Abstract
In general, life expectancy has increased in the whole of Europe in recent decades, especially in western European countries. However, this study detected that the observed mortality is higher than expected in eastern European countries, widening the gap between these countries and Western Europe. The main objective of this paper is to study the space dependence of significant clusters through a spatial panel data model. There are many studies that address the decrease of mortality in Europe. None of them uses spatial methodology to detect significant clusters between countries with similar mortality, implementing in turn a spatial model which controls the space dependence of the European countries over time. Thus, the objective of this study is to determine differentiated behavior areas and control the spatial interaction between European countries over time applying a spatial panel data model. The methodology takes into account the neighboring relationships between the countries. The performance of the model was assessed using the methods of goodness of fit, residual variance, and determination coefficient. This statistical methodology was applied to 26 European countries over the period 1990–2009. The R free software environment for statistical computing was used to perform the whole analysis.
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Support for the research presented in this paper was provided by a grant from Ministry of Economy and Competitiveness, project MTM2013–45381-P.
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Carracedo, P., Debón, A. (2017). Spatial Statistical Tools to Assess Mortality Differences in Europe. In: Londoño, J., Garrido, J., Jeanblanc, M. (eds) Actuarial Sciences and Quantitative Finance. ICASQF 2016. Springer Proceedings in Mathematics & Statistics, vol 214. Springer, Cham. https://doi.org/10.1007/978-3-319-66536-8_3
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