Energy
azadeh mehrabian; Golestaneh Mehrdad; Roya Seifipour; Ali Akbar khosravinejad
Abstract
Energy security, as a key factor in economic growth, plays a crucial role in development, reducing economic uncertainties, and enhancing productivity. However, empirical evidence suggests that its impact on economic growth is not uniform across countries and may be influenced by the level of human development. ...
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Energy security, as a key factor in economic growth, plays a crucial role in development, reducing economic uncertainties, and enhancing productivity. However, empirical evidence suggests that its impact on economic growth is not uniform across countries and may be influenced by the level of human development. Accordingly, this study investigates the nonlinear relationship between energy security and economic growth, emphasizing the threshold role of the Human Development Index (HDI). To this end, a composite energy security index was first calculated using Principal Component Analysis (PCA). Subsequently, its effect on economic growth was estimated using a Panel Threshold Kink Model (PTKM). The sample comprises developed and developing countries over the period 2000 to 2023, a timeframe selected due to contemporary energy security concerns. The results indicate that the effect of energy security on economic growth depends on the level of human development. Specifically, after the HDI surpasses a certain threshold, the intensity of energy security’s impact on economic growth strengthens. The findings also reveal that countries with higher levels of human development characterized by greater human capital, better institutional quality, and superior technological capacity are more capable of harnessing the benefits of energy security. Overall, the results underscore the simultaneous importance of enhancing both energy security and human development in achieving sustainable economic growth.
s
fateme moghtadaei; Narges Salehnia
Abstract
Food security, as one of the pillars of sustainable development, depends on various factors.However, what can influence the intensity and direction of the impact of these factors is the level of innovation.Therefore,the present study investigated the impact of environmental, climatic, and economic variables ...
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Food security, as one of the pillars of sustainable development, depends on various factors.However, what can influence the intensity and direction of the impact of these factors is the level of innovation.Therefore,the present study investigated the impact of environmental, climatic, and economic variables on food security in the context of global innovation in 87 countries from 2012 to 2022.For this purpose, a panel smooth transition regression model was used and the threshold variable of the Global Innovation Index was considered.The results indicate a nonlinear relationship and confirms a model with a threshold and two regimes.The speed of adjustment is 3.8947,which indicates a smooth and gradual transition between regimes, and the location of the regime change is estimated to be 44.0173.The ecological footprint has a significant effect on food security in both regimes, but the intensity of its positive effect in the high regime is much greater than the negative effect in the low regime.Evapotranspiration in the low regime has a negative effect and in the high regime has a positive effect of food security.Urbanization in the low regime has a positive effect and in the high regime has a negative effect of food security.GDP has a positive effect on food security in both regimes, but this effect is greatly reduced in the high regime.Agricultural land has a positive effect only in the high regime and foreign direct investment has a negative effect on food security only in the low regime.
s
Mohammad Mohsen sadr; Hossein Tebyaniyan
Abstract
Monetary policy, as a key tool of macroeconomic management, plays a decisive role in financial stability and economic growth. As an important channel for transmitting monetary policy, the capital market reflects investors' expectations and reactions to changes in interest rates, liquidity, inflation, ...
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Monetary policy, as a key tool of macroeconomic management, plays a decisive role in financial stability and economic growth. As an important channel for transmitting monetary policy, the capital market reflects investors' expectations and reactions to changes in interest rates, liquidity, inflation, and exchange rates. In economies like Iran that face chronic inflation, currency shocks, and budget dependence on oil revenues, the capital market's response to monetary policies is asymmetric and nonlinear, and traditional linear models are unable to fully explain it. This study aims to fill this methodological gap by offering a combined approach of econometrics and artificial intelligence. In this framework, the structural vector autoregression (SVAR) model is used to identify causal and short-run relationships between monetary variables and capital market indicators, and then it is combined with a multilayer artificial neural network (ANN) model to discover nonlinear patterns. Monthly data for Iran during the period 1390 to 1403 were analyzed. The results showed that monetary expansionary shocks increase the growth of the total stock market index by about 4.7 percent in the short term, but have a negative effect through the inflation channel in the long term. In contrast, contractionary policies by increasing interest rates cause a 3.5 percent drop in the index in the short term, but reduce volatility by 22 percent in the long term. The combined SVAR-ANN model predicted the market reaction with 91 percent accuracy (R²=0.91).
