Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/91850
Title: Detecting temporal anomalies with pseudo age groups : homeownership in Canada, 1981 to 2016
Authors: Yuan, Y
Gu, J
Guo, X 
Zhu, Y
Fu, Q
Issue Date: 2021
Source: Population, space and place, 2021, Early View, e2532, https://dx.doi.org/10.1002/psp.2532
Abstract: Methodological advances in demographic research, especially age-period-cohort (APC) analysis, primarily focus on developing new models yet often fail to consider practical concerns in empirical analysis. We propose a mixed approach that integrates multiple data imputation and structural change analysis in time series so that scholars can (i) construct pseudo age groups based on more coarsely grouped age data and (ii) identify temporal anomalies. This approach is illustrated using multiple waves of Canadian Population Census data (1981–2016). We construct pseudo age groups based on more coarse age information available in the Census data and identify a local anomaly in the temporal trajectory of homeownership in Canada's less populous provinces and territories. These findings are assessed and validated in comparison with results from more populous Canadian provinces. This research broadens the methodological repertoire for demographers, geographers, and social scientists in general and extends the literature on homeownership in an understudied area.
Keywords: Age-period-cohort analysis
Homeownership
Multiple imputation
Pseudo data
Structural change analysis
Publisher: John Wiley & Sons Ltd.
Journal: Population, space and place 
EISSN: 1544-8452
DOI: 10.1002/psp.2532
Appears in Collections:Journal/Magazine Article

Open Access Information
Status embargoed access
Embargo End Date 0000-00-00 (to be updated)
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

28
Citations as of May 22, 2022

SCOPUSTM   
Citations

1
Citations as of May 20, 2022

WEB OF SCIENCETM
Citations

1
Citations as of May 19, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.