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Fisher’s amount of information is the most parametric measure in the literature of statistics. However, not for every family of probability density functions do the well‐known regularity assumptions hold. To avoid this problem, several parametric measures have been proposed on the basis of divergence measures. In this work, parametric measures of information are obtained on the basis of the generalized Jensen difference divergence measures. When the regularity assumptions hold, their relations with Fisher’s amount of information are also studied.

Since there is no agreement on the consistency of their estimates, the purpose of this paper is to investigate whether parametric stochastic frontier analysis (SFA) and nonparametric data envelopment analysis (DEA) generate consistent bank efficiency assessments.

The authors utilize four alternative efficiency computation models: two DEA technical efficiency models based on constant and variable returns to scale, and two SFA cost efficiency models employing Translog and Fourier functional specifications. An unbalanced panel of 59 Indian banks over 1990‐2007 is employed as a model, developing country, banking market.

The Translog and Fourier specifications in SFA and the constant and variable returns to scale assumptions in DEA are found to rank and identify “best‐practice” and “worst‐practice” approximately in the same order. The association between DEA efficiency estimates and non‐frontier standard performance measures, however, is mixed and inconclusive. Unlike DEA scores, SFA efficiency assessments were found to be consistent with cost and profit ratios and hence are “believable”.

For regulators and bankers alike, the authors' findings highlight the importance of investigating the consistency of efficiency scores across various research methods. They should ensure that frontier‐based efficiency assessments are not simply “artificial constructs” of models' assumptions/specifications.

This paper extends the existing literature by checking jointly the statistical consistency of both DEA technical efficiency scores and SFA cost efficiency scores. The prior studies focus either on technical efficiency or cost efficiency, but not both. Moreover, as far as the authors are aware, this is the first cross‐methodological validation study to focus on bank efficiency in the context of a developing country banking market.

Due to stern management policies and increased community attentiveness, sustainable supply chain management (SSCM) performs a vast component in endeavor operation and production management. Sustainable circular supplier selection (SCSS) and evaluation presented the environmental and social concerns in the fields of circular economy and sustainable supplier selection. Choosing the optimal SCSS is vital for organizations to persuade SSCM, as specified in various researches. Based on the subjectivity of human behavior, the selection of ideal SCSS often involves uncertain information, and the Pythagorean fuzzy sets (PFSs) have a huge capability to tackle strong vagueness, uncertainty and inaccuracy in the multi-criteria decision-making (MCDM) procedure. Here, a framework is developed to assess and establish suitable suppliers in the SSCM and the circular economy.

This paper introduced an extended framework using the evaluation based on distance from average solution (EDAS) with PFSs and implemented it to solve the SCSS in the manufacturing sector. Firstly, the PFSs to handle the uncertain information of decision experts (DEs) is employed. Secondly, a novel divergence measure and parametric score function for calculating the criteria weights are proposed. Thirdly, an extended decision-making approach, known as PF-EDAS, is introduced.

The outcomes and comparative discussion show that the developed method is efficient and capable of facilitating the DEs to choose desirable SCSS. Therefore, the proposed framework can be used by organizations to assess and establish suitable suppliers in the SCSS process in the circular economy.

Selecting the optimal sustainable circular supplier (SCS) in the manufacturing sector is important for organizations to persuade SSCM, as specified in various research. However, corresponding to the subjectivity of human behavior, the selection of the best SCS often involves uncertain information, and the PFSs have a huge capability to tackle strong vagueness, uncertainty and inaccuracy in the MCDM procedure. Hence, manufacturing companies' administrators can implement the developed method to assess and establish suitable suppliers in the SCSS process in the circular economy.

This paper aims to examine the performance of Islamic and conventional stocks listed at the Pakistan Stock Exchange by using both parametric and non-parametric approaches. The motivation is to do risk-return analysis of Islamic stock prices and conventional stock prices.

It uses various measures of performance, e.g. Sharpe ratio, Treynor ratio, Jensen's alpha, beta, generalized auto-regressive conditional heteroskedasticity and stochastic dominance. Using the Karachi Meezan Index-30 (KMI-30) and the Karachi Stock Exchange Index-30 (KSE-30) as proxies for Islamic and conventional stock prices, respectively, it examines the performance of Islamic and conventional stocks. The daily data of KMI-30 and KSE-30, covering period from June 9, 2009 to June 20, 2020 are used.

