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  5. Spatial variability of total fertility rate and crude birth rate in a low-fertility country: Patterns and trends in regional and local scale heterogeneity across Italy, 2002–2018
 
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Spatial variability of total fertility rate and crude birth rate in a low-fertility country: Patterns and trends in regional and local scale heterogeneity across Italy, 2002–2018

Author(s)
Salvati, Luca  
Benassi, Federico  
Miccoli, Sara  
Rabiei-Dastjerdi, Hamidreza  
Matthews, Stephen A.  
Uri
http://hdl.handle.net/10197/12631
Date Issued
2020-11
Date Available
2021-11-11T14:35:32Z
Embargo end date
2022-10-07
Abstract
Fertility is a key process shaping long-term population dynamics. Distinctive fertility trends have characterized demographic transitions, exhibiting sequential periods of spatial convergence and divergence. This descriptive study investigates the spatiotemporal evolution of Total Fertility Rate (TFR) and Crude Birth Rate (CBR) at different geographical scales in Italy between 2002 and 2018. Descriptive statistics of the TFR and CBR values across geographical scales were computed and the associated maps were prepared for the most detailed spatial levels available; specifically, down to the municipality level. Spatial analysis at the provincial and municipality level was based on both global and local Moran's indexes. Southern Italy, a mostly disadvantaged region, was characterized by relatively stable fertility patterns; fertility then decreased following an opposite trend with respect to economic conditions. The reverse relationship was observed in Northern Italy. As such, economic expansion and recession impacted fertility more intensively in Northern Italy.
Type of Material
Journal Article
Publisher
Elsevier
Journal
Applied Geography
Volume
124
Copyright (Published Version)
2020 Elsevier
Subjects

Total fertility rate ...

Crude birth rate (CBR...

Spatial autocorrelati...

Local and regional de...

Italy

2nd demographic trans...

Great recession

Europe

States

DOI
10.1016/j.apgeog.2020.102321
Language
English
Status of Item
Peer reviewed
ISSN
0143-6228
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
No Thumbnail Available
Name

Applied Geography_2020.pdf

Size

939.11 KB

Format

Adobe PDF

Checksum (MD5)

c61e66ad650603bfe9b539e023a3d0b5

Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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