臺灣博碩士論文加值系統

中文摘要
不論是經濟成長造成物價持續的上漲，抑或是天災、人禍的衝擊而侵蝕貨幣的購買力，依據理論上著名的費雪假說，一般皆認為可以藉由投資行為來對抗通貨膨脹。Irving Fisher (1930) 提出名目利率為預期實質利率與預期通貨膨脹率的總合，換言之為名目利率應隨著通貨膨脹率的變化而調整。將費雪假說擴及到一般金融資產，若其名目報酬具有避險能力，則實質報酬應不受通貨膨脹影響。在實證上費雪假說有相當多的研究與討論，如名目利率是否會與通貨膨脹率同幅度的調整，或是股票、房地產等資產是否能對抗通貨膨脹，但多數都局限於線性模型。
諸如西元1997年的亞洲金融風暴、西元2000年的網路泡沫化及西元2006年的次貸危機等衝擊，都使得總體經濟變數產生結構轉變。另外，資本市場的不完全、投資人的異質性與風險趨避的態度，也都會使得總體經濟變數呈現非線性的走勢。因此本文在以通貨膨脹率的落後期為解釋變數下，建立平滑轉換的費雪方程式，接著在不同轉換變數與不同轉換變數落後期下，衡量兩區間的實質資產報酬率與通貨膨脹率之落後期對資產報酬率的邊際效果，而經濟個體與政策制定者可以輕易的衡量景氣狀態與政策效果。
本文的樣本國家為七大工業國，樣本期間為西元2000年1月至西元2010年9月，資料頻率為月資料。而所選用的標的資產為股票、債券、房地產與黃金，其中股票、房地產與黃金皆為指數型式，並以報酬率的方式呈現，而債券為殖利率。另外，通貨膨脹率以消費者物價指數的變動率為計算方式；轉換變數則有匯率及貨幣供給。
根據本文實證結果指出，在匯率為轉換變數下，加拿大、法國、義大利、英國與美國的股價報酬率存在區間轉換；債券殖利率存在非線性走勢的國家則有加拿大、法國、義大利與美國；而德國、義大利、日本、英國、與美國的房地產報酬率存在平滑轉換的過程。在貨幣供給為轉換變數下，加拿大、法國、義大利、英國與美國的股價報酬率存在區間轉換；債券殖利率存在非線性走勢的國家則有法國與義大利；而德國、義大利與美國的房地產報酬率存在平滑轉換的過程。其次，雖有部分國家的資產報酬率不存在區間轉換，但其通貨膨脹率落後期對資產報酬率的模型之配適度仍優於傳統的線性模型。

Abstract
In 1930, Irving Fisher proposed that nominal interest rates comprise expected real interest rates and expected inflation rates. This proposition is the famous Fisher hypothesis. In other words, nominal interest rates will keep pace with expected inflation rates. Transposing the notion of Fisher hypothesis to other financial assets imply that the nominal returns of assets adjust on a one-to-one basis to inflation rates in a competitive market. While the Fisher hypothesis has been investigated in both theoretical and empirical economics, the models employed in most previous studies are linear forms.
Actually, fatal economic events such as the Asian Financial Crisis in 1997, the Dot-com bubble crash in 2000, the Subprime Mortgage Crisis in 2006, may make financial assets returns have structural changes. In addition, incomplete capital markets, and heterogeneous and risk-averse investors are also the sources of nonlinear adjustment in macroeconomic time series variables. Therefore, this study constructs smooth regime switching Fisher equation with lagged inflation rates to investigate different marginal effects of lagged inflation rates on financial asset returns as lagged exchange rate and lagged money supply in different transition regions.
In performing empirical estimation we choose the G7 countries as sample objects, and the data used are monthly returns of stock, bond, real estate and gold from January 2000 to September 2010. The empirical study shows the following results:
First, choosing lagged exchange rate as the transition variable there exist dynamic smooth switching process of stock returns in Canada, France, Italy, UK and US, and of real estate returns in Germany, Italy, Japan, UK and US. In addition, there are different real asset returns locate in distinct regions in Canada, France, Italy and US.
Second, while lagged money supply is regarded as the transition variable, the results suggest that the stock returns in Canada, France, Italy, UK and US, and the real estate returns in Germany, Italy and US display dynamic smooth switching process. In addition, the real interest rates in France and Italy also have similar process. Overall, the empirical evidences support that the nonlinearity of real returns and nominal returns in most assets in G7 countries.

目錄
中文摘要 I
Abstract III
誌謝辭 V
目錄 VII
表目錄 IX
圖目錄 XI
第壹章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 4
第三節 研究流程與架構 5
第貳章 文獻探討 6
第一節 傳統費雪效果的衡量 6
第二節 資產報酬率與通貨膨脹率之間的關係 10
第三節 非線性模型的相關應用 14
第參章 研究方法與實證模型 17
第一節 單根檢定 17
第二節 逐步迴歸分析 19
第三節 費雪方程式 20
第四節 平滑區間轉換的費雪方程式 22
第五節 線性檢定程序 24
第肆章 實證結果 26
第一節 資料來源與敘述統計 26
第二節 單根檢定 31
第三節 費雪效果 35
第四節 費雪多元迴歸模型 39
第五節 線性檢定與轉換函數型式檢定 45
第六節 平滑區間轉換的費雪方程式 60
第七節 非線性平滑轉換調整過程 70
第伍章 結論與建議 95
第一節 結論 95
第二節 政策建議 97
第三節 未來延伸與建議 99
參考文獻 101
附錄 107


