Research Paper
                                            
            
                            mohaddaseh  soleimani; Aliasghar  Banouei; Esfandiar  Jahangard; teymor  mohamadi
                        
            
                
                    Abstract 
                
 
                
                    Innovation and technological changes spans various geographical locations over the time.The inability of Input-Output models in measuring the effects of technology changes, caused by new innovations, is known as a weakness of these models. In this article, we show how this weakness can be addressed by ... 
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                    Innovation and technological changes spans various geographical locations over the time.The inability of Input-Output models in measuring the effects of technology changes, caused by new innovations, is known as a weakness of these models. In this article, we show how this weakness can be addressed by employing the fields of influence method. Technology changes are modeled as changes of one or more elements in the direct coefficients matrix and the impact of such changes in the Leontief matrix is measured. Here is the main question: Does the technology changes only impact a limited sector or the entire economical system? In other words, how would technology changes in one sector impact other sectors of economic system? The main goal in this paper is proposing a method which can measure how different sectors get impacted by changes at different levels such as one element, all elements, one row or one column and then evaluates the importance of different sectors. To this aim, Iran’s Input-Output tables over the period of 1365-1395 with the fixed price of Iran’s statistics center in 1390 is used. The impact of technology changes on each sector is measured using Leontief’s inverse matrix and the column field of influence approach (CFOI) approach. Our findings indicate that over this period of time, technological changes in the industry and then construction sectors have the most influence and the mining sector has the least influence on other sectors of Iran’s economy. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            Mohammad  Feghhi Kashani; Teymor  Mohammadi; hadi  pirdaye
                        
            
                
                    Abstract 
                
 
                
                    Corporates adjust their information voluntary disclosure according to the volatilities they experience in their cash flows. The purpose of this study is to investigate the effects of news concerning risk, ambiguity level, and investors' ambiguity aversion on the policy adopted by firms as to the voluntary ... 
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                    Corporates adjust their information voluntary disclosure according to the volatilities they experience in their cash flows. The purpose of this study is to investigate the effects of news concerning risk, ambiguity level, and investors' ambiguity aversion on the policy adopted by firms as to the voluntary disclosure (conservative or non-conservative) of soft and hard information in the digital industry subset of Tehran Stock Exchange within the period of 2012-2022. Further, we have used the corporate voluntary disclosure lag to capture the disclosure dynamics along with the control variables including the cost of capital, financial leverage and stock liquidity by dynamic panel models to explain the voluntary disclosure behavior of soft and hard information of the corporates. The results indicate that managers of companies active in the digital industry, depending on the type of information available to them for voluntary disclosure conservatively or non-conservatively, respond differently to the news related to risk, ambiguity and ambiguity aversion of investors. That could be due to the nature of the disclosed information (credibility of information for investors). Likewise, the findings confirm the increasing effects of voluntary disclosure of previous periods on the disclosure of subsequent periods, which somehow confirms the existence of inertia in voluntary disclosure policies in the studied industry. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            Hossein  Esfandiar; teymoor  mohammadi
                        
            
                
                    Abstract 
                
 
                
                    Thanks to Blockchain technology the future of banking can take place without intermediaries (especially banks), and in this regard, Central Bank Digital Currency (CBDCs) and stablecoins of BigTechs are mentioned as the main competitors of the new monetary era. Based on this fact and in parallel with ... 
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                    Thanks to Blockchain technology the future of banking can take place without intermediaries (especially banks), and in this regard, Central Bank Digital Currency (CBDCs) and stablecoins of BigTechs are mentioned as the main competitors of the new monetary era. Based on this fact and in parallel with the efforts of most countries on the (theoretical and experimental) investigation of CBDC’s aspects, this article, using a dynamic stochastic general equilibrium (DSGE) model, in the period Q1 1388 to Q4 1400, economic effects of issuance of RamzRial (Iranian CBDC) was modeled and analyzed. In our model, RamzRial is an account-based, widely available to the general public, interest-bearing and cash complementary money, and the results of the implementation of quantitative and price rule policies were examined in the presence of RamzRial. The results of the model based on the data and calibration indicate that the issuance of RamzRial, while diversifying central bank tools, will improve the effectiveness of monetary policies in the event of (supply and demand) external shocks. One of the significant results, especially for the stagflation condition of Iran’s economy, says that through issuing (an appropriate amount of) RamzRial the central bank can implement disinflation programs while reducing its unwanted negative effects on production. Also, in addition to influencing the level of production, consumption, investment and employment, the results of our model prove that with the introduction of the RamzRial in parallel with cash balances, the most important factor affecting the transmission mechanisms is the dynamics of transaction cost deviations. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            Reza  Taleblou; Parisa  Mohajeri; Abbas  Shakeri; teymoor  mohammadi; zahra  zabihi
                        
