علی سوری

The article provides a detailed dissection of the drivers of output growth across two completely different periods to determine the factors influencing Iran's economic developments over these twenty years. The study aims to identify the shift in Iran's growth trajectory from a pattern based on oil revenues and stability to a limited growth path under the pressure of sanctions. Findings indicate that the average annual GDP growth, which was 4.7% in the first period, plummeted to only 1.05% in the second period as a result of macroeconomic instability and declining productivity.

This study utilizes an input-output accounting framework and a structural decomposition method to break down production growth into four components: Domestic demand, Export expansion, Import substitution and Technological change.This approach allows for the clear quantification of the actual contribution of each factor, including negative factors that hindered growth, across various economic sectors.

The analysis reveals fundamental differences between the two decades:First Period (1383–1389 / 2004–2010): The economy experienced relative stability and abundant foreign exchange revenues. Domestic demand was the primary driver of production with a 69.4-unit share. However, technological change was very limited, even contributing negatively in key sectors like agriculture (-153.4 units) and construction (-59.8 units).Second Period (1390–1400 / 2011–2021): The environment faced severe shocks, including a 60% drop in oil revenues and a 25-fold surge in the exchange rate. The share of domestic demand decreased to 41.9 units, while import substitution rose to 28.4 units as domestic industries reacted to the rising cost of foreign goods.Productivity Decline: A critical finding is the sharp decline in productivity due to sanctions. The technological effect reached -353.6 units in the transport sector and -128.8 units in the construction sector.

The comparison shows that achieving sustainable growth is not possible solely through demand stimulation. The primary necessity for the Iranian economy is the management of exchange rate policies and the strengthening of investment in the technology sector to bolster efficiency. Sustainable improvement in welfare can only be expected if production growth is accompanied by a real promotion of efficiency.

This study proposes a deep learning-based framework for automatic wafer defect detection in integrated circuits. Several architectures, including Recurrent Neural Networks (RNN), VGG16, MobileNet, GoogleNet, ResNet-based models, and DenseNet121, were implemented and comparatively evaluated. The employed dataset consisted of wafer images with various defect types, which were preprocessed and augmented using techniques such as rotation, brightness adjustment, and noise injection. Model performance was assessed based on Accuracy, Sensitivity, Recall, and F-measure. The results clearly indicate that deep learning models significantly outperform traditional image processing methods, with DenseNet121 achieving the highest accuracy of 98.33%. Furthermore, the comparative analysis revealed that deeper architectures with advanced feature extraction capabilities substantially improve defect detection performance. This research not only highlights the effectiveness of deep models for semiconductor manufacturing but also provides a comprehensive reference for researchers and industry practitioners aiming to enhance defect detection systems and ensure higher quality in integrated circuits.

The Social Security Organization is the only major fund in the country with the lowest share of governmental support. This highlights the need for careful attention to the organization’s revenues and expenditures. On the other hand, one of the most pressing challenges in the country today is the financial issues of pension funds, which manifest as a deficit of resources compared to expenditures. If not addressed, this issue could significantly impact the entire economy. In the present study, efforts will first focus on addressing, through actuarial models, how the financial sustainability of the Social Security Organization would change with increased government contributions. Subsequently, the organization’s financial sustainability will be evaluated within a dynamic stochastic general equilibrium (DSGE) framework. Finally, the outputs of these two models will be compared using data from 2016 to 2022. The findings indicate that a government expenditure shock increases financial sustainability in the actuarial model, as it boosts the Social Security Organization’s revenues. Consequently, the current value of the organization’s assets relative to its updated obligations improves. However, the DSGE model reveals that the updated value of the organization’s assets undergoes minimal changes. This is due to labor market disruptions, including reduced willingness to work and increased wages. Moreover, the updated obligations of the fund decrease, leading to improved financial sustainability, though this improvement is less pronounced than in the actuarial calculations. Ultimately, it can be concluded that government debt settlement with the Social Security Organization has a positive effect on its financial sustainability.

