Estimation with data in levels

Dear all,

I’m trying to estimate an RBC model with stochastic growth (labour augmenting technology) as in the “Guide to Specifying Observation Equations” where the model is stationarized. However, I want to use the observed variables in (log) levels rather than in growth rates for the estimation. Is that possible in Dynare? Or is it only possible with deterministic trends? If so, can you suggest some reference or code to look at?

I have read several posts in here about this, but I’m still quite confused about whether this is Dynare constraint or is a broader situation with DSGE modelling.

Thanks all in advance.

It’s a general issue related to perturbation techniques and modeling. Your DSGE model is approximated around a steady state that needs to exist. So you need to work with a detrended model. Now the data itself is trending. If you want to link the stationary model and the trending data, you need to take a stand on what gives rise to the trend in the data, i.e. you need to specify the data generating process. It either features a deterministic or stochastic trend.

Professor, Thank you for your answer.

In many of the models replicated in your website with stochastic trends (Aguiar&Gopinath, GPU, Smets&Wouters) the estimation is in growth rates. Is it possible to estimate those models with the data in (log) levels in Dynare?

No, but there is also no reason to use the level. The only difference between levels and growth rates is that the initial condition is not used.