Education for the Disadvantaged: Analysis of Issues for the ESEA Title I-A Allocation Formulas
Congressional research reportSep 10, 2009
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Education for the Disadvantaged: Analysis of
Issues for the ESEA Title I-A Allocation
Formulas
(name redacted)
Specialist in Education Policy
September 10, 2009
Congressional Research Service
7-....
www.crs.gov
R40672
CRS Report for Congress
Prepared for Members and Committees of Congress
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Summary
Title I, Part A, of the Elementary and Secondary Education Act (ESEA) authorizes federal aid to
local educational agencies (LEAs) for the education of disadvantaged children. Title I-A grants
provide supplementary educational and related services to low-achieving and other pupils
attending pre-kindergarten through grade 12 schools with relatively high concentrations of pupils
from low-income families. In recent years, they have also become a “vehicle” to which a number
of requirements affecting broad aspects of public K-12 education for all pupils have been attached
as a condition for receiving Title I-A grants. These include requirements for assessments of pupil
achievement; adequate yearly progress (AYP) standards and determinations for schools, LEAs,
and states; consequences for schools and LEAs that fail to make AYP for two consecutive years
or more; plus teacher and paraprofessional qualifications.
The ESEA was initially adopted in 1965, and was most recently reauthorized and amended by the
No Child Left Behind Act of 2001 (NCLB), P.L. 107-110. Currently, although the authorization
for ESEA Title I-A has expired, appropriations have continued to be provided, and the program
continues to be implemented under the policies established by the most recent authorization
statute. The 111th Congress is expected to consider proposals to extend and amend the ESEA.
For the allocation of funds to states and LEAs, Title I-A has four separate formulas: the Basic,
Concentration, Targeted, and Education Finance Incentive Grant (EFIG) formulas. Once these
funds reach LEAs, they are no longer treated separately; they are combined and used without
distinction for the same program purposes. While there are numerous complications and special
features associated with the Title I-A allocation formulas, each has the same underlying structure.
For each formula, a maximum grant is calculated by multiplying a “population factor,” consisting
primarily of estimated numbers of school-age children in poor families, by an “expenditure
factor” based on state average per pupil expenditures for public K-12 education. In some
formulas, additional factors are multiplied by the population and expenditure factors, and/or the
population factor is modified to direct increased funds to LEAs with concentrations of poverty.
Major Title I-A reauthorization issues regarding allocation formulas are likely to include the
following: Should annual variations in the poverty estimates used to calculate Title I-A grants be
reduced through multi-year averaging or other methods? Has the targeting of Title I-A funds on
high poverty LEAs increased since 2001? Should the population weighting factors of the Targeted
and Education Finance Incentive Grant (EFIG) formulas be modified to more equally favor LEAs
with large numbers of school-age children in poor families and LEAs with high poverty rates?
Should the expenditure factors continue to play a major role in the Title I-A formulas? Should
there be some consolidation of the four different allocation formulas? Should the authorization
level for Title I-A continue to be specified for future years, and if so, at what levels? Should the
effort factor in the EFIG formula be modified? Should the equity factor in the EFIG formula be
modified? Should the current provisions for intra-LEA allocation be reconsidered? Should the
remaining special constraints on grants to Puerto Rico, the cap on aggregate population weights
in the Targeted Grant formula, be removed? Should the Temporary Assistance to Needy Families
(TANF) formula factor be eliminated? And finally, should each county portion of New York City
and other multi-county LEAs continue to be treated as separate LEAs under the Title I-A
allocation formulas? This report will not be updated.
Congressional Research Service
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Contents
Introduction ................................................................................................................................1
Description of the ESEA Title I-A Allocation Formulas ...............................................................3
General Overview of the Title I-A Allocation Formulas .........................................................4
Detailed Description of Each of the Title I-A Allocation Formulas.........................................6
Basic Grants....................................................................................................................6
Concentration Grants ......................................................................................................9
Targeted Grants............................................................................................................. 11
Education Finance Incentive Grants (EFIG) .................................................................. 14
ESEA Title I-A School Improvement Grants.................................................................. 18
Suballocation of LEA Grants to Schools........................................................................ 19
Recent Funding Trends for Title I-A.......................................................................................... 21
FY2008......................................................................................................................... 21
FY2009......................................................................................................................... 22
FY2010......................................................................................................................... 22
FY2008 Allocation Patterns ...................................................................................................... 23
ESEA Reauthorization Issues Related to the Title I-A Allocation Formulas................................ 34
Should Annual Variations in the Poverty Estimates Used to Calculate Title I-A Grants
Be Reduced Through Multi-year Averaging or Other Methods?........................................ 34
Annual Shifts in Poverty Estimates ............................................................................... 35
Selected Alternatives to Use of Only the Most Current Poverty Estimates...................... 40
Has the Targeting of Title I-A Funds on High Poverty LEAs Increased Since 2001? ............ 48
Should the Population Weighting Factors of the Targeted and EFIG Formulas Be
Modified to More Equally Favor LEAs With Large Numbers of School-Age
Children in Poor Families and LEAs With High Poverty Rates? ....................................... 53
Should the Expenditure Factors Continue to Play a Major Role in the Title I-A
Formulas? ........................................................................................................................ 61
Rationale for the Current Expenditure Factor................................................................. 63
Alternatives to the Title I-A Expenditure Factor............................................................. 66
Should There Be Some Consolidation of the Four Different Allocation Formulas? .............. 74
Should the Authorization Level for Title I-A Continue to Be Specified for Future
Years, and If So, at What Levels? ..................................................................................... 74
Should the Effort Factor in the Education Finance Incentive Grant Formula Be
Modified? ........................................................................................................................ 77
Should the Equity Factor in the Education Finance Incentive Grant Formula Be
Modified? ........................................................................................................................ 79
Should the Current Provisions for Intra-LEA Allocation Be Reconsidered? ......................... 80
Title I-A Allocation Formula Issues Affecting a Limited Number of States or LEAs .................. 82
Should the Last Remaining Special Constraints on Grants to Puerto Rico Be
Removed?........................................................................................................................ 82
Should the Temporary Assistance to Needy Families (TANF) Population Factor Be
Eliminated?...................................................................................................................... 83
Should Each County Portion of New York City and Other Multi-County LEAs
Continue to Be Treated as Separate LEAs Under the Title I-A Allocation Formulas? ........ 83
Impact on Total Title I-A Grants to the New York City LEA .......................................... 85
Impact on the Allocation of Title I-A Funds Within the New York City LEA ................. 86
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Figures
Figure 1. Share of ESEA Title I-A Funds Allocated to LEAs by Poverty Rate Quintile,
FY2008.................................................................................................................................. 51
Tables
Table 1. Brief Summary of ESEA Title I-A Allocation Formula Characteristics ...........................5
Table 2. Weights Applied to Counts of Population Factor Children in the Calculation of
ESEA Title I-A Targeted Grants.............................................................................................. 12
Table 3. Weights Applied to Counts of Population Factor Children in the Calculation of
LEA Grants Under the ESEA Title I-A Education Finance Incentive Grant Formula ............... 15
Table 4. FY2009-FY2010 Appropriations for ESEA Title I, Part A ............................................ 23
Table 5. ESEA Title I-A Grant Amount Per Child Counted in the Allocation Formulas,
FY2008.................................................................................................................................. 24
Table 6. State Shares of Funds Allocated Under Each of the ESEA Title I-A Formulas,
FY2008.................................................................................................................................. 27
Table 7. ESEA Title I-A Grant Amount Per Child Counted in the Allocation Formulas for
LEAs in Selected Categories, FY2008.................................................................................... 30
Table 8. Distribution of School-Age Population, Title I-A Formula Children, and Title I-A
Grants Among LEAs by Locale Type ..................................................................................... 33
Table 9. State Estimated Number of School-Age Children in Poor Families, Income Years
2003-2007.............................................................................................................................. 36
Table 10. Estimated Annual Changes in Estimated Number of School-Age Children in
Poor Families, Income Years 2003-2007, Selected States........................................................ 39
Table 11. State Total Grants under Title I-A, ESEA: Actual Grants for FY2007 and
FY2008 Compared to Estimated Grants Based on the Average of IY2004 and IY2005
Estimates of School-Age Children in Poor Families ............................................................... 42
Table 12. ESEA Title I, Part A, Actual Grants for FY2007 and FY2008 Compared to
Estimated FY2008 Grants Using the Greater of: (i) Poverty Estimates for Income Year
2005 (FY2008) or (ii) the Average of Poverty Estimates for Income Years 2004
(FY2007) and 2005 (FY2008) for Each LEA.......................................................................... 45
Table 13. Share of ESEA Title I-A Funds Allocated to LEAs by LEA Poverty Rate
Quintile, FY2008 ................................................................................................................... 50
Table 14. Title I-A: Illustration of the Allocation of Funds to the Nation’s 15 Largest
LEAs Compared to Other LEAs in the Same State ................................................................ 54
Table 15. Weighted Formula Child Counts for FY2008.............................................................. 57
Table 16. Illustration of the Effect of the Title I-A Formulas on LEAs with High Numbers
but Low Percentages of Formula Children Comparing LEAs in the Same State ...................... 59
Table 17. ESEA Title I-A State Expenditure Factors for FY2008 ............................................... 62
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Table 18. Actual State Total Allocations under Title I, Part A of the Elementary and
Secondary Education Act (ESEA) for FY2008 under Current Law and Estimated
FY2008 Grants Under an Alternative Formula Under Which the National Average
Expenditure Factor Is Used for All States ............................................................................... 67
Table 19. Comparison of State Expenditure Factor and the
Comparable Wage Index (CWI) ............................................................................................. 69
Table 20. Comparison of State Expenditure Factor and Education Expenditure Effort
Index Based on Total K-12 Education Expenditures Relative to Total Taxable
Resources (TTR).................................................................................................................... 72
Table 21. Authorizations and Appropriations for ESEA Title I-A Grants to LEAs,
FY2001-FY2009.................................................................................................................... 76
Table 22. Individual and Aggregate Measures of State Effort ..................................................... 78
Table 23. Total ESEA Title I-A Grants to New York City for FY2008 If Treated as
Five LEAs vs. One LEA ........................................................................................................ 85
Table 24. Data Regarding Allocation of Title I-A Funds to Public Schools in New York
City in the 2008-2009 School Year ......................................................................................... 88
Contacts
Author Contact Information ...................................................................................................... 89
Acknowledgments .................................................................................................................... 89
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Introduction
Title I, Part A, of the Elementary and Secondary Education Act (ESEA) authorizes federal aid to
local educational agencies (LEAs) for the education of disadvantaged children. Title I-A grants
provide supplementary educational and related services to low-achieving and other pupils
attending pre-kindergarten through grade 12 schools with relatively high concentrations of pupils
from low-income families. In recent years, they have also become a “vehicle” to which a number
of requirements affecting broad aspects of public K-12 education for all pupils have been attached
as a condition for receiving Title I-A grants. These include requirements for assessments of pupil
achievement; adequate yearly progress (AYP) standards and determinations for schools, LEAs,
and states; consequences for schools and LEAs that fail to make AYP for two consecutive years
or more; plus teacher and paraprofessional qualifications.
Title I-A is the largest federal elementary and secondary education assistance program, with
services provided to (1) more than 90% of all LEAs; (2) approximately 52,000 (54% of all)
public schools; and (3) approximately 16.5 million (34% of all) pupils, including approximately
188,000 pupils attending private schools. Three-fourths of all pupils served are in prekindergarten through grade 6, while only 8% of pupils served are in grades 10-12.
The ESEA was initially adopted in 1965, and was most recently reauthorized and amended by the
No Child Left Behind Act of 2001 (NCLB), P.L. 107-110. NCLB authorized Title I-A through
FY2007, and an automatic extension, through FY2008 was provided under the General Education
Provisions Act (Title IV of P.L. 90-247, as amended). Currently, although the authorization for
ESEA Title I-A has expired, appropriations have continued to be provided, and the program
continues to be implemented under the policies established by the most recent authorization
statute. The 111th Congress is expected to consider proposals to extend and amend the ESEA.
