Search Results (133)

This article re-examines corporate tax loss carryforward and company regulation under United Arab Emirates law as applied to virtual assets. It uses Egypt as one functional benchmark among several, alongside the United States, the United Kingdom, Singapore, the European Union, and OECD reporting standards. The study asks whether the UAE’s general loss architecture—especially Articles 37–40 of Federal Decree-Law No. 47 of 2022—can address transaction-level problems involving classification, realization, valuation, beneficial ownership, custody, related parties, and evidentiary traceability without departing unnecessarily from tax neutrality. Using a doctrinal, comparative, and policy-oriented method, the article finds that the comparators generally apply ordinary tax categories while supplementing them with crypto-specific guidance, market supervision, and information reporting; they do not establish a general virtual-asset loss ring-fence. The UAE framework already contains substantial safeguards, including a 75% utilization cap, ownership and continuity conditions, transfer-pricing and anti-abuse rules, and the exclusion of exempt persons and Qualifying Free Zone Persons from Article 38 loss transfers. The identified concern is therefore a prospective institutional vulnerability rather than a demonstrated pattern of UAE abuse. The article’s original contribution lies in its UAE-focused synthesis and implementation architecture, not in originating the case for restricting crypto-losses. It proposes a neutrality-first, risk-triggered model: genuine losses remain subject to ordinary law, while enhanced proof and scrutiny apply where identifiable markers arise, including self-custody without reliable records, non-independent valuation, illiquid tokens, related-party crystallization, unlicensed platforms, abrupt ownership changes, acquisition of loss companies, or transactions lacking commercial purpose. Asset-class ring-fencing or special continuity rules should be considered only if future UAE evidence demonstrates that these technologically neutral safeguards are inadequate. This calibrated approach protects the tax base while preserving legal certainty, proportionality, and the UAE’s attractiveness as a digital-finance hub. Full article

International oil price volatility poses severe risks to macroeconomic stability and energy security, presenting complex policy challenges for China as it simultaneously pursues economic growth and a low-carbon transition. To bridge the gap between general equilibrium reallocation and transition quality, this study couples an 18-sector recursive dynamic computable general equilibrium (CGE) model with a super-efficiency slacks-based measure (SBM) model to evaluate China’s macroeconomic path and green total factor productivity (GTFP) from 2023 to 2045. We simulate a permanent 200% international oil price shock starting from 2026—conceived as a tail-risk stress test—together with alternative shock scenarios of varying magnitude and persistence (P50, P100, and a five-year temporary variant of P200_5Y), and evaluate four counterfactual policies under the P200 stress-test condition: household transfers (Tran_HG), price regulation (P_REG), structural tax reduction (T_RED), and energy-transition acceleration (Delta_ENE). The shock triggers imported cost-push inflation and a regressive shift toward coal, with the long-run damage governed jointly by shock magnitude and persistence; since GTFP deteriorates monotonically with shock size, the apparent emission reductions under extreme shocks suggest a contraction-driven “efficiency illusion” rather than genuine green improvements. Individually, P_REG and T_RED are effective only as temporary shields, Tran_HG provides the strongest welfare protection but amplifies the high-carbon rebound, and Delta_ENE uniquely improves resilience and green efficiency simultaneously. Building on these results, a combined policy package (COM) is further designed and simulated, which exhibits positive complementarities; it cuts the 2026 GDP loss by about 70%, turns GDP and welfare losses into net gains by 2043 and 2040, respectively, and delivers favorable green-transition outcomes. These findings call for coordinated, phased policy packages in which fiscal space rotates from emergency shields to demand-side repair and, ultimately, to electrification-led structural transformation. Full article

