I am new to dynare. I am trying to replicate the calibration of the paper ‘Structural transformation and aggregate productivity’ by Margarida Duarte and Diego Restuccia.

In this calibration technique, some parameters are known while others (b and ρ) are estimated such that the squared difference between data and model moments reduces.

My problem is - in all the calibration exercises that I saw regarding macroeconomics models [Picture attached], all the parameter values are assumed and model is calibrated by computing future period values using these initial period values of variables and parameters. (vs my problem where all parameters are not known and have to be calculated from matching model with data)

My question is how can we do calibration in Dynare where we don’t know the values of all the parameters and want to estimate it using least square differences?