Hasil untuk "Revenue. Taxation. Internal revenue"

Abdulmajid Mussa Nsekela, Athenia Bongani Sibindi, Patricia Lindelwa Makoni

This study explores the moderating role of pre-disclosure information leakage on the impact of board-level corporate governance on the financial performance of listed banks in East Africa. The research is driven by ongoing debates surrounding governance and performance, as well as the limited evidence available from emerging-market banking systems, where trading environments are often less regulated. The focus is on all 18 banks traded on stock exchanges in Kenya, Tanzania, Uganda, and Rwanda from 2010 to 2023, utilising a balanced panel dataset. Grounded in agency theory, information asymmetry, and efficient market hypotheses, the analysis investigates how information leakage moderates the effects of board size, independence, and meeting frequency on profitability and asset quality. Employing a sequential econometric approach, comprising pooled OLS, fixed and random effects models, and two-step system GMM, robustness diagnostics were conducted to ensure validity. The findings reveal that information leakage enhances short-term profitability but heightens future credit risk, with its moderating role amplifying both the positive effects of governance on profitability and the negative effects on asset quality. These results indicate that the effectiveness of governance is contingent on the information environment. This study provides novel insights for emerging markets and recommends that regulators and bank boards optimise board structures while reinforcing disclosure controls to strike a balance between market gains and the preservation of asset quality.

A. Ajibola

The purpose of this study is to pinpoint the determinants propelling development and growth in Nigeria's digital tax revenue (DTR) 2010–2024 over a number of different dimensions such as policy, economic environment where it operates, technology, society issues or worldwide factors. Anchored in the dependency theory, its objective is not only to reveal why fiscal performance in the digital economy is coloured by structural asymmetries and domestic institutional dynamics, but also add to empirical evidence for African economic governance, financial crime prevention and sustainable tax policy reform. This study examines Nigeria's 2010–2024 digital economy income possibilities. It situates this question in the taxation, financial crime and global governance debates. The study suggests dependence theory and Nigeria's digital international tax future may be linked. According to the prior view, internal tax reforms were more important than international circumstances in Nigeria's tax status. This study uses time-series econometric specifications like Ordinary Least Squares, Newey–West regression and Prais-Winsten AR(1) to examine how policy, economic conditions, technological penetration, social factors and global integration affect DTR mobilization in Nigeria. The results show that policy, economics, technology, society and the world affect DTR performance statistically. This shows Nigeria's complex digital fiscal competence. Economic development and social trust are good, but technological penetration is bad, indicating poor regulation. Digital taxation in Nigeria is affected by policy coherence, institutional trust, macroeconomic stability and global tax governance frameworks, not just technical adoption. The conclusions emphasize role the public's trust and social agreement plays in sustaining digital tax. Compliance will be enhanced, tax morale will be realized if use of tax revenue is transparent and it results in tangible public goods. Likewise, governance deficits and corruption must be addressed in order to create a perception of tax as a reciprocal obligation rather than just coercion. In society, effective digital tax systems can help distribute wealth more evenly by widening the tax base, providing better services to citizens and reducing social costs of financial crime and tax evasion. The study contributes a novel African perspective by empirically linking dependency theory to DTR mobilization, offering fresh insights into contextualized perspective on DTR mobilization.

Milena Filipova, Antonina Djakona, Volodymyr Haram

The relevance of analyzing the drivers of government expenditures in the Baltic States lies in the growing fiscal pressure, economic volatility, and evolving policy priorities that require data-driven approaches to optimize public spending. Understanding the macroeconomic and institutional variables influencing government expenses is crucial for ensuring fiscal sustainability and development planning across small open economies like Lithuania, Latvia, and Estonia. This study aims to examine the key determinants of government expenditures in the Baltic States and to assess the predictive capacity of macroeconomic indicators using regression-based modelling. The research is based on data from 1998 to 2023 and utilizes Pearson correlation analysis, simple and multiple linear regressions, and regression-based forecasting. Z-score normalization was applied to standardize indicators such as GDP, FDI, interest rates, and public debt levels. Forecasts for the period 2024–2027 were conducted using ARIMA and regression projections. The findings reveal that GDP is the strongest and most statistically significant predictor of government expenditure, explaining 88.9% of the variation in Lithuania, 88.5% in Latvia, and 96.5% in Estonia. Interest rates demonstrated a consistent negative and significant effect across all three countries, with coefficients of -0.807 (Lithuania), -0.417 (Latvia), and -0.328 (Estonia). Foreign direct investment (FDI) had a positive impact in Latvia (0.320) and Lithuania (0.208), while the debt level emerged as a significant positive factor only in Estonia (0.512). Forecasts indicate continued growth of public spending in Lithuania, while Latvia and Estonia show stabilization with minor deviations. These results underscore the need for differentiated fiscal strategies aligned with national economic structures.

Marcel Guhl, Jeffrey Heidemann

Remarkable examples like the flood in July 2021 in Germany showed that regional banks (savings and cooperative banks) and their strong local network were central pillars for the local population. Regional banks have provided financial aid, resources, and pragmatic solutions in response to the disaster. At the same time, it became visible that the measures implemented were reactive rather than preventive. This aspect has received minimal consideration in scientific discourse. The study addresses two research questions by conducting a comprehensive literature review and employing an exploratory qualitative approach: the role of regional banks in disaster risk reduction in Germany and bank-specific services, which should be organised in a more preventative manner to increase the population's resilience to disasters. Semi-structured interviews, followed by qualitative content analysis are used to gather expert opinions. Eleven representative experts from regional banks, banking associations, and the disaster risk management sector were interviewed between July 2023 and March 2024. The results confirm that regional banks have been primarily reactive to disasters. At the same time, the study indicates that regional banks should be more involved in disaster risk prevention because of their local networks, material and immaterial resources, and their central role as local financiers. The study contributed substantially to the academic debate and generated practical insights for regional banks and disaster prevention in Germany.

Juan Camilo Orduz

We present a Bayesian approach to model cohort-level retention rates and revenue over time. We use Bayesian additive regression trees (BART) to model the retention component which we couple with a linear model for the revenue component. This method is flexible enough to allow adding additional covariates to both model components. This Bayesian framework allows us to quantify uncertainty in the estimation, understand the effect of covariates on retention through partial dependence plots (PDP) and individual conditional expectation (ICE) plots, and most importantly, forecast future revenue and retention rates with well-calibrated uncertainty through highest density intervals. We also provide alternative approaches to model the retention component using neural networks and inference through stochastic variational inference.

Julien Laasri, Marc Revol

As Kalyan T. Talluri and Garrett J. Van Ryzin describe in their work [3], Revenue Management aims to maximize an organization's revenue by considering three types of decision categories: structural, pricing, and quantity. In this document, our primary focus will be on decisions related to pricing and quantity for the sale of airline tickets on a direct flight over a certain number of time periods. More specifically, we will only focus on the optimization aspect of this problem. We will assume the demand data to be given, since Air France estimates it beforehand using real data. Similarly, we assume all price options to be predetermined by Air France's algorithms and verified by their analysts. Our objective will be to maximize the revenue of a direct flight by choosing the prices for each product from the predefined set of options. -- Comme décrit par Kalyan T. Talluri et Garrett J. Van Ryzin dans leur ouvrage [3], le Revenue Management consiste en la maximisation du revenu d'un organisme à partir de trois types de catégories de décision : structurelles, prix et quantité. Dans ce document, nous nous intéresserons principalement aux décisions de type prix et quantité pour la vente de billets d'avion sur un vol direct au cours d'un certain nombre de pas de temps. Plus précisément, nous nous situerons dans la partie optimisation du problème. Nous prendrons ainsi les données de demande comme acquises, car elles sont estimées au préalable par Air France à partir des données réelles. De même, pour chaque produit que l'on cherchera à vendre, on nous impose en amont les prix possibles que l'on a droit d'utiliser et qui se basent sur des algorithmes d'Air France dont les résultats sont vérifiés par des analystes. Notre but sera alors de maximiser le revenu d'un vol direct en choisissant les prix de chaque produit parmi ceux imposés.

Mohammadreza Ahmadnejadsaein, Omar El Housni

We study adaptive two-sided assortment optimization for revenue maximization in choice-based matching platforms. The platform has two sides of agents, an initiating side, and a responding side. The decision-maker sequentially selects agents from the initiating side, shows each an assortment of agents from the responding side, and observes their choices. After processing all initiating agents, the responding agents are shown assortments and make their selections. A match occurs when two agents mutually select each other, generating pair-dependent revenue. Choices follow Multinomial Logit (MNL) models. This setting generalizes prior work focused on maximizing the number of matches under submodular demand assumptions, which do not hold in our revenue-maximization context. Our main contribution is the design of polynomial-time approximation algorithms with constant-factor guarantees. In particular, for general pairwise revenues, we develop a randomized algorithm that achieves a $(\frac{1}{2} - ε)$-approximation in expectation for any $ε> 0$. The algorithm is static and provides guarantees under various agent arrival settings, including fixed order, simultaneous processing, and adaptive selection. When revenues are uniform across all pairs involving any given responding-side agent, the guarantee improves to $(1 - \frac{1}{e} - ε)$. In structural settings where responding-side agents share a common revenue-based ranking, we design a simpler adaptive deterministic algorithm achieving a $\frac{1}{2}$-approximation. Our approach leverages novel linear programming relaxations, correlation gap arguments, and structural properties of the revenue functions.

