What does it mean to numerically compute the steady-state in Dynare vs MATLAB
What is the underlying objective function and what does it mean to use numerical optimization techniques when computing the steady-state? This is illustrated by the RBC model, preprocessed manually in MATLAB and using different optimization methods.
This is a Zoom recording (hope the quality is still okay) of a session on computing the steady-state of DSGE models numerically. I try to explain what the underlying objective function is and what it means to use numerical optimization techniques. This is illustrated by the RBC model, preprocessed manually in MATLAB and using different optimization methods. I also compare this to what Dynare’s steady command does.
Note that Dynare’s steady command is capable to do much more things than I cover in this video, but I still hope this is useful for people to understand the underlying objective and approach.
Video
Topics
Recap how to preprocess DSGE models with MATLAB
Preprocess RBC model with MATLAB
(Not so good) explanation of how numerical optimizers (e.g. Newton-Raphson) work
Vector-valued vs scalar objective functions
MATLAB: Provide initial values
MATLAB: Create function handle for vector-valued optimizers
MATLAB: use fsolve to find steady-state numerically
MATLAB: use lsqnonlin with bounds to find steady-state numerically
MATLAB: use fminsearch and sum-of-squared-residuals objective function to find steady-state numerically
MATLAB: use patternsearch and sum-of-squared-residuals objective function to find steady-state numerically
Compare residuals and sum-of-squared-residuals
Compare steady-states computed with MATLAB vs with Dynare vs the analytical way