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題名 t 檢定偵測結構性變動的穩健性
其他題名 On the Robustness of t Ratio in Testing for Parameter Instability
作者 郭炳伸
關鍵詞 靴帶法;ARMA模式;穩健性;結構性變動;t檢定偵測
Bootstrap;ARMA model;Robustness;Structural change;t testing
日期 2002
上傳時間 18-四月-2007 16:36:09 (UTC+8)
出版社 臺北市:國立政治大學國際貿易學系
摘要 Tests for the stationarity null due to Kwiatkowski et al. (1992) continue to be an indispensable part of tool kits for empirical researchers when investigating time series property of aggregate variables. As well-documented in the literature (see for instance, Caner and Kilian, 2001), the tests display considerable size distortions, if the data generated under the null is highly persistent. The paper oers an asymptotic explanation in a local-to-unity framework. Our analytical derivations unveil that the tests fail to converge without a re-normalization. The surprising nding suggests that the size bias deteriorates as sample size increases, but declines as bandwidth number increases, consistent with simulation evidence. The derivations however give little clue to how to mitigate the size bias, because of an inability to consistently estimate the local-to-unity parameter. While it is natural to appeal to the bootstrapping, it proves infeasible to construct a sensible re-sampling scheme, based on the unobserved compo- nent model from which the observed series is generated. We resolve the diculty by drawing bootstrap samples from a parametric ARIMA model, second-order equivalent in moments to the unobserved component model. Even in the presence of highly per- sistent processes, our bootstrap tests are found to yield very satisfactory control over the rejection probability at little cost of power loss.
描述 核定金額:902700元
資料類型 report
dc.coverage.temporal 計畫年度:91 起迄日期:20020801~20040731en_US
dc.creator (作者) 郭炳伸zh_TW
dc.date (日期) 2002en_US
dc.date.accessioned 18-四月-2007 16:36:09 (UTC+8)en_US
dc.date.accessioned 8-九月-2008 15:51:12 (UTC+8)-
dc.date.available 18-四月-2007 16:36:09 (UTC+8)en_US
dc.date.available 8-九月-2008 15:51:12 (UTC+8)-
dc.date.issued (上傳時間) 18-四月-2007 16:36:09 (UTC+8)en_US
dc.identifier (其他 識別碼) 912415H004001.pdfen_US
dc.identifier.uri (URI) http://tair.lib.ntu.edu.tw:8000/123456789/3790en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/3790-
dc.description (描述) 核定金額:902700元en_US
dc.description.abstract (摘要) Tests for the stationarity null due to Kwiatkowski et al. (1992) continue to be an indispensable part of tool kits for empirical researchers when investigating time series property of aggregate variables. As well-documented in the literature (see for instance, Caner and Kilian, 2001), the tests display considerable size distortions, if the data generated under the null is highly persistent. The paper oers an asymptotic explanation in a local-to-unity framework. Our analytical derivations unveil that the tests fail to converge without a re-normalization. The surprising nding suggests that the size bias deteriorates as sample size increases, but declines as bandwidth number increases, consistent with simulation evidence. The derivations however give little clue to how to mitigate the size bias, because of an inability to consistently estimate the local-to-unity parameter. While it is natural to appeal to the bootstrapping, it proves infeasible to construct a sensible re-sampling scheme, based on the unobserved compo- nent model from which the observed series is generated. We resolve the diculty by drawing bootstrap samples from a parametric ARIMA model, second-order equivalent in moments to the unobserved component model. Even in the presence of highly per- sistent processes, our bootstrap tests are found to yield very satisfactory control over the rejection probability at little cost of power loss.-
dc.format applicaiton/pdfen_US
dc.format.extent bytesen_US
dc.format.extent 169165 bytesen_US
dc.format.extent 169165 bytes-
dc.format.extent 19653 bytes-
dc.format.mimetype application/pdfen_US
dc.format.mimetype application/pdfen_US
dc.format.mimetype application/pdf-
dc.format.mimetype text/plain-
dc.language zh-TWen_US
dc.language.iso zh-TWen_US
dc.publisher (出版社) 臺北市:國立政治大學國際貿易學系en_US
dc.rights (權利) 行政院國家科學委員會en_US
dc.subject (關鍵詞) 靴帶法;ARMA模式;穩健性;結構性變動;t檢定偵測-
dc.subject (關鍵詞) Bootstrap;ARMA model;Robustness;Structural change;t testing-
dc.title (題名) t 檢定偵測結構性變動的穩健性en_US
dc.title.alternative (其他題名) On the Robustness of t Ratio in Testing for Parameter Instability-
dc.type (資料類型) reporten