SCHIP Original Allotments: Description and Analysis

SCHIP Original Allotments: Description and Analysis

Order Code RL33366
SCHIP Original Allotments:
Description and Analysis
Updated March 12, 2007
Chris L. Peterson
Specialist in Social Legislation
Domestic Social Policy Division

SCHIP Original Allotments:
Description and Analysis
Summary
The Balanced Budget Act of 1997 (BBA 97, P.L. 105-33) created the State
Children’s Health Insurance Program (SCHIP). In BBA 97, Congress authorized and
appropriated funds totaling nearly $40 billion for FY1998-FY2007, with each state
receiving access to a portion of the annual amount. Each state’s portion — the
original allotment — is calculated based on a formula that has been altered only one
time since the program’s inception.
SCHIP currently has no appropriations past FY2007. As new appropriations are
considered, the focus regarding SCHIP original allotments will be on (1) setting the
national annual appropriations for SCHIP, and (2) deciding how those funds will be
allotted to individual states. Some of the issues are technical — for example,
whether a better data source exists for estimating the number of low-income children.
Other issues raise more fundamental questions about the program.
Since FY2002, states’ total spending of federal SCHIP funds has exceeded the
annual appropriations for original allotments. However, between FY2002 and
FY2005, shortfalls of federal SCHIP funds were largely avoided because of leftover
prior-year balances and the targeted redistribution of other states’ unspent funds.
However, the funds available for redistribution have been shrinking over the past
several years. Because such amounts were projected to be inadequate to prevent
shortfalls in FY2006, Congress appropriated an additional $283 million in the Deficit
Reduction Act of 2005 (DRA, P.L. 109-171) for projected shortfall states. Shortfalls
in 14 states in FY2007 are projected to total nearly $750 million. With less money
available through redistributions and prior-year balances, the amounts states receive
in their own original allotments become increasingly important.
Increasing the national SCHIP appropriations to match states’ projected
spending would not necessarily prevent shortfalls. This is because the current
formula for allotting those funds among states does not take into account states’
SCHIP spending or their likelihood of facing shortfalls. As Congress considers the
level of future SCHIP appropriations, it may also examine whether the formula for
distributing those funds to states should be revised.
If the current allotment level and formula continue into the future, then in a few
years most states will face chronic shortfalls of federal SCHIP funds. However, such
shortfalls are an inherent characteristic of a capped-grant program such as SCHIP.
The federal government’s responsibility to prevent or lessen these shortfalls will be
among the issues Congress grapples with in determining the national appropriation
level and state distribution of future original allotments.
This report describes how SCHIP original allotments have operated and
discusses issues and options Congress might consider for the future.

Contents
Description of Original Allotments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
National SCHIP Appropriations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
Allotment Formula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Number of Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
State Cost Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Floors and Ceilings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Analysis of SCHIP Original Allotments: Issues and Options . . . . . . . . . . . . . . . 10
Allotment Formula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Number of Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
State Cost Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Floors and Ceilings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
List of Tables
Table 1. Federal SCHIP Appropriations, Original Allotments,
and Spending, FY1998-FY2007 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Table 2. Factors, with Associated Weights,
for Calculating States’ SCHIP Original Allotments, by Fiscal Year . . . . . . . 5
Table 3. Applicable Floors and Ceilings for Calculating
States’ SCHIP Original Allotments, by Fiscal Year . . . . . . . . . . . . . . . . . . . 7
Table 4. Application of SCHIP Allotment Formula
to Derive FY2007 Original Allotments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Table 5. FY2007 Original Allotments and
Projected Federal SCHIP Spending, by State . . . . . . . . . . . . . . . . . . . . . . . 10
Table 6. Variation from SCHIP Allotment Formula:
Impact if FY2007 Allotments Were Based on FY1998 Proportion;
States Triggering Formula Floor or Ceiling (FY1998-FY2007) . . . . . . . . . 16
Table 7. Estimates of Uninsured and of All Low-Income Children,
by State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

SCHIP Original Allotments:
Description and Analysis
The Balanced Budget Act of 1997 (BBA 97, P.L. 105-33) established the State
Children’s Health Insurance Program (SCHIP). In general, this program allows
states1 to cover targeted low-income children with no health insurance in families
with incomes above Medicaid eligibility levels. In BBA 97, Congress authorized and
appropriated annual funding levels totaling nearly $40 billion for FY1998-FY2007,
with each state receiving access to a portion of the annual amount. Each state’s
portion — the original allotment2 — is calculated based on a formula that has been
altered only one time since the program’s inception.
Each year’s original allotment is available for three years. At the end of the
three-year period of availability, states’ unspent balances are redistributed to other
states that have exhausted that allotment, with some exceptions. This report does not
analyze the impact or amounts of redistributed funds. Nor does this report quantify
projected state shortfalls of federal SCHIP funds. Other CRS reports delve into these
issues.3 This report is narrowly focused on states’ original allotments as derived from
(1) the federal SCHIP appropriations and (2) the allotment formula. Other SCHIP
issues are presented only to the extent that they inform the discussion of original
allotments.
1 For this report, “states” includes the District of Columbia, since it is treated like other
states for SCHIP purposes. Generally, the word “states” does not include the five territories,
Puerto Rico, Guam, the Virgin Islands, American Samoa, and the Northern Mariana Islands.
These five “commonwealths and territories” are identified in §2104(c)(3) of the Social
Security Act and are treated differently from states for purposes of calculating their original
allotments. Unless noted otherwise, section references in law used in this report are to the
Social Security Act.
2 §2104 is the section entitled “Allotments.” The term “original allotments” does not occur
in the law. However, CRS uses this term to distinguish each year’s original, or initial,
allotment (subsections (a) through (e) of §2104) from the reallocation of the unspent
balances of these funds available for redistribution to other states (subsections (f) and (g)).
3 CRS Report RL30473, State Children’s Health Insurance Program (SCHIP): A Brief
Overview, by Elicia J. Herz and Chris L. Peterson. CRS Report RL32807, SCHIP
Financing: Funding Projections and State Redistribution Issues, by Chris L. Peterson.

