identification and posterior means
Posted: Mon Sep 08, 2014 2:52 pm
question 1 -
While estimating 3 parameters the Identification strength with moments Information matrix (log−scale), show no bars and matlab informs that all variables are collinear with each other.
However when I estimate any two separately the bars appear and all variables are identified.
I was wondering how to correct or explain this behaviour ?
question 2 - Also the posterior means change for parameters when I add one more parameter to the subset of parameters to be estimated ? Is there any rule of thumb if we need to estimate a certain number of parameters ? The acceptance ratio is 30%. Can increasing the number of metropolis hastings replications solve this problem ??
Regards,
While estimating 3 parameters the Identification strength with moments Information matrix (log−scale), show no bars and matlab informs that all variables are collinear with each other.
However when I estimate any two separately the bars appear and all variables are identified.
I was wondering how to correct or explain this behaviour ?
question 2 - Also the posterior means change for parameters when I add one more parameter to the subset of parameters to be estimated ? Is there any rule of thumb if we need to estimate a certain number of parameters ? The acceptance ratio is 30%. Can increasing the number of metropolis hastings replications solve this problem ??
Regards,