Measuring regional labour markets in South Africa: how robust are sub-national estimates from the Quarterly Labour Force Survey?

This article explores the limitations of using data from the Quarterly Labour Force Survey (QLFS) to estimate robust sub-national labour market indicators in South Africa. The precision of labour market indices in the QLFS is very sensitive to which geographic scale is examined - national, provincial or metro - and in each instance the size of the population of the province or metro. The results show that errors from sampling at regional and city levels may be prohibitively large although in some instances broad patterns between regions can be identified notwithstanding a fairly blunt instrument. The findings highlight the imperative to be transparent about sampling errors and to foster sensitivity within government, business and the public in general. This exercise is instructive for generating other regional socio-economic indicators that are based upon similar household sample surveys such as the General Household Survey, Living Conditions Survey and Income and Expenditure Survey.

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Publication Details

Journal
Human Science Research Council SA
Published
2026-05-23
DOI
https://doi.org/10.14749/32380683
Primary Topic
Income, Poverty, and Inequality
Type
article
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article

Measuring regional labour markets in South Africa: how robust are sub-national estimates from the Quarterly Labour Force Survey?

Human Sciences Research Council
Human Science Research Council SA
Income, Poverty, and Inequality
article

Measuring regional labour markets in South Africa: how robust are sub-national estimates from the Quarterly Labour Force Survey?

Human Sciences Research Council
article en

Abstract

This article explores the limitations of using data from the Quarterly Labour Force Survey (QLFS) to estimate robust sub-national labour market indicators in South Africa. The precision of labour market indices in the QLFS is very sensitive to which geographic scale is examined - national, provincial or metro - and in each instance the size of the population of the province or metro. The results show that errors from sampling at regional and city levels may be prohibitively large although in some instances broad patterns between regions can be identified notwithstanding a fairly blunt instrument. The findings highlight the imperative to be transparent about sampling errors and to foster sensitivity within government, business and the public in general. This exercise is instructive for generating other regional socio-economic indicators that are based upon similar household sample surveys such as the General Household Survey, Living Conditions Survey and Income and Expenditure Survey.

Human Science Research Council SA
Decent work and economic growth
Openalex Percentile: Top 2%
Income, Poverty, and Inequality
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