Forecasting Total Fertility Rate (TFR) In Sierra Leone Using a Machine Learning Method
Abstract
In this study, the
ANN approach was applied to analyze TFR in Sierra Leone. The employed 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
Sierra Leone. The results of the study indicate that annual total fertility rates in Sierra Leone are likely to remain around 4.2 births per
woman throughout the out-of-sample period. Therefore, the authorities in Sierra Leone are
encouraged to prioritize creating
demand for family planning services, addressing challenges faced by adolescents
and young adults when seeking sexual and reproductive health (SRH) services and scaling up women
empowerment program activities.
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. 351-354