The focus of this report is on the formulas used to allocate Title I-A funds to states, LEAs, and
schools. These formulas are used to allocate funds not only under the largest federal K-12
education program, but also several other ESEA and non-ESEA programs under which grants are
made in proportion to ESEA Title I-A allocations. This report will not be updated.
Another CRS report (CRS Report RL33731, Education for the Disadvantaged: Reauthorization
Issues for ESEA Title I-A Under the No Child Left Behind Act, by (name redacted) and (name
redacted)) discusses issues related to the accountability and other policies of ESEA Title I-A.
Those interested in a more concise description of the ESEA Title I-A allocation formulas and
review of reauthorization issues related to them than found in this report should refer to the final
section of that report (RL33731).
Additional CRS reports provide more detailed discussions and analyses of selected major aspects
of the Title I-A program, including pupil assessments,1 accountability, 2 and qualifications for
teachers and paraprofessionals.3 Also, see CRS Report RL34721, Elementary and Secondary
1
See CRS Report RL31407, Educational Testing: Implementation of ESEA Title I-A Requirements Under the No Child
Left Behind Act, by (name redacted).
2
See CRS Report RL32495, Adequate Yearly Progress (AYP): Implementation of the No Child Left Behind Act, by
(name redacted); CRS Report RL33032, Adequate Yearly Progress (AYP): Growth Models Under the No Child Left
Behind Act, by (name redacted); and CRS Report RL31329, Supplemental Educational Services for Children from
Low-Income Families Under ESEA Title I-A, by (name redacted).
3
See CRS Report RL33333, A Highly Qualified Teacher in Every Classroom: Implementation of the No Child Left
(continued...)
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Education Act: An Analytical Review of the Allocation Formulas, for a description and analysis of
all of the ESEA’s allocation formulas, as well as a discussion of general allocation formula
concepts and procedures.
This report provides: (a) descriptions of the ESEA Title I-A allocation formulas; (b) a review of
recent funding trends for Title I-A; and (c) analyses of major issues related to the Title I-A
allocation formulas, divided into general categories of broad issues directly affecting all regions
of the nation and issues that directly affect only a limited number of states or local educational
agencies.
In summary, major Title I-A reauthorization issues regarding allocation formulas are likely to
include the following:
Should annual variations in the poverty estimates used to calculate Title I-A grants be reduced
through multi-year averaging or other methods?
•
Annual variations in estimates of school-age children in poor families have been
exceptionally large for a number of states. Several options are available to reduce
the more extreme variations, if desired.
Has the targeting of Title I-A funds on high poverty LEAs increased since 2001?
•
Targeting of Title I-A funds on the highest poverty LEAs has increased since
adoption of the NCLB, although shifts have been gradual and relatively marginal.
Should the population weighting factors of the Targeted and Education Finance Incentive Grant
(EFIG) formulas be modified to more equally favor LEAs with large numbers of school-age
children in poor families and LEAs with high poverty rates?
•
In some respects, the formula population weighting factors of the Targeted and
EFIG formulas favor LEAs with large numbers of formula children over those
with high school-age child poverty rates.
Should the expenditure factor continue to play a major role in the Title I-A formulas?
•
The expenditure factor has a major impact on the distribution of all Title I-A
funds, and the rationale for using this factor may be questioned. At best, it is a
crude and indirect measure of variations in the costs of providing public K-12
education.
Should there be some consolidation of the four different allocation formulas?
•
The allocation of portions of each year’s Title I-A appropriation under four
different allocation formulas is a result of legislative compromise, not design.
Should the authorization level for Title I-A continue to be specified for future years, and if so, at
what levels?
•
An authorized appropriation level was specified in the ESEA only through
FY2007.
(...continued)
Behind Act and Reauthorization Issues for the 111th Congress, and CRS Report RS22545, Paraprofessional Quality
and the No Child Left Behind Act of 2001, both by (name redacted).
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Should the effort factor in the EFIG formula be modified?
•
The current effort factor has very limited impact and favors states where schoolage children are a relatively small share of the total population.
Should the equity factor in the EFIG formula be modified?
•
The current equity factor might be broadened to consider additional categories of
“high cost” pupils.
Should the current provisions for intra-LEA allocation be reconsidered?
•
The participation of middle and, especially, high schools in Title I-A programs is
very low, and might be increased through modification of the requirements for
allocation of funds within LEAs.
Issues Affecting a Limited Number of States or LEAs:
Should the remaining special constraints on grants to Puerto Rico, the cap on aggregate
population weights in the Targeted Grant formula, be removed?
•
Title I-A grants to Puerto Rico would be substantially higher if remaining special
constraints were removed.
Should the Temporary Assistance to Needy Families (TANF) formula factor be eliminated?
•
This formula population factor is of little significance, and may remain primarily
for historic and symbolic reasons.
Should each county portion of New York City and other multi-county LEAs continue to be treated
as separate LEAs under the Title I-A allocation formulas?
•
This provision leads to substantially different treatment of Title I-A schools in
different counties within New York City, and has mixed impact on total Title I-A
grants to the City overall.
Finally, a general introductory note regarding funding levels and allocations: Most references to
appropriation levels, and all discussions and analyses of allocation patterns, in this report refer to
those for FY2008, the most recent year for which actual allocations were available at the time this
report was prepared. Therefore, there will be only marginal reference to FY2009 appropriations
or allocations for Title I-A, whether provided under the American Recovery and Reinvestment
Act (P.L. 111-5) or regular FY2009 omnibus appropriations legislation (P.L. 111-8).
Description of the ESEA Title I-A Allocation
Formulas
For the allocation of funds to states and LEAs, ESEA Title I-A has four separate formulas: the
Basic, Concentration, Targeted, and Education Finance Incentive Grant (EFIG) formulas. Once
these funds reach LEAs, they are no longer treated separately; they are combined and used
without distinction for the same program purposes.
A primary rationale for using four different formulas to allocate a share of the funds for a single
program is that the formulas have distinct allocation patterns, providing varying shares of
allocated funds to different types of localities (e.g., LEAs with high poverty rates, or states with
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
comparatively equal levels of spending per pupil among their LEAs), as is discussed later in this
report. In addition, some of the formulas contain elements—such as the equity and effort factors
in the EFIG formula—that are deemed to have important incentive effects or to be significant
symbolically in addition to their impact on allocation patterns. There is also a historical
explanation: the Targeted and EFIG formulas, in particular, were initially proposed as
replacements for the Basic plus Concentration Grant formulas; that is, each of the Targeted and
EFIG formulas was originally intended to be the Title I-A formula. But in subsequent
deliberations, these formulas were ultimately authorized to supplement, but not replace, the Basic
and Concentration Grant formulas, and implicitly to complement each other.
The discussion below describes the characteristics of the Title I-A allocation formulas as these
have been amended by NCLB. The description immediately below is similar to that in a report on
all of the ESEA program allocation formulas, CRS Report RL34721, Elementary and Secondary
Education Act: An Analytical Review of the Allocation Formulas, by (name redacted). The
formulas are described in three different formats:
•
•
•
First, the general characteristics of all four formulas are introduced in very brief,
narrative form.
Second, selected characteristics of the four formulas are summarized in tabular
format in Table 1.
Third, each of the four formulas is described individually, and in greater detail,
including a mathematical expression of each formula.
General Overview of the Title I-A Allocation Formulas
While numerous complications and special features are associated with the Title I-A allocation
formulas, each of them has the same underlying structure. For each formula, a maximum grant is
calculated by multiplying a “population factor,” consisting primarily of estimated numbers of
school-age children in poor families, by an “expenditure factor” based on state average per pupil
expenditures for public K-12 education. In some formulas, additional factors are multiplied by the
population and expenditure factors. Then these maximum grants are reduced to equal the level of
available appropriations for each formula, taking into account a variety of state and LEA
minimum grant or “hold harmless” provisions. Only LEAs meeting minimum numbers and/or
percentages of children counted in the population factor may receive grants.
Under Title I-A, funds are allocated to LEAs via state educational agencies (SEAs). Annual
appropriations legislation specifies portions of each year’s appropriation to be allocated under
four different formulas; once funds reach LEAs, the amounts allocated under the four formulas
are combined and used jointly. Under three of the formulas—Basic, Concentration, and Targeted
Grants—funds are calculated initially at the LEA level, and state total grants are the total of
allocations for LEAs in the state, adjusted to apply state minimum grant provisions. Under the
fourth formula, Education Finance Incentive Grants, allocations are first calculated for each state
overall, with state totals subsequently suballocated by LEA using a different formula.
The discussion below describes the characteristics of the Title I-A allocation formulas as these
have been amended by NCLB. These characteristics are summarized in Table 1.
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Table 1. Brief Summary of ESEA Title I-A Allocation Formula Characteristics
Formula
Characteristic
Basic Grants
Concentration Grants
Targeted Grants
Education Finance Incentive
Grants
Population factor
(also referred to as
formula children)
Children aged 5-17: (a) in poor families;
(b) in institutions for neglected or
delinquent children or in foster homes;
and (c) in families receiving Temporary
Assistance for Needy Families (TANF)
payments above the poverty income
level for a family of four
Same as Basic Grants
Same as Basic Grants
Same as Basic Grants
Population factor
eligibility threshold
for LEAs
10 or more formula children and a
school-age child poverty rate of more
than 2%
More than 6,500 formula children
or a school-age child poverty rate
of more than 15%
10 or more formula children and
a school-age child poverty rate of
5% or more
10 or more formula children and
a school-age child poverty rate of
5% or more
Weighting of
population factor
None
None
At all stages of the allocation
process, poor and other children
counted in the formula are
assigned weights on the basis of
each LEA’s school-age child
poverty rate and number of poor
school-age children
For allocation of funds within
states only, poor and other
children counted in the formula
are assigned weights on the basis
of each LEA’s school-age child
poverty rate and number of poor
school-age children
Expenditure factor
State average expenditures per pupil for
public K-12 education, subject to a
minimum of 80% and maximum of 120%
of the national average, further
multiplied by 0.40
Same as Basic Grants
Same as Basic Grants
Same as Basic Grants, except that
the minimum is 85% and the
maximum is 115% of the national
average
Minimum state grant
Up to 0.25% of total state grants, subject
to a series of caps
Same as Basic Grants
Up to 0.35% of total state grants,
subject to a series of caps
Same as Targeted Grants
LEA hold harmless
85%-95% of the previous year grant,
depending on the LEA’s school-age child
poverty rate, applicable only to LEAs
meeting the formula’s eligibility
thresholds
Same as Basic Grants except that
LEAs are eligible for the hold
harmless for up to four years
after they no longer meet the
eligibility threshold
Same as Basic Grants
Same as Basic Grants
Stages in the grant
calculation process
Grants are calculated at the LEA level,
subject to state minimum provisions
Same as Basic Grants
Same as Basic Grants
Grants are first calculated for
states overall, then state total
grants are allocated to LEAs in a
separate process
Additional formula
factors
None
None
None
State effort and equity factors are
applied in the calculation of state
total grants
Source: Table prepared by CRS.
CRS-5
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
In the discussion below, each of the four ESEA Title I-A allocation formulas is discussed
separately.
Detailed Description of Each of the Title I-A Allocation Formulas
Basic Grants
Basic Grants are the original Title I-A formula, authorized and implemented each year since
FY1966. It is also the formula under which the largest proportion of funds is allocated (47% of
FY2008 appropriations), and under which the largest proportion of LEAs participate
(approximately 94% in FY2008), largely due to its low LEA eligibility threshold (see below).
However, since all post-FY2001 increases in Title I-A appropriations have been provided for the
Targeted and Education Finance Incentive Grant formulas (see below), the proportion of Title I-A
funds allocated under the Basic Grant formula has been declining steadily since FY2001, when it
was 84% of FY2001 appropriations.
