Improving Small-Area Estimates of Disability: A Model-Based Approach to Combining the American Community Survey with the Survey of Income and Program Participation

• Activity Number: 634
• Type: Topic Contributed
• Date/Time: Thursday, August 13, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Survey Research Methods Section
• Author(s): Jerry Maples* and Amy Steinweg
• Companies: U.S. Census Bureau and U.S. Census Bureau
• Keywords: Small Area ; Disability ; ACS ; SIPP

Abstract

The Survey of Income and Program Participation (SIPP) is designed to make national level estimates of changes in income, eligibility for and participation in transfer programs, household and family composition, labor force behavior, and other associated events. Used cross-sectionally, the SIPP is the source for commonly accepted estimates of disability prevalence, having been cited in the findings clause of the Americans with Disability Act. Because of its sample size, SIPP is not designed to produce highly reliable estimates for individual states nor any estimates for individual counties. The American Community Survey (ACS) is a large sample survey which is designed to support estimates of characteristics at the state and county level, however, the questions about disability in the ACS are not as comprehensive and detailed as in SIPP. We propose combining the information from the SIPP and ACS surveys to improve estimates of disability (as defined by SIPP) by a generalized regression predictor. Both the Bayesian and Frequentist approaches will be explored.