This paper describes a method for solving a class of forward-looking Markov-switching Rational Expectations models under noisy measurement, by specifying the unobservable expectations component as a general-measurable function of the observable states of the system, to be determined optimally...

In this note, a class of nonlinear dynamic models under rational expectations is studied. A particular solution is found using a model reference adaptive technique via an extended Kalman filtering algorithm, for which initial conditions knowledge only is required.

This paper describes a method for solving a class of forward-looking Markov-switching Rational Expectations models under noisy measurement, by specifying the unobservable expectations component as a general-measurable function of the observable states of the system, to be determined optimally...

In this note, a class of nonlinear dynamic models under rational expectations is studied. A particular solution is found using a model reference adaptive technique via an extended Kalman filtering algorithm, for which initial conditions knowledge only is required.