I have run 2 estimations with same configuration and datasets
variance decomposition of risk premium shock are not the same.
I have done that last year, so maybe I have done a mistake about the correction of “(r - pinf(+1) + 0b) + b;” which I replaced by “*(r - pinf(+1) + b);” and similarly for the other occurrences of “b”.
I think u should try with a good correction and compare.
Another question: from where did u take the answer " The consumption Euler equation in the paper, equation (2), premultiplies the risk premium process \varepsilon_t^b, denoted by b in this code, by the coefficient c_3. In the code this prefactor is omitted by setting the coefficient to 1. As a consequence, b in this code actually is b:=c_3*\varepsilon_t^b. This rescaling also explains why the standard deviation of the risk premium shock in the AR(1)-process for b has a different standard deviation than reported in the paper. However, the results are unaffected by this "
Is it your response or does it comes from someone else ?
for research purposes, especially aiming at variance decompositions, I did come across the SW2007 paper and existing mod files as well.
I also modified the mod file like @jonathanb did and found different results for the risk premium / preference shock compared to the estimation results using the mod file published by Prof. Pfeifer and SW.
Unfortunately, I am lacking explanation here since it is stated that the results should be unaffected…
Can anyone help me out with a short explanation please.
I don’t know which model to use for the purpose of variance decomposition.
I ran a few tests with the unstable version now and the results look way more logicial than in the stable version.
Since I already computed many (time consuming) draws with the stable version, I am wondering if it is possible to compute moments_varendo for existing mode_file and load_mh_file with mh_replic=0 using the newest unstable version?