University of Michigan Releases a Request for Applications to Summer Workshop

Lead Instructors: Lori Reeder & Holly Monti, US Census Bureau
Co-Organizers: Gary Benedetto, U.S. Census Bureau & H. Luke Shaefer, University of Michigan
With support from Lars Vilhuber, Cornell University

The Survey Research Center at the Institute for Social Research at the University of Michigan and the United States Census Bureau invite applications to participate in a four-day workshop, August 8-11, 2016, in Ann Arbor, Michigan. This advanced workshop will introduce participants to the use of the Survey of Income and Program Participation Synthetic Beta (SSB) and provide hands-on applications to prepare them to conduct their own SSB-based research. The SIPP Synthetic Beta (SSB) is a Census Bureau data product that integrates person-level micro-data from a household survey (SIPP survey data) with W-2 earnings and OASDI benefits data. Census has synthesized the data to preserve the underlying covariate relationships between variables while protecting respondent confidentiality. Unlike the original, administrative data, the SSB is publicly available. The Census Bureau offers all SSB users the opportunity to submit their programs for validation on the internal, confidential version of these data. As part of this workshop, participants will learn how to prepare programs for submission to the validation process and how to request the release of research results from Census disclosure officers. This experience will help participants not only begin their SSB research projects but also see them through to successful completion after the seminar has finished. Lori Reeder and Holly Monti of the U.S. Census Bureau will lead the workshop, in collaboration with researchers at the University of Michigan, the U.S. Census Bureau, Cornell University, and other nationally recognized SIPP scholars. The Survey Research Center will pay travel, lodging, and meal costs for a limited number of participants. Aims for this workshop include the following:

  • Familiarize participants with the SIPP Synthetic Beta’s (SSB) data structure and outline the synthesis process.
  • Provide hands-on demonstrations for accessing SSB data via the Synthetic Data Server housed at the VirtualRDC at Cornell University.
  • Provide hands-on demonstrations of analyses of SSB data related to employment, annual earnings, and OASDI program participation.
  • Provide participants with an opportunity to conduct analyses for their own research projects and produce preliminary findings based on the SSB that can be continued when the participant returns to her/his home institution. Provide directions on how to submit programs for validation and disclosure review after seminar has ended.
  • Provide opportunities for participants to discuss the current status of key research and policy issues with nationally recognized experts. Classes will meet for two and one-half hour sessions in a computer classroom each morning and afternoon. Participants will work directly with the SSB data via the VirtualRDC at Cornell University.

Classes will meet for two and one-half hour sessions in a computer classroom each morning and afternoon. Participants will work directly with the SSB data via the VirtualRDC at Cornell University. This workshop will not offer instruction in statistics or formal research methods, but presentations will cover appropriate use of this unique dataset. Participants may want to consider attending, at their own expense, other summer courses offered in Ann Arbor by the Institute for Social Research: and

The intent of the SSB is to enable research focusing on the relationship between lifetime earnings, OASDI, and SSI benefit receipt and SIPP outcome variables such as wealth, education, fertility and marital history. Priority will be given to projects that demonstrate creative and insightful uses of the longitudinal nature of these data and which study the relationship between SSA benefit variables and other variables on the file.

To Apply
Applications will be accepted from faculty, postdoctoral fellows, advanced doctoral students, federal, state and local-level policy and research analysts, researchers at non-profit organizations, and others who would benefit from this workshop. Preference will be given to applicants who meet one of the following criteria:

  • Emerging scholars (Assistant Professors, Postdoctoral Fellows, and Advanced Doctoral Students) working at universities and colleges that do not offer instruction in the use of SIPP.
  • Members of groups historically under-represented in the social sciences. Faculty members from Historically Black Colleges and Universities (HBCU), Tribal Colleges and Universities (TCU) and Hispanic Serving Institutions (HSI) are particularly encouraged to apply.

Applicants should submit their proposal via email to Proposals must be received by 5 PM Eastern Time on Friday, May 27, 2016. Items 1 through 3 of this application should be submitted as a single PDF file that includes the following elements, in the order listed below:

  1. Cover sheet indicating you are applying for the SIPP SSB Workshop, with your name and institutional affiliation with mailing address, email address, and telephone number
  2. Curriculum vita or resume
  3. Brief summary of your current research or analysis activities and how these relate to your proposed SIPP SSB project (about 2 pages)
  4. As a separate pdf document, please submit the Census Bureau Application to use the SSB, including a brief description of the project to be undertaken and list of variables to be used.
    Applications can be found at A codebook for the SSB can be found at .
    Please note that the SSB does not contain all variables released in the public use SIPP but rather contains a subset of SIPP variables linked to administrative data.

Direct Questions to:

The deadline for receipt of applications is 5 PM Eastern Time on May 27, 2016. Selected applicants will be notified no later than Friday, June 10, 2016.

This workshop is part of the NSF-Census Research Network project of the Institute for Social Research at the University of Michigan. It is funded by National Science Foundation Grant No. SES 1131500.

For more information, please see