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Modeling Business Cycle Fluctuations through Markov Switching VAR:An Application to Iran

Moradi, Alireza (2016): Modeling Business Cycle Fluctuations through Markov Switching VAR:An Application to Iran.

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Abstract

IN this paper, the Iranian Business Cycle characteristics were investigated via uni-variate and multivariate Markov-switching specifications. By using Hamilton (1989) and Krolzig (1997) (MS-VAR) models, we examined the stochastic properties of the cyclical pattern of the quarterly Iranian real GDP between 1988:Q2 - 2008:Q3. The empirical analysis consists of mainly three parts. First, two kinds of alternative specifications were tried and we were adopted best specification with respect to various diagnostic statistics. Then, selected models were tested against their linear benchmarks. LR test results imply strong evidence in favor of the nonlinear regime switching behavior. Furthermore, the multivariate specification with various macro aggregates and changing variance parameter outperformed the other MS models with reference to one-step ahead forecasting performance. With this specification, we can detect the three recessionary periods experienced by the Iranian economy between 1988:Q2 and 2008:Q3. Finally, based on inference from this model a chronology of business cycle turning points was determined.

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