Compared to some of the other Title I-A formulas, the Basic Grant formula is relatively
straightforward. Grants are based on each LEA’s share, compared to the national total, of a
population factor multiplied by an expenditure factor, subject to available appropriations, an LEA
minimum or “hold harmless,” and a state minimum. These formula factors are described below,
followed by a mathematical expression of the formula.
Population factor—Children aged 5-17: (a) in poor families, according to the latest available
estimates for LEAs from the Census Bureau’s Small Area Income and Poverty Estimates (SAIPE)
program (these constitute approximately 96% of all formula children for FY2008); (b) in
institutions for neglected or delinquent children or in foster homes (approximately 3.9% of all
formula children for FY2008)4; and (c) in families receiving Temporary Assistance for Needy
Families (TANF) payments above the poverty income level for a family of four (less than 0.1% of
all formula children for FY2008). Each element of the population factor is updated annually.
Eligibility threshold—In order for an LEA to be eligible for a Basic Grant, the number of
children counted in the population factor must constitute 10 or more such children and more than
2% of the total school-age population in the LEA.
Expenditure factor—State average per pupil expenditure for public K-12 education, subject to a
minimum of 80% and a maximum of 120% of the national average, further multiplied by 0.40.
The expenditure factor is the same for all LEAs in the same state.
LEA minimum grant or “hold harmless” level—If sufficient funds are appropriated, each LEA
is to receive a minimum of 85%, 90%, or 95% of its previous year grant, depending on the LEA’s
school-age child poverty rate, assuming that the LEA continues to meet the Basic Grant formula’s
eligibility thresholds. 5
4
The portion of funds allocated to states under the Basic Grant and the other three Title I-A allocation formulas that is
based on delinquent youth in local programs is set aside and separately allocated to LEAs providing services to such
youth. SEAs are to allocate these funds to LEAs with concentrations of youth in local correctional facilities. SEAs may
allocate these funds through a state-developed formula or on a discretionary basis.
5
The hold harmless rate is 85% of the previous year grant if the LEA’s school-age child poverty rate (population factor
(continued...)
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Minimum state grant—Each state is to receive a minimum of up to 0.25% of total Basic Grant
appropriations if total Basic Grant funding is equal to or less than the FY2001 level (as has been
the case each year since FY2001 thus far), and up to 0.35% of total Basic Grant appropriations in
excess of the FY2001 amount, if any. A state may not, as a result of the state minimum provision,
receive more than the average of: (1) 0.25% of the total FY2001 amount for state grants plus
0.35% of any amount above the FY2001 level, and (2) 150% of the national average grant per
formula child, multiplied by the number of formula children in the state.
Ratable reduction—After maximum grants are calculated, if appropriations are insufficient to
pay the maximum amounts (as has been the case every year beginning with FY1967), these
amounts are reduced by the same percentage for all LEAs, subject to LEA hold harmless and
state minimum provisions, until they equal the aggregate level of appropriations.
Fiscal requirements—There are three Title I-A fiscal accountability requirements, which are
applicable to total LEA grants under all four formulas: (1) maintenance of effort: recipient LEAs
must provide, from state and local sources, a level of funding (either aggregate or per pupil) in the
preceding year that is at least 90% as high as in the second preceding year; (2) Title I-A funds
must be used so as to supplement, and not supplant, state and local funds that would otherwise be
available for the education of disadvantaged pupils in Title I-A participating schools; (3)
comparability: services provided with state and local funds in schools participating in Title I-A
must be comparable to those in non-Title I-A schools of the same LEA.6
Treatment of Puerto Rico, Outlying Areas, and the Bureau of Indian Affairs—With one
possible exception,7 Puerto Rico is treated the same as a state under the Basic Grant formula.
Grants to schools operated or supported by the Bureau of Indian Affairs, the Outlying Areas of
Guam, American Samoa, the Virgin Islands, and the Commonwealth of the Northern Mariana
Islands, as well as a competitive grant to the Outlying Areas plus certain Freely Associated States8
are provided via reservation of 1% of total Title I-A appropriations.
Further adjustments by SEAs of LEA grants as calculated by the U.S. Department of
Education (ED)—Among ESEA programs, a distinctive aspect of Title I-A is that after
calculation of LEA grants by ED, applying the methods discussed herein, SEAs make a number
of adjustments before determining the final amounts that LEAs actually receive. These
adjustments are made to the total of Title I-A grants to LEAs under all four formulas combined.
These adjustments include (1) reservation of 4% of state total allocations to be used for school
improvement grants;9 (2) reservation of 1% of state total allocations under all formulas for ESEA
(...continued)
divided by total school-age population) is less than 15%, 90% if the school-age child poverty rate is between 15% and
30%, and 95% if the school-age child poverty rate is greater than 30%.
6
If all of an LEA’s schools participate in Title I-A, then services funded from state and local revenues must be
“substantially comparable” in each school of the LEA.
7
Through FY2007, the minimum expenditure factor applicable to Puerto Rico was lower than that for any state. The
NCLB provided for the elimination of this special provision in stages, although scheduled increases in the Puerto Rico
expenditure factor are not to be implemented if doing so would result in a decrease in the grant to any state. The final
step in this process was not implemented as scheduled in FY2007; however, it was implemented in FY2008.
8
The Freely Associated States include Palau, the Federated States of Micronesia, and the Republic of the Marshall
Islands. As of March 2009, Palau is the only Freely Associated State that is eligible for this grant competition.
9
In the process of making this deduction, SEAs may not reduce any LEA’s net grant (i.e., its final grant, after making
deductions for school improvement and state administration, plus any other adjustments) below its previous year level.
(continued...)
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Title I, Part A, plus Title I, Parts C and D (discussed below), or $400,000, whichever is greater,
for state administration;10 (3) optional reservation of up to 5% of any statewide increase in total
Part A grants over the previous year for academic achievement awards to participating schools
that significantly reduce achievement gaps between disadvantaged and other pupil groups and/or
exceed adequate yearly progress standards for two consecutive years or more; (4) adjustment of
LEA grants to provide funds to eligible charter schools or to account for recent LEA boundary
changes; and (5) optional use by states of alternative methods to reallocate all of the grants as
calculated by ED among the state’s small LEAs (defined as those serving an area with a total
population of 20,000 or fewer persons). 11
Basic Grant Allocation Formula—
Step 1: Grant 1 = ( PF * EF ) or L_HH, whichever is greater
In Step 1, the population factor is multiplied by the expenditure factor for each eligible LEA. If
this is less than the LEA’s hold harmless level, the latter amount is used.
Step 2: Grant 2 = ( ( Grant 1 / ∑ Grant 1 ) * APP ) or L_HH, whichever is greater
In Step 2, the amount for each LEA in Step 1 is divided by the total of these amounts for all
eligible LEAs in the nation, then multiplied by the available appropriation. Again, if this is less
than the LEA’s hold harmless level, the latter amount is used.
Step 3: Grant 3 = (Grant 2 * S_MIN_ADJ * L_HH_ADJ) or L_HH, whichever is greater
In Step 3, the amount for each LEA in Step 2 is adjusted through application of the state
minimum grant provision and by a factor to account for the aggregate costs of raising affected
LEAs to their hold harmless level, given a fixed total appropriation level. The state minimum
grant adjustment is upward in the smallest states, where total grants are increased through
application of the minimum, and downward in all other states, where funds are reduced in order
to pay the costs of applying the minimum. The LEA hold harmless adjustment is downward for
all LEAs except those at their hold harmless level. Again at this stage, if this is less than the
LEA’s hold harmless level, the latter amount is the LEA’s grant.
Step 4: Final Grant = Grant 3 * SCH_IMP_ADJ * S_ADMIN_ADJ * AWD_ADJ * OTR_ADJ
In the final step of calculating LEA grants under all Title I-A allocation formulas, LEA grants as
calculated in Step 3 are further adjusted for the school improvement and state administration
(...continued)
According to a recent survey by the Government Accountability Office, this limitation has prevented several states
from being able to reserve the full 4% in recent years (see “No Child Left Behind Act: Education Actions Could
Improve the Targeting of School Improvement Funds to Schools Most in Need of Assistance,” GAO-08-380, February
2008). In addition, as is discussed later in this report, the school improvement reservation may be supplemented by
additional funds separately appropriated for this purpose.
10
If total appropriations for ESEA Title I, Parts A, C, and D exceed $14 billion, then state administration reservations
are capped at the level that would pertain if the total appropriations for these programs were $14 billion. This limit was
applicable for the first time in FY2008.
11
As of March 2009, this statutory authority is exercised by 7 states: Alaska, Iowa, Kansas, Maine, Nebraska, North
Dakota, and Oklahoma.
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reservations, possible state reservations for achievement awards, and other possible adjustments
(such as for grants to charter schools) discussed above.
Where:
PF = Population factor
EF = Expenditure factor
L_HH = LEA minimum or “hold harmless” level
APP = Appropriation
S_MIN_ADJ = State minimum adjustment (proportional increase (in small states) or decrease (in
other states) to apply the statewide minimum grant)
L_HH_ADJ = LEA minimum or “hold harmless” adjustment (proportional decrease, in LEAs not
benefitting from the LEA “hold harmless,” to apply the LEA minimum grant)
SCH_IMP_ADJ = Reservation by SEA for school improvement grants
S_ADMIN_ADJ = Reservation by SEA for state administration
AWD_ADJ = Possible reservation by SEA for achievement awards
OTR_ADJ = Other possible adjustments by the SEA
∑ = Sum (for all eligible LEAs in the nation)
Concentration Grants
The Concentration Grant formula is essentially the same as that for Basic Grants, with one major
exception—it has a much higher LEA eligibility threshold. There are also differences regarding
the LEA hold harmless and state minimum grant provisions. While the Title I-A statute has
included Concentration Grant formulas (with varying provisions and sometimes under different
names) since 1970, the current version dates from 1988 (P.L. 100-297). A relatively small (10%
of FY2008 appropriations) and declining (from 14% in FY2001) proportion of Title I-A
appropriations is allocated under the Concentration Grant formula. Approximately 50% of LEAs
receive Concentration Grants (FY2008).
As with Basic Grants, Concentration Grants are based on each eligible LEA’s share, compared to
the national total, of a population factor multiplied by an expenditure factor, subject to available
appropriations, an LEA minimum or “hold harmless,” and a state minimum. These formula
factors are described below, followed by a mathematical expression of the formula.
Population factor—Same as Basic Grants (see above).
Eligibility threshold—In order for an LEA to be eligible for a Concentration Grant, the number
of children counted in the population factor must exceed either 6,500 such children or 15% of the
total school-age population in the LEA.
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Expenditure factor—Same as Basic Grants (see above).
LEA minimum grant or “hold harmless” level—The hold harmless rates for Concentration
Grants are the same as those for Basic Grants. However, unlike Basic Grants and all of the other
Title I-A formulas, the hold harmless applies to all LEAs that received grants for the previous
year, even if they do not currently meet one of the Concentration Grant formula’s eligibility
thresholds, unless they fail to meet one of the thresholds for 4 consecutive years. That is, an LEA
that is eligible to receive a Concentration Grant in one year can continue to receive a
Concentration Grant for three succeeding years, even if it does not meet either of the eligibility
thresholds in those succeeding years.12
Minimum state grant—The Concentration Grant state minimum is a modified version of the
Basic Grant minimum. Each state is to receive a minimum of up to 0.25% of total Concentration
Grant appropriations if total Concentration Grant funding is equal to or less than the FY2001
level (as has been the case each year since FY2001 thus far), and up to 0.35% of total
Concentration Grant appropriations in excess of the FY2001 amount, if any. A state may not, as a
result of the state minimum provision, receive more than the average of: (1) 0.25% of the total
FY2001 amount for state grants plus 0.35% of the amount above this, and (2) the greater of (i)
150% of the national average grant per formula child, multiplied by the number of formula
children in the state, or (ii) $340,000.
Ratable reduction—Same as Basic Grants (see above).
Fiscal requirements—Same as Basic Grants (see above).
Treatment of Puerto Rico, Outlying Areas, and the Bureau of Indian Affairs—Same as Basic
Grants (see above).
