Economics Research

Abstract  Iran simultaneously faces the dual challenges of economic sanctions and escalating environmental concerns. This study aims to examine how oil export sanctions contribute to increasing carbon dioxide (CO₂) emissions across various economic sectors. Using the dynamic GTAP-E-Power model—a computable general equilibrium (CGE) model tailored for energy and environmental analysis—the impact of sanctions is assessed under three oil export reduction scenarios: 60%, 65%, and 70%. Results indicate a consistent increase in Iran’s total CO₂ emissions under all scenarios, with emissions rising further as the severity of sanctions intensifies. Sectoral analysis reveals that electricity production and distribution, low-tech manufacturing, base-load fossil fuel power generation, and petroleum refining are the most affected, showing substantial emission increases. Conversely, sectors such as renewable-based electricity generation and high-tech manufacturing either experienced a decline or only a marginal increase in emissions. These findings suggest that sanctions not only impact Iran’s economy but also exacerbate environmental degradation. Accordingly, the study recommends prioritizing the removal of sanctions as a macro-level policy objective, enhancing investment in oil extraction with modern technologies, expanding renewable energy infrastructure, and supporting high-tech industries that demonstrate greater resilience to sanctions and lower environmental costs.
Introduction
Iran is concurrently grappling with widespread economic sanctions and escalating environmental challenges. Among these, the impact of oil export sanctions on carbon dioxide (CO₂) emissions stands out as a critical concern. This study investigates the extent to which sanctions, particularly those reducing Iran's oil exports, exacerbate environmental degradation. Employing a computable general equilibrium (CGE) model—specifically, the dynamic GTAP-E-Power model—this study assesses CO₂ emissions under three scenarios of oil export reduction: 60%, 65%, and 70%. The results reveal a direct correlation between intensified sanctions and increased CO₂ emissions, emphasizing the environmental costs of economic isolation.
Methods and Materials
The study utilizes the GTAP-E-Power model, a dynamic extension of the Global Trade Analysis Project framework, tailored to incorporate power sector and energy-related emissions. This model facilitates the analysis of environmental impacts resulting from shifts in economic and energy-related variables. The analysis simulates three scenarios wherein Iran’s oil exports are reduced by 60%, 65%, and 70%, respectively, over the period from 2019 to 2050. The model estimates CO₂ emissions across various economic sectors under these constrained export conditions, comparing them to a baseline of unrestricted oil trade.
Results and Discussion
The simulation results indicate a consistent increase in CO₂ emissions within Iran as oil export sanctions intensify. Specifically, emissions rise by an average of 0.187%, 0.193%, and 0.197% in the three respective scenarios. Conversely, sanctioning countries experience a decline in their own CO₂ emissions, likely due to increased adoption of clean energy alternatives.
Sectoral analysis reveals that electricity production and distribution, low-tech industries, fossil fuel-based power generation, and oil product manufacturing are the most affected sectors. These sectors exhibit the highest CO₂ emission increases, with emission intensity growing alongside the severity of sanctions. In contrast, sectors relying on renewable energy and high-tech industries display minimal or even negative emission growth, highlighting their resilience.
Electricity generation using fossil fuels under base load conditions sees annual average CO₂ increases of 0.602%, 0.641%, and 0.677%, while peak load shows slightly lower increases. However, renewable-based electricity generation demonstrates minimal or negative changes: +0.015% and +0.08% in the first two scenarios, and -0.001% in the third.
Moreover, low-tech and medium-tech industries show significantly higher increases in emissions than high-tech industries, which remain relatively unaffected due to their access to advanced and efficient technologies. Similarly, sectors such as mining, coal, agriculture, and services all show
Conclusion
The findings underscore the substantial environmental costs of oil export sanctions on Iran. Sanctions lead to increased reliance on carbon-intensive industries and outdated technologies, thereby elevating national CO₂ emissions. In contrast, high-tech sectors and renewable energy-based power generation exhibit greater resilience.
Key policy recommendations include:

Prioritizing the removal of international sanctions to mitigate environmental and economic damage.
Investing in oil product manufacturing with access to cleaner, advanced technologies.
Expanding renewable energy sources in electricity production to reduce fossil fuel dependency.
Strengthening high-tech industries to enhance technological resilience.
Focusing development on sanction-resilient sectors, particularly those capable of maintaining efficiency and environmental standards under constrained conditions.