Sleiman Farah, Jens Jakob Sørensen, Kary Främling et al.

Hydrogen Purchase Agreements (HPAs) guarantee revenue streams that mitigate the financial risks inherent in the long-term production of green hydrogen from renewable energy sources. However, the intermittency of renewable electricity and the availability of parallel revenue opportunities in both the electricity and hydrogen markets complicate the scheduling of green hydrogen production. The scheduling should maximise the total revenue from short-term sales of electricity and hydrogen against the long-term HPA delivery obligations. This challenge is addressed by developing a Bounded Fuzzy Logic Control (BFLC) which determines the daily HPA delivery target based on day-ahead forecasts of electricity and hydrogen prices, as well as wind capacity factors. Subsequently, the daily target is imposed as a constraint in dispatch optimisation which allocates energy and hydrogen flows for each hour of the day. Revenue comparisons over several years demonstrate that the BFLC achieves total annual revenues within 9% of optimal revenues that are based on perfect foresight. The BFLC revenues consistently exceed those of steady control, with the largest differences observed under conditions of elevated price levels and variability. The BFLC provides an effective long-term scheduling of green hydrogen production, enabling realistic revenue quantification that mitigates economic risks without overlooking economically viable projects.

Charisse C. Laganson, Jorish Miah S. Suganob, Karl P. Campos

Economic growth is a vital driver of national development, fostering employment, reducing poverty, and raising living standards. In the Philippines, taxation remains the government’s primary tool for resource mobilization, yet the distinct contributions of various tax instruments to economic performance have not been thoroughly examined. This study analyzed the effects of Corporate Income Tax (CIT), Value-Added Tax (VAT), and Excise Tax revenues on the country’s Gross Domestic Product (GDP) using a quantitative econometric approach. Time-series data covering 2014 to 2024 were obtained from the Philippine Statistics Authority, World Bank, and Bureau of Internal Revenue. The Ordinary Least Squares (OLS) regression method was employed, supported by descriptive statistics and correlation analysis to validate the results. Findings show that tax revenues collectively explain 95 percent of the variation in GDP (R² = 0.95, F = 44.21, p < 0.01), confirming their substantial role in driving economic growth. Among the three instruments, VAT had the strongest and most significant positive effect (B = 0.48, β = 0.79, p < 0.01), followed by Excise Tax (B = 0.22, β = 0.49, p = 0.03), while CIT displayed a negative but statistically insignificant impact (B = -0.19, p = 0.23). The Durbin–Watson statistic (2.42) indicated no autocorrelation, and multicollinearity was within acceptable levels. These results suggest that indirect taxes, particularly VAT and Excise Tax, are more effective drivers of economic expansion than corporate taxation. The study concludes that strengthening the administration of VAT and Excise Tax, improving compliance mechanisms, and broadening the tax base are essential for sustaining growth, while future research should incorporate other macroeconomic variables to provide a fuller picture of taxation’s role in development.

Katherine Estefanía Paredes Sánchez, Giovanni David Fernandez Unuzungo

Treaty shopping, tax evasion, and tax avoidance strategies represent significant challenges to Ecuador's tax sustainability. These practices, used by multinational companies and large taxpayers, allow for the artificial reduction of the tax burden through the manipulation of double taxation agreements (DTAs) and other forms of aggressive tax planning. This article seeks to evaluate the effect of various measures on tax revenues and assess the effectiveness of the measures implemented at the national and global levels to mitigate their effects. Through a systematic documentary review of scientific studies, reports from international organizations, and data from the Internal Revenue Service (IRS), it was identified that tax evasion and avoidance undermine the equity of the tax structure and diminish the State's capacity to invest in essential public services. Although Ecuador has adopted some actions from the OECD BEPS Plan, such as transfer pricing control and the regulation of transactions between related parties, regulatory and operational gaps still persist that allow these practices to continue. It is concluded that it is necessary to strengthen enforcement, implement stricter regulations in the DTTs, and improve global cooperation to reduce the negative impacts of these strategies.   Received: 5 April 2025 / Accepted: 19 July 2025 / Published: 05 September 2025

