Forecasting Total Fertility Rate (TFR) In Sri Lanka Using a Machine Learning Algorithm

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: 323-326

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 24-09-2021

doi Logo doi.org/10.47001/IRJIET/2021.508070

Abstract
In this research paper, the ANN approach was applied to analyze TFR in Sri Lanka. 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 Sri Lanka. The results of the study indicate that annual total fertility rates in Sri Lanka are likely to remain around 2.3 births per woman over the out-of-sample period. Therefore, the authorities in Sri Lanka are encouraged to continue improving accessibility of family planning services to adolescents and young adults to minimize adverse SRH outcomes.
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 Sri Lanka Using a Machine Learning Algorithm Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 8, pp 323-326, August 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.508070

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