            
                
                    Abstract 
                
 
                
                    Achieving the correct insight into the structure of connectedness and the spillover of volatilities between different stock exchange industries plays an important role in risk management and forming an optimal stock portfolio. Also, the analysis of inter-sectoral connectedness helps policy makers in ... 
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                    Achieving the correct insight into the structure of connectedness and the spillover of volatilities between different stock exchange industries plays an important role in risk management and forming an optimal stock portfolio. Also, the analysis of inter-sectoral connectedness helps policy makers in designing policies that stimulate economic growth and implementing preventive measures to curb the propagation of systemic risk. In this regard, this article tries to use the data of 3370 trading days during the period of 1388/07/01 to 1402/06/31, encompassing 20 stock market industries (which constitute more than 80% of the Iranian stock market) and applying the connectedness approach based on the vector autoregression model with time-varying parameters (TVP-VAR), to estimate the systemic risk and volatility connectedness of the stock market network. In addition, we implement the minimum connectedness approach in the optimal stock portfolio and compared its performance with two other conventional approaches. The findings reveal that, first; the systemic risk in Iranian stock market is significant and has reached unprecedented figures of 80% in the last three years. Second, the four major export industries (petrochemicals, metals, mining and refining) experience the strongest pairwise connectedness, and among them, base metals appear as one of the most important transmitters of volatilities to the entire stock network. Thirdly, the stock portfolio based on the minimum connectedness method, compared to the minimum variance and minimum correlation methods, shows a better performance based on the criteria of cumulative return and hedge ratio efficiency. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            somayeh  nematollahi; Farshad  Moameni; Alireza  Garshasbi
                        
            
                
                    Abstract 
                
 
                
                    This article aims to investigate the effect of regulatory level on the growth of industrial added value and compare it in developed and developing countries. For this purpose, the estimation of a non-linear equation with the panel GMM method and delta method has been used for the years 2000 to 2019. ... 
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                    This article aims to investigate the effect of regulatory level on the growth of industrial added value and compare it in developed and developing countries. For this purpose, the estimation of a non-linear equation with the panel GMM method and delta method has been used for the years 2000 to 2019. The estimation results in a sample of 99 countries show an inverted U-shaped relationship between regulatory variables and industrial growth, and for about 67% of the sample observations, the level of growth regulation has increased and its effect on industrial growth is positive and significant. . Also, in this example, the growth maximization level for regulation was 2.61 (on a scale of 0-10). Another important result is that the nature of the relationship between regulation and industrial growth in developed countries is fundamentally different from developing countries. In particular, while the model estimate for developing countries is consistent with the findings related to the total observations and is in the form of an inverted U relationship, the findings related to developed countries are completely different and the maximizing level of industrial growth for these countries It was not observed that the reason is related to institutional differences in these two spectrums. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            Shima  Namazi Zavareh; Farshad  Momeni; Ali Asghar  Salem
                        
            
                
                    Abstract 
                
 
                
                    In order to face the challenge of youth poverty, the main focus should be on facilitating the access of the NEET population to quality education and decent job opportunities. Considering that this group of people is a potential threat to the country's achievement of one of the most important goals of ... 
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                    In order to face the challenge of youth poverty, the main focus should be on facilitating the access of the NEET population to quality education and decent job opportunities. Considering that this group of people is a potential threat to the country's achievement of one of the most important goals of sustainable development, i.e. ending poverty through decent work and economic growth, and they turn the young population into a challenge and not an opportunity in the economy, Examining the impact they have on poverty and the impact they receive from poverty is very important. In this regard, the aim of this article is to investigate the simultaneous relationship between household poverty and population phenomenon in the urban and rural society of Iran in 1401. For this purpose, using the detailed data of urban and rural households' expenditure and income plan, the poverty line was first calculated based on the multidimensional poverty approach and poor households were identified. Then, the households that have demographic phenomena were also identified. The results of the estimation of the research model using the two-stage least squares method (2SLS) showed that in urban areas, population phenomenon and poverty both have a positive and significant effect on each other. Unlike in urban areas, the results of the estimation of the research model in rural areas indicated that the population phenomenon does not have a significant effect on household poverty, but on the other hand, household poverty has a positive and significant effect on it. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            Shima  Namazi Zavareh; Farshad  Momeni; Ali Asghar  Salem
                        
