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This study delves into the pivotal role of directors of microfinance banks in developing countries in implementing governance practices to ensure sustainability. As microfinance institutions strive to balance social impact with financial viability, effective governance emerges as a crucial factor for sustainable operations. The research investigates the strategies and frameworks adopted by directors of microfinance institutions to establish robust governance structures that promote long-term sustainability. Through comprehensive case studies and interviews with key stakeholders, the study identifies best practices and common challenges faced by microfinance bank directors in governance implementation. Key areas of focus include risk management, transparency, accountability, and stakeholder engagement. The findings highlight the critical importance of strong governance in mitigating risks, enhancing institutional credibility, and ensuring the alignment of financial and social objectives. Moreover, the research underscores the necessity for tailored governance models that consider the unique socio-economic contexts of developing countries. It reveals that adaptive governance strategies, which incorporate local cultural and regulatory nuances, significantly contribute to the sustainability and resilience of microfinance institutions. By bridging theoretical governance principles with practical implementation, this study provides actionable insights for directors seeking to enhance the sustainability of microfinance institutions. The implications of this research are far-reaching, offering valuable lessons for policymakers, practitioners, and academic scholars. It emphasizes the need for continuous capacity building and the development of governance frameworks that can evolve with the dynamic landscapes of developing economies. Ultimately, the study contributes to the broader discourse on sustainable development by elucidating how effective governance can empower microfinance institutions to drive socio-economic progress in developing countries.

As the world grapples with the challenges of climate change, international cooperation and effective policy tools are crucial for reducing carbon emissions and achieving a sustainable future. This study uses a game-theoretical approach to investigate the negotiations between countries with high and low carbon dioxide emissions, with the goal of achieving zero carbon dioxide emissions by 2050. By fostering collaboration and understanding among nations, game theory provides a robust framework for addressing the complexities of global climate policy. Game theory provides a mathematical framework to model strategic behaviors in climate negotiations between high and low carbon dioxide-emitting countries. By analyzing the payoff functions, the Nash equilibrium strategies for emission reduction efforts are derived. The introduction of a carbon tax increases the marginal cost of emissions, leading to higher equilibrium efforts by both country groups. Simulation results indicate a significant increase in emission reductions with the tax, demonstrating the tax's effectiveness in incentivizing climate action and contributing to global mitigation efforts. This result highlights the potential economic benefits of carbon taxation, including innovation incentives and reduced emissions, which can drive sustainable economic growth and job creation. However, the study also acknowledges potential costs, such as impacts on economic competitiveness and distributional fairness, which must be carefully considered and addressed in policy design. This research offers valuable insights for policymakers, highlighting the importance of crafting carbon tax policies that maximize environmental benefits while minimizing adverse economic and social effects. By balancing these considerations, policymakers can develop more effective strategies that support both environmental sustainability and economic resilience.

As Islamic banks grow and evolve, pricing methods for their services have become essential to study and implement. This study highlights the significance of understanding the factors influencing Islamic banking service pricing in Algeria. The study aims to analyze how Islamic banks price their services, with a focus on cost, market, and value strategies. Additionally, it seeks to evaluate and recommend ways to enhance the current practices of banks operating in the national market. Algeria is experiencing rapid growth in Islamic banking, making it an ideal location to study this subject. The country is home to two Islamic banks, Al Baraka Bank and Al Salam Bank. Algeria was selected as a new market to allow the findings to be applicable to similar situations elsewhere. The research utilizes secondary data obtained from available information on Islamic bank service fees, comparing them with those of traditional banks. It also conducts financing simulations in both banks and compares them with the traditional theoretical framework. Data was gathered from various sources, including bank websites, annual reports, and previous studies. The research reveals that Algerian Islamic banks do not prioritize scientific methods in pricing their services. The results suggest that these banks operate within a traditional framework under the oversight of the central bank. The central bank's rules depend on the prices of services conventional banks offer. This shapes how customers perceive these banks as representatives of Islamic banking. Islamic banks can utilize the study's results to develop pricing strategies that are more effective and compliant with Islamic law. Regulators can utilize these findings to formulate enhanced policies to bolster the Islamic banking sector. The results also assist researchers in delving deeper into the realm of Islamic banking service pricing. This study refutes the hypothesis that Algerian Islamic banks have enhanced the efficiency of their service pricing by adopting models in line with Islamic finance principles, such as profit-sharing, while considering market conditions and service value. They should embrace more pragmatic and beneficial pricing strategies that align with Islamic law, cater to customer needs, and enhance their competitiveness and value in the national banking market.

This article provides an in-depth analysis of the price dynamics and market prospects of Ethereum, the second-largest cryptocurrency by market capitalization. As blockchain technology and cryptocurrencies increasingly integrate into global financial systems, understanding the factors influencing Ethereum’s price becomes crucial for investors, developers, and researchers. The study uses daily price and volume data from an extensive dataset spanning from 2016 to 2023, focusing on the year 2022 to analyze trends and relationships between Ethereum’s price, market volume, and time. Employing correlation and regression analyses, the study aims to identify key patterns, with a focus on understanding how these variables interact within the volatile cryptocurrency market. The methodology centres on refining the data to ensure accuracy and integrity, including the removal of outliers and verification of variable distributions. Correlation analysis was conducted to explore the relationships between price, volume, and time. Regression analysis further assessed the impact of volume and temporal factors on Ethereum's price, using heteroskedasticity-consistent standard errors to address market volatility. The model's robustness was validated through statistical significance tests, and visualizations were used to present data trends and relationships effectively. The findings reveal that Ethereum experienced substantial volatility in 2022, characterized by a general downward price trend. The study identified a weak inverse correlation between price and trading volume, suggesting that periods of higher trading activity often coincide with lower prices, possibly reflecting market corrections or sell-offs. The regression analysis indicated that time is a significant factor in Ethereum’s price dynamics, with a strong positive correlation between the observation order and price, highlighting a clear downward trend over the year. The model demonstrated a high explanatory power, with an Adjusted R-squared of 83.94%, indicating that the selected variables effectively capture the variance in price. The discussion places these findings within the broader context of market developments, including technological shifts like Ethereum 2.0, regulatory changes, and macroeconomic factors that shaped the price movements. The inverse relationship between volume and price underscores the impact of trading behaviour on market sentiment, while the downward temporal trend aligns with the overall market downturn seen in 2022. Despite short-term negative trends, the analysis underscores Ethereum’s long-term potential, given its leading role in decentralized finance, non-fungible tokens, and blockchain innovation. This research remains highly relevant as it addresses the interplay of technical, market, and macroeconomic factors in shaping Ethereum’s price and market prospects, providing a framework for understanding its future trajectory within the evolving cryptocurrency landscape.

This article examines the impact of content personalization on customer engagement in the Algerian e-commerce sector. By analyzing data from 70 e-commerce stores operating in Algeria between January 12, 2023, and October 10, 2023, the study highlights the importance of personalization strategies in enhancing customer experiences and driving sales. The research employs a mixed-method approach, combining quantitative data analysis of website metrics with qualitative insights from customer surveys, to provide a comprehensive understanding of the effectiveness of personalization. The findings reveal a growing adoption of data collection methods, particularly website analytics (86%) and customer surveys (75%), which reflect a heightened awareness among Algerian e-commerce businesses of the need to track and analyze customer behavior. The research identifies a higher-than-average bounce rate (32%) compared to global standards (26%), suggesting technical and behavioral challenges that affect customer retention. Similarly, the average click-through rate for Algerian e-commerce websites (2.5%) is slightly below the global average (3%), indicating a need for building trust and credibility in the online shopping environment. The study underscores the significance of addressing these challenges by improving website performance, simplifying payment processes, and leveraging direct customer feedback to align offerings with customer preferences. Personalized content, derived from robust data analysis, is shown to enhance engagement by creating relevant and meaningful customer experience. The article provides valuable insights into the Algerian e-commerce market, outlining both opportunities and challenges. The emphasis on personalization, trust-building, and a customer-centric approach is critical for businesses aiming to thrive in this evolving landscape.

This study examines the determinants of credit risk in Nepalese commercial banks, emphasizing macroeconomic and bank-specific factors. The study utilizes a random effects regression model to investigate the impact of various factors on non-performing loans using panel data from 10 commercial banks in Nepal from 2013–2022. The study's theoretical framework draws on established economic theories, including Kalecki's business cycle theory and Diamond & Dybvig's banking theory. It aims to contextualize the relationship between credit risk and various influencing factors. The theory sets the stage for analyzing credit risk determinants in Nepalese banks. The findings demonstrate that non-performing loans are significantly and positively associated with bank size and return on assets, whereas asset quality and bank age have a negative and significant impact. The capital adequacy ratio exhibits a positive but insignificant impact. Among macroeconomic variables, the inflation rate has a positive and significant impact on non-performing loan, whereas real gross domestic product growth reveals a positive but insignificant relationship. These findings are of utmost importance for bank managers and policymakers in Nepal, as they provide valuable insights to enhance credit risk management practices and maintain financial stability in the banking sector.

Global Financial Technology adoption grew from 33% in 2017 to 64% in 2019, and in Nepal, Fintech users surged by 207.41% from 6.48 million in 2020 to 19.92 million in 2023, significantly influenced by the COVID-19 epidemic. Despite numerous studies on Financial Technology adoption globally, research on drivers of adoption intention, particularly incorporating mediation and moderation effects across various sectors of urban areas of Nepal, remains limited. Thus, this study examines the drivers of intention to adopt Financial Technology among urban Nepalese in Kathmandu Valley using the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology. The study employs a descriptive and explanatory research design to thoroughly examine the factors influencing the intention to adopt Financial Technology services. A non-probability sampling technique, specifically convenient sampling, was used to gather data from 360 users of Fintech services through a structured questionnaire administered via the Kobo Toolbox. Data analysis was conducted using Structural Equation Modeling with Partial Least Squares version 4.1.0.1. The findings indicate that effort expectancy, trust, and perceived usefulness directly influence the intention to adopt Fintech services. In contrast, security and privacy, and social influence affect adoption indirectly through perceived usefulness. Furthermore, effort expectancy partially impacts adoption through perceived usefulness, but perceived trust only directly affects adoption. Moreover, the education level moderates the impact of trust and social influence on adoption. In contrast, the effects of security and privacy, and effort expectancy are not influenced by education. The study offers vital insights to regulators, policymakers, providers of Financial Technology services, and BFIs as they should prioritize initiatives that enhance trust, effort expectancy, and perceived usefulness of Fintech services.

The management of socio-economic infrastructure projects in developing countries, including roads, bridges, tunnels, railways, ports, airports, dams and others, presents multifaceted challenges, particularly in environments marked by complexity and uncertainty. Despite the efforts of governments in these countries, these types of projects still face numerous risks, including political, technological, regulatory, financial, and market risks. The objective of the study was to examine the practices related to the problem of the decision-making process and risk assessment in the management of socio-economic infrastructure projects in developing countries, focusing on the example of the Algerian experience. This research used a qualitative analysis of the decision-making process through 15 semi-structured interviews conducted with representatives of various institutions and administrations responsible for supervising the East-West highway project in Algeria and several focus groups conducted or observations noted at the meetings where the author participated as a principal engineer at the Ministry of Public Works (project owner) during the different phases of the implementation of this mega-project. This made it possible to carry out a global assessment of current practices and to identify the major risks that can impact the decision-making process to improve the management of socio-economic infrastructure projects in Algeria and also in developing countries. The results of the study reveal the risks related to the complexity of the external and internal environment of the projects, in which among the 13 major risks identified, 61.54% have a high criticality, 30.77% have a medium criticality, and 7.69% have a low criticality. The results show that several important aspects need to be improved, including: 1) strengthening financial stability; 2) political risk mitigation; 3) implementing economic stability measures; 4) clarifying contractual aspects; 5) promoting cultural sensitivity and communication; 6) improving cost and quality control measures. This study provides valuable guidance to governments, businesses, managers, and other individuals or groups interested in promoting the management of socio-economic infrastructure projects in developing countries.

This paper presents a bibliometric analysis examining investment patterns in diverse economies and their relationship with global financial transformations. The study spans from 1964 to 2024, utilising data from the Web of Science (WoS) and analysed with R Studio and CiteSpace to identify trends and shifts in academic focus on investment strategies. A dataset of 1595 articles from 554 sources was processed, revealing key trends and shifts in investment patterns across different regions. The research highlights a notable rise in academic interest since 2015, with an 8.46% annual growth rate in publications. Methodologically, thematic evolution and network visualisation techniques were used to track collaboration patterns and emerging topics. For instance, 40.94% of the articles involved international co-authorship, emphasising global interest in investment dynamics. The study reveals critical insights into foreign direct investment (FDI) trends, particularly in developing and transitional economies, and how various global financial events influence investment behaviours. The average citation rate of 2.7 per article further underscores the significance of this field. The analysis confirms that investment patterns are crucial to understanding global economic transformations, providing a foundation for policymakers to craft economic strategies aimed at promoting balanced and sustained investment growth.

The real estate market in Ukraine, particularly in Kyiv, has experienced significant fluctuations due to the ongoing conflict and associated economic challenges. This research focuses on forecasting trends within the market, with a specific emphasis on price dynamics and the factors influencing these shifts. The actuality of this study stems from the pressing need to understand how the war, macroeconomic instability, and demographic changes impact real estate demand, investment patterns, and property prices. Given the rapid shifts in market dynamics and the complex interplay between economic variables, accurate forecasting is crucial for stakeholders such as investors, policymakers, and analysts. The methodology of this study combines traditional and advanced analytical tools to provide comprehensive and accurate forecasts. A dual-approach forecasting model was employed, using both the Brown-Mayer method implemented in Excel and advanced functionality provided by Statgraphics software. The Brown-Mayer method, which relies on exponential smoothing, allowed for the analysis of basic trends and seasonality in the time series data. Statgraphics, with its capacity to consider complex changes in market dynamics, provided more precise forecasts. The study involved data preparation, anomaly detection, correction, and checks for stationarity to ensure that the forecasts were not distorted by irregularities or missing data. Data were derived from key indicators like the Ukrainian Index of Retail Deposit Rates (UIRD3M), price changes in construction, the National Bank of Ukraine's key interest rate, and the average prices of primary real estate in Kyiv from 2018 to 2023. The findings indicate that Statgraphics was more accurate in forecasting real estate trends in Kyiv than the Brown-Mayer method. The confidence intervals generated by Statgraphics aligned closely with observed price trends, while the Brown-Mayer method showed a larger deviation due to its simpler approach to trend smoothing. The study revealed that external factors such as war-induced economic instability, high interest rates, inflation, and currency devaluation slowed the growth rates of real estate prices, particularly in urban centers like Kyiv. Moreover, the demand for real estate shifted towards rental properties and commercial spaces, particularly warehousing, reflecting changes in business operations and population migration to safer regions. The discussion emphasizes the importance of employing multiple methodologies to enhance forecast reliability. The research underlines that while simpler methods like the Brown-Mayer model are useful for general trends, advanced software tools like Statgraphics are more effective for accurate market prediction in volatile environments. Additionally, the study recommends a holistic approach to future forecasting models by incorporating a wider range of variables and indicators. This would improve model robustness and predictive power, particularly in the context of geopolitical and macroeconomic disruptions. This study contributes to the understanding of real estate market forecasting, providing valuable insights for stakeholders aiming to navigate the complexities of a rapidly changing market landscape in Ukraine. The research highlights the need for adaptive forecasting methods that can account for market volatility and external shocks.

