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Circuit breaker, an automated regulatory instrument employed to deter panic, temper volatility, and prevent crashes, is controversial in financial markets. Proponents claim it provides a propitious time out when price levels are stressed and persuades traders to make rational trading decisions. Opponents demur its potency, dubbing it a barrier to laissez‐faire price discovery process. Since conceptualization in 1970s and practice from 1980s, researchers focused mostly on its ability to allay panic, interference in trading, volatility transmission, prospect of self‐fulfilling prophecy through gravitational pull towards itself, and delayed dissemination of information. Though financial economists are forked on circuit breakers' usefulness, they are a clear favourite among regulators, who downplay the reliability of anti‐circuit breaker findings citing, inter alia, suspect methodology, and lack of statistical power. In the backdrop of 2007–2008 Crisis and 2010 Flash Crash, the drumbeats for more regulatory intervention in markets grew louder. Hence, it is unlikely that intervening mechanism such as circuit breakers will ebb. But are circuit breakers worth it? This paper synthesizes three decades of theoretical and empirical works, underlines the limitations, issues, and methodological shortcomings undermining findings, attempts to explain regulatory rationale, and provides direction for future research in an increasingly complex market climate. [ABSTRACT FROM AUTHOR]

We built an artificial market model and investigated the impact of large erroneous orders on financial market price formations. Comparing the case of consented large erroneous orders in the short term with that of continuous small erroneous orders in the long term, if amounts of orders are the same, we found that the orders induced almost the same price fall range. We also analysed effects of price variation limits for erroneous orders and found that price variation limits that employ a limitation term shorter than the time erroneous orders exist effectively prevent large price fluctuations. We also investigated effects of up-tick rules, adopting the trigger method that the Japan Financial Services Agency adopted in November 2013. We also investigated whether dark pools that never provide any order books stabilize markets or not using the model including one lit market, which provides all order books to investors, and one dark pool. We found that markets become more stable as the dark pool is increasingly used. We also found that using the dark pool more reduces the market impacts. However, if other investors' usage rates of dark pools become too large, investors must use the dark pool more than other investors to avoid market impacts. When a tick size of a lit market is larger, dark pools are more useful to avoid market impacts. These results suggest that dark pools stabilize markets when the usage rate is under some threshold and negatively affect the market when the usage rate is over that threshold. Our simulation results suggest the threshold might be much larger than the usage rate in present real financial markets. This study is the first to discuss whether or not several concrete and actually adoptable regulations, including those that have never been employed (e.g. price variation limits with various parameters), could prevent large fluctuations of market prices, including those beyond our experience, using artificial market simulations, and to discuss quantitatively how spreading of dark pools beyond our experience could affect market price formations using the artificial market simulations. In short, this study is the first study to comprehensively discuss how regulations and financial systems beyond our experience could affect price formations using the artificial market simulations. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper constructs an institutional investor network based on the heavy holdings of the same stock in China and conducts a social network analysis to investigate the influence of this network on stock price volatility from the perspectives of network structure (density) and location (centrality). The study demonstrates that institutional investor network density is negatively related to stock price volatility, while network centrality is positively related to it. Mechanism analyses further reveal that network density reduces stock price volatility by mitigating private information arbitrage behavior among institutional investors, whereas network centrality increases stock price volatility by creating private information arbitrage opportunities within the network. Additionally, the paper finds that information asymmetry enhances the positive effect of network centrality on stock price volatility. These findings are generally consistent across subsample analyses for different market states, reactions to good and bad news, and types of equity ownership, as well as in other robustness tests. The practical implications of these findings are significant for market stability regulation. [ABSTRACT FROM AUTHOR]

This paper studies the complexity analysis in production between competition and R&D for a traditional energy vehicles enterprise and a new energy vehicles enterprise under the introduction of corporate average fuel consumption credits and new energy vehicle credits mandate. From the internal perspective of market complexity evolution, this paper analyzes the internal mechanism of market competition fluctuation and discusses the influence of different corresponding speeds of enterprises on market stability through the nonlinear dynamics' theory. The research results show that the adjustment coefficient of R&D investment and the price coefficient of credit transactions are the key factors affecting the competitive strategies of the two companies. The difference between these two factors will even change the relative R&D investment intensity, relative profitability, and market stability of the two companies in a balanced state. In addition, the numerical analysis showed that the time-delay feedback control method could control the unstable behavior of the dynamic system efficiently and quickly and make the market quickly recover a stable and orderly state, which provided a scientific basis for decision makers to effectively solve the market instability. [ABSTRACT FROM AUTHOR]

While energy risk is increasingly recognized as a systemic risk, there is limited comprehensive analysis of the risk propagation in regional contexts. In this study, we examine oil and natural gas price changes and shocks in relation to equity market returns and volatility for 24 European Economic Area (EEA) countries. In addition to traditional panel regressions, we also deploy the Diebold‐Yilmaz (2014) spillover index for a closed network analysis. We differentiate in the cross‐section across the core EU block, PIIGS countries, EU enlargement countries joining after 2004, and other non‐EU countries, to provide insights into the ongoing debates on the European energy market stability. While we find evidence of the manifestation of energy risk throughout the sample period, we find that until 2019 the primary sources of volatility spillover in the EEA economic network arose from economic or political uncertainty. Energy risks, measured by large crude oil and natural gas price shocks also significantly contributed to equity market volatility, with increasing volatility risk arising from natural gas, a green labelled energy source after 2019. Last, we show that CEEC equity markets are more sensitive to oil and natural gas price shocks when domestic currencies depreciate against the Euro. [ABSTRACT FROM AUTHOR]

This paper presents the development of a model incorporating two manufacturers in a competitive carbon emissions trading market with varying degrees of market competitiveness. Among them, the manufacturer is in a limited market leadership position, and the game process lies between the Stackelberg game and the Cournot game. Additionally, the Pareto solution sets at various model periods are investigated. In addition, the model examined the effect of dynamic government adjustments on carbon emission limitations. The paper conducts an analysis of the fundamental factors contributing to system instability and evaluates the influence of various factors on the model's stability. At the same time, we also discussed the influence of government adjustment strategy on retail decision‐making and stability. The results highlight that the instability of the system is mainly caused by the adjustment strategy of the market leader, whereby the system becomes increasingly unstable as the market leader's position becomes stronger. In addition, the government's implementation of carbon emission limits will promote market stability. [ABSTRACT FROM AUTHOR]

This research delves into the formation of labor values in Latin America, exploring the complex interaction between socio‐demographic characteristics (gender, age, and educational level), well‐being (happiness, health, and life satisfaction), and macroeconomic factors (wealth, equity, and labor market stability). With microdata drawn from the World Values Survey, the study employs Logit and Blinder–Oaxaca decomposition models to analyze data from Brazil, Chile, Colombia, Mexico, and Peru during 2005–2019. It uncovers the significant influence of worker happiness on labor values, especially among self‐employed individuals, and highlights happiness as a critical factor in varying labor values related to different well‐being dimensions. These insights reveal the intricate determinants of work values in the region, providing valuable implications for talent management and policy development aimed at fostering sustainable development through positive labor values. [ABSTRACT FROM AUTHOR]

The synchronization in financial markets has increased during the rise of global markets. Nevertheless, global shocks provoke high levels of returns synchronization that jeopardize market stability. Using correlation-based networks, regressions, and VAR models, we measure and estimate the effect of global synchronization on the world equity markets of North America, Latin America, Europe, Asia, and Oceania between July 2001 and April 2020. We find that our measure of global stock synchronization is dynamic over time, its minimums coincide with significant financial shocks, and it shrinks to its minimum levels, indicating that the returns of global markets are moving in a synchronized way. Also, it is a significant and positive factor of regional synchronization. Regional markets react heterogeneously to global synchronization shocks suggesting both local and global factors are sources of synchronization. Our work helps market participants who need to measure, monitor, and manage the synchronization of returns in a parsimonious, dynamic, and empirically tractable way. Our evidence highlights the necessity of including synchronization as a risk factor to assess the decision-making criteria of a broad range of market participants ranging from regulators to investors. To policy-makers, governments, and central banks, our work is a call to incorporate events of high global synchronization into the radar of hazards of the whole market stability. [ABSTRACT FROM AUTHOR]

In 2021 and 2022, Beijing courts annulled three contracts for cryptocurrency mining, holding that they were contrary to the public interest. The judges based their decisions on Chinese law provisions concerning contractual validity and supported their arguments by citing various policy documents warning of the risks of cryptocurrency‐related activities to financial market stability and energy consumption. Although the provisions that the courts cited were recently reformed, the courts' line of reasoning and approach may set an example for future cases concerning carbon‐intensive activities. This note therefore considers these judgements in the broader context of climate change litigation, reflecting on the role of courts in implementing industrial and microeconomic policy in the interpretation of contract law. [ABSTRACT FROM AUTHOR]

The systemic stability of a stock market is one of the core issues in the financial field. The market can be regarded as a complex network whose nodes are stocks connected by edges that signify their correlation strength. Since the market is a strongly nonlinear system, it is difficult to measure the macroscopic stability and depict market fluctuations in time. In this article, we use a geometric measure derived from discrete Ricci curvature to capture the higher-order nonlinear architecture of financial networks. In order to confirm the effectiveness of our method, we use it to analyze the CSI 300 constituents of China's stock market from 2005 to 2020 and the systemic stability of the market is quantified through the network's Ricci-type curvatures. Furthermore, we use a hybrid model to analyze the curvature time series and predict the future trends of the market accurately. As far as we know, this is the first article to apply Ricci curvature to forecast the systemic stability of China's stock market, and our results show that Ricci curvature has good explanatory power for the market stability and can be a good indicator to judge the future risk and volatility of China's stock market. [ABSTRACT FROM AUTHOR]

The main objective of this article is to analyze and compare the impact of political uncertainty and financial crises on stock market volatility in 10 MENA countries over the period 2005–2018. To test our hypothesis, a variety of GARCH models are used. The results indicate that political events have more significant effect than financial crises on stock market volatility, as we detect an increase in market volatility during political elections and terrorist attacks. The comparative tests employed to identify the best GARCH model in capturing stock markets volatilities reveal that GARCH/EGARCH models perform the best in our study. EGARCH model is more suitable during unpredictable events while GARCH model work well during predictable events. Additionally, we found that the reaction of investors is not similar during the three events studied. In fact, terrorist attacks admit a more significant effect than political election periods. We observed that the reaction of the stock market during expected events is not instantaneous, whereas it is instantaneous during unexpected events. Overall, our findings are of great significance for investors and market regulators in understanding the role of major events on stock market stability, particularly in MENA region. [ABSTRACT FROM AUTHOR]

We evaluate asset returns and volatility connectedness using the time‐frequency connectedness model and machine learning approaches. Using 48 years of monthly indices of equity real estate investment trusts (EREITs), mortgage real estate investment trusts (MREITs), stocks, commodities, and bonds, we find that shocks to EREIT, and MREIT returns have a transitory impact on other assets. However, asset volatility connectedness among assets occurs at lower frequencies as markets slowly process pricing information. Therefore, shocks to EREIT and MREIT decay gradually and spill over to the other three assets for long periods. We also find that the intensity of the time‐frequency connectedness of returns and volatility varies with business cycles and significant domestic and global non‐recession events. We attribute the dominance of real estate investment trusts (REITs) in destabilising the financial system through long‐term volatility transmission to the heavy linkage of REITs to highly illiquid underlying direct real estate markets and high REITs leverage, making them more sensitive to real estate fundamentals, monetary shocks and macroeconomic risks than stocks and bonds. The result of the algorithm‐based GA2M machine learning model broadly supports the dominance of EREITs in the transmission of returns and volatility and shows that commodities have more explanatory power in the transmission of volatility than in returns. The empirical findings have implications for strategic and tactical asset allocation and policy design for market stability. [ABSTRACT FROM AUTHOR]

Freight transport is critical to the development of the global economy, but it also increases greenhouse gas (GHG) emissions. As a result, global challenges, such as climate change, must be addressed. Hydrogen‐fueled transportation could be a viable, sustainable alternative by providing a clean, efficient, and long‐term alternative to fossil fuels, resulting in significantly lower GHG emissions. However, the usage of hydrogen as a fuel is still in its nascent stage, and different nations have initiated strategizing its production and consumption. Understanding the factors that may affect hydrogen's adoption as a fuel in the transportation and logistics sector becomes crucial. The present study attempts to fill this gap by identifying, categorizing, and prioritizing those factors. Initially, the factors have been identified from the literature and further finalized with the consultation with domain experts using the critical success factor theory. Further, relevant factors have been finalized and categorized using exploratory factor analysis. Afterward, the grey–ordinal priority approach is applied to determine the priority weights of the categories and their factors. The findings indicated that operational and environmental are the two most prioritized categories. Specifically, "Substituting Energy Dependency," "Storage and Infrastructure Costs," and "Ability to Mitigate Harmful Gases" are the top three prioritized factors for the adoption of hydrogen‐fueled transportation among stakeholders. According to the findings, the management of related businesses can collaborate as a business strategy to develop a robust hydrogen supply chain and secure the market stability of hydrogen fuel to ensure sustainable freight transportation. [ABSTRACT FROM AUTHOR]

This paper uses agent-based modelling to study the frequent booms and busts in Chinese agricultural markets. First, an artificial agricultural commodity market consisting of heterogeneous agents, such as producers, consumers, and speculators, is built. A numerical simulation suggests that speculation can cause large price fluctuations via nonlinear price dynamics. Then, parameters are estimated by the simulated method of moments using garlic and ginger price data in China from 2006Q2 to 2018Q3. The estimation yields a statistically significant speculative behavior parameter, supporting speculators' existence. Based on the well-estimated model, a low-cost policy experiment aiming at market stabilization is carried out. The essence of this policy is to release the theoretical steady state of the estimated model as the government-guided price to producers. The guided price, even partially followed by producers, can reduce simulated price variances and weaken speculators' negative impact on market stability. Robustness tests show that the effect of policy experiment is robust under a 20% change in any parameter value or a 5% change in the guided price. [ABSTRACT FROM AUTHOR]

Ride‐sharing platforms, such as Uber and Didi Chuxing, widely use differential pricing strategies to encourage platform participation. However, it remains unclear whether differential pricing strategies in ride sharing are reasonable when users care about price fairness. Moreover, platforms face a unique dilemma when considering differential pricing: should it be used for customers, drivers, or both? On the demand side, platforms must deal with taxi competition, while the supply side contends with government regulation; it is this dilemma that motivates our work. Using a stylized model that includes price fairness, market conditions, and government policies, we consider four ride‐sharing platform pricing strategies: uniform pricing, differential customer pricing, differential driver pricing, and bilateral differential pricing. We present results from three perspectives. For platforms, we obtain feasible regions in all four pricing strategies. If the maximal number of potential drivers is below certain thresholds, a platform will use differential driver pricing. Conversely, differential customer pricing is optimal when the maximal number of potential drivers is sufficiently large. Moreover, when customers have stronger fairness concerns, platforms tend to use differential driver pricing to reduce competition. From the government perspective, when a platform charges customers differently, the government can achieve a win‐win solution for sustainable development and market stability by setting a proper taxi rate. Interestingly, we find that, for the demand and supply sides, an increase in fairness concerns may hurt customers and drivers under certain conditions. [ABSTRACT FROM AUTHOR]

The Bank of Papua New Guinea has maintained an active policy of foreign exchange (FX) market intervention. This monetary tool is associated with a depreciating currency and a worsening shortage of foreign currencies in the domestic market, suggesting that at most the policy instrument leans against existing FX‐market pressure. However, the one‐sided sales of central bank securities (or bills) engender an appreciation of the rate and an easing of the shortage in the domestic FX market. Supported by empirical evidence, we demonstrate that the one‐sided sales of central bank bills perform like an instrument of monetary policy for FX‐market stability in the presence of persistent nonremunerated excess bank reserves. [ABSTRACT FROM AUTHOR]

Copyright of Politics & Policy is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Brands share more of their customers with bigger competitors and fewer with smaller ones. However, there are occasional deviations to this predictable Duplication of Purchase (DoP) pattern. When two or more brands share excess customers because of functional or nonfunctional differences—it is called a partition. While past research using the NBD‐Dirichlet model demonstrates partitions in annual or shorter data, there is no empirical evidence for partition persistency over the longer term, although some other NBD‐Dirichlet deviations are known to persist over time. Examining expected partitions in 10 consumer goods categories in the United Kingdom, the authors show partitions overwhelmingly persist over 3 years. The findings contribute support to Dirichlet theory, especially on market stability, boundary conditions, and provide practical implications for portfolio management. [ABSTRACT FROM AUTHOR]

