This study investigates the intricate relationship between electricity consumption and economic development in Nigeria. Drawing on multivariate analysis, we explore how electricity consumption patterns influence economic growth dynamics within the Nigerian context. By employing advanced econometric techniques, we aim to unravel the complexities underlying this nexus and shed light on potential policy implications. Our findings contribute to a deeper understanding of the role of electricity infrastructure in fostering sustainable economic development strategies for Nigeria and other developing nations facing similar challenges.

This study conducts a comparative analysis of predictive models, specifically Partial Least Squares (PLS) and Financial Ratio Analysis, to forecast corporate failure in Malaysia. With corporate failure being a critical concern for investors, creditors, and regulatory bodies, accurate predictive models play a pivotal role in mitigating financial risks and safeguarding stakeholders' interests. The study examines the efficacy of PLS, a data-driven approach that identifies latent variables, against Financial Ratio Analysis, a traditional method based on key financial indicators. Using historical financial data from a sample of Malaysian companies, the study evaluates the predictive performance of both models in identifying early signs of corporate distress. Results highlight the strengths and limitations of each approach and provide insights into their practical applicability in the Malaysian context.