Lila Teeters Knolle

In 1915, the United States sued the treasurer and sheriff of Dewey County, South Dakota, on behalf of six Lakota men at Cheyenne River Reservation. The suit alleged that Dewey County officials had improperly taxed the Lakota men before illegally seizing property for back payment. The case, US v. John Pearson (1916), became a turning point in Indigenous taxation case law. Analyzing the events leading up to the case, this article shows how the relationship between good citizenship and taxation was deeply contested in Dewey County. The primacy of fiscal citizenship was a product of Indigenous dispossession, internal migration, and foreign immigration, which shaped not only South Dakota but also the nation writ large. Local governments and migrants coveted Indigenous lands and the potential tax revenue from Native American citizens, creating a national push to expedite the conferral of citizenship to Indigenous individuals. The events preceding US v. Pearson illustrate how United States officials used citizenship and taxation as settler-colonial tools and tell a story about how an Indigenous community fought back.

Fadipe, A. O., Malomo, E, Osanyibi, T et al.

This study investigates how environmental taxation influences the adopting of sustainable business practices among large and medium-sized firms in Lagos State, Nigeria. Drawing on a cross-sectional survey of 200 senior managers and sustainability officers in the manufacturing, oil & gas, and telecommunications sectors, the research examines perceptions of key tax attributes—clarity of tax bases, administrative ease, cost impacts, revenue transparency, and internal compliance capacity—and their association with five dimensions of corporate sustainability: energy efficiency, waste management, renewable‐energy adoption, environmental reporting, and strategic integration of environmental considerations. Descriptive statistics reveal strong consensus that tax bases are clearly defined (71.5%), remittance processes are straightforward (70.0%), and revenues are transparently earmarked for environmental initiatives (85.0%), while views on cost burdens are evenly split. High levels of sustainable practice adoption are observed for energy efficiency (70.5%), renewables (73.5%), reporting (80.0%), and strategic integration (82.5%), whereas comprehensive waste‐ reduction programs remain relatively uncommon (41.5%). One-sample Chi-Square tests confirm these patterns are statistically significant (all p < .001). Findings suggest that well-designed and effectively administered environmental taxes can drive substantive energy and disclosure practices, but that additional incentives and technical support are needed to bolster waste‐management efforts. The study concludes with recommendations to recalibrate levy rates, introduce waste‐ management credits, sustain administrative enhancements, and publicise revenue impacts, thereby maximising environmental taxation’s potential to foster holistic corporate sustainability in Nigeria’s green economy.

Olena V. Tymoshenko, Kateryna I. Kotsiubivska

The article is devoted to pressing issues of taxation under martial law in Ukraine, particularly the analysis of changes in tax policy, their impact on the economic stability of the State, and the adaptation of the fiscal system to new challenges caused by military actions. The authors emphasize the need to actuate the role of taxes from the perspective of fiscal significance as the primary internal source of budget revenue and outline the regulatory function of taxes in establishing «equal rules» of taxation for economic entities in Ukraine, which will contribute to the de-shadowing of business as a whole. Special attention is given to the role of international support in restoring economic activity. The authors analyze the structure of budget revenue formation and draw conclusions about the growing dependence of the economy on external financial inflows during the crisis period. Thus, in the pre-war period of 2020–2021, tax revenues constituted the main portion of the budget income: 82.57% in 2020 and 87.47% in 2021, which is typical for the socioeconomic systems of developing countries; however, in 2022, their share decreased to 61.16%, while the share of financial assistance from foreign countries and international organizations increased to nearly 22%. The authors assessed key aspects of the reform of the taxation system under martial law, particularly changes in the simplified taxation system and the increase in tax rates. Positive tendencies in the direction of optimizing tax policy are noted, but no less attention is drawn to the ambiguity of this policy and potential risks of its implementation. The article analyzes the reasons for such changes, their impact on the economic stability of the country, and the prospects for financial policy under martial law. The article emphasizes the importance of adopting the Law of Ukraine «On Amendments to the Tax Code of Ukraine Regarding the Features of Tax Administration During Martial Law for Taxpayers with a High Level of Voluntary Compliance with Tax Legislation» and proposes directions for reforming the taxation system in the context of enhancing the level of tax culture, specifically a detailed categorization of taxpayers based on their compliance with tax legislation and the implementation of appropriate measures for each group. It is underscored that the reform of the taxation system in Ukraine must be systematic, completely rejecting the practice of fragmented and «symptomatic treatment», which will contribute to the post-war recovery of Ukraine’s economic system.