            
                
                    Abstract 
                
 
                
                    A major reason for pushing people towards informal jobs is the motivation of necessity. In fact, informal employment is a kind of survival strategy for those who have no other way to earn money and support themselves and their families except by working in these types of low-paid jobs. At the level of ... 
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                    A major reason for pushing people towards informal jobs is the motivation of necessity. In fact, informal employment is a kind of survival strategy for those who have no other way to earn money and support themselves and their families except by working in these types of low-paid jobs. At the level of development, the continuation of this trend affects the economic competitiveness and the quality of life of the citizens, and the foundation of national production and technological and innovative production faces serious limitations. the purpose of this article is to investigate the effect of household poverty along with other socio-economic factors on informal employment in urban areas of Iran in 2019. For this purpose, by using the detailed data of the expenditure and income plan of urban households, first, the poverty line was calculated based on the absolute poverty approach for urban areas and poor households were identified. Then according to the index presented in this research, the type of employment of households was determined in terms of formal and informal. The results of estimating the research model using the two-stage Heckman Probit method indicate that household poverty leads to a significant increase in informal employment, so that with an increase in poverty, the probability of being informally employed increases by 0.57. The strategic message of this study is that the problem of poverty and informal employment in Iran can be overcome only by upgrading the technological production base and creating value-creating capabilities based on increasing productivity. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            Mohammad  Feghhi Kashani; Teymor  Mohammadi; zahra  Aghighi
                        
            
                
                    Abstract 
                
 
                
                    One of the key challenges in empirical studies relates to the identification of the dynamics of bubbles that periodically run up and collapse. This study is an attempt in this field, which initially examines some limitations of one of the relatively new methods in the economic literature as to the identification ... 
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                    One of the key challenges in empirical studies relates to the identification of the dynamics of bubbles that periodically run up and collapse. This study is an attempt in this field, which initially examines some limitations of one of the relatively new methods in the economic literature as to the identification of rational bubbles in the Tehran Stock Exchange for the period of 2009-2020. Then, by assuming the Markov switching regime approach in this area, we have extended the conventional method by taking into account the dynamic interaction of asset prices in the market with the latent factor in the process of bubbles expansion and collapse. It is shown how this framework, while improving the efficiency of detecting financial bubbles through mitigating the specification error of dynamic models compared to existing alternative methods, is capable of incorporating the feature of traders' interactions in the market with no specific assumptions on how they interact, especially with regard to the coordination of their expectations and pursuant trading behavior. The findings resulting from this method indicate the existence of a bubble in asset prices only for the period 2018-2020, as opposed to the use of the conventional method, which implies either no bubble or the existence of two bubbly periods 2012-2014 and 2018-2020. in the Tehran Stock Exchange. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            zahra  bigdeli shamloo; Abbas  Shakeri; Teymur  Mohamadi; Syrous  Omidvar
                        
            
                
                    Abstract 
                
 
                
                    The main purpose of this study is to analyze the nature of the money creation process by examining the approaches related to this process in Iran. The two main views regarding the money creation process are the endogenous and exogenous money approaches. The endogeneity of money means that the money supply ... 
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                    The main purpose of this study is to analyze the nature of the money creation process by examining the approaches related to this process in Iran. The two main views regarding the money creation process are the endogenous and exogenous money approaches. The endogeneity of money means that the money supply is directly influenced by the economic activities and conditions in the economy, and it is not determined by central bank exclusively. The endogeneity of money can also be a very important factor in the efficiency and effectiveness of monetary policies on macroeconomic indicators. Therefore, in order to test the endogeneity based on post-Keynesian approaches, the two-stage method of the state-space approach was applied to determine a time-variable model of money supply using the annual data from 1357 to 1400 in Iran. The results indicate: firstly, money is endogenous. Secondly,the effect of explanatory variables on it is not constant over time, and therefore, it is necessary to change monetary policies from targeting on money aggregates according to the conditions of endogenous money. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            Ahmadreza  Ahmadi; Ghahreman  Abdoli; Fatemeh  Azhari
                        
            
                
                    Abstract 
                
 
                