表目錄
表4-1-1資料來源 26
表4-1-2股價報酬率的敘述統計分析 27
表4-1-3債券殖利率的敘述統計分析 27
表4-1-4房地產報酬率的敘述統計分析 28
表4-1-5黃金報酬率的敘述統計分析 28
表4-1-6通貨膨脹率的敘述統計分析 29
表4-1-7匯率的敘述統計分析 29
表4-1-8貨幣供給的敘述統計分析 30
表4-2-1股價報酬率的ADF單根檢定 31
表4-2-2債券殖利率的ADF單根檢定 31
表4-2-3房地產報酬率的ADF單根檢定 32
表4-2-4黃金報酬率的ADF單根檢定 32
表4-2-5通貨膨脹率的ADF單根檢定 33
表4-2-6匯率的ADF單根檢定 33
表4-2-7貨幣供給的ADF單根檢定 34
表4-3-1股價報酬率的費雪效果 35
表4-3-2債券殖利率的費雪效果 36
表4-3-3房地產報酬率的費雪效果 36
表4-3-4黃金報酬率的費雪效果 37
表4-4-1股價報酬率的費雪多元迴歸模型估計結果 39
表4-4-2債券殖利率的費雪多元迴歸模型估計結果 40
表4-4-3房地產報酬率的費雪多元迴歸模型估計結果 41
表4-4-4黃金報酬率的費雪多元迴歸模型估計結果 42
表4-5-1以匯率作為轉換變數下股價報酬率的線性檢定 45
表4-5-2以匯率作為轉換變數下債券殖利率的線性檢定 46
表4-5-3以匯率作為轉換變數下房地產報酬率的線性檢定 47
表4-5-4以匯率作為轉換變數下黃金報酬率的線性檢定 48
表4-5-5股價報酬率－轉換函數型式檢定（匯率） 49
表4-5-6債券殖利率－轉換函數型式檢定 （匯率） 50
表4-5-7房地產報酬率－轉換函數型式檢定（匯率） 50
表4-5-8黃金報酬率－轉換函數型式檢定（匯率） 51
表4-5-9以貨幣供給作為轉換變數下股價報酬率的線性檢定 52
表4-5-10以貨幣供給作為轉換變數下債券殖利率的線性檢定 53
表4-5-11以貨幣供給作為轉換變數下房地產報酬率的線性檢定 54
表4-5-12以貨幣供給作為轉換變數下黃金報酬率的線性檢定 55
表4-5-13股價報酬率－轉換函數型式檢定（貨幣供給） 56
表4-5-14債券殖利率－轉換函數型式檢定（貨幣供給） 57
表4-5-15房地產報酬率－轉換函數型式檢定（貨幣供給） 57
表4-5-16黃金報酬率－轉換函數型式檢定（貨幣供給） 58
表4-6-1股價報酬率－STARX-FE模型估計結果（匯率） 60
表4-6-2債券殖利率－STARX-FE模型估計結果（匯率） 61
表4-6-3房地產報酬率－STARX-FE模型估計結果（匯率） 63
表4-6-4股價報酬率－STARX-FE模型估計結果（貨幣供給） 65
表4-6-5債券殖利率－STARX-FE模型估計結果（貨幣供給） 66
表4-6-6房地產報酬率－STARX-FE模型估計結果（貨幣供給） 68


圖目錄
圖1-3-1研究流程圖 5
圖4-7-1加拿大股價報酬率的LSTARX-FE模型之轉換函數 71
圖4-7-2法國股價報酬率的ESTARX-FE模型之轉換函數 72
圖4-7-3義大利股價報酬率的ESTARX-FE模型之轉換函數 73
圖4-7-4英國股價報酬率的ESTARX-FE模型之轉換函數 74
圖4-7-5美國股價報酬率的ESTARX-FE模型之轉換函數 75
圖4-7-6加拿大債券殖利率的LSTARX-FE模型之轉換函數 76
圖4-7-7法國債券殖利率的LSTARX-FE模型之轉換函數 77
圖4-7-8義大利債券殖利率的ESTARX-FE模型之轉換函數 78
圖4-7-9美國債券殖利率的LSTARX-FE模型之轉換函數 79
圖4-7-10德國房地產報酬率的ESTARX-FE模型之轉換函數 80
圖4-7-11義大利房地產報酬率的ESTARX-FE模型之轉換函數 81
圖4-7-12日本房地產報酬率的LSTARX-FE模型之轉換函數 82
圖4-7-13英國房地產報酬率的LSTARX-FE模型之轉換函數 83
圖4-7-14美國房地產報酬率的ESTARX-FE模型之轉換函數 84
圖4-7-15加拿大股價報酬率的LSTARX-FE模型之轉換函數 85
圖4-7-16法國股價報酬率的LSTARX-FE模型之轉換函數 86
圖4-7-17義大利股價報酬率的ESTARX-FE模型之轉換函數 87
圖4-7-18英國股價報酬率的LSTARX-FE模型之轉換函數 88
圖4-7-19美國股價報酬率的LSTARX-FE模型之轉換函數 89
圖4-7-20法國債券殖利率的LSTARX-FE模型之轉換函數 90
圖4-7-21義大利債券殖利率的ESTARX-FE模型之轉換函數 91
圖4-7-22德國房地產報酬率的LSTARX-FE模型之轉換函數 92
圖4-7-23義大利房地產報酬率的ESTARX-FE模型之轉換函數 93
圖4-7-24美國房地產報酬率的LSTARX-FE模型之轉換函數 94
附圖1：各國股價報酬率的時間序列走勢 107
附圖2：各國債券殖利率的時間序列走勢 108
附圖3：各國房地產報酬率的時間序列走勢 109
附圖4：黃金報酬率的時間序列走勢 110
附圖5：各國通貨膨脹率的時間序列走勢 111

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