Saeed P. Langarudi, S. Noor

We develop and use a system dynamics model of New Mexico Oil Production and Taxation (NMOPT) to explore the potential impact of exogenous and endogenous oil taxation on the level and stability of state revenue. Endogenous policies determine taxes based on internal dynamics (e.g., production value), whereas exogenous policies are independent of internal dynamics. We examine two exogenous and two endogenous (progressive and regressive) policies. Progressive taxation increases tax rates as production or price increases. Regressive taxation decreases tax rate as production or price increases. Our historical analysis indicates that New Mexico follows non-progressive (exogenous or regressive) taxation. However, our model’s Monte Carlo simulations reveal that transitioning to an exogenous fixed-rate taxation can substantially enhance the level and stability of the state’s revenues. The state can increase its revenue even further by adopting progressive taxation, which could also be considered an environmental policy, as it limits oil production. However, progressive taxation’s benefits come at the expense of higher revenue volatility. This paper also has two computational contributions: (1) a new intergenerational decline curve formulation to capture oil wells’ long-term productivity and (2) a detrended coefficient of variation to measure time series volatility in dynamic simulations reliably.

Ana Njegovanović

Complex systems consist of many components that interact with each other, and nonlinearity is fundamental in the dynamics that arise as a result of the interaction of these components and cannot be studied by observing only a small part of the system. A large number of them make fluctuations an integral part of their dynamics. Through interdisciplinary research, we integrate different disciplines and methodological approaches. We study complexity from different angles through topics that include neuroscience, artificial intelligence, and quantum physics. We have sought to explore these topics that have gained progressive interest in scientific circles as well as outside academic circles, influencing many areas outside academic research. Two goals connect our research. First, theoretical insights from neuroscience, artificial intelligence and quantum physics of the financial stock market. "Financial stock markets are sophisticated machines intertwined with scientific networks" (Ana Negovanović, 2024). They are the core of a system of different blocks that interact on the financial market in an interdisciplinary interaction of the most complex structures, neural networks with interconnected nodes. Second, new technologies- convergence of technologies, new industries, space industry through chaos theory. Investigating the attributes of complex systems is structure. Systems are structured in such a way that some parts of the system are specialized, and systems can naturally be divided into different levels of organization, which should be modeled at different levels of detail. An important component of systems understanding is the ability to break down a system model into its component parts and levels to see how the parts behave and how to connect the parts and levels to understand the overall dynamics and structure of the system. Perhaps one of the most transparent examples of the importance of structure in thinking about complex systems is the space program, where one must equally consider the behavior of individual components and the dynamics of how those components interact with each other.

Amira Benachour, Lamine Tarhlissia

The research makes an attempt at analysing the state of affairs of the electronic payment in Algeria and propose perspectives for future development in that regard. To attain this objective, the bank of Crédit Populaire Algérie (CPA) in Algeria was taken as a case study. The primary reason of choosing this bank was by virtue of its leading market share in the local market and many electronic services and payment cards in use. The bank data from 2016 to 2022 was collected to perform an analysis of the growth rate of electronic payment services and to carry out a forecast of these services using exponential smoothing. Hypotheses tests demonstrate with validity that in the upcoming years, the number of electronic payment services will considerably increase. First, the use of electronic payment in Algeria has increased due to consumers’ changing preferences and due to the necessity of practical and safe payment solutions. Second, the bank used as a case study has invested in the development of electronic payment by proposing e-payment solutions to its consumers. Finally, the future of electronic payment will be marked by an increase in the number of electronic services. The findings of the research highlight consumers’ changing preferences towards electronic payment and consequently all banks should invest in designing and executing strategies of electronic payment services. It is recommended that scholars could use the findings of this research and perform a benchmark with other banks in Algeria or banks in other MENA countries. Moreover, the number of years could be further increased to determine if the growth of these services is to increase, decrease, or stay constant.