This article addresses the critical issue of private benefits in corporate governance, focusing on how executives or controlling shareholders exploit their positions for personal gain, often at the expense of shareholder value and corporate performance. This issue is highly relevant, as it directly impacts the alignment between executive and shareholder interests and can lead to inefficiencies in corporate governance. The primary purpose is to examine the various forms of private benefits, such as excessive compensation and self-serving strategic decisions, and to explore governance mechanisms that can mitigate these practices. The choice of private benefits as the research object is justified by their widespread and detrimental impact on corporate performance and sustainability. This article employs conceptual analysis, grounded in agency theory, to investigate how performance-based compensation, independent audit committees, and increased transparency can reduce the extraction of private benefits. Drawing on key studies, it analyzes the ways in which these governance mechanisms align executive actions with long-term corporate goals. The main findings reveal that private benefits manifest in forms like excessive compensation and biased strategic decisions, undermining long-term performance. Strong governance frameworks, including performance-based pay and independent oversight, are essential in curbing such behaviors. The results of this article have practical applications for corporate boards, regulatory bodies, and governance consultants. They can be used to improve governance policies, ensuring that executive compensation and strategic decisions are in line with sustainable corporate practices, benefiting both shareholders and the broader business ecosystem.

The study aims to investigate the role of Islamic real estate investment funds in stimulating the Saudi economic market. The study focuses on the performance of these funds from 2018 to 2022, assessing their contribution to the wider Islamic capital market. To achieve its objectives, a descriptive and analytical approach was used, which included the collection and analysis of data related to Islamic investment funds. This approach has made it possible to conduct a comprehensive study of the global evolution of these funds and their economic performance indicators. The study also included a literature review to contextualize its findings within existing research. What distinguishes this study from previous research is its special focus on the Saudi context and the detailed analysis of Islamic REITs as a distinct financial instrument. While other studies have explored Islamic finance extensively, this research focuses on the unique characteristics and performance metrics of Islamic Real Estate Investment Trusts, providing a more accurate understanding of their impact on the financial market. The main results of the study indicate that Islamic investment funds effectively attract inactive savings and direct them to productive economic activities, and thus contribute to the real investments that are in line with Islamic principles. In addition, the research highlights that Islamic real estate investment funds gain investor confidence, and often provide returns that exceed the averages of the market. The size of the assets of these funds significantly affects the measures of their performance, which confirms their potential as applicable investment options. In general, the study concluded that Islamic real estate investment funds play a crucial role in enhancing trading activity and stimulating the Saudi economic market, especially during periods of economic recession.

The global outbreak of COVID-19 in 2020 became unprecedented and sent shockwaves through financial markets worldwide. This study investigates the impact of the pandemic on the performance of the U.S. financial market from March 1, 2020, to April 14, 2022. Utilizing Bai and Perron’s (1998) least squares with breaks during this period. The study’s test findings validate the existence of seven structural changes, signifying the occurrence of eight effects of independent factors on the S&P 500 index. The empirical findings demonstrate a substantial influence of COVID-19 pandemic on the performance of financial markets. Specifically, the impact of the number of COVID-19 cases and new fatalities on financial market performance, exhibits variations in terms of direction, nature, depth, and level. Based on an analysis of the structural changes, it can be inferred that the initial period exhibits the most pronounced negative impact on the number of new COVID-19 cases. Subsequently, the direction and nature of this impact undergo a transformation from the second to the eighth periods. Specifically, the impact of the number of new COVID-19 cases becomes positive in the second, third, sixth, seventh, and eighth periods, gradually diminishing until it reaches its lowest levels of impact in the eighth period. The research further identifies a detrimental impact on the occurrence of new fatalities. However, the periods spanning from the third to the fifth period exhibit very modest levels of influence, which then transition into a beneficial effect during the fifth period. Moreover, the research reveals that the impact of mortality rates on the performance of the United States stock market was greater than that of COVID-19 cases across all periods linked to structural changes. Additionally, the exchange rate of the dollar has a consistent and favorable impact, and the real interest rate has a pronounced negative impact, which gradually reduces over time and eventually transitions into a positive value by the eighth period.

Advances in renewable energy technologies, particularly in solar, wind, energy storage, and grid integration solutions, are accelerating the growth of in startups in this sector. Despite the promising outlook, renewable energy startups face several risks, including technological, regulatory, financial and market risks. The article carries out a bibliometric analysis of scientific publications related to the problem of investment and risks associated with the development of entrepreneurship and start-ups in the field of renewable energy. After multi-level filtering of the dataset, the research base consists of 82 publications by 232 scientists for 2005-2023, indexed by Scopus, and the analysis tools used are Biblioshiny and Excel. In 2005-2016, the number of publications grew annually at a rate of 10.47%, with peaks in 2006, 2007, and 2016; in 2017-2023, the number of papers increased (the dependence is described by a third-degree polynomial trend). The article examines 3 different types of Three-field plots in the topic of the investments and risks of the startups and entrepreneurship in renewable energy: 1) “References - Authors – Keywords”, 2) “Countries - Institutions – Authors”, 3) “Authors - Sources – Keywords”. A quantitative and qualitative analysis of the scientific journals that make the largest / periodic but noteworthy / minimal contribution to the dissemination of knowledge in this area was carried out, the top 10 authors and papers were analysed by the levels of local and global influence, the most powerful research networks (based on the results of the analysis of joint citations) were identified both in terms of authors and countries, and the leading countries were identified in terms of the volume of research output of their scientists and the intensity of citation of these works. Building clouds of the most used keywords allowed us to identify priority thematic areas of research, as well as to analyse the structural and logical relationships between different thematic blocks in the research landscape. With the help of multiple correspondence analysis (factorial analysis) and longitudinal thematic map analysis, the scientific landscape in this area is clustered and evolutionary changes and interdependence of individual topics are identified.

This study examines the impact of net interest margin, non-interest income, non-performing loans, and Political Stability Index on the banks’ profitability regarding return on assets in developing Asian countries, focusing on how political stability affects the bank’s profitability. The secondary data from 14 developing countries used in this study are collected from the World Bank and World Financial Studies Report. The dataset includes 154 data points spanning from 2012 to 2022, focusing on 14 underdeveloped countries of Asia. Exploratory and analytical research designs are utilized. Data are analyzed by using EViews 12. Econometric tools such as descriptive statistics, correlation analysis, panel unit root testing, Fisher-Johnsen combined co-integration test, panel vector error correction model, and Wald test investigate the relationship between response and predictor variables. The net interest margin, non-interest income, non-performing loan, and Political Stability Index are jointly integrated to determine the bank’s profit of developing countries of the Asia continent. Interest margin, non-interest revenue, non-performing loans, and the Political Stability Index all show a 38.6 percent variance in bank profit. It has been discovered that for every unit that rises in net interest margin and Political Stability Index, the bank profitability of developing Asian countries increases by 0.4867 and 0.2221 percent, respectively. Non-interest income has little bearing on the profitability of banks. Meanwhile, non-interest income exhibits minimal influence, suggesting a need for a strategic focus on interest margin enhancement and fostering political stability to optimize banking sector profitability in the region.

This study examines the influence of macroeconomic indicators on nonperforming bank loans. This research focuses on the period from 2010:1Q to 2019:4Q to capture significant trends and fluctuations in the economy. Data for receivables to be liquidated as a proxy for nonperforming loans, the consumer price index as a proxy for inflation, total private consumption expenditures as a proxy for economic activity, gross domestic product and total (private) fixed capital expenditures as proxies for economic growth are analyzed using the ARDL bound test, FMOLS, DOLS and VECM Granger methodologies. This study addresses several key questions. First, it examines how the receivables to be liquidated relate to changes in total private consumption expenditures (LNPCE). The findings indicate that higher LNPCE decreases the ability of receivables to be liquidated in both the long run and short run. Second, it explores the impact of gross domestic product (GDP) fluctuations on the amount of receivables to be liquidated, revealing that a higher GDP increases the amount of receivables to be liquidated in both the long and short run. Last, the study assesses the extent to which changes in the consumer price index (CPI) influence the receivables to be liquidated, finding that a higher CPI increases the receivables to be liquidated in the long run.

The aim of this study is to investigate and evaluate the impact of public spending on inflation in Algeria from 1973 to 2022. The data used are obtained from the official website of world Bank (WDI) and the Finance Ministry of Algeria. This study is conducted by applying the Auto-Regressive Distributed Lag model (ARDL)-(bounds testing approach) using eviews13 software. The time series of the data were subjected to statistical tests by applying the Augmented Dickey-Fuller (ADF) test. The cointegration tests were also applied for a common relationship and the Model Stability: The Bounds Test for confirming the existence of a stable long-term relationship, the Breusch-Godfrey serial correlation LM test to test the absence of serial correlation, Test Breusch-Pagan-Godfrey to test the Heteroskedasticity; and the CUSUM and CUSUM Squares test for the stability of the model as well as the estimation of the model’s short- and long-term parameters. The results obtained confirm the hypothesis posed in the introduction on the existence of a cointegration relationship between public expenditure and inflation the indicate that there exists a cointegration relationship between public expenditure and inflation, such that a 1% increase in public spending leads to a 0.23% rise in the inflation rate. It is important to mention that this percentage is relatively low compared to the short term, having reached 2%. As regards the other control variables, we found a positive and statistically significant correlation between the inflation rate and the percentage of broad money to GDP and the percentage of imports to GDP. However, we found an inverse relationship between the inflation rate and GDP per capita at constant 2015 prices, which serves as a measure of inverse economic growth. Based on these results, we can suggest Moving forward, policymakers in Algeria must prioritize measures aimed at curbing inflation while ensuring sustainable economic growth. This may involve reassessing public spending priorities, implementing effective monetary policies, and enhancing fiscal discipline. Furthermore, fostering economic diversification and promoting investment in sectors with high growth potential can contribute to reducing reliance on public expenditure as a driver of inflation.

Environmental reporting is a crucial tool for organisations to effectively communicate their environmental performance to stakeholders, foster transparency, and mitigate potential negative impacts. The study’s goal was to investigate environmental reporting practices in Ghana’s hospitality industry. The hospitality industry, despite its economic significance and environmental impact, is an excellent institution for environmental reporting studies due to Ghanaian problems and hospitality opportunities. This research employed a quantitative analysis of environmental disclosures from 192 hotels in Ghana. The researcher gathered data from annual reports, utility bills, and water bills, then conducted a systematic evaluation of these documents to gauge the extent and calibre of environmental reporting. The data was categorised into five groups using the Index of Environmental Disclosure (IED). Descriptive and inference statistics, such as measures of central tendency and dispersion, was employed to quantify and summarise the environmental disclosures. This allowed for a comprehensive assessment of present practices and the identification of opportunities for improvement in the Ghanaian hospitality industry. The study’s findings reveal the hostels’ environmental performance, with a high score of 75.52% for Environmental Policy and Initiatives. However, the study identified poor pollution management and reduction efforts at 38.44%. The Environmental Reporting Elements category scored 27.89%, which suggests more transparent reporting. The Environmental Audit and Compliance category scored 39.96%, indicating partial compliance. It emerged that a very modest positive correlation (r) of 0.12531 exists between hotel age and total disclosure, suggesting that as hotels age, their total disclosure increases marginally. The result shows significant variances in overall disclosure among the four hotel groups, with star ratings explaining much of the diversity: 2-star hotels have the lowerst mean total disclosure percentage, 3-star slightly higher, 4-star significantly higher, and 5-star highest. This positive correlation between hotel star ratings and environmental transparency shows that 4-star and 5-star hotels are more environmentally conscious. Sustainability in the hospitality industry requires environmental reporting to track progress, create standards, and drive continual improvement. This study offers valuable guidance to hotels, lawmakers, and other individuals or groups interested in promoting sustainability and transparency in the industry.

The 2008 Global Crisis had profound impacts on economies worldwide, prompting significant scrutiny of various institutional frameworks, including court systems. During this period, legal systems faced unprecedented challenges in addressing the ensuing turmoil. Courts were busy with cases related to foreclosures, bankruptcies, and financial misconduct. Due to the exposed weaknesses in regulatory oversight, reforms were made to improve accountability, transparency, and efficiency within judicial systems. Transition economies in Eastern Europe and Central Asia bore a significant brunt of the crisis and its subsequent reform endeavors. In this study, we evaluate the perspectives of Eastern European and Central Asian retailers on their court systems during and after the 2008 global crisis. We assess how many of them dealt with the legal system during and after the crisis, how quickly the cases moved through the court system, how fair and impartial the court was, and how successfully the court could enforce its rulings. To evaluate the impact of the global crisis on retailers’ views on the court system, we compare the crisis period to the post-crisis period. The World Bank’s BEEPSII and BEEPSIV surveys performed in Eastern Europe and Central Asia are used as our crisis and post-crisis samples. To compare the crisis period responses to the post-crisis ones, we use nonparametric tests (i.e. the Mann-Whitney-Wilcoxon and the Chi-square tests). Our results show that, after the crisis, fewer retailers went to court, when compared to the crisis period. This finding can be seen as positive. We also find that, after the crisis, retailers were more optimistic about judicial impartiality and case processing speed in their respective countries, compared to the crisis period. On the other hand, our results show that retailers’ assessments of the court’s ability to implement its rulings in these countries did not seem to change after the crisis. These findings have important policy implications. Policymakers can use these findings to take precautions before a global crisis hits. They will know that a global economic/financial crisis affects the volume of cases, courts’ fairness, and processing speed. Therefore, they can hire more employees to deal with the upcoming problems with the volume and the processing speed, and they can increase the scrutiny of the system to protect the system’s fairness.