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Description of Original Allotments
National SCHIP Appropriations
BBA 97 established SCHIP under a new Title XXI of the Social Security Act.
Section 2104(a) specified the total appropriations available in every fiscal year from
FY1998-FY2007. The only change to these numbers affecting states since BBA 97
was to add $20 million to the total FY1998 appropriation.4 The current-law numbers
in Section 2104(a) are shown in column A of Table 1. For SCHIP’s first four years,
BBA 97 held the total appropriation constant. However, for FY2002-FY2004, the
annual appropriation was $1.125 billion less than in FY1998-FY2001. This drop in
funding, sometimes referred to as the “CHIP dip,” was written into BBA 97 due to
budgetary constraints applicable at the time the legislation was drafted.
Sections 4921 and 4922 of BBA 97 called for $60 million to be used from the
total SCHIP appropriation each year from FY1998-FY2002 for special diabetes
grants.5 These subtractions to the total original allotments available to states and
territories are shown in column B of Table 1. Since FY2003, these two diabetes
programs have been funded by direct appropriations, not from the SCHIP
appropriations.
Except for the $20 million adjustment to the total FY1998 SCHIP appropriation,
all legislative changes to the total SCHIP appropriation since BBA 97 have affected
only the five territories.6 BBA 97 called for the territories to receive 0.25% of the
amounts shown in column A of Table 1. The FY1999 Omnibus Appropriations Act
(P.L. 105-277) appropriated $32 million for the territories’ SCHIP original allotment
for FY1999, in addition to the 0.25% of the total appropriation. The $32 million was
approximately 0.75% of the $4.275 billion in column A of Table 1. The Medicare,
Medicaid and SCHIP Balanced Budget Refinement Act (BBRA) of 1999 (P.L. 106-
113) specified additional amounts to be appropriated to the territories for FY2000-
FY2007. The amounts specified for these years were exactly 0.8% of the total
appropriations shown in column A of Table 1. Thus, for FY2000-FY2007, territories
were slated to receive a total of 1.05% of the amounts specified in §2104(a), although
only the 0.25% portion would reduce the amount of original allotments available to
the states specifically.7 Column C of Table 1 shows the additional appropriations for
the territories from these provisions.
4 §162 of P.L. 105-100 made changes “[e]ffective as if included in the enactment of ... the
Balanced Budget Act of 1997.” Paragraph (8)(A) increased the FY1998 appropriation of
$4,275,000,000 by $20 million to $4,295,000,000.
5 Public Health Service Act §330B and §330C.
6 The appropriation of $283 million to SCHIP for FY2006 through the Deficit Reduction Act
of 2005 (DRA, P.L. 109-171) is not considered a legislative change to original allotments.
This DRA appropriation was a special appropriation targeted to shortfall states. It was not
distributed based on the SCHIP allotment formula, nor was it available for three years.
7 As discussed in other previously referenced CRS reports, the 1.05% amount is used in the
annual reallocation of unspent original allotment funds after their three-year period of
availability has passed. Of the total unspent funds, 1.05% is designated for the territories.

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Column D of Table 1 displays the total amount of federal SCHIP original
allotments provided to the states and territories under current law. For comparative
purposes, column E shows the total spending of federal SCHIP funds in each of those
years (projected for FY2007). The spending is applied against all available federal
SCHIP funds, not just that year’s original allotment. Thus, even though the national
spending of federal SCHIP funds has exceeded the total annual allotments since
FY2002, state shortfalls of federal SCHIP funds have largely been avoided because
of the redistribution of other states’ unspent funds.8
Table 1. Federal SCHIP Appropriations, Original Allotments,
and Spending, FY1998-FY2007
A
B
C

D = A-B+C
E
Subtract
Add
For
Allotments
Special
territories
Original
specified in
diabetes
per
allotments to states
FY
§2104(a)
grants
§2104(c)(4)
and territories
Total spending
1998
$4,295,000,000 $60,000,000
$4,235,000,000
$121,800,000
1999
$4,275,000,000 $60,000,000 $32,000,000 $4,247,000,000
$921,800,000
2000
$4,275,000,000 $60,000,000 $34,200,000 $4,249,200,000
$1,928,800,000
2001
$4,275,000,000 $60,000,000 $34,200,000 $4,249,200,000
$2,671,600,000
2002
$3,150,000,000 $60,000,000 $25,200,000 $3,115,200,000
$3,776,200,000
2003
$3,150,000,000 $25,200,000
$3,175,200,000
$4,276,400,000
2004
$3,150,000,000 $25,200,000
$3,175,200,000
$4,644,700,000
2005
$4,050,000,000 $32,400,000
$4,082,400,000
$5,089,500,000
2006
$4,050,000,000 $32,400,000
$4,082,400,000
$5,453,700,000
2007
$5,000,000,000 $40,000,000
$5,040,000,000
$6,395,300,000
Total $39,670,000,000 $300,000,000 $280,800,000
$39,650,800,000 $35,279,700,000
Source: Social Security Act §2104 and CRS SCHIP Projection Model.
Notes: Section numbers refer to Title XXI of the Social Security Act. The special diabetes grants are
described in Public Health Service Act §330B and §330C. Numbers rounded to the nearest $100,000.
Spending is included for comparative purposes and is from all federal SCHIP funds — reallocated
funds (that is, amounts from the redistribution and retention of unspent funds after original allotments’
three-year period of availability) as well as from original allotments. Spending projections for
FY2007 is based on states’ own estimates, provided to the Centers for Medicare and Medicaid
Services in November-December 2006. The territories do not provide these estimates.
8 For additional details, see CRS Report RL32807, SCHIP Financing: Funding Projections
and State Redistribution Issues, by Chris L. Peterson.

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Allotment Formula
A primary purpose of funding formulas like the SCHIP allotment formula is to
distribute funds based on “need,” defined as “the potential cost of the program based
on the size of the target population and the cost of providing services.”9 The target
population and the cost of providing services were included in the original SCHIP
allotment formula, using data available at the time, as two factors: the number of
children and a state cost factor.10 Once calculated, these two factors are multiplied
by each other for each state, with the results added for a national total. Each state’s
percentage of the total, subject to floors and ceilings, is then multiplied by the total
allotment funds available to states in that year. The result is the amount allotted to
each state for that fiscal year.
Number of Children. The number of children is composed of two estimates
for each state:
! the number of low-income children without health insurance; and
! the number of all low-income children.
A low-income child is an individual under the age of 19 whose family income
is at or below 200% of the poverty line.11 The weight attached to each of the two
factors varies by fiscal year. For FY1998 and FY1999, the “number of children” in
each state relied solely on the number of uninsured low-income children, as shown
in Table 2. As SCHIP began to cover more low-income children, the formula was
designed to rely less on the number of uninsured low-income children and more on
the number of all low-income children. FY2000 was the transition year, in which the
“number of children” used 75% of the number of uninsured low-income children and
25% of the number of all low-income children, as illustrated in Table 2.12 For
FY2001 onward, the “number of children” is weighted evenly between the number
of uninsured low-income children and the number of all low-income children in each
state.
9 Lynn A. Blewett and Michael Davern, “Distributing SCHIP Funds: A Critical Review of
the Design and Implementation of the SCHIP Funding Formula,” Journal of Health Politics,
Policy and Law, forthcoming May 2007, vol. 32, no. 3.
10 §2104(b). The territories’ original allotment amounts are based on §2104(c)(2). Of the
total amount of original allotments available to territories, each territory receives a fixed
percentage: Puerto Rico receives 91.6%, Guam 3.5%, the Virgin Islands 2.6%, American
Samoa 1.2%, and the Northern Mariana Islands 1.1%. These percentages are specified in
law and have been unaltered since BBA 97.
11 For 2005, this measure of poverty for a family of three with two children was $15,735
[http://www.census.gov/hhes/www/poverty/threshld/thresh05.html]. At 200% of this level,
the amount would be $31,470.
12 In BBA 97, FY2001 was slated to be the transition year rather than FY2000. The
transition year was moved up by BBRA.

