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題名 兩群時間序列Granger領先關係之新檢定方法
New Tests of Granger Causality for two Groups of Time Series
作者 張欣惠
貢獻者 洪英超
張欣惠
關鍵詞 向量自我回歸模型
Granger 領先關係
Wald test
檢定力
日期 2013
上傳時間 6-Aug-2014 11:39:53 (UTC+8)
摘要 驗證兩群時間序列間之領先關係不但在經濟的領域上為重要的課題之一，在其他領域也被廣泛地應用。由於傳統檢定此多變量常態分配之平均向量的Uniformly most powerful(UMP) test 通常不存在，因此在本文中介紹一些新檢定統計量，用於檢定多變量Granger 領先關係檢定，判斷兩群時間序列間是否存在領先關係，並於定態(stationary) vector autoregression (VAR) 模型為背景下進行。這些新檢定統計量之接受域臨界值可以從多變量常態分配中計算或估計出，因此不論在操作或執行上皆相當容易，除此之外，在一些參數限制下，這些新檢定統計量皆有各自的使用時機，使得與傳統Wald test相比有較好之檢定力。最後，藉由美國兩組經濟指標資料進行實證分析，評估本研究建議之新檢定統計量。
參考文獻 Dekimpe, M. G., & Hanssens, D. M. (1995). The persistence of marketing effects on sales, Marketing Science, 14, 1-21.

Dekimpe, M. G., & Hanssens, D. M. (1999). Sustained spending and persistent response : A new look at long-term marketing probability, Journal of Marketing research, 36, 397-412.

Dufour, J. M., & Renault, E. (1998). Short-run and lonf-run causality in time series theory. Econometrica, 66, 1099-1125

Genz, A., Bretz, F., Miwa, T., Mi, X., Leisch, F., Scheipl, F., & Hothorn, T. (2014). mvtnorm:Multivariate Normal and t Distributions. R package version 0.9-9997. Retrieved from http://CRAN.R-project.org/package=mvtnorm

Geweke, J., Meese, R., & Dent, W. (1983). Comparing alternative tests of causality in temporal systems. Journal of Econometrics, 21, 161-194.

Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424-438.

Haugh, L. D. (1976). Checking the independence of two covariance-stationary time series: A univariate residual cross-correlation approach. Journal of the American Statistical Association, 71, 378-385.

Hung, Y. C., & Tseng, N. F. (2012). Extracting informative variables in the validation of two-group causal relationship. Computational Statistics, 28(3), 1151-1167.

Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Berlin:Springer-Verlag.

Murdoch, D., Chow, E. D.(2013). ellipse: Functions for drawing ellipses and ellipse-like confidence regions. R package version 0.3-8.Retrieved from http://CRAN.R-project.org/package=ellipse


Pierce, D. A., & Haugh, L. D. (1977). Causality in temporal systems: Characterization and a survey. Journal of econometrics, 5(3), 265-293.

Ripley, B., Venables, B., Bates, D.M., Hornik, K., Gebhardt A, Firth, D. (2014). MASS: Support Functions and Datasets for Venables and Ripley`s MASS. R package version 7.3-33. Retrieved from http://CRAN.R-project.org/package=MASS

Sims, C. A. (1972). Money, income, and causality. The American Economic Review, 62(4), 540-552.

Sims, C. A. (1980). Macroecomonics and reality. Journal of Econometrica, 48, 1-48.

Srinivasan, S. and Bass, F.M (2001). Diagnosing competitive responsiveness: Disentangling retailer-induced and manufacturer induced actions. Paper presented at the MSI Conference on competitive responsiveness, Boston.

Takada, H., & Bass, F. M. (1998). Multiple time series analysis of competitive marketing behavior. Journal of Business Research, 43(2), 97-107.

Trapletti, A., Hornik, K., LeBaron, B. (2013). tseries: Time series analysis and computational finance. R package version 0.10-32. Retrieved from http://CRAN.R-project.org/package=tseries

