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Climate change is a global issue, driven largely by greenhouse gas emission, with carbon dioxide (CO2) being the biggest contributor. Iran, one of the top 10 emitters globally, faces unique challenges in reducing its CO2 emission due to economic sanctions, data gaps, and limited experience with climate policy. To help guide decision-makers, this study uses the Simplified DICE model—DICE model is a widely accepted tool for analyzing climate and economic interactions—to evaluate different strategies for emission reduction. These strategies mainly include carbon pricing, investment in renewables as mitigation of emission growth, and improving energy efficiency. The results show that such policies can positively impact GDP, temperature stabilization, and emission levels. This research provides the first numerical framework tailored to Iran’s specific context, offering practical insights for policymakers. Key policy implications include the necessity to overcome sanctions in aspects of Investment and technology absorption, improved data collection to refine future analyses, and adopting cost-effective measures that balance economic growth with environmental sustainability.

In this paper, the competitive market of crude oil exports of Iran and the world is modeled using game theory. In the present research, we have focused on OPEC's internal competition within the game theory framework to analyze the economic conflicts between OPEC members in detail. In the conditions where each of the producers has their own goals and limitations, the amount of access to the desired goals for each producer depends not only on the decisions they make, but also is affected by the prevailing atmosphere in the oil market, including the strategy of other competitors, sanctions, and different situations of economic growth and oil sale price level. In recent years, Western countries, especially the United States, have imposed extensive sanctions against Iran, mainly targeting. In this regard, three players of Iran, Saudi Arabia, and the United States of America (USA) were defined and a model for the game between them was presented. Then the presented model was solved as a cooperative game and the equilibrium point was obtained for it. The results obtained showed that the three main players have the conditions for cooperation by choosing the options of "reducing pressure and fewer sanctions", "reducing pressure and cooperation", and "cooperation", and Iran can only improve its conditions by competing with Saudi Arabia in OPEC.

Bifurcation constitutes a procedural mechanism in arbitration whereby complex disputes are segmented into separate and distinct issues to be addressed individually over the course of the proceedings. This stratification enables a more organized and methodical approach, commonly by isolating jurisdictional questions from the substantive merits of the case. Through the division of the dispute into discrete phases, bifurcation enhances procedural efficiency, allowing the parties to focus their efforts on pivotal matters while avoiding unnecessary expenditure of time and resources on ancillary issues. As a result, this mechanism often contributes to notable reductions in both the duration and overall cost of the arbitral process. In determining whether to bifurcate proceedings, arbitral tribunals assess key criteria: the preliminary objection must demonstrate substantive merit, be capable of adjudication independently of the merits, and possess the potential to resolve the dispute conclusively. The tribunal’s decision to implement this procedural tool ultimately depends on the specific facts and prevailing circumstances of the case.

The recent surge of artificial-intelligence (AI) activity has sparked concern that large-scale model training, cloud inference, and data-centre expansion could accelerate national energy demand. We marshal a 21-year annual panel for the United States (2004–2024) that couples multiple AI proxies—technology-stock valuations and a ChatGPT-era dummy—with four aggregate energy series (fossil fuels, nuclear, renewables, total primary energy). A five-stage empirical protocol implemented in Python combines Engle–Granger cointegration testing, higher-order ADF stationarity checks, linear and nonlinear dependence diagnostics (Pearson, Dynamic Time Warping, mutual information), multicollinearity screening (variance-inflation factors), and out-of-sample forecasting with linear regression, decision trees, random forests, and support-vector machines augmented by SHAP explainability. Across all tests we find no evidence that AI developments imprint on national energy use: AI variables cointegrate only with one another, their short-run correlations with energy vanish once trends are removed, their mutual-information scores remain near zero, and their inclusion never improves predictive accuracy beyond a parsimonious macro model driven by GDP, inflation, and population. SHAP rankings confirm that AI features carry negligible explanatory weight relative to conventional fundamentals. We conclude that, to date, AI’s macro-level energy footprint is statistically invisible—any electricity it consumes is either too small or offset by efficiency gains within the wider economy. Policymakers should therefore continue to anchor long-range energy scenarios to established economic drivers while monitoring localised data-centre hotspots that national aggregates obscure.