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Table 2. Factors, with Associated Weights, for Calculating
States’ SCHIP Original Allotments, by Fiscal Year
State’s original allotment = “number of children” x “state cost factor”
(subject to floors and ceilings shown in Table 3)
“Number of children” in §2104(b)(2) is the
“State cost factor” in §2104(b)(3) is the
sum of the two factors below multiplied by sum of the two factors below multiplied by
the associated percentage
the associated percentage
Ratio of state’s
Number of low-
average annual
income children
wages (health
without health
Number of all low-
Constant (at the
services industry) to
FY
insurance
income children
national average)
national average
1998
100%
0%
1999
2000
75%
25%
2001
2002
15%
85%
2003
2004
50%
50%
2005
2006
2007
Source: Social Security Act §2104(b).
The source of data for these state-level estimates is the March supplement of the
Current Population Survey (CPS), which is administered by the U.S. Census Bureau.
The CPS is a monthly survey of households that provides estimates of employment
and unemployment in the U.S. Between February and April, respondents are asked
additional questions about their work experience, income, noncash benefits,
migration and health insurance status in the previous year. Because the supplement
is no longer given only in March, it has been renamed the Annual Social and
Economic (ASEC) Supplement, though many analysts continue to call it the March
supplement.
Since survey estimates come from only a sample of the population, the estimates
could differ from the results from a complete census using the same survey questions.
It is possible to estimate this “sampling error” based on the sample size (that is, the
number of respondents). Because sample sizes can be relatively small in less
populous states, results from multiple years are often averaged together to reduce the
sampling error. Current law specifies that for estimating the SCHIP original
allotment’s “number of children,” an average of the most recent three years is used.13
The original allotments for FY2007 were announced on July 28, 2006.14 The
“number of children” for these allotments was based on ASEC data from 2002, 2003,
and 2004. Data for 2005, collected in the 2006 ASEC, were not released until
13 §2104(b)(2)(B).
14 U.S. Department of Health and Human Services, “State Children’s Health Insurance
Program; Final Allotments to States, the District of Columbia, and U.S. Territories and
Commonwealths for Fiscal Year 2007,” 71 Federal Register 42854, July 28, 2006.

CRS-6
August 29, 2006. Regardless, that later data could not be used for calculating the
FY2007 original allotments. The law specifies that the original allotment for a fiscal
year must be based on “the 3 most recent March supplements to the Current
Population Survey of the Bureau of the Census before the beginning of the calendar
year in which such fiscal year begins.”15 FY2007 began (October 1, 2006) in
calendar year 2006. Thus, the Centers for Medicare and Medicaid Services (CMS)
interpreted the law to mean that, for the FY2007 original allotments, the CPS data
can be no more recent than those available on December 31, 2005. On that date, the
2005 ASEC, providing data from 2004, was the most recent officially available.
Thus, the FY2007 original allotments were based on data averaged over the three-
year period 2002-2004.
State Cost Factor. The other major factor used in calculating states’ portion
of the total annual SCHIP appropriation is a state cost factor, based on wages of
employees in the health services industry. The factor is intended to adjust for
geographic variations in health care costs. The national average is scaled to equal
1.00. States with above-average wages in the health services industry will have a
value greater than 1.00, which will increase the amount of their allotment — and vice
versa. As shown in Table 2, 15% of the state cost factor does not vary. In essence,
that portion is held at 1.00, the national average. The remaining 85% reflects how
each state’s average wage compares to the national average.
The law specifies that the wage data are to be obtained from the Bureau of
Labor Statistics (BLS) of the Department of Labor, using three-year averages for the
same years used to calculate the “number of children.” The law also defines the
“health services industry” as employers with a Standard Industrial Classification
(SIC) code of 8000.16 However, in 2002, BLS replaced SIC with the North American
Industry Classification System (NAICS). Although the mapping between the two
systems for the health services industry was not identical, the NAICS wage data
codes “represent approximately 98 percent of the wage data that would have been
provided under the related SIC code 8000.”17 The NAICS codes now used are 621
(ambulatory health care services), 622 (hospitals), and 623 (nursing and residential
care facilities). These three codes are under the broader category (62) for health care
and social assistance. The only NAICS code from this category not used for the state
cost factor is 624 (social assistance).18
The source of data BLS uses for calculating the average wages is from
mandatory reports filed quarterly by every employer on their unemployment
insurance contributions. BLS provides the data directly to CMS. Because the data
cover all employers subject to unemployment insurance coverage under federal law
15 §2104(b)(2)(B).
16 §2104(b)(3)(B).
17 U.S. Department of Health and Human Services, “State Children’s Health Insurance
Program; Final Allotments to States, the District of Columbia, and U.S. Territories and
Commonwealths for Fiscal Year 2006,” 70 Federal Register 36617, June 24, 2005.
18 U.S. Census Bureau, “2002 NAICS Codes and Titles,” Title 62, at [http://www.census.
gov/epcd/naics02/naicod02.htm#N62].

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(nearly 99% of employers), it is not technically a survey, but rather a census.19 As a
result, using a three-year average does not reduce sampling error, since censuses do
not have sampling error. Rather, the three-year average results in consistent reporting
periods for both the “number of children” and the state cost factor.
Table 3. Applicable Floors and Ceilings for Calculating
States’ SCHIP Original Allotments, by Fiscal Year
Floor: state’s minimum share of national appropriation
Ceiling: state’s
(greatest applicable factor applies)
maximum share
Share that equals
90% of last year’s
70% of 1998-1999
145% of 1998-1999
FY
$2,000,000
share
share
share
1998
X
1999
X
2000
X
X
X
X
2001
X
X
X
X
2002
X
X
X
X
2003
X
X
X
X
2004
X
X
X
X
2005
X
X
X
X
2006
X
X
X
X
2007
X
X
X
X
Source: Social Security Act §2104(b)(4).
Note: The “X” represents factors applicable for that fiscal year. Once a state’s original allotment
based on Table 2 is calculated, it is tested against the applicable floors and ceilings in this table. The
tests are evaluated in terms of the state’s share (or percentage) of the total SCHIP appropriation, not
on the dollar amounts. P.L. 105-277 required the FY1999 share be the same as the FY1998 share.
Floors and Ceilings. For FY1998 and FY1999, the only adjustment to the
calculated state shares of annual SCHIP appropriations was a floor, guaranteeing that
every state would receive an allotment of at least $2 million, as shown in Table 3.
No state’s preadjusted allotment for FY1998 or FY1999 was below $2 million, so
this floor never applied.
BBRA added two other tests to ensure states’ share of the total SCHIP
appropriation did not drop below certain levels. The legislation also added a ceiling
to cap the share of the appropriation a state could receive. These BBRA provisions
were effective beginning with the FY2000 allotment. As previously mentioned, in
calculating the allotment for each state, the number of children and the state cost
factor are multiplied together, with the results added for a national total. Each state’s
percentage of the total — its “preadjusted proportion” — is the value against which
BBRA’s floors and ceilings are assessed. For the floor, two new tests were applied:
(1) a state’s share could not be less than 90% of last year’s, and (2) its share could not
be less than 70% of its FY1999 share, as shown in Table 3. For the ceiling, no
state’s share could exceed 145% of its FY1999 share, also shown in Table 3. Once
the floors and ceilings were applied to affected states to produce their adjusted
proportion, the other states’ shares were adjusted equally to use exactly 100% of the
19 U.S. Department of Labor Bureau of Labor Statistics, “Quarterly Census of Employment
and Wages: Overview,” at [http://www.bls.gov/cew/cewover.htm].

