I have actual data from 1990 to 2014 and assumed data for 2015 for some variables in the model (not all the variables). My forecast period is from 2015 to 2020.
In order to match the forecast to the assumed data, I've programmed as below.
For the variable with assumption
smpl 1990 2015
model.append Y = C(1)*X + E_Y
model.append E_Y = C(2)*E_Y(-1)+V_Y
model.control V_Y Y Y_AS
smpl 1990 2020
(E_Y is the error term, V_Y is IID shock, and Y_AS is the assumed 2015 data)
This works for some equations, but not all of them.
The error says " cannot compute due to missing data" and returns NA for V_Y.
Could you teach me whether this programming is appropriate.
If there is another way to do this, I would be grateful if you could teach me.
Thank you in advance.
Solving by matching to the assumed data
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Re: Solving by matching to the assumed data
Seems appropriate. Hard to give more advice without having the workfile.
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Re: Solving by matching to the assumed data
Thank you for your quick reply.
Since I cannot send you my workfile due to confidential reason, I will work on it again by myself and may ask you again.
Thank you again.
Since I cannot send you my workfile due to confidential reason, I will work on it again by myself and may ask you again.
Thank you again.
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