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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:	[Department of Economics] Theses

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