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Forecast of demographic variables using the ARIMA Model in India

International Journal of Statistics and Applied Mathematics · 2023 · Vol. 8(5S) · pp. 1009–1018
Bheemanna BheemannaM. N. MegeriHuchesh H Budihal

Abstract

Life expectancy at birth reflects the overall mortality level of a population. Three important demographic indicators—Life Expectancy at Birth, Death Rate, and Infant Mortality Rate (IMR)—were examined for 1971 to 2020 and projected in this study for the years 2021 to 2030. The projections that went along with the forecasts were created using statistical models. The Auto-regressive Integrated Moving Averages (ARIMA) is discussed in this article for the selected demographic variables. We also used the AIC and BIC to find the best-fitting ARIMA model for the data and provide the life expectancy at birth, Death rate and IMR forecasts for future years. The ARIMA (0, 2, 1), (3, 1, 0), and (3, 1, 0) models were also found to be the best-fitting models for India's Life expectancy at birth, Death rate and IMR respectively. The life expectancy at birth is best fits compared to other variables based on the MAPE values.

Global Health Care IssuesInsurance, Mortality, Demography, Risk ManagementAgricultural risk and resilienceLife expectancyAutoregressive integrated moving averageStatisticsDemographyMortality rateInfant mortalityBirth ratePopulationEconometricsMathematics
Citations
2
FWCI
0.87
field-weighted impact
References
8
Percentile
79%
vs. same field & year
Citations per year
References
Time Series Analysis: Forecasting and Control
Technometrics · 1977 · 3,845 citations
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