International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Forecasting Total Fertility Rate (TFR) in Morocco Using an Artificial Neural Network Approach

Abstract

In this research article, the ANN approach was applied to analyze TFR in Morocco. 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 Morocco. The results of the study indicate that annual total fertility rates in Morocco are generally likely to remain around 2.4 births per woman throughout the out-of-sample period. Therefore, the authorities in Morocco are encouraged to continue improving access to sexual and reproductive health (SRH) services among adolescents and young adults to prevent adverse SRH outcomes, and empowerment of women.

Country : Zimbabwe

1 Dr. Smartson. P. NYONI2 Tatenda. A. CHIHOHO3 Thabani NYONI

  1. ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
  2. Independent Health Economist, Zimbabwe
  3. SAGIT Innovation Center, Harare, Zimbabwe

IRJIET, Volume 5, Issue 8, August 2021 pp. 216-219

doi.org/10.47001/IRJIET/2021.508045

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