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From this page you can view our recent publications, listed below with the most recent at the top of the list.

You may also search publications using the filter options on the left side of the page to narrow down the listing by topic, type of publication, or state. Alternatively, you can use the search box below to conduct a keyword search.

Publication Year: 2011

The Census Bureau’s Small Area Health Insurance Estimates (SAHIE) program produces model-based estimates of health insurance coverage for all counties and states. Estimates for calendar years 2008 and 2009 were released in October 2011.  Currently, the SAHIE program is the only source of health insurance coverage estimates for all counties in the United States. This brief highlights what is new for this release, provides an overview of how the SAHIE estimates are developed, and compares the SAHIE model-based methodology to the American Community Survey.

Publication Year: 2011

SHADAC prepared this working paper for the Census Bureau to describe a revised data imputation technique for health insurance estimates from the Current Population Survey's Annual Social and Economic Supplement (CPS ASEC). 

Publication Year: 2007

Research Objective: To determine whether the imputation procedure used to replace missing data by the U.S. Census Bureau produces bias in the estimates of health insurance coverage in the Current Population Survey's (CPS) Annual Social and Economic Supplement (ASEC).

Publication Year: 2011

This State Data Spotlight describes how the Office of Financial Management (OFM) in Washington State developed an estimation and projection model that can be used to predict county-level population estimates for 2010 through 2020.

Publication Year: 2011

In this brief, SHARE grantee Mike O'Grady (NORC, University of Chicago) details the process of linking data sets, gives an overview of data linkage projects that have been undertaken to date, and considers the potential linkages that would be both relevant and useful in a post-reform environment.  Dr. O'Grady points to several key areas where linked data sets could be beneficial going forward, including the design and implementation of the ACA's health benefit exchanges, comprehension of the complex intersection of Medicare and Medicaid, and reform of the Medicare payment system.