English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 90533/120562 (75%)
Visitors : 24969601      Online Users : 281
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
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/61060

    Title: 貝氏多層次模型在台灣不動產市場估價之應用─以台北市住宅建物為例
    Other Titles: An Application of Bayesian Inference in the Real Estate Market –A Case Study of Taipei Collective Housing
    Authors: 林祖嘉;馬毓駿
    Contributors: 政大經濟系
    Keywords: 特徵方程式;貝氏分析;馬可夫鏈蒙地卡羅法
    hedonic equation;Bayesian inference;Markov Chain Monte Carlo
    Date: 2012-06
    Issue Date: 2013-09-17 10:00:09 (UTC+8)
    Abstract: 在房地產價格估計的領域當中,特徵方程式是最常被應用來估計建物價格的工具之一,然因特徵估價法是建構在線性迴歸的基礎之上,對於建物特徵與建物價格關係的描述過於簡化,同時實務上存在諸多無法量化的因素,致使模型容易產生異質變異的現象,而現有的非參數模型有時過於複雜,且使用上的限制亦多。針對上述問題,本文嘗試採用多層次貝式模型來彌補線性模型的缺陷,有別於多數研究將區位視為建物特徵之一的假設,本文由區位不同造成異質變異的角度切入,重新呈現建物特徵與建物價格的非單調性關係。實證結果指出多數的建物特徵對建物價格的影響,多因區位而產生變化,且時呈不同方向,同時在異質變異現象獲得舒緩後,建物價格估價的精確度亦獲得顯著提升。
    How to estimate housing prices precisely has always been an important issue in the real estate
    market. Most studies adopt parametric or non-parametric methods to deal with problems such as heteroskedasticity or non-monotonic phenomena which come from less influential attributes or from characteristics which can not easily be realized. Researchers have attempted to adopt certain methods such as non-parametric methods to recover from these failures but they still do not work well. This paper therefore tries to re-examine the issue of heteroskedasticity in the housing price model. By using data for collective housing-type buildings in Taipei, this study employs the Hierarchical Bayesian model to bridge the relationship between attributes and housing prices.By means of a random effect device, the location effect gives rise to a non-monotonic effect on regressors that affect housing prices. Besides, capturing the heteroskedasticity effects results in the Bayesian model providing a better estimation than OLS.
    Relation: 住宅學報, 21(1), 1-18
    Data Type: article
    Appears in Collections:[經濟學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    211118.pdf1489KbAdobe PDF670View/Open

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

    社群 sharing

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback