Journal of economics and regional development

Abstract Given the expansion of international trade and the increasing role of the exchange rate in determining foreign exchange returns, this variable has become one of the key components in macroeconomic analyses. In this paper, the dynamic relationship between monetary policy and the exchange rate in the Afghan economy during the period from January 2011 to July 2021 is examined using continuous wavelet analysis. This approach allows the study of the interaction of variables in both time and frequency dimensions and allows short-term and long-term changes in the relationships between variables to be identified.The results of the study indicate that the monetary base in the medium term at the beginning and end of the period under study has played a causal role in the changes in the exchange rate, although at times in the short term this relationship has been reversed. However, the exchange rate has been the cause of the changes in the two variables of foreign exchange auction and capital bond auction, especially in the long term. Therefore, foreign exchange auction and capital bond auction have changed in the long term in response to changes in the exchange rate, while the cause of changes in the exchange rate, especially in the medium term, is related to the change in the monetary base.

Abstract The high share of women in today's economy and its increasing trend in the future show the necessity of addressing women's issues more than ever. The purpose of this research is to study the dimensions of the impact of gender inequalities on the women's human development index. For this purpose, the nonlinear panel smooth transition regression (PSTR) approach has been used. The statistical population includes 142 countries during the years 2000-2022. The modeling results indicate two thresholds of the degree of exposure to the globalization process of countries, which classify them into 3 levels. Given the existence of a nonlinear relationship between the dimensions of gender inequality and the women's human development index, this relationship changes slope at two threshold points. This means that the direction and amount of the impact of the main variables of the model on the women's human development index in different countries is different according to the level of participation in the globalization process. The most important influencing variable that has a positive effect on women's development in different countries and in any situation is the increase in equality in health status, which has a share of (0.12). After that, the improvement of the governance index and the women's legal and political index (WBL) have less positive effects on the women's human development index, respectively. The coefficient of influence of the variables of the educational, economic and political dimensions of gender inequality on the human development index is negative and at the same time very small (-0.015, -0.003 and -0.0007). Accordingly, it seems that if governments place women's health as one of the main drivers of human development at the center of their economic and social policies, they will have the greatest impact in this way.

Abstract 1. INTRODUCTION
According to economic theories, trade liberalization increases efficiency, economies of scale, improves competition, enhances factor productivity, and increases trade flows, ultimately leading to economic growth. In this regard, most countries prefer to establish bilateral or regional trade agreements to expand trade and strengthen international economic relations. In this regard, the Shanghai Cooperation Organization is a regional intergovernmental organization that was formed in 1996. This organization is also the largest producer and consumer of gas and currently has 12 members, including 9 permanent members Russia, China, Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, India, Pakistan and Iran, and 3 observer members. In addition, the Shanghai Cooperation Organization has great capacities in the energy sector, because by covering about a quarter of the world's population, it controls 23% of oil, 55% of natural gas and 35% of coal in the world. Undoubtedly, Iran's accession to the aforementioned organization will increase the potential and capacities of this organization. For this reason, the issue of energy is one of the focal points of Shanghai Cooperation Organization. Therefore, the present study seeks to answer the question of what impact Iran's membership in Shanghai Cooperation Organization and the elimination of trade tariffs between Iran and its members has on major energy sector indicators in Iran?

2- THEORETICAL FRAMEWORK
Operationally, the relationship between trade and energy consumption is a complex and multidimensional issue in energy economics and policy. In summary, it can be examined from the following aspects:
a) The impact of trade on energy consumption
• Increased consumption through trade: International trade often requires extensive transportation (ships, planes, trucks), which increases the consumption of fossil fuels. For example, the export and import of goods can increase global demand for energy, especially in oil and gas exporting countries, whose production and export are directly dependent on energy consumption.
• Reduced consumption through trade: Free trade can help transfer energy-efficient technologies (such as solar panels or optimization equipment). Developing countries can optimize their energy consumption through imports and reduce dependence on domestic resources.
b) Impact of energy consumption on trade
• Energy subsidies and pricing: In countries such as Iran, heavy subsidies on energy (such as cheap fuel) can encourage smuggling and disrupt formal trade. These subsidies increase domestic consumption and divert resources from exports (foreign trade).
• Energy and trade constraints: Energy shortages (such as power or gas outages) can disrupt industrial production and reduce exports. For example, in heavy industries such as steel, high energy consumption directly affects competitiveness in global markets.
• Energy trade as a specific area: Trade in gas, oil and electricity (such as regional gas hubs) is itself a type of trade that affects global energy consumption patterns. Competition for energy hubs can shape trade relations and supply consumption through new routes.
c) Global and policy aspects
According to reports from organizations such as the International Energy Agency (IEA), free trade can reduce energy intensity, but climate change and sanctions complicate this relationship. For example, sanctions have affected Iran’s energy trade and pressured domestic consumption. At the national level, policies such as energy price liberalization can reduce smuggling and facilitate foreign trade, while trade restrictions (such as sanctions) can lead to inefficient energy consumption.

