# South Africa - Quarterly Labour Force Survey 2011 - First Quarter, with ILO standard variables

Reference ID | ZAF_2011_LFS_Q1_v01_M_v01_A_ILOVAR |

Year | 2011 |

Country | South Africa |

Producer(s) | Statistics South Africa - Government of South Africa |

Collection(s) | |

Metadata | Documentation in PDF |

ILOSTAT Indicators Study website |

Created on

May 05, 2017

Last modified

Jun 22, 2017

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252

Sampling

Sampling Procedure

The QLFS sample covers the non-institutional population except for workers' hostels. However, persons living in private dwelling units within institutions are also enumerated. For example, within a school compound, you would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would therefore be excluded.

Survey requirements and design :

The Labour Force Survey frame has been developed as a general purpose household survey frame that can be used by all other household surveys irrespective of the sample size requirement of the survey. The sample size for the QLFS is roughly 30 000 dwellings and these are divided equally into four rotation groups, i.e. 7 500 dwellings per rotation group.

The sample is based on information collected during the 2001 Population Census conducted by Stats SA. In preparation for the 2001 census, the country was divided into 80 787 enumeration areas (EAs). Some of these EAs are small in terms of the number of households that were enumerated in them at the time of Census 2001. Stats SA's household-based surveys use a Master Sample which comprises of EAs that are drawn from across the country. For the purposes of the Master Sample the EAs that contained less than 25 households were excluded from the sampling frame, and those that contained between 25 and 99 households were combined with other EAs to form Primary Sampling Units (PSUs). The number of EAs per PSU ranges between one and four. On the other hand, very large EAs represent two or more PSUs.

The sample is designed to be representative at the provincial level and within provinces at the metro/non-metro level. Within the metros, the sample is further distributed by geography type. The four geography types are: urban formal, urban informal, farms and tribal. This implies that for example, that within a metropolitan area the sample is designed to be representative at the different geography types that may exist within that metro.

The current sample size is 3 080 PSUs. It is equally divided into four sub-groups 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 to four 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 redesigned Labour Force Survey is based on a stratified two-stage design with probability proportional to size (PPS) sampling of primary sampling units (PSUs) in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.

Sample rotation :

The sampled PSUs have been assigned to 4 rotation groups, and dwellings selected from the PSUs assigned to rotation group "1" are rotated in the first quarter. Similarly, the dwellings selected from the PSUs assigned to rotation group "2" are rotated in the second quarter, and so on. Thus, each sampled dwelling will 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, say 2 quarters and a new household moves in then 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 (unoccupied).

Each quarter, ¼ of the sampled dwellings rotate out of the sample and are replaced by new dwellings from the same PSU or the next PSU on the list. A total of 3 080 PSUs were selected for the redesigned LFS, and 770 have been assigned to each of the four rotation groups.

Deviations from Sample Design

The sample is designed to be representative at provincial level and within provinces at metro/non-metro level. Within the metros, the sample is further distributed by geography type. The design effect compares the variance of the estimate from the sample design that was actually implemented to the variance of the estimate that would have been obtained from a simple random sample (SRS) design. Stratification generally leads to a gain in efficiency over simple random sampling, but clustering leads to deterioration in the efficiency of the sample design due to positive intra-cluster correlation among units in the cluster (PSUs in the case of QLFS).

Response Rate

Response rate by province:

Western Cape - 81.9%

Eastern Cape - 98.9%

Northern Cape - 91.5%

Free State - 95.9%

KwaZulu-Natal - 97.4%

North West - 94.9%

Gauteng - 82.0%

Mpumalanga - 96.2%

Limpopo - 99.5%

South Africa - 92.9%

Weighting

Stats SA updated the QLFS results (2008-2013) to reflect the new population benchmarks from Census 2011. Although the weighting changes are not clearly documented by Stats SA, users are advised to remain aware of these slight calibration differences between the previous version and the current (revised) data version when employing weights.

The sampling weights for the data collected from the sampled households are constructed so that the responses could be properly expanded to represent the entire civilian population of South Africa. The weights are the result of calculations involving several factors, including original selection probabilities, adjustment for non-response, and benchmarking to known population estimates from the Demographic division of Stats SA. The base weight is defined as the product of the provincial Inverse Sampling Rate (ISR) and the three adjustment factors, namely adjustment factor for informal PSUs, adjustment factor for subsampling of growth PSUs, and an adjustment factor to account for small EAs excluded from the sampling frame (i.e.EAs with fewer than 25 households).

Non-response adjustment:

In general, imputation is used for item non-response (i.e. blanks within the questionnaire), and edit failure (i.e. invalid or inconsistent responses). The eligible households in the sampled dwellings can be divided into two response categories: respondents and non-respondents, and weight adjustment is applied to account for the non-respondent households (e.g. refusal, no contact, etc.). The sampled dwellings with no eligible households, e.g. foreigners only, or no households, (i.e. vacant dwellings), do not contribute to the survey. The non-response adjusted weight is the product of the base weight with the non-response adjustment

factor given above. If the PSU level non-response rate is too high, the non-response adjustment is applied at the VARUNIT level, where two VARUNITs have been created by grouping PSUs within strata. PSU level non-response adjustment is applied only if the corresponding adjustment factor is less than 1,5.

Final survey weights:

The final survey weights are constructed using regression estimation to calibrate to the known population counts at the national level population estimates (which are supplied by the Demography division) crossclassified

by 5-year age groups, gender and race, and provincial population estimates by broad age groups are used for calibration weighting. The 5-year age groups are: 0–4, 5–9, 10–14,…………………. 55–59, 60–64, and 65 and over. The provincial level age groups are: 0–14, 15–34, 35–64, and 65 years and over. The final weights are constructed in such a manner that all persons within a household would have the same weight.