Dynamics of income diversification and bank performance in India

2019 ◽  
Vol 12 (3) ◽  
pp. 383-407
Author(s):  
Harishankar Vidyarthi
Keyword(s):  
Panel Data ◽  
Performance Indicator ◽  
Stock Exchange ◽  
Scale Efficiency ◽  
Bank Performance ◽  
Tobit Regression ◽  
Income Diversification ◽  
Content Type ◽  
Data Framework ◽  
Indian Banks

Purpose The purpose of this paper is to examine the dynamics between income diversification and performance (cost, profit, revenue, technical, pure technical and scale efficiency) for 38 listed Indian banks within panel data framework during the period 2004-2005 to 2015-16. Design/methodology/approach This study computes bank’s cost, profit, revenue, technical, pure technical and scale efficiency within intermediation approach with data envelopment analysis (DEA) as a performance indicator, followed by exploring the association between income diversification and bank performance using truncated Tobit regression within panel data framework. Findings Tobit regression results revealed inverted U-shaped relationship between the income diversification and estimated efficiency parameters for the overall panel. Size and bank intermediation ratio seems to be a major factor in exploiting the potential benefits of income diversification. The author reconfirmed the inverted U-shaped relationship with these efficiency parameters for exclusive subsamples consisting of government-owned and private sector banks. Research limitations/implications Inverted U-shaped relationship between the income diversification and estimated efficiency parameters suggest that banks should go for limited diversification to improve performance. Thus, regulators and banks should pursue limited diversification strategy for improving banking efficiency. Originality/value This study computes bank performance (cost, profit, revenue, technical, pure technical and scale efficiency) based on DEA followed by exploring the association between performance and income diversification for 38 Bombay stock exchange listed banks.

Cost, revenue, and profit efficiency characteristics, and intellectual capital in Indian Banks

2019 ◽  
Vol 21 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Harishankar Vidyarthi ◽  
Ranjit Tiwari
Keyword(s):  
Panel Data ◽  
Intellectual Capital ◽  
Value Added ◽  
Tobit Regression ◽  
Profit Efficiency ◽  
Content Type ◽  
Significance Level ◽  
Data Framework ◽  
Efficiency Measures ◽  
Indian Banks

Purpose The purpose of this paper is to estimate the economic (namely cost, revenue and profit) efficiency and its association with intellectual capital of 37 BSE-listed Indian banks over the period 2005–2018. Design/methodology/approach This study employs truncated Tobit regression to compute the relationship between intellectual capital and estimated cost, revenue and profit efficiency using Data Envelopment Analysis (DEA) for the 37 BSE-listed Indian banks within the panel data framework. Findings Estimates suggest that banks’ overall annual average cost, revenue and profit efficiency are 0.4466–0.7519, 0.4825–0.8773 and 0.4905–0.8803, respectively, during the sample period. Further, Tobit regression results indicate that the aggregate intellectual capital (value-added intellectual coefficient or Modified Value-added Intellectual Capital) has a positive but minimal impact on these efficiency parameters at 1 percent significance level for the overall sample as well as public sector banks. Among all the sub-components of intellectual capital, human capital, structural capital and relational capital have a positive and moderate impact on these efficiency measures for the overall sample. Control variables, particularly bank size, are significant drivers of the estimated efficiency of banks. Research limitations/implications Findings suggest that banks should invest adequately to enhance their overall intellectual capital to further augment these economic efficiency measures in the long run. Originality/value This study computes cost, revenue and profit efficiency of 37 BSE-listed banks based on DEA followed by intellectual capital using the Pulic approach (1998 and 2000) and the Bontis (1998) approach in the first stage. Later, it examines the dynamics between the computed efficiency parameters and intellectual capital using Tobit regression within the panel data framework.

