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Research Article
Fiscal Deficit and Its Impact on Nigeria’s Economy
Ropheka Emerson Bot*
Issue:
Volume 1, Issue 2, June 2026
Pages:
81-88
Received:
31 January 2026
Accepted:
24 February 2026
Published:
17 March 2026
Abstract: The idea that deficit spending can help promote advanced growth, enable higher tax revenues to be generated and thus reduce the fiscal deficit over time has been area of interest. This research provides an empirical analysis of how fiscal deficits influence economic expansion within the Nigerian context. Utilizing an ex-post facto research framework, the study examines secondary data spanning the years 1990 to 2024, gotten from Central Bank of Nigeria Statistical Bulletin. To investigate the relationship between fiscal deficit indicators and national economic performance, the Fully Modified Ordinary Least Squares (FMOLS) estimation technique was employed. The analytical results indicate that the Government Budget Deficit (GBD) has a statistically significant and positive influence on Nigeria's economic output, based on probability results at a 5% significance level. Conversely, the findings suggest that Public Debt (PUD) does not exert a significant impact on the country's economic performance, with probability outcomes falling outside the 5% significance threshold. Based on these results, the paper recommends that the Federal Government implement strategic measures to refine budget deficit policies, ensuring more effective execution and resource utilization. Furthermore, it is advised that the government establish robust monitoring mechanisms to ensure public borrowing is strictly channelled toward productive economic activities. Such a shift would help protect and stimulate both private investment and the broader real sector of the Nigerian economy.
Abstract: The idea that deficit spending can help promote advanced growth, enable higher tax revenues to be generated and thus reduce the fiscal deficit over time has been area of interest. This research provides an empirical analysis of how fiscal deficits influence economic expansion within the Nigerian context. Utilizing an ex-post facto research framewor...
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Research Article
The Place of Business Education/VTE Curriculum Reforms for Sustainable Growth Especially in AI-based Innovations
Francis Uche Ukaike*,
Olupayimo Esther Olaitan,
Ajayi Bukola Justinah
Issue:
Volume 1, Issue 2, June 2026
Pages:
89-94
Received:
6 March 2026
Accepted:
17 March 2026
Published:
28 March 2026
Abstract: The rapid integration of Artificial Intelligence (AI) into global economies demands transformative reforms in Business Education and Vocational Technical Education (VTE) curricula to foster sustainable growth especially in AI Based Innovations. The study explored the impact of inclusive business education on entrepreneurship development and workforce sustainability in a knowledge-based economy and determine the effectiveness of practical application and experiential learning in bridging the gap between theoretical knowledge and practical skills in business education. Two research questions were structured to guide the study. This study adopts a quantitative research design to investigate the role of inclusive business education in fostering entrepreneurship development and workforce sustainability among business educators in Nigeria. The methodology was structured to ensure systematic data collection, analysis, and presentation of results. The target population for the study comprises 896 Lecturers and Post Graduate Students cutting across 3 Geo Political Zone, North (Ahmadu Bello University (ABU) ZARIA) West (Adeyemi Federal University of Education (AFUED)) and East (Nnamdi Azikiwe University, Awka). 241 (UNIZIK), 121 (ABU ZARIA) and 534 (AFUED) VTE Educators. This population is chosen because they play a critical role in shaping the curriculum as major players in the industry. A sample of 200 VTE educators were randomly selected from those tertiary institution for the study. Key findings highlight the urgency of: embedding AI tools, data analytics, and automation competencies to prepare learners for high-demand roles, Scaling internships, mentorship programs, and community-based projects to enhance entrepreneurial skills and social responsibility, strengthening partnerships between educators, industries, and governments to ensure curricula reflect real-world needs and combining business education with social sciences and environmental studies to address global challenges like climate change and equitable growth. The study recommends among others that: Curriculum Planners should Integrate AI Competencies Across the Curriculum: Business Education and VTE programs should embed AI tools, data analytics, automation, and digital business technologies into all course areas not as standalone topics to ensure learners gain practical AI fluency, Strengthen Experiential and Work-Integrated Learning: Institutions should scale internships, simulations, case studies, mentorship programs, and community-based projects to bridge the gap between theory and real workplace skills, especially in AI-driven environments, Stakeholder should Redesign Curriculum Toward Hands-On, Competency-Based Learning: Curricula must shift from theory-heavy content to practical, problem-solving, innovation-focused modules that align with industry expectations in the digital economy.