In this study, we examine the dynamics of consumer inflation in Iran, with a particular focus on inflationary shocks, defined as deviations from the long-run inflation path. The objective is to compare the response of consumer inflation to supply-side versus demand-side shocks within the frameworks of price stickiness and information stickiness models. In this context, shocks to the growth of the informal exchange rate are treated as supply (or cost-push) shocks, while shocks to liquidity growth are considered demand-driven shocks. This research does not seek to establish causality. Acknowledging that inflation cannot occur without liquidity growth, we analyze the statistical properties of inflation, exchange rate growth, and liquidity growth. Employing a vector autoregression (VAR) framework, we find that consumer inflation responds more strongly to exchange rate shocks than to liquidity shocks, and that such responses become more pronounced during periods of high inflation. Exchange rate shocks, as the primary cost-push disturbances in Iran’s economy, convey more salient and immediate information for price revisions compared to liquidity shocks, which operate through the demand channel. The latter are transmitted gradually due to limited public understanding of concepts such as base money and liquidity, as well as uncertainty regarding monetary policy objectives. As a result, liquidity shocks do not trigger abrupt inflationary jumps, a behavior consistent with information stickiness models. By contrast, exchange rate shocks signal an erosion of inflation control through exchange rate interventions and imports—particularly under circumstances such as intensified sanctions or declining oil revenues—while directly and significantly raising production costs. Consequently, informational and price rigidities are considerably weaker in the face of exchange rate shocks; price adjustments occur more swiftly and forcefully, producing inflationary surges. Moreover, when inflation expectations intensify, the exchange rate—being relatively flexible compared to other prices—adjusts more rapidly. Thus, exchange rate shocks serve as signals of accumulated inflationary pressures, leading to sharper adjustments in inflation.

This research deals with the relationship between the CEO's characteristics and financial statement renewal with emphasis on the moderating role of management mechanisms of acquired companies in the Tehran Stock Exchange. In this regard, the data of 96 companies admitted to the Tehran Stock Exchange for the period 2015-2016 have been tested. To check the significance of the hypothesis test, ordinary square regression method was used. The results showed that among the personal characteristics of the CEO, including age, tenure and knowledge of the CEO, only tenure and overconfidence of the CEO have a positive and significant effect on the value of the company; And no significant relationship was found between age and management knowledge with company value. The results of this research showed that there is a direct relationship between the tenure of the chairman of the board of directors and the CEO of the company with added economic value and the wealth created for the shareholders, and strong corporate governance strengthens the effect of the individual characteristics of the CEO on the value of the company. to be Also, the secondary findings of this research show that company value has an inverse relationship with company size and has a direct and significant relationship with sales growth and leverage ratio. Also, no significant relationship was found between the dual role of the CEO and the chairman of the board of directors.

The relationship between inflation and output (or unemployment) has been and remains a controversial topic. A turning point in this debate is the Friedman-Phelps hypothesis, which asserts that there is no long-term relationship between the two. This idea is accepted by many economists, though doubts about it persist. On the other hand, the trade-off between the volatility of inflation and output has also drawn attention. Within the framework of DSGE models, stabilizing output leads to greater inflation volatility, and similarly, stabilizing inflation results in greater output volatility. In other words, there is a trade-off between stabilizing output and inflation. The findings of this paper suggest that, in addition to a negative relationship, a positive relationship between the volatility of inflation and output may also exist. The results indicate that in a behavioral macroeconomic model, it is possible for a positive relationship between inflation and output volatility to emerge. Such findings also hold for Iranian economic data, demonstrating that the relationship between inflation and output volatility is fully consistent with the outcomes of the behavioral macroeconomic model. These results are valid for both annual and quarterly data. The most important implication of these findings for policymaking is that it is possible to reduce both inflation and output volatility simultaneously. We also show that such simultaneous reductions have occurred during periods when real bank interest rates were positive or close to zero. In this context, the impact of monetary variables and the exchange rate is also examined.

This study investigates the effect of diversification in the underwriting activities and insurance portfolio on the level of risk-taking in the investment activities of insurance companies. According to the coordinated risk management hypothesis, it is expected that there is a negative relationship between investment risk and underwriting risk of insurance companies. To examine the effect of insurance portfolio diversification as independent variable on the level of asset risk-taking as dependent variable, ordinary least squares and two-stage least squares regression models were used. Also, alternative measures of diversification and asset risk-taking, and an event study were used to do a robustness check and support the results. The research sample includes 29 direct insurance companies and covers the period from 2006 to 2023. The findings showed that consistent with coordinated risk management hypothesis, insurance companies that have a more diversified insurance portfolio take more asset risk than those with a less diversified insurance portfolio. The results were robust to corrections for alternative diversification and asset risk measures and potential endogeneity bias of variables.