This study aims to evaluate the effectiveness of the ASEAN regional trade agreement by comparing the growth rates of intra-ASEAN trade with those of the rest of the world as well as with major trading countries, China, the USA, the EU, and India. The objective of this research is threefold: To identify existing trade trends, to determine the underlying explanations for these trends, and finally, to compare intra-ASEAN trade trends with the inter-ASEAN countries’ trade trends. This paper takes a descriptive approach and dynamic panel GMM methods spanning the years 1990 to 2019. Between 2005 and 2019, growth rates among members of intra-ASEAN, Indonesia-Malaysia, Indonesia-Thailand, Singapore-Thailand, Malaysia-Philippines, and Philippines-Thailand, all decreased. Additionally, although the market share of imports and exports within ASEAN has decreased over time, the market share of imports and exports of inter-ASEAN has increased, especially with China and India. The results of descriptive analysis of inter-ASEAN trade openness are supported by first-differenced GMM and system GMM. This is the first study to examine historical intra-ASEAN trade trends and growth and compare them to inter-ASEAN trade trends and growth to determine whether AFTA has a greater impact on intra-ASEAN trade growth than on inter-ASEAN trade growth using updated aggregated data. This study sheds light on the fact that over the periods intra-ASEAN trade could not outperform inter-ASEAN trade by a significant margin due to trade diversity challenges and incomplete implementation of WTO regulations.

COVID-19 altered global economics activities during the pandemic period and still affects the stock returns. As worldwide resulted, this shift has changed the Pakistani stock returns activities. This study unfolds the impact of COVID-19 on stock returns frequency of pharmaceutical, power generation, technology and communication, and food sectors in Pakistan. To examine the relationship of above-mentioned sectors with stock returns, data were evaluated through event window that included the event dates of the 150-day and 60-day estimating period. COVID-19 has a considerable detrimental influence on stock returns during the post-event interval. The study findings showcase significant negative relationship with stock returns of the above-mentioned sectors. However, the results are contradictory during the second wave of coronavirus infection. Furthermore, the study also substantiates that COVID-19 has significantly affected the stock market performances of Pakistan. Still, the impact on the stock market performances was only for a short period, and it diminished in the second wave of COVID-19 spread in Pakistan. The findings contribute to the research on the stock returns of selected sectors and commodity market impact of a pandemic by providing empirical evidence that COVID-19 has spill-over effects on stock market. This result also helps investors in assessing the trends of the stock and commodity markets during the pandemic outbreak. Managers are encouraged to modify their strategies to maintain stocks of the firm for better performance under the direction of study findings.

The research investigates the formal and informal financing practices utilized by labeled startups in Algeria, emphasizing their essential role in economic development. Despite the recent dynamism observed in the Algerian startup ecosystem, these enterprises face substantial growth challenges due to limited access to financing, a critical factor for their success. To address this issue, a study was conducted involving 129 owners of labeled startups as of June 2023, employing a questionnaire for data collection. The data were analyzed using descriptive statistics and multivariate logistic regression. The findings confirm the prevalence of personal financing/love money as the dominant source of funding, with venture capital also identified as a significant financing method. Additionally, 28% of startups resorted to informal financing practices due to inadequate bank financing and difficulties in accessing other funding sources. The study also reveals that support structures have no significant impact on startup financing. This research provides valuable insights into the financing challenges faced by labeled startups and offers directions for future, more comprehensive research.

Despite the prevailing focus on the public markets, private companies represent approximately half of the world economy, if not more. This is a descriptive article presenting a summary of data and results from the 2024 Private Capital Markets Report, which is the product of the annual private capital markets survey. The annual survey was launched in 2009 and examines the behavior and trends of senior lenders, asset-based lenders, mezzanine funds, private equity groups, venture capital firms, angel investors, privately-held businesses, investment bankers, business brokers, limited partners, and business appraisers. Most of the survey panelists are based in the United States of America, but this is not a requirement. The data set also includes many panelists outside of the U.S. There was a total of 1,143 respondents represented in the 2024 survey. An empirical result of this article is that we test the theory that the recent return of warrants to mezzanine deals is associated with a higher interest rate environment. We find evidence supporting that association. These results may be helpful for academics and practitioners forecasting mezzanine activity and deal terms.

The proliferation of FinTech apps has democratized access to financial services, empowering individuals and businesses to take greater control of their finances. These apps have catalyzed financial innovation, disrupted traditional business models, and fostered competition in the financial industry. Moreover, FinTech apps have the potential to drive economic growth, promote financial literacy, and advance financial inclusion on a global scale. FinTech applications have played an important role in the creation of an arena where information is collected, stored, and processed to make the best decisions of investment. This has boosted the investment and increased the activity in capital markets when considered from the investors’ point of view. Capital markets have always been an important place for investors to invest in long-term securities with a maturity of more than one year. Primary as well as secondary markets are part of it. People invest in securities expecting a return in the form of capital gains and/or income. The role of FinTech applications in facilitating various investment decisions has also opened doors to retail investors in capital markets. Traditionally, retail investors have been overlooked because they are perceived not to have enough capital to invest, be too risk-averse, and be too costly to service. Both quantitative and qualitative data have been used. 150 online surveys were used to gather primary data. The outcome from this study showed a major shift in stock market investors towards digital connection due to various reasons. Some cultural and behavioral effects have been found among the investors for the financial transactions.

In the conditions of worsening global energy problems, financial instruments play a key role in reforming the energy market. They provide the necessary financial resources for the development and implementation of environmentally friendly energy technologies, aimed at supporting projects that reduce the negative impact on the environment, and contribute to attracting private capital to finance environmentally friendly projects. The purpose of this study is to analyze trends in research on financial instruments of the green energy transition. The article carries out a comprehensive bibliometric analysis of scientific works devoted to the problem of financing the green energy transition. The object of the research is the publications indexed by the Scopus database for 1954-2023. Research tools are programs for bibliometric data analysis Vosviewer, SciVal and CiteSpace. Based on the trend analysis of publication activity on the issues of financing the green energy transition, the key role of the Paris Agreement of 2015 in the growth of interest in these issues has been proven. Visualization of the most used keywords in scientific works on green energy transition financing allowed us to identify four clusters of keywords that characterize the concepts of green energy transition: the concept of "green construction", the concept of "green technologies and innovations", the concept of renewable energy, and the concept of "green of finance". Analysis of the frequency and number of citations of publications on green energy transition financing issues using the CiteSpace package made it possible to determine the TOP-17 keywords, highlight the period of their greatest citations, and carry out their clustering. Phrases most often used in publications include: finance, alternative economy, green bonds, green innovation, sustainable development, greenhouse gas emissions, sustainable finance, green credit, green economy, climate finance. Based on the analysis of relationships between keywords, seven clusters were identified: sustainable development, financing constraints, green bonds, green credit policy, green bonds, green economic growth, green economic recovery. The obtained results can be used by state institutions to improve financing strategies for green energy transition programs from the point of view of determining modern trends and key vectors of green finance development in the field of energy, analysis of the most effective financing tools, and identification of problems in the field of energy development.

Choosing an appropriate exchange rate regime is crucial for economic policy, particularly for developing countries seeking to establish robust macroeconomic frameworks to mitigate external shocks. However, such nations, including those reliant on oil and natural gas exports, often face challenges in selecting suitable regimes, exacerbated by a lack of traditional advice. The debate around this issue intensified in the aftermath of the 2014 oil price decline. In response, Jeffrey Frankel proposed the currency-plus-commodity basket (CCB) arrangement in 2017, blending the benefits of floating and pegging. This study applies the CCB system to Algeria, aiming to evaluate its impact compared to the current managed floating regime from 2001 to 2021, on indicators of internal (inflation rates) and external (change in foreign exchange reserves) balance using monthly data. Employing wavelet analysis and robustness tests, specifically quantile-on-quantile regression (QQR), the findings suggest that the CCB regime surpasses managed floating in maintaining monetary stability and achieving internal and external balance. Moreover, it provides greater flexibility and stimulates the domestic economy through its ability to stabilize terms of trade via active countercyclical monetary policy. Nonetheless, further discussion, adjustment, experimentation, and development of the proposed regime are warranted.

One of the primary concerns of the Iranian National Pension Fund is managing its investment portfolio. In this respect, the present study aimed to examine the long-term investment portfolio, the largest subset of which is V-sandoq. The analysis used the R2 connectedness approach proposed by Naeem et al. (2023) over the period from September 17, 2013, to September 22, 2023. The study focused on the immediate influence and susceptibility to influence of the stocks within the National Pension Fund. The results showed that, in terms of net influence and susceptibility, the stocks of Group 1 (i.e., Kechad, Foulad, Kegol, and Sheranol) were the most influential, transferring risk to the network. Conversely, the stocks of Group 2 (i.e., Shepas, Pasa, Shekabir, and Vebshahr) were the most influenced by the network. Therefore, risk is transferred from Group 1 stocks to the network, impacting Group 2 stocks the most. In network analysis, during a bear market with a threshold of -4%, there is a high degree of connectivity among the stocks in the portfolio. This suggests that portfolio adjustments are necessary under bear market conditions. Conversely, in a bull market with a threshold of +4%, there is no connectivity between the stocks, indicating that no portfolio adjustments are needed under such conditions.1.IntroductionIn recent years, Iran has consistently faced challenges with pension funds and the inability to generate adequate income to pay retirement salaries. With the number of retirees expected to increase in the coming years (particularly from the 1980s generation), effective management of the investment portfolio of the National Pension Fund’s subsidiaries has become increasingly critical. Many state-owned companies were transferred to the National Pension Fund to finance retired pay from their profitability. However, budget evidence indicates that over 80% of retirement salaries are still financed through the government budget. This underscores the importance and necessity of revising the investment portfolio of the National Pension Fund’s investment holdings. In this respect, the present study aimed to examine the portfolio management of one of the largest subsidiaries of the National Pension Fund, namely the Investment Company of the National Pension Fund or V-sandoq, over the period from September 17, 2013, to September 22, 2023. The study used the vector autoregression (VAR) model with time-varying parameters and R2 connectedness, as an immediate response, proposed by Naeem et al. (2023). The immediate impact analysis of variables on/from each other was chosen because any national, regional, or global event has immediate effects, and providing an appropriate response in portfolio management is of great importance.2.Materials and MethodsThe study employed the TVP-VAR algorithm and the Kalman filter introduced by Antonakakis et al. (2020), in conjunction with the approach proposed by Naeem et al. (2023). The key econometric structure of the TVP-VAR model is outlined below. For the sake of simplicity, it is presented in the form of a first-order VAR. Thus, the TVP-VAR model is as follows:(1) (2) Time-varying parameters and time-varying error variances are essential components for the generalized impulse response functions (GIRF) and generalized forecast error variance decomposition (GFEVD) developed by Koop et al. (1996) and Pesaran and Shin (1998). These components underpin the connectivity approach of Diebold and Yılmaz (2012, 2014). To obtain GIRF and GFEVD, the TVP-VAR needs to be converted to TVP-VMA by applying the Wold representation theorem. According to this theorem, GIRFs i j,t (K) at a forecast horizon K do not assume or depend on the ordering of shocks, providing a more robust interpretation of VAR models compared to standard IRFs, which are sensitive to the order of variables in the econometric system. The GIRF approach reflects the dynamic differences between all variables jjj. Mathematically, it can be expressed as Equation (3):(3) (4) Subsequently, GFEVD ψij,t(K)\psi_{ij,t} (K)ψij,t​(K) represents the unique contribution of each variable to the forecast error variance of variable iii, interpreted as the percentage impact of one variable on the forecast error variance of another variable. This can be expressed as Equation (5):(5) The criteria for GIRF and GFEVD can help determine how much variable iii is influenced by others and how much it influences others. Three metrics are used for this purpose.First, we must determine how much other variables in the system influence variable iii. This is obtained by summing the error variance shares for variable iii relative to variable jjj. The influence from others is then calculated using Equation (6):(6) Second, the impact of variable iii on others in the system is calculated through the measurement known as influence on others. This measurement is derived by summing the effects (error variance) that variable iii imposes on the forecast error variance of other variables:(7) The total connectivity index (TCI) is calculated based on the Monte Carlo simulations presented by Chatzanzinou et al. (2021). It demonstrates that the self-variance share consistently exceeds or equals all cross-variance shares. Since the average co-movement of the network is expressed as a percentage, which should be between [0,1], TCI needs to be slightly adjusted:(8) Finally, the TCI definition is modified to obtain pairwise partial connectivity index (PCI) scores between variables iii and jjj as follows:(9) 3.Results and DiscussionFigure 2 illustrates the temporal dynamics of stock influences received from other stocks. It shows the extent to which each stock has transferred or received risk from others. The stocks above the zero line indicate a net influence on the network, while those below indicate a net reception from the network during the examined period. Notably, Kechad, Foulad, Kegol, and Sheranol (Group 1) predominantly acted as influencers, transferring risk to the network. In contrast, Shepas, Pasa, Shekabir, and Vabshahr (Group 2) exhibited the highest reception from the network. Therefore, it can be inferred that external shocks transfer risk from Group 1 to the network, notably impacting the stocks in Group 2.It is crucial to recognize that this influence/reception patterns vary over time and exhibit significant fluctuations. Specifically, the chart shows that the influence/reception of stocks on/from the network decreased with the outbreak of the COVID–19 pandemic from January 19, 2021. Conversely, the disclosure of the letter regarding the increase in petrochemical feed rates on May 7, 2023 heightened the risk transfer from petrochemical stocks to the studied network. This underscores that external shocks do not uniformly affect the portfolio under review, necessitating separate examination of each. Figure1: Net Influence/Reception of Stocks on/from Each Other Source: Research findings4.ConclusionThe results of the long-term portfolio analysis indicated varying levels of interconnectedness influenced by economic, political, military, and health conditions—with the connectivity averaging around 45%. This reflects a high risk for the long-term portfolio. In terms of net influence and reception, Kechad, Foulad, Kegol, and Sheranol (Group 1) generally exerted influence by transferring risk to the network. In contrast, Shepas, Pasa, Shekabir, and Vabshahr (Group 2) predominantly received risk from the network. Thus, during external shocks, risk tends to shift away from Group 1 stocks, thus impacting Group 2 significantly. The outbreak of the COVID–19 pandemic on January 19, 2021 led to a decrease in the influence/reception of stocks on or from the network. Conversely, the disclosure of an increase in petrochemical feed rates on May 7, 2023 heightened risk transfer from petrochemical stocks to the studied network. Concerning the network analysis, there is a high degree of connectivity among the stocks in the portfolio during a bear market with a threshold of -4%. This suggests that portfolio adjustments are necessary under bear market conditions. In bearish markets, it thus becomes imperative to select stocks that have less connectivity. On the contrary, in a bull market with a threshold of +4%, there is no connectivity between the stocks, indicating that no portfolio adjustments are needed under such conditions. Hence, while the examined portfolio is optimal during bull markets, adjustments are essential during bear markets to mitigate risks associated with high connectivity.

