Abstract
The National Science Foundation-Census Bureau Research Network (NCRN) was established in 2011 to create interdisciplinary research nodes on methodological questions of interest and significance to the broader research community and to the Federal Statistical System (FSS), particularly to the Census Bureau. The activities to date have covered both fundamental and applied statistical research and have focused at least in part on the training of current and future generations of researchers in skills of relevance to surveys and alternative measurement of economic units, households, and persons. This article focuses on some of the key research findings of the eight nodes, organized into six topics: (1) improving census and survey data-quality and data collection methods; (2) using alternative sources of data; (3) protecting privacy and confidentiality by improving disclosure avoidance; (4) using spatial and spatio-temporal statistical modeling to improve estimates; (5) assessing data cost and data-quality tradeoffs; and (6) combining information from multiple sources. The article concludes with an evaluation of the ability of the FSS to apply the NCRN's research outcomes, suggests some next steps, and discusses the implications of this research-network model for future federal government research initiatives.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 589-609 |
| Number of pages | 21 |
| Journal | Journal of Survey Statistics and Methodology |
| Volume | 7 |
| Issue number | 4 |
| DOIs | |
| State | Published - Dec 1 2019 |
Funding
This article began as a presentation on May 8, 2015, to the The National Academies of Sciences, Engineering, and Medicine Committee on National Statistics by two of the principal investigators of the National Science Foundation-Census Bureau Research Network (NCRN): John Abowd and the late Stephen Fienberg (Carnegie Mellon University). The authors acknowledge the contributions of the principal and co-principal investigators of the NCRN who are not co-authors of the article (William Block, William Eddy, Alan Karr, Charles Manski, Nicholas Nagle, and Rebecca Nugent), the comments of Patrick Cantwell, Constance Citro, Adam Eck, Brian Harris-Kojetin, Eloise Parker, the editor (Ting Yan), and two anonymous referees. They also thank Handan Xu, who organized the references. We note with sorrow the deaths of Stephen Fienberg and Allan McCutcheon, two of the original NCRN principal investigators. The conclusions reached in this article are not the responsibility of the National Science Foundation (NSF), the Census Bureau, or any of the institutions to which the authors belong. The NCRN was supported by NSF grants to the participating institutions: 1129475 to Northwestern University; 1130706 to Carnegie Mellon University; 1131500 to University of Michigan-Ann Arbor; 1131848 to Cornell University; 1131897 to Duke University and National Institute of Statistical Sciences (NISS); 1132008 to University of Colorado-Boulder; 1132015 to University of Nebraska-Lincoln; 1132031 to University of Missouri; and 1507241 for the Coordinating Office (Cornell, Duke, and NISS). The principal investigators also wish to acknowledge Cheryl Eavey’s sterling grant administration on behalf of the NSF, and Daniel Weinberg and Nancy Bates (the latter assisted by Krista Park and Renee Ellis) in their role as Census Bureau liaison for the NCRN program.
Keywords
- Administrative records
- Data collection
- Disclosure avoidance
- Statistical modeling
- Survey methods
- Survey statistics
ASJC Scopus subject areas
- Statistics and Probability
- Social Sciences (miscellaneous)
- Statistics, Probability and Uncertainty
- Applied Mathematics