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Quarterly Labour Force Survey 2019, Quarter 3

South Africa, 2019
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Reference ID
ZAF_2019_QLFS-Q3_v01_M
Producer(s)
Statistics South Africa
Metadata
DDI/XML JSON
Created on
Jan 16, 2021
Last modified
Jan 16, 2021
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2996
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  • Study Description
  • Data Dictionary
  • Downloads
  • Get Microdata
  • Identification
  • Version
  • Scope
  • Coverage
  • Producers and sponsors
  • Sampling
  • Survey instrument
  • Data collection
  • Data processing
  • Data Access
  • Disclaimer and copyrights
  • Contacts
  • Metadata production
  • Identification

    Survey ID number

    ZAF_2019_QLFS-Q3_v01_M

    Title

    Quarterly Labour Force Survey 2019

    Subtitle

    Quarter 3

    Country
    Name Country code
    South Africa ZAF
    Study type

    Labor Force Survey [hh/lfs]

    Abstract

    The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (Stats SA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa.

    Kind of Data

    Sample survey data [ssd]

    Unit of Analysis

    Individuals

    Version

    Version Description

    v1.0: Edited, anonymised dataset for public distribution

    Version Date

    2020-04-03

    Version Notes

    This version was downloaded by DataFirst on the 2nd of March 2020.

    Scope

    Notes

    INDIVIDUALS: labour market activity, labour preferences, labour market history, demographic characteristics, marital status, employment status, education, grants, tax.

    Topics
    Topic Vocabulary URI
    employment [3.1] CESSDA http://www.nesstar.org/rdf/common
    in-job training [3.2] CESSDA http://www.nesstar.org/rdf/common
    labour relations/conflict [3.3] CESSDA http://www.nesstar.org/rdf/common
    retirement [3.4] CESSDA http://www.nesstar.org/rdf/common
    unemployment [3.5] CESSDA http://www.nesstar.org/rdf/common
    working conditions [3.6] CESSDA http://www.nesstar.org/rdf/common
    LABOUR AND EMPLOYMENT [3] CESSDA http://www.nesstar.org/rdf/common
    TRADE, INDUSTRY AND MARKETS [2] CESSDA http://www.nesstar.org/rdf/common
    DEMOGRAPHY AND POPULATION [14] CESSDA http://www.nesstar.org/rdf/common
    Keywords
    employment in-job training labour relations/conflict retirement unemployment working conditions labour and employment trade, industry and markets demography and population

    Coverage

    Geographic Coverage

    National coverage

    Geographic Unit

    Provincial and metropolitan level

    Universe

    The QLFS sample covers the non-institutional population of South Africa with one exception. The only institutional subpopulation included in the QLFS sample are individuals in worker's hostels. Persons living in private dwelling units within institutions are also enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.

    Producers and sponsors

    Primary investigators
    Name
    Statistics South Africa

    Sampling

    Sampling Procedure

    The Quarterly Labour Force Survey (QLFS) uses the Master Sample frame that has been developed as a general-purpose household survey frame that can be used by all other Stats SA household-based surveys having design requirements that are reasonably compatible with the QLFS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflects an 8,0% increase in the size of the Master Sample compared to the previous 2008 Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the QLFS estimates.

    The Master Sample is designed to be representative at the provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area the sample is representative of the different geography types that may exist within that metro. It is divided equally into four subgroups or panels called rotation groups. The rotation groups are designed in such a way that each of these groups has the same distribution pattern as that which is observed in the whole sample. They are numbered from one (1) to four (4), and these numbers also correspond to the quarters of the year in which the sample will be rotated for the particular group.

    The sample for the QLFS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.

    For each quarter of the QLFS, a quarter of the sampled dwellings are rotated out of the sample. These dwellings are replaced by new dwellings from the same PSU or the next PSU on the list. Thus, sampled dwellings are expected to remain in the sample for four consecutive quarters. It should be noted that the sampling unit is the dwelling, and the unit of observation is the household. Therefore, if a household moves out of a dwelling after being in the sample for two quarters (as an example) and a new household moves in, the new household will be enumerated for the next two quarters. If no household moves into the sampled dwelling, the dwelling will be classified as vacant (or unoccupied).

    Weighting

    The sample weights were constructed in order to account for the following: the original selection probabilities (design weights), adjustments for PSUs that were subsampled or segmented, excluded population from the sampling frame, non-response, weight trimming, and benchmarking to known population estimates from the Demographic Analysis Division within Stats SA.

    The eligible households in the sampled dwellings can be divided into two response categories: respondents and non-respondents. Weight adjustment is applied to account for the non-respondent households (e.g. refusal, no contact, etc.). The adjustment for total non-response was computed at two levels of non-response: PSU non-response and household non-response.

    In the final step of constructing the sample weights, all individuals within a household are assigned the same adjusted base weight. The adjusted base weights are calibrated such that the aggregate totals will match with independently derived population estimates (from the Stats SA Demographic Analysis Division) for various age, race and gender groups at national level and individual metropolitan and non-metropolitan area levels within the provinces. The calibrated weights are constructed using the constraint that each person within the same household should have the same calibrated weight, with a lower bound on the calibrated weights set at 50.

    Survey instrument

    Questionnaires

    The survey questionnaire consists of five section:
    Section 1: Biographical information (marital status, language, migration, education, training, literacy, etc.)
    Section 2: Economic activities for persons aged 15 years and older
    Section 3: Unemployment and economic inactivity for persons aged 15 years and older
    Section 4: Main work activities in the last week for persons aged 15 years and older
    Section 5: Earnings in the main job for employees, employers and own-account workers aged 15 years and older

    Data collection

    Dates of Data Collection
    Start End
    2019-07 2019-09

    Data processing

    Data Editing

    In general, imputation is used for item non-response (i.e. blanks within the questionnaire) and edit failures (i.e. invalid or inconsistent responses).

    Data Access

    Access authority
    Name Affiliation URL Email
    DataFirst University of Cape Town http://www.datafirst.uct.ac.za support@data1st.org
    Access conditions

    Public use files, available to all

    Citation requirements

    Statistics South Africa. Quarterly Labour Force Survey 2019: Q3 [dataset]. Version 1.0. Pretoria: Statistics South Africa [producer], 2019. Cape Town: DataFirst [distributor], 2020. DOI: https://doi.org/10.25828/1f1a-f611

    Disclaimer and copyrights

    Copyright

    Copyright, Statistics South Africa

    Contacts

    Contacts
    Name Affiliation Email URL
    DataFirst Helpdesk University of Cape Town support@data1st.org http://support.data1st.org/

    Metadata production

    DDI Document ID

    DDI_ZAF_2019_QLFS-Q3_v01_M

    Producers
    Name Affiliation Role
    DataFirst University of Cape Town DDI Producer
    Date of Metadata Production

    2020-04-03

    Metadata version

    DDI Document version

    Version 01: This survey metadata is identical to the same survey metadata (zaf-statssa-qlfs-2019-q3-v1.0) available in the DataFirst website except Document ID and Study ID.

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