The history of modern Iran is marked by numerous movements and revolutions, primarily aimed at achieving a proper balance between the state and society. Despite significant efforts, Iranians have not yet reached the ideal equilibrium. This research aimed to provide a brief overview of modern Iranian history and examine the pathways of progress for both the state and society. Utilizing an institutional analysis framework and the concept of institutional congruity, the study developed a new analytical framework to analyze the state–society interaction in Iran. A game theory approach was then used to examine various scenarios of the state–society interaction. The findings revealed that the depreciation, economy of scale, and instability of preferences are crucial factors in the dynamics between the state and society. However, the rate of time preference emerged as the most decisive factor, leading to three possible equilibriums: democracy, despotic Leviathan, and absent Leviathan.1.IntroductionAccording to Hegel, Iranians were historically the first people to establish a state, with their continuous history beginning with their empire (Hegel, 2004, p. 191). This continuous history narrates the dialectic between the state and society in Iran. The dynamics of this interaction can result in a stable equilibrium, an unstable equilibrium, or a fundamental disequilibrium. Given the unique nature of Iran, is it possible to achieve a balanced relationship where societal demands are met, and the state could provide ideal governance? How can we conceptualize the successive transformations and instability in the state–society interaction in contemporary Iran? Why did the Constitutional Revolution lead to Reza Khan’s dictatorship? Why did the secularization under Pahlavi II lead to the Islamic Revolution? How can we interpret this history of highs, lows, and turbulence? To address these issues, the present study aimed to explain the contemporary interaction between the state and society in Iran by using the institutional congruity framework and game theory. The goal was to present various possible equilibriums for Iran’s contemporary political economy. In other words, the research sought to elucidate the potential balance of the political economy in Iran based on the state–society interaction.2.Materials and MethodsIn the institutional balance between the state and society, a dynamic interplay is unfolding. Building on the model proposed by Acemoglu and Robinson (2023), this study attempted to derive various possible scenarios of the state–society interaction in Iran. Time is represented discretely, with the length of each period denoted as Δ>0. At time t, the variables from the previous period are as follows: where x represents the capacity of society, and s represents the capacity of state. At each point, society and the state are represented by a player. At any time, players simultaneously choose their investments , which determines their current capacity according to the following equations: For both the short-term state and society, various scenarios can be formulated regarding the presence or absence of depreciation and the oscillating nature of their inclinations. Consider the cost function for two players as follows: and 3.Results and DiscussionThe results suggest that beginning with low capacities for both the state and society can lead to a trajectory where a society starting with a weak state might directly evolve into one moving toward either a despotic Leviathan or an absent Leviathan. This dynamic is illustrated in the following phase diagram:Figure 1: First Scenario: The Short-Term Society In this scenario, it is evident that without depreciation, there is significant potential for Iranians to advance within a narrow corridor. However, as depreciation increases, this potential diminishes, eventually leading to a state of collapse (0, 0). Figure 2: Second Scenario: The Short-Term Society with Unstable Preferences The transformations in modern Iranian history show varying dynamics in both society and the state across different periods, reflecting differences in their types and levels of societal participation and efforts to achieve their respective goals. The high dynamics demonstrate that in a short-term scenario-assuming a depreciation rate of 0.1-if society is active (while the state is not), the predominant state tends towards anarchy. In the opposite scenario, the predominant state shifts towards a despotic Leviathan.Figure 3: Third Scenario: The Short-Term State The results of this scenario mirror those of the first scenario, highlighting the significant impact of depreciation on future possibilities. In contrast, the possibilities lean more towards a despotic Leviathan, whereas in the first scenario, the tendencies for a short-term society leaned more towards anarchy. Figure 4: The Short-Term State with Unstable Preferences In this scenario, similar to the second one, it is apparent that the efforts and engagement of both society and the state must be parallel and substantially proportional to each other. If either entity remains passive, the situation tends towards either pure despotism or anarchy.When it comes to time preference rates, it is crucial to consider the long-term, forward-looking perspectives of both the state and society. In the first scenario, the state is short-term and active with . Being active implies significant investment in the state capacity accumulation. In the second scenario, the state remains short-term and active with . These two situations were examined under two conditions: and .Figure 5: The Role of Time Preference in the Long-Run Equilibria of Iran’s Political Economy The above phase diagram effectively illustrates the significance of time preferences and their causal precedence in determining the state of the Leviathan in Iran. Even with depreciation and the short-term nature of both society and the state, achieving a stable equilibrium state (narrow corridor) is feasible when time preferences are appropriately aligned. Otherwise, depending on the short-term nature of either society or the state, the expected outcome will tend towards despotism or pure anarchy.4.ConclusionIn Iran, both society and the state must adopt a long-term rationality based on historical self-awareness to progress harmoniously. The primary challenges faced by Iranian society and the state stem from their short-term outlooks, as reflected in their time preferences. Whether society or the state prioritizes short-term goals, it becomes evident that depreciation significantly limits the possibility to enter the narrow corridor of stability. When both the state and society fail to coordinate efforts— whether in the short-term society or short-term state—it often leads to either pure despotism or anarchy. Despite the depreciation, economies of scale, and instability of preferences, it is the rate of time preferences that ultimately determines whether entry into the narrow corridor is feasible. Furthermore, this rate of time preferences dictates whether the equilibrium state leans towards a despotic Leviathan or an absent one, contingent upon the economies of scale achieved by both the state and society.

Iran’s economy has encountered significant challenges in recent years, with the government debt to contractors emerging as one of the most urgent issues. This situation has negatively impacted Iran’s monetary and banking system, leading to several adverse consequences such as increased funding costs for banks, higher loan interest rates, excessive money supply, and a reduced capacity for banks to provide loans. A proposed solution is based on credit easing and endogenous money, which involves settling the government debt to contractors by making adjustments on the asset side of the Central Bank’s balance sheet. However, the practical implementation of this policy depends on the use of Central Bank resources, which raises concerns about a sudden increase in the money supply and potential negative effects on other economic variables, especially inflation. This uncertainty has led to doubts about the feasibility of such a strategy. The present research aimed to examine the fundamental principles and prerequisites for adopting a credit easing policy in Iran. The study also used stock-flow consistent models to evaluate the potential outcomes of implementation of the policy. The findings indicate that settling the government debt to banks by using the Central Bank resources results in an expansion of the monetary base and money supply, an increase in real GDP, and a reduction in both inflation and interest rates compared to the baseline scenario.1.IntroductionIran’s economy has been facing various problems in recent years. One significant issue is the government debt to contractors, which has adversely affected Iran’s economy, particularly the monetary and banking system. The government’s failure to settle its debts with contractors results in contractors being unable to repay loans taken from banks, leading to an increase in the banks’ non-performing loans. This predicament has precipitated several adverse consequences, including higher funding costs for banks, increased interest rates on loans, an uncontrolled surge in the money supply, and a diminished capacity for banks to provide loans. To address this challenge, some economists, emphasizing endogenous money, look to the quantitative policies applied by central banks in advanced countries like Japan and the United States. They have proposed a solution grounded in credit easing, which involves settling the government debt to contractors by making adjustments on the asset side of the Central Bank’s balance sheet.2.Materials and MethodsIn this method, the government issues bonds to settle its debt with contractors and provides these bonds to the contractors. The Central Bank then purchases these bonds by increasing the bank’s reserves. Since the Central Bank does not directly transact with individuals, it uses commercial banks as intermediaries to facilitate the payments. Consequently, the money supply and the monetary base increase immediately. However, if the contractors owe money to the banks, according to the law of reflux, the newly created money will quickly disappear. This method is largely similar to the second type of treasury bonds used by the Iranian government in recent years. Implementing this policy can reduce non-performing loans, curb the growth of the money supply, and prevent the recognition of illusory profits. It can also lower the level of overdue loans and improve banks’ balance sheets. Additionally, it can reduce the banks’ debt to the Central Bank, thereby lowering the cost of money and reducing loan interest rates. Moreover, the reduction in interest rates can lead to increased loan demand and, consequently, future growth in the money supply.It should be noted that this policy leads to a change in the composition of the Central Bank’s assets, but it does not necessarily result in the growth of monetary base and money supply. However, since the policy relies on the use of Central Bank resources, concerns about a sharp increase in the money supply and potential adverse effects on macroeconomic variables, such as inflation, have always hindered its adoption. The present study used Stock-Flow Consistent (SFC) models to evaluate the effects of these policies on Iran’s macroeconomy. Having gained prominence since the 2007–2008 financial crisis, SFC models aim to integrate the real and financial sectors of the economy within a single framework. They help predict endogenous crises in the economy and enable modeling of the economy based on endogenous money. Therefore, SFC models were used to determine the effects of policies similar to credit easing to settle the government debt with contractors. The focus is on various economic variables, including the monetary base, money supply, and banks’ balance sheets in the monetary sector, as well as real GDP, economic growth, real consumption, inflation, and interest rates in the real sector of the economy.3.Results and DiscussionThe results indicate that settling the government debt to banks by using the Central Bank resources leads to an expansion in the monetary base and money supply, as well as an increase in real GDP and real consumption compared to the baseline scenario. However, the effect of this policy on economic growth completely dissipates after eight periods following its implementation, with the growth rate difference eventually tending towards zero. The graph below illustrates the difference in economic growth between the baseline scenario and the scenario where the government debt to contractors is settled using the Central Bank resources. Figure 1. Difference in Economic Growth: The Baseline Scenario and the Government Debt Settlement Scenario Source: The research analysisAccording to the model’s results, implementing this policy leads to a long-term decrease in inflation by 0.23 percentage points.Figure 2. Difference in Inflation: The Baseline Scenario and the Government Debt Settlement Scenario Source: The research estimationsAdditionally, the results indicate that the policy can lead to a 0.53 percentage point decrease in the interest rate. Figure 3. Difference in the Interest Rate: The Baseline Scenario and the Government Debt Settlement Scenario Source: The research estimations4.ConclusionThe model’s results indicated that the policy, despite increasing the money supply compared to the base scenario, leads to improved economic growth, reduced inflation and interest rates, enhanced bank balance sheets, and increased household welfare (via higher real consumption) compared to the baseline scenario.However, the method is recommended only to address the current problem in the present situation. The research results showed that the proposed policies guide the economy onto a better path than its current trajectory, but they are not a prescription for the government’s indiscriminate use of the monetary base. To improve conditions in the long term, the government needs a program to control its budget deficit and stop borrowing from banks and the Central Bank. According to the findings, borrowing from the Central Bank to settle outstanding debts with contractors is preferable to leaving these debts unpaid. However, the optimal approach is for the government to avoid needing to borrow from the Central Bank altogether.

Financial instability causes uncertainty and a lack of transparency in the market and decision-making processes, ultimately leading to reduced investment and economic growth. Additionally, economic shocks alter investors’ expectations. This study relied on the seasonal data from 1991/3 to 2021/6 in order to identify financial shocks and their impact on macroeconomic variables such GDP, the debt-to-GDP ratio, and financial instability. The Threshold Vector Autoregression (TVAR) model was used to analyze the data. The findings showed that fiscal policies (debt-to-GDP ratio) reduce GDP. Second, positive shocks from financial instability lead to a decrease in GDP and the debt-to-GDP ratio. In the first regime, positive fiscal policy shocks (increase in the debt-to-GDP ratio) leads to an increase in financial instability, while in the second regime, positive fiscal policy shocks can reduce financial instability.IntroductionFinancial instability leads to uncertainty and a lack of transparency in the market and decision-making processes, ultimately resulting in reduced investment and economic growth. Economic shocks also alter investors’ expectations, affecting the value of current assets and influencing both the financial and real sectors. During periods of financial instability, government debt management needs to adopt specific strategies. The simultaneous occurrence of a financial crisis and an economic recession signals a major downturn, and historical evidence shows a relative correlation between economic recessions and heightened financial market instability. In times of increased financial instability, the share of overdue loans rises, and negative market sentiments reduce the value of other financial assets. Disruptions in financial markets or a high level of overdue loans on banks’ balance sheets can lead to an economic recession by restricting credit flows to other sectors. Countercyclical fiscal policy can mitigate the reduction in the private sector demand by increasing government spending or cutting taxes, thereby compensating for the diminished credit flows from a weakened financial sector. Furthermore, government spending dependent on financial aid in weak sectors can improve economic sentiments and expectations, helping to strengthen the economy. However, financial development that facilitates easy access to existing financial resources can increase financial instability due to concerns about government debt sustainability. In this respect, the present study aimed to examine the nonlinear relationship (the effects of positive and negative shocks) between financial market instability, fiscal policy, and the production sector in Iran.Materials and MethodsThis study relied on using the seasonal data from 1991/3 to 2021/6 in order to examine the relationship between financial market instability, fiscal policy, and production in Iran. The Threshold Vector Autoregression (TVAR) model was used for the analysis. The primary version of the model used in this study is as follows:yt=[LGDPt,FSIt, DFt, LCPIt, LM2t]Due to its nonlinearity, the TVAR model can capture the varying magnitudes and directions of shocks that can affect how variables impact each other. Unlike the linear VAR model, where the impact of a negative shock is merely the opposite of a positive shock, the TVAR model allows for asymmetrical effects, where shocks of different sizes and directions can yield different outcomes. Results and DiscussionAccording to the findings, fiscal policies (debt-to-GDP ratio) decrease GDP, and positive shocks from financial instability lead to a decrease in both GDP and the debt-to-GDP ratio. Moreover, a positive shock in fiscal policy (increase in the debt-to-GDP ratio) increases financial instability in the first regime, but reduces it in the second regime. Also, negative shocks have opposite effects in both regimes. This suggests that in strong regimes with high liquidity, the debt-to-GDP ratio is lower, thus reducing the risk of instability. However, when fiscal policies such as tax cuts and increased government spending are pursued in a strong economy, financial instability may increase partly due to higher tax revenue and increased government spending; however, these policies are less profitable. In weak, low-cash regimes with unsustainable and income-dependent economies, the debt-to-GDP ratio is higher, leading to greater instability. Nonetheless, appropriate fiscal policies can prevent financial instability even in weaker regimes, promoting significant economic growth without increasing the risk of financial instability. The estimated TVAR model indicates nonlinear effects in the response of variables to exogenous shocks. Based on threshold effect tests in the first model (production response), the optimal threshold value (liquidity difference) is 0.4794. Periods where the threshold variable is less than 0.4794 are categorized as low regime, while other periods are categorized as high regime. In both regimes, a positive financial instability shock reduces fiscal policy (debt-to-GDP ratio). In the first regime, a positive fiscal policy shock (increase in the debt-to-GDP ratio) increases financial instability, while in the second regime, it reduces financial instability.ConclusionThe present study employed the TVAR model and the seasonal data from 1991 to 2021 in order to examine the relationship between financial market instability, fiscal policy, and production in Iran. Unlike the linear VAR model where effects of negative and positive shocks are symmetrical, the nonlinearity of the TVAR model shows that the size and direction of shocks impact how variables interact, thus leading to different outcomes. The findings revealed a nonlinear response of variables to incoming shocks. The TVAR model results, based on threshold effect tests in the first model (production response), identified an optimal threshold value of 0.04794. Periods below this threshold are categorized as low regime. The instantaneous response functions indicated that positive shocks in financial instability negatively impact GDP in both regimes. Generally, financial instability causes market uncertainty and a lack of transparency, leading to reduced investment and decreased economic growth. Additionally, positive shocks of fiscal policies (e.g., the debt-to-GDP ratio) decrease GDP in both regimes. The instantaneous reaction functions showed that a positive shock in financial instability reduces fiscal policy in both regimes. According to the results, a positive shock in fiscal policy increases financial instability in the first regime, while it decreases financial instability in the second regime.

