Looking Back On Three Years Of Using The Synthetic Lbd Beta
Distributions of business data are typically much more skewed than those for household or individual data and public knowledge of the underlying units is greater. As a results, national statistical offices (NSOs) rarely release establishment or firm-level business microdata due to the risk to respondent confidentiality. One potential approach for overcoming these risks is to release synthetic data where the establishment data are simulated from statistical models designed to mimic the distributions of the real underlying microdata. The US Census Bureau’s Center for Economic Studies in collaboration with Duke University, the National Institute of Statistical Sciences, and Cornell University made available a synthetic public use file for the Longitudinal Business Database (LBD) comprising more than 20 million records for all business establishment with paid employees dating back to 1976. The resulting product, dubbed the SynLBD, was released in 2010 and is the first-ever comprehensive business microdata set publicly released in the United States including data on establishments employment and payroll, birth and death years, and industrial classification. This pa- per documents the scope of projects that have requested and used the SynLBD.
|Date of creation:||Feb 2014|
|Date of revision:|
|Contact details of provider:|| Postal: 4600 Silver Hill Road, Washington, DC 20233|
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- Jorg Drechsler & Lars Vilhuber, 2014. "A First Step Towards A German Synlbd: Constructing A German Longitudinal Business Database," Working Papers 14-13, Center for Economic Studies, U.S. Census Bureau.
- Ron S. Jarmin & Thomas A. Louis & Javier Miranda, 2014. "Expanding The Role Of Synthetic Data At The U.S. Census Bureau," Working Papers 14-10, Center for Economic Studies, U.S. Census Bureau.
- Ron S Jarmin & Javier Miranda, 2002. "The Longitudinal Business Database," Working Papers 02-17, Center for Economic Studies, U.S. Census Bureau.
- John M. Abowd & Kaj Gittings & Kevin L. McKinney & Bryce E. Stephens & Lars Vilhuber & Simon Woodcock, 2012. "Dynamically Consistent Noise Infusion and Partially Synthetic Data as Confidentiality Protection Measures for Related Time Series," Working Papers 12-13, Center for Economic Studies, U.S. Census Bureau.
- Lucia Foster & Ron Jarmin & Lynn Riggs, 2009. "Resolving the Tension Between Access and Confidentiality: Past Experience and Future Plans at the U.S. Census Bureau," Working Papers 09-33, Center for Economic Studies, U.S. Census Bureau.
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