There have been heated debates about the role of stock index futures in the financial market, especially during the crash periods. In this paper, a multiagent spot-futures market model is developed to analyze the micromechanism of shock transfer across spot and futures markets. We assume that there are two stocks and one stock index futures contract in the spot-futures market. Agents are heterogeneous, including fundamentalists, chartists, noise traders, and arbitragers. The spot market and the futures market are linked by arbitragers. The simulation results show that our spot-futures market model can reproduce various important stylized facts, including the price co-movement between stock index prices and index futures prices and the fat-tailed distribution of the returns of risky assets and the basis. Further analysis shows that when we introduce an exogenous fundamental shock to one of the stocks, the backwardation phenomenon appears in the futures market and the shock is widespread across the whole market by means of index futures. Moreover, the backwardation gradually disappears when the number of arbitragers increases. Besides, when there are few arbitragers or when there are sufficient arbitragers, shocks cannot be transferred to other stocks via the futures market, while an intermediate level of arbitrage will amplify the shock transfer and hurt market stability. These findings underscore that arbitragers play an important role in spot-futures market interaction and shock transfer, and adequate arbitrage trading during crises may help eliminate the positive basis and halt the further spread of the crises. [ABSTRACT FROM AUTHOR]

Data transparency is fundamental in the monitoring of markets and provides the bases of data‐driven decision‐making among market players. Energy markets and principally the oil market are by nature dependent on accurate, timely and high‐quality data, particularly during periods of downturn, or structural change. High‐quality and timely energy data also play a vital role in contributing to energy market stability. This paper captures only a small part of the richness in OPEC efforts towards promoting energy and, particularly, oil data transparency throughout the Organization's 60 year history. The Organization and its Member Countries are continuously manifesting their commitment towards a transparent oil market place by numerous freely available publications, such as the OPEC ASB, MOMR and the WOO, while at the same time strongly supporting JODI data collection and several other data‐related activities. The Organization and its Member Countries are pioneers in implementing new technologies, such as digitalisation and Big Data towards setting higher data quality standards. [ABSTRACT FROM AUTHOR]

The adaptive neuro‐fuzzy inference system (ANFIS) is widely employed in modeling intricate systems, especially in forecasting cooking oil prices. However, ANFIS confronts limitations stemming from backpropagation, prompting the exploration of alternatives like particle swarm optimization (PSO). Hybrid PSO‐ANFIS models exhibit enhanced forecasting accuracy, albeit at the expense of increased computational time. Nonetheless, both ANFIS and hybrid PSO‐ANFIS encounter challenges in handling dynamic relationships influenced by macroeconomic factors. To address these issues, the development of the State‐ANFIS (S‐ANFIS) method integrates regime‐switching models, enhancing its capability to manage dynamic relationships. Particularly effective in cooking oil price prediction, S‐ANFIS clarifies the impact of external variables and improves forecast accuracy and interpretability by combining ANFIS with state‐space models. Our analysis underscores S‐ANFIS's superiority over ANFIS, particularly with Gaussian membership functions, as it reduces RMSE and MAPE values by half while requiring fewer nodes, thereby improving computational efficiency. Additionally, integrating key state variables like crude palm oil (CPO) prices, inflation rates, and the USD exchange rate enhances the reliability of the model. Overall, S‐ANFIS offers a more accurate, interpretable, and efficient approach to forecasting cooking oil prices, demonstrating superior predictive capabilities. [ABSTRACT FROM AUTHOR]

The prevalence of B2B platform ecosystem has led to the emergence of revenue‐sharing contracts as the dominant business model adopted by manufacturers and retailers on these platforms. This paper establishes a dynamic game model of B2B platform ecosystem, comprising one manufacturer and one retailer, where the manufacturer engages in technological investments and the retailer engages in consumption investments, both exhibiting bounded rationality. Through a comprehensive analysis of complex behaviors, the results reveal the following: (1) Adjustment speed of the manufacturer influences the stability of the platform ecosystem, with higher adjustment speeds leading to greater instability. In a stable state of the B2B platform ecosystem, an actor with lower costs tends to make higher investments. (2) Higher investment costs contribute to a more stable B2B platform ecosystem. When the ecosystem stabilizes, increasing investment costs will reduce manufacturers' investment levels. (3) The retailer revenue sharing parameter exacerbates the instability of the B2B platform ecosystem. This unequal distribution not only impairs manufacturers' earnings but also disrupts B2B platform ecosystem equilibrium. (4) Market expansion results in B2B platform ecosystem imbalance. As the market size increases, investment levels rise, but this also leads to system instability. Therefore, managers must strike a balance between market expansion and system stability objectives. (5) We incorporate the time‐delayed feedback control (TDFC) method to regulate intricate phenomena. The TDFC method proves effective in mitigating chaotic behaviors within B2B platform ecosystem. [ABSTRACT FROM AUTHOR]

This article assesses the hedging and safe haven properties of energy and agricultural commodities (crude oil, natural gas, and wheat) against the G7 stock market indices and banking sector stock indices during the COVID‐19 pandemic, the Russia–Ukraine military conflict, and the Silicon Valley Bank (SVB) collapse. Using wavelet coherence analysis, our results showed dynamic correlations in which commodities shifted from diversifiers to strong safe havens during periods of turmoil. Particularly, WTI became a safe haven during the SVB collapse, natural gas acted primarily as a safe haven during the pandemic, and wheat evolved into a robust safe haven during crises. Moreover, our results with the G7 banking sector stock indices underscore the safe haven ability of commodities against these financial assets, furnishing valuable insights for investors during unstable financial situations. [ABSTRACT FROM AUTHOR]