The results show that the overall KMI-30 outperforms the KSE-30. The returns of the KMI-30 are greater than the KSE-30. However, the risk and volatility of the KMI-30 and KSE-30 are similar. Further, the KMI-30 has higher excess returns per unit of total risk than the KSE-30. But both indexes have similar excess returns per unit of systematic risk. Moreover, the KMI-30 returns have stochastically dominance over the KSE-30 returns. These results reveal that the Islamic index performs better than the conventional index.

The findings provide several practical implications in financial and investment decisions making by investors, managers and policymakers such as strategies for asset allocation and investment. Further, in risk management, it provides guidance for allocating portfolios and managing risk. The investment in Islamic stocks may mitigate potential risk within asset portfolios.

This research is unique in its approach to the analysis of the performance comparison of conventional and Islamic stock by using comprehensive parametric and non-parametric estimation techniques. Such research has not been undertaken in the Pakistan's equity market since.

A brief review of earlier studies on the productivity scenario of Indian industry shows that most of the studies analysed are confined to either parametric approach or growth accounting approach of measuring productivity. At the same time, the few studies based on the non-parametric [namely, Malmquist productivity index (MPI)] overlook the returns to scale conditions as well as the bias involved in the estimation of distance functions. Given this backdrop, this study aims to provide a robust measure of productivity, which considers the returns to scale assumptions and correct for the bias involved in the estimation of productivity.

This study empirically tests for the returns to scale that exists in the chemical and chemical products industry in India. The test result suggests that Ray and Desli (1997) approach of MPI is the appropriate one for the present context. Initially, the conventional Ray and Desli (1997) estimation and decomposition of MPI for the period 2001 to 2017 is being used. Subsequently, to correct for the bias in the estimation of efficiency scores used for the estimation of MPI, the bootstrapping algorithm of Simar and Wilson (2007) has been extended into the context of MPI estimation.

The results from the conventional Malmquist productivity estimates testifies to an improvement of total factor productivity (TFP) in seven out of 16 years under consideration. On the contrary, TFP growth is recorded only in the four years throughout the period after the bias correction. A greater discrepancy between the two measures has been found in the case of scale change factor component of MPI.

The technical change (TC) component positively influences TFP, whereas scale change factor (SCF) deteriorates the TFP condition of this industry. It will be appropriate for these firms to identify and operate under an optimal scale of operation, along with reaping the benefits of technological change. From a methodological perspective, researchers should consider the potential bias that arise in estimation of TFP and use a larger sample whenever possible.

This paper brings in a new perspective to the existing literature on industrial productivity. As against earlier studies, this study empirically tests the returns to scale of the sector under consideration and uses the most appropriate approach to measure productivity. The effect of sampling bias on TFP and its components is analysed.

The study aims to investigate the relationship between competition and efficiency. Using bank-level data for Indian banks, relationship between competition and efficiency is examined by applying the Granger causality test for the period 1996 to 2011.

Lerner Index is a measure of market power and is applied for estimation of competition. Data envelopment analysis technique is applied for measuring efficiency in the Indian banking system along with the Granger causality test to look at the relationship between competition and efficiency.

Results show an increasing trend for competition for the period 1996 to 2004, and after that there is fall in competitive levels. Granger causality tests show that competition positively effects efficiency and vice-versa.

This study gives an insight into the relationship between competition and efficiency, thus providing an alternative view to the structure–conduct–performance paradigm. An efficient banking system can positively impact the growth of an economy and, hence, competition and efficiency are important decision parameters for regulators and could help them in decision-making and policy formulation.

This study has covered more than 90 per cent of the banking assets for looking at competition and efficiency in the banking sector. Policymakers can try to improve competitive levels in banking so as to improve efficiency in the banking sector which can further help in developing the investment-savings cycle.

The purpose of this paper is to investigate the efficiency of selected conventional and Islamic unit trust companies in Malaysia during the period 2002 to 2005.

The paper adopts Data Envelopment Analysis (DEA) to investigate efficiency, as measured by the Malmquist index, which is decomposed into two components: efficiency change and technical change indexes.

The study indicates that technical efficiency is the main contributor to enhancing the efficiency of the Malaysian unit trust industry. In addition, the larger the size of the unit trust companies, the more inefficient the performance. In comparing the efficiency of unit trust companies, the study finds that some of the Islamic unit trust companies perform better than their conventional counterparts.

The study is limited to five Islamic unit trust companies. Thus, the findings of this study are indicative, but inconclusive for the unit trust industry as a whole.