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funding for the year available to the states. Table 4 shows how all of these factors
were applied to calculate states’ and territories’ FY2007 original allotments.
Although Title XXI requires that FY1999 be the basis for the historical
comparisons in calculating the floors and ceiling, the SCHIP law could also have set
FY1998 as the base year, and the impact of the floors and ceiling would be no
different. This is because P.L. 105-277 required that states’ share of the FY1999
SCHIP appropriation be the same as their share for FY1998. According to one
source:
The reason behind this intervention into the formula allocation process was that
a preliminary calculation based on the average number of low-income uninsured
children as measured in the 1995, 1996, and 1997 [CPS] March supplements
showed substantial variation from the estimates based on the 1994, 1995, and
1996 March supplements. ... What is notable is that 23 of the 51 states would
have had double-digit percentage changes in their shares of the national
allocation, with one state’s share falling by 41.7 per cent and another’s rising by
nearly the same amount. Seeing these results affecting such a highly visible
program, it is no surprise Congress acted.20
Table 4. Application of SCHIP Allotment Formula
to Derive FY2007 Original Allotments
A
B
C=A*B
Number of
Pre-
State or
children
State cost
adjusted
Adjusted
territory
(000s)
factor
Product
proportion proportion
Allotment
Alabama 277
0.9701
268.2199
1.4815%
1.4896%
$74,295,313
Alaska 40
1.0542
41.6420
0.2300%
0.2313%
$11,534,589
Arizona 424
1.0887
461.5930
2.5496%
2.5636%
$127,858,497
Arkansas 195
0.9129
178.0092
0.9832%
0.9886%
$49,307,483
California 2533
1.1271
2854.8962
15.7688%
15.8554%
$790,789,213
Colorado 255
1.0621
270.8420
1.4960%
1.4345%
$71,544,798
Connecticut 128
1.1251
144.0124
0.7954%
0.7998%
$39,890,581
Delaware 39
1.0369
39.9198
0.2205%
0.2217%
$11,057,552
D.C.
34
1.2432
42.2701
0.2335%
0.2348%
$11,708,552
Florida 1036
1.0322
1068.8561
5.9037%
5.9362%
$296,066,768
Georgia 574
1.0433
598.8366
3.3076%
3.3258%
$165,874,160
Hawaii 57
1.1199
63.2741
0.3495%
0.3071%
$15,314,228
Idaho 100
0.8823
87.7868
0.4849%
0.4875%
$24,316,412
Illinois 750
1.0594
794.0428
4.3858%
4.2059%
$209,767,107
Indiana 352
0.9600
337.4418
1.8638%
1.8741%
$93,469,355
Iowa 141
0.9309
130.7962
0.7224%
0.7264%
$36,229,776
Kansas 143
0.9258
131.9224
0.7287%
0.7327%
$36,541,720
Kentucky 267
0.9480
253.1272
1.3981%
1.4058%
$70,114,712
Louisiana 355
0.9123
323.4215
1.7864%
1.7962%
$89,585,836
Maine 59
0.9284
54.7733
0.3025%
0.3042%
$15,171,887
Maryland 221
1.0939
241.7411
1.3352%
1.3426%
$66,960,838
20 John L. Czajka and Thomas B. Jabine, “Using Survey Data to Allocate Federal Funds for
the State Children’s Health Insurance Program (SCHIP),” Journal of Official Statistics, Vol.
18, No. 3, 2002, pp. 417-418, available online at [http://www.jos.nu/Articles/abstract.
asp?article=183409].

CRS-9
A
B
C=A*B
Number of
Pre-
State or
children
State cost
adjusted
Adjusted
territory
(000s)
factor
Product
proportion proportion
Allotment
Massachusetts 244
1.1083
269.8654
1.4906%
1.4704%
$73,334,995
Michigan 532
1.0137
539.2999
2.9788%
2.9951%
$149,382,856
Minnesota 181
1.0218
184.9443
1.0215%
0.9747%
$48,613,498
Mississippi 237
0.9215
218.3966
1.2063%
1.2129%
$60,494,559
Missouri 279
0.9352
260.4401
1.4385%
1.4464%
$72,140,346
Montana 64
0.8877
56.8115
0.3138%
0.3155%
$15,736,459
Nebraska 87
0.9084
79.0326
0.4365%
0.4389%
$21,891,551
Nevada 159
1.2093
192.2753
1.0620%
1.0437%
$52,056,449
New Hampshire
37
1.0518
38.9149
0.2149%
0.2161%
$10,779,193
New Jersey
335
1.1338
379.8138
2.0979%
2.1094%
$105,206,164
New Mexico
160
0.9445
151.1252
0.8347%
1.0435%
$52,045,406
New York
1123
1.0961
1230.3754
6.7959%
6.8332%
$340,806,655
North Carolina
562
0.9771
549.1038
3.0329%
2.7292%
$136,117,313
North Dakota
32
0.8729
27.9339
0.1543%
0.1551%
$7,737,529
Ohio 595
0.9587
570.3984
3.1505%
3.1679%
$157,996,958
Oklahoma 249
0.8767
218.2966
1.2057%
1.4201%
$70,828,185
Oregon 203
1.0090
204.8210
1.1313%
1.1375%
$56,734,200
Pennsylvania 615
1.0196
626.5640
3.4608%
3.4798%
$173,554,494
Rhode Island
50
1.0096
50.4811
0.2788%
0.2804%
$13,982,960
South Carolina
254
1.0042
255.0648
1.4088%
1.4166%
$70,651,421
South Dakota
41
0.9230
37.3810
0.2065%
0.2076%
$10,354,308
Tennessee 348
1.0125
351.8472
1.9434%
1.9541%
$97,459,570
Texas 2080
0.9685
2014.4123
11.1264%
11.1876%
$557,980,188
Utah 166
0.8805
146.1615
0.8073%
0.8117%
$40,485,868
Vermont 23
0.9231
20.7706
0.1147%
0.1154%
$5,753,333
Virginia 329
1.0338
339.6114
1.8758%
1.8861%
$94,070,318
Washington 318
0.9897
314.2298
1.7356%
1.6017%
$79,883,308
West Virginia
111
0.8990
99.3412
0.5487%
0.5517%
$27,516,914
Wisconsin 263
1.0077
264.5260
1.4611%
1.3948%
$69,563,162
Wyoming 27
0.9458
25.0636
0.1384%
0.1392%
$6,942,463
State totals 18,104.7276 100.0000% 100.0000% $4,987,500,000
Total amount available to states = $5 billion less 0.25% for territories =
Puerto Rico
91.6%
$48,090,000
Guam
3.5%
$1,837,500
Virgin Islands
2.6%
$1,365,000
American Samoa
1.2%
$630,000
N. Mariana Islands
1.1%
$577,500
Total amount available to territories = 0.25% of $5 billion + $40 million =
$52,500,000
Total original allotments to states and territories $5,040,000,000
Source: U.S. Department of Health and Human Services, “State Children’s Health Insurance
Program; Final Allotments to States, the District of Columbia, and U.S. Territories and
Commonwealths for Fiscal Year 2007,” 71 Federal Register 42854, July 28, 2006.

