Forecasting Adolescent Fertility Rate for Guinea Using Holt’s Double Exponential Smoothing Technique

Abstract

This research article uses annual time series data of adolescent fertility rate for Guinea from 1960 to 2020 to predict future trends of adolescent fertility rate over the period 2021 to 2030. The study utilizes Holt’s linear exponential smoothing model. The optimal values of smoothing constants α and β are0.9 and0.6 respectively based on minimum MSE. The results of the study indicate that annual adolescent fertility will continue to decline but still remain very high throughout the out of sample period. Therefore, we encourage authorities in Guinea to scale educational campaigns among the communities, continuously promote girl child education, increase funding towards youth empowerment programs and set up adolescent friendly facilities that are well resourced to address adolescent health issues.

Country : Zimbabwe

1 Smartson. P. NYONI2 Thabani NYONI

  1. ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
  2. Independent Researcher & Health Economist, Harare, Zimbabwe

IRJIET, Volume 6, Issue 12, December 2022 pp. 291-295

doi.org/10.47001/IRJIET/2022.612055

References

  1. United Nations (2015). transforming our world: The 2030 agenda for sustainable development, A/RES/70/1. New York: UN General Assembly.
  2. UN (2020) sustainable development goals. https://www.un.org/sustainabl development/development-agenda
  3. UNICEF (2018). Every Child alive. New York: UNICEF
  4. United Nations (2016). Transforming our world: The 2030 agenda for sustainable development.
  5. 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.
  6. de Vienne C.M., Creveuil C., and Dreyfus M (2009). Does young maternal age increase the risk of adverse obstetric, fetal and neonatal outcomes: a cohort study. Eur J Obstet Gynecol Reproductive Biology. 147(2):151–6.
  7. Banke-Thomas O.E., Banke-Thomas A.O., and Ameh C.A (2017). Factors influencing utilization of maternal health services by adolescent mothers in Low-and middle-income countries: a systematic review. BMC Pregnancy Childbirth. 17(1):1–14.
  8. Grønvik T., and Fossgard Sandøy I (2018). Complications associated with adolescent childbearing in Sub-Saharan Africa: A systematic literature review and meta-analysis. PLoS ONE. 2018;13(9):e0204327
  9. World Health Organization (2014). Adolescent pregnancy: fact sheet number 364. Geneva. http://www.who.int/mediacentre/ factsheets/fs364/en/.
  10. United Nations Population Fund (2013). Adolescent pregnancy: a review of the evidence. New York: UNFPA; 2013. http://www.unfpa.org/ sites/default/files/pub-pdf/ADOLESCENT%20PREGNANCY_UNFPA.pdf.
  11. UNFPA (2015). State of the world population report 2015. New York: UNFPA; 2015. https://www.unfpa.org/sites/default/files/sowp/downloads/State_of_World_ Population_2015_EN.pdf.
  12. McMichael C., and Gifford S (2010). Narratives of sexual health risk and protection amongst young people from refugee backgrounds in Melbourne, Australia. Cult Health Sex. 2010; https://doi.org/10.1080/13691050903359265
  13. World Bank (2020). Adolescent fertility rate women aged 15-19 years.