Further adjustments by SEAs of LEA grants as calculated by ED—With one exception, these
are the same as for Basic Grants. The exception is that in states where the state total number of
children counted in the population factor constituted less than 0.25% of the national total of such
children as of the date of enactment of the NCLB,13 SEAs may allocate Concentration Grants
among all LEAs with a number or percentage of children counted in the population factor that is
greater than the state average for that year (not just LEAs meeting the 6,500 or 15% thresholds).
Concentration Grant Allocation Formula—The mathematical expression of the Concentration
Grant formula is the same as that for Basic Grants (above), with one exception. As discussed
immediately above, in states where the number of children counted in the population factor
constituted less than 0.25% of the national total of such children as of the date of enactment of the
NCLB, the state total is to be allocated on the basis of the population factor among the LEAs that
are to receive grants. These LEAs may include, at state discretion, either those LEAs in the state
meeting the Concentration Grant eligibility criteria described above, or all LEAs in the state with
a number or percentage of children counted in the population factor that is greater than the state
average. In either case, for states where the number of children counted in the population factor
12
In this scenario, the Concentration Grant for each year would be equal to 85% of the previous year grant.
This group of states will be very similar to, but not necessarily the same as, the group of states currently receiving
state minimum Concentration Grants.
13
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constituted less than 0.25% of the national total of such children as of the date of enactment of
the NCLB only (after state totals have been determined):
LEA Grant = ( PF / ∑ PF * ALL ) or L_HH, whichever is greater
Where:
PF = Population factor
ALL = State total allocation
L_HH = LEA minimum or “hold harmless” level
∑ = Sum (for all eligible LEAs in the state)
Targeted Grants
Targeted Grants were initially authorized in 1994,14 but no funds were appropriated for them until
FY2002, after the formula was slightly modified by the NCLB. Beginning in FY2002, all
increases in Title I-A appropriations have been allocated as either Targeted or Education Finance
Incentive Grants (below). Thus, Targeted Grants constitute a substantial (21% of FY2008
appropriations) and growing portion of total Title I-A grants. They are allocated among a large
majority of LEAs (87% in FY2008).
The allocation formula for Targeted Grants is essentially the same as that for Basic Grants, except
for significant differences related to how children in the population factor are counted. For
Targeted Grants, the poor and other children counted in the formula are assigned weights on the
basis of each LEA’s school-age child poverty rate and number of school-age children in poor
families. As a result, LEAs receive higher grants per child counted in the formula, the higher their
poverty rate and/or number. There is also a somewhat higher LEA eligibility threshold for
Targeted Grants than for Basic Grants. Aside from these two differences, Targeted Grants are, like
Basic Grants, based on each eligible LEA’s share, compared to the national total, of a population
factor multiplied by an expenditure factor, subject to available appropriations, an LEA minimum
or “hold harmless,” and a state minimum. These formula factors are described below, followed by
a mathematical expression of the formula.
Population factor—The children counted for calculating Targeted Grants are the same as for
Basic Grants (see above). However, for Targeted Grants, LEA-specific weights are applied to
these child counts to produce a weighted child count that is used in the formula. Children counted
in the formula are assigned weights on the basis of each LEA’s number of school-age children in
poor families and on the basis of each LEA’s school-age child poverty rate. As a result, an LEA
would receive higher grants per child counted in the formula, the higher its poverty rate or
number. The weighting factors are applied in the same manner nationwide; formula children in
LEAs with the highest poverty rates have a weight of up to four, and those in LEAs with the
highest numbers of such children have a weight of up to three, compared to a weight of one for
formula children in LEAs with the lowest poverty rate and number of such children (see Table 2,
14
The Improving America’s Schools Act (IASA), P.L. 103-382.
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
below). The higher of its two weighted child counts (on the basis of numbers and percentages) is
actually used in the formula for calculating grants for each LEA.
Table 2. Weights Applied to Counts of Population Factor Children in the Calculation
of ESEA Title I-A Targeted Grants
A. Weights Based on LEA Numbers of Children in the Population Factor
Population Factor Count Range
Weight Applied to Population Factor Children in
This Range
0-691
1.0
692-2,262
1.5
2,263-7,851
2.0
7,852-35,514
2.5
35,515 or more
3.0
B. Weights Based on LEA Population Factor Children as a Percentage of Total School-Age Population
Population Factor Percentage Range
Weight Applied to Population Factor Children in
This Range
Less than or equal to 15.58%
1.0
Above 15.58% but less than or equal to 22.11%
1.75
Above 22.11% but less than or equal to 30.16%
2.5
Above 30.16% but less than or equal to 38.24%
3.25
Above 38.24%
4.0
Source: Table prepared by CRS.
There are five ranges associated with each of the number and percentage weighting scales. These
steps, or quintiles, were based on the actual distribution of Title I-A population factor children
among the nation’s LEAs, according to the latest available data in 2001 (at the time that the
NCLB was being considered). Based upon those data, one-fifth of the national total of population
factor children were in LEAs in each of the five numbers ranges and, separately, each of the five
percentage ranges.
The Targeted Grant population factor weights are applied in a stepwise manner, rather than the
highest relevant weight being applied to all population factor children in the LEA, and the greater
of the two weighted child counts for each LEA is the number actually used to calculate the
Targeted Grant. For example, assume an LEA has 2,000 population factor children, the total
school-age population is 10,000, and therefore the population factor percentage is 20%. The
population factor figure used to calculate Targeted Grants would be determined as follows:
Numbers Scale:
Step 1: 691 * 1.0 = 691
The first 691 population factor children are weighted at 1.0.
Step 2: (2,000 - 691) = 1,309 * 1.5 = 1,963.5
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For an LEA with a total number of population factor children falling within the second step of the
numbers scale, the number of population factor children above 691 (the maximum for the first
step) is weighted at 1.5.
Total (Numbers Scale) = 2,654.5
The weighted population factor counts from Steps 1 and 2 are combined.
Percentage Scale:
Step 1: 15.58% * 10,000 = 1,558 * 1.0 = 1,558
A number of population factor children constituting up to 15.58% of the LEA’s total school-age
population is weighted at 1.0.
Step 2: (20% - 15.58%) = 4.42% * 10,000 = 442 * 1.75 = 773.5
For an LEA with a population factor percentage falling within the second step of the percentage
scale, the number of population factor children above 15.58% of the LEA’s total school-age
population (the maximum for the first step) is weighted at 1.75.
Total (Percentage Scale) = 2,331.5
The weighted population factor counts from Steps 1 and 2 are combined.
Since the numbers scale weighted count of 2,654.5 exceeds the percentage scale weighted count
of 2,331.5, the numbers scale count would be used as the population factor for this LEA in the
calculation of Targeted Grants.
Eligibility threshold—In order for an LEA to be eligible for a Targeted Grant, the number of
children counted in the population factor (with no weights applied) must constitute 10 or more
such children and 5% or more of the total school-age population.
Expenditure factor—Same as Basic Grants (see above).
LEA minimum grant or “hold harmless” level—Same as Basic Grants (see above).
Minimum state grant—Each state is to receive a minimum of up to 0.35% of all Targeted Grant
appropriations. A state may not, as a result of the state minimum provision, receive more than the
average of: (1) 0.35% of total state grants, and (2) 150% of the national average grant per formula
child, multiplied by the number of formula children in the state. (In the latter calculation,
population factor child counts are not weighted.)
Ratable reduction—Same as Basic Grants (see above).
Fiscal requirements—Same as Basic Grants (see above).
Treatment of Puerto Rico, Outlying Areas, and the Bureau of Indian Affairs—Same as Basic
Grants (see above), with the additional provision that for Puerto Rico (only), a cap of 1.82 is
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placed on the aggregate weight applied to the population factor under the Targeted Grant
formula.15
Further adjustments by SEAs of LEA grants as calculated by ED: Same as Basic Grants (see
above).
Targeted Grant Allocation Formula—Same as Basic Grants (see above), except that the
population factor (PF) would be the weighted child count, as described above.
Education Finance Incentive Grants (EFIG)
The EFIG formula is in several ways significantly different from the other Title I-A allocation
formulas. As with Targeted Grants, EFIG Grants were initially authorized in 1994,16 but no funds
were appropriated for them until FY2002, after the formula was (in the case of EFIG)
considerably modified by the NCLB. Beginning in FY2002, all increases in Title I-A
appropriations have been allocated as either EFIG or Targeted Grants. Thus, as with Targeted
Grants, EFIG Grants constitute a substantial (21% of FY2008 appropriations) and growing
portion of total Title I-A grants. They are allocated among a large majority of LEAs (87% in
FY2008).
The distinctive elements of the EFIG formula begin with the fact that the first stage in the process
of calculating grants is based on data for states as a whole, not LEAs. LEA grants are determined
in a separate, later stage of the allocation process.
A second major difference is that the EFIG formula includes not only a population factor and an
expenditure factor, but also two unique factors. These are an effort factor, based on average per
pupil expenditure for public K-12 education compared to personal income per capita for each
state compared to the nation as a whole, and an equity factor, based on variations in average per
pupil expenditure among the LEAs in each state.
A third distinctive feature of the EFIG formula is that while population factor child counts are not
weighted when calculating state total grants, they are weighted in the separate process of
suballocating state total grants among LEAs. This intra-state allocation process is based on the
same number and percentage scales as used for Targeted Grants, although the weights attached to
each point on those scales varies among states, based on the state’s equity factor. A final
difference between the EFIG Grant and other Title I-A formulas is that the expenditure factor is
modified through application of slightly more narrow floor and ceiling constraints for EFIG
Grants.
Thus, state total EFIG Grants are based on each state’s share, compared to the national total, of a
population factor multiplied by an expenditure factor, an effort factor, and an equity factor,
adjusted by a state minimum. Then, each LEA’s share of the state total EFIG Grant is based on a
15
This cap applies to both the numbers and percentages weighting scales, and was intended to provide that the share of
Targeted Grants allocated to Puerto Rico would be approximately equal to its share of grants under the Basic and
Concentration Grant formulas for FY2001. This cap reduces grants below the level that would obtain if there were no
cap at all (i.e., if Puerto Rico were treated in the same manner as the 50 states and the District of Columbia), since
Puerto Rico’s high number and percentage of school-age children in poor families would translate into a significantly
higher aggregate weighting factor if not capped.
16
The Improving America’s Schools Act (IASA), P.L. 103-382.
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weighted population factor count for the LEA, compared to the total for all LEAs in the state,
adjusted by an LEA hold harmless provision. These formula factors are described below, followed
by a mathematical expression of the formula.
Population factor—In the first-stage calculation of state total EFIG Grants, this factor is the
same as for Basic Grants (see above). In the second-stage suballocation of state total grants
among LEAs, as under all stages of the allocation process for Targeted Grants, weights are
applied to child counts before they are actually used in the formula. This process is the same as
for Targeted Grants with respect to the number and percentage scales used, and use of the greater
of the two weighted child counts to calculate LEA grants. However, for EFIG Grants only, the
weights attached to each point on the number and percentage scales differs, depending on the
state’s equity factor (described below). This variation is illustrated in Table 3, below.
Table 3. Weights Applied to Counts of Population Factor Children in the Calculation
of LEA Grants Under the ESEA Title I-A Education Finance Incentive
Grant Formula
A. Weights Based on LEA Numbers of Children in the Population Factor
Weight Applied to Population Factor Children in This Range
Population Factor
Count Range
State Equity Factor
of 0.20 or Above
State Equity Factor
Below 0.10
State Equity Factor
Above 0.10 But
Below 0.20
0-691
1.0
1.0
1.0
692-2,262
1.5
1.5
2.0
2,263-7,851
2.0
2.25
3.0
7,852-35,514
2.5
3.375
4.5
35,515 or more
3.0
4.5
6.0
B. Weights Based on LEA Population Factor Children as a Percentage of Total School-Age
Population
Weight Applied to Population Factor Children in This Range
Population Factor
Percentage Range
State Equity Factor
of 0.20 or Above
State Equity Factor
Below 0.10
State Equity Factor
Above 0.10 But
Below 0.20
Less than or equal to
15.58%
1.0
1.0
1.0
Above 15.58% but less
than or equal to 22.11%
1.75
1.5
2.0
Above 22.11% but less
than or equal to 30.16%
2.5
3.0
4.0
Above 30.16% but less
than or equal to 38.24%
3.25
4.5
6.0
Above 38.24%
4.0
6.0
8.0
Source: Table prepared by CRS.
