scholarly journals FRED-SD: A real-time database for state-level data with forecasting applications

Author(s):  
Kathryn O. Bokun ◽  
Laura E. Jackson ◽  
Kevin L. Kliesen ◽  
Michael T. Owyang
2020 ◽  
Author(s):  
Kevin L. Kliesen ◽  
Michael T. Owyang ◽  
Laura E. Jackson ◽  
Kathryn O. Bokun

2013 ◽  
Vol 29 (1) ◽  
pp. 99-124 ◽  
Author(s):  
Tom Krenzke ◽  
Jane F. Gentleman ◽  
Jianzhu Li ◽  
Chris Moriarity

Abstract This article focuses on methods for enhancing access to survey data produced by government agencies. In particular, the National Center for Health Statistics (NCHS) is developing methods that could be used in an interactive, integrated, real-time online analytic system (OAS) to facilitate analysis by the public of both restricted and public use survey data. Data from NCHS’ National Health Interview Survey (NHIS) are being used to investigate, develop, and evaluate such methods. We assume the existence of public use microdata files, as is the case for the NHIS, so disclosure avoidance methods for such an OAS must account for that critical constraint. Of special interest is the analysis of state-level data because health care is largely administered at the state level in the U.S., and state identifiers are not on the NHIS public use files. This article describes our investigations of various possible choices of methods for statistical disclosure control and the challenges of providing such protection in a real-time OAS that uses restricted data. Full details about the specific disclosure control methods used by a working OAS could never be publicly released for confidentiality reasons. NCHS is still evaluating whether to implement an OAS that uses NHIS restricted data, and this article provides a snapshot of a research and developmental project in progress.


Author(s):  
Michael S. Danielson

The first empirical task is to identify the characteristics of municipalities which US-based migrants have come together to support financially. Using a nationwide, municipal-level data set compiled by the author, the chapter estimates several multivariate statistical models to compare municipalities that did not benefit from the 3x1 Program for Migrants with those that did, and seeks to explain variation in the number and value of 3x1 projects. The analysis shows that migrants are more likely to contribute where migrant civil society has become more deeply institutionalized at the state level and in places with longer histories as migrant-sending places. Furthermore, the results suggest that political factors are at play, as projects have disproportionately benefited states and municipalities where the PAN had a stronger presence, with fewer occurring elsewhere.


1997 ◽  
Vol 26 (2) ◽  
pp. 462-473 ◽  
Author(s):  
Binto George ◽  
Jayant Haritsa

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