Efficiency evaluation of Indian oil and gas sector: data envelopment analysis

2019 ◽  
Vol 14 (2) ◽  
pp. 362-378 ◽  
Author(s):  
Vikas Vikas ◽  
Rohit Bansal
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Capital Investment ◽  
Oil And Gas ◽  
Stock Exchange ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Content Type ◽  
Indian Economy ◽  
Oil And Gas Sector

Purpose Data envelopment analysis (DEA), a non-parametric technique is used to assess the efficiency of decision-making units which are producing identical set of outputs using identical set of inputs. The purpose of this paper is to find the technical efficiency (TE), pure technical efficiency and scale efficiency (SE) levels of Indian oil and gas sector companies and to provide benchmark targets to the inefficient companies in order to achieve efficiency level. Design/methodology/approach In the present study, a group of 22 oil and gas companies which are listed on the National Stock Exchange for which the data were available for the period 2013–2017 has been considered. DEA has been performed to compare the efficiency levels of all companies. To measure efficiency, three input variables, namely, combined materials consumed and manufacturing expenses, employee benefit expenses and capital investment and two output variables – operating revenues and profit after tax (PAT) have been considered. On the basis of performance for the financial year ending 2017, benchmark targets based on DEA–CCR (Charnes, Cooper and Rhodes) model have been provided to the inefficient companies that should be focused upon by them to attain the efficiency level. The performance of the companies for the past five years has been examined to check the fluctuations in the various efficiency scores of the companies considered in the study over the years. Findings From the results obtained, it is observed that 59 percent, i.e. 13 out of 22 companies are technically efficient. By considering DEA BCC (Banker, Charnes and Cooper) model, 16 companies are observed to be pure technically efficient. In terms of SE, there are 14 such companies. The inefficient units need to improve in terms of input and output variables and for this motive, specified targets are assigned to them. Some of these companies need to upgrade significantly and the managers must take the concern earnestly. The study has also thrown light on the performance of the companies over last five years which shows Oil India Ltd, Gujarat State Petronet Ltd, Petronet LNG Ltd, IGL Ltd, Mahanagar Gas, Chennai Petroleum Corporation Ltd and BPCL Ltd as consistently efficient companies. Research limitations/implications The present study has made an attempt to evaluate the efficiency of Indian oil and gas sector. The results of the study have significant inferences for the policy makers and managers of the companies operating in the sector. The results of the study provide benchmark target level to the companies of Oil and Gas sector which can help the managers of the relatively less efficient companies to focus on the ways to improve efficiency. The improvement in efficiency of a company would not only benefit the shareholders, but also the investors and other stakeholders of the company. Originality/value In the context of Indian economy, very limited number of studies have focused to measure the efficiency of oil and gas sector in the context of Indian economy. The present study aims to provide the latest insight to the efficiency of the companies especially operating in the Indian oil and gas sector. Further, as per our knowledge, this study is distinctive in terms of analyzing the efficiency of Indian oil and gas sector for a period of five years. The longitudinal study of the sector efficiency provides a bird eye view of the average efficiency level and changes in the efficiency levels of the companies over the years.

The impact of research and development and marketing costs on the profitability of pharmaceutical companies of Tehran Stock Exchange using panel data 2001-2013

2016 ◽  
Vol 10 (4) ◽  
pp. 467-476 ◽  
Author(s):  
Yahya Bayazidi ◽  
Enayatollah Homaie Rad ◽  
Mehdi Mojahedian ◽  
Mehdi Toroski ◽  
Azita Nabizadeh ◽  
...  
Keyword(s):  
Panel Data ◽  
Research And Development ◽  
Stock Exchange ◽  
Random Effect ◽  
Patent Law ◽  
Pharmaceutical Companies ◽  
Content Type ◽  
Marketing Costs ◽  
The Impact ◽  
D Investment

Purpose The main aim of this study is to investigate the effects of marketing and costs and research and development (R&D) investments on profitability of pharmaceutical companies of Iran. Design/methodology/approach In this study, pharmaceutical companies that have been accepted in Tehran Stock Exchange until March 19, 2013 were investigated. Random-effect panel data estimator was used for this purpose. Findings The findings indicate that variables such as company size, capital-to-total asset ratio and debt-to-asset ratio have an effect on profitability. But, company life, advertising cost and R&D investment are ineffective on profitability. Originality/value Legal issues like not having patent law and pricing mechanism are reasons for the ineffective relationship between R&D and marketing costs and its effect on profitability of the Iran pharmaceutical industry.

Do Women Directors Impact the Risk and Return of Indian Banks?

