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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/32022


    Title: 從貿易型態分析產業內貿易之決定因素
    Other Titles: The determinant of intra-industry trade from the analysis of trade pattern.
    Authors: 宋惠娟;Sung, Hui-chuan
    Contributors: 淡江大學國際貿易學系國際企業學碩士班
    蔡政言;Tsai, Jeng-yan
    Date: 2005
    Issue Date: 2010-01-11 01:33:05 (UTC+8)
    Abstract: 本文主要是探討台灣和貿易國的產業內貿易現象,採用混合資料的最小平方法為實證方法,並分為基本模型及區域虛擬變數模型,以探討不同貿易型態的產業內貿易決定因子,並觀察區域對各產業的產業內貿易之影響。

    實證研究發現,以基本模型來看,國民所得差異和每人國民所得差異均對消費性產業的IIT呈負相關,平均國民所得和每人平均國民所得均對非消費性產業的IIT呈正相關;海外直接投資對消費性和多製程產業的IIT呈正相關;匯率變動率對消費性和非消費性產業的IIT呈負相關;距離對大多數產業的IIT呈負相關,皆說明不同變數對各產業有不同的影響。

    以區域虛擬變數模型來看,每個變數對各產業的結果大致不變;區域方面,美洲、歐洲和澳洲的虛擬變數均對多數非消費性產業的IIT呈負相關,另外歐洲虛擬變數則對所有消費性產業的IIT呈負相關,說明不同的區域因素對各產業的影響,也可發現台灣和亞洲對各產業的產業內貿易程度比其他區域高。

    雖然本文的實證結果會對所有產業的決定因子有進步的了解,然而實證和理論預期有不合的現象仍有待後續研究補充與證明,如平均國民所得和海外直接投資。此外,也希望後繼學者能對產業內貿易的現象和貿易政策作深入的探討,這樣不僅對各國各產業的產業內貿易發展有更進一步的了解,也能爲國家帶來更多的整體利得。
    This thesis mainly investigates phenomenon of intra-industry trade between Taiwan and its trade partners. The thesis adopts pooling least squares method as empirical method, including a basic model and a regional dummy variable model, to investigate key factors of intra-industry trade from different trade pattern, and to observe regional influence on intra-industry trade of every different industry.

    We find that, according to basic model, difference in national income and difference in per capita national income present negative correlations to intra-industry trade of consuming-goods industries, average national income and average per capita national income present positive correlations to intra-industry trade of nonconsuming-goods industries, and foreign direct investment presents positive correlations to intra-industry trade of consuming-goods and value-added manufactuing industries. However, Exchange rate change rate presents negative correlations to intra-industry trade of consuming-goods, and non-consuming-goods industries; distance presents negative correlations to intra-industry trade of most industries. Finally, all prove that different variables have different influences on every industry.

    According to regional dummy variable model, every variable does not roughly change across industries. However, regional variables of America, Europe and Australia present negative correlations to intra-industry trade most nonconsuming-goods industries, and regional variables of Europe presents negative correlation to intra-industry trade of all consuming-goods industries. We also prove that different regional factors impact every industry and that Asia is higher than any other area.

    Although our empirical result shows progressive knowledge of the key factors of all industries, the empirical result seems not reflect what the theory is expected to. It relies on the further studies to find supplementary evidence and a formal proof. Finally, based on our finding, further research regarding to trade policy is worthy of exploring.
    Appears in Collections:[國際企業學系暨研究所] 學位論文

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