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Efficiency analysis of Indian banking industry over the period 2008-2017 using data envelopment analysis

机译:使用数据包络分析对印度银行业在2008-2017年期间的效率进行分析

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Purpose - The purpose of this paper is to estimate the relative efficiencies of banks of the Indian domestic banking sector by employing various models of data envelopment analysis (DEA) using the panel data of the recent decade (2008-2017). The paper provides a comparative analysis of these models based on the efficiency outputs. It compares the performance of banks based on their ownership and sizes and studies the decade-long trend of productivity using Malmquist indices. Design/methodology/approach - This paper estimates overall technical, pure technical and scale efficiencies of 21 public sector banks and 17 private banks. It compares the descriptive statistics of efficiency estimates found out through 18 different DEA models and compares them using two non-parametric statistical tests. It studies the difference in efficiencies based on ownership and size by applying the same statistical tests. It employs the Malmquist index method to study the technological and technical progress in the banks' productivity over the decade of FY 2008-FY 2017. Findings - During FY 2016-2017, only 9 out of 38 banks were overall technically efficient with the whole sample having a mean overall technical inefficiency of 5 percent with scale inefficiency contributing more than pure technical inefficiency. The comparative study ascertains that private sector and public sector banks (PSBs) possess efficiencies that are similar based on super-efficiency slack-based model - variable returns to scale and non-oriented, a model that the authors argue to be the most suitable for the real-life business banking scenarios whereas the private sector banks possess better efficiency than the PSBs. The Malmquist indices prove that private sector banks have a higher increase in productivity based on both technological progress and efficiency improvements whereas PSBs had a loss of efficiency and comparatively less improvement in technology. Research limitations/implications - This study has a limitation of choosing a single model of inputs and outputs. Improved insights can be drawn by employing more models based on different inputs and outputs. Further, relevance of each input and output can be examined using a regression-based feedback mechanism (Ouenniche and Carrales, 2018). The influence of environmental factors on the efficiencies can be studied using second-stage regression models and the relationship between efficiency scores and financial ratios can be examined. Originality/value - This study is based on the panel data of the recent decade (2008-2017) and provides insights into the efficiency scenario of the Indian banking industry and how it changed over the past decade, to the leadership of banks, the banking regulators and the policy makers. The comparative analysis of DEA models based on a sample of Indian banks is first of its kind in the Indian context and helps the researchers to select an appropriate model and delve into further research on the same.
机译:目的-本文的目的是通过使用最近十年(2008-2017)的面板数据采用各种数据包络分析(DEA)模型来估计印度国内银行业银行的相对效率。本文根据效率输出对这些模型进行了比较分析。它根据所有权和规模来比较银行的绩效,并使用Malmquist指数研究十年来的生产率趋势。设计/方法/方法-本文估算了21家公共部门银行和17家私人银行的整体技术,纯技术和规模效率。它比较了通过18种不同的DEA模型发现的效率估计值的描述性统计数据,并使用两个非参数统计检验对它们进行了比较。它通过应用相同的统计检验来研究基于所有权和规模的效率差异。它使用Malmquist指数方法研究了2008-2017财政年度十年间银行生产率的技术进步。调查结果-2016-2017财政年度,在38个银行中,只有9个银行的整体技术效率高具有平均5%的整体技术效率低下,规模效率低下比纯技术效率低下更多。这项比较研究确定,私人部门和公共部门银行(PSB)的效率与基于超效率松弛的模型相似-可变规模收益和非定向模型,作者认为该模型最适合在现实生活中的商业银行业务场景中,而私营部门银行的效率要高于公共部门银行。 Malmquist指数证明,基于技术进步和效率提高,私人银行的生产率提高较高,而PSB则效率降低,技术改进相对较少。研究的局限性/含义-该研究在选择单一输入和输出模型方面存在局限性。通过基于不同的输入和输出使用更多模型,可以得出更深刻的见解。此外,可以使用基于回归的反馈机制来检查每个输入和输出的相关性(Ouenniche and Carrales,2018)。可以使用第二阶段回归模型研究环境因素对效率的影响,并可以检查效率得分与财务比率之间的关系。原创性/价值-这项研究基于最近十年(2008-2017)的面板数据,向银行领导层,银行业领导层提供了有关印度银行业效率情景及其在过去十年中的变化的见解。监管机构和政策制定者。基于印度银行样本进行的DEA模型的比较分析在印度背景下尚属首次,可帮助研究人员选择合适的模型并对其进行深入研究。

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