Strategic investments in clean technology and the facilitation of knowledge transfer are vital to offsetting the negative environmental consequences of continued sanctions.

Abstract  Concerns about energy prices, environmental sustainability, and economic stability highlight the need to examine the effects of energy market liberalization, as fluctuations in oil and gas prices have profound impacts on economic and environmental variables. This study, based on a dynamic computable general equilibrium model and GTAP-E database, investigates the impact of energy price liberalization on environmental variables and mineral products across three country groups—Iran, its major trading partners, and the rest of the world—under two scenarios: (1) a 5% gas price shock and (2) a 5% oil price shock, projecting up to the year 2050. The simulation results show that for Iran, the first scenario leads to a gradual and sustained reduction in carbon dioxide emissions, reflecting a negative relationship between CO₂ emissions and gas prices due to decreased fossil fuel consumption and a shift towards more efficient or alternative energy sources in mineral production. The second scenario results in a smaller but still significant reduction in carbon dioxide emissions. For Iran’s trading partners, the first scenario results in a long-term emission reduction owing to higher production costs and adoption of cleaner technologies, while the second scenario leads to faster reductions due to the mining sector’s dependency on oil and accelerated investments in energy-saving measures. For other regions, the first scenario shows an initial moderate reduction in carbon dioxide emissions followed by a temporary rebound, indicating delayed decarbonization; scenario two, however, leads to a sustained decline, underscoring the key role of oil in energy and mining sectors. The findings emphasize that energy price liberalization must be aligned with market realities and should promote improved consumption efficiency and innovation in clean technologies.
Introduction
Energy market liberalization, particularly through the removal of subsidies and the alignment of domestic energy prices with international levels, has been a subject of growing interest due to its potential implications for economic efficiency, fiscal sustainability, environmental outcomes, and energy security. Fluctuations in oil and gas prices significantly influence macroeconomic variables, industrial competitiveness, and greenhouse gas emissions, particularly in resource-dependent economies like Iran. This study adds to the existing literature by using a dynamic computable general equilibrium (DCGE) model based on the GTAP-E database, an extension of the standard GTAP framework that explicitly incorporates energy substitution, fossil fuel combustion, and CO₂ emissions (Burniaux and Truong, 2002) to analyze the long-term effects of energy price liberalization on CO₂ emissions in mineral production sectors. 
While prior research has utilized GTAP-E in static or limited dynamic contexts, the application of a fully dynamic version with intertemporal adjustments, solved using GEMPACK algorithms and drawing on comprehensive regional and sectoral data from the GTAP database, represents a methodological advancement. This approach enables detailed projections up to 2050 and captures sector-specific responses in mineral industries, which are particularly energy-intensive and play a key role in Iran's economy and trade. The central research question is: How does energy price liberalization modeled as exogenous shocks to natural gas and oil prices affect CO₂ emissions in mineral production across Iran, its major trading partners, and the rest of the world? 
Methods and Material
This study employs the Global Trade Analysis Project-Energy (GTAP-E) model, a multi-region, multi-sector, multi-agent computable general equilibrium (CGE) framework developed by Burniaux and Truong (2002). GTAP-E extends the standard GTAP model (Hertel, 1997) by explicitly incorporating energy substitution mechanisms and the linkage between energy consumption and greenhouse gas emissions, particularly CO₂ emissions from fossil fuel combustion. This allows for a detailed analysis of the environmental and economic impacts of energy price changes across sectors, regions, and agents. The multi-regional structure of GTAP-E provides significant advantages over single-region models by capturing inter-sectoral, inter-country, and inter-factor linkages on a global scale (Wu et al., 2019). Computable General Equilibrium (CGE) models have been widely applied in energy and environmental policy analysis since the 1980s, offering a consistent framework for evaluating the economic and environmental consequences of policy interventions (Rao et al., 2017; Chi et al., 2014). Their comprehensive treatment of resource allocation distortions caused by energy subsidies further justifies their use in this context (Manzoor et al., 2021).
