TY - JOUR
T1 - A framework for exploratory space-time analysis of economic data
AU - Ye, Xinyue
AU - Rey, Sergio
N1 - Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2013/2
Y1 - 2013/2
N2 - The development of exploratory spatial data analysis methods is an active research domain in the field of geographic information science (GIS). At the same time, the coupled space-time attributes of economic phenomena are difficult to be represented and examined. Both GIS and economic geography are faced with the challenges of dealing with the temporal dynamics of geographic processes and spatial dynamics of economic development across scales and dimensions. This paper thus suggests a novel way to generalize the characteristics and the structure of space-time data sets, using regional economic data as the example. Accordingly, a reasonable number of general questions (data analysis tasks) can be abstracted. Then, tools (methods) may be suggested on that basis. The cross-fertilization between exploratory spatial data analysis (ESDA) and spatial economics is also identified and illustrated by the capabilities of these components, which have uncovered some interesting patterns and trends in the spatial income data of China and the United States. Through exploratory analysis of economic data, the detection of rich details of underlying geographical and temporal processes would be the first step toward such cross-fertilization. In addition, this exploratory analytical framework can be applied to other data sets that are also measured for areal units at multiple points in time.
AB - The development of exploratory spatial data analysis methods is an active research domain in the field of geographic information science (GIS). At the same time, the coupled space-time attributes of economic phenomena are difficult to be represented and examined. Both GIS and economic geography are faced with the challenges of dealing with the temporal dynamics of geographic processes and spatial dynamics of economic development across scales and dimensions. This paper thus suggests a novel way to generalize the characteristics and the structure of space-time data sets, using regional economic data as the example. Accordingly, a reasonable number of general questions (data analysis tasks) can be abstracted. Then, tools (methods) may be suggested on that basis. The cross-fertilization between exploratory spatial data analysis (ESDA) and spatial economics is also identified and illustrated by the capabilities of these components, which have uncovered some interesting patterns and trends in the spatial income data of China and the United States. Through exploratory analysis of economic data, the detection of rich details of underlying geographical and temporal processes would be the first step toward such cross-fertilization. In addition, this exploratory analytical framework can be applied to other data sets that are also measured for areal units at multiple points in time.
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U2 - 10.1007/s00168-011-0470-4
DO - 10.1007/s00168-011-0470-4
M3 - Article
AN - SCOPUS:84873273630
VL - 50
SP - 315
EP - 339
JO - Annals of Regional Science
JF - Annals of Regional Science
SN - 0570-1864
IS - 1
ER -