Identification of Neonatal Healthcare Solutions in Austria Using Empirical Evidence Generated By the ARIMA Model
Abstract
Time series forecasting techniques continue to
attract the attention of researchers globally. Their relevance in public health
is well recognized as many researchers are using statistical, econometric and
machine learning approaches to analyze linear and nonlinear data.This research
paper uses annual time series data on neonatal mortality rate (NMR) for Austria
from 1960 to 2019 to predict future trends of NMR over the period 2020 to 2030.
Unit root tests have shown that the series under consideration is an I (1)
variable. The optimal model based on AIC is the ARIMA (5,1,4) model. The ARIMA
model predictions indicate that NMR is likely to decline over the out-of-sample
period. Therefore, the Austrian government must craft and implement neonatal policies to address causes of neonatal deaths so as to keep
neonatal mortality under control.
Country : Zimbabwe
1 Dr. Smartson. P. NYONI2 Thabani NYONI
ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
Independent Researcher & Health Economist, Harare, Zimbabwe
IRJIET, Volume 7, Issue 8, August 2023 pp. 196-201
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