CRS-10
Analysis of SCHIP Original Allotments:
Issues and Options
The last row of Table 5 shows that the FY2007 SCHIP appropriation to states
was nearly $5 billion. However, states’ spending of federal SCHIP funds in FY2007
is projected at $6.3 billion, 27% more than the FY2007 original allotments.
Spending is projected to exceed FY2007 allotments in 34 states. Prior-year balances
prevent 20 of these states from facing shortfalls, so that only the remaining 14 states
are projected to experience shortfalls in FY2007.
Table 5. FY2007 Original Allotments
and Projected Federal SCHIP Spending, by State
(in millions of dollars; sorted by spending as a percentage of original allotment)
Spending as a percent
State
Original allotment
Projected spending
of original allotment
Tennessee $97.5
$22.9
24%
Washington $79.9
$27.1
34%
Nevada $52.1
$31.1
60%
Vermont $5.8
$3.5
61%
Connecticut $39.9
$25.9
65%
South Carolina
$70.7
$53.5
76%
Delaware $11.1
$8.4
76%
DC
$11.7
$9.3
80%
Texas $558.0
$452.8
81%
Idaho $24.3
$20.3
83%
Florida $296.1
$258.9
87%
Colorado $71.5
$63.5
89%
Indiana $93.5
$84.0
90%
Arizona $127.9
$115.1
90%
New Hampshire
$10.8
$10.2
95%
Utah $40.5
$39.0
96%
New York
$340.8
$337.8
99%
Pennsylvania $173.6
$177.2
102%
New Mexico
$52.0
$55.4
106%
Montana $15.7
$17.2
110%
Louisiana $89.6
$98.6
110%
Arkansas $49.3
$54.3
110%
Virginia $94.1
$108.3
115%
Kentucky $70.1
$81.2
116%
Oklahoma $70.8
$82.4
116%
Wyoming $6.9
$8.1
117%
Michigan $149.4
$175.6
118%
Oregon $56.7
$67.1
118%
North Carolina
$136.1
$169.4
124%
Hawaii $15.3
$19.4
127%
Ohio $158.0
$202.5
128%
Alabama $74.3
$98.6
133%
South Dakota
$10.4
$13.9
135%
West Virginia
$27.5
$37.1
135%
Kansas $36.5
$50.0
137%

CRS-11
Spending as a percent
State
Original allotment
Projected spending
of original allotment
Missouri $72.1
$98.7
137%
California $790.8
$1,103.3
140%
Wisconsin $69.6
$99.1
142%
North Dakota
$7.7
$11.4
148%
Nebraska $21.9
$33.7
154%
Iowa $36.2
$56.7
157%
Minnesota $48.6
$78.7
162%
Maine $15.2
$25.0
165%
Georgia $165.9
$312.1
188%
Mississippi $60.5
$120.6
199%
Maryland $67.0
$151.1
226%
Alaska $11.5
$30.2
262%
New Jersey
$105.2
$286.5
272%
Illinois $209.8
$578.5
276%
Massachusetts $73.3
$212.5
290%
Rhode Island
$14.0
$70.3
503%
State total
$4,987.5
$6,348.1
127%
Source: Congressional Research Service (CRS) analysis of data from the Centers for Medicare and
Medicaid Services (CMS), including states’ November-December 2006 projections of FY2007 federal
SCHIP spending.
Although the last SCHIP appropriation scheduled under current law is $5.0
billion in FY2007, the Congressional Budget Office (CBO) is required to assume that
the program continues in perpetuity at the last appropriated level.21 Thus, legislation
that simply appropriates $5.0 billion annually beyond FY2007 would not be scored
by CBO as increasing federal government spending above CBO’s current baseline.
If the FY2007 level and distribution of original allotments remain the same and states
continue their current projected spending, inevitably all 34 states with projected
spending exceeding their original allotments would face shortfalls. If states increase
their spending, even to account for health care inflation, additional states could face
chronic shortfalls. Under baseline assumptions, CBO projects that 43 states would
face shortfalls by FY2017.22
The prospect of chronic long-term SCHIP shortfalls in the majority of states
raises fundamental questions about the role of the federal government in a program
that was created as a capped matching grant to states. Two potentially conflicting
policy goals of the current structure of SCHIP include its efforts (1) to expand (or
21 Section 257 of the Balanced Budget and Emergency Deficit Control Act of 1985 (P.L. 99-
177, also known as Gramm-Rudman-Hollings), as amended by Section 10209 of BBA 97.
The BBA 97 conference report (105-217) describes the amendment as follows: “The
conference agreement amends section 257 to provide that only those programs with current
year outlays in excess of $50 million and that were in existence on or before the date of
enactment of the Balanced Budget Act of 1997 are assumed to continue for the purposes of
the baseline.” Since SCHIP was in BBA 97, this provision applies.
22 Congressional Budget Office, Fact Sheet for CBO’s March 2007 Baseline: State Children
Health Insurance Program, February 23, 2007.

CRS-12
prevent the loss of) health insurance coverage, and (2) to limit and control federal
spending for that coverage. One contention is that inadequate original allotments are
one reason for states’ shortfalls of federal SCHIP funds. For example, Iowa’s SCHIP
director said, “The SCHIP funding formula is flawed in that it allocates funds to
states based on inaccurate data, penalizes states for insuring more children, and
inadequately distributed funding over the 10 years during which the program was
authorized.”23
The sections below discuss some specific options for altering the current
allotment formula, including changes related to the Iowa SCHIP director’s
comments. However, it must be noted that to eliminate states’ shortfalls by altering
original allotments, both the total amount of original allotments and how they are
distributed to states would likely have to be altered.
Allotment Formula
The allotment formula for determining each state’s share of the national SCHIP
appropriation was set in BBA 97. In the absence of established SCHIP programs on
which to base states’ allotments, Congress used the previously discussed number of
children and the state cost factor. In essence, Congress decided that SCHIP
allotments should be based on the number of low-income (below 200% of poverty)
children in each state, with variation in the extent to which the number includes all
low-income children or just those who were uninsured. Having established the
number of children as the basis for states’ share of the total appropriation, the state
cost factor provided an adjustment designed to reflect the cost of health care in each
state. The remainder of this section of the report discusses possible changes to the
existing components of the formula, as well as additional options based on new
information not available a decade ago.