This paper investigates insurance pricing using frequency-severity models, focusing on the Potential Deviation Ratio (PDR) as a key measure in premium determination. The objective is to develop an accurate and actuarially sound pricing approach by modeling claim frequency and severity using appropriate statistical distributions. Specifically, we propose that the product of two fitted distributions—one for frequency and the other for severity—can be used to calculate the pure premium. The methodology includes fitting various distributions to frequency and severity data from a major Iranian insurance company. To model the dependency structure, we employ the Clayton copula. This dependency structure is used when calculating pure premium by multiplying frequency and severity samples based on the fitted distributions. Kolmogorov-Smirnov, Anderson-Darling, and Chi-Squared tests are applied to evaluate model performance. The results demonstrate that using the pure premium, based on their respective fitted distributions, significantly enhances the accuracy of the model. This approach leads to more precise risk classification, improved premium setting, and ultimately, fairer pricing strategies. Additionally, the findings indicate that incorporating dependency structures between frequency and severity not only improves risk assessment but also contributes to greater financial stability for insurers.

This study examines the redistributive policies of governments, focusing on allocating resources to achieve equitable distribution. It highlights that government expenditures in health care, education, and social services are crucial in income redistribution, particularly benefiting vulnerable populations. Healthcare spending enhances community well-being by providing access to medical services, while educational investments improve knowledge and skills, leading to better job opportunities and income levels. Social services, including insurance and subsidies, further support income distribution. The study also explores the role of taxation in redistributing income from higher-income to lower-income groups. The research first analyzes budget laws and development programs in Iran concerning redistributive and supportive policies. It then employs a vector error correction model to assess the impact of government spending on health care, education, and social services, alongside taxation, on income distribution from 1966 to 2022. Income distribution is measured with the Gini index. Control variables such as GDP, inflation rate, and real exchange rate are included to account for their contextual effects on income distribution. The findings indicate that increased government spending improves income distribution, while tax policies have no long-term impact. Furthermore, GDP[AN1]  growth initially increases inequality before reducing it, and inflation exacerbates income inequality, whereas a rise in the real exchange rate contributes to its reduction. Overall, the results align with established economic theories regarding macroeconomic variables. The findings can create a good understanding for policymakers in the field of redistribution and support matters.

The Civil Service Pension Fund and the Armed Forces Pension Fund rely on government budgets for more than 85% of their funding. In contrast, the Social Security Organization (SSO) is the only major pension fund in the country with the lowest share of government support, highlighting the need for careful attention to its revenues and expenditures.One of the most pressing issues facing the country today is the financial instability of pension funds, manifesting as a resource deficit relative to expenditures. Without timely solutions, this problem could have a significant impact on the overall economy.This study aims to address this issue by first using actuarial models to assess how changes in parameters, such as the contribution rate, affect the financial sustainability of pension funds. Subsequently, the financial sustainability of the Social Security Organization is evaluated within a dynamic stochastic general equilibrium (DSGE) framework, and the outputs of these two approaches are compared.The results reveal that following a change in the contribution rate and the introduction of shocks, the actuarial model indicates an improvement in the financial sustainability of the SSO due to increased resources. However, the DSGE model presents different findings. It shows that the fund's resources did not grow substantially because the higher contribution rate and the associated shock disrupted the labor market, leading to negligible changes in the fund’s assets. Moreover, due to the equilibrium maintained across various economic sectors, the fund's liabilities increased. This is attributed to contributors paying higher premiums now expecting higher pensions in return, thereby worsening the fund's sustainability challenges.