As indicated in Table 3, the weights rise more rapidly as the numbers and percentages of
population factor children increase in states with higher equity factors. For states with an equity
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factor below 0.10, the weights are the same as for Targeted Grants. For states with equity factors
between 0.10 and 0.20, or above 0.20, the maximum weights are 50% higher, and twice as high,
respectively, as for Targeted Grants. As is discussed below, states with higher equity factors have
relatively high degrees of variation in average per pupil expenditure among the state’s LEAs.
Factors Not Found in Other ESEA Program Formulas—As noted above, the EFIG formula
has two additional factors not found in any other ESEA program allocation formula.
Effort Factor—The effort factor is based on a comparison of state average per pupil expenditure
(APPE) for public elementary and secondary education with state personal income per capita
(PCI). More specifically, it is the ratio of APPE to PCI for each state divided by the ratio of APPE
to PCI for the nation. The resulting index number is greater than 1.0 for states where the ratio of
expenditures per pupil for public elementary and secondary education to personal income per
capita is greater than average for the nation as a whole, and below 1.0 for states where the ratio is
less than average for the nation as a whole. Narrow bounds of 0.95 and 1.05 are placed on the
resulting multiplier, so that its influence on state grants is rather limited and its importance is
largely symbolic.
Equity Factor—The equity factor is based upon a measure of the average disparity in average
per pupil expenditure among the LEAs of a state called the coefficient of variation (CV). The CV
is expressed as a decimal proportion of the state average per pupil expenditure. In the CV
calculations for this formula, an extra weight (1.4 vs. 1.0) is applied to estimated counts of
children from poor families. The effect is that grants would be maximized for a state where
expenditures per pupil from a poor family are 40% higher than expenditures per pupil from a nonpoor family. 17 Typical state equity factors range from 0.0 (for the single-LEA jurisdictions of
Hawaii, Puerto Rico, and the District of Columbia, where by definition there is no variation
among LEAs), to approximately 0.25 for a state with high levels of variation in expenditures per
pupil among its LEAs; the equity factors for most states fall into the 0.10 - 0.20 range.18 In
calculating grants, the equity factor is subtracted from 1.30 to determine a multiplier to be used in
calculating state grants. As a result, the lower a state’s expenditure disparities among its LEAs,
the lower is its CV and equity factor, the higher is its multiplier and its grant under the EFIG
formula. Conversely, the greater a state’s expenditure disparities among its LEAs, the higher is its
CV and equity factor, and the lower is its multiplier and its grant under the EFIG formula.
Eligibility threshold—Same as Targeted Grants (see above).
Expenditure factor—State average per pupil expenditure for public K-12 education, subject to a
minimum of 85% (not 80%, as in the other Title I-A formulas) and a maximum of 115% (not
120%, as in the other Title I-A formulas) of the national average, further multiplied by 0.40. The
expenditure factor is the same for all LEAs in each state.
17
Limited purpose LEAs, such as those providing only vocational education, are excluded from the calculations, as are
small LEAs with enrollment below 200 pupils.
18
There is a special provision for states meeting the expenditure disparity standard established in regulations for the
Impact Aid program (ESEA Title VIII), for which the equity factor is capped at a maximum of 0.10. For an explanation
of the Impact Aid equalization provision, see CRS Report RL34119, Impact Aid for Public K-12 Education:
Reauthorization Under the Elementary and Secondary Education Act, by (name redacted) and (name redacted),
pages 17-18.
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LEA minimum grant or “hold harmless” level—Same as Basic Grants (see above), with one
exception. The hold harmless is not taken into consideration in the initial calculation of state total
grants. Therefore, it is possible (and has occurred in a small number of instances) that state total
grants are insufficient to fully pay hold harmless amounts to all LEAs in the state. In that case,
each LEA gets a proportional share of its hold harmless amount.
Minimum state grant—Same as Targeted Grants (see above).
Ratable reduction—Same as Basic Grants (see above).
Fiscal requirements—Same as Basic Grants (see above).
Treatment of Puerto Rico, Outlying Areas, and the Bureau of Indian Affairs—Same as Basic
Grants (see above).
Further adjustments by SEAs of LEA grants as calculated by ED—Same as Basic Grants (see
above).
Education Finance Incentive Grant Allocation Formula—
Stage 1: Calculation of State Total EFIG Allocations
Step 1: State Grant 1 = PF * EF * EFF * (1.30 - EQ)
In Step 1, the population factor is multiplied by the expenditure factor, the effort factor, and 1.30
minus the equity factor for each state.
Step 2: State Grant 2 = ( ( State Grant 1 / ∑ State Grant 1 ) * APP * S_MIN_ADJ ) or S_MIN, if
greater
In Step 2, the amount for each state in Step 1 is divided by the total of these amounts for all
eligible states in the nation, then multiplied by the available appropriation, adjusted through
application of the state minimum grant provision. The state minimum grant adjustment is upward
in the smallest states, where total grants are increased through application of the minimum, and
downward in all other states, where funds are reduced in order to pay the costs of applying the
minimum.
Stage 2: Calculation of LEA EFIG Allocations
Step 1: LEA Grant 1 = ( ( PF / ∑ PF ) * S_ALL ) or L_HH, whichever is greater
In Step 1, the population factor for each eligible LEA is divided by the total population factor for
all eligible LEAs in the state. If this is less than the LEA’s hold harmless level, the latter amount
is used.
Step 2: LEA Grant 2 = ( LEA Grant 1 * L_HH_ADJ ) or L_HH, whichever is greater
In Step 2, the amount for each LEA in Step 1 is adjusted through application of a factor to
account for the aggregate costs of raising affected LEAs in the state to their hold harmless level,
given a fixed total state allocation level. The LEA hold harmless adjustment is downward for all
LEAs except those at the hold harmless level.
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Step 3: Final LEA Grant = LEA Grant 2 * SCH_IMP_ADJ * S_ADMIN_ADJ * AWD_ADJ *
OTR_ADJ
In the final step of calculating LEA grants under all Title I-A allocation formulas, LEA grants as
calculated in Step 2 are further adjusted for the school improvement and state administration
reservations, possible state reservations for achievement awards, and other possible adjustments
(such as for grants to charter schools) discussed above.
Where:
PF = Population factor
EF = Expenditure factor
EFF = Effort factor
EQ = Equity factor
APP = Appropriation
S_MIN_ADJ = State minimum adjustment (proportional increase (in small states) or decrease (in
other states) to apply the statewide minimum grant)
S_MIN = State minimum
S_ALL = State total allocation
L_HH = LEA minimum or “hold harmless” level
L_HH_ADJ = LEA minimum or “hold harmless” adjustment (proportional decrease, in LEAs not
benefitting from the LEA “hold harmless,” to apply the LEA minimum grant)
SCH_IMP_ADJ = Reservation by SEA for school improvement grants
S_ADMIN_ADJ = Reservation by SEA for state administration
AWD_ADJ = Possible reservation by SEA for achievement awards
OTR_ADJ = Other possible adjustments by the SEA
∑ = Sum (for all states in the nation in Stage 1, and for all eligible LEAs in the state in Stage 2)
ESEA Title I-A School Improvement Grants
Under ESEA Title I-A, two different mechanisms are authorized for the generation of funds for
School Improvement activities. Whatever the source, these funds are to be targeted on schools
that are identified as being in need of improvement, corrective action, or restructuring because
they have failed to make AYP for two consecutive years or more. 19 First, states are to reserve 4%
19
See CRS Report RL33731, Education for the Disadvantaged: Reauthorization Issues for ESEA Title I-A Under the
(continued...)
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
of their total Title I-A LEA grants, under the four formulas described above, for School
Improvement activities.20
Second, the ESEA authorizes a separate appropriation for state School Improvement Grants.
These funds are allocated to states in proportion to state total grants under ESEA Title I, Parts A,
C (State Agency Migrant Program—see below), and D (State Agency Neglected, Delinquent, or
At-Risk Program—see below). At least 95% of each state’s funds from either source (the
reservation or the separate appropriation) is to be allocated to LEAs for schools identified as
being in need of improvement, corrective action, or restructuring. The funds are allocated at state
discretion—there is no statutory intrastate allocation formula for School Improvement funds,
beyond the general direction that they are to be directed to LEAs with schools identified as being
in need of improvement, corrective action, or restructuring.
Title I grant factor—Funds are allocated to states in proportion to total grants under Title I, Parts
A, C, and D.
School Improvement Grant Allocation Formula—
State Grant = [ ( T1A + T1C + T1D ) / ∑ ( T1A + T1C + T1D ) ] * APP
Each state (including Outlying Areas and the Bureau of Indian Affairs) receives a School
Improvement Grant equal to its proportional share of total grants under ESEA Title I,
Parts A, C, and D.
Where:
T1A = State total grant under ESEA Title I, Part A
T1C = State total grant under ESEA Title I, Part C
T1D = State total grant under ESEA Title I, Part D
APP = Appropriation (separate) for School Improvement Grants
∑ = Sum (for all states)
Suballocation of LEA Grants to Schools
Unlike other federal elementary and secondary education programs, most Title I-A funds are
allocated to individual schools, although LEAs retain substantial discretion to control the use of a
significant share of Title I-A grants at a central district level. 21 While there are several rules
(...continued)
No Child Left Behind Act, by (name redacted) and (name redacted) for details.
20
In reserving these funds, SEAs may not reduce any LEA’s grant below its previous year level. As a result, in some
years, a number of states may be unable to reserve the full 4% of state total LEA grants for this purpose. For details, see
Government Accountability Office, “No Child Left Behind Act: Education Actions Could Improve the Targeting of
School Improvement Funds to Schools Most in Need of Assistance,” GAO-08-380, February 2008.
21
Detailed guidance regarding the selection of schools to receive Title I-A grants and the allocation of funds among
them may be found in the following ED policy guidance document—Local Educational Agency Identification and
(continued...)
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
related to school selection, LEAs must generally rank their public schools by their percentage of
pupils from low-income families, and serve them in rank order. All participating schools must
generally have a percentage or number of children from low-income families that is higher than
the LEA’s average, or 35%, whichever of these two figures is lower, 22 although LEAs have the
option of setting school eligibility thresholds higher than the minimum in order to concentrate
available funds on a smaller number of schools. 23
Once schools are selected, Title I-A funds are allocated among them (and reserved for services to
private school pupils) in proportion to their number of pupils from low-income families. In a
large majority of cases, the data used to determine which pupils are from low-income families for
the distribution of funds to schools are not the same as those used to identify school-age children
in poor families for purposes of calculating allocations to states and LEAs. This is because data
are not typically available on the number of school-age children enrolled in a school, or living in
a residential school attendance zone, with income below the standard federal poverty threshold.
Such “population in poverty” estimates, as used in the standard formulas for allocation of funds to
states and LEAs (discussed above), are usually available only for LEAs, counties, and states.
Thus, LEAs must use available proxies for low-income status. The Title I-A statute allows LEAs
to use the following low-income measures: (a) eligibility for free and reduced-price school
lunches; (b) eligibility for Temporary Assistance to Needy Families (TANF); or (c) eligibility for
Medicaid. 24 At the level of individual schools, the most commonly used criterion for determining
whether pupils are from low-income families is eligibility for free and reduced-price school
lunches. According to the most recent relevant data, approximately 90% of LEAs receiving Title
I-A funds use free/reduced-price school lunch data—sometimes alone, sometimes in combination
with other authorized criteria—to select Title I-A schools and allocate funds among them. 25 The
income eligibility thresholds for free and reduced-price lunches are higher than the poverty levels
used in the allocation formulas to states and LEAs: 130% of poverty for free lunches, 185% for
reduced-price lunches.