Although metal-modified biochar demonstrates high efficacy for phosphorus (P) removal in aqueous systems, its soil-scale mechanisms and ecological consequences under extreme rainfall remain largely unknown. In this study, we investigated how iron-modified biochar (BC+Fe) regulates P leaching and soil microbial communities in acidic soils using adsorption assays and column leaching experiments under simulated prolonged heavy rainfall. Mechanistically, BC+Fe exhibited adsorption kinetics that were better described by the pseudo-second-order model, consistent with a chemisorption-dominated P retention mechanism. Across six consecutive leaching events, BC+Fe significantly increased soil pH from 4.1 to 4.5 and reduced cumulative P loss by 37.7% compared to unmodified biochar (BC), with the most pronounced mitigation occurring during the initial leaching events when P losses were greatest. After leaching, soil total and available P concentrations under BC+Fe were approximately 3.4- and 3.7-fold higher, respectively, than under BC. Crucially, while both biochar types shifted bacterial community composition, BC+Fe maintained bacterial Shannon diversity and network complexity at levels comparable to the unamended soil and significantly higher than those under BC. Further analysis revealed that P leaching loss and soil pH were the primary environmental drivers shaping these microbial responses, and specifically, severe P loss was directly associated with simplified network complexity and intensified microbial competition (reflected by increased negative cohesion). Functional profiles inferred using Tax4Fun2 further showed that BC+Fe supported higher predicted microbial functional redundancy than both BC and the unamended control. Collectively, these findings demonstrate that iron-modified biochar mitigates P leaching through robust chemisorption and pH stabilization, while concurrently safeguarding microbial network complexity and functional redundancy. This dual benefit highlights the potential of iron-modified biochar as a sustainable amendment for maintaining soil ecosystem buffering capacity against severe hydrological stress. Full article

Systematic trend-following strategies applied to equity markets are widely studied, yet most reported performance statistics are non-reproducible in live trading. This paper makes three contributions. First, we introduce a formal taxonomy of look-ahead bias organised around point-in-time correctness: a strategy is point-in-time correct if, for every decision time t, its information set lies in the natural filtration ${\mathcal{F}}_t$. Three bias classes—universe-membership contamination, price-data forward leakage, and stop-exit sequencing violations—are characterised as filtration breaches. Second, we formalise the average true range (ATR) trailing stop as a stochastic recurrence and codify its monotonic non-decreasing ratcheting property (Lemma 1), providing a structural per-trade loss bound. Third, we exhibit a closed-form construction (Theorem 1) of two return sequences with identical Sharpe ratios but arbitrarily divergent maximum consecutive negative-year runs, establishing investor-experience metrics as independent optimisation objectives. We complement these contributions with an 18-year empirical study (2008–2025) on the NASDAQ-100 with reconstructed point-in-time index constituency (Class I compliant) and measured residual Class II exposure, applying combinatorially symmetric cross-validation (CSCV) to a 14-configuration ATR-multiplier grid. The grid exhibits a stop-multiplier-insensitive, CAGR-flat region across $k\in [3.5,7.0]$ (CAGR 10.28–10.39%, net of Dutch progressive tax) and a uniform maximum consecutive negative-year run of 1 across all 14 configurations. The correlation-matrix eigenvalue spectrum of the grid is dominated by a single mode (${\lambda }_1=13.91$ of 14), yielding an effective independent-test count of $M_{\mathrm{eff}}=1.09$. This near-degeneracy persists in a parallel grid with the regime classifier disabled, establishing the ATR multiplier as a structurally near-redundant parameter for this strategy class. The associated PBO value of $=0.9351$ co-occurs with this near-degeneracy under the CSCV maximum-selection rule. The plateau-level performance survives Bonferroni correction for both $M=14$ and $M_{\mathrm{eff}}$. The combined evidence supports a region-based interpretation of robust strategy parameters rather than single-point optimisation. Full article

The growing demand for high-strength and low-core-loss soft magnetic materials in high-efficiency energy conversion devices necessitates the development of novel alloys that combine excellent mechanical and soft magnetic properties. This work investigated the effect of Ta content on the microstructure and properties of as-cast (Fe₇Co₆Ni₆)_93-xTa_xAl₇ (x = 3, 5, 7) multiprincipal element alloys (MPEAs). Microstructural characterization and mechanical and magnetic testing were conducted using scanning transmission electron microscopy (STEM), tensile testing, and vibrating sample magnetometry (VSM). The alloys featured an FCC matrix, in which Ta addition led to the precipitation of a Ta-rich Laves phase and significant grain refinement. The Ta5 alloy demonstrated an optimal balance of properties, with a yield strength approaching 992 MPa, an elongation of 10%, a saturation magnetization (M_s) of 94.16 emu/g, and a coercivity of 6.69 Oe, indicating a good balance of strength, ductility, and soft magnetic performance. An appropriate amount of Ta enhanced strength via precipitation and grain-boundary strengthening, while the M_s showed only a moderate reduction. Full article

