I am having problem estimating the Gertler - Karadi (2011) model of uncoventional monetary policy.
I have read (hopefully) all threads on this forum regarding this issue, however, I am still struggling to produce decent results.
From the things I tried - at first, I followed approach of SW, defining measurement equations in the form of
y_obs = y - y(-1)trying to include constant term in the form of (estimated) measurement error or trend growth rate. Dataset used in the estimation was log differenced. Neither of this worked, all ending with dynare and mode_compute=4 unable to find mode and well known error
Error using chol
Matrix must be positive definite.
I have also tried to pass the data through the HP filter to get rid of trend (then removing measurement equations and having observables defined only as y, c etc.) - this didn’t work as well.
The only method that worked and with which dynare was able to find mode and subsequently run Metropolis-Hastings was to have the data log differenced and have measurement equations including measurement error
y_obs = y - y(-1) + me_y which was defined in the shocks section as
var me_y; stderr 1; This produced results, however, the historical shock decomposition of observable variables was useless, since the only thing I saw on the graphs was the whole area explained by measurement error…
I also tried to multiply the observable data by the factor of 100 as in SW, but reading their code I was not so sure how should I update the rest of my .mod file, mainly the steady state values to get this working…
Same goes with values for prior distributions, I tried many many different values.
I attached the .mod file (available also at macromodels database) as well as the data, with the version including measurement equations, without me errors defined. Data are log differenced, taken from FRED database and include real GDP growth (levels), consumption, net investment, bank net worth and inflation (calculated as log differenced CPI)