3- METHODOLOGY
Between the computable general equilibrium models, the multi-regional general equilibrium model is specifically designed for the analysis of world trade and can conduct research and studies on the international flow of goods and services and factors of production in a dynamic and static manner. Using the multi-regional general equilibrium model instead of the single-regional general equilibrium model has several advantages. One of the strengths of these models is their ability to help understand the relationship between sectors, countries and factors of production on a global scale. Among the multi-regional general equilibrium models, the Global Trade Analysis Project for Energy-based models provides a variety of possibilities for world trade and energy-related research. Also, the required data are extracted from the Global Trade Analysis Project for Energy-based (GTAP-E) version 10 database and analyzed with the regional computable general equilibrium model and MATLAB software.

4- RESULTS & DISCUSSION
Results showed that reducing trade tariffs between Iran and other SCO member countries, on the one hand, due to the ease of replacing domestically produced goods with imported goods and on the other hand, due to the increased use of fossil energy exploration, production, and distribution technologies, leads to a decrease in fossil energy consumption, a decrease in total energy consumption, and an increase in energy consumption efficiency (a decrease in energy intensity and a decrease in energy consumption coefficient) in Iran. However, after a few periods, due to feedback effects, this decrease in total energy consumption, energy intensity, and energy consumption coefficient is neutralized. In other words, saving energy consumption and increasing energy consumption efficiency lead to an implicit decrease in energy prices and subsequently lead to a re-increase in total energy consumption, energy intensity, and energy consumption coefficient. In addition, reducing trade tariffs between Iran and other SCO member countries leads to an increase in renewable energy consumption in Iran due to increased cooperation in the development of renewable energy technologies.

5- CONCLUSIONS & SUGGESTIONS
According to the results of the research, Iran's most important trade advantages in the Shanghai Cooperation Organization should be sought in the energy sector, because on the one hand, the largest producers (such as Russia) and the largest consumers (such as China) of energy in the world are in this organization, and on the other hand, membership in this organization leads to a reduction in fossil energy consumption, an increase in the efficiency (intensity) of energy consumption, and an increase in the consumption of renewable energies. Therefore, it is suggested to the country's foreign policy and macroeconomic officials to take the necessary measures to reduce trade tariffs between Iran and other countries of the Shanghai Cooperation Organization.

Abstract The circular economy The circular economy has has emerged as a transformative paradigm in sustainable supply chain management, offering a strategic response to growing environmental challenges and resource constraints. Given the urgent need for industrial transformation in Iran, this study evaluates the performance of circular supply chains in Iranian industries using the innovative Intuitionistic Fuzzy Importance-Performance Analysis (I-FIPA) method. By measuring key indicators across five dimensions—institutional, behavioral, infrastructural, technological, and strategic—through surveys of industry experts, urban managers, and environmental specialists, the research reveals that successful implementation requires simultaneous attention to policy factors (e.g., supportive regulations), cultural aspects (e.g., awareness-raising), technological development (e.g., digital infrastructure), and structural frameworks (e.g., institutional mechanisms). The I-FIPA gap analysis further identifies critical bottlenecks in transitioning toward circular models. Beyond providing a comprehensive status assessment, this study serves as a strategic tool for policymakers, industrial managers, and planners to design operational frameworks and make evidence-based decisions.

Abstract Income inequality is one of the major economic challenges that significantly impacts the economic development of provinces. This phenomenon creates serious obstacles to provincial progress by reducing equal opportunities, increasing social instability, and limiting economic growth. Accordingly, the primary aim of this study is to examine the effects of economic fluctuations on income inequality in the urban areas of Iran's provinces. To achieve this objective, the present study utilizes a Bayesian panel model to analyze the impacts of inflation, economic growth, government expenditures, household income, unemployment rate, and population growth on the Gini coefficient of urban areas in 31 Iranian provinces over the period 1382–1402 (2003–2023). The findings indicate that, in the long term, inflation, government expenditures, unemployment rate, and annual household income changes have a positive effect on inequality across all provinces. In contrast, economic growth reduces inequality in the long term and positively contributes to income distribution. Additionally, the impact of population growth on inequality in urban areas of the provinces varies, reflecting the influence of regional variables. Furthermore, variance decomposition results reveal that, excluding the effect of the variable itself, inflation has the most significant impact in 20 provinces, while government expenditures are the most influential economic factor on the Gini coefficient in 11 provinces. The study's findings underscore the necessity of adopting targeted policies to reduce inflation, promote sustainable economic growth, and optimize government expenditures.

