SCHIP's impact on dependent coverage in the small-group health insurance market.

As part of the State Children's Health Insurance Program's (SCHIP) enabling legislation, states are required to implement strategies to prevent families from substituting publicly funded SCHIP coverage for an existing private policy. Beyond broad estimates of this problem's magnitude, states have limited information on how to focus their efforts across insurance markets. This paper examines the role of SCHIP on children's coverage in the small-group health insurance market and tests whether SCHIP take-up and crowd-out differ for children with parents working at small firms and large firms. A key concern surrounding SCHIP and other plans to cover the uninsured is the degree to which public insurance substitutes, or crowds-out, private insurance. An extensive literature examines the impact on private coverage of SCHIP and previous public eligibility expansions. Total crowd-out estimates vary. For the Medicaid expansions in the early 1990s, Cutler and Gruber (1996) found that up to 50 percent of the increase in public coverage was offset by a decrease in private coverage. Subsequent studies for the same expansions with different data and varying methodologies found lower crowd-out rates, and, in a few cases, no crowd-out (Dubay and Kenney 1996; Thorpe and Florence 1998; Ham and Shore-Sheppard 2005; Shore-Sheppard 2005;). Studies examining the more recent SCHIP have produced crowd-out rates approaching the 50 percent mark found by Cutler and Gruber (LoSasso and Buchmueller 2004; Hudson, Selden, and Banthin 2005;). A detailed overview of the crowd-out literature can be found in Gruber and Simon (2008). Few authors have examined how crowd-out varies across subpopulations and state-level regulations. Since SCHIP extends public eligibility to higher income children who are covered more often by private insurance, several studies estimate crowd-out at different levels of income. These studies find little to no crowd-out for households in poverty, but crowd-out increases to 50 percent for households at 150 and 185 percent of the federal poverty level (Dubay and Kenney 1997; Card and Shore-Sheppard 2004;). In addition to these poverty level effects, LoSasso and Buchmueller (2004) incorporated other state policies into their models and found waiting periods imposed before enrollment also reduced the crowd-out effect. No previous study examines whether crowd-out might differ in the small group market or for small businesses. Although many cut-points are used in the academic literature, the GAO defines the small-group market as firms with up to 50 employees (GAO 2009), and the U.S. Small Business Administration (SBA) defines small businesses as firms with up to 500 employees. In 1995, before the SCHIP expansions, one-fifth of the children in households with parents working at small businesses (fewer than 500 employees) lacked health insurance, compared with only 4 percent of children with both parents working at large firms (Seiber and Florence 2008). However, it is unclear whether small businesses and the small-group market would experience more or less crowd-out than the large-group market. Since children with parents at large firms are more likely to be insured, crowd-out could be higher at large firms. However, access to a group plan with employer premium contributions could make public insurance less appealing for children with parents working at large firms. This study will be the first to examine these questions of crowd-out in the small-group market. This study uses the 1996–2007 March Supplements to the Current Population Survey (CPS) to examine the impact of SCHIP in the small-group market. We use a two-stage least squares instrumental variables estimator (2SLS) to estimate the impact of Medicaid and SCHIP eligibility on the children's insurance outcomes. We estimate separate crowd-out estimates for large and small firms and test the sensitivity of the estimates against firm size definitions. Finally, we compare the crowd-out observed in the 2SLS estimates in the small- and large-group market.