Economic Growth
Ali Hasanvand
Abstract
In recent years, environmental concerns in emerging economies have become a crucial challenge. This study investigates the determinants of the ecological footprint in ten selected N11 countries over the period 2000–2022. Considering cross-sectional dependence and heterogeneity in the data, a dual ...
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In recent years, environmental concerns in emerging economies have become a crucial challenge. This study investigates the determinants of the ecological footprint in ten selected N11 countries over the period 2000–2022. Considering cross-sectional dependence and heterogeneity in the data, a dual methodological framework was applied, consisting of panel regression with Driscoll–Kraay robust standard errors and Method of Moments Quantile Regression (MM-QR). The Driscoll–Kraay results indicate that GDP per capita (0.65), population (0.31), and trade openness (0.33) exert significant positive effects on the ecological footprint, whereas renewable energy consumption (–0.19), environmental innovation (–0.06), and telecommunications development (–0.12) contribute to its reduction. The quantile regression analysis reveals notable heterogeneous relationships. While the effects of GDP per capita and renewable energy consumption remain stable across the distribution, the mitigating role of environmental innovation becomes significantly stronger in countries with higher ecological footprints, with coefficients increasing from –0.04 to –0.07. In contrast, the positive impact of population and trade openness weakens at upper quantiles, and the environmental benefits of telecommunications development become statistically insignificant at higher pollution levels. These findings highlight the necessity of designing targeted policies tailored to countries’ pollution levels and suggest that achieving sustainable growth requires greater investment in clean energy and green innovation.
s
Abstract
One of the factors in the lack of balanced development is the political influence index. This index highlights the impact of lobbying and the influence of regional elites on the country's decision-making process, particularly in relation to regional development. The existence of unbalanced development ...
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One of the factors in the lack of balanced development is the political influence index. This index highlights the impact of lobbying and the influence of regional elites on the country's decision-making process, particularly in relation to regional development. The existence of unbalanced development in the country and the fundamental reasons for this heterogeneity increase the importance of research in this regard. The present study, seeks to investigate its effect on the industrial growth of regions in 31 provinces for the period of the third to twelfth governments in Iran. In this regard, the political influence index was introduced, and using the multiple-attribute decision-making method and the TOPSIS model, provincial data was extracted for it. Then, the impact of this index and the financial index on the industrial index of the regions was estimated using the panel data quantile regression model and the Eviews software. the impact of the political influence coefficient index on the industrial index has been greater than the financial index. The influence of independent variables on the dependent variables varied in different deciles, with the average political influence index influencing the industrial index 2.62 times as much as the financial index. Provinces with higher political influence coefficients also enjoyed higher financial and industrial growth. Tehran, with the highest political influence coefficient, had the highest financial and industrial growth, and Ilam, with the lowest political influence coefficient, had the lowest growth in these indicators.
Monetary policy
Nazar Dahmardeh; Ali Heydari Dizgarani
Abstract
This study analyzes the roots of government fiscal instability in the Iranian economy during the period 1978-2024. Despite the extensive literature on debt sustainability, there is a significant gap in understanding the structural interaction between oil revenues, expanding social obligations, and monetary ...
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This study analyzes the roots of government fiscal instability in the Iranian economy during the period 1978-2024. Despite the extensive literature on debt sustainability, there is a significant gap in understanding the structural interaction between oil revenues, expanding social obligations, and monetary policies in shaping fiscal sustainability in a petroleum economy like Iran. To address this gap, this study uses a methodological framework that simultaneously employs two complementary econometric methods: the Vector Error Correction Model (VECM) to identify short-run and long-run equilibrium relationships, and the Dynamic Least Squares (DOLS) method to directly and robustly estimate long-run coefficients. It also uses instantaneous response functions and historical variance decomposition to analyze the dynamics of shocks. The findings of this study indicate that fiscal instability in Iran is rooted in two structural crises: 1) dependence on oil revenues that makes policies pro-cyclical and reactive, and 2) the growing social security organization liabilities that make the budget inflexible. In the long-run model, economic growth and stable oil revenues have a stabilizing effect, while liquidity growth and the level of social obligations significantly exacerbate instability. Also, regarding the monetary base, the evidence is not uniform and conclusive in all estimates; therefore, its interpretation is presented with caution. These findings indicate that fiscal sustainability in Iran, in addition to dependence on oil revenues, also depends on the way social obligations and monetary discipline are managed.