2020 ◽  
Vol 10 (1) ◽  
pp. 44-65
Author(s):  
Ankur Shukla ◽  
Narayanasamy Sivasankaran ◽  
Prakash Singh ◽  
Ayyaluswamy Kanagaraj ◽  
Shibashish Chakraborty
Keyword(s):  
Panel Data ◽  
Stock Exchange ◽  
Data Models ◽  
Panel Data Models ◽  
Women Directors ◽  
Return On Assets ◽  
Risk And Return ◽  
Form Part ◽  
Indian Banks ◽  
The Impact

The purpose of the paper is to investigate whether women directors impact the risk and return of Indian banks. This study employs panel data models for a sample of 29 Indian banks that form part of the National Stock Exchange 500 index for the period 2009–2016. This paper concludes that women directors influence the accounting returns (measured through Return on Assets) of Indian banks. However, it was found that women directors did not affect the risks (measured through Equity Beta and gross NPA to Total Assets) of the sample banks. This paper contributes to the literature and practitioners in several ways. To the best of the knowledge of the authors, no study has examined the impact of women directors on the risk and return of banks operating in India. Hence, the findings of this article have substantial implications both to academia and practitioners.

scholarly journals Estimating technical efficiency of Chinese table grape wholesalers

2015 ◽  
Vol 117 (6) ◽  
pp. 1670-1688 ◽  
Author(s):  
Weihua Jiao ◽  
Zetian Fu ◽  
Weisong Mu ◽  
Xiaoshuan Zhang ◽  
Jianjun Lu ◽  
...  
Keyword(s):  
Technical Efficiency ◽  
Agricultural Research ◽  
Table Grape ◽  
Scale Efficiency ◽  
Tobit Regression ◽  
Policy Makers ◽  
Content Type ◽  
Explanatory Variables ◽  
Parametric Data ◽  
Grape Varieties

Purpose – The purpose of this paper is to estimate the technical efficiency of Chinese table grape wholesalers and subsequently to examine the degree to which the calculated efficiency correlates with a set of explanatory variables. Design/methodology/approach – A two-stage procedure is applied in this paper. First, a non-parametric data envelopment analysis (DEA) technique is applied to investigate the degree of technical efficiency for Chinese table grape wholesalers. Second, Tobit regression is used to analyze the factors influencing technical efficiency. Findings – Research results reveal that the mean technical efficiency of the sample is 0.544 and 0.860 under constant returns scale (CRS) and VRS assumptions, respectively, and the scale efficiency (SE) is 0.620. The variables of experiences, number of grape varieties on sale, daily selling volumes and fixed sale ratio have a significant effect on technical efficiency, while the other exogenous variables do not affect the efficiency in any significant way. Research limitations/implications – The findings of this research are specific to table grape wholesalers in China, however, the method used in this study is transferrable and applicable to the study of similar problems in others countries. Originality/value – This research has yielded some interesting and original insights into the efficiency level of Chinese grape wholesalers and the factors that influence the level of efficiency. The findings have practical implications for Chinese agriculture policy makers, and are able to stimulate further research of a similar type in the international agricultural research community.

Corruption and economic growth in some selected transitional economies

2009 ◽  
Vol 5 (1) ◽  
pp. 70-82 ◽  
Author(s):  
Hakeem Ishola Mobolaji ◽  
Kamil Omoteso
Keyword(s):  
Economic Growth ◽  
Maximum Likelihood ◽  
Panel Data ◽  
Maximum Likelihood Estimation ◽  
Random Effect ◽  
Likelihood Estimation ◽  
Transitional Economies ◽  
Content Type ◽  
Estimation Techniques ◽  
Data Framework

PurposeThe general objective of the paper is to investigate the impact of corruption and other institutional factors on economic growth in some selected transitional economies for the period of 1990‐2004 and make policy recommendations for combating it. Specifically, the study attempts to: assess whether corruption has any impact on the growth of the sample countries; examine whether simultaneous policy reform focussing on accountability and rule of law impact positively on growth of these economies; and investigate whether corruption in these countries exhibit the efficient grease syndrome.Design/methodology/approachThe indices for corruption and other institutional variables were drawn from International Country Risk Guide (ICRG – PRS) for the period of 1990‐2004, the polity data were obtained from the Polity IV, while the real gross domestic product (GDP) per capita growth were obtained from the Penn World 6.2. The study covered the period between 1990 and 2004 that coincides with the real transition of these economies from centrally planned to market economies. It adopts the panel data framework, the fixed effect, the random effect and the maximum likelihood estimation techniques for the analysis.FindingsThe study's findings support Mauro's hypothesis that corruption has a negative impact on the economies. However, the study cannot find a robust statistical evidence to support the efficient grease hypothesis of Leff and Huntington.Research limitations/implicationsThe paper recommends policy efforts that would strengthen accountability and bureaucratic quality, reduce discretionary power, ethnic fractionalisation and military involvement in politics with a view to enhancing social responsibility practices at both micro and macro levels.Originality/valueUnlike previous studies that focussed on single cross‐country regression with an assumption of identical aggregate production function for all countries, this study adopts the panel data framework that makes it possible to allow for differences in the form of unobservable individual country effects. The paper employs the fixed effect, the random effect and the maximum likelihood estimation techniques.

