_____________________________________________________________________________________________________ ++ ASSOC. Prof.; *Corresponding author: E-mail: effiongemmyinec@gmail.com; Asian J. Econ. Busin. Acc., vol. 23, no. 21, pp. 182-196, 2023 Asian Journal of Economics, Business and Accounting Volume 23, Issue 21, Page 182-196, 2023; Article no.AJEBA.107829 ISSN: 2456-639X Effect of Non - Renewable Energy on Manufacturing Output in Nigeria Abayomi Awujola a++ , Obumneke Ezie a and Effiong Emmanuel Sunday a* a Department of Economics, Faculty of Social Science, School of Post Graduate Studies, Bingham University, Karu, Nasarawa State, Nigeria. Authors’ contributions This work was carried out in collaboration among all authors. All authors read and approved the final manuscript. Article Information DOI: 10.9734/AJEBA/2023/v23i211126 Open Peer Review History: This journal follows the Advanced Open Peer Review policy. Identity of the Reviewers, Editor(s) and additional Reviewers, peer review comments, different versions of the manuscript, comments of the editors, etc are available here: https://www.sdiarticle5.com/review-history/107829 Received: 09/08/2023 Accepted: 14/10/2023 Published: 19/10/2023 ABSTRACT The role of energy, especially non-renewable energy in promoting manufacturing sector activities and operations in developing countries like Nigeria cannot be over-emphasized. This paper investigated the effect of non-renewable energy on textile and clothing output as a sub-sector of the manufacturing sector in Nigeria using time series data covering the period 1986 to 2021. Expost - Facto design was employed as a guide. The study used annual time series data on hydro-electricity, petroleum and gas energy respectively as components of non-renewable energy and textile and clothing manufacturing sub-sector output in Nigeria spanning from 1986 to 2022. Data used were obtained from the Central Bank of Nigeria (CBN) Publication and the World Development Indicators (WDI) considered as reliable sources of data for econometric analysis. The ARDL regression technique was used to estimate depicting the relationship between the variables, while the econometric properties of the data were determined using the Phillip-Perron (PP) unit root test and the Bounds cointegration methods. Mean, kurtosis and skewness were employed to describe the data. Results showed among others, that textile and clothing (coefficient, 1.25449; probability value, 0. 000) has significant positive effect on output level. Coal energy consumption (CEC) (coefficient, - Original Research Article