Abstract
This study examines the time series behavior of infant mortality rates within a long memory approach with non-linear trends using data for 37 countries. The main results show significant differences both in the degree of integration and non-linearities among the analyzed series. Furthermore, non-linearities in the time trends are found in most of the cases, in contrast with the main assumption of linearity used in the literature. Finally, the results on the integration order of the series have important policy implications in many areas, such as on international convergence in mortality rates, on the income and infant mortality relationship, and, on whether health policy interventions will have transitory or permanent effects on infant mortality rates.
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Notes
See Cuestas and Gil-Alana (2015).
We only used series with sample sizes higher than 50 observations. Otherwise, the results would be completely unreliable.
Based on the short sample sizes used in this application, we believe that the I(d) specification with white noise errors can be sufficient to describe the time dependence in the data, with no need of extra (weakly) autocorrelation in the error term.
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Acknowledgments
Luis A. Gil-Alana gratefully acknowledges financial support from gratefully acknowledges financial support from the Ministerio de Economía y Competitividad (ECO2014-55236). Juncal Cunado gratefully acknowledges financial support from the Ministerio de Economía y Competitividad (ECO2014-55496). Comments from the Editor and two anonymous reviewers are gratefully acknowledged.
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Gil-Alana, L.A., Cunado, J. & Gupta, R. Persistence, Mean-Reversion and Non-linearities in Infant Mortality Rates. Soc Indic Res 131, 393–405 (2017). https://doi.org/10.1007/s11205-016-1253-1
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DOI: https://doi.org/10.1007/s11205-016-1253-1