Abstract
While spatial data analysis has received increasing attention in demographic studies, it remains a difficult subject to learn for practitioners due to its complexity and various unresolved issues. Here we give a practical guide to spatial demographic analysis, with a focus on the use of spatial regression models. We first summarize spatially explicit and implicit theories of population dynamics. We then describe basic concepts in exploratory spatial data analysis and spatial regression modeling through an illustration of population change in the 1990s at the minor civil division level in the state of Wisconsin. We also review spatial regression models including spatial lag models, spatial error models, and spatial autoregressive moving average models and use these models for analyzing the data example. We finally suggest opportunities and directions for future research on spatial demographic theories and practice.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 17-42 |
| Number of pages | 26 |
| Journal | Population Research and Policy Review |
| Volume | 27 |
| Issue number | 1 |
| DOIs | |
| State | Published - Feb 1 2008 |
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All Science Journal Classification (ASJC) codes
- Demography
- Management, Monitoring, Policy and Law
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Spatial regression models for demographic analysis. / Chi, Guangqing; Zhu, Jun.
In: Population Research and Policy Review, Vol. 27, No. 1, 01.02.2008, p. 17-42.Research output: Contribution to journal › Review article
TY - JOUR
T1 - Spatial regression models for demographic analysis
AU - Chi, Guangqing
AU - Zhu, Jun
PY - 2008/2/1
Y1 - 2008/2/1
N2 - While spatial data analysis has received increasing attention in demographic studies, it remains a difficult subject to learn for practitioners due to its complexity and various unresolved issues. Here we give a practical guide to spatial demographic analysis, with a focus on the use of spatial regression models. We first summarize spatially explicit and implicit theories of population dynamics. We then describe basic concepts in exploratory spatial data analysis and spatial regression modeling through an illustration of population change in the 1990s at the minor civil division level in the state of Wisconsin. We also review spatial regression models including spatial lag models, spatial error models, and spatial autoregressive moving average models and use these models for analyzing the data example. We finally suggest opportunities and directions for future research on spatial demographic theories and practice.
AB - While spatial data analysis has received increasing attention in demographic studies, it remains a difficult subject to learn for practitioners due to its complexity and various unresolved issues. Here we give a practical guide to spatial demographic analysis, with a focus on the use of spatial regression models. We first summarize spatially explicit and implicit theories of population dynamics. We then describe basic concepts in exploratory spatial data analysis and spatial regression modeling through an illustration of population change in the 1990s at the minor civil division level in the state of Wisconsin. We also review spatial regression models including spatial lag models, spatial error models, and spatial autoregressive moving average models and use these models for analyzing the data example. We finally suggest opportunities and directions for future research on spatial demographic theories and practice.
UR - http://www.scopus.com/inward/record.url?scp=38049043440&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=38049043440&partnerID=8YFLogxK
U2 - 10.1007/s11113-007-9051-8
DO - 10.1007/s11113-007-9051-8
M3 - Review article
AN - SCOPUS:38049043440
VL - 27
SP - 17
EP - 42
JO - Population Research and Policy Review
JF - Population Research and Policy Review
SN - 0167-5923
IS - 1
ER -