Forecasting Total Fertility Rate (TFR) in Benin Using a Machine Learning Algorithm
Abstract
In this research paper, the ANN approach was applied to analyze TFR in
Benin. The employed annual data covers the period 1960-2019 and the
out-of-sample period ranges over the period 2020-2030. The residuals and
forecast evaluation criteria (Error, MSE and MAE) of the applied model indicate
that the model is stable in forecasting TFR in Benin. The results of the study
indicate that
annual total fertility rates in Benin are likely to be around 4.8 births per
woman throughout the out-of-sample period. Therefore, the
government of Benin should improve awareness of family planning services to adolescents and young
adults through mass media and other locally available platforms and channel
more resources towards girl child and 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. 131-134
United Nations
(1995). United Nations International Conference on Population and Development,
Cairo 5-13 September, 1994. Programme of Action. New York: United Nations,
Department for Economic and Social Information and Policy Analysis.
World Health Organization (WHO). The World Health Report.
Geneva: WHO; 1998.
World Health
Organization (2011). WHO Guidelines on Preventing Early Pregnancy and Poor
Reproductive Outcomes among Adolescents in Developing Countries. Geneva.
Gribbl JN., & J.Bremner J (2012). “Achieving a
demographic dividend.” Population Bulletin 67 (2). 2012
Graff M & Bremner
J (2014). A practical guide to population and development Washington:
Population Reference Bureau.
Canning D & Schultz TP (2012). The economic consequences
of reproductive health and family planning. Lancet, 380 (9837):165-71
