This paper discusses how corporations have been impacted by changes in tax laws that regulate how businesses report their revenues over time. Accounting for these changes can lead corporations to manipulate income (profit) by manipulating various aspects of a company’s operations, including regular business practice, and, therefore, how much corporate taxes will be owed due to choices companies have made regarding which generally accepted accounting principles to follow (IFRS or GAAP). I will examine over 20 years of data on more than 20 global corporations that each file a public offering prospectus from 2015 through 2023 and tally to approximately 180 cases in total.
This study examines the relationship between inflation and economic growth in 13 least developed African countries from 1981 to 2019. Using Two-Step Least Squares (2SLS) and the Generalized Method of Moments (GMM), it identifies a nonlinear relationship between inflation and growth. The findings reveal an inflation threshold of 21.52%: below this level, inflation promotes economic growth, while above it, inflation negatively affects growth. Thus, high inflation hampers economic performance. The results also show that growth in these countries is mainly driven by gross fixed capital formation, population growth, and trade openness. In contrast, public spending and institutional development have a significant negative impact on economic growth. These findings highlight the importance for policymakers to consider the inflation threshold when designing monetary policies to ensure sustainable growth and effective inflation control.
This study examines the weak-form efficiency of developed and developing green financial markets using statistical tests, including unit root, autocorrelation, runs, and variance ratio tests. The analysis is based on weekly returns of two indices: the SRI KEHATI Index representing developing markets and the NASDAQ Clean Edge Energy Index representing developed markets. The sample is divided into two sub-periods: January 2, 2017–December 30, 2019, and March 2, 2022–December 30, 2024. Results showed that both markets exhibit weak-form efficiency, implying that abnormal returns cannot be consistently achieved.
Regional disparities still impact education, employment, and access to technology in Romania. The analysis of the evolution of these discrepancies over the 2018-2023 period is carried out based on regional variables on education, labour market conditions, and digital access. GIS mapping, Moran’s I, LISA cluster analysis, and PCA are used for the determination of territorial patterns and regional adaptation. The results reveal important differences between Bucharest-Ilfov and less developed regions, especially as regards the link between education, digitalization, and chances of employment. The results suggest that skill difference and technology access differences are still crucial determinants of regional development and long-term change.
This study presents a comprehensive bibliometric analysis of evacuation research, focusing on the integration of symmetry and asymmetry elements. By analyzing a dataset of scholarly papers from the ISI Web of Science database spanning 2000 to 2023, we reveal a sustained annual growth rate of 8.1% in academic interest. Key contributors, influential publications, and leading journals in the field are identified. The analysis highlights the importance of considering information symmetry/asymmetry, symmetric/asymmetric Hausdorff distance, evacuation layout symmetry/asymmetry, and symmetry-breaking behaviors of evacuees. We show that N-gram analysis techniques uncover various applications of symmetry and asymmetry in evacuation research, emphasizing their significance in addressing evacuation challenges and enhancing strategies.
This paper aims to analyze the effects of the digital economy on economic growth in low- and middle-income countries in Africa. We use a sample of 52 countries, comprising 21 low-income countries (LICs) and 31 middle-income countries (MICs), over the period 2004–2022. The two-stage generalized method of moments (GMM) estimation technique, corrected to finite sample bias of Windmeijer’s (2005), is applied to a panel model. The main results show that the digital economy has a more positive influence on economic growth in LICs than in MICs. This supports the argument that these countries are "leapfrogging" in terms of growth thanks to digitization. Otherwise, our results highlight that "Internet access" remains the dimension of the digital economy with the greatest impact on economic growth in both types of countries. Governments in African countries may invest in digital infrastructure and support to increase internet access.
Environmental pressures in the ASEAN-5 region have intensified alongside accelerated human development and rising carbon emissions driven by industrialization. This study examines the impact of human development, renewable energy consumption, and economic growth on CO₂ emissions in ASEAN-5 countries. Using annual panel data from 2000–2019, the Autoregressive Distributed Lag (ARDL) approach is employed to analyze both short-run and long-run relationships. The results show that, in the long run, human development significantly increases CO₂ emissions, while renewable energy consumption and economic growth contribute to emission reductions. In the short run, human development and renewable energy consumption have no significant effect, whereas economic growth exerts a positive and significant impact on CO₂ emissions. The findings also support the Environmental Kuznets Curve (EKC) hypothesis in the ASEAN-5 region. These results underscore the importance of promoting clean energy transitions and strengthening human development policies to achieve sustainable economic growth and carbon emission mitigation.