This study examines the association between Integrated Reporting (IR) quality and tax avoidance among South African listed firms from 2012 to 2021, and whether this relationship differs across the highest and lowest levels of IR quality. The extent to which the adoption of a Combined Assurance (CA) model strengthens the IR monitoring role in reducing tax avoidance, as well as the IR quality link with ESG-related implications of tax avoidance, are also explored. IR quality is directly derived from the EY Excellence in Integrated Reporting Awards ranking. This ranking evaluates firms’ adherence to the IR framework and is thus employed as a comprehensive proxy for IR quality. Tax avoidance is captured through multiple proxies. The main findings reveal no significant overall association between IR quality and tax avoidance, suggesting a decoupling between IR and tax behavior. However, when examining firms at the highest and lowest levels of IR quality, a significant negative relationship emerges only for the top performers (highest IR quality), indicating that IR constrains tax avoidance only when supported by a strong ethical corporate culture. Firms adopting CA exhibit higher tax avoidance, suggesting that IR and CA may be constrained by underlying corporate culture and used symbolically. Higher IR quality is also associated with lower tax avoidance relative to GDP and reduced potential revenue losses relative to government expenditures on education, health, and environmental protection. These findings contribute to the literature on IR, corporate governance, and tax avoidance, while also informing policymakers and regulators on the need to strengthen IR and CA frameworks through enhanced tax transparency requirements, thereby supporting equitable resource mobilization, institutional trust, and long-term sustainable development. Full article

This paper proposes a bi-level optimal dispatch model for a wind–solar–thermal-storage hybrid power system that considers the optimal curtailment rate. The upper-level model minimizes net-load fluctuations and curtailment penalties by coordinating renewable curtailment and energy storage scheduling under multiple uncertainty scenarios. The lower-level model minimizes the total operating cost by optimizing thermal unit commitment and dispatch while accounting for deep peak-regulation costs, spinning reserve costs, environmental taxes, and the environmental benefits of renewables. A piecewise nonlinear cost model is introduced to characterize the increasing wear-and-tear and oil-support costs of thermal units operating under deep peak regulation. Simulation results obtained on a modified IEEE 30-bus system demonstrate that, compared with benchmark models, the proposed approach significantly smooths the net-load curve, reduces the peak-to-valley difference, and lowers the total system operating cost. The results further indicate that moderate active curtailment, when coordinated with energy storage, can be more economical than rigid full renewable accommodation. Consequently, active curtailment should be regarded not merely as a loss of renewable energy utilization but as a flexible and economically rational resource for enhancing system security, flexibility, and overall dispatch performance. Full article

This paper examines the effect of trade openness on corporate tax revenue in the Middle East and North Africa (MENA) region, where increased economic integration might incite more business activity and expand taxable corporate income but also intensify losses due to practices such as profit shifting. The study follows a quantitative empirical approach and applies a panel ARDL model to secondary data collected from international databases (World Bank and IMF), such as GDP, trade openness (exports and imports as % of GDP), inflation, corporate tax revenues, foreign direct investment inflows and tax evasion via informal economies, for a sample of ten developing countries from the MENA region, including Morocco, Tunisia, Egypt, Jordan, Lebanon, Algeria, Saudi Arabia, Oman, the United Arab Emirates, and Bahrain, over the period 2010–2023. We employ a PMG ARDL model to study our panel data, allowing the analysis of both short-run and long-run effects to investigate the relationship between trade openness and tax revenues. Our results show that in the long run, export-driven economies generate higher corporate tax revenues by expanding profitability and the tax base, and imports also positively affect revenues, indicating that trade openness stimulates economic activity. Conversely, FDI inflows reduce corporate tax revenues, consistent with profit shifting and tax incentives in developing countries. GDP growth does not necessarily increase tax receipts, likely due to tax elasticity effects and growth-oriented tax structures. Also, tax evasion appears to decline, likely reflecting improved compliance, and no significant short-run effects are observed. The results contribute to the literature on tax compliance and economic integration in the case of open economies in developing countries. From a practical perspective, our findings have implications for policymakers and tax regulators in the MENA region, as they highlight the dual nature of globalization for developing countries and their tax systems and underscore the need for effective compliance measures in trade and investment policies. Full article