The present research was conducted to present the model of improving human resources according to the approach of technical and professional education. This research is applied in terms of purpose and mixed in terms of the nature of the data. The statistical population included all experts and expert professors in the field of technical and professional human resource management in Alborz province, who were selected through saturation. In this way, after conducting interviews with 15 experts and professors in the field of human resources, technical and professional, the researcher reached repeated answers and reached the point of saturation. The results showed that the designed model includes 40 components and 7 dimensions (educational, organizational, individual, professional, ethical, cultural-social, and technological). Based on the results, it can be said that the dimensions of human resources improvement and the components have measured the dimensions of human resources improvement well. Therefore, it can be said that the fit of the components with the dimensions in the conceptual model of the research is a good fit. Therefore, all dimensions of human resources improvement should be paid attention to in the human resources improvement programs according to the approach of technical and professional education. Paying attention to these factors will improve the human resources in the target society.

Insurance industry as a financial institution has a specific role in economic growth and development. Therefore, the stability and efficiency of this industry is essential for the Economy. The insurance market is one of those markets where the actions of free agents does not lead to efficiency and is subject to market failure. The issue of market failure has provided justifications for the intervention of the government through the establishment of regulations in order to increase social welfare. Some economists have introduced theories to explain the necessity of regulations by the government. Among these theories are the public interest theory, capture theory, the economic theory of regulation and the Enforcement Theory of Regulation. Considering the existence of many rules and regulations in Iran's insurance industry, this research seeks to investigate the reasons for regulations in this industry according to the theories of regulation. In other words, which regulation theory has a better explanation for regulation in Iran's insurance industry Were the regulations made in line with the public interest or the product of the efforts of interest groups to achieve their goalsFor this purpose, the main regulation theories have been reviewed and the regulatory process in Iran's insurance industry has been studied. In the following, based on the evidence, the theory that has the most compliance with the reasons for the regulations made in Iran's insurance industry has been identified. The analyzes showed that the theory of public interest provides the most appropriate framework to explain the regulations of the Iranian insurance industry.

The purpose of this study is to design a quality risk management model in the supply chain of the automotive industry. This research was conducted with a mixed approach. In the qualitative part, Delphi method was used to identify effective factors and derive a conceptual model. In the quantitative part, hierarchical data analysis was used to prioritize the indicators. The statistical sample includes 16 academic and automotive industry experts who were selected by judgmental sampling and snowball sampling. The data collection tool includes a questionnaire According to the results of the Delphi, the 70 sub-indices finalized in the research are divided into 14 main branches and 3 main fields including quality risk based on: supply chain capabilities, different parts of the supply chain and work stages. After performing the process of hierarchical analysis of data at three levels, the first 14 indicators of the research, which obtained the most weights, were identified as the most important indicators.By identifying the types of quality risks during the process and supply chain in the automotive industry, this research helps the managers of the automotive industry in developing the correct strategies for risk management and quality management of the supply chain.

This study measured the investor sentiment to understand its role in the behavior of the Tehran Stock Exchange and its relationship with the stock price during a monthly period from March 2016 to March 2022. The returns on some TSE-listed indices were compared to analyze the relationship between the investor sentiment and the stock price. This study improves our understanding of the price formation process at purchases or sales caused by sentiments acting as the major determinant of the stock price change. Statistical evidence indicates the impact of sentiments on the price formation process in specific TSE-listed indices. The autoregressive integrated moving average (ARIMA) was employed to estimate parameters and the behavior induced by the investor sentiment. According to the results, they respond asymmetrically to sentiment changes and trade more aggressively when sentiments reduce. There are also significant relationships between some of the market variables and the investor sentiment. Finally, comparing the sentiment index with each price index of the market will lead to the conclusion that there is a positive significant relationship between the sentiment tendency and the price formation process at the Tehran Stock Exchange.

Inflation, as one of the structural and chronic issues of Iran's economy, has always remained at high levels and has had widespread effects on macroeconomic variables and social welfare. The persistence of high inflation leads to instability in economic, social, and political spheres, to the extent that in some cases, inflationary instability can even result in the downfall of governments. Therefore, understanding the roots of inflation can help policymakers in designing appropriate policies to control and curb it. Numerous studies have examined the factors influencing inflation and the role of inflation expectations.The literature review revealed that, so far, no comprehensive research has been conducted on the factors affecting inflation, with an emphasis on the nonlinear relationship between inflation expectations and budget deficits within the framework of the New Keynesian approach in Iran. Additionally, the study employs the Hodrick-Prescott filter and the Kalman filter to measure inflation expectations, which is considered an innovative approach. Furthermore, relying on the New Keynesian framework, this study examines the role of the output gap, budget deficit, exchange rate, and inflation expectations in the formation of inflation, specifically identifying the asymmetric impact of inflation expectations.

