后亚洲货币危机时期印尼银行业的效率

B. Santosa
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摘要

本研究探讨印尼银行效率的决定因素后亚洲货币危机。它采用了定量方法和历史数据,其中使用的数据既包括时间序列(2000-2012年),也包括横截面(对于一些符合样本要求的商业银行)。从概念上讲,它将依赖于法雷尔(1957)提出的效率概念。同时,在DEA中运用银行效率测度技术,以中介方法作为投入产出选择的依据。在DEA的应用中,它将同时使用CRS模型(模型CCR)和VRS模型(BCC模型)。而在其构造中,它将使用面向输入的方法。从这里,我们通过使用Tobit回归模型确定影响印尼银行效率的变量在后亚洲货币危机。基于17家商业银行的样本,我们的研究结果表明,印度尼西亚商业银行通过中介方法的效率一直正常运行,并且在后亚洲货币危机中趋于高效。此外,印度尼西亚的银行受到规模、国有、私营、非合并、外资、风险和经济增长的显著影响。从研究中可以看出,国有-私营和内外资企业的规模和所有权都是影响整体技术效率(OTE)、纯粹技术效率(PTE)和规模效率(SE)的变量。此外,非合并是影响整体技术效率(OTE)和规模效率(SE)的变量。同时,风险只影响纯技术效率(PTE),经济增长只影响整体技术效率(OTE)。相反,竞争、通货膨胀和全球危机并没有影响所有类型的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Indonesian Banking Efficiency in the Post-Asian Monetary Crisis
This study examines the determinants of Indonesian banking efficiency in post-Asian monetary crisis. It used a quantitative approach and historical data, where the data used is both time series (2000–2012), and crosssectional (for some commercial banks that meet the requirements of the sample). Conceptually, it will rely upon the concept of efficiency proposed by Farrell (1957). Meanwhile, banking efficiency measurement techniques are used in the DEA with the intermediation approach as the basis for the selection of input and output. In the application of DEA, it will use both CRS models (models CCR) and VRS (BCC models). While in its construction, it will use an input-oriented approach. From here we identify the variables that affect the Indonesian banking efficiency in the post-Asian monetary crisis, by using Tobit Regression Model. Based on the sample of 17 commercial banks, our findings reveal that the efficiency of Indonesian commercial banks via the intermediation approach has been running normally and tends to be efficient in the post-Asian monetary crisis. In addition, banks in Indonesia are significantly affected by Size, State Ownership, Private Ownership, Non-merger, Foreign Ownership, Risk, and Economic Growth. From the study, it appears that the Size and Ownership of both state-private and domestic-foreign are variables that affect the Overall Technical Efficiency (OTE), Pure Technical Efficiency (PTE), and Scale Efficiency (SE). Furthermore, Non-Merger is a variable that affects the Overall Technical Efficiency (OTE), and Scale Efficiency (SE). Meanwhile, Risk affects only Pure Technical Efficiency (PTE), as well as Economic Growth which only affects Overall Technical Efficiency (OTE). Instead, Competition, Inflation, and Global Crisis did not affect all types of efficiency.
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