本文以Stock and Watson自1989年陸續提出以狀態空間方法的動態因子模型估計共同波動性，並結合Aruoba et al. (2010)兩階段動態因子模型分析方法。探討隨著不同期間，跨國景氣波動相關性是否會有所改變。
本研究證實以下三個結論。(1)地域性所造成的區域經濟，使跨國間的景氣波動具有顯著相關性。(2) 區域或全球性共同衝擊會使跨國景氣波動相關性提高。(3) 不同經濟發展程度的國家面對全球性共同衝擊時，危機所影響的深度與期間長度會有所不同。

In this thesis, we use the dynamic factor model in state space, proposed by Stock and Watson (1989), to estimate the fluctuations of common factor by using lots of macroeconomic variables. Besides, with the combination of two stage dynamic factor analysis model which is proposed by Aruba et. al (2010), we want to discuss the possibility for the correlation of economic fluctuations across countries to change with different time periods.
The thesis verifies the following three conclusions: First, the correlations of the economic fluctuations across countries are significant due to the regional economics. Second, the global or regional common shocks will increase the correlations of the economic fluctuations across countries. Finally, developed countries and emerging countries response differently during the Financial Tsunami from 2008 to 2009.

誌 謝 .......................................................................................................................................... ii
摘 要 ......................................................................................................................................... iii
目 錄 .......................................................................................................................................... v
圖 次 ..........................................................................................................................................vi
表 次 ......................................................................................................................................... vii
第一章 緒論 ............................................................................................................................. 1
第一節 研究背景 ................................................................................................................. 1
第二節 研究動機與目的 ..................................................................................................... 1
第三節 本文架構 ................................................................................................................. 2
第二章 文獻回顧 ..................................................................................................................... 4
第一節 國際景氣循環 ......................................................................................................... 4
第二節 動態因子模型發展演變 ......................................................................................... 5
第三章 理論模型 ..................................................................................................................... 8
第一節 HP濾波 .................................................................................................................. 8
第二節 選擇最適模型之因子落後期數 ............................................................................. 8
第三節 因子模型 ................................................................................................................. 9
第四節 狀態空間模型 ....................................................................................................... 12
第五節 動態因子模型 ....................................................................................................... 20
第四章 結論與建議 ............................................................................................................... 24
第一節 資料來源 ............................................................................................................... 24
第二節 資料說明 ............................................................................................................... 24
第三節 模型矩陣 ............................................................................................................... 25
第四節 國家因子(country factors) ............................................................................. 27
第五節 各國間係數矩陣 ................................................................................................... 30
第六節 不同時期跨國景氣同步性的變化 ....................................................................... 31
vi
第七節 2000年代各國經濟波動 ...................................................................................... 37
第五章 結論與建議 ............................................................................................................... 42
第一節 研究結論 ............................................................................................................... 42
第二節 未來研究方向與建議 ........................................................................................... 44
參考文獻 .................................................................................................................................... 45