With the increasing penetration rate of renewable energy in the power system, it becomes increasingly important to coordinate adequacy, flexibility, and environmental protection. The development of the power market provides diverse signals for power investors and plays an increasingly significant role in the decarbonization of the power system. However, due to the interdependent operations of various power markets, measuring the multifaceted value of power generation within traditional market mechanisms poses considerable challenges. Herein, a bi‐level optimization model is proposed to integrate the capacity remuneration mechanism (CRM), energy market (EM), and carbon emission trading (CET). The adequacy, flexibility, and environmental revenue expectations of different generation resources through synergistic transactions are derived using Lagrange multipliers. Furthermore, the bilevel optimization model is converted to its equivalent single‐level scheme based on the Karush–Kuhn–Tucker optimality conditions. Finally, several case studies are conducted to demonstrate the effectiveness of the proposed model, along with comparisons and sensitivity analyses to study the principles behind synergistic transactions and the impact of some key parameters. [ABSTRACT FROM AUTHOR]

Geopolitical risk (GPR) presents a profound challenge to firms, particularly in regions with persistent political instability. In Eastern Europe, where conflicts like the Russia–Ukraine war heighten uncertainty, firms face immediate financial threats and long‐term strategic vulnerabilities. This study examines the impact of GPR on firm performance, focusing on the moderating role of environmental, social, and governance (ESG) practices as a resilience mechanism. Using a comprehensive dataset of 1360 publicly listed firms across Poland, Russia, and Ukraine from 2014 to 2023, the analysis employs a base panel data regression model, followed by a two‐step generalized method of moments (GMM) approach to account for endogeneity and ensure robustness. The findings reveal a significant negative relationship between GPR and firm performance, measured by return on assets (ROA). Firms exposed to higher geopolitical risks exhibit weaker profitability. However, firms with stronger ESG performance demonstrate greater resilience, as the GMM results show that ESG engagement moderates the adverse effects of GPR on profitability. This suggests that ESG initiatives enhance adaptive capacity in volatile geopolitical environments. In terms of policy implications, ESG should be promoted as a key strategy for firms operating in politically unstable regions. Governments and regulatory bodies may consider mandatory ESG disclosures and incentivizing sustainability practices to help firms mitigate external risks, improve financial resilience, and attract stable investment. Aligning corporate strategies with global ESG standards is essential to ensuring business sustainability amid ongoing geopolitical threats. [ABSTRACT FROM AUTHOR]

The study of consumption behavior on green food plays an important role in promoting agricultural environmental protection and eco‐agricultural production. Based on the practical investigation, this paper makes an empirical study on the consumption behavior of green food by using binary logistic regression model. It is found that consumer's education level has a significant positive effect on green food consumption. Consumer income level does not pass the test on consumption behavior, but the change direction is opposite. Consumer age and premium of green food are negatively correlated with consumption motivation and behavior, while green food reliability and satisfaction are positively correlated with consumption motivation and behavior. Consumer gender, marital status, and information channels have no significant impact on consumption motivation and behavior. According to the research results, the production and marketing of green food should pay attention to the product quality and the actual feedback from consumers, and should increase the market propaganda to improve the attention and recognition ability on green food, and should take effective measures to develop the older consumer's market. [ABSTRACT FROM AUTHOR]

At present, the problems of homogenization and low quality in China's iron and steel industry are particularly prominent and the ability of the enterprises to cope with change is insufficient. Adopting product differentiation strategy and dynamic adjustment strategy can allow steel enterprises and the industry to better adapt to future changes. By introducing the product differentiation degree (substitution coefficient) and the bounded rationality strategy to simulate these two strategic means, this paper constructs an extended two-stage dynamic game model to analyse the dynamic game scenarios and steel market stability in China. As new findings, we report the following: (1) The system is more likely to fall into an unbalanced state when multiple enterprises adopt the policy of dynamic output adjustment simultaneously. (2) Enterprises with large output and small output have different output adjustment policies. When enterprises with big-scale output adopt a bit larger adjustment policies, enterprises with small output will be strongly impacted, and the available adjustment space will be sharply compressed. (3) The gradual increase in the difference between products reduces the stability of the market. (4) When product differentiation and bounded rationality strategies coexist, the steel market may fall into an unbalanced state when the degree of product difference increases excessively and the enterprise adopts more drastic output adjustment policies. Therefore, there are pros and cons to product differentiation strategy and bounded rationality adjustment strategy. When each steel oligopoly enterprise formulates a production plan, it needs to comprehensively consider the output changes of the other enterprises and carefully weigh the strategic issues. [ABSTRACT FROM AUTHOR]

Copyright of Review of Policy Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the 2007–08 financial crisis, over‐the‐counter (OTC) derivatives triggered the collapse of colossal financial institutions. In response, global policy makers instituted clearinghouse mandates. As a result, all standardized OTC derivatives must now use clearinghouses, and global financial market stability now depends upon these institutions. Yet certain underlying legal and regulatory structures threaten to undermine clearinghouse stability, particularly were a significant clearinghouse to become distressed. This article argues that the clearinghouse mandates are incomplete in that they fail to reform these problematic arrangements. As with electric utilities, the lights at the financial market infrastructures known as clearinghouses must always be on. Yet the legal frameworks for handling a distressed clearinghouse, the problem of clearinghouse recovery, and resolution, remain uncertain. This article advances debate on this issue. It argues that recovery, a private market restructuring process, can be conceptualized as a bargaining game dependent upon time‐critical cooperation between a clearinghouse and members. This article uses transaction cost economics to demonstrate, however, that certain underlying legal and regulatory structures could work at cross‐purposes to this necessary cooperation, and actually increase its cost. Based upon this analysis, it proposes reforms designed to ensure that parties' incentives promote efficient recovery. In the absence of efficient recovery frameworks, the path of a distressed, significant clearinghouse is likely to resemble that of the government‐backed mortgage lenders whose fate more than ten years after their entry into conservatorship remains uncertain. This article aims to help avoid a repeat of this history. [ABSTRACT FROM AUTHOR]

