Journal of Money & Economy
Volume:14 Issue: 4, Fall 2019

This paper examines the impact of internal bank governance on bank liquidity creation in Iran during 2010-2017. We analyze whether banks with larger size and liquidity levels creates higher levels of liquidity. The results using panel GMM method show that corporate governance has a positive effect on liquidity creation; of course, it is not significant. Also, this effect is not affecting by bank size level, but a bank with higher liquidity levels have a higher elasticity to the governance change. Moreover, banks with higher financial stability have higher liquidity creation. Furthermore, the equity ratio index harms liquidity creation, which means “the fragility hypothesis” is confirmed within Iranian banks.

Businesses are increasingly interested in how big data, artificial intelligence, machine learning, and predictive analytics can be used to increase revenue, lower costs, and improve their business processes. In this paper, we describe how we have developed a data-driven machine learning method to optimize the collection process for a debt collection agency. Precisely speaking, we create a framework for the data-driven scheduling of outbound calls made by debt collectors. These phone calls are used to persuade debtors to settle their debt, or to negotiate payment arrangements in case debtors are willing, but unable to repay. We determine daily which debtors should be called to maximize the amount of delinquent debt recovered in the long term, under the constraint that only a limited number of phone calls can be made each day. Our approach is to formulate a Markov decision process and, given its intractability, approximate the value function based on historical data through the use of state-of-the-art machine learning techniques. Precisely, we predict the likelihood with which a debtor in a particular state is going to settle its debt and use this as a proxy for the value function. Based on this value function approximation, we compute for each debtor the marginal value of making a call. This leads to a particularly straightforward optimization procedure, namely, we prioritize the debtors that have the highest marginal value per phone call. We believe that our optimized policy substantially outperforms the current scheduling policy that has been used in business practice for many years. Most importantly, our policy collects more debt in less time, whilst using substantially fewer resources leading to a large increase in the amount of debt collected per phone call.

The 2008 Great Financial Crisis increased the fluctuations in the stock market in the US and other countries that were linked together through various channels. In this regard, derivative instruments, as one of the main elements of the world's financial markets, had an essential role in reducing the stock market fluctuations and contagion of the crisis. The primary purpose of this study is to examine the negative effect of the derivative instruments on the contagion of stock markets in developing countries, including Brazil, India, China, and Russia, using monthly stock and futures indices over the 2007:01 to 2018:08. By considering the United States of America as the source of the crisis, the hypothesis was tested with the Copula function and Kendall's tau (rank correlation coefficient). The results have confirmed the hypothesis. According to the findings, we suggest that the economy moving towards openness should develop the derivative instruments to minimize the fluctuations as well as reduce the devastating effects of crisis contagion. Also, by upgrading the information of the investors and speculators, it can decrease the depth and intensity of the fluctuations that originated from international crises.

This study aimed to investigate the role of financial and non-financial determinants of the sustainability of Iranian banks. Accordingly, the sustainability score of 27 public and private Iranian banks were evaluated in 2017 by employing a sustainability model. The model was developed by the acquisition of sustainability codes, themes, and categories in the banking industry through Meta Synthesis, while its casual structure was determined by a combined method of Interpretive Structural Modeling and Analytical Network Process. Subsequently, we calculated the sustainability scores by using our proposed model to analyze the content of the banks’ disclosed information. Then, the effect of capital adequacy, total assets, financial leverage, loan to deposit ratio, return on assets and number of branches were investigated using multiple regressions on the banks' sustainability scores. Findings depict that total assets have a positive and significant relationship and capital adequacy has a negative and significant relationship with a bank's sustainability. Therefore, banks with more assets are more willing to participate in sustainability activities, due to more appropriate financial resources, as well as to support the bank's brand and its reputation to stakeholders. On the other hand, due to the wrong belief that sustainability is costly, and non-value adding for the banks, they get less involved in order to increase their capital adequacy ratio.

In this study, the effect of socioeconomic variables on provincial bread demand using the QUAIDS model has been investigated. In this model, socioeconomic variables such as age, gender and marital status of the head of household, the education level of the head of household and spouse’s head of household, household size, and occupation status of the head household have been used. The virtual variable of the target law of subsidies is also used to study the effects of this policy. To this end, the quadratic almost ideal demand system was applied. This model has been estimated using the consolidated data and Iterated Linear Least Squares Estimator and the information of more than 165,000 urban households in Iran for the years 1386-1394 and for different provinces. The results of the research show that during the studied years, bread is an essential good for all provinces except in Isfahan, Chaharmahal o Bakhtyari, and Kohgilouye. The compensated and uncompensated price elasticities of bread for all provinces are negative and less than one, so the bread is an inelastic good for all provinces. Also, the coefficients related to household size, gender, and marital status of the head of household and the target law of subsidies are positive and significant.

By using the household data on food consumption, income and other social indicators including activity status, age, literacy, place of residence employment, and marital status, this paper aims to investigate the transitory impact of temporary and permanent income shocks on food consumption in Iran over the period 2009-2014. To study the deterministic effects of the household on food consumption and income, firstly, an Ordinary Least Squares (OLS) method is used to estimate the impact of some Iranian social characteristics on households’ income and food consumption. Then, the variance– covariance structure of income and food consumption processes is utilized, which has described by the Permanent-Temporary model (PT) to identify the characterizing parameters, which link the behavior of consumption and income to estimate the consumption-smoothing parameters. The results indicate that there is nearly complete food consumption smoothing against temporary and permanent income shocks throughout the sample period. Moreover, households’ social indicators have significant effects on their food consumption, income levels, and insurance opportunities.