In recent decades, the functioning of financial markets and banks has undergone significant changes. Many institutions resembling traditional banks have emerged outside the regulatory framework of the central bank, a phenomenon known as shadow banking. Instead of engaging in the traditional activities of conventional banks, shadow banking employs a more diverse set of resources and instruments, lead to changes in economic risks and influencing economic policies in various countries. The present study aimed to examine shadow banking and its relationship with traditional banking from 2011 to 2021 in Iran. It relied on the modeling of money demand functions within a system of simultaneous equations along with the Minflex Laurent flexible functional form. Moreover, the BEKK–GARCH model was used to address heteroscedasticity. The findings indicate that shadow banking has grown at an increasing rate over the past decade. According to the Morishima elasticity of substitution, conventional banking and shadow banking alternated in replacing each other during the 2010s. Additionally, the results showed that the spillover effect of short-term deposit shocks and fixed-income funds on Islamic bonds was positively significant, while the effect of shocks from fixed-income funds on cash and short-term deposits was not significant.1.IntroductionSince the early 1960s, a new phenomenon has emerged in the banking sector and has rapidly expanded, which involves the shift of intermediation from traditional banks to non-banks outside the supervision of the central bank (Buchak et al., 2018). These institutions, known as shadow banks, have grown rapidly in both developed and emerging countries over the past decades, playing a crucial role in the development of their monetary and financial markets (Łasak, 2015). However, shadow banking has also posed several challenges. Many financial experts attribute the recent global financial crisis to the complex structure of shadow banking, supported by a global consensus on the significant role of shadow banks in the 2007–2009 financial crisis (Pozsar et al., 2013; Lysandrou & Nesvetailova, 2014). Shadow banking presents both an opportunity and a challenge. While companies and households benefit from shadow banking as an alternative financial channel, maintaining financial stability in the market has become even more complex and challenging (Allen & Gu, 2020). In the present study, the term cash includes paper money, foreign currency, coins, traveler’s checks, and short-term deposits as liabilities of bank deposits. Fixed-income funds and commercial papers are considered the liabilities of shadow banks. The study is based on the hypothesis that substitutability or complementarity between bank services and shadow banks is a critical factor in the effectiveness of monetary policies. An explanatory framework was developed to examine whether the relationship between traditional banking services and shadow banking in Iran is complementary or substitutive.2.Materials and MethodsTo model the money demand function, the study used the Minflex Laurent flexible functional form within a dual approach encompassing both conventional and shadow banking, as well as demand systems proposed by Diewert (1974). Additionally, Barnett’s (2002) approach was employed to ensure the systematicity conditions of classical models, namely monotonicity, curvature, and positivity. The BEKK–GARCH model was used to address heteroscedasticity and estimate the model. MATLAB R2018b, Eviews11, and WinRATS10 were used estimate the theoretical models of the study.3.Results and DiscussionThe Morishima elasticity of substitution between different components of money demand showed that despite fluctuations in the level of elasticity, the elasticity of all components is less than one. Furthermore, since all elasticities are positive, the components act as substitutes for each other. Among the examined elasticities, the highest average substitution occurred with Islamic securities compared to changes in fixed-income funds, while the lowest substitution occurred with fixed-income funds compared to changes in cash. In addition, investigating the response to shocks in each component of money demand revealed several points. First, the reaction of assets to demand shock fluctuations was initially positive for cash, although for Islamic securities, this effect decreased after three periods or months. The reaction of cash fluctuations to cash shock was significantly greater and increased for all assets. Second, the reaction of each asset to short-term deposit shocks was positive but small, except for the case of cash in which it was slightly negative in the first and second periods. This reaction increased during subsequent periods in the case of short-term deposits themselves. Third, concerning the fixed-income fund shock, although it was negative in the first period, it became positive in subsequent periods. The shock related to Islamic bonds and short-term deposits maintained a stable positive trend, and shocks from fixed-income funds increased for three periods but had a decreasing but positive trend thereafter. Fourth, investigating the reaction of fluctuations to shocks in Islamic securities showed that-except for cash which had a positive increasing trend-the trend for the other three assets initially increased and then decreased.4.ConclusionThe results indicate that the demand for shadow banking services has gradually increased in Iran, aligning with global economic trends and the advantages shadow banks offer over conventional banks. Although shadow banks in Iran are perceived as competitors to conventional banks, studies show that the limitations imposed by unilateral policies in Iran’s monetary market have led many shadow banking activities to be conducted by institutions related to conventional banking. In fact, utilizing shadow banking capacities has helped establish stability in Iran’s conventional banking system. This finding aligns with the results of the Financial Stability Board (2013) and the related studies (Liu & Xie, 2020; Moshirian, 2014). According to these studies, many shadow banking services by conventional banks are carried out to bypass central bank regulations. Moreover, the findings of the present study on the substitution between conventional and shadow banking are consistent with the findings of Serletis and Zhou (2019), as contrasted to Lin and Li (2017), Górnicka (2016), and Noeth and Sengupta (2011), who view conventional and shadow banking as two complementary systems.

The negative correlation between an asset’s volatility and its return is known as leverage effect. This relationship is explained by the effect of a firm’s equity return on the degree of leverage in its capital structure. If this relationship holds, the increased volatility resulting from a fall in stock price should be comparable with the decreased volatility resulting from a price rise with the same magnitude, and this effect should also be persistent. Most research on the leverage effect has examined the relationship between the behavior of returns and return volatility. The present study aimed to examine the relationship between return volatility, returns, and the debt ratio. The data were collected from 22 biggest companies listed on the Tehran Stock Exchange for the period from March 2009 to March 2019. The value of debt in the capital structure of the selected companies was calculated using the Geske compound option pricing model. According to the results, the existence of an asymmetric effect on returns only during bearish market conditions, alongside the instability of this effect, indicates that the debt ratio cannot explain the behavior of returns and return volatility.1.IntroductionExtensive research on return volatility and its modeling reflects the considerable attention and importance this topic holds within various financial domains. The sheer number of scientific inquiries into volatility modeling and prediction underscores its significance in financial discourse, playing a pivotal role in both theoretical and empirical realms (Kambouroudis et al., 2021). Uncovering the influential factors affecting return volatility and gaining insights into their impact can contribute to a deeper understanding of return volatility. The leverage effect, which denotes the negative relationship between an asset’s return and its return volatility, suggests that as an asset’s return increases, its volatility decreases and vice versa. A common explanation attributes the divergent behavior of stock returns and return volatility to the debt ratio in a company’s capital structure (Aït-Sahalia et al., 2013). When a company’s value increases, assuming the debt value remains stable, the relative return on equity will rise more than the overall company return because the total stock value is less than the total company value. Therefore, equity in a company with a higher debt ratio will exhibit greater volatility compared to the overall company, with this difference depending on the equity ratio in the company’s capital structure. This relationship with the debt ratio also leads to a systemic and inverse change in equity return volatility relative to its own return. When negative stock returns lead to a decrease in equity value relative to the fixed amount of debt, the debt ratio increases, resulting in an anticipated increase in stock volatility in the future. Conversely, positive stock returns are expected to have the opposite effect. The market value of a company’s equity affects the value of its debt. This research aimed to examine the ability of debt ration to explain the observed leverage effect. Therefore, accurately estimating the debt ratio and the value of the debt is crucial. In this line, the present inquiry investigated the relationship between stock return volatility and the debt ratio in the case of companies listed on the Tehran Stock Exchange.2.Materials and MethodsThis study used the model proposed by Figlewski and Wang (2000) in order to investigate the leverage effect. A distinctive aspect of the current research lies in the calculation of the debt value and the debt ratio using the Geske compound options pricing model (Geske, 1979).The sample of the study consisted of 22 non-banking companies selected from the top 30 listed on the Tehran Stock Exchange. Seven banking symbols and one symbol with insufficient information were excluded from the analysis. Banking symbols were excluded due to the unique nature of the banking business, which significantly influences debt performance (Damodaran, 2013). Data on prices, number of shares, and debt structure for these companies were systematically collected from 2009 to 2019. The study relied on quantile regression as the analytical approach. Quantile regression is particularly robust in scenarios where errors deviate from a normal distribution or outliers are present in the data. This method allows for model estimation without being constrained by assumptions typical in ordinary regression, such as homoscedasticity and the influence of outliers on coefficient estimation.3.Results and DiscussionIf the leverage effect, characterized by the negative relationship between return volatility and stock returns, were solely due to returns influencing the debt ratio, one would expect this effect to be consistent across positive and negative returns. Additionally, assuming the effect of returns on the debt ratio remains stable over time, one would anticipate a stable effect on return volatility as well. The findings indicated asymmetric effects of returns on return volatility, with a notable difference between positive and negative returns. Moreover, over time, both the magnitude and significance of this effect diminish. Another objective was to explore the direct effect of the debt ratio on return volatility. Similar to the previous case, the data suggested differing effects of the debt ratio during upward and downward trends. When the debt ratio increases due to declining returns, there is a consistent relationship observed between return volatility and the debt ratio. Conversely, during upward trends, the relationship between the debt ratio and return volatility is inverse. Furthermore, in assessing the stability of the effect of debt ratio on return volatility, the coefficients of lagged debt ratios were not significant, with only the coefficient of the current period’s debt ratio showing meaningful impact over the study duration.4.ConclusionAccording to the results, if a leverage effect exists, it manifests primarily in bearish market conditions (associated with an increasing debt ratio), and this effect is not stable over time. Consequently, the debt ratio alone cannot fully explain the relationship between return behavior and return volatility.

One of the significant challenges in regional development is examining the role of local governments and their relationship with large local companies in income distribution. This challenge is particularly pertinent when large companies have national objectives, and most of their production capacity is capital-intensive and knowledge-intensive, but their operational area is locally focused on the user. The present research aimed to explore the role of the government and large local companies in income distribution. Khuzestan Province was chosen due to its unique characteristics in this regard. The study covered the period from 2006 to 2020, analyzing seasonal data using the generalized method of moments (GMM). The findings indicate that the government’s current and construction expenditures in the province have a negative and significant effect on the urban Gini coefficient. In contrast, the value-added variable of large industrial companies in the province has a positive and significant effect on the urban Gini coefficient. The results suggest that careful planning and coordination between large companies and provincial managers should be sought by adopting policies such as increasing local employment and training local workforce, thereby reducing dissatisfaction and income inequality in the province.IntroductionOne of the significant challenges in regional development is examining the role of local governments and their relationship with large local companies in income distribution. This challenge is particularly pertinent when large companies have national objectives, and most of their production capacity is capital-intensive and knowledge-intensive, but their operational area is locally focused on the user. Based on the available evidence, large companies in Khuzestan Province (e.g., oil, petrochemical, and steel companies), which are part of national entities, generate national income. However, the local population’s share of this income is small. Meanwhile, private companies in Khuzestan Province are under pressure to pay taxes. This has led to the perception among the people in the province that the presence of these national entities has resulted in a low local share of their income. In other words, the income generated by these companies flows out of the province, leaving the local population with a minimal share. In this respect, the present research aimed to explore the role of the government and large local companies in income distribution in Khuzestan Province during 2006–2020. Materials and MethodsThe primary research question is whether the government’s financial policies and the presence of large companies in Khuzestan Province significantly affect income distribution within the province. Using the generalized method of moments (GMM), the study relied on the seasonal data from 2006 to 2020 to address the research question. Results and DiscussionThe results indicate that government’s current and construction expenditures in the province have a negative and significant effect on the urban Gini coefficient. Conversely, the value-added variable of large industrial companies in the province has a positive and significant effect on the urban Gini coefficient. This suggests that the presence of large industrial companies has not only failed to reduce inequality but actually increased urban inequality in the province. The findings also show that both types of user investment and Berber knowledge are effective in reducing the urban Gini coefficient in Khuzestan Province. Additionally, the study found that air pollution in the province has a positive and significant effect on the urban Gini coefficient. This implies that increased pollution, caused by industrial activities, disproportionately impacts the lower classes as the benefits of these activities do not reach the lower-income population. Instead, these polluting industries impose negative external effects on the local population while contributing to increased inequality by introducing imbalances considering payments to national production factors. ConclusionAccording to the research results, the presence of large companies in the province has neither generated local benefits nor reduced income inequality in the urban sector. It is thus recommended that careful planning and coordination between large companies and provincial managers should be sought by adopting policies such as increasing local employment and training local workforce, thereby reducing dissatisfaction and income inequality in the province.AcknowledgementsWe express our gratitude to the Vice-Chancellor for Research Affairs of Shahid Chamran University of Ahvaz for his assistance in conducting this research.Conflict of interestThe authors declare no conflict of interest in publishing this articleFundingThis study is part of a research project related to industry between Shahid Chamran University of Ahvaz and the Management and Planning Organization of Khuzestan Province, financially supported by contract number 100z1310004 (971875).

