Estimation of vacancies by NACE and ISCO at disaggregated regional level

Abstract

"At the end of the 1990s a discussion on the need and possibilities to set up quarterly European statistics on unmet labour demand as a counterpart to the unemployment statistics on the supply side of the labour market has started. In most countries business surveys are the only way to find out the total number of vacancies. They need to use comparable methods and definitions to allow country comparisons. In 2005 the European Commission formulated additional and very specific requirements concerning breakdowns by regions (NUTS), sectors (NACE) and occupations (ISCO). With our work we tried to answer the question, if and how it could be possible to estimate data on a very deep disaggregated sectoral, regional and occupational level respectively. We have analyzed the available database with several methods, like Small Area Estimation, Multiple Imputation and regressions. Part of our research was successful; some questions require more research to find satisfying answers and we continue working on these. Data on occupations by NUTS 2, e.g. can not be produced without a considerable increase in the sample size and great effort in developing usable estimation techniques, since NUTS 2 regions in Germany are relatively small. A cost-benefit-analysis does not justify the large amount of financial resources required. Therefore NUTS 1 is the appropriate regional level for vacancy data from our perspective. A publication of occupational data by NUTS 2 is insufficient anyhow for good analyses of mismatch, since a classification by ISCO major or sub major groups is too rough for this. Furthermore such analyses would need to take into account regional specifics on both sides of the labour market. Missing values are a common problem in analyses of business data. Our report has discussed concepts regarding mechanisms that create missing data, as well as the strengths and weaknesses of commonly used approaches. Using only the long questionnaire from 2005, our simulation studies show that multiple imputation for the German job vacancy survey can lead to unbiased results for the missing data and multiple imputation has been used successfully for business data in several other applications. The methodological work on methods of multiple imputation and of split survey designs will be continued to reduce the answering burden for respondents and to fill in missing variables." (Author's abstract, IAB-Doku) ((en))

Cite article

Kettner, A., Drechsler, J., Rebien, M., Schmidt, K., Smerdjieva, M., Stops, M. & Vogler-Ludwig, K. (2007): Estimation of vacancies by NACE and ISCO at disaggregated regional level. (IAB-Bibliothek 310), Nürnberg, 197 p.