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研究生(外文):Yu-Tou Hsieh
論文名稱(外文):The Great Moderation in Taiwan
指導教授(外文):Nai-Fong Kuo
外文關鍵詞:Great ModerationFinanceVARMS-VAR
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經濟「大平穩」(Great Moderation)議題主要發現美國與多數國家間自1980年代中期之後經濟波動具有長期平穩趨勢,諸如實質GDP成長率、通貨膨脹率、失業率等重要經濟變數皆可發現週期波動有平穩趨勢,McConnell and Perez-Quiros (2000)與Blanchard and Simon(2001)較先觀察此相關主題之研究,爾後學者稱此一現象為經濟大平穩現象(Great Moderation)。
導致經濟大平穩現象的原因,多方研究指出許多可能因素,有近年存在較少的負向外部衝擊之「好運說」(Good Luck)、資訊科技發展與庫存管理的改進使產出平穩、產出內部組成分結構的波動狀態的轉變致使國家產出成長率波動趨於穩定、為使通膨穩定所使用的貨幣政策與金融創新假說等,但主導角色仍爭論至今,本研究以金融面向做為依歸,探討金融市場發展與金融創新對我國經濟波動之影響狀況。而近期聯合國所公佈之創意經濟報告(UN(2008))相關概念與文建會所提出之「文化創意草案」皆重視創意經濟(Creative Economy)所創造之經濟產值及其具有之獨特性等相關概念不謀而合,故本研究藉由觀察多國之創意出口與經濟波動之關聯判斷是否國家發展創意相關產業出口對一國之經濟平穩狀況有所助益。
The Great Moderation is an expression in use to describe the decline in real GDP growth, inflation and other important economical variables’ volatility of a country since the mid-1980s. McConnell and Perez-Quiros (2000) and Blanchard and Simon(2001) were among the early to point at this phenomena which later became known as the Great Moderation.

There has been much significant research on the factors behind this phenomenon like better monetary police, the improvement of inventory control, the smaller and less frequent shocks hitting the economy ‘good-luck hypothesis’, the change in the composition of output and financial innovation. We want to know the fluctuation of output growth et al. in Taiwan, and find the relation between volatility and financial improvement. Furthermore, we want to know the improvement of creative industrial export of a country will or will not to help decline the economical volatility.
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 5
第三節 研究架構 5
第二章 文獻探討 7
第一節 經濟大平穩現象相關文獻 7
第二節 波動度計算相關文獻 15
第三節 馬可狀態轉換向量自我迴歸(MS-VAR)模型相關文獻 16
第三章 我國經濟平穩狀況及相關議題觀察 19
第四章 研究方法 27
第一節 波動度之衡量 27
第二節 實證模型 27
第五章 實證研究 42
第一節 敘述統計 42
第二節 單根檢定 44
第三節 向量自我迴歸(VAR)模型 48
第四節 Granger因果關係檢定 52
第五節 衝擊反應函數分析 53
第六節 預測誤差變異拆解 57
第七節 馬可夫狀態轉換向量自我迴歸(MS-VAR)模型 60
第六章 結論 64
參考文獻 66
附錄 70
附錄一 創意產業與GDP成長率波動之相關性 70
附錄二 Lowess平滑法(Lowess Smooth) 78
附錄三 GDP細項組成波動相關資訊觀察 79
附錄四 考量貿易波動狀況之模型檢定結果 83
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