Forecasting Total Fertility Rate (TFR) In Nigeria Using a Machine Learning Approach
Abstract
In this research
paper, the ANN approach was applied to analyze TFR in Nigeria. The employed
annual data covers the period 1960-2018 and the out-of-sample period ranges
over the period 2019-2030. The residuals and forecast evaluation criteria
(Error, MSE and MAE) of the applied model indicate that the model is stable in
forecasting TFR in Nigeria. The results of the study indicate that annual total fertility rates in Nigeria are likely to remain around 5.5 births per
woman over the out-of-sample period. Therefore, the Nigerian government should to prioritize creating demand for family
planning, HIV testing, antiretroviral therapy (ART) services mainly targeting
15-49 age group and women empowerment programs.
Country : Zimbabwe
1 Dr. Smartson. P. NYONI2 Tatenda. A. CHIHOHO3 Thabani NYONI
ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
Independent Health Economist, Zimbabwe
SAGIT Innovation Center, Harare, Zimbabwe
IRJIET, Volume 5, Issue 8, August 2021 pp. 367-370
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