This study attempts to evaluate the efficacy of macroeconomic policies in resolving financial market disequilibria and to elucidate the influence of the political landscape and global financial integration on the policymaking process. The current investigation examines three macroeconomic policies: (a) government spending, (b) liquidity provision, and (c) central bank interest rates by analysing 21 countries around the globe. The results suggest that government spending is a suboptimal macroeconomic policy for mitigating imbalances in financial markets, as it may have destabilizing effects. Liquidity provision was found to be ineffective in facilitating financial market stability whereas the adjustment of interest rates was found to be a viable tool for mitigating financial market imbalances. Therefore, an appropriate policy framework would comprise the following: prudent government spending, conditional liquidity provision, and a reduction in interest rates following the development of financial market disequilibria. Furthermore, this study found strong evidence against the notion that political orientations influence policy frameworks, which were designed to redress financial market disequilibria. This study also found that global financial integration does not influence the policymaking process. [ABSTRACT FROM AUTHOR]

We survey more than 1,100 risk managers from around the world regarding their risk management policies. We find evidence consistent with some traditional theories of risk management, but not with all. We then study "why" or "why not" firms hedge and find that almost 90% of risk managers in nonfinancial firms hedge to increase expected cash flow. We also find that 70% to 80% of risk managers hedge to smooth earnings or to satisfy shareholders' expectations. Our analysis also suggests that regulatory changes implemented to increase market stability (e.g., Dodd‐Frank Act) could discourage corporate hedging. Finally, we provide evidence regarding hedging in six areas of risk: interest rate, foreign exchange, commodity, energy, credit, and geopolitical. We find that operational hedging is more common than financial hedging in all risk areas except foreign exchange. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Economics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: Applying a principal‐agent perspective on trilogue negotiations, this article examines how the rapporteur and the Presidency, as agents of respectively the European Parliament and the Council, are able to reach a deal with their fellow agent while avoiding an involuntary defection among their principals. Despite these intra‐ and inter‐institutional constraints, early agreements can be concluded because agents execute two parallel tasks on behalf of their principals: representing them inter‐institutionally and acting as the deal‐facilitator intra‐institutionally. We identify three ways in which the agents can combine these two acts of delegation and conclude an early agreement: (1) creating a tied‐hand situation for themselves; (2) affecting the intra‐institutional coalition formation by bringing in allies from the other institution; and (3) actively searching for signals from the principals and the fellow agent on the zone of possible agreement. We illustrate these dynamics through a case study of the policy‐making process on the 2015 Decision on the Market Stability Reserve. [ABSTRACT FROM AUTHOR]

In recent years, the importance of deregulated power systems has grown significantly, resulting in positive effects on stability, reliability, innovation, and investment in new energy grid technology. The competitive landscape among energy providers and distributors has empowered consumers to not only save money on their energy bills but also incorporate sustainable energy sources into the grid. To efficiently manage electricity distribution, deregulated power systems must include a smart grid and microgrid (MG). Herein, the potential for sustainable expansion of these systems, as well as their economic and environmental implications, are examined. A comprehensive grid system that integrates smart grids and MGs can offer a complete solution, catering to the evolving energy needs of communities and businesses. The advantages of establishing such a system, including improved grid stability, reliability, and increased utilization of renewable energy sources (RES), are highlighted. Furthermore, the integration of MGs and smart grids enhances the management of distributed generation, allowing power companies to optimize system operations for profitability and efficiency. By following these suggestions, businesses and stakeholders in the power sector can enhance the efficiency and responsibility of their systems, resulting in benefits for both the economy and the environment. [ABSTRACT FROM AUTHOR]

This paper studies the complexity of the decision system when a brand enterprise introduces new products and makes dynamic quality decisions to cope with imitation threats caused by a counterfeit enterprise. Using game theory, nonlinear system theory, and numerical simulation, the complexity characteristics of this system and consumer utility are further discussed; moreover, delay feedback control is used to restrain chaos. The conclusions are as follows: (1) The stable scope of the brand enterprise price adjustment enlarges with the increase of the adjustment parameters of new product quality and imitation price. (2) The attraction domain of the initial decisions of the counterfeit enterprise decreases when the brand enterprise makes dynamic decisions on new product quality; a higher new product quality adjustment parameter can reduce the imitation ability of the counterfeit enterprise. (3) With the growth of the degree of substitution between new products and existing products, the quality of new products is improved, the output of existing products is reduced, and the counterfeit enterprise withdraws from the market if the degree of substitution between existing products and imitations is high. (4) The dynamic system can suppress chaos and restore stability by using the delay feedback control method. Results are of great importance for managers to make reasonable decisions when dealing with imitation threats. [ABSTRACT FROM AUTHOR]

This study delves into the effect of environmental, social and governance (ESG) indicators on economic growth trajectory of an emerging economy. A sample of firms listed on the ESG index of the National Stock Exchange (NSE) was examined. The findings reveal a positive and statistically significant relationship between ESG performance indicators and economic growth represented as gross domestic product (GDP) per capita. The sample is further segregated into energy and non‐energy sectors, where the aggregate ESG scores exhibited a statistically significant influence on economic growth in both sectors. However, upon a closer examination of the individual ESG pillars, the governance pillar is observed to exert a negative influence on economic performance in non‐energy firms. In contrast, the environment and social pillars show no significant influence. The analysis then employs a unique approach by applying a Difference‐in‐differences estimator to assess the impact of Business Responsibility and Sustainability Reporting (BRSR) regulations, which confirms a positive impact on economic growth after regulations but exclusively within the non‐energy sector. This study underscores the substantial impact of ESG aggregate and individual scores on GDP per capita, which translates to economic growth. [ABSTRACT FROM AUTHOR]

