Banking

Given the rapid development of the banking sector, it is reasonable to expect that the performance of banks has become the centre of attention among bank managers, stakeholders, policy makers, and regulators. In order to maximizing the share-holders’ satisfactory level, two bank efficiency measurement approaches, i.e. the production approach and the user cost approach, which are financial evaluations, are employed. The evaluations are done by means of data envelopment analysis method. The proposed methodology is run on the 15 privet bank branches in Markazi province. By using this approach, four regions that show the various performances are obtained. In addition the status of returns to scale for each bank branch is calculated.

In this study, an evaluation model is developed to assess the credibility of the loan applicants. The proposed model is a multicriteria decision making (MCDM) problem consisting of numerous criteria by integrating analytic hierarchy process (AHP) and genetic algorithm (GA). In the case of apparent consensus for several measures, the research clearly indicates that both quantitative and qualitative information must be employed in evaluating loan applicants. The AHP approach is widely used for MCDM in various scopes. In 2008 Lin et al proposed the adaptive AHP approach (A 3 )in order to decrease the number of steps for checking the inconsistency in the AHP model. The study presents a MCDM model by developing the new adaptive AHP approach (N_A 3 ) already proposed by Herrera-Viedma in 2004. The proposed model has led to fewer calculations, and less complexity. The model was applied to 200 clients in order to show its efficiency and applicability. A brief look at the implementation of the model showed that it is significantly valid in selecting clients with respect to the known criteria, besides decision making regarding the determination of the assessment factors.

Social capital is a relatively new concept in the social sciences and is one of the most important challenges of new era in a way that based on experts’ comments, the solution for all the problems of today’s modern world is social capital. To this end, one of the problems that managers of organizations particularly; service and manufacturing organizations have faced with today is lack of trust in accurate implementation of contract specifically implied contracts. If managers tend to control the whole organization for the accurate implementation of these contracts, it would lead to extravagant costs. One proper and certain way to solve this problem is to apply elements and components of social capital in organizations. By deploying scientists’ thoughts regarding social capital, the present research attempts to analyze the evidence of social capital reduction in banking industry and test its impact along with other forms of capital on GDP of the country. Findings of this study indicate that there is a significant and reverse relation between social capital reduction in banking industry and GDP. JEL Classifications: J24, E23, D81, E58

The Basel Committee on Banking Supervision (BCBS), in response to the recent financial crisis, has developed new stability rules aimed at preventing financial crises in the future. This paper uses the new Liquidity Ratio (LCR) and attempts to determine the impact of this ratio on the stability of the banking system. The objective of the LCR is to promote the short-term resilience of the liquidity risk profile of banks. It does this by ensuring that banks have an adequate stock of unencumbered high-quality liquid assets. The LCR will expand the banking sector’s ability to bear shocks arising from financial and economic stress. We find that liquidity coverage ratio as a requirement in the regulation develops bank stability. Specifically, banks with more liquidity coverage ratio are more stable. The role of banking ownership is also pursued as another goal in the paper. According to the results, there is the positive effect of the liquidity coverage ratio on stability in private banks and there are the negative effects of the liquidity coverage ratio on stability in state and specialist banks. We find that there is a difference between state banks and specialized banks with private banks. The state and specialized bank have more liquidity risk than private banks in Iran.

Economic growth is the most common goal in any economy, and capital is one of the most important determinants of growth. In the last few decades, the use of securities in various countries' capital markets has expanded and has become an essential part of the economic system supplying the capital need for investors and other institutions. This study aims to analyze the effect of securities used to finance banks (securitization) on economic growth. For this purpose, the theoretical analysis method is used in the framework of a Dynamic Stochastic General Equilibrium (DSGE) model. The theoretical model used is based on Frank Ramsey's (1928) economic growth model. To transform this model into a suitable model for research, the shadow banking system and securitization have been added. The model is then simulated using the calibration method and using the real data of the US economy; then, the macroeconomic changes and fluctuations created by bank securities are explained and analyzed. According to the research findings, issuing securities by banks will lead to slower economic growth. Therefore, it is recommended to avoid the use of securitization in banking.

In the real world, situations frequently occur when we want to allocate a fixed cost between a set of decision-making units (DMUs) such as institutions, organizations. In this paper, we use the data envelopment analysis (DEA) technique to allocate fixed costs among DMUs. First, we introduce semi-additive production technology in DEA and present efficiency evaluation models in this technology. In estimating the frontier of this technology, in addition to the observed DMUs, the set of all aggregations of these DMUs are also used. In the following, we propose an interactive process for fixed cost allocation between DMUs in DEA based on the concept of cross-efficiency. We show that our proposed iterative approach is always feasible, and ensures that all DMUs become efficient after the fixed cost is allocated as an additional input measure. The cross-efficiency scores corresponding to all DMUs are improved at each stage of the interactive process. We also illustrate the proposed approach with a numerical example. The proposed approaches are demonstrated using an application of the fixed cost allocation problem for branches of commercial banks. Finally, we bring the results of the research.

In many practical problems, we face situations where the data ratio is important for the decision-maker (DM). Data envelopment analysis ratio-based (DEA-R) and ratio analysis models are presented to deal with the above issue in data envelopment analysis (DEA). If the data is uncertain, it is no longer possible to use the basic DEA-R and ratio analysis models to evaluate the efficiency of decision-making units (DMUs). In this paper, we will first discuss robust optimization modelling based on DEA-R models. In this regard, we consider a case where the inputs have an uncertain numerical value and the outputs have certain values. In the following, we present the ratio analysis model based on the set of common weights of all the ratios of input to output components and obtain this model for robust optimization. To show the validity of the proposed approach, we use it to evaluate the efficiency of 38 excellent banks that compete in the global market and compare the results of the proposed approach in this paper with the results of previous approaches.