政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/69638
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113325/144300 (79%)
Visitors : 51155609      Online Users : 912
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: https://nccur.lib.nccu.edu.tw/handle/140.119/69638


    Title: 加值型營業稅中營業人涉嫌虛設行號之實證分析
    Other Titles: An Empirical Study of Business Entity Tax Fraud in the Value-Added Tax System
    Authors: 林左裕
    Lin, Calvin Tsoyu
    Contributors: 地政系
    Keywords: 區別分析;羅吉斯分析;虛設行號;營業稅
    tax fraud;value added tax;logit analysis;dicrriminant analysis
    Date: 2006.06
    Issue Date: 2014-09-03 11:44:49 (UTC+8)
    Abstract: 本研究以最近幾年所查獲並經地檢署起訴之虛設行號集團為對象,探討其特徵因子,建立區別模型。其目的是求出區別函數,判別營業人是否屬虛設行號,以決定是否須加強查核。首先找出進項金額、銷項金額、進項金額減銷項金額、實繳稅額、加值率、實繳稅額占銷項金額比率、進貨廠商家數、銷貨廠商家數等八個變數,並檢定是否符合多元常態分配、共變異數及兩母體平均數是否相等。其次以逐步區別分析,篩選出進貨廠商家數、銷貨廠商家數兩個變數具有區別能力,並建立區別模型。另外再加上營業人擅自歇業、負責人異常、租用房屋、循環開立發票等四個名義變數,以無母數區別分析、羅吉斯分析,分別建立區別模型。結果其分類正確率均達91%以上。本研究發現進貨廠商家數在三種方法分析中均顯著; 而加值率並不顯著;其計算公式,分母銷貨為零時,電腦程式產出結果亦為零,似有誤,財稅主管機關宜檢討修正。
    Some business entity in Taiwan usually utilizes falsified transaction uniform invoice to aid others in committing the tax evasion, or to add sales amount to make a loan from financial institutes for the purpose of tax fraud in Taiwan. The object of this study is thus to construct a discriminant model for tax authorities to decide whether there is any necessity to enhance investigation on a business entity that prosecuted by public prosecutor of tax fraud.First, eight quantity variables, including the sales amount, the purchases amount, the differences of between sales and purchases, the payment of business tax, the ratio of value added, the ratio of tax payment over sales, and the number of purchasers and sellers, are selected and tested respectively for normality, equality of group means, equality of covariance matrices, by means of stepwise discriminant. As a result, the number of purchasers and sellers are significant in determining the tax fraud. Second, several qualitative dummy variables are added, including de-registration, sponsor, renting business house, purchase-sale uniform invoices cycle. We employ nonparametric and logistic regression in the prediction of binary dependant variables. The overall classification accuracy is approximately 91-95 percent.The empirical findings of this study indicate that a relative few number of purchasers and sponsor are more likely to be tax fraud. The ratio of value added, however, often taken for granted as a discriminant indicator of tax-fraud business entity in practice, is ambiguous in the significance.
    Relation: 財稅研究, Vol.38, No.3, pp.174-188.
    Data Type: article
    Appears in Collections:[Department of Land Economics] Periodical Articles

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML21052View/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