貨幣危機日期的認定 : 馬可夫轉換模型的應用

Abstract

本研究目的為建立一個全面性且長期的認定貨幣危機日期系統，以三種馬可夫轉模型與Hadi方法來分別認定在國際貨幣基金中的138個會員國貨幣危機發生的日期。資料使用1970年到2003年的月資料。實證結果顯示簡單的馬可夫轉換模型較能認定出著名危機的發生日期，而GARCH下的馬可夫轉換模型與Hadi方法較無法涵蓋著名危機的日期，然而GARCH馬可夫轉換模型所認定的危機日期品質卻較其他兩種模型為佳。此外，本文亦明確指出導致馬可夫轉換模型應用於貨幣危機日期的認定結果不理想的可能原因。

We apply the Markov-switching models to the identification of currency crises in a sample of 138 IMF member countries. We try three specifications: a simple switching model in which the two states have different mean and variance, a model with autoregressive mean, and a GARCH switching model in which conditional mean and conditional variance are allowed to vary. Using monthly data ranging from 1970 to 2003, we compare the results of crises classification with Hadi’s outlier detection method. We find that regime-switching models can identify most well known crisis episodes, but they tend to identify too much crises, and the results are not robust to different model specifications. We discuss potential reasons that lead to the unsatisfactory performance of the regime-switching models in currency crises identification.