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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/99637


    Title: 大數據預測通貨膨脹率
    Forecasting Inflation with Big Data
    Authors: 廖珈燕
    Liao, Jia Yan
    Contributors: 林馨怡
    Lin, Hsin Yi
    廖珈燕
    Liao, Jia Yan
    Keywords: Google trends 關鍵字
    通貨膨脹率
    Google trends
    Inflation
    Date: 2016
    Issue Date: 2016-08-03 10:27:27 (UTC+8)
    Abstract: 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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    Description: 碩士
    國立政治大學
    經濟學系
    103258016
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0103258016
    Data Type: thesis
    Appears in Collections:[經濟學系] 學位論文

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