                    The present study examines the impact of globalization on Iran’s underground economy over the period 1979–2020. In this regard, the size of the underground economy was estimated using the MIMIC method. Subsequently, the effects of the three main dimensions of globalization—economic, ... 
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                    The present study examines the impact of globalization on Iran’s underground economy over the period 1979–2020. In this regard, the size of the underground economy was estimated using the MIMIC method. Subsequently, the effects of the three main dimensions of globalization—economic, social, and political—as well as the dual components of each dimension (de facto and de jure), were analyzed using the autoregressive distributed lag (ARDL) approach. The findings from the long-run estimations indicate that the economic and social dimensions of globalization have a negative effect on the underground economy, whereas the political dimension exerts a positive effect. Further analysis of the components of each globalization dimension reveals that both the de facto and de jure components of social globalization negatively influence the underground economy. Although the de jure component of economic globalization also has a negative impact, its de facto component does not have a significant effect. Regarding the political dimension, de facto component has a significant positive effect on the underground economy, while the de jure component does not show a meaningful impact. Additionally, the results demonstrate that, in all four estimated models, unemployment has a positive effect and financial deepening has a negative effect on the underground economy. These findings offer useful guidance for policymakers aiming to reduce the size of the underground economy and enhance economic transparency in the country. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            Ali  Mazyaki; Sina  Ashouri; Javid  Bahrami; Somayeh  Shahhoseini
                        
            
                
                    Abstract 
                
 
                
                    This theoretical study investigates the factors influencing the deterrence of foreign firm entry through strategic R&D investment by an incumbent domestic firm. Understanding this phenomenon, as an endogenous barrier potentially detrimental to free trade, is crucial for designing optimal national ... 
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                    This theoretical study investigates the factors influencing the deterrence of foreign firm entry through strategic R&D investment by an incumbent domestic firm. Understanding this phenomenon, as an endogenous barrier potentially detrimental to free trade, is crucial for designing optimal national trade policies, particularly in the current context of rising global market concentration. We develop a comprehensive theoretical framework integrating theories from international trade and industrial organization, where investment in innovation plays a pivotal role. Within this model, we examine whether a domestic firm, following trade liberalization, might strategically utilize R&D investment as an entry barrier against potential foreign competitors. We also analyze the factors that increase the likelihood of such strategic behavior. This strategic interaction is formulated as a Stackelberg market entry game where the incumbent domestic firm chooses an R&D-based 'hinder' strategy against the foreign rival and an 'accommodation' strategy. Our findings indicate that under endogenous pricing, the domestic firm may strategically invest in R&D to raise entry costs for foreign rivals, potentially eliminating their expected profits from entering the market. Intermediate market size plays a crucial role in this determination. Specifically, we identify a range of intermediate market sizes where the incumbent firm can successfully deter entry by the foreign rival through strategic R&D investment, thereby preserving its monopoly position even after trade liberalization. Consequently, under these circumstances, trade liberalization may paradoxically lead to a reduction in overall welfare. These findings underscore the importance of considering market size in the design of competition and trade policies. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            seyed hadi  arabi; ali  azin; Mohammad hasan  maleki
                        
            
                
                    Abstract 
                
 
                
                    The current research tries to identify and analyze the factors affecting subjective poverty in Iran. In terms of orientation, the current research is applied, and in terms of methodology, it is mixed-method quantitative. The theoretical population of the research involves experts in the field of subjective ... 
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                    The current research tries to identify and analyze the factors affecting subjective poverty in Iran. In terms of orientation, the current research is applied, and in terms of methodology, it is mixed-method quantitative. The theoretical population of the research involves experts in the field of subjective poverty, and the sampling method is judgmental. The data was collected through two questionnaires: an expert evaluation questionnaire and a prioritization questionnaire. In the first step, 36 factors were obtained through literature review and interviews with experts. These factors were screened by distributing  a questionnaire distribution and the fuzzy Delphi method. Thirteen factors had a defuzzified value higher than 0.65 and were selected for final prioritization. The screened factors were ranked using the Marcus method by distributing prioritization questionnaires. The factors affecting subjective poverty in Iran, based on the Marcus method output, include personality traits, economic inequality, online social networks, social anomie, and unemployment. The findings indicate that personality traits such as self-esteem and hope for the future, along with other factors such as economic inequalities and active participation in online social networks, can contribute to subjective poverty in society. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            Gholamhossein  Golarzi; Mahnaz  Khorasani
                        
            
                
                    Abstract 
                
 
                