Tsai, M. T. M., & Sen, P. K. (1993). On the local optimality of optimal linear tests for restricted alternatives. Statistica Sinica, 3, 103-115.
描述 碩士
國立政治大學
統計研究所
101354012
102
資料來源 http://thesis.lib.nccu.edu.tw/record/#G1013540121
資料類型 thesis
dc.contributor.advisor 洪英超zh_TW
dc.contributor.author (Authors) 張欣惠zh_TW
dc.creator (作者) 張欣惠zh_TW
dc.date (日期) 2013en_US
dc.date.accessioned 6-Aug-2014 11:39:53 (UTC+8)-
dc.date.available 6-Aug-2014 11:39:53 (UTC+8)-
dc.date.issued (上傳時間) 6-Aug-2014 11:39:53 (UTC+8)-
dc.identifier (Other Identifiers) G1013540121en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/68229-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計研究所zh_TW
dc.description (描述) 101354012zh_TW
dc.description (描述) 102zh_TW
dc.description.abstract (摘要) 驗證兩群時間序列間之領先關係不但在經濟的領域上為重要的課題之一，在其他領域也被廣泛地應用。由於傳統檢定此多變量常態分配之平均向量的Uniformly most powerful(UMP) test 通常不存在，因此在本文中介紹一些新檢定統計量，用於檢定多變量Granger 領先關係檢定，判斷兩群時間序列間是否存在領先關係，並於定態(stationary) vector autoregression (VAR) 模型為背景下進行。這些新檢定統計量之接受域臨界值可以從多變量常態分配中計算或估計出，因此不論在操作或執行上皆相當容易，除此之外，在一些參數限制下，這些新檢定統計量皆有各自的使用時機，使得與傳統Wald test相比有較好之檢定力。最後，藉由美國兩組經濟指標資料進行實證分析，評估本研究建議之新檢定統計量。zh_TW
dc.description.tableofcontents 第一章 導論 1
第二章 Granger Non-causality 檢定 3
第一節 向量自我回歸模型 3
第二節 模型選擇與定態檢定 4
第三節 多變量領先關係檢定 6
2.3.1 多變量領先關係 6
2.3.2 Wald檢定統計量 8
2.3.3 Wald檢定統計量之檢定力 9
第四節 新檢定統計量 10
2.4.1 檢定統計量M 10
2.4.2 檢定統計量 M_s 11
2.4.3 檢定統計量 B 12
2.4.4 檢定統計量 B_s 13
第三章 實際資料分析與模擬 14
第一節 實例分析 14
3.1.1 定態檢定與模型選擇 14
3.1.2 領先關係檢定 15
第二節 檢定統計量之拒絕域(接受域)與檢定力 16
3.2.2 統計量M之接受域 17
3.2.3 統計量 M_s 之接受域 17
3.2.4 統計量B 之接受域 18
3.2.5 統計量 B_s 之接受域 18
3.2.6 檢定統計量之接受域比較 19
第三節 檢定力 20
第四節 小樣本之接受域與檢定力 24
3.4.1 領先關係檢定 24
3.4.2 小樣本接受域與檢定力 25
第五節 模擬研究 29
參考文獻 36		zh_TW
dc.format.extent 905273 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G1013540121en_US
dc.subject (關鍵詞) 向量自我回歸模型zh_TW
dc.subject (關鍵詞) Granger 領先關係zh_TW
dc.subject (關鍵詞) Wald testzh_TW
dc.subject (關鍵詞) 檢定力zh_TW
dc.title (題名) 兩群時間序列Granger領先關係之新檢定方法zh_TW
dc.title (題名) New Tests of Granger Causality for two Groups of Time Seriesen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) Dekimpe, M. G., & Hanssens, D. M. (1995). The persistence of marketing effects on sales, Marketing Science, 14, 1-21.

Dekimpe, M. G., & Hanssens, D. M. (1999). Sustained spending and persistent response : A new look at long-term marketing probability, Journal of Marketing research, 36, 397-412.

Dufour, J. M., & Renault, E. (1998). Short-run and lonf-run causality in time series theory. Econometrica, 66, 1099-1125

Genz, A., Bretz, F., Miwa, T., Mi, X., Leisch, F., Scheipl, F., & Hothorn, T. (2014). mvtnorm:Multivariate Normal and t Distributions. R package version 0.9-9997. Retrieved from http://CRAN.R-project.org/package=mvtnorm

Geweke, J., Meese, R., & Dent, W. (1983). Comparing alternative tests of causality in temporal systems. Journal of Econometrics, 21, 161-194.

Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424-438.

Haugh, L. D. (1976). Checking the independence of two covariance-stationary time series: A univariate residual cross-correlation approach. Journal of the American Statistical Association, 71, 378-385.

Hung, Y. C., & Tseng, N. F. (2012). Extracting informative variables in the validation of two-group causal relationship. Computational Statistics, 28(3), 1151-1167.

Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Berlin:Springer-Verlag.

Murdoch, D., Chow, E. D.(2013). ellipse: Functions for drawing ellipses and ellipse-like confidence regions. R package version 0.3-8.Retrieved from http://CRAN.R-project.org/package=ellipse


Pierce, D. A., & Haugh, L. D. (1977). Causality in temporal systems: Characterization and a survey. Journal of econometrics, 5(3), 265-293.

Ripley, B., Venables, B., Bates, D.M., Hornik, K., Gebhardt A, Firth, D. (2014). MASS: Support Functions and Datasets for Venables and Ripley`s MASS. R package version 7.3-33. Retrieved from http://CRAN.R-project.org/package=MASS

Sims, C. A. (1972). Money, income, and causality. The American Economic Review, 62(4), 540-552.

Sims, C. A. (1980). Macroecomonics and reality. Journal of Econometrica, 48, 1-48.

Srinivasan, S. and Bass, F.M (2001). Diagnosing competitive responsiveness: Disentangling retailer-induced and manufacturer induced actions. Paper presented at the MSI Conference on competitive responsiveness, Boston.

Takada, H., & Bass, F. M. (1998). Multiple time series analysis of competitive marketing behavior. Journal of Business Research, 43(2), 97-107.

Trapletti, A., Hornik, K., LeBaron, B. (2013). tseries: Time series analysis and computational finance. R package version 0.10-32. Retrieved from http://CRAN.R-project.org/package=tseries

Tsai, M. T. M., & Sen, P. K. (1993). On the local optimality of optimal linear tests for restricted alternatives. Statistica Sinica, 3, 103-115.		zh_TW