Does using mixed-frequency data enhance the strength of parameter identification?
That question is ill-posed. Relative to what? A model where you do not observe the data at the highest frequency? In that case, the answer would be yes. Having more data generally helps with identification.
Thank you, Professor. May I also ask if there are any specific algorithms used in Dynare for Bayesian estimation when dealing with mixed-frequency data? If so, could you please tell me which paper proposed the algorithm adopted by Dynare?