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Frontiers of Economics in China

ISSN 1673-3444

ISSN 1673-3568(Online)

CN 11-5744/F

Postal Subscription Code 80-978

Front. Econ. China    2020, Vol. 15 Issue (1) : 56-69
Orginal Article
Interest Rate Volatility Regimes in Selected Asian Countries: A Univariate Markov Switching Analysis
Dicle Ozdemir()
Faculty of Economics and Administrative Sciences, Mugla Sitki Kocman University, Kotekli Kampusu, Mugla, 48000, Turkey
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Business cycle dynamics are determined by relatively large volatilities in output, consumption, and investment, which leads to cyclical fluctuations in interest rates. Using the Markov switching model, we model the nominal interest rate movements to explain the volatility regime shifts in a set of selected emerging Asian economies. The estimated results provide significant evidence of regime-dependent means, variances, and probabilities in both stable and volatile regimes in selected countries, confirming the existence of two distinct regimes in nominal interest rate movements. In addition, the smoothed probability results of switching autoregressive model show that the model is capable of capturing the two regimes for the corresponding nominal interest rate behaviors. Besides, the results reveal that the stables regimes have higher durations than the volatile regimes. This study also shows the advantage of Markov switching models over conventional regression models, allowing the identification of different regimes for the cyclical behavior of interest rates.

Keywords regime switching      Markov regime      nominal interest rate      Asian countries      emerging economies      business cycle      volatility      switching autoregressive model     
Issue Date: 18 April 2020
 Cite this article:   
Dicle Ozdemir. Interest Rate Volatility Regimes in Selected Asian Countries: A Univariate Markov Switching Analysis[J]. Front. Econ. China, 2020, 15(1): 56-69.
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[2] Jian Chen,Chenghu Ma. Option Pricing Based on Alternative Jump Size Distributions[J]. Front. Econ. China, 2016, 11(3): 439-467.
[3] Keqiang Hou,Luke Chan,Xin Zeng. Information Linkages between Chinese and World Copper Futures Markets[J]. Front. Econ. China, 2015, 10(2): 272-300.
[4] Biao Gu, Jianfeng Wang, Jingfei Wu. An Estimated DSGE Model for Business Cycle Analysis in China[J]. Front Econ Chin, 2013, 8(3): 390-429.
[5] Dinghai Xu, Yuying Li. Empirical Evidence of the Leverage Effect in a Stochastic Volatility Model: A Realized Volatility Approach[J]. Front Econ Chin, 2012, 7(1): 22-43.
[6] James Laurenceson. The Impact of Volatility on Growth in China[J]. Front Econ Chin, 2010, 5(4): 527-536.
[7] YANG Guang, . Local government expenditure, RBC model and regional business cycle in China—Take Tianjin for example[J]. Front. Econ. China, 2009, 4(4): 588-600.
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