Improving Small-Area Estimates of Disability: Combining the American Community Survey with the Survey of Income and Program Participation

• Activity Number: 39
• Type: Contributed
• Date/Time: Sunday, August 4, 2013 : 2:00 PM to 3:50 PM
• Sponsor: Survey Research Methods Section
• Author(s): Jerry Maples*+ and Matthew Brault
• Companies: US Census Bureau and US Census Bureau
• Keywords: disability statistics ; small area estimation ; model-assisted ; American Community survey

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 estimates for individual states. 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 produce state and county level estimates of disability (as defined by SIPP). Two approaches are compared: a model-assisted regression projection method and a bivariate Fay-Harriot area level model.