I need to estimate the following equation, to estimate β1:
πt= β0 + β1π(t-1) + ∑(k=2)βk∆π(t-k) + εt
Can someone help me?
Distributed lag model
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startz
- Non-normality and collinearity are NOT problems!
- Posts: 3797
- Joined: Wed Sep 17, 2008 2:25 pm
Re: Distributed lag model
In EViews you represent a lagged variable x(t-k) by writing x(-k)
For example, x(-1), x(-2) and so on.
For example, x(-1), x(-2) and so on.
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diogoretti
- Posts: 5
- Joined: Tue Nov 10, 2015 5:28 pm
Re: Distributed lag model
Startz,
I estimated the equation. How do I know the coefficient of CPIARG(-1)?
Dependent Variable: CPIARG
Method: Least Squares
Date: 11/11/15 Time: 19:43
Sample (adjusted): 2003Q4 2014Q4
Included observations: 45 after adjustments
CPIARG = C(1) + CPIARG(-1) + D(CPIARG(-2))
Coefficient Std. Error t-Statistic Prob.
C(1) 0.006779 0.006489 1.044679 0.3019
R-squared 0.193395 Mean dependent var 0.101659
Adjusted R-squared 0.193395 S.D. dependent var 0.048465
S.E. of regression 0.043527 Akaike info criterion -3.408896
Sum squared resid 0.083363 Schwarz criterion -3.368748
Log likelihood 77.70016 Hannan-Quinn criter. -3.393929
Durbin-Watson stat 1.083475
I estimated the equation. How do I know the coefficient of CPIARG(-1)?
Dependent Variable: CPIARG
Method: Least Squares
Date: 11/11/15 Time: 19:43
Sample (adjusted): 2003Q4 2014Q4
Included observations: 45 after adjustments
CPIARG = C(1) + CPIARG(-1) + D(CPIARG(-2))
Coefficient Std. Error t-Statistic Prob.
C(1) 0.006779 0.006489 1.044679 0.3019
R-squared 0.193395 Mean dependent var 0.101659
Adjusted R-squared 0.193395 S.D. dependent var 0.048465
S.E. of regression 0.043527 Akaike info criterion -3.408896
Sum squared resid 0.083363 Schwarz criterion -3.368748
Log likelihood 77.70016 Hannan-Quinn criter. -3.393929
Durbin-Watson stat 1.083475
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startz
- Non-normality and collinearity are NOT problems!
- Posts: 3797
- Joined: Wed Sep 17, 2008 2:25 pm
Re: Distributed lag model
You seem to not have specified a coefficient for CPIARG(-1). Try something like
Code: Select all
ls CPIARG c CPIARG(-1) D(CPIARG(-2))
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