This paper presents the results of an empirical investigation of business cycle nonlinearities and asymmetries in the Iranian economy. Seasonal Gross Domestic Products (GDP) time series are subjected to nonlinearity and asymmetry tests. The recessions and expansions states are modeled with Markov-Switching Autoregressive models (MSM). The paper shows that allowing for three regimes for the finding of asymmetry and nonlinearity in Iranian business cycle fluctuations. The paper also provides evidence on the usefulness of a non-linear model as compared with a linear alternative in the context of business cycle research in an emerging economy using LR test.
Moradi, A. (2017). Nonlinearity and Asymmetries in Iranian Business Cycle: Through Markov Switching Auto Regression Model. Medbiotech Journal, 01(03), 100-104. doi: 10.22034/mbt.2017.86983
MLA
Alireza Moradi. "Nonlinearity and Asymmetries in Iranian Business Cycle: Through Markov Switching Auto Regression Model". Medbiotech Journal, 01, 03, 2017, 100-104. doi: 10.22034/mbt.2017.86983
HARVARD
Moradi, A. (2017). 'Nonlinearity and Asymmetries in Iranian Business Cycle: Through Markov Switching Auto Regression Model', Medbiotech Journal, 01(03), pp. 100-104. doi: 10.22034/mbt.2017.86983
VANCOUVER
Moradi, A. Nonlinearity and Asymmetries in Iranian Business Cycle: Through Markov Switching Auto Regression Model. Medbiotech Journal, 2017; 01(03): 100-104. doi: 10.22034/mbt.2017.86983
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