Number of Children. What is the target population of SCHIP, and does the
current SCHIP allotment formula accurately target funds to that population?
According to Title XXI, the target population is “uninsured, low-income children.”24
In the first two years of SCHIP, the number of children was defined in the
formula as the number of uninsured low-income children, based on the CPS
estimates. Theoretically, perhaps only uninsured low-income children eligible for
SCHIP should have been included (for example, excluding uninsured low-income
children who were eligible for Medicaid). However, “the potential magnitude of the
error that would accompany state-specific estimates of this group makes it difficult
to argue” that such estimates should have been used instead.25
23 Anita Smith, director of Iowa’s SCHIP program, quoted in the CRS Congressional
Distribution memorandum “Status of Federal SCHIP Financing Among Nine States
Reporting Identical Lower- and Upper-Income SCHIP Eligibility Levels,” by Chris L.
Peterson, September 12, 2006.
24 §2101(a)
25 John L. Czajka and Thomas B. Jabine, “Using Survey Data to Allocate Federal Funds for
(continued...)

CRS-13
If the “number of children” had continued with its FY1998-1999 structure, then
if a state had enrolled all its uninsured low-income children in SCHIP, the formula
would have caused the state to ultimately receive no more SCHIP funds. Thus, the
formula came to rely equally on the number of uninsured low-income children and
the total number of low-income children.
However, by including the total number of low-income children, states are
allotted SCHIP funds for other low-income children who are not part of the target
population (for example, those with private health insurance). Again, although it
may be desirable to use more detailed estimates, such a step comes at the risk of
increasing sampling error and bias with the CPS data. Some researchers suggested
a “more obvious solution of adding the children enrolled in SCHIP to the estimated
number of uninsured low-income children.”26 This would focus the formula on
states’ current child enrollees as well as potentially eligible uninsured low-income
children. However, their “more obvious solution” would include all child enrollees
in the formula, even though some states cover children in their SCHIP programs well
above 200% of poverty. Moreover, as the researchers state, “[i]ntroducing
administrative estimates into the allocation formula would place reliance on the fund
recipients — the states — to estimate a component of need, which then affected the
size of their allocations.”27
More generally, some states have suggested that the portion of the formula that
includes the number of uninsured low-income children be dropped altogether. One
argument is that this portion of the formula creates a perverse incentive. As one state
official said, “Efforts to reduce the number of uninsured children by increasing
enrollment in one of a state’s government-sponsored programs would appear to
potentially have a negative impact on the SCHIP allocation a state may receive in a
given fiscal year.”28 By dropping the uninsured estimates from the calculation for the
number of children, no state’s original allotment would change by more than 10%,
according to a previous CRS analysis of states’ FY2006 original allotments.29
Nevertheless, the tension is in how much the formula should be geared toward
25 (...continued)
the State Children’s Health Insurance Program (SCHIP),” Journal of Official Statistics, Vol.
18, No. 3, 2002, pp. 417-418, available online at [http://www.jos.nu/Articles/abstract.asp?
article=183409].
26 John L. Czajka and Thomas B. Jabine, “Using Survey Data to Allocate Federal Funds for
the State Children’s Health Insurance Program (SCHIP),” Journal of Official Statistics, Vol.
18, No. 3, 2002, p. 424, available online at [http://www.jos.nu/Articles/abstract.asp?
article=183409].
27 Ibid.
28 George L. Hoover, Deputy Commissioner, Pennsylvania’s CHIP and Adult Basic
Programs, quoted in CRS Congressional Distribution memorandum “Status of Federal
SCHIP Financing Among Nine States Reporting Identical Lower- and Upper-Income SCHIP
Eligibility Levels,” by Chris L. Peterson, September 12, 2006.
29 Table 3 of “Federal SCHIP Financing: Testimony Before the Senate Finance Health
Subcommittee,” Chris L. Peterson, Congressional Research Service (CRS), July 25, 2006,
at [http://finance.senate.gov/hearings/testimony/2005test/072506cptest.pdf].

CRS-14
financing current SCHIP enrollees versus the potential enrollees (uninsured low-
income children) specified in the statute.
Outside of the question of the overall structure of this portion of the formula is
the issue of whether the current formula uses the best available data. For example,
there are well-documented concerns with the CPS’s estimates of the uninsured,
which have been acknowledged by the Census Bureau.30 Some states have reported
that their own estimates of the uninsured do not correspond with the CPS estimates.31
During BBA 97, the CPS was the only source of data that could provide state-
level estimates of the number of low-income children and of those who were
uninsured in all the states. Even so, the high sampling error in many states requires
the use of three-year averages of the CPS estimates. Congress appropriated an
additional $10 million annually to expand the CPS sample size by about 34,500
households beginning with 2002 survey data. Even so, concerns remain regarding
the substantial variation and unpredictability in states’ allotments, partly driven by
the relatively large standard errors associated with the CPS estimates.32
Table 6 and Table 7 illustrate some of this variation. Table 6 shows states’
share of the total appropriation available in FY1998 and FY2007. The table also
shows how much more, or less, states would have received in their FY2007 original
allotments had the percentage been based on the FY1998 percentages rather than
those from FY2007. If the FY2007 original allotments had been based on the
FY1998 percentages, approximately $500 million allotted to 33 states in FY2007
would have gone to the other 18 states instead. The differences shown in Table 6
include not only changes in the CPS-derived number of children, but also in the state
cost factor. The table does not ascertain how much of the changes are due to actual
changes in state-level circumstances rather than sampling error or other potential
measurement issues.33
Since BBA 97, the Census Bureau has developed a new source of data that can
provide state-level estimates of low-income children — the American Community
Survey (ACS). The ACS is mailed to 3 million addresses annually, compared to the
CPS’s sample of approximately 100,000 households. As a result, use of the ACS
would lead to less year-to-year variation in states’ allotments due to the smaller CPS
sample.34 However, the ACS does not currently obtain estimates of the uninsured.
30 U.S. Census Bureau, “Income, Poverty, and Health Insurance Coverage in the United
States: 2004,” Current Population Reports P60-299, Washington, DC, 2005, available at
[http://www.census.gov/prod/2005pubs/p60-229.pdf], p. 16.
31 David Bergman, Perspectives on Reauthorization: SCHIP Directors Weigh In, National
Academy for State Health Policy, June 2005, p. 5, available at [http://www.nashp.org/
Files/CHIP25_final.pdf].
32 For example, see David Bergman, “Perspectives on Reauthorization: SCHIP Directors
Weigh In,” National Academy for State Health Policy, June 2005.
33 The changes were also limited by the floors and ceiling.
34 Table 2 of “Federal SCHIP Financing: Testimony Before the Senate Finance Health
(continued...)

