Revisiting the forecasting power of public health expenditure and climate change impact on life expectancy in Nigeria: A scenario analysis.
Abubakar Orlando Ijoko
Department of Economics, Faculty of Social Sciences, Nigerian Army University Biu, Biu, Borno State, Nigeria.
https://orcid.org/0000-0001-5632-2365
Salam S Mohammed
Department of Economics, Faculty of Social Sciences, Prince Abubakar Audu University PAAU, P.M.B 1008, Ayingba, Kogi State, Nigeria.
https://orcid.org/0000-0002-6772-2468
DOI: https://doi.org/10.20448/economy.v12i1.6521
Keywords: Bias-adjusted OLS, Climate change, Forecasting power, In-sample forecast, Life expectancy, Nigeria, Out-of-sample forecast, Prediction, Public health expenditure, Scenario analysis.
Abstract
In this study, we investigate the forecasting power of public health expenditure and the impact of climate change on life expectancy in Nigeria. This study relies on time-series data covering a period of 35 years (1988 to 2022) and uses a bias-adjusted ordinary least squares (OLS) method to predict the relationship and ARMSE to forecast with 8 policy options (scenarios) for 5 years. The analysis is based on data sourced from FAO, 2025, and WDI, 2025 databases. The results reveal a positive impact of both climate change (CC) and public health expenditure (PHE) on life expectancy (LE). In a single predictor model, for every one-degree Celsius rise (or fall) in CC and a percentage rise (or fall) in PHE, LE will rise (or fall) by 52.3 and 2.82, respectively. However, in a multiple predictor equation, the responses of LE to a change in CC and PHE are 15.14 and 2.12, respectively. We also reveal the 3rd scenario as the best option for policymaking. Given these positive impact results, the study concludes that climate change has led to an improvement in healthcare investment in Nigeria to mitigate the effects of climate-induced health challenges. We thus advise the government to sustain its improvement in the health sector through budgetary allocation and implementation.