Banking outreach, infrastructure development and regional growth

2017 ◽  
Vol 13 (2) ◽  
pp. 114-127 ◽  
Author(s):  
Harishankar Vidyarthi
Keyword(s):  
Panel Data ◽  
Income Elasticity ◽  
Regional Growth ◽  
Composite Index ◽  
Least Square ◽  
Infrastructure Development ◽  
Indian States ◽  
Content Type ◽  
Data Framework ◽  
Long Run

Purpose The purpose of this paper is to examine the dynamics between banking penetration, infrastructure development and regional growth within a multivariate framework in 23 Indian states over the period 2000-2012. Design/methodology/approach The study employs the multivariate panel data framework to analyze the dynamics between banking penetration, infrastructure development and regional growth within the vector error correction model (VECM) framework. Findings The findings confirm the long-run equilibrium relationship between banking penetration, infrastructure and income for the panel. Long-run income elasticity of infrastructure, estimated using Panel dynamic ordinary least square, is positive, statistically significant and has a value of 0.1531. Further, results show bidirectional causality between income and aggregate infrastructure and unidirectional causality running from banking penetration to income and aggregate infrastructure in the long run. However, there is unidirectional causality running from income to banking penetration and aggregate infrastructure and from banking penetration to aggregate infrastructure in the short run. Research limitations/implications The study mainly concentrates on the 2000-2012 period and includes transportation (roadways and railways), energy (including electricity) and telecommunication as indicators for infrastructure, as the data for these sectors are easily available at the state level. Second, this study employs the panel data technique as it has a shorter data count. Practical implications In order to minimize the existing regional disparity in a developing India, national infrastructure policies should be aimed toward improving the overall access to as well as the quality of infrastructure (existing as well as newly planned). Further, widening the banking outreach at the bottom level may further help the economy as well as the infrastructure sector in mobilizing long-term finances for productive investments, in order to have a balanced, more inclusive and faster growth in the long run. Originality/value The study employs panel unit root, cointegration and Granger causality tests within the panel VECM framework to explore the dynamics among the system variables. Further, the study creates a composite index of infrastructure with principle component analysis.

Cost efficiency analysis of scheduled commercial banks: empirical evidence from India

2018 ◽  
Vol 37 (7) ◽  
pp. 586-602
Author(s):  
Aparna Bhatia ◽  
Megha Mahendru
Keyword(s):  
Cost Efficiency ◽  
Commercial Banks ◽  
Banking Sector ◽  
Global Financial Crisis ◽  
Allocative Efficiency ◽  
Specific Reference ◽  
Tobit Regression ◽  
Content Type ◽  
Cost Inefficiency ◽  
Indian Banks

Purpose The purpose of this paper is to analyze and evaluate cost efficiency (CE) scores of Indian Scheduled Commercial Banks (SCBs) in India over a period of 22 years, i.e. 1991–1992 to 2012–2013. Design/methodology/approach Data envelopment analysis (DEA) – a non-parametric approach is used to calculate efficiency scores of banks. Further the efficiency scores are decomposed into technical and allocative efficiency. The differences in the efficiency scores across ownership as well as across reformatory and post-reformatory era are examined by applying Panel Tobit Regression. Findings The paper also identifies the reason for cost inefficiency among Indian banks. In addition, the nature of their return to scale of all SCBs has also been evaluated. The results of the paper depict that Indian SCBs have never achieved full CE score of 1 in any of the years of study. The dominant reason identified behind cost inefficiency is allocative inefficiency. Surprisingly, the results also highlight that SCBs exhibit higher CE scores in reformatory era as compared to the post-reformatory era. Originality/value With specific reference to India, even lesser literature is found on CE. Indian banking sector has witnessed many changes on account of liberalization, privatization and globalization (LPG). Before banks adapted to the new environment, the global financial crisis acted as a fuel to fire affecting the performance of banks. Thus, a reassessment over a longer period would help to know a wholistic view of the issue of cost inefficiency, which has always been a troubling factor for Indian banks.

