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Abiola John Asaleye

Researcher at Landmark University

Publications -  66
Citations -  819

Abiola John Asaleye is an academic researcher from Landmark University. The author has contributed to research in topics: Agriculture & Exchange rate. The author has an hindex of 15, co-authored 57 publications receiving 534 citations.

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Economic growth, financial development and trade openness in Nigeria: An application of the ARDL bound testing approach

TL;DR: In this paper, the authors used the ARDL bound estimation techniques to examine the existence of cointegration among economic growth, financial development and trade openness in Nigeria, and they concluded that the policy instruments need to be manipulated so as to achieve economic growth and financial stability.
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Foreign aid, human capital and economic growth nexus: Evidence from Nigeria

TL;DR: In this article, the authors investigated the link between aid and human capital in promoting economic growth of Nigeria using two models; the first model was used to test the validity of the medicine model in Nigeria; while the extended model is used to investigate the effect of aid and Human Capital shocks on growth using Engle-Granger and Vector Error Correction Model (VECM) estimation techniques respectively.
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Examining the linkages between electricity consumption and economic growth in African economies

TL;DR: In this article, the authors examined the relationship between economic growth and electricity consumption in sub-Sahara African economies between 1971 and 2017 using System Generalized Methods-of-Moments (System GMM) techniques.
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Human capital and poverty reduction in OPEC member-countries

TL;DR: Since human capital is a crucial determinant of improving economic growth, OPEC member countries should invest more on the quality of human capital through education and health to improve the living standard of people and societal welfare.
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Financial sector and manufacturing sector performance: evidence from Nigeria

TL;DR: Asaleye et al. as mentioned in this paper examined the causal effects, shock effect and long-run impact using Granger Non-Causality, Vector Error Correction Model, and Dynamic Ordinary Least Square method, respectively.