Quarterly Labour Force Survey 2016, Quarter 3 - South Africa

Abstract
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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.

Geographic coverage
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National coverage

Analysis unit
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Individuals

Universe
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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.

Kind of data
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Sample survey data [ssd]

Sampling procedure
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The Quarterly Labour Force Survey (QLFS) uses a master sample frame which has been developed as a general-purpose household survey frame that can be used by all other Stats SA household surveys that have reasonably compatible design requirement as the QLFS. The 2013 master sample is based on information collected during the 2011 population 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 (2007) master sample (which had 3 080 PSUs). The larger master sample of PSUs was selected to improve the precision (smaller CVs) of the QLFS estimates.

The master sample is designed to be representative at 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 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 (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.

There are a number of aspects in which the 2013 version of the master sample differs from the 2007 version. In particular, the number of primary sample units increased. Mining strata were also introduced which serves to improve the efficiency of estimates relating to employment in mining. The number of geo-types was reduced from 4 to 3 while the new master sample allows for the publication of estimates of the labour market at metro level. The master sample was also adjusted Given the change in the provincial distribution of the South African population between 2001 and 2011. There was also an 8% increase in the sample size of the master sample of PSUs to improve the precision of the QLFS estimates. The sample size increased most notable in Gauteng, the Eastern Cape and KwaZulu-Natal. For more details on the differences between the two master samples please consult the section 8 (technical notes) of the QLFS 2015 Q3 release document (P0211).

From the master sample frame, the QLFS takes draws exmploying 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. The primary stratification occurred at provincial, metro/non-metro, mining and geography type while the secondary strata were created within the primary strata based on the demographic and socio-economic characteristics of the population.

For each quarter of the QLFS, a ¼ of the sampled dwellings is 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 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).

Mode of data collection
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Face-to-face [f2f]

Data appraisal
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Industry Coding in the QLFS

The QLFS variable Q43INDUSTRY shows the industry in which household members are employed. The data is collected from Questions 4.3.a and 4.3.b, which were write-in questions. The responses to these two questions were used to determine the type of industry. Industry was coded to three digits on the basis of Industrial Classification of all Economic Activities (SIC) standard industry codes. However, the SIC codes used in the QLFS are not the latest (version 7 2012) but an older standard industry code list, v5. This code list is available at http://www.statssa.gov.za/classifications/codelists/sic.zip.

摘要
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南非统计局（Stats SA）实施的季度劳动力调查（QLFS）是一项基于家庭的抽样调查。该调查搜集了年龄在15岁及以上的南非居住者的劳动力市场活动数据。
地理覆盖范围
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全国覆盖
分析单位
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个人
总体
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QLFS样本涵盖了南非的非机构人口，唯一例外的是工人宿舍中的个体。居住在机构内私人住宅单位的人也被纳入统计。例如，在学校园区内，校长住宅和教师宿舍因其为私人住宅而被计算在内。然而，居住在学校园区宿舍的学生则不包括在内。
数据类型
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抽样调查数据 [ssd]
抽样程序
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季度劳动力调查（QLFS）采用一个主样本框架，该框架作为一个通用的家庭调查框架开发，可用于所有其他与QLFS设计要求合理兼容的Stats SA家庭调查。2013年的主样本基于南非统计局在2011年进行的全国人口普查收集的信息。为了准备2011年的人口普查，全国被划分为103,576个统计区域（EA）。普查统计区域及其辅助信息被用作主样本中一级抽样单位（PSU）的框架单元或构建块，因为它们覆盖了整个国家，并拥有对分层和形成PSU至关重要的其他信息。主样本中有3,324个一级抽样单位（PSU），预计样本量约为33,000个住宅单位（DU）。与之前的（2007年）主样本（拥有3,080个PSU）相比，当前主样本中PSU的数量反映了主样本规模8.0%的增长。较大的主样本PSU被选中，以提高QLFS估计的精确度（较小的CVs）。
主样本旨在在省级层面以及省内的都市/非都市层面具有代表性。在都市内，样本进一步按地理类型分配。三种地理类型是：城市、部落和农场。这意味着，例如，在都市区域内，样本代表了该都市内可能存在的不同地理类型。它被平均分为四个子组或面板，称为轮换组。轮换组的设计方式使得每个组都具有与整个样本相同的分布模式。它们被编号为1（1）至4，这些编号也对应于样本将轮换的特定组的一年中的季度。
2013年主样本的2013年版与2007年版在多个方面存在差异。特别是，一级样本单位数量增加。还引入了采矿层，这有助于提高与采矿就业相关的估计效率。地理类型从4个减少到3个，而新的主样本允许发布都市层面的劳动力市场估计。鉴于2001年至2011年南非人口在省级分布上的变化，主样本也进行了调整。主样本PSU的样本量也增加了8%，以改善QLFS估计的精确度。样本量在豪登省、东开普省和夸祖鲁-纳塔尔省显著增加。有关两个主样本之间差异的更多详细信息，请参阅QLFS 2015 Q3发布文档（P0211）的第8节（技术说明）。
从主样本框架中，QLFS采用分层两阶段设计，第一阶段采用与规模成比例的概率（PPS）抽样PSU，第二阶段采用住宅单位的系统抽样。一级分层发生在省级、都市/非都市、采矿和地理类型，而二级分层基于人口的社会人口和经济社会特征在一级分层内创建。
对于每个QLFS季度，1/4的样本住宅将被轮换出样本。这些住宅将由来自同一PSU或列表中下一个PSU的新住宅所替代。因此，样本住宅预计将在连续四个季度内保持样本状态。应注意的是，抽样单位是住宅，观测单位是家庭。因此，如果一个家庭在样本中居住了两个季度后搬离住宅，新家庭将进入下一个两个季度进行统计。如果没有新家庭搬入样本住宅，该住宅将被归类为空置（或无人居住）。
数据收集方式
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面对面 [f2f]
数据评估
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QLFS中的行业编码
QLFS变量Q43INDUSTRY显示了家庭成员工作的行业。数据来自问题4.3.a和4.3.b，这些问题是开放式问题。这两个问题的回答被用来确定行业类型。行业根据所有经济活动的《工业分类》（SIC）标准行业代码进行了三位数的编码。然而，QLFS中使用的SIC代码并非最新版本（2012年第7版），而是一个较旧的行业标准行业代码列表，v5。此代码列表可在http://www.statssa.gov.za/classifications/codelists/sic.zip上找到。