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    Title: 吉布列法則 : 分量迴歸之應用
    Other Titles: Gibrat's law : application of quantile regression
    Authors: 張庭威;Chang, Ting-wei
    Contributors: 淡江大學產業經濟學系碩士班
    胡登淵;Hu, Teng-yuan
    Keywords: 吉布列法則;分量回歸;Quantile Regression
    Date: 2006
    Issue Date: 2010-01-11 01:16:39 (UTC+8)
    Abstract: 吉布列法則指出廠商成長與規模無關,文獻中支持與不支持吉布列法則者兩派並存,分析超過最小效率規模廠商者(譬如Hart與Prais, 1956),傾向支持吉布列法則者;反之,分析小廠者則傾向於拒絕 (譬如Dunne與Hughes, 1994)。近年來,Lotti等 (2003) 利用義大利1987年開始營運製造業廠商 (1987-1993年),並以分量迴歸分析法分析,討論新進入市場之小規模廠商在早期的生命循環 (life cycle) 階段,吉布列法則是否成立。該研究發現小廠商在開始營運後必須快速成長並達到夠大的規模以增加其存活可能性,故吉布列法則在此段時間內不成立;然而此段期間後小廠商成長路徑則沒有顯著異於大廠商,此時支持吉布列法則。本研究擬觀察廠齡較長之相對大廠的成長型態是否與Lotti等 (2003) 對小廠之預測一致,以及是否有別於以傳統方法分析超過最小效率規模廠商者所得之結論,係利用DTI-Meeks-Whittington英國廠商資料(UK Department of Trade and Industry),以相對高廠齡之大規模廠商 (1955-1985年) 為樣本,使用分量回歸法分析,發現只有在最低分量上符合其論述,其他分量則傾向於拒絕,有別於Hart與Prais (1956) 等分析超過最小效率規模廠商者,大廠中的相對高分量廠商仍傾向拒絕吉布列法則。
    Gibrat’s Law indicates that the growth rate of a given firm is independent of its size. In the literature, both supporting and opposing opinions coexist. Scholars investigating firms exceeding the minimum scale tended to agree with Gibrat’s Law; for example, Hart and Prais (1956). In contrast, scholars investigating small firms tended to disagree with Gibrat’s Law; for example, Dunne and Hughes (1994). Recently, Lotti et al. (2003) analyzed the data of Italian manufacturing firms over the period from 1987 to 1993 and used quantile regression techniques to test whether Gibrat’s Law holds for new small firms in the early stage of their life cycle. Their main finding is that small firms have to rush in order to achieve a size large enough to enhance their likelihood of survival. Conversely, in subsequent years the patterns of growth rate of new smaller firms do to differ significantly from those of relatively larger entrants, and the Law cannot be rejected. This thesis applied the method of quantile regression and analyzed the data of DTI-Meeks-Whittington British firms over the period from 1955 to 1985. It aimed at using relatively older and larger firms’ data to compare with Lotti’s results and to compare the results from quantile regression with the results from the conventional method, OLS, which was used to investigate firms exceeding MES. In contrast to the results of Lotti et al. (2003), the results of this thesis indicate that Gibrat’s Law only holds at low-quantile and being rejected at other quantiles. In particular, the high-quantile in large firms tends to reject Gibrat’s Law. This finding is also different from the results of Hart and Prais (1956), which supported the Law while investigating firms exceeding MES.
    Appears in Collections:[產業經濟學系暨研究所] 學位論文

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