This paper examines the evolution of government expenditure, tax policy, and effective tax rates in Greece over the post-transition period 1974–2018. Using a comprehensive fiscal dataset and the Martinez-Mongay methodology for estimating effective tax rates, the study provides an integrated view of how expenditure dynamics and tax structures shaped the country’s macroeconomic performance before and after key political and economic shifts. The analysis highlights the interplay between fiscal consolidation episodes, tax reforms, and expenditure pressures, while identifying structural weaknesses—particularly the heavy reliance on indirect taxation and the volatility of public investment. Empirical results show that shifts in effective tax rates significantly affected revenue composition and that expenditure rigidities constrained fiscal adjustment capacity. The findings contribute to a deeper understanding of Greece’s fiscal trajectory, offering implications for sustainable tax policy design and long-term public finance management.
This paper analyses the compatibility between the expansion of military spending generated by the SAFE (Strategy, Armament, Financing, Efficiency) programme and the long-term fiscal sustainability of the European Union Member States, with a focus on the cases of Romania, Poland and Hungary. Starting from a dual theoretical framework: the crowding-out effect versus the Keynesian multiplier, the research applies the public debt sustainability equation (Δd = r − g · d + pb) and the fiscal multiplier analysis to assess the allocative efficiency of the programme. The results of the longitudinal comparison (2021–2026) demonstrate that the economic impact of the SAFE programme is non-linear and critically dependent on industrial absorption capacity: Poland transforms defence into a competitive advantage (multiplier > 1), while Romania experiences a structural deterioration in the trade balance (−1.2% of GDP). The conclusions emphasize that the economic sustainability of SAFE requires the localization of production, the implementation of the Fiscal Golden Rule, and the stimulation of public-private partnerships.
Artificial intelligence is commonly discussed in terms of information access, automation, productivity, and decision support. While these functions are important, they may not fully capture the broader significance of adaptive AI systems. Unlike many previous informational technologies, adaptive AI systems engage in ongoing interaction that can adapt to the needs, questions, communication styles, and understanding of individual users. This creates opportunities for a more personalized and responsive form of engagement with information. This article explores the possibility that the importance of adaptive AI extends beyond the information it provides. Through repeated adaptive interaction, individuals may encounter and practice new approaches to reasoning, communication, information organization, perspective exploration, and problem-solving. Over time, some of these patterns may become incorporated into how individuals learn, think, communicate, and engage with new situations. The article argues that adaptive AI systems may increasingly function as a source of pattern formation alongside the human relationships, educational experiences, professional environments, and social contexts that have historically contributed to human development. As individuals integrate patterns encountered through adaptive AI interaction with those acquired from other sources, new forms of pattern merging may emerge within the developmental process itself. Building on perspectives from developmental psychology and historical accounts of technological change, this article proposes a framework for understanding adaptive AI as a participant in processes of learning and development rather than solely as a tool for information retrieval. The article concludes that the long-term significance of adaptive AI may lie not only in what it knows, but also in its capacity to support the acquisition, refinement, and application of patterns that contribute to human development across different areas of life.
Household financial wealth is often treated as a visible sign of economic strength, yet its gross size offers only a partial view of how household finance relates to development. The European evidence challenges the idea that larger household financial assets are, by themselves, associated with stronger economic performance. Gross financial wealth does not provide a robust growth signal when separated from liabilities, portfolio structure and country-specific conditions. The stronger pattern emerges from net financial strengthening, where improvements in the household sector’s financial position after debt is taken into account are positively associated with real economic performance. This distinction changes the interpretation of household wealth: the relevant issue is not simply how much financial wealth households hold, but whether that wealth improves the resilience and net capacity of the household balance sheet. The findings support a balance-sheet quality perspective in which financial assets become economically meaningful only when they translate into stronger net positions. Economic development is therefore connected less with the visible accumulation of gross household wealth and more with the financial strength that remains once liabilities are considered.