                    This research aims to examine the asymmetric effects of domestic economic policy uncertainty (DEPU) and global economic policy uncertainty (GEPU) on the return of the Tehran Stock Exchange (TSE) All-Share Index.  The main innovation of this research lies in the simultaneous analysis of economic policy ... 
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                    This research aims to examine the asymmetric effects of domestic economic policy uncertainty (DEPU) and global economic policy uncertainty (GEPU) on the return of the Tehran Stock Exchange (TSE) All-Share Index.  The main innovation of this research lies in the simultaneous analysis of economic policy uncertainty with both domestic and global origins within a nonlinear framework, and the investigation of the asymmetric response of the stock market to these uncertainties. The data used were collected on a quarterly basis over the period from 1997 to 2024. In addition to the uncertainty indices, control variables such as exchange rate, global oil prices, consumer price index, money supply, real non-oil GDP, and stock market liquidity are also included in the model. The results indicate that positive and negative shocks from domestic economic policy uncertainty have significant positive and negative effects on the return of the Tehran Stock Exchange (TSE) All-Share Index, respectively, in both the short and long term. Furthermore, shocks from global economic policy uncertainty have a significant impact in the short term, with a time lag; specifically, positive shocks have a positive effect, and negative shocks have a negative effect on the index returns. In the long term, however, only positive shocks from global economic policy uncertainty exert a significant positive effect on stock index returns. Additionally, control variables have shown significant effects on the return of the Tehran Stock Exchange (TSE) All-Share Index 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            Reza  Taleblou; Mir ALI  Kamali Seyyed Baglou; Parisa  Mohajeri
                        
            
                
                    Abstract 
                
 
                
                    This study employs a comparative analytical framework to examine credit default prediction using a comprehensive dataset of 56,965 loan contracts issued between 2019 and 2024 at Bank Melli Iran's northern branches. Three distinct modeling approaches were evaluated: traditional logistic regression, ... 
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                    This study employs a comparative analytical framework to examine credit default prediction using a comprehensive dataset of 56,965 loan contracts issued between 2019 and 2024 at Bank Melli Iran's northern branches. Three distinct modeling approaches were evaluated: traditional logistic regression, and two ensemble machine learning methods—Random Forest (RF) and Extreme Gradient Boosting (XGBoost). The analysis incorporates 29 predictive features categorized into three conceptual groups: loan contract characteristics (e.g., principal amount, repayment tenure, collateral type), borrower attributes (e.g., age, occupational profile, credit history), and institutional factors (e.g., branch location, branch type). The dataset underwent preprocessing procedures such as outlier removal, text categorization, extraction of variables like age and grace period. The models were evaluated under both baseline and optimized (hyperparameter-tuned) conditions. Results demonstrate machine learning models significantly outperformed conventional approaches, with XGBoost achieving superior discrimination (ROC-AUC = 99.73%) followed closely by RF (99.68%), while logistic regression trailed substantially (75.34%). The average AUC difference between the machine learning models and logistic regression was approximately 0.243, and statistical tests with 95% confidence intervals confirmed the significance of this gap. Overall, the findings confirm the reliable superiority of machine learning approaches in predicting loan default. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            Reza  Maaboudi; Zeynab  Dare Nazari
                        
            
                
                    Abstract 
                
 
                
                    This study aims to investigate the threshold effect of FinTech on the oil rent–growth nexus in Iran. The threshold regression approach and seasonal data for 2013-2022 were used to analyze the relationships among variables. Results indicate that oil rent has a significant and negative impact on economic ... 
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                    This study aims to investigate the threshold effect of FinTech on the oil rent–growth nexus in Iran. The threshold regression approach and seasonal data for 2013-2022 were used to analyze the relationships among variables. Results indicate that oil rent has a significant and negative impact on economic growth both before and after FinTech reaches its threshold level of 0.146. However, once FinTech surpasses this threshold, the intensity of the resource curse's effect on economic growth diminishes. Additionally, the interaction effect between oil rent and FinTech has a significant and negative effect on economic growth before FinTech reaches the threshold, but after surpassing the threshold, the interaction effect of oil rent and FinTech on economic growth is significant and positive. Inefficient use of oil revenue through increased rent and corruption reduces economic growth. However, the expansion of FinTech, using digital technologies, increases the access of non-oil sector firms and entrepreneurs to financial services, which in turn leads to an increase in employment and a decrease in the pivotal role of oil in the economy. Therefore, fintech development reduces the negative impact of oil rents on economic growth. Accordingly, it is recommended that government, by developing FinTech platforms and blockchain technologies, in addition to further monitoring the allocation of oil revenues to the country's public budget, facilitate access to capital for entrepreneurs and small businesses active in the high technology sector, and reduce negative effects of oil rent on economic growth through optimal resource management and balanced development of various production sectors. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            ali  nikoonesbati; abbas  assari; farshad  Momeni; Lotfali  Agheli
                        
