This study investigates the impact of Value Added Tax on Economic Development and Human Capital Development from 1994 to 2022. Employing a longitudinal research design, the study utilizes data specific to Nigeria and obtained from the office of the Federal Inland Revenue Service (FIRS), the Statistical Bulletin of the Central Bank of Nigeria (CBN), and the World Bank. The collected data is then analyzed using the Johansen Co-integration, Vector Error Correction Model, and Vector Autoregressive analysis technique. The research establishes a connection between Value Added Tax (VAT) and the Exchange rate, demonstrating their impact on Economic Development and Human capital development in Nigeria. The verdicts show that both VAT and Exchange Rate significantly impact both Economic Development and Human Capital Development, though negatively. However, these findings are not meant to discourage but rather to serve as a catalyst for change. The recommendations outlined in the study emphasize the importance of training, oversight, exchange rate stabilization, investment in education, and financial security in promoting Economic Development and Human Capital Development in Nigeria. Tax regulatory authorities should improve management of VAT funds to ensure they are utilized for developmental objectives. Finally, organizations such as the EFCC must remain steadfast in their commitment to preventing the misuse or diversion of VAT funds meant for Capital Expenditure and the development of the nation’s human resources, thereby safeguarding the financial security of the government and the nation as a whole.
Regional economics. Space in economics, Economics as a science
The Ethereum blockchain network enables transaction processing and smart-contract execution through levies of transaction fees, commonly known as gas fees. This framework mediates economic participation via a market-based mechanism for gas fees, permitting users to offer higher gas fees to expedite pro-cessing. Historically, the ensuing gas fee volatility led to critical disequilibria between supply and demand for block space, presenting stakeholder challenges. This study examines the dynamic causal interplay between transaction fees and economic subsystems leveraging the network. By utilizing data related to unique active wallets and transaction volume of each subsystem and applying time-varying Granger causality analysis, we reveal temporal heterogeneity in causal relationships between economic activity and transaction fees across all subsystems. This includes (a) a bidirectional causal feedback loop between cross-blockchain bridge user activity and transaction fees, which diminishes over time, potentially signaling user migration; (b) a bidirectional relationship between centralized cryptocurrency exchange deposit and withdrawal transaction volume and fees, indicative of increased competition for block space; (c) decentralized exchange volumes causally influence fees, while fees causally influence user activity, although this relationship is weakening, potentially due to the diminished significance of decentralized finance; (d) intermittent causal relationships with maximal extractable value bots; (e) fees causally in-fluence non-fungible token transaction volumes; and (f) a highly significant and growing causal influence of transaction fees on stablecoin activity and transaction volumes highlight its prominence.
This study presents a comprehensive techno-economic analysis of gray, blue, and green hydrogen production pathways, evaluating their cost structures, investment feasibility, infrastructure challenges, and policy-driven cost reductions. The findings confirm that gray hydrogen (1.50-2.50/kg) remains the most cost-effective today but is increasingly constrained by carbon pricing. Blue hydrogen (2.00-3.50/kg) offers a transitional pathway but depends on CCS costs, natural gas price volatility, and regulatory support. Green hydrogen (3.50-6.00/kg) is currently the most expensive but benefits from declining renewable electricity costs, electrolyzer efficiency improvements, and government incentives such as the Inflation Reduction Act (IRA), which provides tax credits of up to 3.00/kg. The analysis shows that renewable electricity costs below 20-30/MWh are essential for green hydrogen to achieve cost parity with fossil-based hydrogen. The DOE's Hydrogen Shot Initiative aims to lower green hydrogen costs to 1.00/kg by 2031, emphasizing the need for CAPEX reductions, economies of scale, and improved electrolyzer efficiency. Infrastructure remains a critical challenge, with pipeline retrofitting reducing transport costs by 50-70%, though liquefied hydrogen and chemical carriers remain costly due to energy losses and reconversion expenses. Investment trends indicate a shift toward green hydrogen, with over 250 billion projected by 2035, surpassing blue hydrogen's expected 100 billion. Carbon pricing above $100/ton CO2 will likely make gray hydrogen uncompetitive by 2030, accelerating the shift to low-carbon hydrogen. Hydrogen's long-term viability depends on continued cost reductions, policy incentives, and infrastructure expansion, with green hydrogen positioned as a cornerstone of the net-zero energy transition by 2035.
