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Optimal nsample size for Bayesian estimation

PostPosted: Wed Jul 20, 2016 8:41 pm
by JX2016
Hi, there. I wonder if there is a rule of thumb for the sample size of the observations used for Bayesian estimation?

Thanks in advance

Re: Optimal nsample size for Bayesian estimation

PostPosted: Wed Jul 20, 2016 10:14 pm
by JX2016
If I use the logged 1st-differenced data for the estimation, should I write an equation for dy?

i.e. dy = y - y(-1) and put dy in the varobs block.

Or dynare can understand that y is the 1st-differenced variable so I don't need to specify another variable dy = y - y(-1) ? And I can just treat y as a 1st-differenced variable?


Thanks in advance

Re: Optimal nsample size for Bayesian estimation

PostPosted: Thu Jul 21, 2016 6:41 am
by jpfeifer
1. There is no such thing as the optimal sample size (except for the trivial "as much data as you have from that joint probability distribution"). If your Bayesian, you even do without any data. It is then just called your prior.
2. As detailed in Pfeifer(2013): "A Guide to Specifying Observation Equations for the Estimation of DSGE Models" https://sites.google.com/site/pfeiferecon/Pfeifer_2013_Observation_Equations.pdf the user is responsible for specifying the mapping from model to data variables. That also captures first differences.

Re: Optimal nsample size for Bayesian estimation

PostPosted: Thu Jul 21, 2016 11:49 pm
by JX2016
Thank you so much, professor pfeifer! problem solved