Abstract Present study examines impact of governance quality on financial sector development using a selected empirical dataset from the Middle Eastern countries for the period 1996-2022. For this purpose, overall governance quality index and six dimensions of governance quality index (dimensions of accountability, political stability and absence of violence/terrorism, government efficiency, regulatory quality, control of corruption, rule of law) on financial sector development are estimated using a quantile panel regression approach. Reason for using this technique is based on the argument that impact of governance quality is conditional on existing level of financial development and that sovereign financial development policies should be adjusted in countries with low, medium, and different levels to be effective. The empirical estimation based on quantile regression showed that overall governance quality index and its different dimensions have positive and significant effects in most quantiles. Furthermore, in most cases, the impact of governance quality is greater in magnitude in the higher quantiles. The empirical findings of this study show that differences in improvement of governance institutions explain differences between countries in terms of financial sector development. Based on conclusions drawn from findings; it is suggested that authorities should prepare groundwork for development of financial systems by expanding urbanization and facilitating entry into global village.

Abstract Innovation, one of the most important factors of development, has a special place in today's societies. Special science and technology zones are associated with physical buildings of high-tech activities and many relationships created in the environments with universities, research and industry. One of the important features of innovation region is creating an attractive living environment and improving the quality of life in the area. The innovation region of Yazd province has many advantages due to the defined centers. The dispersion of the centers of the region, the lack of necessary attention to the potentials and the vacuum resulting from the lack of complete clustering of the region are a major issue facing regional planning. The present study has attempted to assess the clustering capability of the centers of the innovation region of Yazd province and the degree of differentiation and commonality of these centers. The research is of an applied and descriptive-analytical type, which uses document study and field study tools to collect data about the area, and using the theme analysis method, the innovation cluster indicators were categorized, its accuracy was confirmed using the kappa coefficient, and using interviews, questionnaires, and the hierarchical clustering method to determine the possibility of clustering the product clusters of the area, and the reliability of the questionnaire was confirmed using Cronbach's alpha. The results obtained indicate that clusters have the ability to aggregate and become innovation clusters, and this process is logical until three clusters are aggregated together, and other clusters, such as the tile and ceramic cluster, the sesame product cluster, etc., also have the ability to become innovation clusters on their own.

Abstract Employment is a cornerstone of human existence, anchoring not only financial security but also mental well-being, personal identity, and social cohesion. In an era where economic systems are increasingly intertwined with technological advancements, the empowerment of women stands as a linchpin for achieving sustainable development and fostering inclusive growth. The rise of artificial intelligence (AI), heralded as a transformative force capable of boosting productivity by up to 40% and unlocking novel income streams, has sparked both excitement and apprehension. While AI promises to reshape economies by enhancing efficiency and creating new opportunities, it also raises critical questions about job displacement and equitable access to its benefits. Against this backdrop, this research embarks on an ambitious exploration of AI’s impact on women’s economic participation, a topic of profound significance given persistent gender inequalities that risk limiting women’s ability to capitalize on technological progress.The emergence of AI has accelerated debates about the future of work, with some envisioning a world of unprecedented prosperity and others warning of deepened inequities. For women, who have historically faced structural barriers in labor markets, the stakes are particularly high. AI’s potential to automate routine tasks and augment human capabilities could either dismantle these barriers or erect new ones, depending on how its benefits are distributed. Recognizing that gender disparities in economic participation slow the pace of development and diminish societal resilience, this study seeks to illuminate whether AI serves as a catalyst for women’s empowerment or a force that further marginalizes them. By delving into this question, the research aims to contribute to a more nuanced understanding of how technological revolutions can be harnessed to promote equity and justice.
This triadic approach not only broadens the scope of the findings but also underscores the importance of context in shaping technological outcomes. By benchmarking regional results against global statistics, the study reveals how economic, cultural, and institutional factors mediate the relationship between AI and women’s economic roles, offering insights that are both granular and universally relevant. Globally, the results paint a sobering picture. Unemployment emerged as a formidable barrier, with a statistically significant negative coefficient of -1.144 (p=0.047), indicating that rising joblessness markedly reduces women’s economic participation. This finding aligns with economic theory, which posits that labor market conditions are critical determinants of workforce engagement. In contrast, the technology-education index yielded a negligible and non-significant effect coefficient (-0.01, p=0.919). his lack of clarity may stem from the diverse economic landscapes and social norms across countries, which dilute the index’s global impact. The high and significant intercept (54.81, p=0.001) suggests a baseline level of participation influenced by unmodeled factors, such as cultural attitudes or policy frameworks. In Europe, a region synonymous with advanced infrastructure and progressive gender policies, the technology-education index showed a positive but non-significant effect (coefficient: 0.11, p=0.467). This suggests that while technology and education are abundant, their marginal contribution to women’s economic participation may be limited by market saturation or already high participation rates. Unemployment, with a negative coefficient of (-1.07, p=0.108), exhibited a borderline effect, likely due to smaller sample sizes or varied labor policies across European nations. The intercept (58.51, p=0.002) reflects a robust baseline participation rate, underscoring Europe’s structural advantages. In the Arab world, the findings were striking and cautionary. The technology-education index displayed a significant negative coefficient (-0.37, p=0.043), suggesting that increased access to technology and education may, paradoxically, correlate with reduced economic participation. This could reflect structural rigidities, skill mismatches, or cultural barriers that prevent women from translating technological advancements into economic gains. Unemployment also exerted a significant negative effect (coefficient: -0.49, p=0.040), reinforcing the labor market’s critical role. The lower intercept (27.26, p=0.005) highlights a more constrained baseline for women’s participation, shaped by regional socioeconomic realities. The study’s value lies in its methodological creativity and analytical depth.
The technology-education index represents a novel tool for dissecting AI’s socioeconomic impacts, offering a replicable framework for future research. The comparative analysis across global, European, and Arab contexts reveals the nuanced interplay of technology and gender, challenging one-size-fits-all narratives. By enriching the discourse on gender economics, this research provides policymakers with evidence to craft targeted interventions—whether by addressing unemployment globally, leveraging technology in Europe, or reforming labor markets in the Arab world. Ultimately, it inspires a vision of an equitable digital future, where AI empowers women to thrive as equal architects of progress.

