t he objective of this study is using the markov switching vector autoregressive method and regime dependent impulse response functions to measure the pass-through of world food prices to consumer price index in iran from 1990 to 2013. with respect to information criteria and the log-likelihood ratio statistic, msia(2)-var(1) model has a better fit to data than other models. the magnitude of th...

This paper employ the discrete hidden Markov model (HMM) in order to capture information about the Markov switching model’s inner states that is not directly observable, and to pre-detect the real estate business cycle’s volatility trend. The empirical results show that this HMM can capture the asymmetry in the duration of states. Compared with the real estate leading indicator announced by the...

By utilizing the state-space representation of Markov-switching vector autoregressive models, we develop impulse response functions with regards to shocks to variables of the system The proposed analysis in related to the concept of generalized impulse responses introduced by Koop, Pesaran and Potter (1996) but characterizes the properties of the model dynamics in a more concise form. In contra...

This paper employs Hamilton’s (1989) original Markov-switching model and time-varying Markov-switching model developed by Filardo (1994), respectively, to investigate the business cycle and evaluate the usefulness of the coincident and leading indexes in dating the business cycle and in predicting future GDP in Taiwan. The empirical results do suggest that these two indexes help date the busine...

During periods of market stress, electricity prices can rise dramatically. Electricity retailers cannot pass these extreme prices on to customers because of retail price regulation. Improved prediction of these price spikes, therefore, is important for risk management. This paper builds a time-varying-probability Markov-switching model of Queensland electricity prices, aimed particularly at for...

A procedure is proposed for computing the autocovariances and the ARMA representations of the squares, and higher-order powers, of Markov-switching GARCH models. It is shown that many interesting subclasses of the general model can be discriminated in view of their autocovariance structures. Explicit derivation of the autocovariances allows for parameter estimation in the general model, via a G...

We develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional mean and variance switch in time from one GARCH process to another. The switching is governed by a hidden Markov chain. We provide sufficient conditions for geometric ergodicity and existence of moments of the process. Because of path dependence, maximum likelihood estimation is not feasible. By enlarging the parameter...

We consider the problem of investment and consumption with a hidden Markov model and a regime switching structure. The Bayesian approach is followed to integrate econometric consideration and to make inference of the hidden Markov model. The optimal investment strategy is characterized by the method of stochastic dynamic programming and simulation results are given.