Optimizing sustainability among smallholder farms poses challenges due to inherent trade‐offs. In the study of organic and conventional cocoa smallholder farming in Ghana, 398 farms are assessed using the Food and Agriculture Organsation of the United Nations (FAO) Sustainability Assessment of Food and Agriculture systems (SAFA) Guidelines and Sustainability Monitoring and Assessment Routine (SMART)‐Farm Tool. Organic farming exhibited synergies in environmental aspects (e.g., soil quality, energy efficiency) and between biodiversity conservation and risk management. Conventional farming showed potential vulnerabilities, including trade‐offs with long‐range investments (e.g., chemical inputs) and species diversity. Both systems demand tailored approaches for short‐term economic and environmental sustainability, aligning with community‐wide long‐term goals. To mitigate trade‐offs in conventional farming, smallholders should adopt practices like material reuse, recycling, and recovery within their operations. [ABSTRACT FROM AUTHOR]

For the past several decades, the container shipping industry has grown rapidly. As a result, container shipping companies (CSCs) play a vital role in the global cargo transportation market. Thus, measuring the efficiency of CSCs is a primary concern of managers and practitioners. When the COVID‐19 pandemic broke out, the industry was severely disrupted and presented with unprecedented challenges. For this reason, evaluating how CSCs performed and learning the practices they took to achieve successful business results during this period have become necessary. To serve that purpose, this article used a hybrid method that combined data envelopment analysis Malmquist index with window analysis to analyze the world's nine leading CSCs' performance over time and their efficiency relative to each other, using data collected within a 5‐year period from 2016 to 2020. Our findings revealed different characteristics and trends in efficiency among these CSCs in terms of technical efficiency change, technological change, and total productivity change. Then, managerial implications were discussed to understand the best practices of successful CSCs as well as the circumstances in which some of them underperformed during this time. In closing, the study summarized a fact‐based guideline CSCs could take as management reference should a similar crisis occur. [ABSTRACT FROM AUTHOR]

Physical unclonable functions (PUFs) have emerged as a promising encryption technology, utilizing intrinsic physical identifiers that offer enhanced security and tamper resistance. Multi‐level PUFs boost system complexity, thereby improving system reliability and fault tolerance. However, crosstalk‐free multi‐level PUFs remain a persistent challenge. In this study, a hierarchical PUF system that harnesses the spontaneous phase separation of silk fibroin /PVA blend and the random distribution of silicon‐vacancy diamonds within the blend is presented. The thermodynamic instability of phase separation and inherent unpredictability of diamond dispersion gives rise to intricate random patterns at two distinct scales, enabling time‐efficient hierarchical authentication for cryptographic keys. These patterns are complementary yet independent, inherently resistant to replication and damage thus affording robust security and reliability to the proposed system. Furthermore, customized authentication algorithms are constructed: visual PUFs authentication utilizes neural network combined structural similarity index measure, while spectral PUFs authentication employs Hamming distance and cross‐correlation bit operation. This hierarchical PUF system attains a high recognition rate without interscale crosstalk. Additionally, the coding capacity is exponentially enhanced using M‐ary encoding to reinforce multi‐level encryption. Hierarchical PUFs hold significant potential for immediate application, offering unprecedented data protection and cryptographic key authentication capabilities. [ABSTRACT FROM AUTHOR]

This study compares the price dynamics of a Caputo fractional order delay differential cobweb model with existing cobweb models that have conformable fractional derivatives, Caputo fractional derivatives, and nonsingular kernel fractional derivatives to determine the effect of the time delay parameter on commodity price, besides the positivity of the solution that was investigated. In contrast to previous research, the stability study shows the practical usefulness of our model since the literature's various time intervals showed short‐term equilibrium price convergence but long‐term price divergence. The results showed that the time gap between supply and demand accounts for the noise associated with the fractional‐order time delay differential cobweb regarding convergence (or divergence), which is nonexistent in the literature models. It is observed in the paper that lower fractional order goes with a higher time delay, while we have the reverse for high fractional order. This depicts the realities of price behaviour in connection with the law of demand and supply of commodities that take a finite period for them to be ready for distribution to the market. It is, therefore, recommended that price adjustment models be modeled using fractional delay differential equations. The numerical simulations were done using MATLAB. [ABSTRACT FROM AUTHOR]

Historically, European Union (EU27) member states have held sway over the administration of aquaculture sectors. However, challenges have arisen within this regulatory framework, particularly concerning the implementation of sustainable conservation measures across the EU27 region. In response to perceived regulatory shortcomings, alternative strategies like economic and community‐based management have emerged. Thus, this study aims to investigate how global governance factors have influenced the growth of the aquaculture industry within the European Union (EU13) and European Union (EU14) from 1990 to 2023. To address endogeneity concerns, robust least squares, two‐stage least squares (2SLS), and ordinary least squares estimators were employed, yielding significant findings. Notably, the impact analysis reveals that property rights, economic stability, private sector quality, and private interest are pivotal drivers of aquaculture industry growth in EU14 developed countries compared to their EU13 developing counterparts. Conversely, the novelty of the paper shows that economic growth, social development, and aquaculture industry advancement hold greater significance in EU13 developing countries relative to EU14 developed ones, as indicated by the estimators. Given these insights, policymakers in EU13 developing countries are urged to prioritize initiatives aimed at fortifying property rights, economic stability, and private interest. Conversely, policymakers in EU14 developed countries are encouraged to focus on fostering economic growth, enhancing public sector quality, and promoting social development in blue farming. [ABSTRACT FROM AUTHOR]