This study explores the economic value of Aleppo pine forests, a unique and threatened ecosystem in the border region of central Tunisia. These forests play a vital role in supporting small rural communities, but face increasing pressures and restrictions on their use. This research aims to assign a monetary value to forest conservation, considering the region's specific socio-economic context. Strategies for empowering local residents as key actors in developing sustainable cross-border initiatives are further investigated. Employing the contingent valuation method, a survey of 350 local residents and international users was conducted to assess their willigness to pay fo forest conservation efforts. Logistic regression analysis revealed that sociodemographic factors, such as monthly income and preferred payment method, significantly influence both and the likehood of participation. These findingd highlight the feasibility and importance of reconciling economic development with ecological sustainability in this critical region.
Семья является основой многих социальных институтов и вносит огромный вклад в развитие региона и страны в целом. Доступность жилья служит одним из индикаторов уровня жизни населения в регионе, что в конечном итоге определяет его рейтинг. В работе предлагается использование показателя «коэффициент доступности жилья», базирующегося главным образом на фазах создания и становления ячейки общества (семьи), что позволяет учитывать влияние жизненных обстоятельств (препятствий) на пути к приобретению жилья для конкретного домохозяйства в конкретном регионе. Данный показатель включает в себя две составляющие: первая — константа, определяющая период формирования накоплений семьей за время от начала беременности до достижения ребенком возраста 1,5 года, вторая — период выплаты ипотеки. Рассматриваемый коэффициент доступности жилья был апробирован на данных в целом по РФ и по двум регионам ЦФО (с самой низкой и высокой стоимостью жилья). В работе подчеркивается, что показатель доступности жилой недвижимости должен иметь не абстрактное значение, а конкретное, которое можно воспринять и представить. В статье был проведен сравнительный анализ авторской и общепринятой методик в целом по Российской Федерации за период 2006–2021 гг. В ходе проведенного анализа было замечено значительное улучшение показателя доступности жилья в конце анализируемого периода. Этому факту значительно поспособствовали наличие и рост величины материнского капитала, разрешение его использования в качестве первоначального взноса, сокращение банками величины первоначального взноса и ставки по ипотеке. Авторская методика более наглядно подтвердила гипотезу, предполагающую, что жизненные обстоятельства (преграды) значительно влияют на доступность жилья, существенно повышая значения коэффициента доступности жилья. Полученные результаты исследования могут быть использованы при составлении регионального рейтинга в целом и оценки жилищной сферы региона в частности.
Abdullah Al Abrar Chowdhury, Azizul Hakim Rafi, Adita Sultana
et al.
The escalating challenge of climate change necessitates an urgent exploration of factors influencing carbon emissions. This study contributes to the discourse by examining the interplay of technological, economic, and demographic factors on environmental sustainability. This study investigates the impact of artificial intelligence (AI) innovation, economic growth, foreign direct investment (FDI), energy consumption, and urbanization on CO2 emissions in the United States from 1990 to 2022. Employing the ARDL framework integrated with the STIRPAT model, the findings reveal a dual narrative: while AI innovation mitigates environmental stress, economic growth, energy use, FDI, and urbanization exacerbate environmental degradation. Unit root tests (ADF, PP, and DF-GLS) confirm mixed integration levels among variables, and the ARDL bounds test establishes long-term co-integration. The analysis highlights that AI innovation positively correlates with CO2 reduction when environmental safeguards are in place, whereas GDP growth, energy consumption, FDI, and urbanization intensify CO2 emissions. Robustness checks using FMOLS, DOLS, and CCR validate the ARDL findings. Additionally, Pairwise Granger causality tests reveal significant one-way causal links between CO2 emissions and economic growth, AI innovation, energy use, FDI, and urbanization. These relationships emphasize the critical role of AI-driven technological advancements, sustainable investments, and green energy in fostering ecological sustainability. The study suggests policy measures such as encouraging green FDI, advancing AI technologies, adopting sustainable energy practices, and implementing eco-friendly urban development to promote sustainable growth in the USA.
We demonstrated the analogy between Economics and Gauge Theory of Plasticity and used it to describe the relationship between money supply and inflation at the economic market. The received equations of economical dynamics in phase space are similar to the plasticity equations and economic variables - choice, competition and profit correspond to the state of the market with inflation. We described the meaning of equations and the role of its variables in the stabilization mechanism of the market with inflation. The equation of market equilibrium including the Profit turnover, time changes of competition, capital and choice was discussed in detail.
The study examined the market profile and status of Electronic National Agriculture Market (e-NAM) in Sirsa Agricultural Produce Market Committee (APMC) The study also analysed the arrival and price pattern of major agricultural commodities before and after the implementation of e-NAM in the study area.
Regional economics. Space in economics, Economics as a science
Phoebe Koundouri, Georgios I. Papayiannis, Electra V. Petracou
et al.
