Full Citation

Title: Population distribution over time: modelling local spatial dependence with a CAR process

Citation Type: Journal Article

Publication Year: 2020

ISBN:

ISSN: 1742-1772

DOI: 10.1080/17421772.2020.1708442

NSFID:

PMCID:

PMID:

Abstract: The effectiveness of local spatial dependence in shaping the population density distribution is investigated. Individual location preferences are modelled by considering the status-related features of a given spatial unit and its neighbours as well as local random spatial dependence. The novelty is framing such a dependence through conditionally autoregressive (CAR) census random effects that are added to a spatially lagged explanatory variable X (SLX) setting. The results not only confirm that controlling for the spatial dimension is relevant but also indicate that local spatial dependence warrants consideration when determining the population distribution of recent decades. In this respect, the framework turns out to be useful for the analysis of microdata in which individual relationships (in a same spatial unit) enforce local spatial dependence.

Url: https://www.tandfonline.com/doi/abs/10.1080/17421772.2020.1708442

Url: https://www.tandfonline.com/doi/full/10.1080/17421772.2020.1708442

User Submitted?: No

Authors: Epifani, Ilenia; Ghiringhelli, Chiara; Nicolini, Rosella

Periodical (Full): Spatial Economic Analysis

Issue: 2

Volume: 15

Pages: 120-144

Data Collections: IPUMS NHGIS

Topics: Other, Population Mobility and Spatial Demography

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