This study explores the considerable significance of candlestick chart patterns as a foundational asset within the realm of stock market analysis and prediction. As a graphical representation of historical price movements and patterns, Candlestick charts offer a distinct and valuable perspective for understanding how the financial market operates. This perspective assists us in accurately pinpointing the most advantageous times for making decisions to buy or sell financial securities, such as stocks or bonds. These charts provide insights into market trends and potential trading opportunities. We adopt an innovative approach by harnessing image processing techniques to extract and analyze patterns from Candlestick charts systematically. Our findings underscore the pivotal role of visual data in financial analysis, particularly in times of market volatility and uncertainty. Investors often resort to technical analysis strategies when confronted with erratic market trends, often relying on insights derived from chart-based analysis to guide their decision-making processes. By meticulously extracting essential insights from candlestick charts, our study aims to provide investors with more efficient and less error-prone tools. Ultimately, this endeavor contributes to the enhancement of decision-making precision and the mitigation of risks inherent in participating in the dynamic stock market landscape.

The positive impacts of fiscal policy could be undermined when accompanied by uncertainty. We examined the effect of fiscal policy uncertainty on economic activities in the provinces of Iran. It includes production, investment, unemployment, and economic participation of the active workforce in these provinces, taking into account the effects of economic sanctions imposed on the economy. We employed two types of shocks: fiscal level shock (representing fiscal policy) and its volatility shock (as fiscal policy uncertainty), which derived from a specified fiscal reaction function. We estimated a Panel VAR model using provincial data from 2003 to 2020. The results of the impulse response function indicated that following the impulse in the fiscal policy uncertainty, the response shows an increase in the unemployment rate in the short run, a decrease in the capital investment, and an increase in the inflation rate in the short and medium terms. In the medium and long term, the response indicates a decrease in GDP growth and a reduction in the economic participation rate of the active workforce.

The implementation of an effective tax system requires specific conditions, among the most critical being equity and efficiency. Taxation on income must align with the principle of the ability to pay; therefore, governments strive to set tax rates appropriately and impactfully. An disproportionate increase in income tax rates can lead to significant social repercussions on income distribution and public welfare. Consequently, calculating the optimal tax rate to maximize social welfare is deemed essential. This paper models the strategic interaction between taxpayers and the tax authority to achieve an optimal tax rate and identifies the factors influencing this rate. By designing a game among taxpayers, assumed to be uniformly distributed within the interval [0, 1], and evaluating the revenue generation of the tax authority, the paper delves into the game formulation and analyses the results. Findings indicate that the optimal tax rate exhibits an inverse relationship with the assessment rates set by investigating groups. Additionally, under specific conditions, the optimal performance tax rate has been determined to be 18%.

The exchange rate is a critical variable that impacts the economy in the international environment. The purpose of this study is to evaluate and compare the two approaches to exchange rate determination outlined in the Law on Permanent Decrees of the Country's Development Programs under economic sanctions. The analysis involves a theoretical discussion of a set of mathematical equations and software results, obtained from the algebraic and numerical solving of a simulated version of a dynamic stochastic general equilibrium model in the context of the international economy for a small open economy. The model is calibrated using the structural parameters of the Iranian economy. The criterion for evaluating the rule and comparing it with other policy options is the "stability" of macroeconomic variables, a key aspect of the Resistive Economy Strategy as the obliging basic document in economic policy-making and planning. The stability is quantified using the "Variance" index. Based on the results of this study, the adoption of the rule-based inflationary exchange rate determination approach, compared with the contingency approach to exchange rate determination, on the one hand, offers the possibility of achieving lower inflation rates and exchange rate growth pace. On the other hand, it will reduce the instability of selected macroeconomic variables, which is desirable from the perspective of the overall policies of the resistance economy strategy. Therefore, it is recommended that, in the presence of foreign economic sanctions, the economic authority should implement inflationary rule of exchange rate determination based on the current inflation rate.