Parameter calibration DSGE

[hosey_29]

Dear members and Professor Johannes,

I am working on a DSGE model with baseline as the Gali 2015 (by Johannes) with additions of CBDC and deposit fee.

As for the parameters and calibration of the parameters, I have questions:

• Can I use the same parameters as used in the Gali 2015 mod 3? Because;:

• I am going to test for Financial crisis. What happened (by running simulation with the baseline model without our adjustments) and then run simulation with our adjusted model and compare how fast we would come out of a recession in our economy.

• If not, how can I calibrate them in dynare?

• Also, for the parameters we have added, how can we do calibration on them? They are not so far applied in any models we have seen:

• : eta_cbdc = 1.5; % Semi-elasticity of CBDC demand
  eta_paper = 0.5; % Semi-elasticity of paper currency demand
  alpha_cbdc = 0.7; % Weight of CBDC in total money demand
  gamma = 0.05; % Sensitivity of deposit fee
  gamma_zero = 0; % No deposit fee when interest rate high

[jpfeifer]

Nobody can make that decision for you. The Gali model is very stylized and not targeted towards a particular country or time period. It’s more about stylized facts. Given the round numbers you picked for the additional parameters, that may be all you need.

[hosey_29]

No that is true. I have never calibrated parameters until this model. Therefore I wanted to know if there are certain ways to estimate them if not found in other research papers. I want to identify a number that makes sense.
So I wished to learn more about ways to calibrate the parameters or maybe there is some topic about this, but from my search i could not find more than a few comments about it.
If there are any pages here I can check to understand and learn more, especially since these parameters are not used before not in the most places at least.,

[jpfeifer]

Search the forum. There have been various topics like

Model validation of Bayesian estimation

This is a rather philosophical matter. Historically, models were calibrated to long-run growth facts and then cross-validated by looking at the implies short- to medium-run implications for the business cycle, which is in a sense a different dataset. When estimating a model, the parameters are chosen by looking at the same dataset for which you try to match second moments. You could argue that this is not a rigid “out of sample” test. People nevertheless do this, because when estimating, you t…

or

Calibration for less developed economies

Usually, there are three ways of setting parameters: Using micro-estimates. Doing informal moment-matching, e.g. based on the great ratios Formal estimation using either full or limited information techniques Option 2 often has the least data requirements I doubt that parameters are exactly the same for all economies, but priors differ on whether the difference between countries is the structural parameter values or the underlying structure of the economy Targeting the great ratios is…