Liquid assets are critical for banking operations. They guarantee avoiding liquidity risk and widens managerial decision options to invest in emerging profitable projects; however, holding extra liquidity entails opportunity costs. Accordingly, empirical literature does not provide a conclusive relationship between liquidity and profitability. The purpose of this research is to analyze the asymmetric effects of holding liquid assets by commercial banks on their profitability. Parallel to a detailed review of contradicting theories and empirical evidence, we have developed an econometric model to capture the nonlinear effects of liquidity on performance. The proposed model is tested for a sample of seven listed Iranian commercial banks during 2006-2018 by Arellano-Bond dynamic panel-data estimation. We found that the nonlinear relationship, if any, is not an inverse U as Bordeleau and Graham (2010) suggested. Results show a positive (holding more liquid assets increases the profitability of Iranian banks), and even an accelerating effect for liquidity, likely due to the low level of liquid assets maintained by Iranian banks.
Corporate governance of banks is one of the most important structures required by banks to maintain the health and stability of banks, which can play an important role in managing banks' risk. This paper examines the effect of corporate governance on liquidity risk management, credit risk management, and total bank risk management. We used board structure effectiveness, transparency, and responsibility as corporate governance indicators. The financial ratio approach is also used to measure risk management. The period under review was 2006-2018. In addition to corporate governance criteria, other explanatory variables affecting banks' risk management have also been used. This paper used the performing unit root, cointegration, and F-Limmer tests to ensure panel estimation. Given the impact of past banks' risk management on current risk management, this variable has also been modeled as an explanatory variable. For this reason, the GMM method has been used to estimate the models in question. Given the importance of bank size in corporate governance on bank risk management, Banks are divided into large and small groups, so the effect of corporate governance in large and small banks has also been investigated on bank risk management. The results show that compliance with corporate governance criteria positively affects banks' risk management. However, due to weak corporate governance in large banks, corporate governance in large banks hurts bank risk management.
This study investigates monetary and financial shocks on macroeconomic variables, focusing on the role of banking intervention. For this purpose, a Keynesian dynamic stochastic general equilibrium (DSGE) model is designed for Iran’s economy that involves financial and banking sectors. The results of the model simulation show that the financial accelerator theory works in the Iranian economy. Also, the intermediary role is confirmed by the impulse response function. In other words, economic policies can impress on macroeconomic indicators more when banks intervene in the economy. Therefore, to control the effects of economic shocks on banks' performance, it has been suggested that monetary policymakers pay attention to the important roles of financial markets in the transfer mechanism and monetary policy intensity. On the other hand, because of mandatory rules of interest rates determination, banks have to establish a commission and nonprofit services instead of sharing income to decrease the effect of economic shocks.
The technological revolution has spread over today's world, and it is clearly seen in banking, especially electronic banking. E-Banking has many dimensions, criteria, and components, and judging its progress based on dimensions leads to difficulty and bias. There is also a lack of comprehensive information references in the literature. Therefore, introducing a combinational index to accurately assess its progress is inevitable. In this research, the E-Banking Progress Index (E-BPI), which focuses on the infrastructures and the tools of e-banking and has five dimensions: Technical and Communicational Infrastructures; Services; Cultural-Educational Infrastructures; Security and Supervision; and Legal-Regulatory Infrastructures is created. It also has several applications in investigating the progress of e-banking in a bank or a country and comparing it among banks or countries. This research, using Analytic Hierarchy Process (AHP), leads to the introduction of a combinational index to measure the progress of e-banking, which is able to analyze its strength and weakness. E-BPI provides a score between 0 and 1. The more the score, the stronger the e-banking is.
This paper studies the effect of the space (distance) between lotteries' outcomes on risk-taking behavior and the shape of estimated utility and probability weighting functions. Previously investigated experimental data shows a significant space effect in the gain domain. As compared to low spaced lotteries, high spaced lotteries are associated with higher risk aversion for high probabilities of gain and higher risk-seeking for low probabilities of gain. Hence, the investigation is carried under cumulative prospect theory that respects framing effect and characterizes risk attitudes with respect to probabilities and outcomes. The observed certainty equivalents of lotteries are assumed to be driven by cumulative prospect theory. To estimate the parameters of cumulative prospect theory with maximum likelihood, the usual error term is added. The cumulative prospect theory is incapable of explaining the space effect as its parameters cannot explain the average behavior. Taking account of heterogeneity, a two-component mixture model shows that behavioral parameters of around 25% of the sample can explain the observed differences in relative risk aversions. The results confirm the previous findings of aggregation bias associated with representative-agent models. Furthermore, the results have implications for experimental designs as high space between lotteries' outcomes is required to guarantee the curvature of utility functions.
Foreign Direct Investment (FDI) is frequently regarded as a key driver of global economic integration because it brings job opportunities, capital investment, and business experience. The current study examines the impact of foreign direct investment on Afghanistan's economic growth using time-series data from 2007 to 2019, which are collected from the World Bank and the International Monetary Fund's annual macroeconomic data sources for the country. Foreign direct investment (FDI), trade (Trd), inflation (InfR), and real interest rate (Int) are independent variables for regressing on this country's gross domestic product (GDP), while "GDP" is as a dependent variable. The method of ordinary least squares (OLS) was utilized to investigate the impact of these variables on Afghanistan's economic growth. For unit root test, the Augmented Dickey-Fuller (ADF) one was utilized, while co-integration, Granger causality, and the Vector Error Correction Model (VECM) were all used to capture two-way linkages between variables and were shown to hold in the long run. Our findings indicate that foreign direct investment and trade have a negative and significant impact on Afghanistan's economic performance in the short run but that all variables except inflation have a positive and significant impact on economic growth in the long run. According to the study, a rigorous policy mix is required to absorb "FDI" while supporting infant industries and reducing Afghanistan's balance of payments deficit for growth and future development.