{"title":"印度定期商业银行收入效率的决定因素","authors":"A. Bhatia, Megha Mahendru","doi":"10.22452/AJAP.VOL12NO1.4","DOIUrl":null,"url":null,"abstract":"Research aim: The purpose of this paper is to investigate the internal (bank-specific) and external (macroeconomic and industry-specific) factors thataffect the revenue efficiency of banks. \nDesign/Methodology/Approach: The paper considers all the Scheduled Commercial Banks operating in India over a period of 22 years from 1991-92 to 2012-13. Due to the non-availability of information for certain variables the sample varies across years. The revenue efficiency of banks is calculated by employing a non-parametric approach, namely, Data Envelopment Analysis (DEA). To determine the factors affecting revenue efficiency, the Panel Data Tobit model, as proposed by James Tobin (1958), is used. It is applied due to the censored nature of the dependent variable, i.e., the efficiency scores, which range from 0 to 1. \nResearch finding: The results indicate that the Capital Adequacy Ratio (CAR), Net Non-Performing Assets to Net Advances (NPANA), Operating Expenses to Total Expenses (OETE), Business per Employee (BPE), Return on Assets (ROA), Size (LNTA), and Inflation (INF) reveal a negative relationship with the revenue efficiency scores. Equity to Total Assets (ETA), Total Loans and advances to Total Deposits (TATD), Total Investments to Total Assets (TITA), Total Expenses to Total Income (TETI), Spread to Total Assets (STA), Non-Interest Income to Total Income (NIITI), Cash Deposit Ratio (CDR), Time Dummy (TD), Public Dummy (PUBD), and Log of Gross Domestic Product (LNGDP) disclose a positive relationship for the revenue efficiency model. \nTheoretical contribution/Originality: This study is among the few that examine factors affecting the revenue efficiency of Indian Commercial Banks as limited research is available in the Indian Banking Literature. \nPractitioner/Policy implication: The empirical findings of this article clearly provide assistance to bank managers in understanding the factors that positively or adversely affect the revenue efficiency. It specifically recommends that managers focus on credit risk management and asset liability management. \nResearch limitation/Implication: The present study may be extended by considering other efficiency parameters as dependent variables. Various risks faced by banks and off-balance sheet activities can also be taken into consideration. The impact of other events, such as global financial recession, might also be captured for future research. \nKeywords: Revenue Efficiency, Bank Specific Variable, Industry Specific Variable, Data Envelopment Analysis, Panel Tobit Regression Analysis, Indian Scheduled Commercial Banks \nType of manuscript: Research paper \nJEL Classification: G2, C24, D61","PeriodicalId":33532,"journal":{"name":"Asian Journal of Accounting Perspectives","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Determinants of The Revenue Efficiency of Indian Scheduled Commercial Banks\",\"authors\":\"A. 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引用次数: 0
摘要
研究目的:本文的目的是研究影响银行收益效率的内部(银行特定)和外部(宏观经济和行业特定)因素。设计/方法/方法:本文考虑了从1991-92年到2012-13年的22年间在印度经营的所有预定商业银行。由于某些变量的信息不可获得,样本在不同年份有所不同。银行收入效率的计算采用非参数方法,即数据包络分析(DEA)。为了确定影响收入效率的因素,我们使用了James Tobin(1958)提出的Panel Data Tobit模型。它的应用是由于因变量的审查性质,即效率分数,其范围从0到1。研究发现:结果表明,资本充足率(CAR)、净不良资产与净垫款(NPANA)、营业费用与总费用(OETE)、人均业务量(BPE)、资产收益率(ROA)、规模(LNTA)和通货膨胀率(INF)与收入效率得分呈负相关。权益与总资产之比(ETA)、总贷款与预付款与总存款之比(TATD)、总投资与总资产之比(TITA)、总费用与总收入之比(TETI)、总资产之比(STA)、非利息收入与总收入之比(NIITI)、现金存款比率(CDR)、时间虚拟人(TD)、公共虚拟人(PUBD)和国内生产总值对数(LNGDP)对收入效率模型显示出正相关关系。理论贡献/独创性:本研究是为数不多的研究影响印度商业银行收入效率因素的研究之一,因为印度银行业文献中的研究有限。从业者/政策启示:本文的实证研究结果清楚地为银行管理者理解积极或消极影响收入效率的因素提供了帮助。它特别建议管理者关注信用风险管理和资产负债管理。研究局限/启示:考虑其他效率参数作为因变量,本研究可以扩展。银行和表外活动面临的各种风险也可以考虑在内。其他事件的影响,如全球金融衰退,也可能被纳入未来的研究。关键词:收益效率,银行特定变量,行业特定变量,数据包络分析,面板Tobit回归分析,印度上市商业银行手稿类型:研究论文JEL分类:G2, C24, D61
Determinants of The Revenue Efficiency of Indian Scheduled Commercial Banks
Research aim: The purpose of this paper is to investigate the internal (bank-specific) and external (macroeconomic and industry-specific) factors thataffect the revenue efficiency of banks.
Design/Methodology/Approach: The paper considers all the Scheduled Commercial Banks operating in India over a period of 22 years from 1991-92 to 2012-13. Due to the non-availability of information for certain variables the sample varies across years. The revenue efficiency of banks is calculated by employing a non-parametric approach, namely, Data Envelopment Analysis (DEA). To determine the factors affecting revenue efficiency, the Panel Data Tobit model, as proposed by James Tobin (1958), is used. It is applied due to the censored nature of the dependent variable, i.e., the efficiency scores, which range from 0 to 1.
Research finding: The results indicate that the Capital Adequacy Ratio (CAR), Net Non-Performing Assets to Net Advances (NPANA), Operating Expenses to Total Expenses (OETE), Business per Employee (BPE), Return on Assets (ROA), Size (LNTA), and Inflation (INF) reveal a negative relationship with the revenue efficiency scores. Equity to Total Assets (ETA), Total Loans and advances to Total Deposits (TATD), Total Investments to Total Assets (TITA), Total Expenses to Total Income (TETI), Spread to Total Assets (STA), Non-Interest Income to Total Income (NIITI), Cash Deposit Ratio (CDR), Time Dummy (TD), Public Dummy (PUBD), and Log of Gross Domestic Product (LNGDP) disclose a positive relationship for the revenue efficiency model.
Theoretical contribution/Originality: This study is among the few that examine factors affecting the revenue efficiency of Indian Commercial Banks as limited research is available in the Indian Banking Literature.
Practitioner/Policy implication: The empirical findings of this article clearly provide assistance to bank managers in understanding the factors that positively or adversely affect the revenue efficiency. It specifically recommends that managers focus on credit risk management and asset liability management.
Research limitation/Implication: The present study may be extended by considering other efficiency parameters as dependent variables. Various risks faced by banks and off-balance sheet activities can also be taken into consideration. The impact of other events, such as global financial recession, might also be captured for future research.
Keywords: Revenue Efficiency, Bank Specific Variable, Industry Specific Variable, Data Envelopment Analysis, Panel Tobit Regression Analysis, Indian Scheduled Commercial Banks
Type of manuscript: Research paper
JEL Classification: G2, C24, D61