This study focuses on optimizing hybrid photovoltaic (PV)–wind–lithium-ion battery systems, aiming to balance lifecycle cost (LCC) minimization and power supply reliability (measured by loss of power supply probability, LPSP). A multi-algorithm optimization framework was constructed to compare the performance of Particle Swarm Optimization (PSO), Moth–Flame Optimization (MFO), Grey Wolf Optimization (GWO), and Hybrid Optimizer of PSO and GWO Merits (PSO-GWO) for off-grid power supply; additionally, a PSO-GWO was proposed to address multi-objective demands of economy, environment, and reliability for remote grid-connected power supply. Combined with system architecture design, energy management strategies, and component availability analysis, the PSO-GWO reduced 25-year LCC to $2.024 million, LPSP to 0.05, and cost of energy (COE) to $0.06254/kWh. PSO-GWO further optimized carbon emissions (CEs, operational carbon emissions only) to 2750 tons/year (14.1% lower than PSO) while maintaining LCC at $1.981 million and LPSP at 0.01. Thirty independent runs of each algorithm were conducted for statistical validation, and sensitivity analysis verified the algorithms’ robustness to PV efficiency, battery cost, wind speed fluctuations, battery price volatility, and carbon tax changes. The study also expanded the analysis to multiple climatic scenarios, providing an economical, reliable, low-carbon solution with strong generalizability. Full article

Positional consumption is spending valued mainly for relative standing rather than intrinsic usefulness. A progressive consumption tax can, in principle, reduce the social costs of status-driven spending by taxing consumption rather than saving, but it may face resistance. We examine a behavioral evaluation channel in which status quo bias and loss aversion can sustain positional consumption and reduce support for this reform. We combine a fully specified, reproducible in silico simulation of tax acceptance with a real-participant gain–loss questionnaire that benchmarks positional-choice patterns under matched items. In grouped fractional-response estimates from the simulated data, the post-condition increases predicted acceptance from about 0.11 to about 0.22 and is statistically significant (p < 0.001), while higher status quo and loss-aversion proxy intensity predicts lower acceptance and is statistically significant (p < 0.001). Policy framing increases predicted acceptance relative to the Neutral frame. In the questionnaire, loss framing shifts choices toward absolute outcomes relative to gain framing, consistent with attenuated positional motives. The framework provides a transparent way to stress test how framing and bundled communication and comprehension supports can shift acceptance of progressive consumption taxation under stated assumptions. Full article

This study develops a novel AI-based trading framework designed to consistently generate profits across cyclical bullish and bearish futures markets. Unlike conventional strategies that rely on static rules or a single predictive model, the proposed framework introduces a dual-agent deep reinforcement learning (DRL) architecture, where one agent specializes in bullish conditions and the other in bearish conditions, while a trading decision selector dynamically predicts market regimes and allocates execution accordingly. This design enables the system to adapt to regime shifts and mitigate risks arising from market volatility and extreme events. Using Mini Taiwan Stock Exchange Index Futures (MTX) as a case study, a four-year historical backtest is conducted covering multiple disruptive periods, including the tax adjustment and the Russia–Ukraine conflict. The empirical results show that, under a monthly capital reset and loss-compensation rule with a fixed investment of TWD 500,000 per month, the proposed framework achieves an average cumulative return of 2240%, an annualized return of 109%, and a Sharpe ratio of 0.31, with the cumulative ROI exceeding twice the MTX index growth over the same period. Although the Sharpe ratio remains moderate, this outcome reflects the framework’s emphasis on directional trading and absolute return maximization, where profitable trades outweigh intermittent losses despite higher short-term volatility. These findings suggest that adaptive, regime-aware DRL architectures are particularly effective for futures trading in markets characterized by frequent trend reversals, offering both methodological innovation and practical applicability under realistic market conditions, with strong returns achieved at a moderate risk-adjusted level. Full article

Thailand’s 2024 excise tax reform aimed to stimulate the tourism economy through the elimination of import tariffs and the reduction in excise rates on wine. This study evaluates the causal economic and distributional impacts of this policy intervention. The analysis employs a quasi-experimental Doubly Robust Difference-in-Differences (DR-DiD) estimator on a stratified cluster sample to isolate shifts in consumption expenditure, volume, and net ethanol intake. Results indicate a null effect for the general population, which confirms that the price floor remained prohibitive for median earners despite the tax reduction. The top income quintile conversely exhibited a statistically significant “additive premiumization” effect characterized by a surge in wine quantity without the substitution of other beverage categories. This behavioral shift generated a substantial Net Economic Loss driven by the divergence between foregone tax revenue and projected human capital productivity losses. The policy consequently functioned as a regressive fiscal transfer to the elite and created severe allocative inefficiency. These findings suggest that ad valorem tax incentives for luxury goods in emerging markets generate deadweight loss. Future policy strategies should therefore prioritize specific volumetric taxation to align fiscal incentives with public health objectives. Full article