This paper examines the dynamic evolution and volatility spillovers between China's green bond market and conventional financial markets (bond, stock, commodity, and foreign exchange markets) using time and frequency connectedness measures. The empirical findings are as follows: firstly, there is a significant volatility spillover effect between the green bond market and other traditional financial markets, with the spillover effect showing clear time‐varying characteristics. The total spillover effects among all markets increase notably during extreme market conditions. Secondly, the green bond market primarily acts as a net risk spillover transmitter in most periods. Thirdly, compared to the stock, foreign exchange, and commodity markets, the green bond market has a more significant spillover effect on the traditional fixed‐income market. Finally, the volatility spillover effect of the green bond market on other markets exhibits a time‐frequency evolution, predominantly driven by short‐term factors. However, as market maturity increases, the influencing factors of the spillover effect gradually shift from short‐term to medium and long‐term factors. These findings offer insights for portfolio and risk management. [ABSTRACT FROM AUTHOR]

To further enhance the precision of carbon trading price forecasting, this research proposes a combined forecasting model, CEEMDAN–VMD–IPSO–BiLSTM, considering the unsatisfactory high‐frequency sequence decomposition and the reliance on unidirectional neural networks in current carbon price‐prediction models. First of all, the original sequence of carbon prices is decomposed into multiple independent subsequences through the completely ensemble empirical mode decomposition with adaptive noise (CEEMDAN) technique. The sample entropy values of each subsequence are calculated to reconstruct them as high‐frequency, low‐frequency, and trend sequences. Second, we employ the variational mode decomposition (VMD) approach to decompose the high‐frequency series. The obtained subsequences, along with the low‐frequency and trend sequences, are separately input into an improved particle swarm optimization (IPSO) optimized bidirectional long short‐term memory neural network (BiLSTM) model for forecasting. Finally, an IPSO–BiLSTM model is used to integrate the forecasting outcomes from the previous step, yielding the ultimate results for predicting carbon prices. The case studies reveal that compared with the benchmark model, this model exhibits superior predictive precision and universality. It offers theoretical support for optimizing carbon market operations and fostering low‐carbon economic growth, holding practical importance. [ABSTRACT FROM AUTHOR]

Blue finance research has recently made significant progress, but comprehensive research is still in its infancy. This paper established a consolidated database of 223 articles on blue finance and used CiteSpace for visualization analysis. Firstly, blue finance develops in embryonic, fluctuating, and stable growth phases. The main research countries are the US, Australia, England, and Canada. The University of California and the University of Queensland are the main research institutions. Marine Policy and Science are highly cited journals. A few core authors shape blue finance research with limited collaboration. Secondly, three themes were established by categorizing ten keyword clusters: financial instruments and mechanisms for marine conservation and sustainability, policy frameworks for adaptation and climate resilience, and policy frameworks for adaptation and climate resilience. Thirdly, contingent valuation, marine protected areas, and the blue economy are the main research hotspots. The results' theoretical contribution is identifying the progress of blue finance and its potential directions. Researchers, managers, and policymakers can use it to promote economic growth and ocean sustainability. [ABSTRACT FROM AUTHOR]

With the gradual attention of global climate change, a series of carbon emission plans have been formally implemented in the field of energy. There is a consistent relationship between the carbon market and the electricity market in promoting clean energy development and improving carbon dioxide emission reduction targets. The market design of a low‐carbon power system should be considered as a whole to promote the coordinated development of carbon and power markets. Taking an industrial park in China as the research object, an internal market trading model of an industrial park considering carbon dioxide emission reduction targets is proposed. The proposed trading mechanism considers both carbon dioxide emission reduction targets and social welfare maximization. The proposed market trading model connects day‐ahead and intraday electricity markets, which deal with uncertainty about renewable energy sources. [ABSTRACT FROM AUTHOR]

Recent research examining the growth impacts of institutions have found that institutions are important in fostering economic growth. By building a framework around the institutional taxonomy proposed by Rodrik (2005), our paper contributes to the literature in the following way. First, we confirm the result that 'institutions matter' and show that different types of institutions matter differently for growth. By applying a dynamic panel model, we find that market-creating and market-stabilising institutions are important in fostering economic growth. We then extend this analysis and investigate whether countries at different levels of development could respond heterogeneously to changes in their institutional structure. We find that poor countries benefit the most from market-creating institutions and institutions that support market stability. We also find some evidence that market-legitimising institutions such as 'democracy' are not necessarily optimal for growth in poor countries. These results have important implications for countries that decide on the optimal strategy to improve their institutional framework. [ABSTRACT FROM AUTHOR]

Motivated by the growing interest of investors in commodities and by advances in risk measurement, we present a full‐scale analysis of expected shortfall (ES) in commodity futures markets. Besides illustrating the dynamics of historic ES, we evaluate whether popular estimators are suitable for forecasting future ES. By implementing a new backtest, we find that the performance of estimators hinges on market stability. Estimators tend to fail when markets are in turmoil and accurate forecasts are urgently needed. Even though a kernel method performs best on average, our results advise against the use of established estimators for risk (and margin) prediction. [ABSTRACT FROM AUTHOR]

We investigate whether there are any identifiable differences in market perceptions of rating news released by Moody's, S&P and Fitch following the establishment of a new regulatory regime in July 2011, when the European Securities and Markets Authority assumed responsibility for rating agencies' regulation in Europe. We focus the analysis on the impact of bank rating actions on stock returns and volatility during 2008-2013. Among the intended effects of the new regulatory regime are higher rating quality and enhanced market stability, yet we find very mixed evidence. Many differentials in market responses across CRAs are identified, which mean that a consistent effect of the new regulatory regime is not discernible. [ABSTRACT FROM AUTHOR]