| 中文摘要 |
資料包絡分析（data envelopment analysis, DEA）廣泛的應用於衡量銀行經營效率，不過傳統的DEA模型係以線性規劃衡量技術效率，不具有隨機性質，無法進行有關生產技術之規模報酬性質的統計檢定。本研究將不良放款視為具有弱可拋性質的非意欲產出，延伸Simar and Wilson （1998; 2002）所建議的拔靴法估計程序，檢定本國商業銀行的規模報酬性質，並估計本國商業銀行的誤差修正效率值及檢定不同型態之商業銀行的平均效率是否存在顯著的差異。研究樣本包含34家台灣商業銀行，共102個觀測值。研究結果指出：在1%的顯著水準下，我們否決固定規模報酬之虛無假說，以BCC模型估計本國商業銀行之技術效率；此外，泛公股銀行之技術效率顯著的優於民營銀行，而金控銀行雖略低於非金控銀行，但是未達到顯著的差異。
Data envelopment analysis (DEA) is widely used to evaluate the technical efficiency of commercial banks.However, traditional DEA approaches rely on linear programming techniques for solutions known to be non-statistical innature. Therefore, the methods of statistical inference concerning the property of returns to scale do not directly apply.This study takes into account non-performing loans as undesirable output in the efficiency measurement modelling, andextends the bootstrap method of Simar and Wilson (1998, 2002), to test returns to scale of commercial banks and examinethe efficiency difference among different types of commercial banks in Taiwan. The dataset, obtained from the TaiwanEconomic Journal database, consists of 34 Taiwan’s commercial banks for the period 2011-2013. In this study, the nullhypothesis of constant returns to scale is rejected at 1% level of significance. Therefore, BCC model is used to estimate theefficiency of banking sector. The mean efficiency between financial holding and non-financial holding companies does notreveal significant difference, while public banks outperform private banks. |
本站僅提供期刊文獻檢索。