The aim of this study is to examine the nonlinear effects of inflation expectations and budget deficits on inflation in Iran. For this purpose, the New Keynesian approach and the Nonlinear Autoregressive Distributed Lag (NARDL) method have been used to estimate the model over the period 1988 to 2022. Inflation expectations have been calculated using two methods the Hodrick-Prescott filter and the Kalman filter.

The research findings indicate that the estimated models based on both filters yielded very similar results, demonstrating the robustness of the study's outcomes. Additionally, the results show that variables such as the output gap, inflation expectations, budget deficit, and exchange rate influence the inflation rate. Furthermore, inflation expectations have an asymmetric effect on inflation, where their increase leads to greater persistence and stability of inflation. Moreover, inappropriate fiscal policies exacerbate inflationary pressures by intensifying the budget deficit.

One of the important issues that has attracted the attention of economists over the past decades is the role of financial systems in the economic growth of countries. Insurance industry is one significant component of financial markets. Therefore, the stability and efficiency of insurance industry as a financial market sector is important for a country's economy. One of the most crucial changes in Iran's insurance industry is the regulations having been made in recent years. One main goal of regulation is to eliminate problems of market failure and improve efficiency. This research investigates the effect of these regulations on the efficiency of insurance companies in Iran.

The studied community is 27 insurance companies in the country and the relevant statistics were collected for the years 1385-1400 Persian Year (2005-2020). This study was conducted in two stages. In the first stage, the efficiency of insurance companies has been measured, using the method of data envelopment analysis (DEA) with the bootstrap approach. The implicit assumption of the traditional data envelopment analysis method is that the inputs and outputs are definite. But the output of an insurer is not necessarily certain. To solve this problem, we can use the bootstrap approach to obtain statistical characteristics for this technique. In the second stage, in order to investigate the effect of regulation on efficiency, according to the reviewed studies, the purpose of the present study, and the conditions of Iran's insurance industry, the effective factors on efficiency are determined and the regression model is defined. Then, the dynamic regression model was estimated using the generalized method of moments (GMM) and the related tests confirmed the validity of the results of the model. To calculate the efficiency and estimation of the model, MATLAB and Eviews software were used.

The most important finding of the research is the significant effect of regulation on efficiency. Also the coefficient of regulation, market share, and privateness of insurance companies are estimated as -0.066, 0.041 and 0.306 respectively.

The results of the research show that regulation had a negative effect on the efficiency of insurers and led to a decrease in their efficiency, but the market share and the privateness of insurance companies had a positive effect on the efficiency. In the end, suggestions for improving the efficiency of insurers have been presented.

As a revolutionary invention, the Internet is always evolving into a new type of hardware and software that makes it irresistible to anyone. The type of communication seen today is human-to-human or human-to-machine, but the Internet of Things promises a great future for the Internet, where it is machine-to-machine. The Internet of Things is defined as a paradigm in which objects with sensors, actuators and processors communicate with each other to achieve a meaningful purpose. Human resource management is a systematic approach that provides practices to support all aspects of the employee life cycle, from recruitment to exit. This article examines the impact of the Internet of Things on human resource management in the fourth industrial revolution and tries to develop a framework to understand it. The results of the survey showed that during the transfer of workflow to a digital and simple workflow, there is a need to measure the benefits of internal and outsourcing solutions for personnel management. These are the parameters that can justify the costs of an internal solution or a cloud-based human capital management solution by objectively measuring both options. These key performance indicators are workflow, flexibility, accountability and cost-effectiveness. Workflow is a continuous input-output process in a company that can sometimes be compressed. Without the help of automation, these setups are prone to mistakes due to repetitiveness.

