{"doc_desc":{"title":"zaf-statssa-ies-2022-2023-v1.1","producers":[{"name":"DataFirst","abbr":"","affiliation":"University of Cape Town","role":"Metadata Producer"}],"prod_date":"2026-04-28","version_statement":{"version":"Version 4"}},"study_desc":{"title_statement":{"idno":"zaf-statssa-ies-2022-2023-v1.1","title":"Income and Expenditure Survey 2022-2023","alternate_title":"IES 2022-2023"},"authoring_entity":[{"name":"Statistics South Africa","affiliation":"Government of South Africa"}],"series_statement":{"series_name":"Income and Expenditure Survey"},"version_statement":{"version":"Version 1.1: Edited, anonymised dataset for licensed distribution","version_date":"2026","version_notes":"In the original IES 2022-2023 data (Version 1) the household identifier (UQNO) variable was unique as a string but non-unique when converted to a numeric variable (when using the Stata 'destring' command). In version 1.1 this variable has been converted to numeric while preserving the uniqueness of the identifier. Other variables that should be numeric were strings, and these have also been converted to numeric variables. Version 1.1 also has variable labels added where these were missing. A document is provided by DataFirst with more detail on the changes."},"study_info":{"topics":[{"topic":"Income","vocab":"","uri":""},{"topic":"Expenditure","vocab":"","uri":""},{"topic":"Consumption","vocab":"","uri":""}],"abstract":"The Income and Expenditure Survey (IES) is a household\u2011based survey that collects detailed data on acquisitions, consumption, spending, and income among South African households. Alongside the Living Conditions Survey (LCS), it forms part of Statistics South Africa\u2019s household survey programme, which is essential for updating and reweighting the Consumer Price Index (CPI) to reflect evolving consumption patterns. These surveys also provide the most reliable data for assessing poverty and inequality. Previously, these two surveys were conducted on a rotating basis every 3-5 years, but due to funding limitations, Stats SA has not been able to conduct a new survey since the LCS 2014-2015.\n\nThe objectives of the IES are to: establish household income and expenditure profiles; identify and reweight the Consumer Price Index (CPI) basket of goods and services based on household consumption patterns; provide inputs for developing and maintaining the household component of the National Accounts; update the country\u2019s money\u2011metric, subjective, and multidimensional poverty profiles; revise inequality estimates; contribute to the rebasing of national poverty lines; and generate food security statistics. Going forward, the survey is planned to be fully integrated into the upcoming Continuous Population Survey (CPS) programme, along with the LCS and other Continuous Data Collection (CDC) surveys such as the General Household Survey (GHS) and Domestic Tourism Survey (DTS).","coll_dates":[{"start":"2022-11","end":"2023-11","cycle":"Round 6"}],"nation":[{"name":"South Africa","abbreviation":"zaf"}],"geog_coverage":"The survey had national coverage","geog_unit":"Lowest level of geographic aggregation in the data is province.","analysis_unit":"The units of analysis in the survey are households and individuals","universe":"The sample for the survey included all dwelling types (domestic households, holiday homes, and all households in workers' residences, such as mining hostels and dormitories for workers). It excluded institutions such as hospitals, prisons, old-age homes, student hostels, and dormitories for scholars. Boarding houses, hotels, lodges, and guesthouses were also excluded from the sample.","data_kind":"Sample survey data [ssd]","notes":"The survey measures the detailed income and expenditure of households in South Africa"},"method":{"data_collection":{"time_method":"Cross-section [cross section]","data_collectors":[{"name":"Statistics South Africa","abbr":"StatsSA","role":"","affiliation":"Government of South Africa"}],"sampling_procedure":"A total of 3,324 Master Sample (MS) Primary Sampling Units (PSUs) were selected for the creation of an up-to-date GIF to be used in the selection of a systematic sample of dwelling units (DUs) for the survey. However, during the sampling process, it was realised that six (6) of the PSUs could not provide the sample due to a PSU being partly or completely demolished and the PSU count being shrunk at the time of unpacking as compared to the Census 2011 count. Consequently, the resulting sample drawn consisted of 31,042 dwelling units from the 3,318 PSUs.","coll_mode":["Face-to-face computer-assisted interviews [CAPI]"],"research_instrument":"The IES 2022-2023 employed three instruments to gather household information: a household questionnaire, two weekly diaries, and the Classification of Individual Consumption According to Purpose (COICOP) codebook. Each instrument served a distinct function, collectively ensuring the collection of comprehensive data necessary for producing reliable income and expenditure estimates.","sources":[{"name":"","origin":"","characteristics":""}],"coll_situation":"The IES 2022-2023 employed a mixed-methodology combining diary and recall approaches. Respondents were asked to record their daily acquisitions of non-durable, semi-durable, and durable goods, as well as services, in weekly diaries over two weeks. In addition, they were required to recall acquisitions of semi-durable and durable goods, along with selected services, for the 12 months preceding the survey month. Data collection was conducted primarily through Computer-Assisted Personal Interviews (CAPI). Where CAPI was not feasible, Computer-Assisted Telephone Interviews (CATI) were implemented as a supplementary mode of data collection.\n\nThe COICOP questions were asked of all income contributing persons in a household (see Section 26 of the IES 2022-2023 questionnaire). Thus, in the Total and Person Income data files, there can be more than one observation for COICOP data per household. Furthermore, the unit of observation in the Total data file is not the household, it is the expenditutre\/income unit.\n\nThe estimates\u00a0produced in the statistical release were based on an earlier version of the data which used rental yields to calculate owners' equivalent rent for housing and utilities expenditure\u00a0division. As part of the improvement related to the rebasing of the poverty lines, Stats SA adopted the use of regression method to calculate owners' equivalent rent. As a result, the income and expenditure estimates\u00a0contained in\u00a0the statistical release will not be the same as those produced when using this dataset. The estimates in the poverty trends report were obtained using the updated regression method, enabling users to replicate those results."}},"data_access":{"dataset_use":{"contact":[{"name":"DataFirst","affiliation":"University of Cape Town","email":"support@data1st.org","uri":"http:\/\/support.data1st.org"}],"cit_req":"Statistics South Africa. Income and Expenditure Survey 2022-2023 [dataset]. Version 1.1. Pretoria: Statistics South Africa [producer], 2025. Cape Town: DataFirst [distributor], 2026. DOI: https:\/\/doi.org\/10.25828\/z52z-re15","deposit_req":"Users of the data must send DataFirst a copy of or link to any publication based on the data.","conditions":"Creative Commons 4.0 CC-BY Attribution License."}}},"schematype":"survey"}