Improving Markov switching models using realized variance

Asymmetric Effects of Monetary Policy and Business Cycles in Iran using Markov-switching Models

This paper investigates the asymmetric effects of monetary policy on economic growth over business cycles in Iran. Estimating the models using the Hamilton (1989) Markov-switching model and by employing the data for 1960-2012, the results well identify two regimes characterized as expansion and recession. Moreover, the results show that an expansionary monetary policy has a positive and statist...

State Space Markov Switching Models Using Wavelets

We propose a state space model with Markov switching, whose regimes are associated with the model parameters and regime transition probabilities are time-dependent. The estimation is based on maximum likelihood method using the EM algorithm. The distribution of the estimators is assessed using bootstrap. To evaluate the state variables and regime probabilities, the Kalman filter and a probabili...

Markov-Switching Models

Markov-switching generalized additive models

We consider Markov-switching regression models, i.e. models for time series regression analyses where the functional relationship between covariates and response is subject to regime switching controlled by an unobservable Markov chain. Building on the powerful hidden Markov model machinery and the methods for penalized B-splines routinely used in regression analyses, we develop a framework for...

Explicit-Duration Markov Switching Models

Markov switching models (MSMs) are probabilistic models that employ multiple sets of parameters to describe different dynamic regimes that a time series may exhibit at different periods of time. The switching mechanism between regimes is controlled by unobserved random variables that form a first-order Markov chain. Explicit-duration MSMs contain additional variables that explicitly model the d...