After data have been compiled on the percentage or number of pupils from low-income families
who are either enrolled in a LEA’s public schools or residing in the attendance areas served by
such schools, available Title I-A funds are allocated among these schools in rank order, beginning
with the highest poverty schools, until no further funds are available. LEAs may choose to
consider only schools of selected grade levels (e.g., only elementary schools) in determining
eligibility for grants, as long as all schools with 75% or more of pupils from low-income families
receive grants.
Funds are allocated among schools in proportion to their number of pupils from low-income
families, although grants to eligible schools per pupil from a low-income family need not be
(...continued)
Selection of School Attendance Areas and Schools and Allocation of Title I Funds to Those Areas and Schools, 2003.
22
This minimum percentage is reduced from 35% to 25% for schools participating in certain desegregation plans.
23
There is an exemption from all of the Title I-A school selection requirements for small LEAs—defined in this case as
those with enrollments of 1,000 or fewer pupils. Such small LEAs do not have to meet any of the school ranking
requirements discussed in this report.
24
LEAs may also develop and use a composite of two or more of these measures—for example, school-age children in
families receiving TANF or Medicaid benefits.
25
U.S. Department of Education, Study of Education Resources and Federal Funding: Final Report, 2000, p. 33
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
equal for all schools. LEAs may choose to provide higher grants per child from a low-income
family to schools with higher percentages of such pupils (e.g., higher grants per child to a school
where 70% of pupils are from low-income families than to a school where 40% of pupils are from
low-income families). If a LEA provides Title I-A funds to schools with low-income pupil
percentages below 35%, then it must provide a minimum amount of funds per child from a lowincome family—equal to at least 125% of the LEA’s Title I-A grant per child from a low-income
family—to each participating school.
In the 2004-2005 school year, an estimated 56% of all public schools in the nation received Title
I-A grants. This included 82% of public schools in the highest quartile with respect to their
percentage of pupils in low-income families, declining to 37% of schools in the lowest quartile.
Elementary schools (70%) are much more likely than secondary schools (39%) to receive Title IA grants. 26
Similarly, the share of funds to be used by each recipient LEA to serve educationally
disadvantaged pupils attending private schools is determined on the basis of the number of
children from low-income families living in the residential areas served by public schools
selected to receive Title I-A grants. LEAs may use for this purpose either the same source of data
used to select and allocate funds among public schools (i.e., usually free/reduced-price school
lunch data) or one of a specified range of alternatives.27
Recent Funding Trends for Title I-A
Information on the Title I-A appropriations for FY2007-2009, plus the Administration budget
request for FY2010 may be found in Table 4, below. The table is preceded by brief descriptions
of appropriations for FY2008 and FY2009 plus the FY2010 request.
FY2008
The Administration’s budget for FY2008 requested $13,909,900,000 for Title I-A LEA grants, an
increase of $1,071,775,000 (8.3%) over the FY2007 appropriation, plus a separate appropriation
of $500 million for school improvement grants, a fourfold increase over FY2007. All of the
increase in LEA grants would have been devoted to Targeted Grants (along with a $62.5 million
reduction in EFIG grants). P.L. 110-161, the Consolidated Appropriations Act for FY2008,
provided a total of $13,898,875,000 for Title I-A grants to LEAs, plus a separate appropriation of
$491,265,000 for school improvement grants. As in the recent past, the funding level for
26
Jay G. Chambers, Irene Lamb, and Kanya Mahitivanichcha, et al., State and Local Implementation of the No Child
Left Behind Act: Volume VI—Targeting and Uses of Federal Education Funds, U.S. Department of Education, Office
of Planning, Evaluation, and Policy Development, Policy and Program Studies Service, A report from the National
Longitudinal Study of No Child Left Behind (NLS-NCLB) and the Study of State, Washington, DC, January 2009, p.
p. 23, 28, and 50. http://www.ed.gov/rschstat/eval/disadv/nclb-targeting/nclb-targeting.pdf.
27
According to the ED policy guidance document, Local Educational Agency Identification and Selection of School
Attendance Areas and Schools and Allocation of Title I Funds to Those Areas and Schools (p. 16), “To obtain a count
of private school children, an LEA may use: (1) The same poverty data it uses to count public school children. (2)
Comparable poverty data from a survey of families of private school students that, to the extent possible, protects the
families’ identity. The LEA may extrapolate data from the survey based on a representative sample if complete actual
data are not available. (3) Comparable data from a different source, such as scholarship applications, so long as the
income level for both sources is generally the same. (4) Proportional data based on the poverty percentage of each
public school attendance area applied to the total number of private school children who reside in that area. (5) An
equated measure of low income correlated with a measure of low income used to count public school children.”
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Concentration Grants was the same for FY2008 as for FY2007, and equal amounts were
appropriated for the Targeted and EFIG formulas ($2,967,949,000 for each). All of an across-theboard reduction for Title I-A was applied to Basic Grants, reducing funds under that formula to
$6,597,946,000.
FY2009
For FY2009, regular appropriations are provided under P.L. 111-8, an omnibus appropriations act.
Under P.L. 111-8, total regular FY2009 appropriations for grants to LEAs are $14,492,401,000.
The FY2009 funding for Basic and Concentration Grants is the same as for FY2008, while
Targeted and EFIG grants each receive $3,264,712,000. In addition, $545,633,000 is separately
appropriated for School Improvement Grants.
In addition to regular FY2009 appropriations legislation for ED, the American Recovery and
Reinvestment Act of 2009 (ARRA), P.L. 111-5, provides a total of $13 billion in additional
FY2009 appropriations for Title I-A—$10 billion for grants to LEAs and $3 billion for School
Improvement Grants. These funds are in addition to amounts provided in regular FY2009
appropriations legislation. Half of the additional grants to LEAs will be allocated under the
Targeted Grant formula and half under the Education Finance Incentive Grant formula.
FY2010
On May 7, 2009, the Obama Administration released its detailed budget recommendations for
FY2010. For ESEA Title I-A, the Administration requested a total of $12,992,401,000 for grants
to LEAs, a reduction of $1,500,000,000 (10.4%) from the FY2009 amount. All of this reduction
would be applied to Basic Grants, which would decline from $6,597,946,000 for FY2009 to
$5,097,946,000 for FY2010. At the same time, for School Improvement Grants under Title I-A,
the Administration requested a $1,000,000,000 increase, from $545,633,000 for FY2009 to
$1,545,633,000 for FY2010.
On July 24, 2009, the House passed H.R. 3293, to provide FY2010 appropriations for the
Departments of Labor, Health and Human Services, and Education and Related Agencies. As
passed by the House, H.R. 3293 would provide $14,492,401,000 for Title I-A grants to LEAs,
$1,500,000,000 more than the Administration request for Basic Grants but the same as requested
for all other formulas, and $545,633,000, the same as the Administration request, for School
Improvement Grants. The Senate Committee on Appropriations reported its version of H.R. 3293
on July 30, 2009. As reported by the Senate Committee on Appropriations, H.R. 3293 would
provide $13,792,401,000 for Title I-A grants to LEAs, $800,000,000 more than the
Administration request for Basic Grants but the same as requested for all other formulas, and
$545,633,000, the same as the Administration request for School Improvement Grants. Table 4,
below, shows total Title I-A appropriations for FY2009-FY2010.
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Table 4. FY2009-FY2010 Appropriations for ESEA Title I, Part A
FY2010
Under H.R.
3293 as
Reported by
Senate
Committee
Formula
FY2009
Regular
Appropriations
FY2009 ARRA
Additional
Appropriations
FY2010
Administration
Budget
Request
FY2010
Under H.R.
3293 as
Passed by
House
Basic Grantsa
$6,597,946,000
—
$5,097,946,000
$6,597,946,000
$5,897,946,000
Concentration
Grants
1,365,031,000
—
1,365,031,000
1,365,031,000
1,365,031,000
Targeted Grants
3,264,712,000
$5,000,000,000
3,264,712,000
3,264,712,000
3,264,712,000
Education
Finance
Incentive Grants
3,264,712,000
5,000,000,000
3,264,712,000
3,264,712,000
3,264,712,000
Total ESEA Title
I-A Grants to
LEAs
14,492,401,000
10,000,000,000
12,992,401,000
14,492,401,000
13,792,401,000
School
Improvement
Grants
(separate
authorization)
545,633,000
3,000,000,000
1,545,633,000
545,633,000
545,633,000
Source: Table prepared by CRS.
a.
The amounts shown above for Basic Grants include approximately $3.5 million each year for census
updates.
FY2008 Allocation Patterns
FY2008 (school year 2008-2009) grants are the latest available actual allocations under Title I-A.
Overall, the FY2008 funding level for Title I-A is 8.3% above the FY2007 level. This contrasts
with the period of FY2005-2007, when aggregate funding for Title I-A LEA grants was
essentially constant.
Due largely to the comparatively large increase in Title I-A funding for FY2008, all states except
one (Wisconsin, where grants declined by 1.3%) received higher total grants for FY2008 than for
FY2007. At the LEA level, approximately 61% of all LEAs nationwide that received Title I-A
grants for both FY2007 and FY2008 received larger grants for FY2008, while 39% received
lower grants for FY2007. LEAs receiving lower Title I-A grants for FY2008 than in FY2007 have
been experiencing reductions in their estimated number of school-age children in poor families;
these include LEAs of all sizes and degrees of poverty concentration, in contrast to the FY2002FY2006 period when a large majority of large or high-poverty LEAs experienced grant increases,
while a majority of LEAs overall were losing funds.
Tables 5-8 provide a series of analyses of the distribution of Title I-A funds among the states, as
well as different types or categories of LEAs. Each table is preceded by a brief description of the
information provided in the table. Subsequently, these tables will be referred to in the course of a
series of analyses of possible Title I-A formula reauthorization issues.
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Table 5, below, shows state average FY2008 Title I-A grants per child counted in the Title I-A
allocation formulas. Separate amounts are provided for each of the four formulas, plus a Title I-A
total. The substantial variation in these amounts reflect a combination of factors, many of which
are analyzed in detail in the final section of this report. These factors include:
•
State minimum grant provisions—Under all formulas, average grants per formula
child are much higher for the smallest (in population) states.
•
Expenditure factor—Under all formulas, but especially with respect to Basic
Grants, average grants per formula child are much higher for states with high
expenditure factors (e.g., Connecticut, Massachusetts, New Jersey, or New York)
than for states with low factors (e.g., Alabama, Arkansas, Mississippi, or Utah).
•
Targeting on LEAs with large numbers of school-age children in poor families—
With the exception of the smallest states (where average grants per formula child
are high regardless of poverty rates), average grants per child under the
Concentration, Targeted, and Education Finance Incentive Grant (EFIG) formulas
are higher for several states containing LEAs with very high numbers of schoolage children in poor families (e.g., Illinois, Michigan, New York, or
Pennsylvania) than for other states. In contrast, states with large numbers of
LEAs with high poverty rates (e.g., Alabama, Arkansas, Mississippi, New
Mexico) are below the national average, primarily due to low expenditure factors
for these states.
•
Equity factor—Several states with especially favorable equity factors (e.g., the
District of Columbia, Hawaii, West Virginia, and Wisconsin) receive relatively
high average grants per formula child under the EFIG formula.
However, many key formula factors operate in opposite directions, largely cancelling each other
out. For example, California has LEAs with very large numbers of school-age children in poor
families, but also a relatively low expenditure factor, resulting in an average Targeted Grant per
formula child that is approximately the same as the national average.
