6/30/09
THE EFFECTS OF SCHIP EXPANSIONS
ON FAMILY INSURANCE AND OUT OF
POCKET MEDICAL COSTS:
NEW RESULTS FROM THE SIPP
H. LUKE SHAEFER*
COLLEEN M. GROGAN
HAROLD A. POLLACK
*CORRESPONDING AUTHOR
UNIVERSITY OF MICHIGAN
SCHOOL OF SOCIAL WORK
lshaefer@umich.edu
Project supported with a grant from the
National Poverty Center at the University of
Michigan with funds provided by the U.S.
Census Bureau, Housing and Household
Economics Statistics Division.
Conclusions are solely those of the authors.
We thank Matt Rutledge, Melissa Kearney and
Phil Cook for thoughtful comments.
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6/30/09
DRAMATIC INCREASE IN PUBLIC
INSURANCE FOR CHILDREN
  From 18 million in 1987 to 30 million in 2007
  Expanded most significantly under the creation of
the State Children’s Health Insurance Program
(SCHIP) in 1997
  Started
for uninsured children in families earning less
than 200% of poverty, but has expanded up to 350% of
poverty in some states
SCHIP REAUTHORIZATION DEBATE:
KEY ISSUE
  Crowd-Out: Possibility that SCHIP expansions
have substantially displaced private coverage
  Disagreement: Extent of crowd-out
  0 to 177% (Davidson et al., 2004)
  0 to 59% (Gruber and Simon, 2007)
  Consensus: Crowd-out represents a policy problem
  34 states have adopted waiting periods to limit crowd-out
  Suggests that crowd-out represents a total cost to society
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6/30/09
RESEACH QUESTIONS
  We know little about the implications of crowd-out
for affected families

Crowd-out point estimates “distract policymakers from the
larger and more important challenge of weighing various
program benefits against program costs” (Hudson et al., 2005,
p.233).
  What are the characteristics of families who
crowd-out?
  What is the impact of crowd-out on:
  Health
insurance premiums?
  Out-of-pocket medical expenditures?
WHO CROWDS-OUT?
WHAT ARE THE EFFECTS?
  Theory suggests crowd-out will occur when public
insurance outweighs the value of private coverage
  We predict child health status should play an
important role in determining who crowds-out
  As an effect of crowd-out, we expect to see effective
cash transfers in the form of:


Reduced out-of-pocket medical expenditures
Reduced health insurance premium payments
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6/30/09
PART ONE: ESTIMATING CROWD-OUT
  Pooled sample of 2001 & 2004 SIPP panels
  Continuous
data from start of 2001 to end of 2005
  Restrict to children, 0-18, and their parents
  Replicate standard individual instrumental
variable (IV) approach (Gruber & Simon,
2007)
Use random national sub-sample by age & year
  Apply each state’s eligibility rules to sub-sample
  Calculate proportion eligible for public insurance by agestate-year
  New technique: Bootstrap crowd-out estimates with 200
replications to address non-normality in standard errors.

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6/30/09
STANDARD CROWD-OUT RESULTS
  We find substantial crowd-out during 2001-2005
period
  Might
be expected given eligibility expansions up the
income ladder
  Important: Results sensitive to specification
  Different models
  Different operationalizations of crowd-out
  Relatively large bootstrapped confidence
intervals
  C.I.s
for crowd-out vary by as much as a factor of two
Who is Crowding Out?
21%
10%
11%
12%
19%
16%
19%
19%
10%
10%
15%
20%
20%
30%
25%
Crowd-out = Began year with private ins only;
transitioned to public ins during the year
0%
African American Hispanic Origin
All Children
Poor to Good
Health Status
Crowd-out Grp
Head Single
Female
Priv. all year
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6/30/09
DATA FOR ANALYSES OF MEDICAL COSTS
  The SIPP topical models (TMs) on medical
expenditures

2001 panel, waves 3, 6, 9; 2004 panel, wave 3
  TMs provide parent-reported annual data on these
outcomes
  Construct sample of person-year observations for
children, ages 0-18
  n= 85,840 person-year observations
  Sub-sample descriptives match larger sample
Annual Health Care Costs for Children, 0-18
$1,600
$1,200
$1,592
$1,068
$891
$800
$400
$163
$219
$134
$0
All Children
Crowd-out Grp
Out of Pocket Expenses
Private all yr
Family Premium
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6/30/09
METHOD FOR MULTIVARIATE MODELS
 Employ an instrumental variable approach
 Use two-stage least squares:
  Stage 1: Probit model for probability of crowd-out transition
  Use
Gruber & Simon individual eligibility I.V. as one predictor
  Exclude this in stage 2

Stage 2: Predicted probability for crowd-out transition acts
as instrument with outcomes (1) out of pocket costs; and (2)
family premiums
  Addresses
binary nature of endogenous crowd-out variable
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CONCLUSIONS ON CROWD-OUT
  Evidence is strong that crowd-out occurs
  Difficult/ impossible to draw precise conclusions as
to its exact extent
  Estimates are highly sensitive to specification
  Given non-normality of standard errors, crowd-out
point estimates should include properly adjusted
confidence intervals
  Bootstrap analysis finds that 95% confidence
intervals for crowd-out estimates can range by as
much as a factor of two
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EFFECTS OF CROWD-OUT
  Gruber & Simon instrument highly predictive of
crowd-out
  Child health status predictive of a private to public
transition and substantially increased out-of-pocket
and premium costs
  Crowd-out provides a large financial benefit to
affected families
$318 reduction in out-of-pocket medical expenditures
[$169, 464]
  $2,242 reduction in family premium costs [$1,766,
2,601]

LESSONS FOR NATIONAL HEALTH
CARE REFORM
  During the 2007 SCHIP reauthorization debate:
  Concern was raised that only 60% of eligible children in
families earning < 200% FPL were enrolled
  Further, families with incomes higher than 200% FPL are
more likely to crowd-out
  Our study and others highlight the financial burden
of middle-income families with a child in poor health
Crowd-out may result in a substantial cash transfer for families
  This may serve important social ends for vulnerable families
  Any larger public/private health reform package should
account for this

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