實質國內生產毛額主要是衡量國家的經濟狀況，如果能準確預測景氣走勢，將有利於政府實施正確的政策，帶動經濟與貿易發展。實證研究上，對實質國內生產毛額是否為單根無確切的結論，故以OECD國家為研究的對象，運用傳統單變量單根檢定和追蹤資料單根檢定進行分析，實證結果大部分得出接受實質國內生產毛額單根。

近年來的經濟事件的衝擊，對實質國內生產毛額的資料產生巨幅波動，故模型中要納入結構性變化這項因素。因此本文引用 Lee et al. (2015) 提出的BCIPS檢定，此檢定設定以平滑性的傅立葉函數捕捉結構性變化和多因子表示橫斷面相依，實證結果為接受實質國內生產毛額單根，其含義為當經濟衝擊發生之後，實質國內生產毛額無法恢復到穩定產出路徑，意味著政府執行穩定政策的效果有限。

Real GDP is a major measure of national economy. If researchers can estimate business trend accurately, then government will implement correct policy to push ahead with the development of economics and trade. In fact, whether Real GDP is unit root has conflicting conclusion. This paper applies univariate unit root tests and panel unit root tests to analyze Real GDP. Most of tests point out that Real GDP don't reject unit root.

Because economic events have the great effect on Real GDP, it's data fluctuate drastically. Some papers suggested that the model should be adopted in structural breaks. Hence, this paper considers mainly the breaks and cross-sectional dependence augmented version of the IPS test (BCIPS test), proposed by Lee et al. (2015), to analyze Real GDP in 20 OECD countries. The conclusion is that Real GDP don't reject unit root. Regarding the policy, the existence of unit root in Real GDP doubts about the appropriateness of running stabilization policies since there is no well-defined steady output path to which the economy would revert after the occurrence of a shock.

論文審定書 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .i
論文公開授權書 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . ii
摘要 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .iii
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . .iv
圖次 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . vii
表次 . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . .viii
1 緒論 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 研究動機及目的 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 研究架構 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 文獻回顧 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1 回顧單根檢定 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1.1 DF單根檢定 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1.2 ADF單根檢定 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1.3 PP單根檢定 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1.4 KPSS單根檢定 . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1.5 IPS 追蹤資料單根檢定 . . . . . . . . . . . . . . . . . . . . . .9
2.1.6 CIPS 追蹤資料單根檢定 . . . . . . . . . . . . . . . . . . . . .9
2.1.7 LLC 追蹤資料單根檢定 . . . . . . . . . . . . . . . . . . . . . 12
2.2 實質國內生產毛額相關實證文獻 . . . . . . . . . . . . . . . . . . . 15
3 研究方法 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .16
3.1 理論模型 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.2 多因子單根檢定 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.3 以 BCADF 為基礎的追蹤資料單根檢定 . . . . . . . . . . . . . . 21
3.4 單根檢定以單一因子表示 . . . . . . . . . . . . . . . . . . . . . . . . 22
3.5 具序列相關的殘差項 . . . . . . . . . . . . . . . . . . . . . . . . . . . .23
4 實證分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.1 資料來源說明 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.2 傳統單根檢定結果 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27
4.3 第一代追蹤資料單根檢定結果 . . . . . . . . . . . . . . . . . . . . . .29
4.4 CIPS 和 BCIPS 追蹤資料單根檢定結果 . . . . . . . . . . . . . . .30
5 結論 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
參考文獻 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33
附錄 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

