مطالعات اقتصادی کاربردی ایران

Monetary policy is one of the most important tools for policymakers to influence macroeconomic variables including production. However, implementing this policy sometimes yields unintended consequences. Understanding monetary policy transmission mechanisms is therefore critical for effective implementation. Research following the 2008-2009 financial crisis indicates that the shadow banking activity can disrupt the monetary policy transmission and weaken its effectiveness. An analysis of Iran’s financial system reveals increasing shadow banking activity. This paper therefore examines how shadow banking affects monetary policy transmission in Iran using a DSGE model that innovatively incorporates the shadow banking sector. We compare two scenarios: a financial system without shadow banking and one including shadow banking. The effects of two contractionary monetary policies—interest rate increase and reductions in money supply growth—on GDP, investment, and inflation were analyzed under each scenario. The findings indicate that shadow banking diminishes monetary policy’s impact on all three variables by weakening the credit channel of monetary policy transmission. In the scenario without shadow banking, In the scenario without shadow banking, all three variables will decline in response to the monetary shock of decreasing money supply growth. However, in the scenario with shadow banking, investment levels are not declining but rising. The impact of monetary policy on output and inflation is diminished in the presence of shadow banking. In the case of interest rate shocks, the results also indicate a negative impact of shadow banking on the effectiveness of monetary policy.

Understanding the impact of financialization on the economy is crucial for policymakers seeking to design strategies that enhance social welfare. This study examines the effect of financialization on economic welfare in Iran from 1990 to 2023, employing a threshold regression approach to account for nonlinear dynamics. The results reveal a threshold level of institutional quality at 57%. Across both, i.e., low and high institutional quality regimes, financialization exerts a negative and significant influence on economic welfare. However, once institutional quality surpasses the threshold, the adverse impact of financialization intensifies markedly. Findings highlight the paradoxical role of institutional quality, showing that greater financialization consistently undermines welfare in Iran, with stronger institutions amplifying rather than mitigating its negative effects. It means that in environments with higher institutional quality, advanced financial instruments and capital markets develop; however, access to financial development is usually asymmetrical. Consequently, wealthy individuals and large corporations benefit the most, while low-income households receive minimal benefits and may even suffer from asset inflation or consumer debt. Thus, strong institutions do not necessarily prioritize public welfare. Policymakers may regulate to develop financial markets in a way that prioritizes the financial sector’s profitability over social interests. This mechanism can lead to financial sector growth occurring faster than the real economy’s capacity, ultimately undermining welfare.

The ecological footprint is an effective tool for evaluating the pressures exerted on ecosystems and the environment. Given its importance, the present study examines the impact of uncertainty in factors influencing the ecological footprint across 10 selected Asian and European countries. To this end, a fuzzy regression model was employed to analyze these effects during the period from 1996 to 2022. Leveraging the capabilities of fuzzy regression, the intensity of each factor’s influence on the ecological footprint was calculated in terms of fuzzy centers, left spreads, and right spreads. The findings reveal that Gross Domestic Product (GDP) in Iran (+5.5 and -4.5) had the most significant negative environmental impact, attributable to oil dependence and insufficient attention to environmental concerns. In contrast, China (+0.29 and -0.23) demonstrated improvements due to greener policies. Regarding trade (EX), Azerbaijan and Malaysia exhibited asymmetric effects due to their reliance on natural resource exports, whereas Romania (stable at 0.37) maintained more sustainable performance owing to European regulatory standards. Financial Development (FDI) showed high volatility in China (±6.13) and Thailand (+2.77 and -2.34), while Belarus (stable at 0.24) had the least impact. Hydropower energy consumption (HP) in Turkiye and Romania faced uncertainties due to large-scale projects, whereas Russia (stable at 0.007) played a minimal role. The key conclusion indicates that resource-dependent countries (e.g., Iran and Azerbaijan) exert greater environmental pressure, whereas economies with diversification (e.g., China) or strict regulatory standards (e.g., Romania) achieve better integration of economic growth and sustainability. These findings underscore the need for revising development policies to prioritize ecological balance.

