TY - JOUR
T1 - Bringing regional detail to a CGE model using census data
AU - Wittwer, Glyn
AU - Horridge, Jonathan
PY - 2010
Y1 - 2010
N2 - The number of regions and sectors in most regional CGE models is small, due to data and computing limitations. The uses of such models will broaden if they have larger CGE databases. The TERM model combines a massive database with a variable aggregation facility and techniques to economize on computing capacity. This paper goes further, by outlining the use ofsmall-region census data to devise a CGE database with an unprecedented number ofregions. Already, the original TERM methodology has been used to devise multi-regional models for a number of countries. Census detail could enhance the detail in these models. Here we group small regions of Australia to develop the first bottom-up regional CGE model which distinguishes all 150 Federal single-seat electoral districts.
AB - The number of regions and sectors in most regional CGE models is small, due to data and computing limitations. The uses of such models will broaden if they have larger CGE databases. The TERM model combines a massive database with a variable aggregation facility and techniques to economize on computing capacity. This paper goes further, by outlining the use ofsmall-region census data to devise a CGE database with an unprecedented number ofregions. Already, the original TERM methodology has been used to devise multi-regional models for a number of countries. Census detail could enhance the detail in these models. Here we group small regions of Australia to develop the first bottom-up regional CGE model which distinguishes all 150 Federal single-seat electoral districts.
UR - https://www.scopus.com/pages/publications/77951971631
U2 - 10.1080/17421771003730695
DO - 10.1080/17421771003730695
M3 - Article
SN - 1742-1780
VL - 5
SP - 229
EP - 255
JO - Spatial Economic Analysis
JF - Spatial Economic Analysis
IS - 2
ER -