The main purpose of this research is to design a model to measure the maturity of risk management in Iran's insurance industry, emphasizing the role of internal audit. To achieve the objective of the research, first, the existing theoretical and empirical literature was studied by using the qualitative content analysis method. The key propositions indicating the maturity of risk management and the role of internal audit in risk management were also identified. Next, the propositions were classified based on similarity, semantic connection, and also by referring to risk management frameworks and standards in the form of dimensions, components, and main indicators of risk management maturity. Then, to ensure the validity of the obtained model, the Delphi method was used to examine and apply the opinions of risk management and internal audit experts in the insurance industry. At this stage, a questionnaire was used to collect data. The reliability of the questionnaire was confirmed with the help of Cronbach's alpha statistic. By employing qualitative content analysis, the process of identifying and categorizing significant and recurring propositions led to the identification of 68 indicators of risk management maturity. These indicators were organized into nine components, forming three primary dimensions of risk management maturity within Iran's insurance sector, with a specific emphasis on the role of internal audit. Subsequently, the developed model was presented to professionals and academics with substantial experience in the realm of risk management and internal audit. This was carried out through a questionnaire that was distributed to experts in these domains. They announced their agreement, disagreement, or their proposed amendments regarding each of the dimensions, components, and indicators. After gathering their feedback, 50 indicators were agreed upon by experts, and the rest were removed from the final model. The model put forth encompasses three primary dimensions: corporate governance, policy and strategy, and the risk management process, along with the roles and responsibilities of internal audit. The result is in line with the "three lines of defense against risk" model proposed by the International Association of Internal Auditors. Therefore, all operational units of the organization under good corporate governance and strategy form the first layer of defense against risk. Risk management is the second layer of defense by implementing the processes of identification, evaluation, response to risk and reporting. The internal audit, by monitoring and evaluating the risk management process, forms the third layer of defense against risk. The model developed within this study comprises 50 indicators sourced from risk management standards, existing research, and insights from experts in the Iranian insurance industry. These indicators delineate the ideal condition of risk management, organized into three primary dimensions and nine crucial components. Iranian insurance firms have the capability to assess the maturity level of their risk management practices by gauging their alignment with the indicators outlined in this model. This assessment aids in recognizing both their strengths and areas that require improvement. Also, unlike previous risk management maturity models, this model could successfully address the roles and duties of internal audit. Therefore, The internal auditors within the insurance industry can incorporate the indicators outlined in this model while devising and executing assurance and consulting services related to the organization's risk management procedures.

This study determines the optimal investment portfolio of insurance companies by considering underwriting activities. investment decisions in insurance companies are affected by underwriting activities. In this paper, the investment optimization problem of insurers is modeled using the copula-based conditional risk value, taking into account the results of insurance activities. Also, since the emphasis is on tails of distribution, the probability distribution of variables in tails is estimated using Pareto distribution and in other parts of the distribution using the Empirical probability distribution. Data collected on monthly basis covers two periods in-sample, between 2006 to 2015 and out-of-sample, between 2016 to 2019.The findings show that the optimum portfolio includes eighty percent of risky assets (stock and real estate) and only twenty percent of risk-free assets (bank deposits) and it is outside the legal constraints set by Central Insurance Therefore, legal constraints prevent insurance companies from the optimal selection of investment portfolio. Also, the comparison of out-of-sample performance with in-sample performance of portfolios shows that portfolios based on copula functions have better and more robust performance than traditional models.

The purpose of this research is to model Value-at-Risk (VaR) of portfolio with EVT-Pair-Copulas approach. In the financial literature, a significant amount of empirical studies have been done on the characteristics of financial assets returns and researchers have found a set of stylized facts about this subject. In this regard leptokurtic, left-skewed, weak autocorrelation, volatility clustering, and heteroscedasticity can be mentioned. Any estimation of risk without considering these characteristics or using unrealistic assumptions about financial assets returns increases the probability of failure in the risk management process. For this purpose, at first, the marginal distributions of returns are obtained using extreme value theory (EVT). Concerning characteristics of financial assets returns and also the primary filter to apply EVT, we use heteroscedasticity models for the marginal distributions of assets. Then the structure of the dependence between different stocks is estimated by using C-Vine, D-Vine, and R-Vine pair copula models. Afterward, the VaR of portfolio is estimated using the Monte Carlo simulation method. The final results show that the model with GARCH marginal distribution and R-Vine pair copula has been able to achieve the best performance among rival models at 95% confidence level.