In today’s global economy, sports, especially football, have become key drivers of economic activity, with an estimated fan base of five billion worldwide. Professional football is no longer just entertainment; it has evolved into a dynamic sector that makes substantial contributions to employment and economic output. Football clubs, as multifaceted economic entities, engage in competition not only on the field but also within a fiercely competitive commercial and financial environment. This study employs the Data Envelopment Analysis method to assess the economic performance and growth potential of Iran’s football industry. By analyzing data from 48 football clubs—including a selected group of international benchmarks and eight clubs from Iran’s Premier League—the research provides a comparative evaluation of technical efficiency across diverse organizational and market contexts. The results highlight a stark contrast between benchmark clubs and Iranian clubs. Only a handful of international clubs are positioned on the efficiency frontier, while Iranian clubs show inefficiency levels exceeding 90%, indicating a significant performance gap. This suggests a latent growth potential of more than 700% in critical areas such as revenue, market value, and global competitiveness. The findings underscore the need for institutional, financial, and managerial reforms to address these inefficiencies and unlock the considerable economic potential of Iran’s football industry. Improving technical efficiency could significantly boost the international standing of Iranian clubs and contribute to the broader development of the country’s sports economy.

Accurate stock market forecasting is a challenging and complex problem for the market analysts and decision makers. During the past decade’s accuracy of different methods are examined yet there is no consensus on optimum forecasting method. In this regard, the main objective of present study is to investigate eligibility of nonlinear time series, such as exponential smoothing and regime-switching models beside Box-Jenkins scheme in forecasting of stock return time series. Data set consist of daily observations of Apple and Microsoft corporations as of 2024 to 2025. The Terasvirta-Lin-Granger procedure chaotic behavior of data generating process of the selected samples being examined. The Self-Exciting Threshold Autoregressive procedure combined with GARCH component (SETARMA-GARCH) and ARMA model combined with EGARCH component (ARMA-EGARCH) in order to capture the heterogeneous variance of financial time series, which yield dynamic hybrid models. Moreover, due to the overwhelming application of Artificial Intelligence methods in computation, besides the Exponential Smoothing (ES) approach as a non-parametric method, a recently developed Multilayer Perceptron Network (MLP) based on Feed-Forward-Back Propagation (FF-BP) algorithm being developed either. Both of the in-sample and out-sample forecasting are carried out and performance of models is evaluated using standard error criteria. Finally, the Diebold-Mariano test is employed in order to determine the significance of forecasting differences among the models. Findings indicated that the behavior of the return series for the both of the corporations are chaotic and nonlinear methods are appropriate in modeling. The exponential smoothing method outperformed the developed SETARMA-GARCH and ARMA-EGARCH procedures in terms of the majority of error criteria in the both of in-sample and out-sample forecasting. However, the MLP has outweighed the ES model based on every calculated error criteria. The estimated S-statistic of Diebold-Mariano test confirmed results of the forecasting in favor of the MLP method. This finding suggests application of the dynamic nonparametric methods in modeling and forecasting of the selected time series. Implication of such finding recommends use of dynamic nonlinear and nonparametric methods in financial series prediction.

Total factor productivity (TFP) is a pivotal determinant of sustained economic growth, serving as a measure of how efficiently inputs are transformed into output. Elevating TFP is not just a technical goal but a strategic necessity for nations aiming to achieve enduring prosperity and bolster their global competitiveness. This study analyzes the influence of key factors—including domestic R&D accumulation, R&D spillovers via imports, human capital, property rights, and economic freedom—on TFP in selected developing countries between 2011 to 2022. The findings indicate that while domestic R&D accumulation alone yields a positive but statistically insignificant effect on TFP, other variables such as R&D spillovers, property rights, and economic freedom have significant and positive impacts. Importantly, the interplay between strong property rights and domestic R&D acts as a potent driver of productivity gains. These insights suggest that policymakers should not only support innovation and research efforts but also cultivate institutional environments that protect property rights and promote economic liberalization. Such a holistic approach is essential for maximizing productivity, fostering sustainable development, and enhancing a nation’s position on the world stage. By understanding and leveraging these mechanisms, developing countries can unlock greater economic potential and chart a path toward long-term growth.