“Total Variability Measures for Selected Quarterly Workforce Indicators and LEHD Origin Destination Employment Statistics in OnTheMap”, Kevin McKinney (U.S. Census Bureau), Lars Vilhuber (Cornell University and U.S. Census Bureau), John Abowd (Cornell University and U.S. Census Bureau), Andrew Green (Cornell University)
We report results from the first comprehensive total quality evaluation of three major indicators in the U.S. Census Bureau’s Longitudinal Employer-Household Dynamics (LEHD) Program Quarterly Workforce Indicators (QWI): beginning-of-quarter employment, full-quarter employment, and average monthly earnings of full-quarter employees. Beginning-of-quarter employment is also the main tabulation variable in the LEHD Origin-Destination Employment Statistics workplace reports as displayed in OnTheMap (OTM). The evaluation is conducted using the multiple threads generated by the edit and imputation models used in the LEHD Infrastructure File System. These threads conform to the Rubin (1987) multiple imputation model. Each implicate is the output of formal probability models that address coverage, edit and imputation errors. Design-based sampling variability and finite population corrections are also included in the evaluation. We derive special formulas for the Rubin total variability and its components that are consistent with the disclosure avoidance system used for QWI and LODES/OTM workplace reports. These formulas allow us to publish the complete set of detailed total quality measures for QWI and LODES. The analysis reveals that the three publication variables under study are estimated very accurately for tabulations involving at least 10 jobs. Tabulations involving three to nine jobs have acceptable quality. Tabulations involving one or two jobs, which are generally suppressed in the QWI, have substantial total variability but their publication in LODES allows the formation of larger custom aggregations, which will in general have the accuracy estimated for tabulations in the QWI of similar magnitude.
“Improving Access and Data Security to Confidential Labor Market Data”, Warren Brown (Cornell University), Stephanie Jacobs (Cornell University), David Schiller (German Institute for Employment Research), Jörg Heining (German Institute for Employment Research)
Abstract: The Cornell Institute for Social and Economic Research (CISER), Cornell University and the Institute for Employment Research (IAB), German Federal Employment Agency are collaborating to expand use of IAB’s confidential Sample of Integrated Labour Market Biographies (SIAB). DDI 2.5 is used to enable researchers to discover the files by means of variable level searching in a repository of metadata on U.S. and German labor market related data files. The repository is the Comprehensive Extensible Data Documentation and Access Repository (CED2AR) being developed by researchers at Cornell University with funding from the U.S. National Science Foundation. CED2AR provides researchers access to machine-readable codebooks with variable characteristics thus enabling researchers to develop detailed proposals for access to these data that are submitted to IAB. Researchers with approved projects are able to access and analyze the data using the Cornell Restricted Access Data Center (CRADC), a remote access virtual data enclave using remote desktop protocol. In the initial testing phase several researchers located in Europe and North America are successfully accessing and analyzing the Scientific Use Files of the SIAB. The project is well on its way to realizing the goal of wider access to researchers while improving secure management of confidential data.
The presentation can be found at http://hdl.handle.net/1813/44707
“Formal Privacy Protection for Data Products Combining Individual and Employer Frames”, Ashwin Machanavajjhala (Duke University), Samuel Haney (Duke University), Matthew Graham (U.S. Census Bureau), Mark Kutzbach (U.S. Census Bureau), Lars Vilhuber (Cornell University and U.S. Census Bureau), John Abowd (Cornell University and U.S. Census Bureau)