Creating a 2000 IES-LFS Database in Stata

PROVIDE Project Technical Paper 2005:1

The personwgt.dta file, which contains alternative but unofficial person-level weights for IES
2000, is also merged with person.dta at this point.³²

Next two sub-do-files are run within person.do. The first is do-file factors.do, which
converts employment information contained in variable jobcode to create factor codes as used
in the SAM (variable factors). Variable jobcode is based on answers given to the following
question in the IES 2000 questionnaire: “What kind of work did [the respondent] do in
his/her main job during the past seven days?” Statistics South Africa uses this information to
give each respondent a four-digit occupation code based on the International Standard
Classification of Occupations (ISCO 88). The meta-data file included with the LFS 2000:2
data shows how these codes can be used to derive an aggregated occupation code variable
(factors) containing ten types of work and one category for ‘unspecified or not adequately
defined’ (see Table 7). This aggregation differs only in one respect to the occupation codes
used before in PROVIDE (2003b) in that ‘domestic workers’ have now replaced ‘armed
forces’.³³

Table 7: Occupation codes (variable factors)

Source: (SSA, 2002a)

The second do-file in person.do is do-file activities.do. Individuals were asked to indicate
in which industry they work. The answers were used to derive an industry code variable
called stccode, based on the International Standard Industrial Classification (ISIC 1993) of all
economic activities. Variable stccode was then used to group workers into 96 different

³² Statistics South Africa has been unable to confirm whether these new weights can be used, hence the
continued use of the old weights.

³³ Previously domestic workers were included under unskilled factors, but given that a separate industry for
domestic services is also included in the SAM this distinction is useful. Armed forces used to be a
separate group, but there were concerns about the representativity of this group as a separate factor
account. Only 0.3% of African, 0.2% of Coloured and 0.2% of White workers were members of the
armed forces. On aggregate only 0.2% of all workers were employed as members of the armed forces
(IES 1995). On the other hand, 5.9% of African, 3.6% of Coloured, 0.4% of Asian and 0.1% of White
workers are domestic workers, giving an aggregate of 5.0% of all workers (IES 2000).

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