Modelling Long-Range Dependence and Non-linearity in the Infant Mortality Rates of African Countries
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Modelling Long-Range Dependence and Non-linearity in the Infant Mortality Rates of African Countries OlaOluwa Simon Yaya 1 & Luis Alberiko Gil-Alana 2,3
Published online: 24 August 2020 # International Atlantic Economic Society 2020
Abstract Infant mortality rates in 34 Sub-Saharan African countries (1960–2016), obtained from the Federal Reserve Bank of St. Louis database, were examined in this paper by focusing on the degree of persistence and non-linearities in the growth rate series. Persistence deals with the degree of association between the observations. Nonlinearity occurs when departing from the linear assumption as in a time trend. These two issues are relevant in this context because they are intimately related. Based on the high degree of persistence observed in the series examined, instead of investigating structural breaks, which produce abrupt changes in the data, a non-linear approach was used based on Chebyshev polynomials in time, producing smooth rather than abrupt changes. This approach has never been examined in a unified framework in the treatment of infant mortality rates. The results indicate that half of the countries examined display non-linearities and the orders of integration of the series are extremely large in all cases, being around two in the majority of them. Looking at the growth rate series, significant negative trends were observed for: Chad, Equatorial Guinea and Mozambique. Evidence of mean reversion and thus transitory shocks, were observed for Lesotho, Rwanda, Botswana and Mozambique. Time dynamics of the series were expected to persist in order to ascertain the decline in mortality rates. Therefore, serious government interventions are required in managing infant health in these countries. Keywords Infant mortality rates . Fractional integration . Long range dependence . Nonlinearity . Africa * OlaOluwa Simon Yaya [email protected]
1
Economic and Financial Statistics Unit, Department of Statistics, University of Ibadan, Ibadan, Nigeria
2
Faculty of Economics, University of Navarra, Pamplona, Spain
3
Facultad de C. Juridicas y Empresariales, Universidad Francisco de Vitoria, Madrid, Spain
304
Yaya O.O.S., Gil-Alana L.A.
JEL Classification C22 . C40 . D60
Introduction The infant mortality rate (IMR) is defined as the probability of dying between birth and the first birthday, and this is usually measured as deaths per 1000 live births. In advanced countries, such as the Organisation of Economic Cooperation and Development (OECD) group, government interventions in health technology, better access to health care and disease prevention for infants and children have assisted considerably in reducing the mortality rates of infants and children. Meanwhile, as a result of limited facilities available in many African countries, the mortality rates are still high compared to those in of non-African countries despite health management interventions. Furthermore, with the overall decline in IMRs in Africa, mortality remains at unacceptably high levels, and about half of all dea
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