本研究旨在實證本國銀行之財務狀況對其放款成長率之影響，以及比較第二版巴塞爾協定（Basel II）實施前後銀行財務狀況對其放款成長率之影響。透過1998年至2016年共計19年之國內8間公股銀行及24間民營銀行共計32間銀行作為樣本分析放款成長率及銀行財務狀況的關聯，並以二階系統性動差法進行估計。本研究之主要發現如下：第一，放款成長率與前一期之逾放比呈現負相關，當銀行之放款逾期無法收回時，銀行將減少其下一期之放款，避免其資金的流動性不足進而對銀行甚至整個經濟體造成危害。第二，放款成長率和其前一期之槓桿比呈現正相關，當銀行之股東權益佔其資產比率較高時，則表示其負債佔總資產比例較低，負債較低的銀行財務結構相對健全，其籌措資金的成本亦相對較低，因此可更積極的進行放款之業務。由此，監管單位可藉由觀察銀行之槓桿比率及逾放比率，預測其對放款成長率可能造成的影響並對其做出適度之規範。最後，研究結果亦顯示Basel II實施後，銀行財務狀況對其放款成長率之影響比Basel II實施前更為顯著，由此可見金融監管單位所制定之規範產生效果且Basel II之實施著實影響著銀行放款。

The purpose of this paper is to present evidence on the impact of the financial position of Taiwan’s banks on their loan growth rates, and to compare the effect of bank financial position on the growth rate of lending before and after the implementation of Basel II. Through 32 banks including 8 domestic public banks and 24 private banks from 1998 to 2016, a total of 32 banks were used as samples to analyze the relationship between the growth rate of loan and the bank’s financial position, and estimated using system GMM estimator. The main results of this paper are as follows: First, the growth rate of loan is negatively related to the non-performing loans ratio of the previous period. Second, the growth rate of loan is positively correlated with its leverage ratio of the previous period. Finally, the research results also show that after the implementation of Basel II, the bank’s financial position had a more significant impact on the growth rate of lending than before Basel II was implemented.
 

目錄
第一章 緒論 1
第二章 文獻回顧 4
第三章 研究方法 6
第一節 模型設定 6
第二節 變數及資料說明 9
第三節 計量方法 12
第四章 實證結果 15
第一節 銀行財務狀況及放款成長率關係 15
第二節 Basel II對銀行財務狀況及放款成長率之影響 18
第五章 穩健性測試 21
第六章 結論 23
參考文獻 25

表目錄
表一 32間銀行列表 27
表二 敘述統計量 27
表三 固定效果之實證結果 28
表四 一階差分動差法之實證結果 29
表五 一階系統動差法之實證結果 30
表六 二階系統動差法之實證結果 31
表七 Basel ll實施前之實證結果 32
表八 Basel ll實施後之實證結果 33
表九 忽略季節性調整之穩健性測試結果 34
表十 以國內生產總值替代景氣指標之穩健性測試結果 35

圖目錄
圖一 放款成長率與景氣指標 25
圖二 個別銀行放款成長率與逾放比關係 36

周美欣，2010，「台灣地區外商銀行放款管理模式之探討」，淡江大學國際貿易學系國際企業學碩士論文
張振芳，2012，「國內銀行存放款成長率與資產品質之相關性研究」，國立政治大學經營管理碩士學程碩士論文
黃郁荏，2010，「放款成長率與存款成長率的關係：本國銀行追蹤資料分析」，世新大學經濟研究所碩士論文
Arellano, M., and Bond, S. (1991). “Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations.” The review of economic studies, 58(2), 277-297.
Arellano, M., and Bover, O. (1995). “Another look at the instrumental variable estimation of error-components models.” Journal of econometrics, 68(1), 29-51.
Bernanke, B., and Blinder, A. (1988). “Credit, money, and aggregate demand.” American Economic Review Papers and proceedings 78, 435-439.
Blundell, R., and Bond, S. (1998). “Initial conditions and moment restrictions in dynamic panel data models.” Journal of econometrics, 87(1), 115-143.
Bowsher, C.G. (2002). “On testing overidentifying restrictions in dynamic panel data models.” Economics Letters 77, 211–20.
Hancock, D., and Wilcox, J. A. (1993). “Has There Been a 'Capital Crunch' in Banking? The Effects on Bank Lending of Real Estate Market Conditions and Bank Capital Shortfalls.” Journal of Housing Economics 3, 31-50.
Holtz-Eakin, D., Newey, W., and Rosen, H. (1988). “Estimating Vector Autoregressionss with panel data. ” Econometrica, 56, 1371-1395.
 
Johnson, R., and Lee, C. K. (1994). “The Link Between the 1980s Credit Boom and the Recent Bank Credit Slowdown.” Studies on the Causes and Consequences of the 1989-92 Credit Slowdown, Federal Reserve Bank of New York.
Levintal, O. (2013). “The real effects of banking shocks: Evidence from {OECD} contries.” Journal of International Money and Finance 32, 556-578.
Nickell, S. (1981). “Biases in dynamic models with fixed effects.” Econometrica: Journal of the Econometric Society, 49(6), 1417-1426.
Rappoport, S. A. (2016). “The effect of bank’s financial position on credit growth: evidence from OECD countries.” Finance and Economics Discussion Series 2016-101, Board of Governors of the Federal Reserve System.
Roodman, D. (2009). “A note on the theme of too many instruments.” Oxford Bulletin of Economics and statistics, 71(1), 135-158.
Sharpe, S. A. (1995). “Bank capitalization, regulation, and the credit crunch: a critical review of the research finding.” Finance and Economics Discussion Series 95-20, Board of Governors of the Federal Reserve System.
Stein, J.C. (1998). “An adverse-selection model of bank asset and liability management with implications for the transmission of monetary policy.” RAND Journal of Economics 29(3), 466–486.
Windmeijer, F. (2005). “A finite sample correction for the variance of linear efficient two-step GMM estimators.” Journal of econometrics, 126(1), 25-51.