Population ageing is one of the most important demographic phenomena of this century. Driven by fertility decline and the continuing extension of the life expectancy, the process of population ageing has not been uniform across time and space. Italy has one of the oldest populations in the world. The combination of a very old population and large territorial differences has made Italy an interesting laboratory for studying population ageing. The purpose of this paper is to study how population ageing developed between 2002 and 2014 across different geographical areas within Italy. We analyse patterns of population ageing across the five major socio-economic regions using the 110 provinces of Italy as our spatial units of analysis. We use a statistical model that integrates patterns of variation of population ageing data by accounting for autocorrelation in space and time. The results indicate that the provincial age structures tend to converge and demonstrate the importance of considering the role of space in studies of population ageing.
Population ageing in Italy: an empirical analysis of change in the ageing index across space and time / Reynaud, Cecilia; Miccoli, Sara; Lagona, Francesco. - In: SPATIAL DEMOGRAPHY. - ISSN 2364-2289. - (2018). [10.1007/s40980-018-0043-6]
Population ageing in Italy: an empirical analysis of change in the ageing index across space and time
Cecilia Reynaud;Sara Miccoli;Francesco Lagona
2018
Abstract
Population ageing is one of the most important demographic phenomena of this century. Driven by fertility decline and the continuing extension of the life expectancy, the process of population ageing has not been uniform across time and space. Italy has one of the oldest populations in the world. The combination of a very old population and large territorial differences has made Italy an interesting laboratory for studying population ageing. The purpose of this paper is to study how population ageing developed between 2002 and 2014 across different geographical areas within Italy. We analyse patterns of population ageing across the five major socio-economic regions using the 110 provinces of Italy as our spatial units of analysis. We use a statistical model that integrates patterns of variation of population ageing data by accounting for autocorrelation in space and time. The results indicate that the provincial age structures tend to converge and demonstrate the importance of considering the role of space in studies of population ageing.File | Dimensione | Formato | |
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