Population growth and changes in age structure both are the most important consequences of demographic transition. how the interaction between these two important variables is resulted from fertility and mortality, and in turn affects national economy is a question which has not been answered in previous researches. Examining the age details of the effect of demographic changes on the economic growth rate, the purpose of this article is to provide an answer to this question. To do this, the population growth rate has been aggregated into age-specific growth rates and using the age profiles of production and consumption, the impacts of the weight and changes of population by age segments on the first demographic dividend have been estimated and analyzed. The findings show that the share growth rate, which indicates both the size and the changes of population of each age, is capable to represent the effect of phenomena such as baby boom, and population momentum on the amount of Iran's demographic dividend. Also, almost simultaneously with the age transition, a demographic-economic transition is taking place due to the interaction of the economic life cycle and the change in the age structure. The results show that the decrease in the population of age groups under 30 years old, during a period from the middle of the first phase to the middle of the third phase of the age transition, makes an important contribution to the negative growth of the effective number of consumers and the increase of the population of prime age adult (30-49 years old) leading to the positive growth of the effective number of producers per consumers and, as a result , the realization of the first demographic dividend in Iran.

In this paper, using an agent-based model, the behavior of commercial banks and investment funds is simulated. We have tried to show systemic risk transmission mechanism from the money market to the capital market through balance sheet changes. In this model, the money and capital markets are endogenously modeled and the price is determined by interest rate and stock market index in these markets respectively. 81 percent of Iranian commercial banks have a mixed portfolio of interbank loans and securities and can spread the crisis throughout the financial system in case of a shock. This process happens through the fire sale mechanism and investment fund unit redemption and can make stocks undervalued in the capital market. Although higher imposed capital adequacy and liquid assets rate can reduce the shock effect on price in the capital market, these high rates make banks portfolios mixed and increases systemic risk. Optimal capital adequacy rate is estimated 19 percent.

Understanding the water content of export and import products in international trade has an effective role in the optimal management of water in Iran as a country with water stress. The main purpose of this study is to identify the balance of water content of products in Iran's foreign trade. For this purpose, using the input-output tables - 2016 and considering the interrelationships and dependencies between major economic sectors including agriculture, mines, manufacturing, electricity and gas production, treatment, supply and wastewater, buildings, services and others, the Water footprint index, net import of virtual water and some indicators related to water consumption have been calculated. The results show that in 2016, Iran was a net importer of virtual water. Although the agricultural sector has the highest national water footprint ( 89%), according to the water consumption multiplier index, increasing water consumption in this sector has very little effect on increasing water consumption in other sectors. After the agricultural sector, the manufacturing sector has the highest intensity of indirect water consumption (3.5 cubic meters / million Rials), and the increase in water consumption in this sector has the greatest impact on increasing water consumption in the economy. So that the increase of one unit of water consumption in this sector increases the water consumption of the agricultural sector by 7 times and the water consumption of the whole country by 9 times. After the agricultural sector, the highest amount of virtual water content (direct and indirect water consumption) was allocated to the treatment, supply and wastewater sector(5.8 cubic meters / million Rials). The services and other sectors, which has been the largest net exporter of virtual water ( 217 million cubic meters), have the largest water footprint after agriculture.

In this study, we have used the total capital market index (TEDPIX) as an index of the real sector of the economy and the index of banks and credit financial institutions as an index that explains the developments of the banking system. Also, oil revenues, exchange rate uncertainty, tax revenues, liquidity, nominal interest rates, inflation uncertainty and GDP have been used as macroeconomic variables in the research period (1370-1396). To estimate the systemic risk of the banking system, the quarterly data of the banks' index is used and the value at risk of the return of the seasonal data of the index is estimated using an exponential GARCH model. In order to model the interaction of macroeconomic variables and systemic risk of the banking system, an unrestricted vector autoregression (VAR) model was estimated and then using instantaneous impact functions and based on Chulsky analysis, systemic risk response to other variables was investigated and analyzed. In order to identify the channels of impact of economic shocks on the systemic risk of the banking system, based on the structures of the Iranian economy, a structural vector autoregression (SVAR) model was specified and then the instantaneous impact functions were extracted and the effect of macro variable shocks on the systemic risk of the banking system was investigated. Also, the effect of systemic risk of the banking system on macroeconomic variables was investigated and analyzed using instantaneous impact functions. Finally, the interaction model of macroeconomic variables and systemic risk of the banking system was approved using the vector autoregressive model.