Abstract: The rapid integration of Artificial Intelligence (AI) into global economies demands transformative reforms in Business Education and Vocational Technical Education (VTE) curricula to foster sustainable growth especially in AI Based Innovations. The study explored the impact of inclusive business education on entrepreneurship development and workfor...
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Research Article
Techno-Economic Evaluation and System Design of Evacuated Tube Collector Based Water Heating for Institutional Hostels
Issue:
Volume 1, Issue 2, June 2026
Pages:
95-113
Received:
13 August 2025
Accepted:
6 February 2026
Published:
31 March 2026
Abstract: Water heating is increasingly becoming one of the major energy-consuming activities in Kenya and globally. This trend is largely driven by significant efficiency improvements in other energy consuming sectors such as lighting and household appliances, while heating technologies have experienced relatively minimal advancements. Although electric water heaters are efficient, their adoption in institutions such as Multimedia University (MMU) has declined due to several challenges, including high electricity costs, high maintenance costs associated with elevated chlorine levels in water, carbon dioxide (CO2) emissions from grid electricity, and national trade imbalances linked to the importation of heavy fuel oil used in non-renewable electricity generation. This study evaluates the techno-economic feasibility of replacing electric immersion heaters with evacuated tube solar collectors (ETCs) for large-scale water heating at MMU’s executive hostel, serving over 300 users. Water consumption patterns were monitored over one week, revealing an average usage of 49.1 L per person per bath and a total daily demand of 15,529.6 L, corresponding to an energy demand of 400.48 kWh/day. RETScreen Expert software was used to simulate and optimize the solar thermal system using a site solar radiation of 5.32 kWh/m2/day and collector parameters Fr(τα)=0.68 and FrUL=1.33. The results indicate that immersion heaters currently consume 175,200 kWh annually at a cost of $31,658.51 and generate 8,628.7 kg of CO2 emissions per year. The optimal ETC system achieves a 64% solar fraction with a collector capacity of 21,300 L, a tilt angle of 15°, and storage of 75 L/m2. Economic analysis at a nominal discount rate of 10.75% yields a net present value of $29,083.96, an internal rate of return of 24%, and a payback period of less than three years, demonstrating the strong economic viability of solar water heating for institutional applications.
Abstract: Water heating is increasingly becoming one of the major energy-consuming activities in Kenya and globally. This trend is largely driven by significant efficiency improvements in other energy consuming sectors such as lighting and household appliances, while heating technologies have experienced relatively minimal advancements. Although electric wat...
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Research Article
An Analysis of Predictive Models for Market Volatility, Using Macroeconomic Indicators
Timothy Smith*,
Luca Guida
Issue:
Volume 1, Issue 2, June 2026
Pages:
114-120
Received:
9 April 2026
Accepted:
25 April 2026
Published:
19 May 2026
DOI:
10.11648/j.iecon.20260102.14
Downloads:
Views:
Abstract: In asset pricing applications one of the most powerful and widely used models is the famous Black-Sholes model. In applications of stock option pricing, the resulting Black-Scholes formula requires inputting several values, including the current price of the stock and the market volatility. The question of how to input the volatility in real-time can be very challenging, as commonly utilized measures, such as the volatility index (VIX), can be viewed as lagging economic indicators. This research discusses a scheme that applies a mathematical model which defines how far the current market value is above or below from where macroeconomic conditions would expect it to be. In prior research, a regression model was created to define a framework that theoretically outlined a new measure related to market volatility. When computing various financial predictions, such as evaluating the fair price of an option, this measure can be used to supplement common current measures, such as the VIX. In the current work, several mathematical methods, including machine learning, are investigated to determine if improvements to accuracy can be made, and define a practically usable scheme. Slight improvements to accuracy were discovered in comparison to the prior regression model; the Principal Component Analysis method is recommended for usage in real time applications.
Abstract: In asset pricing applications one of the most powerful and widely used models is the famous Black-Sholes model. In applications of stock option pricing, the resulting Black-Scholes formula requires inputting several values, including the current price of the stock and the market volatility. The question of how to input the volatility in real-time c...
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