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YADA Version 5.30

 

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Released on 27/10/2023:

Added parallel computing support to unconditional and conditional forecasting for DSGE models under rational expectations, also subject to the zero lower bound.
Added a single Kalman filter algorithm under adaptive learning when the three learning parameters (rhoAL, sigmaeAL and sigmarAL) are all zero since the belief coefficients are never updated and the solution to the model is given by the steady-state solution.
Added Monte Carlo filtering for the adaptive learning model.
Added DSGE model solution eigenvalues for the adaptive learning model.
Added observation weight decomposition of the unconditional point forecasts at posterior mode and at initial values for the DSGE model.

 

 


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