https://ecoj.sbu.ac.ir/ Journal of Economics and Modelling en daily 1 Sun, 22 Feb 2026 00:00:00 +0330 Sun, 22 Feb 2026 00:00:00 +0330 https://ecoj.sbu.ac.ir/article_106795.html networks naturally diminishes, and the distribution structure and inequality at the macro level become more uniform. On the other hand, as emphasized by Carvalho (2014), the structure of the production network plays a crucial role in determining how microeconomic shocks originating in a firm or a specific technology are transmitted to other sectors and eventually to the entire economy.The aim of this study is to examine the role of Iran’s production network structure in the transmission of micro shocks to the macroeconomic level. For this purpose, using input–output tables, Iran’s production network at the industry level was constructed, and its characteristics were described using various network indicators including indegree, outdegree, degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Furthermore, by estimating the parameters of the Pareto distribution, the role of the production network structure in the propagation of micro shocks to macroeconomic fluctuations in Iran was evaluated.The results indicate that Iran’s production network is characterized by “small-world” properties, but with a lower level of concentration compared to industrial economies. The existence of certain hub sectors such as finance, wholesale, and chemicals highlights their potential importance in shock transmission. However, the large values of the Pareto parameters suggest that in most years sectoral shocks are mainly absorbed within the respective industry, and only in specific periods (such as 2004) does the probability of their transmission to the macro level increase. https://ecoj.sbu.ac.ir/article_106793.html This study examines the role of the government in financial stability in Iran. By analyzing data and deriving relevant indices, the paper shows that even without a zero lower bound— which in advanced economies marks the limits of monetary policy and justifies fiscal intervention— it remains essential to assess the government’s capacity in Iran. By using an NK-DSGE model, three scenarios of the government’s response to financial instability are examined: (i) non-intervention, (ii) transfer of funds to banks, (iii) stimulus fiscal policy. The analysis reveals a trade-off between financial stability, output stabilization, and inflation. when financial stability and output stabilization are policy priorities, fiscal policy proves more effective, although it is more inflationary. Both non-intervention and transfer of funds are inflationary, yet avoiding fiscal stimulus may lead to a stagflation. As far as financial stability is concerned, even non-intervention performs better than transferring funds. Moreover, the channels through which government expenditure is financed have distinct effects: government bank financing, when announced, increases inflation and weakens financial stability, whereas private bank financing results in lower inflation and greater financial stability. The situation is very different under fiscal shocks, financing through private banks weakens financial stability, while government ones enhance it. Finally, the average fiscal multiplier is 0.7691, indicating that the impact of fiscal stimulus is limited. All in all, these findings suggest that the government's influence on financial stability is constrained by its policy priority and financing mechanism of public expenditure. https://ecoj.sbu.ac.ir/article_106794.html Modeling based on the dynamics of a four-sector economy is a powerful approach for analyzing the structure and long-term behavior of the macroeconomy. By identifying causal and feedback relationships among variables, it enables the simulation of various scenarios. The problem addressed in this research is the creation of an analytical and feedback-driven framework for the Iranian economy, based on four sectors: households, firms, government, and the external sector (sanctions and other variables). Utilizing a System Dynamics (SD) model within the Vensim software environment, this study analyzes each of the four sectors and their interconnections for the period 1978 to 2029 (where 1978–2024 involves simulations based on existing historical data, and 2025–2029 constitutes the forecasting years). The simulation results indicate that policies lacking deep insight into the functioning of Iran's macroeconomy are ultimately doomed to failure and "self-sanctioning." Given the feedback loops presented in the four economic sectors—which represent the economy's aggregate demand—various types of sanctions seek to inflict "multi-layered pain," steering the economic system toward continued stagflation and altering the target country's behavior to the point of degrading its status to that of a colony. This multi-layered pain acts as a multi-dimensional pressure, encompassing high commodity prices, restricted foreign exchange earnings, rising unemployment rates, and the creation of a destructive environment for investment. Considering the probable scenarios of intensifying sanctions, it is essential to simultaneously prioritize three counter-policies: the integration and targeting of policies, economic diversification and strengthening the production base, and the expansion of alternative interactions. https://ecoj.sbu.ac.ir/article_106796.html Outward migration from Iran has, in recent decades, emerged as a salient consequence of macroeconomic instability, particularly inflation and unemployment. Given pervasive macro-level uncertainty, structural rigidities, and asymmetric behavioral responses, positive and negative shocks to these variables are expected to exert differential effects on migration decisions. This study employs a Nonlinear Autoregressive Distributed Lag (NARDL) model to examine the asymmetric impacts of inflation and unemployment on Iran’s outward migration over the period 1974–2023. The findings indicate that positive shocks to inflation and unemployment generate strong and statistically significant push effects on migration, whereas negative shocks exhibit markedly weaker and limited deterrent effects. In addition, real per capita income and foreign direct investment are found to reduce migration in the long run, while population growth intensifies migration pressures. The primary contribution of this research lies in identifying the behavioral rigidity of migration and providing empirical evidence of asymmetric macroeconomic effects, demonstrating that the disruptive force of crises in stimulating emigration outweighs the restraining capacity of stabilization. Accordingly, policy emphasis on anchoring inflation expectations, implementing structural labor market reforms, and mitigating institutional uncertainty is recommended to achieve a sustained containment of outward migration. https://ecoj.sbu.ac.ir/article_106797.html Nowadays, as global investment in fintech has increased sharply, there are various perspectives regarding the impact of fintech products on reducing banks’ risk-taking behavior through improving their operational efficiency. Since identifying and explaining the channels through which fintech innovation affects different dimensions of banks’ risk can provide an answer to this unexplored aspect of fintech innovation, the following question arises, Therefore, the aim of this study is to investigate the impact of FinTech innovations on the risk-taking and financial stability indicators of banks listed on the Tehran Stock Exchange. Data from 10 banks during 2017-2024 were analyzed using panel data and multivariate linear regression. The results showed that FinTech innovation has a positive and significant impact on the asset-to-capital ratio and Z-Score, in a way that improves the capital structure and increases the distance from the bankruptcy threshold. It also has an inverse and significant impact on the deposit-to-lending ratio, which indicates a decrease in reliance on traditional resources and diversification in banks' financial resources. https://ecoj.sbu.ac.ir/article_106798.html This study proposes a structural optimization framework for simulating electricity capacity markets, incorporating both fossil-fuel and renewable energy sources. The proposed model integrates market economic behavior with intelligent computational methods through the Grey Wolf Optimizer algorithm. In the first stage, the inverse demand function is estimated using real market data, including short-term stochastic fluctuations to capture demand uncertainty. Next, the cost structure of electricity generation units is derived by separating fixed and variable components, based on observed capacity and production patterns. Finally, the GWO algorithm is applied to determine the optimal allocation of generation capacity under technical and market constraints. The hierarchical design of the algorithm enables efficient exploration of the decision space, rapid convergence, and preservation of economic consistency. Simulation results indicate inefficiencies in the utilization of fossil-fuel units, while renewable energy units, with near-zero marginal costs, demonstrate superior economic performance. The proposed framework serves as a comprehensive tool for market equilibrium analysis and capacity planning and can inform energy policy evaluation and strategic decision-making in electricity markets and capital-intensive industries.