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研究生：	蔡宛軒 Tsai, Wan-Hsuan
論文名稱：	新興市場債券利差與基本經濟因子之間的資訊傳遞-以拉丁美洲為例 Information transmission between sovereign debt spreads and economic fundamentals-The case of Latin America
指導教授：	王澤世 Wang, Tza-Shr
學位類別：	碩士 Master
系所名稱：	管理學院 - 財務金融研究所 Graduate Institute of Finance
論文出版年：	2012
畢業學年度：	100
語文別：	英文
論文頁數：	85
中文關鍵詞：	新興市場、新興市場債券利差、單根檢定、共整合檢定、向量誤差修正模型、衝擊反應分析、預測誤差變異數分解
外文關鍵詞：	Emerging market, Sovereign spread, Unit root test, Cointegration test, Vector Error Correction model, Impulse response, Forecast error variance decompositions
相關次數：	點閱：152 下載：1
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本研究主要探討五個拉丁美洲國家(阿根廷、巴西、智利、墨西哥和委內瑞拉)的新興市場債券利差與其基本經濟因子間的資訊傳遞。本文藉由時間序列的單根檢定、交叉相關、共整合檢定和向量誤差修正模型檢定債券利差與基本經濟因子的長短期關係，並以衝擊反映分析和預測誤差之變異分解觀察變數間短期動態過程。
本研究結果發現，不同國家的新興市場債券利差和十一種基本經濟因子間，不具有相同的關係，而各個基本經濟變數對不同國家的新興市場債券利差的影響方向以及影響的程度也不相同。實證結果顯示：阿根廷過去的新興市場債券利差為預測目前消費者物價指數之因子;巴西的消費者物價指數為新興市場債券利差的領先因子，而利差為此國之貿易開放比率、強勢貨幣之新興市場債券的有效期間、美國十年政府公債利率的領先因子;墨西哥的消費者物價指數為新興市場債券利差的領先因子，且在短期具有顯著正向關係；智利與委內瑞拉的新興市場債券利差為美國十年公債利率的領先因子。

This paper examines the information transmission between sovereign debt spreads and economic fundamentals in the case of five Latin American countries: Argentina, Brazil, Chile, Mexico and Venezuela. We can capture the long-term and short-term relationships between emerging market spreads and fundamental variables by assessing time-series Vector Error Correction Model approach of stationary test, cross correlogram test, cointegration test, Granger causality test, impulse response test and variance decompositions analysis,.
Our results show that with the quarterly sample of EMBI spread and eleven determinants, sovereign spreads play the different roles and are not exclusively determined by the same variables in different countries. Besides, for each determinant, the direction and the degree of the effect vary among the countries in our sample. It has proven that for Argentina, the past value of EMBI can predict the current value of CPI. For Brazil, CPI is the leading factor for EMBI while EMBI is the leading factor for trade openness, effective time to maturity and U.S. ten-year government bond rate. For Mexico, CPI is the leading factor for EMBI and has the positive significant explanation in the short run. For Chile and Venezuela, EMBI is the leading factor for U.S. ten-year government bond rate.

Content
摘要 	I
Abstract 	II
Chpater1. Introduction 	1
Chpater2. Literature Review	4
Chapter3. Methodology 	8
3.1 Unit root test 	8
3.2 Cross Correlogram 	10
3.3 Cointergration Test 	11
3.4 Vector Error Correlation Model (VECM) 	14
3.5 Granger Causality Test 	15
3.6 Impulse response Analysis 	16
3.7 Forecast Error Variance Decomposition 	18
Chapter4. Empirical results 	20
4.1 Data and descriptive of analysis 	20
4.1.1 The sovereign Spread and the JP Morgan EMBI 	20
4.1.2 Choice of Variables and Data Description 	21
4.1.3 Data and descriptive of analysis 	30
4.2 Time series result 	32
4.2.1 Unit root test 	32
4.2.2 Cross Correlogram 	34
4.2.3 Cointergration Test 	36
4.2.4 VECM empirical results 	38
4.2.5 Granger Causality 	52
4.2.6 Impulse response 	59
4.2.7 Variance decomposition 	67
Chapter5. Conclusions and Suggestions 	72 
Reference 	75
Appendix 1: Graph of countries variables 	78
Appendix 2: Results of cross correlation 	81

List of Tables
Table 1  Introduction of EMBI	21
Table 2  Expected sign between EMBI spread and variables	26
Table 3  The data	28
Table 4  Data abbreviation	29
Table 5  Summary statistic	31
Table 6.1 Test for stationary (variable in levels). Augmented Dickey Fuller test	33 
Table 6.2 Test for stationary (variable in difference). Augmented Dickey Fuller test	33
Table 7  Data selection of each country	36
Table 8  Johansen cointegration test for nonstationary variables of five countries	39
Table 9  Estimation of error correction term	41
Table 10 Results from error correction terms	43
Table 11 Results from vector error correction model (VECM)	49
Table 12 Results of Granger Causality	56
Table 13 Variance decomposition	69

List of Figures
Figure 1  Research framework	3
Figure 2  Classification of variables	22
Figure 3  Impulse reponses of EMBI to innovation for countries 	62





                                    

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