فصلنامه مطالعات اقتصادی کاربردی ایران
پیاپی 46 (تابستان 1402)

Banking crises have been widespread in recent decades in different countries and have incurred significant costs to economies. Banking crises are highly disruptive events which lead to sustained declines in economic activity, financial intermediation, and ultimately in welfare. It is then no surprise that academics and policymakers devote significant efforts to develop models to attempt to predict crises and to design policies to resolve them and mitigate their economic impacts. Due to the weakness of other financial institutions in country, the banking system is one of the main institutions which has particular importance in Iran`s economy. Financial markets persistently confront with fluctuations in assets such as housing, gold and foreign exchange where these assets are often considered as a substitution for household deposits. Because these deposits are regarded as the most significant banks’ resources, an analysis of resource shortage impact on banks’ lending power on the one hand and the effect of lending power on macroeconomic variables such as output and inflation on the other hand makes it very important. Therefore, Banking system challenges cause substantial effects on the economy, especially if it is affected by the balance sheets crisis, it doubles its significance. This research, will explaining the crisis in the banking system of the country and its dimensions. By estimating the limits of the fictitious assets of the banking system of the country and the estimation of the balance sheets insolvency; within the framework of a model dynamic stochastic general equilibrium reviews its effects on macroeconomic variables. The results show bank loss impact growth negatively through decline in capital formation, raise in inflation and increase in firm’s capital and labor costs. It increase economic volatility respectively.

The purpose of the present study is to evaluate projection bias in people’s beliefs and behavioral intentions under the influence of temperature changes. For the aforementioned evaluation using of a simple binary distinction under two temperature 22 C^0and 38 C^0, projection bias in  people’s beliefs and behavioral intentions about water and electricity consumption-reducing devices has been investigated. The statistical population of this study consisted of 203 Ilam residents. The ordered probit regression analysis revealed that projection bias is evident in people’s beliefs (importance level) and behavioral intentions (willingness to purchase) concerning water and electricity consumption-reducing devices in hot weather (38°C) compared to cool weather (22°C). Regarding both categories of saving water and electricity consumption, in hot weather compared to cool weather, the level of people’s belief about devices that reduce water and electricity consumption is more than their willingness to purchase. In addition, the results showed that there is the positive and significant relationship between belief in water consumption reducing devices and the level of education as well as between the willingness to purchase of water consumption reducing devices and financial situation. Nevertheless, no significant relationship between people’s beliefs and intentions as dependent variables and age, gender, residence status and residence dimensions as independent variables were found. The results of the present study could be used by the activists of the goods and services market as well as environmental activists. It also requires the attention of the government to support eco-friendly products by setting incentives for people and to encourage people to use these products.

Environmental problems and global warming are one of the biggest concerns of societies. Using renewable energy generation technologies as one of the most basic solutions is one of the main concerns of planners and beneficiaries of power grids, considering the variability of their output power day and night and their dependence on weather conditions. The uncertainty caused by these generations can have many effects on the costs imposed on the grid and the operation of electricity grids, such as an increase in power outages and energy not supplied. To solve this problem, a comprehensive multi-objective and probabilistic model has been proposed to determine the installation location, type, and optimal capacity of DGs in the modern supply chain of electricity. The final objective of this model is to minimize energy losses, investment and operation costs, energy not supplied, and environmental emissions. The proposed methods have been implemented by MATLAB software on the Garver power grid and IEEE 33-bus distribution grid and solved by the multi-objective NSGA-II. The final model can be effectively used to plan the supply chain of the modern electricity grid with the influence of renewable energy-based products in various economic, environmental, and social dimensions.

Recently, logistics system has increasingly been recognized as one of the main driving forces of economic growth. Petrochemical industry is considered one of the strategic industries and the developments of this industry can have a great impact on the global economy and the countries in this industry. The purpose of this study is to provide an export development model in the Persian Gulf petrochemical industry with a logistics system-based approach using Grounded theory based on Strauss and Corbin method to manage it. The statistical population consisted of 10 interviews with individual experts in the sections of Persian Gulf Petrochemical Business Management, as well as prominent academic professors and experts in this field were selected as participants in the study. The interviews were conducted using the targeted method. Data were collected through interview using the general guidance method in an unstructured manner. Two methods of reviewing the participants as well as reviewing the non-participating experts were used to obtain the validity of the data. The reliability of the model was evaluated using the kappa index. The value of Kappa index was calculated to be 0.63 and was at the level of valid agreement. Interviews and coding were examined using MAXQDA software. In this research, in the open coding section, 76 open codes out of 495 concepts; In the central coding section, 76 initial codes were identified in 10 categories including export market, international marketing, export potentials, export challenges, market competition, organizational factors, macro factors, export sales, export logistics, export product characteristics.