scholarly journals Bank Mergers Performance and the Determinants of Singaporean Banks’ Efficiency: An Application of Two-Stage Banking Models

2007 ◽  
Vol 9 (1) ◽  
pp. 19 ◽  
Author(s):  
Fadzlan Sufian ◽  
Muhamed-Zulkhibri Abd. Majid
Keyword(s):  
Banking Sector ◽  
Positive Impact ◽  
Negative Influence ◽  
Scale Efficiency ◽  
Bank Performance ◽  
Tobit Regression ◽  
Bank Efficiency ◽  
Factors Affecting ◽  
Overall Efficiency ◽  
Loan Quality

An event study window analysis of Data Envelopment Analysis (DEA) is employed in this study to investigate the effect of mergers and acquisitions on Singaporean domestic banking groups’ efficiency. The results suggest that the mergers have resulted in a higher post-merger mean overall efficiency of Singaporean banking groups. However, from the scale efficiency perspective, our findings do not support further consolidation in the Singaporean banking sector. We find mixed evidence of the efficiency characteristics of the acquirers and targets banks. Hence, the findings do not fully support the hypothesis that a more (less) efficient bank becomes the acquirer (target). In most cases, our results further confirm the hypothesis that the acquiring bank’s mean overall efficiency improves (deteriorates) post-merger resulted from the merger with a more (less) efficient bank. Tobit regression model is employed to determine factors affecting bank performance, and the results suggest that bank profitability has a significantly positive impact on bank efficiency, whereas poor loan quality has a significantly negative influence on bank performance.

Trends of cost efficiency in response to financial deregulation

2015 ◽  
Vol 22 (5) ◽  
pp. 808-838 ◽  
Author(s):  
Rachita Gulati
Keyword(s):  
Panel Data ◽  
Cost Efficiency ◽  
Banking Industry ◽  
Positive Impact ◽  
Balance Sheet ◽  
Content Type ◽  
Financial Deregulation ◽  
Efficiency Measures ◽  
Dea Models ◽  
Indian Banks

Purpose – The purpose of this paper is to examine the trends of cost efficiency (CE) of Indian banks in response to financial deregulation programme launched in early 1990s. More specifically, the findings of this paper offer empirical testing of the basic underlined hypothesis that the CE of banks will rise in the more liberal and competitive environment. Design/methodology/approach – The study employs input-oriented data envelopment analysis (DEA) models that incorporate the quasi-fixed inputs to compute the cost, technical, and allocative efficiency scores for individual banks. The unbalanced panel data spanning from the financial year 1992-1993 to 2007-2008 are used for obtaining efficiency measures. In addition, the panel data Tobit model has been applied to investigate the bank-specific factors explaining variations in the CE. Findings – The empirical findings pertaining to the trends of efficiency measures suggest that: first, deregulation programme has had a positive impact on the CE of Indian banks, and the observed increase in CE is entirely due to improvements in technical efficiency (TE); second, the ranking of ownership groups provides that public sector banks are more cost efficient along with the foreign than private banks; and third, there is a strong presence of global advantage hypothesis in the Indian banking industry. The results of post-DEA analysis reveal that size and exposure to off-balance sheet activities are the key determinants of CE. The results also support the existence of bad luck or bad management hypothesis in Indian banking industry. Practical implications – The practical implication of the research findings is that the financial deregulation programme seems to be successful in achieving the CE gains in the Indian banking industry. This explicitly signals that the cautious approach of banking reforms adopted by Indian policy makers has started bearing fruit in terms of the creation of an efficient banking system, which is immune to any sort of financial crisis, and resilient to both internal and external shocks. Originality/value – The present study offers new evidence on the time-series properties of cost, allocative, and TEs of Indian banks. The DEA models used in this study explicitly incorporate the equity as a quasi-fixed input, which accounts for “risk” in the bank efficiency measurement.

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