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Detecting currency manipulation: An application of a state-space model with Markov switching

机译：检测货币操纵：带马尔可夫切换的状态空间模型的应用

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Following an idea of Milton Friedman's "plucking model," we propose to use a state-space model with Markov switching as an auxiliary tool for detecting currency manipulation. Without imposing any a priori restrictions, our model tests if fluctuations of a country's exchange rate are symmetric or if there exists a time-varying support level or resistance level of exchange rate. Using weekly and monthly data of countries on the "monitoring list" of the US Treasury as of April 2017, we find that exchange rates of China, South Korea, Switzerland, and Taiwan rarely fall below their time-varying trends, but are plucked upward from time to time by transitory shocks, suggesting that the FX (foreign exchange) authorities of these countries may have been intervening more actively against appreciation shocks. Our sub-sample analysis reveals that our model accurately captures the period of Switzerland's minimum exchange rate policy with probability of one and Japan's exchange rate rarely falls below its trend after implementing Abenomics. We discuss the difficulties of detecting FX intervention along with the relative advantage of our approach.
机译：遵循米尔顿·弗里德曼（Milton Friedman）的“拔除模型”的思想，我们建议使用带有马尔可夫切换的状态空间模型作为检测货币操纵的辅助工具。在不施加任何先验限制的情况下，我们的模型测试一个国家的汇率波动是否对称，或者是否存在随时间变化的支撑水平或汇率阻力水平。使用截至2017年4月的美国财政部“监测名单”上的国家的每周和每月数据，我们发现中国，韩国，瑞士和台湾的汇率很少低于其随时间变化的趋势，但是由于短暂的冲击而时不时地往上拉，这表明这些国家的外汇（外汇）当局可能一直在更加积极地干预升值冲击。我们的子样本分析显示，我们的模型准确地把握了瑞士实行最低汇率政策的时期，概率为1，而日本的汇率在实施安倍经济学后极少低于其趋势。我们讨论了检测外汇干预的困难以及我们方法的相对优势。

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