DDI_ZAF_1994-2007_OLCS_v01_M DataFirst 2013-06-12 NADA Version 02 (August 2013). Edited version based on Version 1.1 DDI (ddi-zaf-datafirst-olcs-1994-2007-v1.1) that was done by DataFirst. OHS-LFS Consistent Series Weights 1994-2007 OLCS 1994-2007 ZAF_1994-2007_OLCS_v01_M Branson, Nicola NADA Mellon Foundation DataFirst Helpdesk World Bank Microdata Library Other Household Survey [hh/oth] Version 0411: Edited, anonymised dataset for public distribution Version 0410 was provided to DataFirst by Nicola Branson in 2010. Version 0411 is this dataset, with cross-entropy weights for OHS 1996 included. These were not in the original set of weights created by Nicola Branson, but have been created subsequently by DataFirst. Version 0410 was provided to DataFirst by Nicola Branson in 2010. Version 0411 is this dataset, with cross-entropy weights for OHS 1996 included. These were not in the original set of weights created by Nicola Branson, but have been created subsequently by DataFirst. One focus of post apartheid research in South Africa is change. Questions include the progress of South Africa in the economic, social and political arena. National datasets such as the October Household Surveys (OHS) and Labour Force Surveys (LFS) provide a rich source of information on both economic and social variables in a cross sectional framework. These datasets are repeated annually or biannually and therefore have the potential to highlight changes over time. Yet to treat the cross sectional national data as a time series requires that, when stacked side by side, the data produce realistic trends. Since these data were not designed to be used as a time series, there are changes in sample design, the interview process and shifts in the sampling frame which can cause unrealistic changes in aggregates over a short period of time. This raises concerns about the validity of using these datasets as a time series to examine change. The aggregate trends calculated from the OHS and LFS show the data to be both temporally and internally inconsistent. Examining the weights given in the datasets, in addition to the public documentation, it is clear that the Statistics South Africa (StatsSA) household and person weights are not simple design weights i.e. inverse inclusion probability weights. StatsSA poststratifies the person design weight to external population totals. Since the data are cross sectional the intention of the post-stratification adjustment is to produce best estimates of the population given the information available at the time and temporal consistency is not considered. This creates problems when the data is used as a time series. A project was thus undertaken by Nicola Branson at the University of Cape Town, with a scholarship from DataFirst as part of DataFirst's Data Quality Project, funded by the Mellon Foundation. to design a new set of person and household weights for the OHS 1994-1999 and the LFS 2000-2007. These weights are generated using an entropy estimation technique. The new weights result in consistent demographic and geographic trends and greater consistency between person and household level analysis. This dataset consists of the cross-entrophy weights and the research resources used to construct them, including the syntax files, as well as background documentation on the project, and other research output. These should be used with the OHS and LFS data available from the data portal. South Africa National coverage Sample survey data [ssd] Face-to-face [f2f] The purpose of survey weights is to inflate the sample to represent the entire population. These weights therefore play an important role in creating consistent aggregates over time. Statistics South Africa's (StatsSA) household and person weights are not simple design weights i.e. inverse inclusion probability weights. The weights presented in the StatsSA National Household surveys are the design weight post-stratified to external population totals. Since the data are cross sectional the intention of the post-stratification adjustment is to produce best estimates of the population given the information available at the time and temporal consistency is not considered. These cross entropy weights have been provided to render the OHS and LFS series consistent over time. The original cross entropy weights created by Nicola Branson did not include weights for OHS 1996. These have now been created by DataFirst, using a later version of the OHS 1996 data provided by Statistics South Africa. Manager, DataFirst Use of the dataset must be acknowledged using a citation which would include: - the Identification of the Primary Investigator - the title of the survey (including country, acronym and year of implementation) - the survey reference number - the source and date of download Example: Nicola Branson, University of Cape Town, South Africa. OHS-LFS Consistent Series weights 1994-2007. Ref. ZAF_1994-2007_OLCS_v01_M. Dataset downloaded from http://www.datafirst.uct.ac.za/catalogue3/index.php/catalog/402 on [date]. Public use files, accessible to all The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.