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. CRS-2 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. 106113) specified additional amounts to be appropriated to the territories for FY2000FY2007. 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. CRS-3 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 Allotments specified in FY §2104(a) 1998 $4,295,000,000 1999 $4,275,000,000 2000 $4,275,000,000 2001 $4,275,000,000 2002 $3,150,000,000 2003 $3,150,000,000 2004 $3,150,000,000 2005 $4,050,000,000 2006 $4,050,000,000 2007 $5,000,000,000 Total $39,670,000,000 B Subtract Special diabetes grants $60,000,000 $60,000,000 $60,000,000 $60,000,000 $60,000,000 $300,000,000 C D = A-B+C Add For territories Original per allotments to states §2104(c)(4) and territories $4,235,000,000 $32,000,000 $4,247,000,000 $34,200,000 $4,249,200,000 $34,200,000 $4,249,200,000 $25,200,000 $3,115,200,000 $25,200,000 $3,175,200,000 $25,200,000 $3,175,200,000 $32,400,000 $4,082,400,000 $32,400,000 $4,082,400,000 $40,000,000 $5,040,000,000 $280,800,000 $39,650,800,000 E Total spending $121,800,000 $921,800,000 $1,928,800,000 $2,671,600,000 $3,776,200,000 $4,276,400,000 $4,644,700,000 $5,089,500,000 $5,453,700,000 $6,395,300,000 $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. CRS-4 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. CRS-5 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 lowaverage annual wages (health income children without health Number of all lowConstant (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 14 §2104(b)(2)(B). 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 threeyear 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]. CRS-7 (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 FY 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Floor: state’s minimum share of national appropriation (greatest applicable factor applies) Share that equals 90% of last year’s 70% of 1998-1999 $2,000,000 share share X X X X X X X X X X X X X X X X X X X X X X X X X X Ceiling: state’s maximum share 145% of 1998-1999 share X X X X 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]. CRS-8 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 State or territory Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware D.C. Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland 20 A B Number of children State cost (000s) factor 277 0.9701 40 1.0542 424 1.0887 195 0.9129 2533 1.1271 255 1.0621 128 1.1251 39 1.0369 34 1.2432 1036 1.0322 574 1.0433 57 1.1199 100 0.8823 750 1.0594 352 0.9600 141 0.9309 143 0.9258 267 0.9480 355 0.9123 59 0.9284 221 1.0939 C=A*B Product 268.2199 41.6420 461.5930 178.0092 2854.8962 270.8420 144.0124 39.9198 42.2701 1068.8561 598.8366 63.2741 87.7868 794.0428 337.4418 130.7962 131.9224 253.1272 323.4215 54.7733 241.7411 Preadjusted Adjusted proportion proportion 1.4815% 1.4896% 0.2300% 0.2313% 2.5496% 2.5636% 0.9832% 0.9886% 15.7688% 15.8554% 1.4960% 1.4345% 0.7954% 0.7998% 0.2205% 0.2217% 0.2335% 0.2348% 5.9037% 5.9362% 3.3076% 3.3258% 0.3495% 0.3071% 0.4849% 0.4875% 4.3858% 4.2059% 1.8638% 1.8741% 0.7224% 0.7264% 0.7287% 0.7327% 1.3981% 1.4058% 1.7864% 1.7962% 0.3025% 0.3042% 1.3352% 1.3426% Allotment $74,295,313 $11,534,589 $127,858,497 $49,307,483 $790,789,213 $71,544,798 $39,890,581 $11,057,552 $11,708,552 $296,066,768 $165,874,160 $15,314,228 $24,316,412 $209,767,107 $93,469,355 $36,229,776 $36,541,720 $70,114,712 $89,585,836 $15,171,887 $66,960,838 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 PreState 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) State Tennessee Washington Nevada Vermont Connecticut South Carolina Delaware DC Texas Idaho Florida Colorado