We expand Nakamura’s (2005) neural network based inflation forecasting experiment to an alternative non-linear model; a Markov switching autoregressive (MS-AR) model. The two non-linear models perform approximately on par and outperform the linear autoregressive model on short forecast horizons of one and two quarters. Furthermore, the MS-AR model is the best performer on longer horizons of thr...

Logistic smooth transition and Markov switching autoregressive models of a logistic transform of the monthly US unemployment rate are estimated by Markov chain Monte Carlo methods. The Markov switching model is identified by constraining the first autoregression coefficient to differ across regimes. The transition variable in the LSTAR model is the lagged seasonal difference of the unemployment...

This paper reviews the analysis of the threshold autoregressive, smooth threshold autoregressive, and Markov switching autoregressive models from the Bayesian perspective. For each model we start by describing a baseline model and discussing possible extensions and applications. Then we review the choice of prior, inference, tests against the linear hypothesis, and conclude with models selectio...

according to the importance of careful review of crude oil market fluctuations on the iranian economy, in this paper a multivariate model of markov switching vector error correction model (have been used). variables such as real gross domestic product in industrial sector, real effective exchange rate, real governmental expenditure, real import, inflation rate and real crude oil price is used t...

In this paper, we empirically investigate the relationship between oil price changes and output in a group of oil exporting countries. The dynamics of business cycles in Libya, Saudi Arabia, Nigeria, Kuwait, Venezuela and Qatar are modeled by alternative regime switching models. We show that the extension of uni-variate Markov Switching model in order to include oil revenue improves dating busi...

In Markov-switching regression models, we use Kullback–Leibler (KL) divergence between the true and candidate models to select the number of states and variables simultaneously. Specifically, we derive a new information criterion, Markov switching criterion (MSC), which is an estimate of KL divergence. MSC imposes an appropriate penalty to mitigate the overretention of states in the Markov chai...

T he main purpose of this article is to analyze exchange rate behavior based on monetary fundamentals in the context of Iranian economy over the period 1990:2 to 2014:3. To do so, two monetary exchange rate models is investigated, the first by regarding interest rate differential as a monetary variable, and the second one regardless of interest rate differential as a monetary variabl...

We propose a statistical model to assess whether individuals strategically use mixed strategies in repeated games. We formulate a hidden Markov model in which the latent state space contains both pure and mixed strategies, and allows switching between these states. We apply the model to data from an experiment in which human subjects repeatedly play a normal form game against a computer that al...

In this paper, I find that real U.S. GDP is better characterized as a trend stationary Markov-switching process than as having a (regime-dependent) unit root. I examine the effects of both assumptions on the analysis of business cycle features and their implications for the persistence of the dynamic response of output to a random disturbance. JEL Classification: E32, C22, E27.

this paper examines the impact of 2005 presidential election of iran on the tehran stock exchange volatility as a political shock. it uses garch family (fiegarch, egarch, and garch) and markov regime switching (mrs) models as the analytical frameworks for the main the stock daily prices index. our findings confirm statistical validity of arima – fiegarch-x and ar(1) mrs as appropriate specifica...