中文部分
1. 王孟倫 (2013), 消費-所得比的定態性實證分析-以 OECD 國家為例。國立中山大學經濟研究所碩士論文。
2. 李慶男 (2006), 時間序列講義 Chapter 21。高雄市, 國立中山大學經濟研究所。
3. 陳姩彣 (2013), 考慮平滑性變化的實質 GDP 定態性-OECD 國家實證研究。國立中山大學經濟學研究所碩士論文。
4. 葉華容和蔡依恬 (2015), 國際經濟情勢雙週報。中華經濟研究院, 第1827期, 頁1-73。
5. 楊奕農 (2009), 時間序列分析: 經濟與財務上之應用。第二版, 台北市, 雙葉書廊。
6. 賴景昌 (2004), 總體經濟學。第二版, 台北市, 雙葉書廊。
英文部分
1. Aslanidis, N. and Fountas, S. (2012), Is Real GDP Stationary? Evidence from a Panel Unit Root Test with Cross-Sectional Dependence and Historical Data. Working Paper.
2. Ben-David, D. and Papell, D.H. (1995), The Great Wars, the Great Crash, and Steady State Growth: some New Evidence about an old Stylized fact. Journal of Monetary Economics, 36: 453-475.
3. Banerjee, A. (1999), Panel Data Unit Roots and Cointegration: An overview. Oxford Bulletin of Economics and Statistics, 61: 607-629.
4. Breitung, J. and Das, S. (2003), Panel Unit Root Tests under Cross Sectional Dependence. manuscript, Institute of Econometrics, University of Bonn.
5. Bai, J. and Ng, S. (2004), A PANIC Attack on Unit Roots and Cointegration. Econometrica, 72: 1127-1177.
6. Chang, Y. (2002), Nonlinear IV Unit Root Tests in Panels with Cross-Sectional Dependence. Journal of Econometrics, 110: 261-292.
7. Choi, I. and Chue, T. (2007), Subsampling Hypothesis Tests for Nonstationary Panels with Applications to Exchange Rates and Stock Prices. Journal of Applied Econometrics, 22: 233-264.
8. Dickey,D. and Fuller, W. (1979), Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the American Statistical Association, 74: 427-431.
9. Darne, O. (2009), The Uncertain Unit Root in real GNP: A Re-examination. Journal of Macroeconomics, 31: 153-166.
10. Friedman, M. (1968), The role of monetary policy. American Economic Review, 58: 1-17.
11. Giulietti, M., Otero, J. and Smith, J. (2009), Testing for Stationarity in Heterogeneous Panel Data in the Presence of Cross-Section Dependence. Journal of Statistical Computation and Simulation, 79 (2): 195-203.
12. Im, K., Pesaran, H., and Shin, Y. (2003), Testing for Unit Roots in Heterogeneous Panels. Journal of Econometrics, 115: 53-74.
13. Kydland, F.E. and Prescott, E.C. (1982), Time to build and aggregate fluctuations. Econometrica, 50: 1345-1370.
14. Kwiatkowski, D., Phillips, P.C.B., Schmidt, P., and Shin, Y. (1992), Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root. Journal of Econometrics, 54: 159-178.
15. Long, J.B. and Plosser, C.I. (1983), Real business cycle. Journal of Political Economy, 91: 39-69.
16. Levin, A. and Lin, F. (1992), Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties. Discussion Paper, University of California, San Diego.
17. Levin, A., Lin, F. and Chu, C. (2002), Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties. Journal of Econometrics, 108: 1-24.
18. Lee, C.N., Wu, J.L. and Yang, L. (2015), A Simple Panel Unit Root Test with Smooth Breaks in the Presence of a Multifactor Error Structure. Oxford Bulletin of Economics and Statistics, Institute of Economics, National Sun
Yat-sen University.
19. Maddala, G.S. and Wu, S. (1999), A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test. Oxford Bulletin of Economics and Statistics, 61: 631-652.
20. Moon, H.R. and Perron, B. (2004), Testing for a unit root in panels with dynamic factors. Journal of Econometrics, 122: 81-126.
21. Nelson, C. and Plosser, C. (1982), Trend and Random Walks in Macroeconomics Time Series: Some Evidence and Implication. Journal of Monetary Economics 10: 139-162.
22. Noriega, A.E. and Ramirez-Zamora, A. (1999), Unit Roots and Multiple Structural Break in Real Output: How Long does an Economy Remain Stationary? Estudios Economicos, 14 (2): 164-188.
23. Narayan, P.K. and Narayan, S. (2010), Are Business Cycles Stationary Fluctuations around a Deterministic Trend? Empirical Evidence from 79 Developing Countries. International Review of Applied Economics, 24 (6): 649-664.
24. Perron, P. (1989), The Great Crash, the Oil Price Shock, and The Unit Root Hypothesis. Econometrica, 57, 1361-1401.
25. Phillips, P.C.B and Perron, P. (1988), Testing for a Unit Root in Time Series Regression. Biometrika 75: 335-346.
26. Phillips, P.C.B. and Sul, D. (2003), Dynamic Panel Estimation and Homogeneity Testing under Cross-Section Dependence. Econometrics Journal, 6:217-259.
27. Pesaran, M.H. (2007), A Simple Panel Unit Root Test in the Presence of Cross-Section Dependence. Journal of Applied Econometrics, 22: 265-312.
28. Pesaran M.H., Smith, L.V. and Yamagata, T. (2009), A Panel Unit Root Test in the Presence of a Multifactor Error Structure. Working paper, University of Cambridge.
29. Pesaran M.H., Smith, L.V. and Yamagata, T. (2012), A Panel Unit Root Test in the Presence of a Multifactor Error Structure. Working paper, University of Cambridge.
30. Pesaran, M.H., Smith, L.V. and Yamagata, T. (2013), Panel Unit Root Tests in the Presence of a Multifactor Error Structure. Journal of Econometrics, 175: 94-115.
31. Rapach, D. (2002), Are Real GDP Levels Nonstationary? Evidence from Panel Data Tests. Southern Economic Journal, 68 (3): 473-495.
32. Romero-Avila, D. (2009), Multiple Breaks, Terms of Trade Shocks and the Unit Root Hypothesis for African Per Capita Real GDP. World Development 37 (6): 1051-1068.
33. Said, S.E. and Dickey, D.A. (1984), Testing for Unit Roots in Autoregressive-Moving Average Models of Unknown Order. Biometrika, 71: 599-608.
34. Smith, L.V., Leybourne, S., Kim, T-H and Newbold, P. (2004), More Powerful Panel Data Unit Root Tests with an Application to Mean Reversion in Real Exchange Rates. Journal of Applied Econometrics, 19: 147-170.