A partially corrected estimate of medicaid enrollment and uninsurance: Results from an imputational model developed off linked survey and administrative data

Abstract

To improve the utility of estimates of Medicaid enrollment and uninsurance from the Current Population Survey (CPS) we use linked data from the CPS and the Medicaid Statistical Information System (MSIS) to build a probabilistic imputation model that partially corrects the public use data files for systematic under-reporting of Medicaid. We estimate the probability that a CPS survey case was enrolled in Medicaid, conditional on whether or not in the CPS the individual responded that they had Medicaid. We use the imputed data to develop adjusted estimates of Medicaid enrollment and uninsurance by demographic characteristics. The net Medicaid enrollment total using our imputation model for CY 2006 and 2007 is 41.0, compared to 34.0 million using the standard CPS variables. The resulting net adjusted uninsurance estimate is 4.5% below the unadjusted estimate.