Log-linearization
Posted: Wed May 13, 2009 4:14 am
Hi,
I was wondering how to express log-deviation in DYNARE (for log-linearized model):
a) x_t=log(X_t) - log(X) or
b) x_t=X_t - X,
where X_t is a variable, X is its steady state value, and x_t is log-deviation.
It seems that a) case is correct (and I use it) but as I understood DYNARE MANUAL Version 4.0.3.1 (see the middle of page 25 or very end of this post) advocates for b) case.
If I suppose to use a) case to log-linearize the model then what does DYNARE MANUAL (i.e. yh_t=y_t-ys) imply?
Cheers,
Sigitas
P.S. DYNARE MANUAL Version 4.0.3.1 (see the middle of page 25)
First order approximation
y_t = ys + A yh_t-1 + B u_t
where ys is the steady state value of y and yh_t=y_t-ys.
I was wondering how to express log-deviation in DYNARE (for log-linearized model):
a) x_t=log(X_t) - log(X) or
b) x_t=X_t - X,
where X_t is a variable, X is its steady state value, and x_t is log-deviation.
It seems that a) case is correct (and I use it) but as I understood DYNARE MANUAL Version 4.0.3.1 (see the middle of page 25 or very end of this post) advocates for b) case.
If I suppose to use a) case to log-linearize the model then what does DYNARE MANUAL (i.e. yh_t=y_t-ys) imply?
Cheers,
Sigitas
P.S. DYNARE MANUAL Version 4.0.3.1 (see the middle of page 25)
First order approximation
y_t = ys + A yh_t-1 + B u_t
where ys is the steady state value of y and yh_t=y_t-ys.