The effect of the state children’s health insurance program on health insurance coverage

Abstract

This paper presents the first national estimates of the effects of the SCHIP expansions on insurance coverage. Using CPS data on insurance coverage during the years 1996-2000, we estimate instrumental variables regressions of insurance coverage. Our regression results imply that 9% of children meeting income eligibility standards for SCHIP gained public insurance. While low, our estimates indicate that states were more successful in enrolling children in SCHIP than they were with prior Medicaid expansions that were focused on children just above the poverty line. Crowd-out of private health insurance was estimated to be nearly 50%, which is in line with estimates for the Medicaid expansions of the early 1990s. In addition, state anti-crowd-out provisions in the form of waiting periods were found to significantly affect both take-up and crowd-out.

Public-Private Substitution Among Medicaid Adults: Evidence from Ohio

“…In a key early econometric study of crowd-out for child coverage, Cutler and Gruber (1996) found that up to 50% of the increase in Medicaid coverage for children in the early 1990s was offset by a decrease in private coverage. More recent studies have produced similar estimates while others found lower crowd-out estimates for the same Medicaid expansions and the later CHIP program (Gruber & Simon, 2008;Thorpe & Florence, 1998-1999LoSasso & Buchmueller, 2004;Shore-Sheppard 2008;Ham & Shore-Sheppard, 2005). Due to methodological limitations, most studies estimate a single substitution value nationwide.…”

“…In the first, econometric-based approaches are used to estimate the impact of Medicaid expansion on private insurance take-up (usually referred to as "crowd-out" studies). These studies use variations of Cutler and Gruber's original identification technique (Gruber & Simon, 2008;LoSasso & Buchmueller, 2004;Seiber & Florence, 2010;Shore-Sheppard, 2008). This econometric approach examines eligibility variation across states to produce national estimates for the magnitude of substitution, often through instrumental variable models designed to address the possible endogeneity of public insurance eligibility.…”

“…First, IV models can produce estimates with large standard errors that are sensitive to assumptions in the model. In a large econometric evaluation of the CHIP expansions, the crowd-out estimate ranged from 10% to 50% of all children, depending on the treatment of the private insurance variable (LoSasso & Buchmueller, 2004). Second, estimation via IV models also relies on variation across states, limiting the ability to derive state specific crowd-out estimates.…”

State Variability in Children’s Medicaid/CHIP Crowd-Out Estimates

“…Subsequent analysis has suggested varying estimates ranging from values similar to Cutler and Gruber to estimates that there is near zero crowd-out (Gruber & Simon, 2008). These studies primarily relied on three methods: an econometric instrumental variable (IV) approach (Cutler & Gruber, 1996;Lo Sasso & Buchmueller, 2004), comparing children who gained access to expanded Medicaid/CHIP programs to control groups that did not (Blumberg, Dubay, & Norton, 2000;Yazici & Kaestner, 2000), and estimates of substitution using surveys (Sommers, Zuckerman, Dubay, & Kenney, 2007), all of which have weaknesses (Seiber & Sahr, 2011).…”

How Do Public Health Expansions Vary by Income Strata? Evidence from Illinois' All Kids Program

“…Using a simulated eligibility design, Lo Sasso and Buchmueller (2004) found a marginal take-up rate for public insurance of 8.1%, and crowd-out rates between 18% and 50% depending on the exact specification used. A similar paper by Gruber and Simon (2008) largely confirmed these results, estimating a low take-up rate of 5.5% for public insurance accompanied by a direct crowd-out rate of 30%.…”