The results have two important implications for both conventional and Islamic unit trust companies in Malaysia. First, the deterioration of total factor productivity (TFP) in the unit trust industry in Malaysia is due to the deficiency of innovation in technical components. Second, the size of the unit trust companies has an adverse effect on the TFP performance.

The contribution of this study is that it analyzes the efficiency of the two types of unit trust industry which are important and relevant for Malaysia. This significance arises from the dual financial system, in which the Islamic unit trust companies operate in parallel with their conventional counterparts. The comparison sheds some light on the performance of the Islamic unit trust companies, whose operations are based on profit‐sharing, in contrast to the conventional unit trust companies.

The purpose of this paper is to investigate whether differences in media exposure regarding corporate corruption appear to influence companies’ anti-corruption disclosures. The authors also examine whether the level of press freedom in firms’ home countries affects disclosure and the impact of media exposure in different ways.

The authors use Transparency International’s 2012 ratings of anti-corruption disclosure by the 105 largest multinational firms in the world, press freedom assessments from the non-governmental organization Reporters Without Borders, and media exposure measures based on a search using the Dow Jones Factiva database. The authors assess relations using regression analysis controlling for other firm-specific factors potentially impacting disclosure choices. Finally, the authors consider the potential effect of other country-level factors.

The results indicate that media exposure, using either an existence or an extensiveness measure, is positively related to differences in sample companies’ anti-corruption disclosures. The authors also find that disclosure is more (less) extensive where home country press freedom is less (more) restricted and that reduced press freedom appears to reduce the impact of media exposure on the disclosure. The authors further document that press freedom levels explain more difference in anti-corruption disclosures than other country-level factors potentially influencing the practice.

Because the investigation is limited to very large international firms for a single year, the degree to which the findings apply to other companies and time periods cannot be assessed. Further, the authors cannot determine how the findings would hold using an alternative disclosure rating scheme. Finally, the authors do not assess whether differences in the source of media exposure impact the findings.

The findings suggest that, to the extent that improved anti-corruption disclosure reflects greater corporate attention to corruption issues, the media may be a powerful player in addressing this social ill. Unfortunately, the results also indicate that media efforts may not be sufficient to bring about change in locations where the freedom of the press is limited. Further, the results suggest that disclosure appears to be a function of exposure to social and political exposures, and the authors therefore question whether it will actually lead to improved corruption performance.

The study is the first to consider the impacts of media exposure and press freedom on corporate social disclosures.

The purpose of the research presented in this paper is to measure the relative market efficiency of the top listed companies in Egypt.

Applying a two‐stage approach, this study uses production frontier analysis (PFA) to measure the relative market efficiency of 62 listed companies in Egypt, and Tobit regression to examine the dependence of efficiency on the specific operating environment of these companies.

The results indicate that the performance of several companies is sub‐optimal, suggesting the potential for significant improvements over both profitability and marketability dimensions. Separate benchmarks were derived for possible reductions in resources used, and the results indicate that several companies deploy a much larger number of employees than required by a best practice company, and significant savings are possible on this account.

From a policy perspective, this study highlights the economic importance of encouraging increased market efficiency throughout the business sector in Egypt.

The purpose of this paper is to examine the evolution of interconnectedness of European insurers among themselves, as well as with other non-financial firms, for the period 2000–2021 and to analyze the stock return movements around the costliest catastrophic events (hurricanes) in the past two decades.

This paper follows the “simple” approach of Patro et al.(2013) and examines the daily stock return correlations of the largest 30 insurers and the largest 30 non-financial firms headquartered in Europe. In addition, the study uses event study methodology to examine stock return movements around the costliest hurricanes.

We find that the European insurance sector has become highly interconnected during the past two decades; however, its increasing connectedness with non-financial firms is limited to a few firms. In addition, we find weak evidence of the destabilizing effects of catastrophic events on European insurers and non-financial firms; however, the potential for cat risk contagion effects exists as the insurance industry becomes heavily interconnected.

The extant literature is largely concerned with the contribution of the insurance sector to the systemic risk of the financial sector. We focus on a specific region (Europe) and analyze the evolution of interconnectedness of the largest insurers within the insurance sector as well as with the largest non-financial firms encapsulating important crisis periods. In addition, we relate to the literature that examines the market reactions around catastrophic events to test the relevance of traditional insurance activities in instigating potential contagion shocks.