本文主要是透過 Google trends 網站提供的關鍵字搜尋量資料，
探討網路資料是否能夠提供通貨膨脹率的即時資訊。
透過美國消費者物價指數的組成細項作為依據，蒐集美國2004年1月至2015年12月的 Google trends 關鍵字變數，並藉由最小絕對壓縮挑選機制(Least absolute shrinkage and selection operator)、
彈性網絡(Elastic Net)以及主成分分析法(Principal component analysis)等等變數挑選機制，有效地整合大量的關鍵字資料。實證結果發現，透過適當變數挑選後的 Google trends 關鍵字變數確實可改善美國通貨膨脹率的即時預測表現，並為美國通貨膨脹率提供額外有效的資訊。此外，我們透過台灣的關鍵字資料檢驗，也確認Google trends 關鍵字資料可以幫助台灣通貨膨脹率的即時預測。

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