To capture long-run dynamics and cumulative effects of policy reforms, this study employs a dynamic version of the GTAP-E model (DCGE). Unlike static CGE models, which are limited in their ability to account for growth effects, capital accumulation, and transitional paths, dynamic CGE models incorporate intertemporal adjustments, enabling realistic projections of medium- to long-term impacts where short-run and long-run effects may differ substantially (Zhang et al., 2020). The model is calibrated using the GTAP-E database and solved with GEMPACK software, allowing for the simulation of exogenous energy price shocks and their propagation through the global economy up to 2050.
Results and Discussion
Carbon intensity (CO₂ emissions per unit output) measures sectoral carbon efficiency. Table 4 reports changes under two 5% price shock scenarios—gas (Scenario 1) and oil (Scenario 2)—for Iran, trading partners, and other regions. The moderate price shock corresponds to historical fluctuations, consistent with prior studies (Eskandaripour et al., 2023; Lebrand et al., 2023).
In Iran, Scenario 1 reduced intensity markedly in oil (-26.22%), industry (-42.6%), minerals (-11.09%), and services (-13.27%) via cost-induced efficiency, but increased electricity (+46.9%) due to substitution to dirtier fuels (Barro et al., 2025). Gas intensity fell (-8.37%). Scenario 2 raised intensity in oil (+26.39%), gas (+4.69%), industry (+10.74%), and electricity (+16.73%) from fuel switching, while lowering it in agriculture (-16.12%), minerals (-8.93%), and services (-8.63%).
Trading partners exhibited heterogeneous responses: Scenario 1 increased gas (+0.52%) and coal (+0.23%) most; Scenario 2 amplified oil (+1.31%) and coal (+1.69%) rises, offset by non-energy sector declines. Other regions showed mostly reductions under Scenario 1 (except gas +0.65%, coal +0.29%), but energy sector increases under Scenario 2. Asymmetric patterns reflect fuel substitutability and sectoral vulnerabilities, implying uneven carbon pricing effects.
Table 5 shows fuel-specific CO2 emissions. Iran’s Scenario 1 raised oil/petroleum emissions but cut gas (-61.64%) and coal; Scenario 2 reversed oil trends. Trading partners shifted to coal/gas in Scenario 2; other regions reduced gas/petroleum more in Scenario 1 and oil in Scenario 2. Both scenarios trended downward overall.
Long-term mineral products CO2 emissions (Table 6, 2023–2050) declined steadily in Iran under Scenario 1 (~ -26.7 to -34 units) via efficiency incentives (Mosavi et al., 2017; Attílio et al., 2024), and less sharply under Scenario 2 (~ -9.5 to -12 units) due to lower oil substitutability (Ebaid et al., 2022). Trading partners had sharper Scenario 2 reductions (-0.95 by 2050); other regions showed sustained deepening under Scenario 2 (-0.87), consistent with oil-driven decarbonization and EKC dynamics (Kuznets, 1955; Zhou et al., 2021).
Gas shocks yield rapid gas-sector efficiency but risk dirty substitution in electricity; oil shocks promote broader long-term decarbonization. Policies should address substitution risks and facilitate technological transitions.
Conclusion
This study utilizes a dynamic computable general equilibrium (DCGE) model based on GTAP-E (version 10) data to simulate the effects of two energy price shocks—a 5% increase in natural gas prices and a 5% increase in oil prices—from 2023 to 2050. The results highlight distinct emission reduction pathways for Iran, its major trading partners, and the rest of the world, offering important insights for energy transition and climate mitigation policies.
In Iran, a natural gas price shock drives a gradual and sustained decline in greenhouse gas emissions, reflecting substitution toward cleaner energy sources and improved energy efficiency in mineral production. An oil price shock produces a milder but steady reduction, indicating lower substitutability in industrial sectors. These responses are consistent with the Environmental Kuznets Curve, where higher energy prices stimulate emission-reducing investments, with effects varying depending on sector-specific energy dependence and technological capacity. The reductions also stem from cleaner production technologies and a shift to low-carbon mineral products, consistent with Khan et al. (2022) and Antimiani et al. (2014).
Iran’s trading partners show a slow but steady emission decline under the gas price shock due to initial inelastic demand and subsequent technological adjustments. Oil price shocks lead to faster and sharper reductions, driven by greater oil reliance in their mineral sectors and stronger incentives for energy-saving innovations—patterns similar to those in developed industrial economies.
In other world regions, natural gas price increases result in an initial decline, temporary rebound, and eventual sustained reduction, reflecting structural rigidities and transition dynamics. Oil price shocks, however, cause more consistent and substantial declines, emphasizing oil’s pivotal role in global energy and industry.
Overall, energy price liberalization can effectively reduce greenhouse gas emissions, especially when supported by policies that promote technological innovation, energy efficiency, and cleaner alternatives in energy-intensive sectors. Region-specific policies are essential to balance environmental gains with economic impacts.