In this paper we propose a consensus group decision making scheme under model uncertainty consisting of an iterative two-stage procedure and based on the concept of Fréchet barycenter. Each step consists of two stages: the agents first update their position in the opinion metric space by a local barycenter characterized by the agents' immediate interactions and then a moderator makes a proposal in terms of a global barycenter, checking for consensus at each step. In cases of large heterogeneous groups the procedure can be complemented by an auxiliary initial homogenization step, consisting of a clustering procedure in opinion space, leading to large homogeneous groups for which the aforementioned procedure will be applied. The scheme is illustrated in examples motivated from environmental economics.
Emma Stevenson, Victor Rodriguez-Fernandez, Hodei Urrutxua
et al.
This paper presents a novel methodology for improving the performance of machine learning based space traffic management tasks through the use of a pre-trained orbit model. Taking inspiration from BERT-like self-supervised language models in the field of natural language processing, we introduce ORBERT, and demonstrate the ability of such a model to leverage large quantities of readily available orbit data to learn meaningful representations that can be used to aid in downstream tasks. As a proof of concept of this approach we consider the task of all vs. all conjunction screening, phrased here as a machine learning time series classification task. We show that leveraging unlabelled orbit data leads to improved performance, and that the proposed approach can be particularly beneficial for tasks where the availability of labelled data is limited.
Purpose ― The paper queries the impacts of income inequality on economic growth in selected advanced and emerging market economies by adopting nonlinearity and endogeneity.
Methods ― This research analysis is based on a balanced panel from 1996 to 2018 and employs the dynamic panel threshold analysis after baseline estimations with the fixed-effect, system Generalized Method of Moments, and difference Generalized Method of Moments.
Findings ― This study finds a nonlinearity between income inequality and economic growth. Income inequality has a significant threshold effect on the growth of both panels. Besides, the threshold effect of emerging market countries is higher than the level for advanced countries. This means emerging market economies are negatively affected above the estimated threshold value according to the advanced economies.
Implication ― This paper supports that inequality may harm much more economic growth above a specific level. On the other hand, these distorting effects are related to the other economic issues of countries, such as government spending, inflation, export of goods and services, gross fixed capital formation, and foreign direct investment.
Originality ― This paper contributes to the literature by focusing on the nonlinear effects of income inequality and different aspects of economic growth above or below the estimated threshold value, thereby providing cross-country comparability and endogeneity.
Economic growth, development, planning, Regional economics. Space in economics
There has been a long-running debate in Information Technology (IT) and economics literature about the contrary arguments of IT concerning digitalization and the economic growth of nations. While many empirical studies have shown a significant value of IT, others revealed a detrimental impact. Given the ambiguous results and anecdotal commentary on the increase in digitalization attributed to the COVID19 global pandemic, this paper aims to explore the economic growth-digitalization nexus of 59 countries in 7 regions by employing correlation and regression analyses over the period 2018-2020. The findings indicate a positive relationship between economic growth and digitalization for both HIGH and LOW digitalized country categorization and regional assessment. Consistent with regional results, except for Northern Africa and Western Asia, and Sub-Saharan Africa regions, the remaining regions show a positive correlation and regression results. The findings of this study can be helpful in future prospective national IT and economic development policies.
Complex agricultural problems concern many countries, as the economic motives are increasingly higher, and at the same time the consequences from the irrational resources use and emissions are becoming more evident. In this work we study three of the most common agricultural problems and model them through optimization techniques, showing ways to assess conflicting objectives together as a system and provide overall optimum solutions. The studied problems refer to: i) a water-scarce area with overexploited surface and groundwater resources due to over-pumping for irrigation (Central Greece), ii) a water-abundant area with issues of water quality deterioration caused by agriculture (Southern Ontario, Canada), iii) and a case of intensified agriculture based on animal farming that causes issues of water, soil quality degradation, and increased greenhouse gases emissions (Central Ireland). Linear, non-linear, and Goal Programming optimization techniques have been developed and applied for each case to maximize farmers welfare, make a less intensive use of environmental resources, and control the emission of pollutants. The proposed approaches and their solutions are novel applications for each case-study, compared to the existing literature and practice. Furthermore, they provide useful insights for most countries facing similar problems, they are easily applicable, and developed and solved in publicly available tools such as Python.
