Call for Papers
Deadline: May 16, 2022
October 25–27, 2022
Washington Convention Center*, Washington D.C.
Great Expectations: New Directions and Innovations for Sustainable Federal Statistics
The 2022 FCSM Research and Policy Conference provides a forum for experts and practitioners from around the world to discuss and exchange current methodological knowledge and policy insights about topics of current and critical importance to federal agencies.
We seek abstracts that address advances in credible and accurate survey and statistical methodologies from both research and policy perspectives. Submissions may address but are not limited to the following topics of importance to the Federal Statistical System:
- Applied statistics
- Data collection
- Data dissemination
- Data linkage
- Data processing
- Data quality
- Establishment surveys
- Estimation and inference
- Privacy and disclosure control
- Questionnaire design
- Statistical computing
- Survey sampling and weighting
Policy Submissions: Abstracts should discuss a statistical policy topic and discuss the implications or impacts observed thus far and may raise questions or issues without having a definitive answer.
Research Submissions: Abstracts should present research studies and findings related to the topics listed above. Submissions should not simply describe a data collection program or be highly specialized.
Organized Session Submissions: An organized session submission should include 3 or 4 papers, a discussant and a chair. Organized sessions with both research and policy presentations will be given priority when the program is assembled.
Instructions: Submission forms and instructions can be found at https://fcsm2022.org/
- For conference information, or to be included on the mailing list, contact Paul Schroeder at COPAFS at email@example.com
- For questions on abstract submissions or the program, contact the Program Chair, Jessica Graber at firstname.lastname@example.org
*Note: If unsafe to congregate due to COVID-19 the conference may be switched from in-person to virtual.