According to Piketty’s point of view, the rate of income from wealth is always higher than the rate of economic growth, and the share of national income that belongs to capital is always more than the share of labor force. Therefore, inequality increases systematically and increasingly. The solution to this problem is to impose a maximum tax on wealth. Therefore, the tax on the components of wealth was imposed with the aim of reducing inequality. In Iran, this type of tax is collected from different components of wealth. Therefore, this research was conducted with the aim of investigating the impact of wealth tax on income distribution in Iran. For this purpose, a model was estimated in which the Gini coefficient was the dependent variable and the wealth tax and income tax were the independent variables along with the unemployment rate. Estimates were made using the time series data of 1991-2018 with the help of the Johansen-Juselius cointegration method. The results showed that there is a negative relationship between wealth tax and Gini coefficient. So that a one percent increase in wealth tax reduces inequality by 0.729 percent. The results showed that the speed of impact of wealth tax policies on income distribution is very slow, so that applying a change in wealth tax every year shows only 12% of the total impact on inequality.

Today, one of the policies that some developed countries have chosen in recent decades to deal with all kinds of problems in their society is the implementation of decentralization policy. In other words, the central governments observed that they could not perform their duties properly without the presence and role of local governments, and it is necessary that part of their powers in local and provincial areas be delegated to the relevant units. But the most important form of decentralization is financial decentralization, which has received more attention among economists and politicians in recent years. In addition to financial decentralization, the issue of social capital has entered the economic debate in recent years and has been given serious attention along with other capitals, and in Iran it has also been considered for development and growth. So, in this paper we analyze the effects of financial decentralization on social capital during 2011- 2019 period by using panel data model. The results shows that in the first model, income decentralization, per capita income and economic participation rate have a positive and significant relationship with social capital but inflation and business environment variables have a negative relationship with social capital. Also, the results of second model shows that cost decentralization, per capita income and economic participation rate have a positive and significant relationship with social capital but the variables of inflation and business environment have a negative relationship with social capital.

Economic growth is one of the headmost aims of developing and developed countries. Increasing economic growth can increase public welfare, reduce poverty and reduce unemployment. Recognizing the factors affecting economic growth is essential and undeniable, but distinguishing the obstacles to economic growth can be far headmost and effective. Risks are among the most influential and vital factors affecting economic growth. Economic and non-economic risks are consequential obstacles to economic growth. Iran is constantly exposed to various risks due to its geopolitical situation in one of the turbulent regions of the world, the Middle East. The main aim of this paper is to investigate the impact of operational risk on economic growth in Iran during 2014Q1 – 2021Q4 using the time-varying parameter vector auto-regressions (TVP-VAR). This research uses operational risk for the first time, with four main sub-indices: i.e., labor market risk, trade and investment risk, logistics risk, and security-crime risk. The results of this research show that the improvement in operational risk and its sub-indices has a positive effect on economic growth in Iran. Furthermore, international sanctions have an immense impact on operational risk and, consequently, have a negative impact on economic growth. Nevertheless, policymakers are suggested to reduce Iran’s international tensions, concretely, the countries that have an extensive impact on the world’s economy to improve the operational risk, increase foreign investments, improve the business environment, reduce the cost of trade and business transactions, and, as a result, provide the country’s economic growth and development.

In this study, due to the contradictory statements and the lack of studies on quantifying the effects of creating free zones on economic variables, the impact of this policy on the total economic value added in the provinces of West, East, Khuzestan and Gilan using the synthetic control method (SCM) has been examined. According to the results, the establishment of the Arvand Free Zone initially had a net positive effect. Then, from 1394, the net effect of policy become negative. Finally, the impact of policy on average in the whole period, has been about 8% of province value added. For Anzali Free Zone, according to the results, the average impact of policy is about 14%. After the enlargement of Anzali region in 1392, the impact of this policy increases to 30% per year. For Aras and Mako Free Zones, the impact of politics has been negative. The average effect of the policy for East Azerbaijan is (-4.5) percent and for West Azerbaijan is about (-4.7) percent per year.

The hyper volatilities of the housing market and the reasons for the emergence of boom-and-bust cycles cannot be explained by traditional theories. Recent studies indicate that behavioral factors are responsible for market volatility in the financial and real estate sectors, making it impossible to comprehend housing market events if they are neglected. According to this new viewpoint, the main objective of this study is to investigate the influence of two major behavioral principles, namely herd behavior and overoptimism, on the Iranian housing market. The seasonal data of Iran’s housing market from 2004:4 to 2021:5 and the bounds testing approach to cointegration of Pesran et al. (2001) based on the ARDL model have been utilized in this research. Since herd behavior is a hidden unobservable variable, Hwang & Salmon’s (2004) method was employed to quantify it. The quantification of herd behavior in the housing market demonstrates observable changes over time, confirming the methodology employed to quantify it in this study. The results of the cointegration test demonstrate that the correct variables influencing house prices were chosen and that there is a cointegration relationship between the research variables. Also, the results of this study reveal that behavioral components are among the most important determinants of housing prices, and that both herd behavior and overoptimism have a positive and statistically significant effect on housing prices. In addition to behavioral considerations, the results of this study indicate that economic factors such as real volume of liquidity, real GDP, and informal market exchange rate also influence housing prices, with all three variables having a positive effect on real housing prices.