PROVIDE Project Technical Paper 2005:1
February 2005
Table 3: Cross-tabulating gender, location and race
|
Gender________ |
_____________Person-level_____________ |
__________Household-level__________ | ||
|
LFS^ IES→ |
Male__________ |
Female___________ |
Male___________ |
Female__________ |
|
Male___________ |
________48799 |
_____________424 |
__________15785 |
_____________79 |
|
Female__________ |
__________414 |
___________53960 |
____________46 |
_________10196 |
|
Accuracy________ |
_______99.2% |
__________99.2% |
_________99.7% |
_________99.2% |
|
Location________ |
__________Household-level__________ | |
|
LFS^ IES→ |
Urban_________ |
Rural______________ |
|
Urban__________ |
________14466 |
_____________383 |
|
Rural____________ |
__________1415 |
____________9854 |
|
Accuracy________ |
_______91.1% |
__________96.3% |
|
Race___________ |
________________________________Person-level________________________________ | |||
|
LFS^ IES→ |
African_________ |
Coloured__________ |
Asian___________ |
White___________ |
|
African__________ |
________83896 |
______________60 |
______________2_ |
______________12 |
|
Coloured________ |
_____________93 |
___________11462 |
______________12 |
_______________7 |
|
Asian___________ |
____________3_ |
_______________0_ |
__________2040 |
_______________4 |
|
White___________ |
____________36 |
_______________6_ |
_____________0_ |
__________5914 |
|
Accuracy________ |
_______99.8% |
__________99.4% |
_________99.3% |
_________99.6% |
|
_____________________________Household-level_____________________________ | ||||
|
LFS^ IES→ |
African_________ |
Coloured__________ |
Asian___________ |
White___________ |
|
African__________ |
________20719 |
________________15 |
______________1_ |
_________________5 |
|
Coloured________ |
_____________33 |
____________2689 |
_____________2_ |
______________1_ |
|
Asian___________ |
_____________1_ |
_______________0_ |
____________523 |
_______________2 |
|
White___________ |
____________6_ |
_______________2_ |
_____________0_ |
__________2098 |
|
Accuracy________ |
_______99.8% |
__________99.4% |
_________99.4% |
_________99.6% |
2.4. IES 2000 data problems
2.4.1. Literature review
Most of the data problems in the IES 2000 dataset can be ascribed to accounting and coding
errors (Poswell, 2003). There are also a few inconsistencies when compared to the IES 1995
dataset. This restricts the confidence with which conclusions can be drawn about changes in
income or expenditure over time. Van der Berg et al. (2003a) point out some of the specific
problems that they have encountered in the IES 2000 dataset:
• When compared to IES 1995 the 2000 results indicate that income in South Africa has
been declining strongly in real terms between 1995 and 2000. This contradicts national
accounts and demographic statistics also compiled by Statistics South Africa. Statistics
South Africa has since admitted that the surveys are incomparable.15, 16 When building a
15 This inconsistency is also pointed out by Simkins (2003). Simkins looks at the components of income and
finds that there are large and inexplicable drops in some of these components, particularly net profits
from business (half the 1995-level in nominal terms), occupational perquisites (down 42%) and
16
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