Table 5. ESEA Title I-A Grant Amount Per Child Counted in the Allocation
Formulas, FY2008
Title I-A Grant Amount Per Child Counted in the Allocation Formulas,
FY2008
Basic Grant
Concentration
Grant
Targeted
Grant
Education
Finance
Incentive
Grant
Total Title
I-A Grant
United States
$684
$142
$308
$308
$1,441
Alabama
$566
$134
$241
$269
$1,211
Alaska
$979
$132
$518
$515
$2,143
Arizona
$624
$135
$264
$264
$1,287
Arkansas
$610
$143
$242
$307
$1,301
California
$641
$135
$303
$269
$1,347
Colorado
$624
$112
$259
$281
$1,275
State
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Title I-A Grant Amount Per Child Counted in the Allocation Formulas,
FY2008
Basic Grant
Concentration
Grant
Targeted
Grant
Education
Finance
Incentive
Grant
Total Title
I-A Grant
Connecticut
$950
$142
$290
$371
$1,754
Delaware
$1,002
$123
$521
$521
$2,167
District of Columbia
$861
$212
$504
$438
$2,015
Florida
$576
$139
$336
$273
$1,324
Georgia
$658
$152
$295
$319
$1,424
Hawaii
$764
$178
$412
$421
$1,774
Idaho
$550
$90
$252
$252
$1,144
Illinois
$847
$165
$360
$321
$1,692
Indiana
$717
$120
$256
$330
$1,423
Iowa
$616
$78
$189
$287
$1,170
Kansas
$710
$123
$242
$353
$1,429
Kentucky
$642
$150
$272
$318
$1,382
Louisiana
$616
$153
$303
$244
$1,315
Maine
$822
$138
$337
$393
$1,690
Maryland
$872
$180
$419
$369
$1,840
Massachusetts
$869
$142
$319
$371
$1,702
Michigan
$773
$146
$342
$367
$1,629
Minnesota
$713
$80
$238
$305
$1,335
Mississippi
$584
$137
$254
$268
$1,243
Missouri
$628
$124
$242
$273
$1,266
Montana
$673
$148
$368
$368
$1,557
Nebraska
$695
$98
$267
$354
$1,414
Nevada
$548
$131
$331
$267
$1,277
New Hampshire
$939
$99
$481
$503
$2,022
New Jersey
$875
$138
$293
$375
$1,682
New Mexico
$605
$150
$276
$297
$1,328
New York
$917
$202
$481
$376
$1,975
North Carolina
$560
$133
$257
$271
$1,221
North Dakota
$1,198
$175
$631
$633
$2,636
Ohio
$740
$138
$294
$345
$1,518
Oklahoma
$559
$120
$225
$264
$1,169
Oregon
$650
$132
$246
$325
$1,352
Pennsylvania
$844
$155
$361
$372
$1,732
Puerto Rico
$548
$141
$269
$290
$1,248
State
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Title I-A Grant Amount Per Child Counted in the Allocation Formulas,
FY2008
Basic Grant
Concentration
Grant
Targeted
Grant
Education
Finance
Incentive
Grant
Total Title
I-A Grant
Rhode Island
$908
$158
$354
$399
$1,818
South Carolina
$614
$146
$261
$303
$1,324
South Dakota
$807
$151
$467
$465
$1,888
Tennessee
$549
$129
$250
$266
$1,193
Texas
$593
$136
$290
$269
$1,287
Utah
$570
$72
$224
$261
$1,126
Vermont
$1,251
$204
$657
$665
$2,778
Virginia
$722
$127
$284
$300
$1,434
Washington
$631
$98
$225
$284
$1,238
West Virginia
$708
$168
$276
$361
$1,512
Wisconsin
$849
$125
$308
$379
$1,661
Wyoming
$1,345
$180
$716
$713
$2,954
State
Source: Table prepared by CRS.
Table 6, below, provides each state’s percentage share of the funds allocated under each of the
Title I-A formulas, as well as total Title I-A grants, for FY2008. The distinctive feature here is
that while these shares are similar under all formulas for most states, some states receive
substantially higher or lower shares under some formulas than under the other formulas. Focusing
on those states where the highest share of grants under any formula is one-third or more above its
lowest share, there are 19 states where the share of funds received under one of the four formulas
is substantially different from the others. These include:
•
•
•
•
•
Seven small states where the share under the Targeted and/or EFIG formulas is
much greater than under Basic or Concentration Grants, due to the higher state
minimum under the former formulas (Alaska, Delaware, New Hampshire, North
Dakota, South Dakota, Vermont, and Wyoming);
Four states with relatively low poverty rates where the share of Basic Grants is
substantially higher than under any other formula (Connecticut, Minnesota, New
Jersey, and Wisconsin);
Two states with many LEAs with relatively high poverty rates where shares are
substantially higher under Concentration Grants than the other formulas
(Louisiana and West Virginia);
One state where the share of Targeted Grants is substantially higher than under
the other formulas, due to the impact of one very large LEA (Nevada); and
Five states where the share of EFIG Grants is substantially higher than under the
other formulas, due primarily to relatively favorable equity factors (Iowa,
Kansas, Nebraska, Utah, and Washington).
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Table 6. State Shares of Funds Allocated Under Each of the ESEA
Title I-A Formulas, FY2008
ESEA Title I-A Grants to LEAs: State Shares of Grants by Formula
Basic Grants
Concentration
Grants
Targeted
Grants
Education
Finance
Incentive
Grants
100.00%
100.00%
100.00%
100.00%
100.00%
Alabama
1.54%
1.77%
1.46%
1.63%
1.57%
Alaska
0.27%
0.18%
0.32%
0.32%
0.28%
Arizona
2.04%
2.14%
1.92%
1.92%
2.00%
Arkansas
1.04%
1.17%
0.91%
1.16%
1.05%
California
12.37%
12.62%
12.98%
11.54%
12.35%
Colorado
1.01%
0.88%
0.94%
1.01%
0.98%
Connecticut
0.96%
0.69%
0.65%
0.83%
0.84%
Delaware
0.27%
0.16%
0.31%
0.31%
0.28%
District of Columbia
0.31%
0.37%
0.40%
0.35%
0.34%
Florida
4.37%
5.10%
5.66%
4.61%
4.77%
Georgia
3.16%
3.52%
3.14%
3.41%
3.24%
Hawaii
0.29%
0.33%
0.35%
0.36%
0.32%
Idaho
0.34%
0.27%
0.35%
0.35%
0.34%
Illinois
4.55%
4.29%
4.30%
3.83%
4.32%
Indiana
1.91%
1.54%
1.51%
1.95%
1.80%
Iowa
0.59%
0.36%
0.40%
0.61%
0.53%
United States
Total LEA
Grants
Kansas
0.73%
0.61%
0.55%
0.80%
0.69%
Kentucky
1.48%
1.67%
1.40%
1.63%
1.52%
Louisiana
2.11%
2.53%
2.31%
1.86%
2.14%
Maine
0.38%
0.31%
0.35%
0.41%
0.37%
Maryland
1.40%
1.39%
1.49%
1.31%
1.40%
Massachusetts
1.83%
1.45%
1.49%
1.74%
1.70%
Michigan
3.83%
3.50%
3.77%
4.04%
3.83%
Minnesota
1.04%
0.56%
0.77%
0.99%
0.92%
Mississippi
1.35%
1.53%
1.30%
1.37%
1.36%
Missouri
1.71%
1.63%
1.46%
1.65%
1.64%
Montana
0.29%
0.31%
0.35%
0.35%
0.32%
Nebraska
0.45%
0.31%
0.39%
0.51%
0.44%
Nevada
0.53%
0.61%
0.71%
0.58%
0.59%
New Hampshire
0.27%
0.14%
0.31%
0.32%
0.28%
New Jersey
2.29%
1.74%
1.70%
2.18%
2.09%
New Mexico
0.79%
0.95%
0.80%
0.86%
0.82%
New York
8.72%
9.27%
10.16%
7.96%
8.92%
Congressional Research Service
27
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
ESEA Title I-A Grants to LEAs: State Shares of Grants by Formula
Basic Grants
Concentration
Grants
Targeted
Grants
Education
Finance
Incentive
Grants
North Carolina
2.52%
2.89%
2.57%
2.71%
2.61%
North Dakota
0.23%
0.17%
0.27%
0.28%
0.25%
Ohio
3.82%
3.44%
3.38%
3.96%
3.72%
Oklahoma
1.09%
1.13%
0.97%
1.14%
1.08%
Oregon
1.03%
1.01%
0.87%
1.14%
1.02%
Pennsylvania
4.22%
3.74%
4.01%
4.14%
4.11%
Total LEA
Grants
Puerto Rico
3.43%
4.28%
3.75%
4.04%
3.71%
Rhode Island
0.41%
0.34%
0.35%
0.40%
0.39%
South Carolina
1.46%
1.68%
1.38%
1.60%
1.49%
South Dakota
0.27%
0.25%
0.35%
0.35%
0.30%
Tennessee
1.69%
1.91%
1.70%
1.81%
1.74%
Texas
9.17%
10.14%
9.97%
9.23%
9.45%
Utah
0.47%
0.28%
0.41%
0.47%
0.44%
Vermont
0.23%
0.18%
0.26%
0.27%
0.24%
Virginia
1.74%
1.49%
1.52%
1.61%
1.64%
Washington
1.50%
1.13%
1.18%
1.50%
1.39%
West Virginia
0.71%
0.82%
0.62%
0.81%
0.72%
Wisconsin
1.56%
1.11%
1.26%
1.54%
1.45%
Wyoming
0.22%
0.14%
0.26%
0.26%
0.23%
Source: Table prepared by CRS.
Table 7, below, provides average Title I-A grants per formula child, by formula and total, for
LEAs in five illustrative categories. It must be emphasized that these are limited numbers of
LEAs in each category, selected to concretely illustrate certain patterns of Title I-A allocations.
They are not necessarily representative of all LEAs in each category. (The following Table 8
provides summary data for all LEAs in each of 12 standard categories of localities.)
The illustrative categories for Table 7 are:
•
LEAs with very large numbers of formula children,
•
LEAs with very high percentages of formula children,
•
LEAs in minimum grant states,
•
LEAs with relatively large numbers, but relatively low percentages, of formula
children, and
•
LEAs with low numbers and percentages of formula children.
Distinctive allocation patterns illustrated in Table 7, all of which will be discussed further in the
issue analyses at the end of this report, include the following:
Congressional Research Service
28
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
•
Grants per formula child are much higher than average under the Targeted and
EFIG grant formulas for the selected LEAs with very large numbers of formula
children;
•
The selected LEAs with very high percentages of formula children receive higher
than average grants per formula child under the Targeted and EFIG formulas, but
much lower than the LEAs with very large numbers of formula children, partially
due to their treatment under these formulas but primarily because they are located
in states with low expenditure factors;
•
The selected LEAs in minimum grant states receive higher grants per formula
child than LEAs in any other category under all formulas except possibly
Concentration Grants;28
•
The selected LEAs with relatively large numbers, but relatively low percentages,
of formula children receive Concentration, Targeted, and EFIG grants per
formula child that are above the national average, in spite of their low formula
child percentages; and
•
The selected LEAs with low numbers and percentages of formula children
receive grants per formula child that are well below average under all formulas
except Basic Grants.
28
As discussed earlier in this report, SEAs have a substantial degree of discretion regarding the distribution of
Concentration Grants to LEAs in minimum grant states. The amounts shown in Table 6 are those calculated by ED
under the national Concentration Grant formula; the Concentration Grant amounts actually received by these LEAs
may differ substantially from the amounts shown.