            
                
                    Abstract 
                
 
                
                    The challenges of policy making in the current evolving world have caused the idea of presenting hybrid models to analyze the causes of policy success and failure should be considered in recent years. Studies show that institutional and behavioral approaches face challenges in adequately explaining policy ... 
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                    The challenges of policy making in the current evolving world have caused the idea of presenting hybrid models to analyze the causes of policy success and failure should be considered in recent years. Studies show that institutional and behavioral approaches face challenges in adequately explaining policy failure. The institutional approach does not provide an adequate explanation for policy mistakes in a democratic structure, and the behavioral approach cannot adequately explain the lack of policy reform despite nudges. o overcome these challenges, a new model for explaining policymaking has been proposed, relying on two institutional-behavioral approaches, which emphasizes the importance of institutions, heuristics, and the institutional structure in the success or failure of policymaking.
Using the comparative analysis method, indicators and policies in Iran in the housing and health sectors were examined., the share of housing and health costs in total urban household expenses in Iran is almost twice the global average, which means a failure of policymaking. The reason for this failure is, on the one hand, the gap between the country's institutional structure and the democratic system, which has a negative impact on the quality of policymaking. In addition, cognitive bias can be seen due availability heuristics in both housing and treatment sectors. In fact, the policy maker simply assumes that he can improve the conditions by using resources and increasing supply. Also, the policymaker neglects the effective laws and rules (institutions) in each sector, which is also very effective in the failure of policies 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            alireza  Erfani; elmira  asl roosta; abdolmohamad  kashian
                        
            
                
                    Abstract 
                
 
                
                    The exchange rate has always been one of the most important economic indicators, influenced by various factors. Some of these factors are reflected in economic variables, while others are manifested in political-economic news. An important question that has not yet been precisely answered is whether ... 
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                    The exchange rate has always been one of the most important economic indicators, influenced by various factors. Some of these factors are reflected in economic variables, while others are manifested in political-economic news. An important question that has not yet been precisely answered is whether it is possible to have a comprehensive model for modeling and predicting the exchange rate that encompasses all effective variables and factors. In this research, as an answer to this question, a comprehensive model based on deep learning is presented using machine learning and a data fusion approach. The model supports various types of data, and for its training, news affecting the exchange rate from 10 major domestic and international sources were collected over the period from 2014 to 2023. These were provided to the model along with exchange rate data and other economic indicators. To find the best model, eight machine learning models, two statistical models, and a large language model (LLM) were trained and tested in both regression and classification modes. To avoid bias and random results, cross-validation techniques and repeated training and testing of the models with different random initial values were employed. The results indicate that the proposed approach, by directly considering all influential factors, has significantly outperformed previous approaches. 
                
             
            
            
            
        
    
        
        
            
                                    Research Paper
                                            
            
                            Azam  Ahmadyan
                        
            
                
                    Abstract 
                
 
                
                    Today, the importance of the presence and emergence of fintechs, especially fintechs active in the financial field, is not hidden from anyone. This issue is important to the extent that a wide range of recent studies have focused on the performance of fintechs and their relationship with macroeconomics ... 
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                    Today, the importance of the presence and emergence of fintechs, especially fintechs active in the financial field, is not hidden from anyone. This issue is important to the extent that a wide range of recent studies have focused on the performance of fintechs and their relationship with macroeconomics at the international level. International experiences show that fintechs have greatly improved economic growth and controlled inflation by expanding access to financial services. Therefore, their presence can affect the macroeconomic performance. One of the main concerns of economic policymakers in recent years has been to improve economic growth. There are several basic questions. First, how the emergence and presence of fintechs can affect economic growth. Second, what is the long-term and short-term effects of the presence of fintechs on economic growth. Third, the effect of fintechs on economic growth is different in different thresholds of inflation, liquidity, exchange rate and stock price index variables. In this article, using time series data during 1991-2022 and using ARDL method, the short term and long term effect of fintechs on economic growth has been investigated. Then, using the threshold regression method, the effect of fintechs has been investigated in different thresholds of inflation, liquidity, exchange rate and stock price index. The results of the autoregression method with a break indicate the negative effect of fintechs on economic growth in the short term and its positive effect in the long term.