Volume 28 - Article 10 | Pages 271–312
Progress in Spatial Demography
|Date received:||31 Jul 2012|
|Date published:||13 Feb 2013|
|Keywords:||geographically weighted regression, multilevel modeling, pattern analysis, spatial demography, spatial econometrics|
|Weblink:||You will find all publications in this Special Collection “Spatial Demography” at http://www.demographic-research.org/special/13/|
Background: Demography is an inherently spatial science, yet the application of spatial data and methods to demographic research has tended to lag that of other disciplines. In recent years, there has been a surge in interest in adding a spatial perspective to demography. This sharp rise in interest has been driven in part by rapid advances in geospatial data, new technologies, and methods of analysis.
Objective: We offer a brief introduction to four of the advanced spatial analytic methods: spatial econometrics, geographically weighted regression, multilevel modeling, and spatial pattern analysis. We look at both the methods used and the insights that can be gained by applying a spatial perspective to demographic processes and outcomes. To help illustrate these substantive insights, we introduce six papers that are included in a Special Collection on Spatial Demography. We close with some predictions for the future, as we anticipate that spatial thinking and the use of geospatial data, technology, and analytical methods will change how many demographers address important demographic research questions.
Conclusions: Many important demographic questions can be studied and framed using spatial approaches. This will become even more evident as changes in the volume, source, and form of available demographic data - much of it geocode - —further alter the data landscape, and ultimately the conceptual models and analytical methods used by demographers. This overview provides a brief introduction to a rapidly changing field.
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