Abstract   The role of deep hapbit in countercyclical behavior of mark-up and its impact on the transmission of monetary and fiscal shocks have already been studied, but its strength in the presence of Philips curve with price stickiness is not clear. The purpose of this study is to develop a New Keynesian Philips Curve (NKPC) following Cristiano et al. (2005), to investigate the simultaneous effect of price stickiness and deep habits on monetary and fiscal shock transmission using Markov- switching stochastic dynamic general equilibrium (MS-DSGE) model for the Iranian economy. The results of impulse-response functions show reducing markup for one period due to deep habits and then increasing markup and inflation after a period due to a stronger role of price stickiness. Moreover, although the negative effect of wealth due to government spending is compensated by deep habits consumption and thus makes consumption increase, it is weak in comparison to the strength of expected inflation, and therefore, inflation increases eventually. Overall, the results of this study indicate that deep habits cannot be a dominant factor in the transmission of monetary and fiscal shocks, but according to the obtained impulse response functions, it can be the strong reason to delay increasing inflation. Also, deep habits consumption can be a good reason for increasing consumption and compensating of the negative effect of wealth due to fiscal shock.

Abstract This study investigates the potential threshold effects in the relationship between corruption control index and GDP growth for the D-8 countries with the presence of other variables, including education expenditures, government consumption expenditures, agricultural raw materials exports, inflation rate, and index of openness over the period 1996-2011. For this purpose, the paper uses a Panel Smooth Transition Regression (PSTR) model that is an appropriate method for explaining cross-country heterogeneity. Our result rejects the linearity hypothesis, and gives a threshold at corruption control of -0.862. Based on this threshold, we can build a two-regime model.  In the first regime, corruption control, education expenditures, agricultural raw materials exports and index of openness variables have a significantly positive impact on GDP growth and government consumption expenditures and inflation rate variables have a significantly negative impact on GDP growth. In the second regime, however, corruption control, education expenditures, agricultural raw materials exports and index of openness variables have a positive impact and government consumption expenditures and inflation rate variables have a negative impact on GDP growth. Though, the impact of corruption control, education expenditures, agricultural raw materials exports and index of openness are increased and the impact of government consumption expenditures and inflation rate are dramatically declined.

Abstract The price index of shares of companies accepted in the Tehran Stock Exchange (TSE) is one of the main variables in evaluating macroeconomic performance­ of Iranian economy. One of the factors affecting stock price index of developing countries like Iran­, that has high degree of  volatility, is exchange rate uncertainty.The main objective of this paper is to investigate the effects of exchange rate uncertainty on price index in the TSE for the period of 1994-2009 using monthly data. In this regard,­ first, an index of exchange rate uncertainty is calculated using  EGARCH models. Then, in order to obtain the relationship between uncertainty in real exchange rate and the stock price index, Bounds test approach is applied to the relationship between level data. The results show that in both long-run and short-run, there is a negative and significant relationship between the exchange rate and stock prices. Moveover, real exchange rate uncertainty has a non-­significant negative effect on stock price in short-­run. In the long-run, the relationship between­ real exchange rate uncertainty and stock price is negative and significant. The results of Granger causality­­ test also show that bidirectional causality exists between the­ real exchange rate and real exchange rate uncertainty in the short­-run. While we could not find such an interactive relationship between other variables in the short-run, an indirect causality exists from exchange rate and exchange rate uncertainty to the stock price in the long-run.