The article is aimed at the current issues of using smart technologies and innovative approach during evolution and transformation processes in banking. The study identifies the special place of this topic for achieving a high level of efficiency and competitiveness of banks and characterizes the impact of the introduction of technological approaches on the customer base and its perception of banking products. The main functions of banking innovations in this area are analyzed and the justification of their feasibility at the present stage of economic development is provided. A number of the most promising technologies and approaches to banking activities are allocated, namely: contactless payment, digital wallets, biometric identification, person-to-person payments, collective financing, omnichannel banking, interaction with FinTech companies, blockchain, big data, artificial intelligence, smart machines, Internet of Things, behavioral banking, retail bank, application programming interfaces, multi-component bank, open banking, augmented reality, robotic automation, hybrid clouds. The relevance of the identified areas is proved based on their perception by analyzing the popularity of the identified topics in Google search queries using the Google Trends tool. The perception of smart technologies in banking by Internet users in the world and specifically in Ukraine is investigated, which gave grounds to conclude that there is a significant interest in them, and therefore the expediency of further study and implementation in the activities of banks. It is identified that the most perspective technologies are biometric identification, blockchain, Internet of Things, big data analysis, artificial intelligence, etc. Several technologies have been identified, namely, collective financing (crowdfunding), application programming interfaces (APIs) and digital wallets, which are less popular in Ukraine than in the world in general, and therefore require detailed research and study of the relevance of their application in the domestic banking market. Possible directions for further innovative development of banking institutions based on the use of smart technologies are proposed. Based on panel data for 60 banks of Ukraine for the period 2014-2022, the author analyzes the correlations between the indicators of the use of digital technologies and the financial performance of banks and builds regression dependencies of financial indicators of banks on the indicator of the number of electronic means of payment in active circulation. The theoretical value of the study is to identify the most promising smart technologies and innovative approaches to banking business in modern conditions. The practical value lies in studying the level of perception of high-tech innovations in the field of banking services by the active public and identifying further directions for the development of this process. We consider it advisable to direct further research in the context of a detailed study of the possibilities of applying the identified technologies in specific banking products or business processes.

The research makes an attempt at analysing the state of affairs of the electronic payment in Algeria and propose perspectives for future development in that regard. To attain this objective, the bank of Crédit Populaire Algérie (CPA) in Algeria was taken as a case study. The primary reason of choosing this bank was by virtue of its leading market share in the local market and many electronic services and payment cards in use. The bank data from 2016 to 2022 was collected to perform an analysis of the growth rate of electronic payment services and to carry out a forecast of these services using exponential smoothing. Hypotheses tests demonstrate with validity that in the upcoming years, the number of electronic payment services will considerably increase. First, the use of electronic payment in Algeria has increased due to consumers’ changing preferences and due to the necessity of practical and safe payment solutions. Second, the bank used as a case study has invested in the development of electronic payment by proposing e-payment solutions to its consumers. Finally, the future of electronic payment will be marked by an increase in the number of electronic services. The findings of the research highlight consumers’ changing preferences towards electronic payment and consequently all banks should invest in designing and executing strategies of electronic payment services. It is recommended that scholars could use the findings of this research and perform a benchmark with other banks in Algeria or banks in other MENA countries. Moreover, the number of years could be further increased to determine if the growth of these services is to increase, decrease, or stay constant.

Good corporate governance influences the capital structure adopted by a firm. Higher financial leverage increases a firm’s risk. This might result in a window-dressing of financial statements to maintain the value of the firm. The study examined the interaction between corporate governance, financial leverage, external audit quality, and their combined influence on the quality of financial reporting inside enterprises in Ghana. The extensive inquiry was conducted using a dataset consisting of 650 observations and encompassing the timeframe from 2009 to 2021 using SPSS Process version 4.2. The findings of this study revealed a significant inverse correlation between the size of the board and the level of compliance with International Financial Reporting Standards with a correlation coefficient of -0.056. With a correlation coefficient of 0.003, the analysis revealed that there is no linear association between Board Gender Diversity (BGD) and International Financial Reporting Standards. With regards to Independent Audit Committee with a correlation coefficient of around 0.068, the findings of the study indicated a statistically significant positive relationship between the presence of an Independent Audit Committee and the level of compliance with International Financial Reporting Standards. The study showed a negative correlation of -0.024 between Financial Leverage and International Financial Reporting Standards Compliance. The observed data suggests a notable and favourable correlation between Audit Fee and International Financial Reporting Standards Compliance with a significant positive correlation of around 0.157. The model employed in the study exhibited multiple R (R) of about 0.191, indicating a modest positive association between the predictor variables and International Financial Reporting Standards Compliance. The coefficient of determination (R Square) was 0.037, indicating that 3.7% of the variation in International Financial Reporting Standards Compliance can be attributed to the predictor variables in the model used for the study. Furthermore, the study revealed an unstandardized coefficient of -0.003 and a standardized coefficient of -0.078 for Board Size, 0.023 and 0.016 for Board Gender Diversity, 0.028 and 0.109 for the Independent Audit Committee, -2.152E-05 and -0.031 for Financial Leverage and 2.809E-08 and 0.156 for Audit Fee. The study again revealed a significant indirect effect through Financial Leverage (FL) on Board Size and International Financial Reporting Standards Compliance with bootstrapped results of 0.0001. On the contrary, the study revealed that Financial Leverage does not mediate Board Gender Diversity and International Financial Reporting Standards Compliance, Independent Audit Committee, and International Financial Reporting Standards Compliance with, an indirect effect of -0.0021 and -0.0009 respectively. With mediation through Audit Fee, the study showed significant indirect effects for all three independent variables. Board Size at 0.0000, Board Gender Diversity at -0.0016, and Independent Audit Committee at -0.0027. The findings from the direct effects study indicate that Board Size and Audit Fee have a notable influence on IFRS Compliance, hence affecting the quality of financial reporting. However, no concrete evidence was found to establish a link between Board Gender Diversity and Independent Audit Committee and IFRS Compliance. For the mediation effects, it was discovered that Financial Leverage played a role as a mediator in elucidating the connection between Board Size and IFRS Compliance. Furthermore, the Audit Fee variable served as an intermediary in clarifying the associations between Board Size, Board Gender Diversity, Independent Audit Committee, and IFRS Compliance. It is recommended for companies to give utmost importance to the principles of openness, accountability, and consistent monitoring of financial leverage. Moreover, the study recommends the allocation of resources towards high-caliber external audits as it plays a pivotal role in bolstering the precision and dependability of financial reporting.

This study aims to make theoretical and practical contributions by addressing stagnation in the context of digital transformation (DX) and proposing specific measures. Focusing on the banking industry’s skilled response to rapid changes to maintain and improve competitiveness, this study employs quantitative methods to investigate the expectations and assessments of Chinese financial service users regarding Internet banking. With a clear objective, this study seeks to contribute theoretically and practically by addressing stagnation in DX. Specifically, it focuses on the banking industry’s response to rapid changes, employing quantitative methods to assess and understand Chinese financial service users’ expectations of Internet banking. The results reveal that the prevalent use of payment services through mobile applications has significantly expanded the scope of financial services among citizens. Key factors driving innovation in the financial industry through fintech include close communication with consumers, service enhancement and sophistication and ensuring reliability. Privacy and the ethical use of personal information have been found to function as an indirect pathway that plays a vital role in socio-economic activities, acting as a critical element for the future development of the financial industry. These findings provide actionable insights for fostering innovation and development in the financial sector. The uniqueness of this study lies in its primary quantitative data analysis, which compares the prospects of financial services in China’s advanced DX market. It shows the path the banking industry should take, emphasising the simplicity of mobile applications and the high frequency with which vital components are used. Going beyond theoretical insights, this research is a practical guide for implementing specific actions in a real business environment. It provides valuable insights into the Chinese market and offers guidelines for the broader financial industry currently navigating the intense waves of DX, ultimately aiming for sustainable and effective DX.

This article is written for a general audience of economists, including those who have a novice understanding of this subject. China continues to become more important in the community of nations. In order\to promote further internationalization of China’s influence, major strategies are being pursued. The focus of this article is the implementation of the ambitious program of the Belt Road Initiative (BRI). Within China, this program is called One Belt One Road (Chinese: 一带一路; pinyin: Yīdài Yīlù) or OBOR for short. This is a global infrastructure development strategy adopted by the Chinese government in 2013 to invest in more than 150 countries and international organizations (World Bank, 2019). This article states that China benefits from the BRI and it was found that lower- and middle-income countries are more inclined to join the BRI, in comparison to high income countries This tendency is not 100 percent true. Simultaneously, there is the effort to increase the use of Chinese Renminbi (RMB) in transactions between all nations. (Chinese yuan is another phrase for RMB.) The Chinese RMB already has attained the status of reserve currency (Gentle, 2016). Of course, there is a lot of synergy between the implementation of the BRI and other means for increasing the international presence of China. This article asks the research question of does the BRI increase China’s international presence in the BRI? The answer is yes, considering the many countries, organizations and projects involved in the BRI. Tables in this article convey this information. This article may serve as a broad introduction to the BRI. The reader can thus move on to explore what other researchers have done on this issue.

Recently, the interest of researchers in the use of hybrid models in the process of analyzing model time series with fluctuations and forecasting fluctuations in financial time series has increased significantly. Hybrid ARMA-GARCH models were created for medium- and long-term forecasts of time series of financial market index prices: ARMA models are used to analyze their linear component, which is a combination of autoregressive models and moving average models, and GARCH models are used to analyze the nonlinear component. which are generalized autoregressive models that depend on the nonconstancy of variance models. Hybrid ARMA-GARCH models eliminate the weaknesses and gaps that exist in each group of models (ARMA and GARCH) separately, which increases their forecasting accuracy and reliability, so they have already been successfully applied to model and forecast daily stock returns for three standard indices in the USA. The purpose of this article is to investigate which of the hybrid ARMA-GARCH models is optimal for forecasting the return of the DAX index, which is the most important stock index of the German securities market. It is the German equivalent of the American Dow Jones Index, has been calculated since 1988 by Deutsche Börse AG and reflects the total return on capital of the largest stock companies listed on the Frankfurt Stock Exchange (currently 40; by 2021 – 30): calculated as a weighted average of capitalization of the value of Free Float share prices on the Xetra electronic exchange, and also takes into account dividends on shares, assuming that the dividend is reinvested in the share on which it was accrued. The database of this study consisted of the daily closing prices of the DAX index presented on the official website of the Frankfurt Stock Exchange during the period from 01.01.2018 to 09.30.2023 (altogether about 1,500 observations), the stability of the time series was assessed using Expanded Dickey Fuller Liquidity (ADF). The article proposes 7 hybrid models, from which the one that is best suited for modeling the volatility of the DAX index is selected. It is an ARMA (2,3)-EGARCH (1,1) model because it captures volatility and leverage effects on DAX returns and its expected returns more than other models. The selection of the best alternative from the developed array of hybrid models was carried out according to the following criteria: AIC (Akaike Information Criterion), BIC (Bayesian Information Criterion), H-QIC (Hannan-Quinn Information Criterion).

The reputation of auditing firms is of paramount importance in ensuring trust and confidence in financial markets. This article investigates the information dissemination model and its impact on the reputation formation of auditing companies, focusing on the choice between official sources (formal channels, corporate communications, regulatory disclosures, etc.) and word-of-mouth mechanisms (informal channels, client recommendations, corporate gossip, etc.). The research reveals the complex dynamics between formal and informal information dissemination strategies (official sources provide trust and transparency, while word-of-mouth mechanisms offer detailed information and trust) and their implications for reputation management in the auditing industry. The relevance of this research problem lies in the critical role of auditing firms in supporting transparency and honesty in financial reporting, especially after corporate scandals and regulatory scrutiny. The primary aim of this research is to understand the relative effectiveness of different information dissemination models in shaping the reputation of auditing companies. The choice of research subject is justified by the significant influence of auditing firms on financial markets, corporate governance, and investor trust. Using VOSviewer 1.6.16 software, the article conducts a bibliometric analysis of English-language articles and conference abstracts indexed in the Scopus database from 2007 to 2023 (1177 publications) using the keywords "Reputation" and "Auditing Firm." The analysis confirms the increasing scholarly interest in this topic and identifies 8 thematic clusters, the largest of which combines corporate, image, and social reputation with stability and consistency. The empirical part of the research involves constructing a polygamous model similar to the SIR model, which describes the behavior of three groups of subjects depending on the presence of information and actions regarding its dissemination (active, passive, neutral). The article models the intensity of changes in the number of group members considering various phenomenological parameters (e.g., intensity of communicative processes between groups, structure of social system connections, mathematical expectation of time required for a subject to transition from one group to another, etc.). The results of this research have practical implications for auditing firms, regulatory bodies, and stakeholders in the financial sector. By understanding the relative strengths and weaknesses of different information dissemination models, auditing firms can adapt their communication strategies to effectively enhance their reputation. This research contributes to the ongoing discourse on reputation management and trust-building in financial markets.

Complex systems consist of many components that interact with each other, and nonlinearity is fundamental in the dynamics that arise as a result of the interaction of these components and cannot be studied by observing only a small part of the system. A large number of them make fluctuations an integral part of their dynamics. Through interdisciplinary research, we integrate different disciplines and methodological approaches. We study complexity from different angles through topics that include neuroscience, artificial intelligence, and quantum physics. We have sought to explore these topics that have gained progressive interest in scientific circles as well as outside academic circles, influencing many areas outside academic research. Two goals connect our research. First, theoretical insights from neuroscience, artificial intelligence and quantum physics of the financial stock market. "Financial stock markets are sophisticated machines intertwined with scientific networks" (Ana Negovanović, 2024). They are the core of a system of different blocks that interact on the financial market in an interdisciplinary interaction of the most complex structures, neural networks with interconnected nodes. Second, new technologies- convergence of technologies, new industries, space industry through chaos theory. Investigating the attributes of complex systems is structure. Systems are structured in such a way that some parts of the system are specialized, and systems can naturally be divided into different levels of organization, which should be modeled at different levels of detail. An important component of systems understanding is the ability to break down a system model into its component parts and levels to see how the parts behave and how to connect the parts and levels to understand the overall dynamics and structure of the system. Perhaps one of the most transparent examples of the importance of structure in thinking about complex systems is the space program, where one must equally consider the behavior of individual components and the dynamics of how those components interact with each other.