Objective: To construct a conceptual innovatory formulation of the Resource Distribution Index (RDI) integrating the distribution of income and the level of accessibility of key resources. This presents a multidimensional perspective of inequality at the micro-level the study attempts to address the issue of inequality paradox at the micro and macro perspective simultaneously. Study/Method: The study is of the archival type and is based on secondary data research and publications. The study constructs the RDI, and then attempts to assess empirically the relation of RDI scores to Gini Index and Palma Ratio. Results: RDI, paradoxically, in relation to the income measure that suggests more equality, there existed a greater number of poorly accessible key resources. Next, the RDI with the measure of access to resources and income embedded ratio over-spilled limitlessly the other resources in the accessible ratio of the income metrics. Therefore, the RDI the basis of is a perfect platform in establishing the feasibility of the policy recommendations. The assumptions and results of the RDI are congruent with the prevailing, modern, and religious texts. Study Limitations: The study is bound to a phenomenon that involves secondary data that lacks particular local data. The RDI’s applicability may need to be modified to the specific circumstances of the studied population. The RDI can be enhanced by collecting primary data in the next study. Implication: The RDI provides direct social interventions centered on fair resource distribution to policymakers, urban developers, and social community organizers. The RDI, accompanied by additional indicators, provides a framework to communities for assessing and measuring social deprivation, which goes beyond income, inequality. The RDI can be used as a benchmark for other nations, and Australia can similarly, be positioned in pursuit of its goal for Inclusive and Sustainable Development. Novelty/value: A key element of this study is the development of a novel composite index of inequality that measures income and resource accessibility, providing additional depth to the resource inequality index, and presenting a framework for local interventions designed to achieve change at both the micro and macro levels.
The proliferation of artificial intelligence technologies has fundamentally transformed marketing practices in global markets, shifting organizational paradigms from intuition-based decision-making toward data-driven strategic frameworks. This study investigates how AI-driven marketing models function as sources of sustained competitive advantage in contemporary global commerce. Employing a systematic analysis of theoretical frameworks, empirical evidence, and organizational implementations, the research examines mechanisms through which machine learning algorithms, predictive analytics, and autonomous optimization systems enhance marketing effectiveness across heterogeneous market contexts. Findings reveal that AI-driven marketing models generate competitive advantages through superior customer targeting precision, real-time resource allocation optimization, enhanced attribution accuracy, and continuous adaptive learning capabilities. However, competitive advantage sustainability depends critically on organizational capabilities spanning data infrastructure maturity, analytical talent acquisition, ethical governance frameworks, and cultural adaptability. The study contributes theoretical insights regarding the resource-based foundations of AI-driven competitive advantage while providing practical implications for marketing leaders navigating digital transformation imperatives in global markets.
The share of tourism in GDP is below 3% in Romania, while the PIGS countries are recognized for the significant impact of tourists influx on socio-economic development. Following the analysis carried out at national level, I found a stronger relationship between the dynamics of the tourist flows and that of GDP per capita / employed population in PIGS countries, compared to Romania, where the linkage is weaker. At regional level, significant divergences were found, especially in terms of the percentage change in the employed population, both between PIGS and Romania NUTS 2 regions, and between the regions of Romania.
This paper analyzes the contribution of inclusive business models to multidimensional poverty. The survey data were collected in Burkina Faso in 2019 from households that were beneficiaries and nonbeneficiaries of these inclusive initiatives. The methodology is based on the approach developed by Alkire and Foster (2011) for calculating the multidimensional poverty index. Next, a semi-ordered recursive bivariate probit model was adopted to correct for endogeneity bias between participation in inclusive business models and multidimensional poverty. The results identify participation in IBMs, income, associative membership, age, and bank card ownership as the key determinants of multidimensional poverty. Specifically, participation in IBMs reduces the likelihood that a household will fall into multidimensional poverty by 31.25%, confirming their role in improving well-being. Therefore, the promotion of these models by policymakers is a strategic lever for social development.