CRS-15
Thus, the ACS cannot estimate the number of uninsured low-income children that
is currently part of the SCHIP allotment formula. The Census Bureau recently
completed testing a number of health insurance questions for possible inclusion in
the ACS, and preliminary results indicate the test questions performed well.
However, even if a decision is made to include a health insurance question(s) in the
ACS, it will be a couple of years before the data would be available.
Table 7 shows a comparison of the estimates and margins of error of estimates
of low-income children based on the CPS and the ACS. Even using a three-year
average on the CPS estimates, its margins of error are higher than the single-year
ACS estimates. This is a function of the ACS’s much larger sample of people.
Although the CPS provides estimates of uninsured low-income children, which the
ACS currently does not, the CPS margins of error by state are quite high, exceeding
50% in some states, as shown in Table 7. Such margins of error may raise additional
questions as to whether it is an appropriate basis for distributing billions of federal
SCHIP dollars.
Some states have expressed concern that the CPS estimates, even for the total
number of low-income children, are lower than states’ Medicaid and SCHIP
enrollment counts of low-income children — and that the ACS estimates are not
much better.35 However, for program eligibility purposes, states often count income
differently than surveys. In determining eligibility for Medicaid and SCHIP, states
have the flexibility to disregard certain amounts and types of income. Estimates from
the CPS and ACS do not reflect such disregards. In the CPS and the ACS, income
is counted identically across states for statistical purposes. As a result, states using
income disregards would be expected to have more enrollees below certain income
amounts than if the surveys’ gross income were used.
The income disregards differ by state. Thus, even in states reporting the same
upper-income eligibility level, a person who is ineligible in one state might be
eligible in another because of different income disregards. Indeed, even within a
particular state, a person with a particular amount of gross income may be eligible
for SCHIP while another person with the same amount of gross income may be
ineligible because of the type of income they have and how the disregards apply.
Thus, although the surveys have acknowledged limitations in the estimates they
provide, there would also be potential drawbacks to using states’ enrollment data.
The policy question is which of these (along with other possible factors) would best
allot the SCHIP appropriations consistent with Congress’s goals.
34 (...continued)
Subcommittee,” Chris L. Peterson, Congressional Research Service (CRS), July 25, 2006,
at [http://finance.senate.gov/hearings/testimony/2005test/072506cptest.pdf]. Other
comparisons in the characteristics of the ACS and CPS are available on pages 6-7 of that
document.
35 CRS Congressional Distribution memorandum “Status of Federal SCHIP Financing
Among Nine States Reporting Identical Lower- and Upper-Income SCHIP Eligibility
Levels,” by Chris L. Peterson, September 12, 2006, pp. 4-5 and 10-11 regarding North
Carolina.

CRS-16
Table 6. Variation from SCHIP Allotment Formula: Impact
if FY2007 Allotments Were Based on FY1998 Proportion;
States Triggering Formula Floor or Ceiling (FY1998-FY2007)
Difference in
# of years
# years state
FY2007 allotment
state hit
hit SCHIP
if based on
SCHIP
formula
State
FY1998
FY2007
FY1998 share
formula floor
ceiling
Alabama
2.04%
1.49%
$27,213,856
2
0
Alaska
0.16%
0.23%
-$3,400,539
0
1
Arizona
2.76%
2.56%
$10,042,266
0
0
Arkansas
1.13%
0.99%
$7,256,459
1
0
California
20.23%
15.86%
$218,272,362
1
0
Colorado
0.99%
1.43%
-$22,203,557
0
3
Connecticut
0.83%
0.80%
$1,384,881
1
0
Delaware
0.19%
0.22%
-$1,548,994
2
2
DC
0.29%
0.23%
$2,549,336
2
0
Florida
6.40%
5.94%
$22,970,208
1
0
Georgia
2.95%
3.33%
-$18,690,497
0
0
Hawaii
0.21%
0.31%
-$4,752,691
0
6
Idaho
0.38%
0.49%
-$5,567,568
0
1
Illinois
2.90%
4.21%
-$65,100,137
0
2
Indiana
1.67%
1.87%
-$10,216,774
1
0
Iowa
0.77%
0.73%
$2,095,626
0
0
Kansas
0.73%
0.73%
-$346,196
0
0
Kentucky
1.18%
1.41%
-$11,160,403
0
0
Louisiana
2.41%
1.80%
$30,532,763
2
0
Maine
0.30%
0.30%
-$428,770
0
0
Maryland
1.46%
1.34%
$5,801,318
1
0
Massachusetts
1.01%
1.47%
-$22,759,137
0
6
Michigan
2.17%
3.00%
-$41,249,727
0
1
Minnesota
0.67%
0.97%
-$15,086,947
0
5
Mississippi
1.33%
1.21%
$5,643,684
0
0
Missouri
1.22%
1.45%
-$11,130,951
0
0
Montana
0.28%
0.32%
-$1,874,816
1
0
Nebraska
0.35%
0.44%
-$4,343,199
1
0
Nevada
0.72%
1.04%
-$16,155,449
0
1
New Hampshire
0.27%
0.22%
$2,749,509
3
0
New Jersey
2.09%
2.11%
-$812,966
0
0
New Mexico
1.49%
1.04%
$22,305,174
8
0
New York
6.05%
6.83%
-$38,993,803
0
0
North Carolina
1.88%
2.73%
-$42,243,305
0
4
North Dakota
0.12%
0.16%
-$1,786,030
0
3
Ohio
2.74%
3.17%
-$21,351,771
0
0
Oklahoma
2.03%
1.42%
$30,354,937
8
0
Oregon
0.93%
1.14%
-$10,544,056
0
0
Pennsylvania
2.78%
3.48%
-$34,875,991
0
0
Rhode Island
0.25%
0.28%
-$1,368,082
1
0
South Carolina
1.50%
1.42%
$4,389,991
1
0
South Dakota
0.20%
0.21%
-$269,860
0
0
Tennessee
1.57%
1.95%
-$19,353,984
0
0
Texas
13.29%
11.19%
$104,772,413
2
0
Utah
0.57%
0.81%
-$11,864,829
0
0
Vermont
0.08%
0.12%
-$1,579,106
0
4

CRS-17
Difference in
# of years
# years state
FY2007 allotment
state hit
hit SCHIP
if based on
SCHIP
formula
State
FY1998
FY2007
FY1998 share
formula floor
ceiling
Virginia
1.62%
1.89%
-$13,412,301
0
0
Washington
1.10%
1.60%
-$24,791,372
0
5
West Virginia
0.56%
0.55%
$355,084
1
0
Wisconsin
0.96%
1.39%
-$21,588,567
0
2
Wyoming
0.18%
0.14%
$2,162,510
0
0
State total
100.0%
100.0%
$0
19 states
15 states
Source: Congressional Research Service (CRS).
Table 7. Estimates of Uninsured and of All Low-Income
Children, by State
American Community
Current Population Survey (CPS)
Survey (ACS)
3-year average (2003, 2004, and 2005)
2005
Number of low-income Number of low-income Number of low-income
uninsured children
children
children
Margin of
Margin of
Margin of
State
Estimate
error
Estimate
error
Estimate
error
United States
5,532
241
±4%
29,982
539
±2%
30,323
218
±1%
Alabama
48
22 ±45%
493
71 ±14%
550
15
±3%
Alaska
10
4 ±39%
68
10 ±14%
67
6
±9%
Arizona
187
49 ±26%
761
94 ±12%
756
21
±3%
Arkansas
37
16 ±42%
339
47 ±14%
363
12
±3%
California
835
110 ±13%
4,190
237
±6%
4,217
49
±1%
Colorado
110
35 ±32%
397
65 ±16%
424
15
±3%
Connecticut
37
18 ±48%
213
41 ±19%
221
13
±6%
Delaware
13
6 ±45%
68
12 ±17%
67
6
±9%
DC
7
4 ±56%
62
10 ±16%
61
5
±9%
Florida
431
71 ±16%
1,677
139
±8%
1,760
27
±2%
Georgia
196
51 ±26%
993
110 ±11%
1,030
25
±2%
Hawaii
8
4 ±49%
92
16 ±17%
96
9 ±10%
Idaho
28
10 ±35%
168
24 ±14%
174
7
±4%
Illinois
230
53 ±23%
1,233
118 ±10%
1,201
31
±3%
Indiana
95
31 ±33%
640
80 ±13%
622
19
±3%
Iowa
33
16 ±48%
235
41 ±18%
246
9
±4%
Kansas
34
16 ±46%
260
41 ±16%
269
10
±4%
Kentucky
68
25 ±37%
452
67 ±15%
464
14
±3%
Louisiana
88
31 ±36%
575
76 ±13%
590
17
±3%
Maine
11
6 ±53%
109
20 ±18%
106
7
±6%
Maryland
73
29 ±40%
416
67 ±16%
383
19
±5%
Massachusetts
50
24 ±47%
431
67 ±15%
397
16
±4%
Michigan
88
31 ±36%
968
102 ±11%
970
22
±2%
Minnesota
45
22 ±48%
307
55 ±18%
371
13
±3%
Mississippi
71
24 ±33%
416
53 ±13%
432
13
±3%

