Research chronicle
Papers, preprints, data releases, and policy documents related to the indicators in this dataset, gathered daily and summarized by AI.
AI summaryThis study uses ARDL modeling on 1991-2025 Nigerian time-series data to examine how fertility rate, infant mortality, population growth, and net migration affect life expectancy, finding a stable long-run relationship among these variables. Fertility rate showed a positive effect (cautiously interpreted as reflecting broader healthcare and socioeconomic improvements), while infant mortality and population growth had significant negative effects, and net migration's negative effect was statistically insignificant. The authors recommend strengthening maternal and child healthcare, expanding primary healthcare coverage, and promoting family planning to improve longevity, while suggesting future panel-data research to address endogeneity.
Abstract
This study investigates the effects of fertility rate, infant mortality rate, population growth rate, and net migration on life expectancy in Nigeria over the period 1991-2025. The study was motivated by limited empirical evidence on the combined influence of key demographic variables on longevity despite their importance for health and development policy. Annual time-series data were analysed using the Autoregressive Distributed Lag (ARDL) approach following Phillips Perron unit root tests and ARDL bounds cointegration analysis. The results confirmed the existence of a stable long-run relationship among the variables. Fertility rate exerted a positive and statistically significant effect on life expectancy, whereas infant mortality rate and population growth rate exhibited significant negative effects. Net migration showed a negative but statistically insignificant relationship with life expectancy. Diagnostic tests revealed no evidence of serial correlation or heteroskedasticity, while normality, specification, and stability tests confirmed the robustness and reliability of the estimated model. The findings suggest that demographic characteristics remain important determinants of life expectancy in Nigeria. The unexpected positive fertility coefficient is interpreted cautiously because it may reflect improvements in maternal and child healthcare, broader socioeconomic progress, and unobserved structural factors rather than a direct beneficial effect of higher fertility. The study concludes that sustained reductions in infant mortality and effective population management are essential for improving longevity. It recommends strengthening maternal and child healthcare services, expanding primary healthcare coverage, promoting voluntary family planning and reproductive health education, and improving demographic data systems. Future research should employ panel datasets to address endogeneity in Nigeria.