Forecasting Total Fertility Rate (TFR) in Eritrea Using a Machine Learning Technique
Abstract
In this research
article, the ANN approach was applied to analyze TFR in Eritrea. 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 Eritrea. The results of the study shows that annual total fertility rates in Eritrea are likely to decline slightly over the
out-of-sample period. Therefore, the government of Eritrea is
encouraged to (1) focus
on improving access to family planning services by creating more demand for the
service and addressing barriers to access, and (2) engage on a
women empowerment drive to improve their labor participation and contribution
to economic development.
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. 123-126
