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DOI Prefix: 10.47001/IRJIET

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

Dr. Smartson. P. NYONIZICHIRe Project, University of Zimbabwe, Harare, ZimbabweTatenda. A. CHIHOHOIndependent Health Economist, ZimbabweThabani NYONISAGIT Innovation Center, Harare, Zimbabwe

Vol 5 No 8 (2021): Volume 5, Issue 8, August 2021 | Pages: 216-219

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 14-09-2021

doi Logo doi.org/10.47001/IRJIET/2021.508045

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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.

Keywords

ANN, Forecasting, Total fertility rate (TFR).


Citation of this Article

Dr. Smartson. P. NYONI, Tatenda. A. CHIHOHO, Thabani NYONI, “Forecasting Total Fertility Rate (TFR) in Morocco Using an Artificial Neural Network Approach” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 8, pp 216-219, August 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.508045

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