|
1990 2006 |
0.0543 0.0803 |
2.3% 2.5% |
(80.1%) |
(157.9%) 0.0762 (140.3%) 0.0952 (118.6%) |
(-138.0%) -0.0305 (-56.2%) -0.0360 (-44.8%) |
|
Asia 1971 |
0.1088 |
7.2% |
0.0084 (7.7%) |
0.1246 (114.5%) |
-0.0242 (-22.2%) |
|
1990 |
0.0467 |
9.9% |
0.0093 (20.0%) |
0.0654 (139.9%) |
-0.0280 (-59.9%) |
|
2006 |
0.0350 |
13.3% |
0.0069 (19.6%) |
0.0457 (130.3%) |
-0.0175 (-49.9%) |
|
China 1971 |
0.0590 |
2.7% |
0.0006 (1.1%) |
0.0663 (112.5%) |
-0.0080 (-13.6%) |
|
1990 |
0.0446 |
5.9% |
0.0005 (1.1%) |
0.0507 (113.7%) |
-0.0066 (-14.8%) |
|
2006 |
0.0095 |
15.5% |
0.0000 (0.0%) |
0.0096 (101.2%) |
0.0095 (-1.2%) |
Source: Authors’ own calculations based on the IEA (2009a, 2009b). The percentages in the
second column show the weight of GDP relative to global GDP while in the remaining columns
the weights of the different components in intra-group inequality are given.
The first column shows the cross country inequality within each of the regions
considered. The factorial decomposition analysis for the different regions
provides a much more detailed and interesting information. For instance, it
allows identifying in which groups the weight of both the transformation index
and the interaction component are relevant enough to have increased their
importance in the intra-group component analyzed previously. This way, we are
able to identify certain divergent patterns that are reflected in the behaviour of
the different factors at regional level.
16
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