The paper examines the changing nature of consumer behaviour in the digital business age, and how digital platforms, marketing approaches, and behavioural economics are influencing the relationship between the youth entrepreneurs and contemporary consumers. It was a quantitative study that was carried out in India amongst urban, sub-urban and rural areas through a structured questionnaire that was filled by 900 individuals to ensure generalizability. The research used four central dimensions of digital platform influence, digital marketing effectiveness, consumer trust, and entrepreneurial adaptability by employing statistical techniques based on SPSS with correlation and regression tests. The results showed that the level of consumer perceptions and purchasing behaviour is greatly affected by the digital platform presence, and digital marketing tactics, including social media marketing, SEO, and influencer partnerships, positively impact ROI and brand performance by great margins. Moreover, consumer trust turned out to be a decisive factor of loyalty and preference to youth-led entrepreneurship. Another important observation of the analysis was the positive correlation of entrepreneurial challenges with adaptability, in which, increased digital complexities promote innovation and learning. The findings highlight the complexities of the relationship between psychology, technology, and marketing strategy in the development of sustainable digital entrepreneurship. This research will have an impact on the literature in behavioural economics and digital marketing as it provides practical information to young entrepreneurs aiming to operate in the ever-changing consumer ecosystem.
This paper investigates the main factors influencing migration inflows within the European Union over the 2013-2024 period. Using a dynamic panel data approach based on the Arellano-Bond GMM estimator, it accounts for persistence in migration patterns and potential endogeneity in socio-economic indicators. The research focuses on the differences between high- and low-inflow countries regarding "push" and "pull" migration factors. Primary results show that labour cost increases act as a significant "pull" factor in high-immigration states, whereas in low-immigration countries it loses statistical significance. Notably, the NEET rate emerges as the strongest inhibitor of immigration across the EU-27, having a substantial negative impact in the low-inflow country model. Moreover, the old age dependency ratio behaves like a "push" factor, while GDP per capita growth positively shapes migration dynamics. These findings suggest that EU migration policies should address the asymmetrical influence of labour cost on intra-EU migration through targeted interventions.
This paper examines whether, beyond its conventional aims of price stability, monetary policy is a determinant of inclusive social development in Africa. The analysis is based on a panel of African countries covering the period 2010–2022. The empirical strategy employs three complementary econometric models: a fixed-effects model to capture country-specific variations, a two-stage least squares (2SLS) regression to address endogeneity, and an instrumental-variable quantile regression (IV-QR) to study the heterogeneity impact according to levels of inclusive development. The empirical results provide robust evidence that monetary policy has positive and causal effects on inclusive human development in Africa. Bank liquidity, monetary depth, and real interest rate stability significantly improve the inequality-adjusted human development index (IHDI). Instrumental variable quantile regressions reveal remarkably stable coefficients across the conditional distribution of inclusive development, indicating the absence of strong heterogeneity across countries. Furthermore, alternative estimations show that monetary policy reduces social and income inequalities while enhancing human development. These findings suggest that monetary policy operates as a macrostructural lever for inclusive development rather than a purely distributive instrument. These findings call for monetary authorities to strengthen macroeconomic stability, enhance liquidity management, and foster financial deepening as strategic tools to promote inclusive human development in African economies.
This research examines the effect of institutional quality on economic growth in West Africa. Several dimensions of institutional quality are used: the composite index of institutional quality, three aggregate indicators (economic, political, and institutional governance), and the World Bank’s six governance indicators. Using a sample of 15 countries, we estimate a panel data model using the Augmented Mean Group method, whose robustness is reconfirmed by the Driscoll-Kraay method over the period 2000-2023. We obtain three main results: first, the composite institutional quality index promotes economic growth. Second, economic, political, and institutional governance stimulate economic growth. Ultimately, the six governance indicators have a positive influence on economic growth. The results suggest a general improvement in the quality of institutions. In particular, these countries must fight corruption, have sound and robust regulations, strengthen the principles of the rule of law, have qualified administrative staff, maintain political stability, and promote democratic principles.
This paper investigates the transmission mechanisms of geopolitical risk and commodity price volatility to Morocco’s monetary policy and assesses the central bank’s response to externally driven inflationary pressures. Using monthly data from 1995-2025, a Bayesian Vector Autoregression (BVAR) model comprising six macroeconomic variables is estimated. The results indicate that shocks to geopolitical risk, crude oil, and cereal prices exert persistent inflationary effects through imported inflation channels. The policy rate responds with a lag, consistent with its periodic decision-making framework, underscoring the structural constraints faced by monetary authorities in managing externally induced inflation and requiring fiscal coordination and targeted supply-side measures.