This research focuses on the challenge of measuring the socio-economic impact of road traffic accidents (RTAs) by examining how losses are redistributed across major institutional sectors, including the government, businesses, and households. Unlike traditional cost-based approaches, the analysis relies on a modified input–output framework that captures not only the direct losses but also the indirect damage flows transmitted from one sector to another. This methodology makes it possible to reveal the multiplicative propagation of losses, determine the proportion of net costs, and quantify the transfer dependencies between institutional agents. Using compiled and adapted data for the Azerbaijani economy, the study estimates the net economic damage from RTAs at 2268.17 million manats after adjusting for internal transfers. The results show that households bear more than 47% of total losses, the enterprise sector accounts for approximately 39%, and the government absorbs nearly 13%. The model also isolates an “additional damage” component, reflecting lost income, profits, and tax revenues, and demonstrates that every 1000 RTA generates a chain reaction of interlinked costs that substantially amplifies the overall effect. The findings highlight the necessity of integrating input–output analytical approaches into the practical assessment of RTA-related economic consequences, particularly in countries with limited statistical capacity and structurally diverse institutional linkages. Full article

Despite growing research on sustainable aviation, multi-airport systems, and environmentally constrained capacity allocation, critical gaps persist. Existing studies often treat passenger choice, airline competition, and airport regulation in isolation, or evaluate environmental policies such as carbon taxation only as macro-level constraints. Consequently, the endogenous feedback among pricing, capacity reallocation, and regulatory intervention in shaping equilibrium outcomes within multi-airport systems remains underexplored, particularly within a unified dynamic framework that links low-carbon policies to operational decision-making. This study develops such a dynamic framework to support the sustainable transition of carbon-constrained multi-airport regions. Focusing on the Beijing–Tianjin multi-airport system and China’s “Dual Carbon” goals, we construct a three-layer iterative equilibrium game integrating passenger airport choice (modeled using a multinomial logit specification), airline capacity reallocation (formulated as an evolutionary game internalizing carbon taxes), and airport slot regulation (implemented through a multi-objective mechanism balancing economic revenue, hub connectivity, and environmental performance). An agent-based simulation of the Beijing/Tianjin–Nanchang route demonstrates robust convergence to a stable systemic equilibrium. Intensified competition reduces fares and improves accessibility, while capacity shifts from higher-cost Beijing airports to Tianjin Binhai Airport, whose market share rises from 10.6% to 34.0%. Airport utilization becomes more balanced, total airline profits increase slightly, and both total and per-passenger CO₂ emissions decline, indicating improved carbon efficiency despite demand growth. The results further identify a range of carbon-tax levels that jointly promote emission reduction and traffic rebalancing with limited profit loss. Full article

In the context of global climate change and carbon-neutrality goals, carbon taxes and carbon tariffs have become key policy tools for regulating corporate emissions. However, most existing studies examine these policies in isolation and overlook firms’ behavioral responses under their joint implementation, especially with product heterogeneity. This study analyzes production and emission-reduction decisions of two-country manufacturers under carbon taxation and further investigates corporate behavior and social welfare outcomes when both carbon taxes and carbon tariffs are imposed. The results show that carbon taxes enhance emission-reduction efforts, though with diminishing marginal effects. Moderate carbon tariffs further motivate exporting firms to reduce emissions, while overly high tariffs may induce market exit, particularly for high-quality manufacturers. Consumer preferences also interact with policy effects: stronger preferences for high-quality products encourage firms to expand domestic markets and increase green investments, whereas weaker preferences shift focus toward exports. Social welfare responds asymmetrically, moderate tariffs improve environmental performance, while excessive tariffs lead to trade distortions and welfare losses. Overall, this study highlights nonlinear and heterogeneous firm responses under combined carbon policies, offering insights for policy design and corporate strategy. Full article