We study random-turn resource-allocation games. In the Trail of Lost Pennies, a counter moves on $\mathbb{Z}$. At each turn, Maxine stakes $a \in [0,\infty)$ and Mina $b \in [0,\infty)$. The counter $X$ then moves adjacently, to the right with probability $\tfrac{a}{a+b}$. If $X_i \to -\infty$ in this infinte-turn game, Mina receives one unit, and Maxine zero; if $X_i \to \infty$, then these receipts are zero and $x$. Thus the net receipt to a given player is $-A+B$, where $A$ is the sum of her stakes, and $B$ is her terminal receipt. The game was inspired by unbiased tug-of-war in~[PSSW] from 2009 but in fact closely resembles the original version of tug-of-war, introduced [HarrisVickers87] in the economics literature in 1987. We show that the game has surprising features. For a natural class of strategies, Nash equilibria exist precisely when $x$ lies in $[λ,λ^{-1}]$, for a certain $λ\in (0,1)$. We indicate that $λ$ is remarkably close to one, proving that $λ\leq 0.999904$ and presenting clear numerical evidence that $λ\geq 1 - 10^{-4}$. For each $x \in [λ,λ^{-1}]$, we find countably many Nash equilibria. Each is roughly characterized by an integral {\em battlefield} index: when the counter is nearby, both players stake intensely, with rapid but asymmetric decay in stakes as it moves away. Our results advance premises [HarrisVickers87,Konrad12] for fund management and the incentive-outcome relation that plausibly hold for many player-funded stake-governed games. Alongside a companion treatment [HP22] of games with allocated budgets, we thus offer a detailed mathematical treatment of an illustrative class of tug-of-war games. We also review the separate developments of tug-of-war in economics and mathematics in the hope that mathematicians direct further attention to tug-of-war in its original resource-allocation guise.
Decision-making often involves ranking and selection. For example, to assemble a team of political forecasters, we might begin by narrowing our choice set to the candidates we are confident rank among the top 10% in forecasting ability. Unfortunately, we do not know each candidate's true ability but observe a noisy estimate of it. This paper develops new Bayesian algorithms to rank and select candidates based on noisy estimates. Using simulations based on empirical data, we show that our algorithms often outperform frequentist ranking and selection algorithms. Our Bayesian ranking algorithms yield shorter rank confidence intervals while maintaining approximately correct coverage. Our Bayesian selection algorithms select more candidates while maintaining correct error rates. We apply our ranking and selection procedures to field experiments, economic mobility, forecasting, and similar problems. Finally, we implement our ranking and selection techniques in a user-friendly Python package documented here: https://dsbowen-conditional-inference.readthedocs.io/en/latest/.
Introduction. The rhetoric of the leaders of the countries of the European Un ion shows large-scale contradictions on key issues as well as the “geocultural” incompatibility of views. The objective of the study is to prove the need for a dichotomous division of the European Union into “West” and “East”, the conceptual application of the idea of “multi-speed Europe” being the theoretical basis for such separation.
Materials and Methods. The method of unity of the qualitative and quantitative parameters of the countries of the former socialist bloc and Western European states was used to establish a sufficient evidence base. Empirical and theoretical studies as well as statistical data from international organizations were used as the materials for this study.
Results. In the process of a comprehensive study, an up-to-date geocultural analysis of the comparative characteristics of the countries of the European Union was carried out. On this basis, the effectiveness of the concept of “multi-speed Europe” as a way of formalizing the existing differences within the European Union has been proved. An assessment of the consequences of the regionalization of Europe, optimistic for Russia, has been given. The actual application of this concept will improve the socio-economic ties between Russia and Western Europe.
Discussion and Conclusion. The study has revealed the controversy and ineffectiveness of the existence of a united Europe. A comprehensive study of the concept of “multi-speed Europe” will make it possible to predict the further development of the European Union and evaluate the role of Russia in modern Europe. The results may be used by scientists and politicians to analyze the consequences of the enlargement of the European Union.
Global economy is undergoing a new systemic transformation, which led to a significant increase in popularity and profitability of green entrepreneurship throughout the world. The article explores the main trends in the development of green entrepreneurship in modern world economy through a wide range of aspects: as a megatrend in global economy, its share in foreign direct investments (FDI), international trade and consumption, its role and impact. Following the study of the related EU regulations, the author explores the specifics of green entrepreneurship management in Portugal with the focus on the Azores Islands. The research has been conducted using electronic and paper based bibliographic sources in English and Romanian, interviews with the specialists in the field, case study and personal observations.
Teresa Nieves-Chinchilla, Bhavya Lal, Robert Robinson
et al.
Advances in space weather science and small satellite (SmallSat) technology have proceeded in parallel over the past two decades, but better communication and coordination is needed among the respective worldwide communities contributing to this rapid progress. We identify six areas where improved international coordination is especially desirable, including: (1) orbital debris mitigation; (2) spectrum management; (3) export control regulations; (4) access to timely and low-cost launch opportunities; (5) inclusive data policies; and (6) education. We argue the need for internationally coordinated policies and programs to promote the use of SmallSats for space weather research and forecasting while realizing maximum scientific and technical advances through the integration of these two increasingly important endeavors.