2007年8月美國爆發次貸危機(Subprime Crisis)，如此新型態的金融危機是否可由金融危機預警系統預測？是本文所欲探討的目標。本文採用訊號方法、固定效果下的Panel Logit Model和CART(Classification and Regression Tree)三種計量方法建構危機預警模型。最後利用美國2006年至2008年資料，驗證本文所建構之預警模型是否能夠有效預測次貸危機的發生。

“Could banking early warning systems help to predict Sub-prime crisis?” That is the main issue that we want to discuss. We combine three kinds of early warning systems models – Signal Approach, fixed effect panel logit model, and CART approach – to create a new banking early warning system(EWS). We will use the US 2006-2008 data to examine whether this new EWS could predict the Sub-prime crisis correctly.

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