The attached file implements the Adaptive Metropolis Hastings algorithm of Haario, Saksman and Tamminen. Generally speaking, its performance is significantly better than the standard random-walk metropolis hastings when dealing with DSGEs, in the sense that it explores the posterior distribution more efficiently and more accurately. But of course, YMMV.
It is backwards-compatible with the standard Dynare implementation. To turn on the adaptive MH computation, include these lines before the “estimation” command:
amh_t0 = 20000;
Reducing the value of amh_t0 will start the adaptation earlier, at the risk of mis-estimating the covariance matrix.
This code is based on some stand-alone work by Kristoffer Nimark and Francisco Barillas. Maximum respect to them; all errors are mine.
random_walk_metropolis_hastings.m (8.11 KB)