Testing Fractional Persistence and Nonlinearity in Infant Mortality Rates of Asia Countries

Yaya, OlaOluwa S and Adekoya, Oluwasegun B. and Babatunde, Oluwagbenga T. (2021): Testing Fractional Persistence and Nonlinearity in Infant Mortality Rates of Asia Countries.

Abstract

The infant mortality rates in 45 Asian countries (1960-2018), obtained from the Federal Reserve Bank of St. Louis database, are investigated using the I(d) framework, which allows for simultaneous estimation of the degree of persistence and nonlinearities in infant mortality rates as well as their growth rates. A high degree of persistence in the decreases of mortality rate is found with nonlinear evidence in the majority of the cases, confirming nonlinear dynamics of mortality rates. In the growth of mortality rates, we find ten countries (Armenia, Indonesia, Israel, Japan, Kuwait, Myanmar, Saudi Arabia, Sri Lanka, Thailand, and UAE) with evidence of mean reversion. Health management in those listed countries needs to kick start interventions that improve the survival rates of infants.

• Item Type: MPRA Paper
• Language: English
• Keywords: Infant mortality rate; Death rate; Fractional persistence; Nonlinearity; Asia
• Subjects: C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes; C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C40 - General; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C60 - General

References

Booth, H. (2006). Demographic Forecasting: 1980–2005 in Review. International Journal of Forecasting, 22, 547–581.

Booth, H., Maindonald, J., & Smith, L. (2002). Applying Lee-Carter under conditions of variable mortality decline. Population Studies, 56, 325–336.

Caporale, G. M. & Gil-Alana, L. A. (2015). Infant mortality rates: time trends and fractional integration. Journal of Applied Statistics, 42(3), 589-602.

Cuestas, J. C. & Gil-Alana, L. A. (2016). A nonlinear approach with long range dependence based on Chebyshev polynomials. Studies in Nonlinear Dynamics and Econometrics, 20(1), 57-94.

Federal Reserve Bank of St Louis (2020). Infant Mortality Rate, Number per 1,000 Live Births, Annual, Not Seasonally Adjusted. Federal Reserve Economic Data (FRED). https://fred.stlouisfed.org/searchresults?st=infant+mortality+rate. Date last accessed: 12.07.2020.

Granger, C. W. J. & Joyeux, R. (1980). An introduction to long memory time series and fractional differencing. Journal of Time Series Analysis, 1(1), 15-29.

Hill, K., Pande, R., Mahy M. & Jones, G. (1999). Trends in Child Mortality in the Developing World: 1960-1990. UNICEF. New York, NY 10017 USA.

Hosking, J. R. M. (1981). Fractional Differencing. Biometrica, 68(1), 168-176.

Lee, R. & Carter, L. (1992). Modeling and forecasting U.S. mortality. Journal of the American Statistical Association, 87(419), 659–675.

Park, R. E. & Mitchell, B. M. (1980). Estimating the autocorrelated error model with trended data, Journal of Econometrics, 13(2), 185-201.

Robinson, P. M. (1994). Efficient tests of nonstationary hypotheses. Journal of the American Statistical Association, 89(No.428), 1420-1437.

Shang, H. L., Hyndman, R. J., & Booth, H. (2011). Point and interval forecasts of mortality rates and life expectancy. A comparison of ten principal component methods for forecasting mortality rates. Demographic Research, 25(5), 173–214.

UNICEF (2013). Levels & Trends in Child Mortality. Report 2013, United Nations Children’s Fund.