Indiana Arizona New Hampshire Utah New York Pennsylvania New Mexico Montana Louisiana Arkansas Virginia Kentucky Oklahoma Wyoming Michigan Oregon North Carolina Hawaii Ohio Alabama South Dakota West Virginia Kansas Original allotment $97.5 $79.9 $52.1 $5.8 $39.9 $70.7 $11.1 $11.7 $558.0 $24.3 $296.1 $71.5 $93.5 $127.9 $10.8 $40.5 $340.8 $173.6 $52.0 $15.7 $89.6 $49.3 $94.1 $70.1 $70.8 $6.9 $149.4 $56.7 $136.1 $15.3 $158.0 $74.3 $10.4 $27.5 $36.5 Spending as a percent Projected spending of original allotment $22.9 24% $27.1 34% $31.1 60% $3.5 61% $25.9 65% $53.5 76% $8.4 76% $9.3 80% $452.8 81% $20.3 83% $258.9 87% $63.5 89% $84.0 90% $115.1 90% $10.2 95% $39.0 96% $337.8 99% $177.2 102% $55.4 106% $17.2 110% $98.6 110% $54.3 110% $108.3 115% $81.2 116% $82.4 116% $8.1 117% $175.6 118% $67.1 118% $169.4 124% $19.4 127% $202.5 128% $98.6 133% $13.9 135% $37.1 135% $50.0 137% CRS-11 State Missouri California Wisconsin North Dakota Nebraska Iowa Minnesota Maine Georgia Mississippi Maryland Alaska New Jersey Illinois Massachusetts Rhode Island State total Original allotment $72.1 $790.8 $69.6 $7.7 $21.9 $36.2 $48.6 $15.2 $165.9 $60.5 $67.0 $11.5 $105.2 $209.8 $73.3 $14.0 $4,987.5 Spending as a percent Projected spending of original allotment $98.7 137% $1,103.3 140% $99.1 142% $11.4 148% $33.7 154% $56.7 157% $78.7 162% $25.0 165% $312.1 188% $120.6 199% $151.1 226% $30.2 262% $286.5 272% $578.5 276% $212.5 290% $70.3 503% $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. 99177, 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 lowincome 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 statelevel 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) State Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware DC Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont FY1998 2.04% 0.16% 2.76% 1.13% 20.23% 0.99% 0.83% 0.19% 0.29% 6.40% 2.95% 0.21% 0.38% 2.90% 1.67% 0.77% 0.73% 1.18% 2.41% 0.30% 1.46% 1.01% 2.17% 0.67% 1.33% 1.22% 0.28% 0.35% 0.72% 0.27% 2.09% 1.49% 6.05% 1.88% 0.12% 2.74% 2.03% 0.93% 2.78% 0.25% 1.50% 0.20% 1.57% 13.29% 0.57% 0.08% FY2007 1.49% 0.23% 2.56% 0.99% 15.86% 1.43% 0.80% 0.22% 0.23% 5.94% 3.33% 0.31% 0.49% 4.21% 1.87% 0.73% 0.73% 1.41% 1.80% 0.30% 1.34% 1.47% 3.00% 0.97% 1.21% 1.45% 0.32% 0.44% 1.04% 0.22% 2.11% 1.04% 6.83% 2.73% 0.16% 3.17% 1.42% 1.14% 3.48% 0.28% 1.42% 0.21% 1.95% 11.19% 0.81% 0.12% Difference in # of years FY2007 allotment state hit if based on SCHIP FY1998 share formula floor $27,213,856 2 -$3,400,539 0 $10,042,266 0 $7,256,459 1 $218,272,362 1 -$22,203,557 0 $1,384,881 1 -$1,548,994 2 $2,549,336 2 $22,970,208 1 -$18,690,497 0 -$4,752,691 0 -$5,567,568 0 -$65,100,137 0 -$10,216,774 1 $2,095,626 0 -$346,196 0 -$11,160,403 0 $30,532,763 2 -$428,770 0 $5,801,318 1 -$22,759,137 0 -$41,249,727 0 -$15,086,947 0 $5,643,684 0 -$11,130,951 0 -$1,874,816 1 -$4,343,199 1 -$16,155,449 0 $2,749,509 3 -$812,966 0 $22,305,174 8 -$38,993,803 0 -$42,243,305 0 -$1,786,030 0 -$21,351,771 0 $30,354,937 8 -$10,544,056 0 -$34,875,991 0 -$1,368,082 1 $4,389,991 1 -$269,860 0 -$19,353,984 0 $104,772,413 2 -$11,864,829 0 -$1,579,106 0 # years state hit SCHIP formula ceiling 0 1 0 0 0 3 0 2 0 0 0 6 1 2 0 0 0 0 0 0 0 6 1 5 0 0 0 0 1 0 0 0 0 4 3 0 0 0 0 0 0 0 0 0 0 4 CRS-17 State Virginia Washington West Virginia Wisconsin Wyoming State total FY1998 1.62% 1.10% 0.56% 0.96% 0.18% 100.0% FY2007 1.89% 1.60% 0.55% 1.39% 0.14% 100.0% Difference in # of years FY2007 allotment state hit if based on SCHIP FY1998 share formula floor -$13,412,301 0 -$24,791,372 0 $355,084 1 -$21,588,567 0 $2,162,510 0 $0 19 states # years state hit SCHIP formula ceiling 0 5 0 2 0 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.