Search Results (453)

Among developed-market stock exchanges, the NZX is distinctive. Its imputation credit system and capital-gains-tax exemption create financial incentives for firms to distribute earnings that have no close parallel elsewhere, yet what actually drives payout decisions at the firm level has never been tested in a multivariate panel framework. We analyzed 116 NZX-listed companies from 2017 to 2023. The results show that revenue and net profit prove to be the dominant positive predictors of dividend payout; cash flow and shareholders’ equity are negatively associated with the payout, suggesting that the firms prioritize capital retention in a manner consistent with the pecking order theory. Market capitalization adds nothing once earnings quality is accounted for in the model. Firms in which women occupied more than half of board seats paid, on average, seventeen times more in dividends than those with minimal female representation, a gap sustained without exception across all seven years. Domestic firms outpaid multinational firms throughout and, by 2023, had exceeded their own pre-period baseline, while multinationals had not. Our findings have implications for income-focused investors, for boards weighing payout strategies, and for policymakers assessing the case for diversity requirements. Full article

In this paper, we formulate a new endogenous growth framework designed for the artificial intelligence era. We theorize AI as a hybrid production factor, possessing the non-rivalrous properties of public knowledge and the rivalrous constraints of computing power. By endogenizing the role of public finance, the model demonstrates that strategic government investment in digital infrastructure and AI-specialized human capital acts as a primary catalyst for the marginal productivity of private capital. We derive the Theorem of Digital Optimality, identifying the optimal allocation of tax revenue between physical hardware and intangible intelligence. Our findings suggest that in an AI-driven economy, public spending generates a significant crowding-in effect, shifting the private investment frontier upward. The model warns that failure to optimize these public inputs leads to digital secular stagnation, in which the lack of sovereign digital platforms bottlenecks private-sector innovation. Full article

The deployment of grid-side independent energy storage stations (IESSs) is critical for managing the volatility introduced by high renewable energy penetration. However, investment in IESSs faces significant uncertainties, including fluctuating spot prices, policy changes, and equipment degradation, which traditional static valuation methods fail to address adequately. To bridge the gap between operational optimization and investment decision-making, this study proposes a novel framework integrating a mixed-integer linear programming (MILP) operational optimization model with the Black-Scholes-Merton Model (BSM). The MILP model explicitly incorporates capacity degradation, multi-market revenue structures and comprehensive cost expenditures. The BSM, with volatility estimated via Monte Carlo simulation, quantifies the value of delaying investment under different policy scenarios. Results indicate that capacity price subsidies provide superior early-stage cash flow relief compared to tax incentives, and their combination yields a synergistic effect, increasing the maximum tolerable electricity price decline rate from 4.08% to 8.88%. Furthermore, in pessimistic scenarios, the real options approach identifies positive returns (up to 8.02 million CNY) from delayed investment, whereas the net present value method would suggest immediate rejection. Sensitivity analysis reveals that construction cost and frequency control mileage are the most influential factors. This framework offers a robust quantitative tool for IESS investment timing and regional policy design. Full article

This study examines the effect of institutional quality on tax revenue mobilization in 10 selected Sub-Saharan African (SSA) countries spanning from 2002 to 2023. The period was chosen because it captures a significant era of fiscal and institutional reforms across Sub-Saharan Africa. The data explored in this study originate from the World Development Indicators (WDI) dataset. The data includes tax revenue mobilization, institutional quality components such as regulatory quality (REQ), voice and accountability (VOA), control of corruption (COC), rule of law (ROL) and government effectiveness (GOE) and political stability (POS). The study also explored some other control variables such as GDP Growth, macroeconomic stability (Inflation) and international economic integration (FDI Inflows and Trade Openness). The study explored total tax revenue as a percentage of GDP to proxy tax revenue mobilization. Utilizing a Pooled Mean Group (PMG) Autoregressive Distributed Lag (ARDL) estimation technique, the study analyzes the distinct short-run and long-run dynamics of fiscal capacity. The empirical results reveal a robust long-run cointegrating relationship, evidenced by a statistically significant and negative Error Correction Term (ECT) of −0.1858, which suggests that an 18.6% annual deviation from equilibrium is corrected within the following year. The long-run estimates indicate that institutional quality is a pivotal catalyst for tax. Additionally, inflation and trade openness exhibit significant and positive long-run effects, while Foreign Direct Investment (FDI) exerts a significant damping effect on tax revenue, likely due to aggressive tax incentives. Conversely, the short-run results revealed a significant effect of institutional quality, which suggests that stricter regulations and administrative overhauls may cause immediate transition costs and compliance shocks. Robustness checks using disaggregated institutional quality indicators, which include control of corruption, rule of law and government effectiveness, consistently validate the primary findings. The study concludes that while institutional reforms may disrupt revenue collection in the short term, they are indispensable for building a sustainable long-term social contract and expanding the formal base. Policymakers should prioritize institutional transparency and trade integration while rationalizing FDI-related tax holidays. Full article

