0.248215
S.E. of regression 0.221805 Akaike info criterion -0.157328
Sum squared resid 8.609538 Schwarz criterion -0.103702
Log likelihood 17.00219 Hannan-Quinn criter. -0.135581
F-statistic 23.33024 Durbin-Watson stat 2.238876
Prob(F-statistic) 0.000000
----------
Please help and thank you very much!