Changing Determinants of low fertility and diffusion: a spatial analysis for Italy
Changing Determinants of low fertility and diffusion: a spatial analysis for Italy
Italy is a case study in lowest-low fertility. Its internal heterogeneity is substantial and changing over time. The paper has two main aims. First, it aims at investigating whether the theoretical framework offered by the diffusionist perspective to fertility transition could still be relevant in explaining fertility changes in contemporary advanced societies. Second, the paper aims at investigating if and how the associations between fertility and a series of indicators of secularisation, female occupation, contribution of fertility of immigrants, and economic development change across space and over time. We make use of geographically weighted regressions and spatial panel regressions to model explicitly spatial dependence in fertility among Italian provinces over the period between 1999 and 2010. Results show that spatial dependence in provincial fertility persists even after controlling for standard correlates of fertility, consistently with a diffusionist perspective. Further, the local association between fertility and its correlates is not homogeneous across provinces. The strength and in some cases also the direction of such associations vary spatially, suggesting that the determinants of low fertility change across space. Finally, the associations between fertility and its correlates change over time.
low fertility, italy, geographically weighted regression, spatial panel models
1-18
Vitali, Agnese
56acb6b8-5161-4106-9e73-20712840d675
Billari, Francesco C.
b6fdac68-4fd1-4fe1-ad75-6b4b0115c6bb
12 November 2015
Vitali, Agnese
56acb6b8-5161-4106-9e73-20712840d675
Billari, Francesco C.
b6fdac68-4fd1-4fe1-ad75-6b4b0115c6bb
Vitali, Agnese and Billari, Francesco C.
(2015)
Changing Determinants of low fertility and diffusion: a spatial analysis for Italy.
Population, Space and Place, .
(doi:10.1002/psp.1998).
Abstract
Italy is a case study in lowest-low fertility. Its internal heterogeneity is substantial and changing over time. The paper has two main aims. First, it aims at investigating whether the theoretical framework offered by the diffusionist perspective to fertility transition could still be relevant in explaining fertility changes in contemporary advanced societies. Second, the paper aims at investigating if and how the associations between fertility and a series of indicators of secularisation, female occupation, contribution of fertility of immigrants, and economic development change across space and over time. We make use of geographically weighted regressions and spatial panel regressions to model explicitly spatial dependence in fertility among Italian provinces over the period between 1999 and 2010. Results show that spatial dependence in provincial fertility persists even after controlling for standard correlates of fertility, consistently with a diffusionist perspective. Further, the local association between fertility and its correlates is not homogeneous across provinces. The strength and in some cases also the direction of such associations vary spatially, suggesting that the determinants of low fertility change across space. Finally, the associations between fertility and its correlates change over time.
Text
PSP2015.pdf
- Accepted Manuscript
More information
Accepted/In Press date: 1 October 2015
Published date: 12 November 2015
Keywords:
low fertility, italy, geographically weighted regression, spatial panel models
Organisations:
Social Statistics & Demography
Identifiers
Local EPrints ID: 384174
URI: http://eprints.soton.ac.uk/id/eprint/384174
ISSN: 1544-8444
PURE UUID: 8307944b-d226-460f-a2ca-671de552d751
Catalogue record
Date deposited: 02 Dec 2015 09:43
Last modified: 15 Mar 2024 05:22
Export record
Altmetrics
Contributors
Author:
Agnese Vitali
Author:
Francesco C. Billari
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics