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金融發展對經濟成長的影響-動態追蹤資料門檻模型

The Role of Financial Development to Economic Growth-Dynamic Panel Threshold Model

摘要


本文旨在探討於全球的架構下,各國金融發展對於經濟成長之關係爲何?並且進一步探討銀行發展及股市發展是否對經濟成長有不對稱效果。對於過去相關文獻無法獲得金融發展與經濟成長間一致的關係,我們懷疑應與金融發展與經濟成長間爲非線性關係有關。延伸Shen and Lee (2006)我們將探討是否於金融發展與經濟成長間存在著銀行的門檻效果,並提出兩個假說,第一是「blessing-in-low-regime」,即在低度銀行發展區域,金融發展對於經濟成長有正面影響。第二是「curse-in-high-regime」,即在高度銀行發展區域,金融發展對於經濟成長有負面影響。本文發展一個新的模型:動態追蹤資料門檻模型(dynamic panel threshold model, DPTM)是延伸Hansen (1999)的追蹤資料門檻模型(panel threshold model, PTM),認爲經濟成長會受到自己上一期變數所影響,結果指出就銀行發展對於經濟成長的影響而言,在低度銀行發展區域支持「blessing-in-low-regime」;在高度銀行發展區域支持「curse-in-high-regime」。反之,就股市發展對於經濟成長的影響,在低度銀行發展區域並不支持「blessing-in-low-regime」;在高度銀行發展區域亦不支持「curse-in-high-regime」。

並列摘要


This paper is aimed to investigate the asymmetric effect between financial development and the economic growth. Following Shen and Lee's (2006) findings, we plan to examine whether the effect of financial development on the growth depends on the threshold variable of bank development. Our hypothesis is thus that the bank development is a blessing to economic growth at the low bank development regime but a curse at the high bank development regime. To examine this ”blessing-in-low-regime” and ”curse-in-high-regim” hypothesis, we develop a dynamic panel threshold model (DPTM) to test this hypothesis. The DPTM is a direct extension of the non-dynamic panel threshold model of Hansen (1999). We can conclude with that the effect of bank development on the growth support the hypothesis ”blessing-in-low-regime” and ”curse-in-high-regime” but the effect of stock market development on the growth does not.

參考文獻


李建強、洪福聲、黃柏農(2005)。金融發展與經濟成長的關係會消失嗎?-門檻迴歸之應用。經濟研究。41(1),45-74。
Alfaro, L.,A. Chanda,S. Kalemli-Ozcan,S. Sayek(2004).FDI and Economic Growth: The Role of Local Financial Markets.Journal of International Economics.64(1),89-112.
Andersen, T.,F. Tarp(2003).Financial Liberalization, Financial Development and Economic Growth in LDCs.Journal of International Development.15,189-209.
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Arellano, M.,O. Bover(1995).Another Look at the Instrumental Variable Estimation of Error-components Models.Journal of Econometrics.68,29-52.

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