This paper examines the role of fiscal policy in shaping CO₂ emissions for a sample of 23 countries, including the Euro Area, the United States, Canada, and China, over the period 2000–2023. The analysis moves beyond aggregate fiscal measures to identify taxes and expenditure categories contributing most to reduce CO₂ emissions. We investigate the transmission channels through which fiscal policy affects environmental outcomes and address potential non-linear fiscal effects. The study also highlights the critical role of recycling fiscal resources toward environmentally relevant expenditures. The System GMM results suggest that some market-based mechanisms and targeted public expenditure contribute to reducing CO₂ emissions, while other fiscal tools exhibit opposite or context-dependent effects. A non-linear relationship is detected for compliance emissions. Moreover, results reveal that supply-side and demand-side transmission channels generate contrasting effects on emissions. Finally, the effectiveness of environmental fiscal policies is shown to depend critically on the pattern of fiscal revenue recycling. These results provide important insights for the design of effective fiscal strategies aiming to achieve climate objectives. Full article

In this study, we conduct an exploratory and econometric assessment of the multidimensional impact of recent immigration, predominantly Venezuelan, on Peru (2000–2022). Utilizing 4565 time-series indicators, we apply a two-stage methodology: Pearson correlations to identify baseline exploratory associations, followed by Ordinary Least Squares (OLS) with temporal controls and First Differences models to isolate genuine structural effects from time-trend artifacts and spurious correlations. Econometric validation refines oversimplified public narratives. Socially, immigration robustly correlates with increased food insecurity, localized detainments, and a reduced youth demographic, while aggregate crime complaints are identified as a time-trend artifact. Economically, migration structurally stimulates income for the poorest 40% and broadens financial inclusion, despite negatively impacting aggregate macroeconomic consumption. Educationally, the influx of skilled migrants robustly drives scientific publications and increases average formal education years, though it introduces challenges like delayed primary school attendance and a negative shift in educational gender parity. Finally, perceived impacts on central government expenditures and consumption tax revenues are econometrically isolated as either time-trend artifacts or spurious correlations rather than direct migratory consequences. This approach separates true structural responses from historical inertia, providing a balanced, quantitative perspective on migration in Peru. Full article

This study presents a systematic literature review of 68 peer-reviewed articles (2015–2025) on artificial intelligence in tax compliance and evasion mitigation. Using the PRISMA 2020 protocol and textometric analysis via IRAMUTEQ software, we map publication trends, geographic distribution, and three research paradigms: machine learning and predictive modeling; artificial intelligence, technology and tax compliance; and government, financial development and revenue administration. The CIMO (Context–Intervention–Mechanism–Outcome) framework structures our synthesis of how institutional conditions shape intervention design and why identical technologies produce divergent outcomes across settings. While existing reviews have focused primarily on detection metrics without theorizing institutional boundary conditions, behavioral dynamics without addressing governance capacity, or ethical deficits without a theoretical framework, this study constructs the Adaptive AI Tax Compliance Framework (AAITCF), a context-sensitive implementation roadmap differentiated across three institutional maturity tiers. The results indicate that AI achieves high detection accuracies in digitally mature economies, yet effectiveness is contingent on data quality, governance capacity, and organizational readiness. Developing countries face structural asymmetries, infrastructural deficits, and human capital gaps that constrain algorithmic performance even where technical sophistication is high. The AAITCF treats context as constitutive of intervention effectiveness and identifies underexplored areas regarding causal pathways from AI deployment to long-term institutional change, taxpayer trust, and equitable fiscal governance. Full article

