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Interest Rate Volatility Regimes in Selected Asian Countries: A Univariate Markov Switching Analysis
2 作者信息
Dicle Ozdemir
Mugla Sitki KocmanUniversity
Dicle Ozdemir. Interest Rate Volatility Regimes in Selected Asian Countries: A Univariate Markov Switching Analysis[J]. Front. Econ. China, 2020, 15(1): 56-69.
链接
http://journal.hep.com.cn/fec/EN/10.3868/s060-011-020-0003-3
http://journal.hep.com.cn/fec/EN/Y2020/V15/I1/56
4 摘要
Abstract：Business cycle dynamics are determined by relatively large volatilities in output, consumption, and investment, which leads to cyclical fluctuations in interestrates. 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 inselected 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 stable 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.
摘要：商业周期动态由产出、消费和投资中相对较大的波动决定，而这些波动又会导致周期性的利率波动。我们使用马尔科夫机制转换模型，模拟名义利率变动来解释在一组选定的亚洲新兴经济体里的利率波动机制转换情况。估计结果提供了这些国家在固定机制和浮动机制下的平均值、方差和概率，它们作为重要依据证实了名义利率波动存在两套不同机制。此外，转换自回归模型的平滑概率结果显示，该模型能够捕捉到与名义利率行为相对应的两套机制。同时，结果还显示，固定机制比浮动机制持续时间更长。本研究还表明马尔科夫转换模型相比传统回归模型更具优势，可以通过利率的周期性行为甄别出不同机制。
5.作者简介
Dicle Ozdemir，美国纽约社会研究新学院经济学博士，土耳其MuglaSitki Kocman大学经济系助理教授。主要研究领域为经济活动中的周期性波动和后凯恩斯时代背景下的经济增长模式，曾发表过多篇关于经济增长的实证研究文章。
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