Foreign direct investments are an instrument widely used by countries, both developed and emergent, to achieve their economic development. Among others benefits, discussed in the specialized literature, investment inflows accelerate production, improve productivity, facilitates the transfer of technology, raise the qualification oh human capital, contributes to create new jobs and to boost the economic growth of the host countries. The main purpose of the research is to examine the short and long runs relationships between foreign direct investment (FDI) and economic growth in Algeria. To carry out our investigation, the time series data of the two variables are used over the period 1990-2023. This period covers the span time in which data on the volume of foreign direct investments are available. To achieve the research purpose, an ARDL model is built based on the unit root methodology of the Augmented Dickey Fuller and Phillips  Perron tests. The findings of the study show that the foreign direct investment (FDI) and economic growth are cointegrated, indicating the existence of a long relationship among them. They establish also that foreign direct investment (FDI) has a positive impact on economic growth. Building on the research results, Algerian decision makers should take the required actions to improve the climate business, making it more attractive for foreign investors.

The Supplemental Nutrition Assistance Program (SNAP, also known as food stamps) offers tens of millions of American beneficiaries a crucial lifeline. This welfare benefit has been associated with better nutritional outcomes and has been linked to an efficient tool to fight hunger, improve labour market outcomes for the beneficiaries, achieve higher birth weight for children born to the beneficiary mothers, improve height and health outcomes for the beneficiaries. SNAP has been found to be an essential tool to ensure the availability of vital resources during times of need, etc. Despite the program's numerous advantages, serious doubts exist about its viability and stability of the program especially, given the steep rise in program costs over the years. Over the past 50 years, SNAP has experienced tremendous growth both in terms of the number of beneficiaries and amount of spending. From over $1.82 billion in 1969 to over $113 billion in 2022, the total cost of the SNAP initiative has increased over 62 times in 53 years. This research uses data from the US Department of Agriculture to investigate the time series properties in the rise in the total expenditure devoted to the SNAP between 1969 and 2022. With and without trends, Augmented Dickey-Fuller tests are run with carefully chosen lag lengths. The existence of a unit root cannot be rejected in all specifications pointing to the possibility that the program might have grown in an unstable manner over time. An overwhelming amount of evidence points to an unstable and unstable growth in the overall amount spent on SNAP recipients. This unchecked growth may present substantial difficulties for policymakers especially since the program competes with other welfare programs in an environment of rapidly rising national debt and persistent budget deficits. The report does not attempt to estimate program fraud or abuse which may partially contribute to higher expenditures.

In the context of rapid technological development, digitalization and transparency have a critical impact on national security, promoting transparency and combating corruption, while posing challenges to cybersecurity due to the increased availability of information. The purpose of this study is to identify, based on bibliometric analysis, trends and subject areas in research on the impact of digitalization and transparency on national security. To achieve this goal, a comprehensive bibliometric analysis of scientific works on the role of digitalization and transparency in national security published in the publications indexed by the Scopus database for 1991-2023 was conducted, which formed the statistical basis of the analysis. The bibliometric programs Vosviewer and SciVal were chosen as research tools, which allowed for an in-depth analytical review and identification of the main trends and interrelationships between different research areas, confirming the hypothesis of increasing interest in the study of digitalization and transparency in the context of national security. Based on the analysis of the common use of keywords, seven clusters were identified, covering a wide range of topics from digital transformation and adaptive governance for national security to global political and economic strategies, each of which reveals unique interrelationships between digitalization, transparency, innovation and their impact on national security, including cybersecurity challenges, ethics in governance, and the importance of transparency for democracy and human rights. The analysis of the evolutionary trends in research allowed us to identify four key periods of development of scientific interest in the impact of digitalization and transparency on national security: 1) the period from 2014 to 2016 is characterized by initial research on the role of digitalization in national security and mainly concerns e-government studies; 2) during 2017-2018, research focuses on the growing attention to transparency and its role in national security 3) in the period from 2019 to 2021, there is an increase in the number of studies related to cybersecurity and the impact of digital technologies on democracy; 4) from 2022 to the present, there is further in-depth research on topics related to artificial intelligence The spatial clustering of studies shows a high level of international integration in research on the impact of digitalization and transparency on national security. The findings can be used by state institutions to improve national security strategies, in particular by adapting the legislative framework to the challenges of digitalization and ensuring transparency at all levels of government and public life, including macro (national), meso (regional) and micro (local) levels, ensuring openness and accountability in all spheres of government and public control, which will ultimately contribute to ensuring stability and security at the national level.

This article delves into the analysis of the effectiveness of economic policies implemented in 20 countries in the Middle East and North Africa (MENA) region. The countries considered include Algeria, Saudi Arabia, the Palestinian Authority, Bahrain, Djibouti, the United Arab Emirates, Egypt, Iraq, Iran, Jordan, Kuwait, Lebanon, Libya, Morocco, Mauritania, Oman, Qatar, Syria, Tunisia, and Yemen. The study is based on an Autoregressive Distributed Lag (ARDL) regression model, employing the Ordinary Least Squares (OLS) method. This model is suitable for non-stationary time series and those with a mixed order of integration. The analysis covers the period from 2000 to 2023.The results obtained highlight the diversity of the impacts of economic policies, strongly influenced by the specific economic and social contexts of each country. Governments, in their pursuit of efficiency and sustainability, are often faced with the delicate balance between multiple objectives. Among the measures considered are the money supply, inflation rate, government spending, and structural reforms. These measures have demonstrated their effectiveness in stimulating economic growth, promoting economic activity, encouraging investment, and creating employment opportunities. Monetary and fiscal policies are also crucial levers aimed at maintaining macroeconomic stability. This is expressed notably through controlling inflation, managing budget deficits, and ensuring the stability of the financial system. The results of econometric tests converge towards unanimous conclusions, suggesting the existence of one-directional causal relationships between economic growth and specific indicators of economic policy. This in-depth understanding of regional economic dynamics provides valuable insights for tailoring economic policies to each national context within the MENA region.

This study aims to examine the key economic indicators with private sector credit and economic growth in Nepal. Commercial banks and other financial institutions lend money to businesses and individuals for investment and consumption. This study aims to analyze key economic indicators in Nepal, including Real Gross Domestic Product (RGDP), Private Sector Credit (PSC), and Gross Capital Formation (GCF), spanning from 1975 to 2022. Employing a quantitative methodology, econometric techniques such as time series analysis, regression modeling, and hypothesis testing were utilized to examine the long-term relationships among these variables, with a particular focus on the impact of Private Sector Credit on Economic Growth (EG). The findings, derived from comprehensive econometric analyses including co-integration tests and vector error correction models, reveal significant insights into Nepal's economic performance and financial system. Results indicate that Private Sector Credit plays a crucial role in stimulating economic growth, with approximately 40.07% of the previous year's imbalance influenced by the long-term elasticity of independent variables. These findings offer valuable insights for policymakers, businesses, and investors, facilitating informed decision-making to promote sustainable economic development in Nepal. Further research is recommended to explore the correlation between the diversification of Private Sector Credit types and economic growth more comprehensively.

The utilization of natural resources, particularly energy, is essential for economic well-being. However, the increasing consumption of economic resources raises concerns about sustainable development. This study aimed to investigate the dynamic decoupling of economic growth, energy consumption, and pollution in Iran from 2000 to 2020, employing the method proposed by Tapio (2005) and factor analysis on three levels of energy consumption (i.e., primary, final, and useful). The findings revealed that economic growth is often associated with negative decoupling, with this negative decoupling being more pronounced in useful and final energies compared to primary energy. Decomposing energy consumption further confirmed negative decoupling in various energy components. Additionally, the study confirmed weak decoupling between energy consumption and pollution (CO2 emissions), with stronger negative decoupling observed at lower energy levels. Furthermore, the decoupling of economic growth and pollution closely mirrors the decoupling of economic growth and energy consumption. The negative decoupling can be attributed to the inefficiency in energy consumption, limited access to new technologies, and the lack of appropriate structures due to the absence of a specific strategy for sustainable development. The research recommends the prioritization of energy efficiency across different energy levels as well as the investment in infrastructure and energy technology.IntroductionEconomic growth is intricately linked to the consumption of natural resources, with these scarce and costly resources serving as the primary catalyst for the development and acceleration of economic growth process in modern societies (Song et al., 2019; Song et al., 2020; Zhang et al., 2018). Meanwhile, the production and consumption of energy resources are associated with significant social costs and diminished welfare (Feng et al., 2020a; Feng et al., 2020b; Li et al., 2018; Rjoub et al., 2021; Wang et al., 2020). The world grapples with the challenge of balancing economic development and energy consumption (Bradshaw, 2010). Despite the looming threat of global warming, many countries, particularly developing nations, have prioritized economic development over environmental conservation (Shah et al., 2016). Consequently, decoupling energy consumption from economic growth is widely recognized as a significant achievement in the global effort to combat climate change and mitigate adverse environmental effects. The experience of developed countries instill hope for overcoming resource scarcity and growth limitations, as well as fostering green and sustainable economic growth. While relative decoupling has been achieved in numerous countries, absolute decoupling remains challenging and seemingly unattainable (Hickel & Kallis, 2020). In this respect, the present study aimed to scrutinize the decoupling dynamics of economic growth, energy consumption, and pollution in Iran from 2000 to 2020, employing the method proposed by Tapio (2005) as well as factor analysis across three energy levels.Materials and MethodsThe study followed the method proposed by Tapio (2005) in order to calculate the decoupling between energy consumption and economic growth. First, the decoupling elasticity coefficient was calculated as outlined below: (1)e(E) is the elasticity coefficient of decoupling between economic growth and energy consumption. ∆E represents changes in energy consumption during the time period under study. E (t-1) indicates energy consumption in the base year. ∆G refers to changes in GDP per capita during the time period, and G (t-1) indicates the GDP per capita in the base year (Wang & Zhang, 2021). In the method proposed by Tapio (2005), eight decoupling states can be distinguished (Figure 1).Figure 1. Decoupling states The present study conducted a more comprehensive analysis of decoupling by using factor analysis at various energy levels. In this line, the consumption across three energy levels (primary, final, useful) was divided into three distinct effects: activity (production rate), structural (change of economic structure), and intensity (technology effect). The logarithmic mean division method and each of these effects were used as follows: (2) (3) (4) (5)The study also divided economic activities into several categories: agriculture, services, industry, residential, and transportation. This categorization aligns with the most feasible separation based on the available data and statistical classifications within domestic data sources. In Iran’s energy balance, although household, public, and commercial sectors are categorized under one group, these sectors were individually reported, and the residential sector was distinguished from the commercial and public sector (as the service sector).Results and DiscussionFigure 2 presents the decoupling dynamics of Iran’s economic growth, energy consumption, and carbon dioxide emissions during 2000–2020. The figure is divided into two parts focused on various energy levels for different components: the first part depicts the decoupling of economic growth and energy consumption, while the second part shows the decoupling of energy consumption from carbon dioxide emissions. As show in Figure 2, the decoupling of economic growth and carbon dioxide follows a pattern similar to and influenced by the decoupling process between economic growth and fossil energy consumption. The decoupling of economic growth and fossil energy consumption aligns with changes in decoupling at different energy levels (primary, final, and useful), reflecting the significant share of fossil energy in Iran’s overall energy consumption. Figure 2 also highlights the weak decoupling between fossil energy consumption and carbon dioxide, which can be attributed to the nature of fossil fuel pollution. Consequently, the decoupling of economic growth from carbon dioxide is influenced by fossil energy consumption.The first part of Figure 2 reveals various forms of negative decoupling (expansive negative, weak negative, and strong negative) concerning economic growth and energy consumption. Correspondingly, the second part indicates a generally weak decoupling for different energy levels and carbon dioxide emissions. Within the energy consumption components, the intensity component exhibits strong decoupling, though it fluctuates, sometimes displaying positive decoupling (weak, recessive, and strong) and occasionally negative decoupling (expansive and strong negative)—which can be caused by the drop in technology. This finding aligns with the second part of Figure 2, where the decoupling of the intensity component and carbon dioxide experiences fluctuations. Notably, the structural component in the first part of Figure 2 exhibits the strongest negative decoupling from economic growth, signifying a change in Iran’s economic structure that has exacerbated the decoupling between energy consumption and economic growth. However, the decoupling of the structural component and carbon dioxide, as depicted in the second part of Figure 2, remains within the range of weak but fluctuating decoupling.Finally, the first part of Figure 2 indicates that economic growth is often associated with negative decoupling (expansive and strong negative) from total energy consumption. Despite weak decoupling in initial periods and subsequent fluctuations, the last two years show strong decoupling between total energy consumption and carbon dioxide. Overall, Figure 2 illustrates a fluctuating trend in the decoupling of economic growth and energy consumption over time, predominantly featuring negative decoupling, which corresponds to the decoupling trend between energy consumption and carbon dioxide. Among the components of energy consumption, the intensity component exhibits strong negative decoupling, while the structural component displays weak decoupling, both characterized by fluctuating patterns. This fluctuation may stem from the absence of a specific plan and strategy to decouple economic growth, energy consumption, and carbon dioxide.Figure 2. Decoupling of economic growth, energy consumption, and carbon dioxide emission in Iran during 2000–2020 Expansive negative decoupling decoupling ExpansiveWeak decouplingStrong decouplingRecessive decoupling Recessive coupling Weak negative decoupling Strong negative decouplingConclusionUsing the method proposed by Tapio (2005) and factor analysis across three energy levels, the present study investigated the dynamics of decoupling economic growth, energy consumption, and pollution in Iran during 2000–2020. The findings underscored challenges faced by the policy aimed at reducing energy consumption, which is primarily due to the dependency of Iran’s economy on energy. Specifically, the research showed the dependency of Iran’s economy on energy on energy consumption across all three levels: primary energy, final energy, and useful energy. Moreover, the results highlighted a low degree of energy efficiency, particularly at higher energy levels (secondary and useful). Considering the relation between environmental pressure and restrictions on economic growth, there is a pressing need to address energy intensity and energy efficiency to strike a balance between economic growth and energy consumption. The observed negative decoupling in structural, intensity, and activity effects suggests a lack of a specific strategy in Iran’s economy concerning the decoupling and balance between energy consumption and economic development. In light of these findings, it is imperative to focus on enhancing energy consumption efficiency across diverse energy levels. Additionally, the study recommends prioritizing more effective decoupling in sustainable development policies concerning energy consumption, economic growth, and pollution.

