English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113648/144635 (79%)
Visitors : 51571012      Online Users : 447
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/84743


    Title: 動態追蹤資料分量迴歸
    Other Titles: Dynamic Panel Data Quantile Regression
    Authors: 林馨怡
    Contributors: 經濟學系
    Keywords: 動態追蹤資料;內生性偏誤;配適值方法;分量迴歸
    Dynamic panel data;Endogeneour bias;Fitted value approach;Quan- tile regression
    Date: 2012
    Issue Date: 2016-04-15 10:28:17 (UTC+8)
    Abstract: 本研究計劃預計應用分量迴歸方法於動態追蹤資料具有固定效果的模型, 以下簡稱 DPQR 模型, 此模型可以分析解釋變數對不同分量下的被解釋變數的異質性效果。 由於在 DPQR 模型下, 落後期被解釋變數具有內生性, 本研究計劃將應用配適值方法 (fitted value ap- proach) 來解決內生性偏誤的問題。 因此, 在 DPQR 模型下, 本人將建構一個兩階段的估 計步驟, 其中第一個步驟為先對具內生性的落後期被解釋變數進行估計, 並得出其配適值, 接著第二步驟再利用此配適值來取代落後期被解釋變數, 然後進行追蹤資料分量迴歸之估 計。 此方法由於相當簡單可行, 因此預計將會被廣泛使用。
    This project applies a quantile regression method for dynamic panel data model with fixed effects, henceforth the dynamic panel quantile regression (DPQR) model, for revealing heterogeneity effects of regressors on the dependent variable. In the DPQR model, the lagged dependent variable is endogenous due to the existence of fixed effects. This project adjusts for the bias of endogeneity by adopting a “fitted value” approach, and develops a two-stage estimation procedure for the DPQR model with fixed effects. The first step of the two-stage estimation consists of estimation of a fitted value for the lagged endogenous dependent variable. The second step is to replace the endogenous variable in the model by its fitted value, and to run a quantile regression for panel data directly to obtain the estimators. The fitted value approach, by simply running two-stage regressions, is appealing in that it is generally applicable and easy to implement.
    Relation: 計畫編號 NSC101-2410-H004-011
    Data Type: report
    Appears in Collections:[經濟學系] 國科會研究計畫

    Files in This Item:

    File Description SizeFormat
    101-2410-H004-011.pdf499KbAdobe PDF2331View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback