jpfeifer wrote:You are not taking the log of the whole expression, but of k. k is not 0 in steady state. Hence, there is not a problem. If you want to see how the result looks, take a multivariate first order Taylor approximation in k and k(+1) of the expression where you substituted exp(k) for k (and similarly for k(+1)).
Hello,
I tried this method and got the following (assuming the math is correct):
phi((k_ss/k_ss)-1) (log(k_t+1) - log(k_ss)) - phi((k_ss/k_ss)-1) (log(k_t+1) - log(k_ss)) = 0
If it was the actual taylor approximation then the equation would be log(phi/2((k_ss/k_ss)-1)^2) + (1/(phi/2((k_ss/k_ss)-1)^2))*phi((k_ss/k_ss)-1) (log(k_t+1) - log(k_ss)) - phi((k_ss/k_ss)-1) (log(k_t+1) - log(k_ss))
That equation above cannot be defined.
How can we handle this in log-linearization in Dynare or by hand, especially when you may have a budget constraint line of, for example,
y = c + i + phi/2((k_t+1/k_t)-1)^2
as part of your model.
Furthermore, suppose your adjustment cost is instead phi/2((i_t/k_t))^2, which would equal 0 in steady state. How can we handle this log-linearization?
Although I read your manual on log-linearization, can you please provide clarification?
Thanks.