This study investigates how a territorially uneven distribution of informal economic activity affects subnational fiscal capacity and potentially distorts fiscal equalization systems. Using a Multiple Indicators, Multiple Causes (MIMIC) model, we estimate the size of the informal economy across the eight statistical regions of North Macedonia over the 2008–2023 period. The estimated shares of regional informality are subsequently linked to indicators of fiscal dependence and local revenue performance. The findings suggest that regions characterized by larger informal economies tend to exhibit greater dependence on intergovernmental transfers and weaker effective fiscal autonomy. The analysis further indicates that intergovernmental transfer systems relying primarily on regional gross domestic product and realized tax collections may systematically underestimate the true economic potential of highly informal jurisdictions. The paper contributes to the literature by conceptualizing informality not merely as an informal economic activity, but as a structural distortion affecting the measurement of fiscal capacity and the functioning of decentralized public finance systems. Full article

Taxing multinational corporations raises significant government revenue to support progress towards the Sustainable Development Goals (SDGs).This study examines Philips, a multinational corporation that publicly reports country-by-country data on revenue, profits, taxes, employees and tangible assets, using the Government Revenue and Development Estimations (GRADE) econometric model to estimate the development impact of its corporate income tax contributions. Tax payments do not always reflect actual economic activity in host countries due to profit shifting. This study also assesses the degree to which reported profits align with economic activity. Results indicate Philips’ tax payments make a meaningful positive contribution to sustainable development: government revenue equivalent to these payments enables over 1100 additional children to attend school daily and advances SDG progress on basic water (8100 people), sanitation (13,400 people), clean fuels (28,000 people) and electricity (1700 people). However, analysis reveals some misalignment between reported profits and economic activity across countries, suggesting unrealised potential in Philips’ development contribution. Modelling a reallocation of taxing rights to host countries where economic activity occurs using unitary tax with formulary apportionment indicates that annual tax payments may average $78 million higher in constant 2015 USD, potentially enabling 900 more children to attend school and expanding access to basic water (6500 people), sanitation (9600 people), clean fuels (22,600 people) and electricity (7400 people). These findings highlight the value of transparent country-by-country reporting as a foundation for evidence-based tax policy reform and the significant development gains from Philips’ tax payments and greater gains if profits were better aligned with economic activity. Full article

Active labor market policies (ALMPs) targeting self-employment have become a well-established and relevant instrument within employment promotion strategies across many European countries. However, despite their strategic and economic importance, there is limited evidence on their potential performance prior to implementation. This paper aims to address this gap by conducting an ex-ante cost–benefit simulation of different types of ALMPs designed to promote self-employment in Spain. The methodology is based on estimating public costs per beneficiary and quantifiable potential benefits, including avoided welfare payments, additional tax revenues, and the generation of economic activity. These benefits are adjusted using two key parameters: additionality (the proportion of the effect genuinely attributable to the policy) and persistence (the duration of the impact over time). In addition, three sensitivity scenarios (conservative, baseline, and favorable) are developed. The results suggest that financing and access to credit policies exhibit the most robust returns, while direct subsidies, general tax incentives, and emergency policies are more sensitive to intervention design features. Consequently, the effectiveness of ALMPs targeting self-employment depends fundamentally on their ability to align with the specific frictions faced by potential entrepreneurs and on the persistence of their effects. Full article

Achieving sustainable development requires decoupling economic growth from fossil fuel dependence—a challenge that places carbon pricing at the intersection of environmental policy, economic efficiency, and social equity. Carbon taxation is widely regarded among economists as the most cost-effective instrument for reducing greenhouse gas emissions, yet the United States has not adopted a federal carbon price. This study examines the macroeconomic and sectoral consequences of a hypothetical federal carbon tax using the Standard GTAPv7 computable general equilibrium model calibrated to GTAP Database version 12 (2023). A tax rate of 27.7% is derived from the Regional Greenhouse Gas Initiative (RGGI) average auction price of USD 12.81/t CO₂ for 2023—the lowest among active U.S. state carbon programs—and applied as a production tax shock to the fossil fuel sector. Simulations at the California (USD 32.93/t CO₂) and Washington state (USD 53.10/t CO₂) prices provide sensitivity bounds. Under the baseline scenario, U.S. real GDP falls by 0.09%, unskilled employment declines by 0.17%, and fossil fuel production and exports contract sharply. Outside the fossil fuel complex, most sectors record output and export gains, and total U.S. net exports improve by 0.33 percentage points. Bilateral GDP spillovers across eighteen trading partners range from −0.17% (South Korea) to −0.01% (Australia), principally through fossil fuel trade exposure. The results demonstrate that a federal carbon tax at the RGGI price can achieve meaningful emissions reduction at a contained macroeconomic cost, supporting the environmental pillar of sustainability. The concentration of adjustment burdens on unskilled workers highlights the social sustainability challenge of ensuring a just transition. The production reallocation from fossil-intensive to non-fossil sectors is consistent with the circular economy framework and contributes to long-run economic sustainability by reducing dependence on finite, non-renewable resources. Revenue recycling, just-transition provisions, and carbon border adjustment are identified as complementary policy instruments essential for aligning carbon taxation with the integrated environmental, economic, and social dimensions of sustainable development. Full article