1. Artis, M.J. and W. Zhang. (1999). "Further Evidence on the International Business Cycle and the Erm: Is There a European Business Cycle?" Oxford Economic Papers, 51, 120-32.
2. Arouba, S. B., F. X. Diebold, M. A. Kose, and M. E. Terrones (2010), "Globalization, the business cycle, and macroeconomic monitoring." NBER working paper, No. 16264.
3. Bai, J. and S. Ng. (2002). "Determining the Number of Factors in Approximate Factor Models." Econometrica, 70(1), 191-221.
4. Bates, J.M. and C.W.J. Granger. (1969). "The Combination of Forecasts." Operational Research Quarterly, 20(4), 451-68.
5. Bernanke, B.S. and J. Boivin. (2003). "Monetary Policy in a Data-Rich Environment." Journal of Monetary Economics, 50(3), 525-46.
6. Bernanke, B.S., J. Boivin and P. Eliasz. (2005). "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach." Quarterly Journal of Economics, 120, 387-422.
7. Boivin, J. and M. Giannoni. (2008). "Global Forces and Monetary Policy Effectiveness," NBER working paper, No. 13736
8. Boivin, J. and S. Ng. (2006). "Are More Data Always Better for Factor Analysis?" Journal of Econometrics, 132(1), 169-94.
9. Burns, A.F. and W.C. Mitchell. (1946). " Measuring Business Cycles. "National Bureau of Economic Research, New York.
10. Canova, F. and H. Dellas. (1993). "Trade Interdependence and the International Business Cycle." Journal of International Economics, 34(1-2), 23-47.
11. Chamberlain, G. and M. Rothschild. (1984). "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Econometica, 51, 1281-1304.
12. Chauvet, M. and C. Yu. (2006). "International Business Cycles: G7 and OECD Countries." Economic Review, 43-54.
13. Clark, T.E. and K. Shin (1998). "The Sources of Fluctuations within and across Countries." Federal Reserve Bank of Kansas City, Working Paper No. 98-104.
14. Engle, R. and M. Watson. (1981). "A One-Factor Multivariate Time Series Model of Metropolitan Wage Rates." Journal of the American Statistical Association, 76(376), 774-81.
15. Geweke, J. (1977). "The Dynamic Factor Analysis of Economic Time Series." in Latent variables in socio-economic models, eds. D. J. Aigner and A. S. Goldberger, Amsterdam: North–Holland.
16. Kim, J.O. and C.W. Mueller. (1978). Factor Analysis: Statistical Methods and Practical Issues. Beverly Hills, CA: Sage.
17. Kose, M.A., C. Otrok and C.H. Whiteman. (2003)."International Business Cycles: World, Region, and Country-Specific Factors." The American Economic Review, 93(4), 1216-39.
18. Kose, M.A., C. Otrok and C.H. Whiteman. (2008). "Understanding the Evolution of World Business Cycles." Journal of International Economics, 75(1), 110-30.
19. Krugman, P.R. (1991). Geography and Trade. Cambridge, MA: MIT Press.
20. MacCallum, R.C., Widaman, K.F., Zhang, S., and Hong, S. (1999). "Sample size in factor analysis. " Psychological Methods, 4, 84-99.
21. Moneta, F. and R. Ruffer. (2009). "Business Cycle Synchronisation in East Asia." Journal of Asian Economics, 20(1), 1-12.
22. Sargent, T.J. and C.A. Sims. (1977). "Business Cycle Modeling without Pretending to Have Too Much a Priori Economic Theory." In Sims, C.A. (ed) New Methods in Business Research, Minneapolis: Federal Reserve Bank of Minneapolis.
23. Stock, J.H. and M.W. Watson. (1988), "A Probability Model of the Coincident Economic Indicators." NBER Working Paper, No. 2772.
24. Stock, J.H. and M.W. Watson. (1989). "New Indexes of Coincident and Leading Economic Indicators," NBER Macroeconomics Annual, 351–393.
25. Stock, J.H. and M.W. Watson. (1998). "Diffusion Indexes," NBER Working Paper, No. 6702.
26. Stock, J.H. and M.W. Watson. (1999). "Forecasting Inflation," Journal of Monetary Economics,44,293-335.
27. Stock, J.H. and M.W. Watson. (2002). "Macroeconomic forecasting using diffusion indexes." Journal of Business and Economic Statistics, 20, 147-162.
28. Stock, J.H. and M.W. Watson. (2007). "Why Has US Inflation Become Harder to Forecast?" Journal of Money, Credit and Banking, 39, 3-33.
29. Stock, J.H. and M.W. Watson. (2008). "Phillips Curve Inflation Forecasts," Presented at the Federal Reserve Bank of Boston’s 53 rd Economic Conference, Understanding Inflation and the Consequences for Monetary Policy: A Phillips Curve Retrospective. June 10, 2008.
30. 李振宇(2009)，「外匯市場之預測與分析」，暨南大學國際企業學系碩士論文。
31. 徐士勛、管中閔與羅雅惠(2005)，「以擴散指標為基礎之總體經濟預測」，《台灣經濟預測與政策》，36:1，頁1-28。
32. 黃裕烈、徐之強與陳惠薇(2005)，「景氣基準循環指數之檢討與修訂」，《經濟論文叢刊》，33:4，頁295-319。
33. 陳雅玫、高志祥與徐之強(2004)，「多變量動態因子預測方法應用之研究」，《中華民國台灣地區國民經濟動向統計季報》，104，頁52-67。
34. 劉名寰、郭迺鋒、林崑峰、林祝吉(2009)，「國際經濟因子對台灣貨幣政策傳遞效果的影響：結構因子擴充向量自迴歸模型」，台灣經濟學會研討會。
35. 閻靜瑤(2009)，「台灣經貿伙伴景氣指標聯動關係之探討－VAR模型分析」，世新大學經濟研究所碩士論文。