CRS-18
American Community
Current Population Survey (CPS)
Survey (ACS)
3-year average (2003, 2004, and 2005)
2005
Number of low-income Number of low-income Number of low-income
uninsured children
children
children
Margin of
Margin of
Margin of
State
Estimate
error
Estimate
error
Estimate
error
Missouri
71
29 ±41%
531
74 ±14%
583
16
±3%
Montana
24
8 ±33%
105
16 ±15%
100
7
±7%
Nebraska
19
10 ±52%
151
25 ±17%
161
9
±5%
Nevada
63
20 ±31%
246
37 ±15%
245
12
±5%
New Hampshire
7
6 ±84%
66
14 ±21%
72
7 ±10%
New Jersey
125
37 ±30%
550
76 ±14%
603
19
±3%
New Mexico
61
18 ±29%
272
39 ±14%
273
11
±4%
New York
248
55 ±22%
1,966
149
±8%
1,801
33
±2%
North Carolina
179
45 ±25%
955
102 ±11%
978
20
±2%
North Dakota
10
4 ±39%
55
10 ±18%
51
4
±8%
Ohio
153
43 ±28%
1,043
108 ±10%
1,088
25
±2%
Oklahoma
86
27 ±32%
406
59 ±14%
429
14
±3%
Oregon
63
25 ±40%
366
57 ±16%
359
14
±4%
Pennsylvania
175
45 ±26%
1,053
106 ±10%
1,054
24
±2%
Rhode Island
10
6 ±59%
93
16 ±17%
84
7
±8%
South Carolina
66
25 ±39%
461
67 ±14%
500
15
±3%
South Dakota
9
4 ±44%
73
12 ±16%
79
5
±7%
Tennessee
101
35 ±35%
611
84 ±14%
647
20
±3%
Texas
927
114 ±12%
3,246
204
±6%
3,235
41
±1%
Utah
52
18 ±34%
288
39 ±14%
292
12
±4%
Vermont
3
2 ±65%
41
8 ±19%
45
4 ±10%
Virginia
88
33 ±38%
560
80 ±14%
571
18
±3%
Washington
72
29 ±41%
568
80 ±14%
555
19
±3%
West Virginia
20
10 ±49%
187
27 ±15%
195
9
±5%
Wisconsin
60
25 ±42%
483
71 ±15%
446
14
±3%
Wyoming
6
4 ±65%
41
8 ±19%
40
4 ±10%
Source: Congressional Research Service (CRS) analysis of published Current Population Survey
(CPS) data, available at [http://www.census.gov/hhes/www/hlthins/lowinckid.html], and of American
Community Survey (ACS) data provided upon request by the U.S. Census Bureau. Margins of error
calculated using 95% confidence intervals.
State Cost Factor. Technical adjustments to this factor could be considered.
For example, the state cost factor is calculated based in part on wages paid in the
states’ nursing and residential care facilities. However, if the factor is to adjust for
the health care costs of children in the state, wages in nursing and residential care
facilities may not be critical. They could be dropped from the calculation or
weighted in a way that is more reflective of children’s utilization.
BLS has other employer surveys that could also provide similar information.
However, the currently used source of data is a virtual census of employers, which
may be preferable to a survey. Because it is a census, a three-year average may not

CRS-19
be necessary, as with the CPS estimates for the number of children. Using a single
year would also mean that the most recently available data could be the basis of the
factor, rather than also incorporating two previous years.
Floors and Ceilings. The key questions for floors and ceilings in formula
grant programs is whether they are needed and, if based on prior-year information,
what year(s) should be the base. The floors and ceilings in SCHIP were added to
ensure in part that no state’s share of the appropriation went below or above certain
historical levels — to provide some stability and predictability in their federal SCHIP
financing. Table 6 shows that 19 states have had their allotments raised and 15
states have had their allotments lowered because of the statutory floors and ceilings.
The historical floors and the ceiling are tied to states’ FY1999 (and the identical
FY1998) share of the national SCHIP appropriation. While this ensures some
predictability in states’ share of the national SCHIP appropriations, those years were
also when the CPS sample size was smaller than it has been since, predating the
sample expansion. The changes in the estimates since FY1999 may be because of
improvements in the CPS. However, the floors and ceiling limit states’ allotments
to the share of the appropriation in those early years.
Six of the 15 states that have ever had their allotments lowered because of the
ceiling are projected to experience a shortfall in FY2007. These states might argue
that their federal SCHIP financial status would be better if the ceiling were not in
place. Thus, future consideration of floors and ceilings might consider whether they
are useful and, if so, whether a different base year(s) should be incorporated.
Conclusion
SCHIP has been lauded for the health insurance it provides to children and for
the flexibility states have in designing their SCHIP programs. With SCHIP’s final
appropriation slated to occur in this fiscal year (FY2007), the possibility of enacting
new appropriations might also be used by Congress to examine some of the issues
surrounding both the national SCHIP appropriation levels and the allotment formula.
States’ projected shortfalls of federal SCHIP funds is one issue that has received
recent legislative attention. FY2006 was the first year in which several states faced
the prospect of shortfalls, projected initially at $283 million. In response, Congress
appropriated an additional $283 million for SCHIP in FY2006. To eliminate
shortfalls in FY2007 and beyond, additional funds will be needed beyond the annual
$5 billion in appropriations assumed in the current baseline. Original allotments —
both their national level and their distribution among the states — have become
increasingly critical to states in operating their SCHIP programs, determining not
only how much federal money states receive but, for a given level of states’ projected
spending, what size shortfall states are projected to face. As a result, future original
allotments could be set and distributed using information not known or available
when the program was created a decade ago.