The rapid expansion of housing financialization (REF) has profoundly reshaped China’s subnational fiscal landscape, yet the dynamic nature of this relationship remains under-explored. This study investigates how the impact of REF on fiscal deficits (DB) evolves over time and identifies the specific transmission channels mediating this influence. First, we construct a multidimensional REF index by integrating enterprise, household, market, financial, and industry indicators via the fuzzy-TOPSIS method. A Markov Regime Switching model identifies three distinct volatility regimes, revealing that REF dynamics are highly sensitive to policy shifts and exhibit significant path dependency. Second, using a Time-Varying Parameter Vector Autoregression model, we find that REF initially functioned as a fiscal stabilizer providing short-term revenue relief; however, as financialization deepened, REF transformed into a procyclical driver of deficit expansion. Third, we further decompose this mechanism, demonstrating that land finance (LAND) and local government debt (UID) amplify systemic fiscal fragility as dynamic mediating channels. Finally, due to the unsustainability of the current “real estate-land-debt” model, we propose policy interventions including the institutionalization of fiscal-debt firewalls, the formation of counter-cyclical fiscal risk reserve funds, and an accelerated transition toward a stable, tax-oriented revenue structure to mitigate systemic risks. Full article

Advances in probability distributions are important for modelling complex data across fields such as actuarial science, environmental science, biomedical science, economics, finance, and insurance. Classical distributions often have limitations when dealing with highly skewed data, heavy tails, or unusual failure patterns. To address these challenges, this study introduces the Sine Inverse Lomax Burr III distribution, a new flexible model that combines the tail behaviour of the Burr III distribution with the skewness-control properties of the sine inverse transformation. Statistical properties, including quantiles, moments, moment generating functions, and order statistics, are derived. Some risk measures, including the value at risk, tail value at risk, and tail variance, are derived and studied. Parameter estimation is performed using five different estimation techniques: maximum likelihood estimation, least squares, weighted least squares, percentile matching, and Anderson–Darling. The usefulness of the proposed model is demonstrated using monthly tax revenue data. The results show that the SILBIII distribution performs better than the competing distributions. The proposed model is an alternative model suitable for modeling data in finance, actuarial, and related fields. Full article

Over the past decade, Portugal has increasingly focused on public policies that promote healthy eating, driven by growing concerns about the population’s health and its social, economic, and political effects. These policies aim to reduce unhealthy eating habits, which are major risk factors for disease, and to reduce the overall disease burden. Tax measures are specifically intended to curb the consumption of foods high in sugar, salt, and saturated fats to prevent chronic non-communicable diseases such as obesity, type 2 diabetes, and cardiovascular disease. This article analyzes the measures adopted in Portugal to reduce sugar consumption and examines their effects on tax revenue and consumption volume. Using document analysis, the results indicate a decrease of 3853 tons in sugar consumption and tax revenue of 432 million euros from taxing sugary drinks and sweeteners since 2017. Although significant progress has been made, including product reformulation to reduce sugar content, challenges remain. It is essential to continue and expand these policies to other products, along with ongoing impact assessments, to foster a healthier future in line with the World Health Organization’s guidelines for 2030. Full article

This study examines how digital tax transformation contributes to fiscal sustainability through the interaction of technological, organizational, and institutional factors. Using a systematic literature review (SLR), the study synthesizes evidence on digital tax administration to identify key drivers of transformation. The findings indicate that digital technologies improve tax compliance, administrative efficiency, and transparency. However, technological adoption alone is insufficient to ensure sustainable outcomes. Organizational capabilities play a critical role in translating digital investments into performance, while institutional environments shape the effectiveness of reform implementation. In addition, temporal dynamics highlight that early policy and institutional decisions influence long-term transformation outcomes. These findings suggest that successful digital tax reform requires not only technological investment but also strong organizational capacity and supportive institutional frameworks. Policymakers should prioritize integrated reform strategies, strengthen human capital, and ensure regulatory alignment to achieve sustainable fiscal outcomes. This study contributes by providing an integrated framework that explains how digital transformation supports sustainable revenue mobilization and offers practical guidance for digital government reform. Full article