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    題名: Gaussian Inference in AR(1) Models with Trend: A Note
    作者: Chen, Jhih-Gang;Kuo, Biing-Shen
    陳致綱;郭炳伸
    貢獻者: 國貿系
    關鍵詞: 自我迴歸模型;去除趨勢;一階差分;單根;動態追蹤資料;固定效果
    AR model;detrend;first difference;unit root;dynamic panel;fixed effects
    日期: 2014-06
    上傳時間: 2015-09-15 11:17:45 (UTC+8)
    摘要: 本文將Phillips and Han(2008)之一階差分估計式推展至有時間趨勢之一階自我迴歸模型的估計與推論上。藉由簡易的去除時間趨勢過程,一階差分估計式仍具有漸近常態分配的性質;同時,據以建構之單根檢定相較於以雙重差分估計式為基礎之單根檢定更有檢定力。本文提出的方法在固定效果動態追蹤資料模型下更具應用價值。
    This paper adapts the first-difference estimator of Phillips and Han (2008) to the estimation and inference in AR(1) models with trends. With a detrending procedure, the first-difference estimator remains applicable and is shown to retain the Gaussian asymptotics. A unit root test based on the estimator is more powerful than that based on the double-difference estimator. The proposed estimator is especially useful when applied to dynamic panels.
    關聯: Taiwan Economic Review, 42(2), 297-313
    資料類型: article
    DOI 連結: http://dx.doi.org/10.6277/TER.2014.422.4
    DOI: 10.6277/TER.2014.422.4
    顯示於類別:[國際經營與貿易學系 ] 期刊論文

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