Abstract On the one hand, crony capitalism provides the basis for the use of clean technologies and, as a result, the reduction of carbon dioxide emissions by allocating funds to government-supported industries, and on the other hand, it leads to an increase in carbon dioxide emissions by weakening competitiveness and disrupting the optimal allocation of resources. This article aims to analyze the effect of crony capitalism on carbon dioxide emissions in a selection of OPEC countries during the period 1996-2023 using the PQARDL method. The results show that in the short term, crony capitalism has led to a reduction in carbon dioxide emissions in the low and middle quantiles, while in the long term, it has led to an increase in carbon dioxide emissions in the middle and upper quantiles. On the other hand, fossil fuel consumption, gross domestic product, and industrial value added have had a positive effect on carbon dioxide emissions in the short and long term. Population had no effect in the short run in all quantiles but had a positive effect on carbon dioxide emissions in the long run. The results of the Wald test show that in the long run, crony capitalism, fossil fuel consumption, GDP, and population had an asymmetric effect and industrial value added had a symmetric effect on carbon dioxide emissions, but in the short run, the effect of all independent variables on carbon dioxide emissions was symmetric.

Abstract The study of the changes that have occurred in the Iranian stock market, as one of the most important sectors of the country's economy, has always been affected by various factors, including uncertainties in domestic and foreign economic policies. These uncertainties in the economic environment can significantly weaken the ability of a country's financial system to allocate resources optimally and support economic growth. On the other hand, one of the most important industries in the Iranian stock market is the petrochemical industry, which plays a fundamental role in the country's economy as a strategic industry and the mother and source of nutrition for other sectors. Hence, the aim of this study is to investigate the effects of global economic policy uncertainty along with the variables of exchange rate, inflation, and oil price uncertainties on the returns of petrochemical industry stocks in the Iranian stock market in different periods of high and low returns for this industry. In this regard, monthly data from the period 2009 to 2024 and the nonlinear Markov switching approach have been used. The results of the study indicate that global economic policy uncertainty has asymmetric effects on the stock returns of the petrochemical industry in low and high-return regimes. Moreover, exchange rate and oil price uncertainties only have significant effect in the high-return regime, but inflation rate uncertainty in the low-return regimes has a significant effect on the petrochemical industry in the Iranian stock market.

Abstract This study aims to analyze the growth trajectory of artificial intelligence (AI) technology and assess its impact on energy consumption in the United States, with the intention of deriving implications for Iran. To measure the level of AI development, two proxy indicators were employed: the number of AI-related patents and the share of AI patents in total registered patents. A logistic growth function was used to model the technology growth, given its suitability for describing saturating growth patterns. The findings indicate that both indicators exhibit rapid growth, with the midpoint of growth estimated to occur in 2024 for both cases. The saturation level for the number of patents is projected around 2050, while the saturation for the share of AI patents is anticipated by 2060. Subsequently, using two forecasting scenarios, the impact of AI growth on energy consumption was examined. The results of energy demand modeling, using a structural time series model, reveal that AI-related variables have a positive and significant effect on energy consumption. These findings offer valuable insights for AI investment strategies in Iran and highlight that the expansion of data centers and related infrastructure—currently in its early stages in Iran—could substantially increase energy demand.