Devendra Parajuli, Gyan Mani Adhikari, Ganesh Bhattarai

Global Financial Technology adoption grew from 33% in 2017 to 64% in 2019, and in Nepal, Fintech users surged by 207.41% from 6.48 million in 2020 to 19.92 million in 2023, significantly influenced by the COVID-19 epidemic. Despite numerous studies on Financial Technology adoption globally, research on drivers of adoption intention, particularly incorporating mediation and moderation effects across various sectors of urban areas of Nepal, remains limited. Thus, this study examines the drivers of intention to adopt Financial Technology among urban Nepalese in Kathmandu Valley using the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology. The study employs a descriptive and explanatory research design to thoroughly examine the factors influencing the intention to adopt Financial Technology services. A non-probability sampling technique, specifically convenient sampling, was used to gather data from 360 users of Fintech services through a structured questionnaire administered via the Kobo Toolbox. Data analysis was conducted using Structural Equation Modeling with Partial Least Squares version 4.1.0.1. The findings indicate that effort expectancy, trust, and perceived usefulness directly influence the intention to adopt Fintech services. In contrast, security and privacy, and social influence affect adoption indirectly through perceived usefulness. Furthermore, effort expectancy partially impacts adoption through perceived usefulness, but perceived trust only directly affects adoption. Moreover, the education level moderates the impact of trust and social influence on adoption. In contrast, the effects of security and privacy, and effort expectancy are not influenced by education. The study offers vital insights to regulators, policymakers, providers of Financial Technology services, and BFIs as they should prioritize initiatives that enhance trust, effort expectancy, and perceived usefulness of Fintech services.

Bouyacoub Brahim

This article delves into the analysis of the effectiveness of economic policies implemented in 20 countries in the Middle East and North Africa (MENA) region. The countries considered include Algeria, Saudi Arabia, the Palestinian Authority, Bahrain, Djibouti, the United Arab Emirates, Egypt, Iraq, Iran, Jordan, Kuwait, Lebanon, Libya, Morocco, Mauritania, Oman, Qatar, Syria, Tunisia, and Yemen. The study is based on an Autoregressive Distributed Lag (ARDL) regression model, employing the Ordinary Least Squares (OLS) method. This model is suitable for non-stationary time series and those with a mixed order of integration. The analysis covers the period from 2000 to 2023.The results obtained highlight the diversity of the impacts of economic policies, strongly influenced by the specific economic and social contexts of each country. Governments, in their pursuit of efficiency and sustainability, are often faced with the delicate balance between multiple objectives. Among the measures considered are the money supply, inflation rate, government spending, and structural reforms. These measures have demonstrated their effectiveness in stimulating economic growth, promoting economic activity, encouraging investment, and creating employment opportunities. Monetary and fiscal policies are also crucial levers aimed at maintaining macroeconomic stability. This is expressed notably through controlling inflation, managing budget deficits, and ensuring the stability of the financial system. The results of econometric tests converge towards unanimous conclusions, suggesting the existence of one-directional causal relationships between economic growth and specific indicators of economic policy. This in-depth understanding of regional economic dynamics provides valuable insights for tailoring economic policies to each national context within the MENA region.

Mridu Prabal Goswami

We consider an economic environment where a seller wants to sell an indivisible unit of good to a buyer. We show that revenue from any strategy-proof and individually rational mechanism defined on closed intervals of rich single crossing domains considered in \citep{Goswami1}, can be approximated by the revenue from a sequence of strategy-proof and individually rational mechanisms with finite range. Thus while studying optimal mechanisms without loss of generality we can study mechanisms with finite range.

A. Chukwunweike, C. Egolum

The rapid urbanization in Nigeria necessitates effective revenue generation sources available to municipal authorities. Land taxation has emerged as a significant source of municipal revenue in both developed and developing countries. This study examined the practice of land taxation in Delta State, Nigeria, with a view to identifying critical issues that impede its effectiveness. This research utilized survey method based on policy implementation to explore issues in property tax, capital gains tax, and probate tax practices in Delta State. Data collection was based on a questionnaire survey of a sample of 49 property tax administrators in the study area. Data were presented using a weighted mean Table, and results show that despite various reforms, including the Delta State Internal Revenue Service Act of 2020, the implementation of property taxation remains challenged by fragmented administration, outdated valuation systems, poor revenue collection mechanisms, and a lack of transparency and accountability. Following statistical analysis with Factor Analysis and Spearman’s Bivariate Correlation, the study further reveals low awareness among property owners, significant barriers to implementation such as policy design flaws and political interference, and administrative inefficiencies. Recommendations include simplifying tax laws, enhancing transparency, improving technological infrastructure, and providing continuous training for tax officials. Addressing these issues is critical for optimizing revenue generation and fostering sustainable development in Delta State.