Human demand for natural resources is surpassing the Earth’s biocapacity and regenerative capacity, leading to environmental degradation. Accurate research is essential to investigate and predict these changes more precisely. The ecological footprint serves as a suitable index for tracking human demand, resource recovery capacity, and waste absorption in the environment. The concept aims to offer a land-based measure that estimates the impact of consumption on the environment in the land area required to fulfill consumption. The dynamic input–output approach represents a novel method for measuring the ecological footprint, predicting land use based on economic growth rates. Pioneering the dynamic ecological footprint calculation using real-world data, the current study calculated Iran’s ecological footprint by relying on 1395/2016 input-output tables from the Central Bank in three sectors: agriculture, industry, and services. The per-capita ecological footprint for Iran was determined to be 0.42 hectares with an 8% planned economic growth rate. If the ecological footprint continues to grow at the same rate, it is estimated that Iran’s land biocapacity will be depleted by the year 1412/2033. Considering a growth rate of 6.4% (excluding oil) in the year 1395/2016, this scenario is anticipated to occur by the year 1417/2038. IntroductionLand use has undergone significant changes due to urbanization and the expansion of economic activities, surpassing the Earth’s capacity for regeneration and absorption and resulting in environmental degradation. Exacerbated by population growth, the issue has caused more serious concerns among policymakers and researchers regarding the future of the environment. It is thus necessary to measure human demand and regenerative capacity of natural resources. In this respect, the ecological footprint is considered a useful measure, defined as an environmental index that quantifies natural resource consumption based on land use, and reflects the impact of human demand on nature. The comparison between human consumption and biocapacity aids in assessing the level of sustainability. Existing literature refers to two methods of ecological footprint calculation. Employing a macro perspective, the first method relies on the evident consumption of resources (land or water) involved in producing domestic goods and services—including imported goods but excluding exported goods. Many scholars have used the input–output model to calculate the ecological footprint for resource management at the sectoral level. The versatility of the model has led to its widespread application in recent years, as it can adapt to variations in monetary and physical units at the same time. It proves particularly useful in analyzing a wider range of environmental issues, such as life cycle assessment and ecological footprint calculation. While the ecological footprint is a vital tool for studying sustainable development, its traditional version primarily focuses on static calculations derived from past footprints. Some critics contend that ecological footprint analysis lacks a dynamic approach to the future, but offers more of a snapshot in time. Dobos and Tóth-Bozó (2023) employed a dynamic input–output model to develop a method for ecological footprint calculation. Within this dynamic model, the ecological footprint becomes predictable through the utilization of the capital coefficient matrix (investment matrix) in conjunction with the direct input coefficient matrix. The present study pioneered the dynamic ecological footprint calculation by utilizing real-world data and the dynamic input–output table of the year 1395/2016.Materials and MethodsThe study employed a dynamic input–output model that maintains equilibrium between supply and demand over specific time periods. Investment was taken into account through capital-output coefficients within an intra-sectoral capital coefficient matrix which shows capital exchanges between demand sectors and capital suppliers, proving valuable in predicting crucial economic variables and growth patterns. It also serves as an efficient tool for economic planning. The model proposed by Dobos and Tóth-Bozó (2023) is a function of vectors representing final consumption, exports, and imports of final goods. They had actually used the dynamic model developed by Leontief (1970) to calculate land demand for each period of national production. The present study showed how the index changes by taking into account the investment flow and the equilibrium path of consumption and production growth. The total ecological footprint is predicted in relation to the potential economic growth rate; Iran’s Sixth Five-Year Economic, Cultural and Social Development Plan (1396–1400); and the growth rate excluding oil in 1395/2016. To accomplish this, three sectors (agriculture, industry, and services) were formed within a closed dynamic input–output model, referred to as forward-looking. The data was gathered from the 1395/2016 input–output table from the Central Bank database, capital stock, inventory data (agriculture and industry) from the Statistical Center of Iran. The lands were studied in three sectors: agriculture, industry, and services.Results and DiscussionIn the dynamic input-output model, the potential growth rate is determined by the maximum eigenvalue of the matrix composed of the direct input coefficient matrix and the capital coefficient matrix. The potential growth rate was found to be 41%. Moreover, the planned growth rate of 8% in Iran’s Sixth Five-Year Economic, Cultural and Social Development Plan (1396–1400) was also considered. According the Statistical Center of Iran, the gross domestic product experienced an overall growth of 11.1% in 1395/2016. Excluding oil, this growth rate stands at 6.4%. The per-capita Iranian ecological footprint was measured at 0.42 hectares with an 8% planned economic growth rate. If the ecological footprint continues to grow at the same rate, it is estimated that Iran’s land biocapacity will be depleted by the year 1412/2033. Considering a growth rate of 6.4% (excluding oil) in the year 1395/2016, this scenario is anticipated to occur by the year 1417/2038.ConclusionAccording to the research results, changes in the growth rate alter the time horizon for land use. The growth rate is influenced by various factors. Consequently, advocating for short-term planning becomes crucial to either manage its effects in the long run or mitigate its adverse consequences—in case of its deviation from sustainable development goals. This model does not incorporate assumptions about technological progress in the economy. Future research could enhance the economic model by integrating technological progress, allowing for the evolution of model matrices over time. In the contemporary economy, Research and Development (R&D) plays a vital role in developing new technologies to promote environmental preservation. Furthermore, providing ample data can enable the creation of inverse Leontief matrices with larger dimensions, facilitating more practical outcomes, such as dynamic analysis of land-use changes within specific timeframes. The current research exclusively sought to introduce the index alongside its predictability. However, the absence of sufficient data might have resulted in estimates based on unrealistic data, impacting the accuracy and validity of the results. Nonetheless, these findings can aid in large-scale policymaking.

The paper aims to reassess “the Coase Theorem” in its historical context and highlight the discernible gap between the Coase Theorem and the often-overlooked arguments articulated by Coase. In “the Problem of Social Costs”, Ronald Coase intended to emphasis on the irrelevance of Pigou's argument in dealing with externalities. The theorem implies that in a world with zero-transaction cost, external effects are internalized without government intervention and the allocation of legal rights does not matter. These implications have led observers to criticize the theorem, notwithstanding the accurate scrutiny reveals that almost all of the critiques center around the main assumption of the theorem­­ – namely, zero transaction costs- rather than the theorem itself. While the correctness of the theorem heavily depends on the concept of “transaction costs”, the concept suffers from a lack of clear definition. It is important to note, in that paper, Coase intended to argue that Pigou's analysis in “the Economics of Welfare” is irrelevant, and in a zero-transaction cost world, market forces internalize externalities, and government intervention is not needed. In contrast, when positive transaction cost is considered the allocation of legal rights and liabilities becomes important. This latter point has been almost ignored in the literature and entailed that the Coase theorem is an unrealistic one. IntroductionCoase Theorem stands as a highly discussed and well-developed theorem in law and economics. The theorem received too much of critiques even before the publication of the Coase’s seminal paper. These hot debates made “the Problem of Social Costs” one of the most cited articles in Law and Economics. In this paper I am going to reconsider the theorem in its historical context and highlight the discernible gap between the Coase Theorem and the often-overlooked arguments articulated by Coase in the aforementioned article.Methods and MaterialTo conduct the research, I adopted the library and document research method. To do so, I thoroughly reviewed Coase’s methodological background and highlighted his consequentialist mind as well as his approach to externalities and rejection of Pigouvian liability and taxation rules. Furthermore, I analyzed critiques of the Coase Theorem and discussed why the theorem has remained robust against those attacks. Finally, I argued why the Coase theorem is a misunderstanding of Coase’s approach to real economy and should be interpreted as the departure point of his theoretical approach to real economy.Results and DiscussionAnalyzing nuisance and externalities, respectively in legal and economic literature was at the core of the Coase’s discussion in “the Problem of Social Costs”. At the time, the dominant legal approach to delineate liability was fault based. The Pigouvian solution to internalize externalities had been developed based on this legal tradition. Based on Pigou, taxes have to be employed to motivate polluters or injurers to take into account the costs they impose on others without compensating them.Coase, first of all, intended to undermine these legal and economic approaches to liability and nuisance. He developed, in that paper, his consequentialist approach to law, based on which alternative liability rules should be assessed in terms of their consequences, and the adopted rule should entail higher total net benefit. This was evident in his opening discussion in which he mentions the case of Sturges vs. Bridgman.In addition, he highlights the role of property rights in performing economies as well as the power of markets in exchanging legal rights and allocating them to the parties who value the rights higher than other parties. He made this clear when he assigned legal rights to farmer and herder alternatively and concluded that the resulting property right is efficient and invariant, regardless of the initial holder of the legal right. This argument named by George Stigler, The Coase Theorem.In this approach, not only markets are considered as a mechanism which is capable to allocate rights efficiently but also what are exchanged in markets are considered as bundles of rights rather than mere physical goods and services. He emphasized on this critical point at the concluding part of the paper.Among these and other exciting issues, what absorbed most attentions was the Coase Theorem and even most of the critics allocated their time and effort to undermine the Theorem, while the Theorem was only the departure point of his arguments. In the first half of the paper, maybe under the influence of the Black Stone Avenue’s discussions, he considered the case in which costs of using price mechanism is zero and argued that in such a world, market exchanges would internalize externalities, government intervention is not required, Pigouvian taxes are irrelevant, and the allocation of legal rights does not matter.In this paper, I discussed alternative critiques of the Coase Theorem and indicated that almost all of them, in fact, argue that in a non-zero transaction costs world the theorem does not hold. This is why these critiques are, in effect, the proof of the theorem rather than its refutation. As a matter of fact, the Coase Theorem is a development of the first fundamental theorem of welfare economics, and both of them are valid in a zero transaction costs world.ConclusionAs indicated, Coase’s main argument is different from the Coase Theorem. While the latter underscores the irrelevance of legal rules, the former highlights the importance of legal rules in real world, in which transaction costs are positive. In this world, reducing transaction costs by defining legal rights is efficiency enhancing (normative Coase Theorem). Furthermore, Legal rights should be chosen based on their merits in economizing exchanges and supporting arrangements with higher total net benefits. This is the main mission of the law and economics.

The present study aimed to develop a model for determining an optimal bidding strategy for electricity producers, including the recommended selling price and the amount of electricity to be offered for participation in both the competitive electricity market and the energy exchange market. Hourly bids are suggested for the electricity market, while a monthly package, comprising peak load, medium load, low load, and base load, is proposed for the exchange market. By modeling a self-scheduling problem, the study aimed to develop optimal power production plans that maximize net profit over a one-month period. The research approach involved mathematical modeling using mixed-integer non-linear programming, which was performed in Lingo software and then validated in terms of effectiveness through an application to the case of a thermal power station. Relying on fuzzy necessity, credibility, and possibility, the research presented a robust model against the uncertainty of price with an adjustable level of robustness. Sensitivity analysis and the simulation approach were used to validate the performance of the model, demonstrating that the optimal response from the robust model, compared to the deterministic model, can maintain its efficiency in the face of fluctuations in the parameter of price uncertainty. Furthermore, the findings indicated that offering a base load package on the energy exchange market can yield a higher net profit value for the producer. Finally, the fuzzy interest rate and decision-making based on fuzzy goals were also examined.1. IntroductionIn recent years, researchers have directed their attention toward robust optimization in markets with uniform pricing systems. However, the application of robust methods in pay-as-bid systems remains unexplored. Therefore, a notable research gap exists, specifically in the robust optimization of pay-as-bid systems in the Iranian electricity market. Moreover, with the establishment of the energy exchange market in Iran, the simultaneous bidding, in both the energy exchange market and the day-ahead electricity market, has surfaced as a significant gap in existing research literature. In this respect, the present study contributes to relevant research by addressing existing gaps while considering the specific needs of the Iranian electricity market. The study tried to model the self-scheduling problem of an electricity producer to determine an optimal and robust strategy. Employing fuzzy theory to address the uncertainty of the market clearing price parameter, the model can protect the producer from electricity price uncertainty in the market, as well as foster a more secure environment for participation in competitive electricity markets.2. Materials and MethodsAs an applied and developmental research, the present study aimed to develop robust optimization models for bidding in the electricity market. This descriptive–analytical study examined, described, and explained uncertainty in decision-making, employing a fuzzy approach to tackle uncertainty. The research involved the mathematical modeling of the problem of determining the bidding strategy for electricity producers, presented as mixed-integer programming. First, the variables and parameters of the modeling process were introduced, followed by presenting the problem formulation. Subsequently, the implementation and its procedural steps were performed in the Lingo software to validate the effectiveness of the proposed model by applying it to the case of a thermal power station. 3.Results and DiscussionThe research proposed a model designed to address bidding challenges encountered by a price-taker electricity producer. The model centers on optimizing simultaneous monthly bidding in both the day-ahead electricity market and the energy exchange market. The objective is to optimally allocate the producer’s capacity between these two markets to maximize profit. To handle the uncertainty of electricity prices, a robust method is employed, necessitating estimates of the next day’s market price and the energy exchange price for the upcoming month. The proposed model underwent testing across various modes, including base load, off-peak load, medium load, and peak load packages. The results revealed that the producer’s profit is maximized when offering the base load package to the energy exchange market, followed by the medium load package. Peak and off-peak packages ranked third with equal values. Therefore, it is recommended for producers seeking participation in the energy exchange market to consider offering a base load package.4. ConclusionThe present research employed a robust fuzzy technique to deal with the volatility of electricity market prices, allowing decision-makers to make firm decisions with an adjustable level of robustness. The results of the proposed method indicated that the possibility criterion adopts an optimistic stance towards the settlement price, thus suggesting prices at higher levels than the necessity and credibility criteria. This criterion is suitable only when market signals indicate a potential price increase. In contrast, the necessity criterion adopts a cautious approach, showing robustness even at low confidence levels. This approach is well-suited for risk-averse decision-makers and scenarios where market signals point towards a potential price reduction.