A Framework for Investigating Micro Data Quality, with Application to South African Labour Market Household Surveys
AbstractIn this paper the Total Survey Error (TSE) paradigm is combined with detailed data quality indicators to develop a framework for investigating micro data quality. The TSE framework is widely used in the survey methodology literature to identify different components of error that arise in the survey process. Consequently, it provides a very useful typology for researchers to understand which data quality issues are relevant in applied work based on these surveys. In order to demonstrate how the framework sheds light on micro data quality, two labour market household surveys conducted by Statistics South Africa are reviewed, spanning a time-frame from 1995-2007. It is argued that efforts to improve data quality should involve a virtuous interaction between producers and consumers of micro data and should be considered an evolving process. For producers of data, the preparation and publication of detailed data quality frameworks is recommended, and two examples of these frameworks are reviewed. For consumers of data, judicious analyses of the univariate, bivariate and multivariate relationships in public-use versions of the datasets can help shed light on different components of survey error, and should be communicated back to survey organisations. Ultimately, improving data quality is about being more explicit about the limitations of data production at each stage of the process, which does not stop at initial public release.
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Bibliographic InfoPaper provided by Southern Africa Labour and Development Research Unit, University of Cape Town in its series SALDRU Working Papers with number 90.
Date of creation: 2012
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Data Quality Evaluation and Assessment; Total Survey Error;
Find related papers by JEL classification:
- C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
- C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-11-11 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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