Congressional Research Service
29
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Table 7. ESEA Title I-A Grant Amount Per Child Counted in the Allocation Formulas for LEAs in Selected Categories, FY2008
State
LEA Code
LEA Name
Number of
Formula
Children,
FY2008
Formula
Child %,
FY2008
Basic Grants
Concentration
Grants
Targeted
Grants
Education Finance
Incentive Grants
Grant Amount Per Formula Child, FY2008
Category 1: LEAs with very large numbers of formula children
CA
622710
Los Angeles
245,840
28.8%
$641
$160
$463
$495
GA
1300120
Atlanta
24,617
32.0%
$761
$192
$391
$481
IL
1709930
Chicago
138,144
26.6%
$910
$230
$551
$581
NY
3682047
Kings County (Brooklyn)
137,262
29.5%
$902
$228
$628
$533
PA
4218990
Philadelphia
89,179
33.6%
$814
$210
$603
$728
$806
$204
$527
$564
Average for Category 1
LEAs Listed Above
Category 2: LEAs with Very High Percentages of Formula Children
AZ
401940
Chinle
3,461
61.7%
$548
$141
$401
$474
KY
2105970
Wolfe County
626
49.7%
$662
$161
$405
$474
MS
2801980
Holmes County
2,432
61.7%
$597
$141
$401
$502
TX
4823100
Hidalgo
1,574
63.0%
$559
$144
$413
$383
TX
4828290
Los Fresnos
4,494
62.1%
$559
$144
$411
$380
$585
$147
$406
$443
Average for Category 2
LEAs Listed Above
Category 3: LEAs in Minimum Grant States
DE
1000200
Christina
3,376
11.3%
$1,002
$0
$635
$660
NH
3304980
Nashua
1,424
9.1%
$929
$0
$616
$643
VT
5007050
Rutland City
487
19.0%
$1,273
$398
$717
$700
WY
5601980
Laramie County 01
1,465
10.4%
$1,341
$0
$815
$808
ND
3819260
Warwick 29
127
42.2%
$1,205
$483
$1,136
$1,343
$1,150
$176
$784
$831
Average for Category 3
LEAs Listed Above
CRS-30
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
State
LEA Code
LEA Name
Number of
Formula
Children,
FY2008
Formula
Child %,
FY2008
Grant Amount Per Formula Child, FY2008
Basic Grants
Concentration
Grants
Targeted
Grants
Education Finance
Incentive Grants
Category 4: LEAs with Relatively Large Numbers, but Relatively Low Percentages, of Formula Children
FL
1200180
Broward County
42,837
13.9%
$576
$149
$383
$311
CO
804800
Jefferson County R-1
7,540
8.1%
$615
$159
$300
$322
GA
1301290
Cobb County
9,829
8.7%
$638
$164
$335
$372
MD
2400480
Montgomery County
9,244
5.6%
$1,085
$274
$444
$390
VA
5101260
Fairfax County
10,034
5.5%
$712
$184
$377
$436
$725
$186
$368
$366
Average for Category 4
LEAs Listed Above
Category 5: LEAs with Low Numbers and Percentages of Formula Children
IL
1731920
Pleasant Plains Community
62
4.3%
$721
$0
$0
$0
MA
2506900
Lincoln
50
3.7%
$822
$0
$0
$0
MN
2718810
Maple Lake
57
5.1%
$683
$0
$184
$217
NY
3606990
Chappaqua Central
74
1.8%
$0
$0
$0
$0
NY
3629850
Wantagh Union
71
2.1%
$822
$0
$0
$0
$609
$0
$37
$43
Average for Category 5
LEAs Listed Above
Source: Table prepared by CRS.
CRS-31
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
The last of the data tables in this report section, Table 8, displays the distribution of total schoolage population, Title I-A formula children, and Title I-A grants (by formula and total) among
LEAs in 12 standard locale categories. (Note that Puerto Rico is excluded from this analysis.)
These categories are based on the “urban-centric” locale codes developed by the National Center
for Education Statistics (NCES).29
The final column (Column J) in Table 8 shows the percentage difference between the share of
total Title I-A grants going to LEAs in that category (Column I) and the share of Title I-A formula
children (Column D). This figure indicates the aggregate size and direction of variations in the
distribution of Title I-A formula children and the distribution of Title I-A grants. For example, if
the amount in Column J were large and positive, this would indicate that LEAs in that category
receive a substantially higher share of Title I-A funds than their share of the children counted in
the Title I-A formulas. Conversely, if the amount in Column J were large and negative, this would
indicate that LEAs in that category receive a substantially smaller share of Title I-A funds than
their share of the children counted in the Title I-A formulas.
As shown in Table 8, applying an arbitrary threshold of +/- 10% or more to indicate substantial
differences in shares of grants versus formula children, the following patterns are illustrated:
•
The urban group as a whole (locale codes 11-13) receives substantially higher
shares of grants than their share of formula children (+13.8%) with virtually all
of this differential occurring with respect to the large city groups of LEAs (code
11) with a difference of +25.3%. In addition, whether substantial or not, the
direction of the difference is negative for all locale code groups except large city
(11) and midsize city (12).
•
The town (codes 31-33) and rural (codes 41-43) LEA groups as a whole receive
substantially lower shares of grants than their share of formula children.
•
The suburban (codes 21-23) LEA group receives lower shares of grants than its
share of formula children, although the difference does not exceed the 10%
threshold with respect to the large suburban group (code 21) or the suburban
codes overall (codes 21-23).
29
For a description of these locale codes, see http://nces.ed.gov/whatsnew/commissioner/remarks2006/6_12_2006.asp,
visited Oct. 1, 2008.
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Table 8. Distribution of School-Age Population, Title I-A Formula Children, and Title I-A Grants Among LEAs by Locale Type
LEA Percentage Shares of Title I-A Grants and Population by Locale Code, FY2008
A
B
C
D
Locale Code
Locale Type
Total
School-Age
Population,
FY2008
Title I-A
Formula
Children,
FY2008
Basic
Grants
11
Large City
16.90%
24.93%
12
Midsize City
7.53%
13
Small City
11-13 Total
E
F
G
H
I
J
Concentration
Grants
Targeted
Grants
Education
Finance
Incentive
Grants
Total
Title
I-A
Grants
% Difference
(Col. I –
Col. D)
26.58%
32.20%
35.62%
36.75%
31.23%
25.3%
9.25%
9.04%
10.13%
9.57%
9.73%
9.41%
1.8%
8.41%
9.11%
9.01%
9.06%
8.17%
8.04%
8.63%
-5.2%
32.84%
43.28%
44.63%
51.39%
53.36%
54.52%
49.26%
13.8%
21
Large Suburb
32.32%
22.16%
22.23%
17.83%
19.91%
18.67%
20.55%
-7.3%
22
Midsize Suburb
3.38%
2.63%
2.54%
1.81%
2.14%
2.01%
2.27%
-13.8%
23
Small Suburb
2.08%
1.63%
1.61%
1.21%
1.23%
1.11%
1.38%
-15.1%
37.79%
26.41%
26.37%
20.85%
23.28%
21.79%
24.20%
-8.4%
21-23 Total
31
Fringe Town
3.48%
3.04%
3.03%
2.53%
2.20%
2.10%
2.61%
-14.3%
32
Distant Town
4.85%
5.50%
5.20%
5.37%
4.13%
4.07%
4.75%
-13.7%
33
Remote Town
3.79%
4.70%
4.45%
4.83%
3.87%
4.07%
4.28%
-8.9%
12.12%
13.25%
12.68%
12.74%
10.20%
10.24%
11.64%
-12.2%
31-33 Total
41
Fringe Rural
7.65%
6.69%
6.29%
5.14%
4.94%
4.99%
5.61%
-16.1%
42
Distant Rural
6.47%
6.56%
6.25%
5.80%
4.82%
4.82%
5.60%
-14.7%
43
Remote Rural
3.13%
3.81%
3.78%
4.09%
3.40%
3.64%
3.70%
-2.9%
41-43 Total
17.25%
17.06%
16.32%
15.03%
13.16%
13.45%
14.91%
-12.6%
Grand Total
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
0.0%
Source: Table prepared by CRS based on provisions of ESEA Title I-A.
CRS-33
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
ESEA Reauthorization Issues Related to the
Title I-A Allocation Formulas
The remainder of this report describes and analyzes a number of issues that may arise in the
context of efforts to amend and reauthorize the ESEA during the 111th Congress.
Should Annual Variations in the Poverty Estimates Used to
Calculate Title I-A Grants Be Reduced Through Multi-year
Averaging or Other Methods?
As noted earlier, all the factors used to calculate Title I-A grants are now updated each year. This
includes the primary formula factor, estimated numbers of school-age children in poor families,
which constitute approximately 96% of all children counted in the Title I-A allocation formulas.
The poverty estimates for Title I-A are from the Census Bureau’s Small Area Income and
Population Estimates (SAIPE) program, which provides estimates of poor and total children aged
5-17 for LEAs, counties, and states. Under the provisions of the Improving America’s Schools
Act (IASA) of 1994 (P.L. 103-382), use of SAIPE estimates replaced the previous practice of
relying on data from the decennial Census surveys that were updated only once every 10 years.30
As amended by the IASA in 1994, the Title I-A statute provided that beginning in FY1997, the
Secretary of Education “shall” use updated population data prepared by the Census Bureau
“unless the Secretary [of Education] and the Secretary of Commerce determine that use of the
updated population data would be inappropriate or unreliable, taking into consideration the
recommendations” of a series of studies of the updating methodology to be conducted by the
National Academy of Sciences (NAS).31 In March 1997, a NAS panel32 recommended use of a
combination of 1990 census and income year (IY)199333 updated population estimates in
allocating FY1997 (1997-1998) grants.34 In a later report, the panel recommended use of a
slightly revised set of IY1993 SAIPE estimates as the sole basis for calculating FY1998 grants,
and ED followed this recommendation as well. Finally, beginning with FY1999 grants, the NAS
panel recommended that ED use the latest available SAIPE estimates of school-age children in
poor families and that grants be calculated by ED on the basis of LEA, not county, population
data,35 and ED has followed these recommendations.
30
Before initiation of the SAIPE program, the sole exception to the use of decennial Census poverty estimates was the
period FY1980-FY1988, when a portion of Title I-A grants (half of the increase over the FY1979 level) was allocated
based on state-level estimates, using a different measure of low-income (children in families with income below 50%
of the national median income for a family of four), from the one-time (1976) Survey of Income and Education.
31
Section 1124(c)(3) and (4) of the ESEA text as in effect between 1994 and 2001.
32
Panel on Estimates of Poverty for Small Geographic Areas, Committee on National Statistics, National Research
Council. The most recent of the reports on SAIPE by this Panel is “Small-Area Income and Poverty Estimates:
Priorities for 2000 and Beyond,” published in 2000 by the National Academy of Sciences.
33
Estimated numbers of school-age children in poor families, based on income received in calendar year 1993.
34
Specifically, the panel recommended that each county’s school-age child poverty rates based on 1990 census and
IY1993 SAIPE estimates should be averaged, and those average poverty rates be multiplied by the IY1993 estimate of
total school-age children in the county. The resulting “combined estimate” of school-age children in poor families was
used in calculating Title I-A grants for FY1997.
35
From the beginning of the Title I-A program in FY1966 until FY1999, LEA grants were calculated by ED on a
county basis, and SEAs suballocated these amounts by LEA in the majority of states where LEA and county boundaries
(continued...)
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
The latest available poverty estimates from SAIPE are used to calculate each year’s Title I-A
grants. The SAIPE estimates are updated every year. As of this writing, the latest SAIPE data are
for income year 2007; these estimates were initially published in December 2008, and will be
used to calculate FY2009 Title I-A allocations. For IY1993 through IY1999 (FY1997-2002 Title
I-A grants), these estimates were updated every two years. Since IY1999 (Title I-A grants from
FY2003 through the present), they have been updated annually. There is a two-year gap in the
income year for SAIPE estimates used to calculate FY2009 Title I-A grants (IY2007) versus
FY2008 grants (IY2005) because Census has reduced the time required to develop the SAIPE
estimates (previously the gap was three years).
SAIPE is not a survey of households separate from other federal surveys conducted by the Census
Bureau or other agencies. SAIPE data are indirect estimates, produced through statistical
modeling of data from the most recent decennial census, other Census Bureau household surveys,
primarily the American Community Survey (ACS),36 and administrative records, such as federal
income tax returns, Food Stamp and Supplemental Security Income program participation, and
income data from the Bureau of Economic Analysis of the Department of Commerce.
The provision for use of population updates was added to Title I-A in an attempt to distribute
funds on the basis of the latest available, reliable data on the distribution of school-age children in
poor families among states and localities, and to try to minimize the considerable disruption that
had occurred previously with the introduction of new population data only once every 10 years.
However, somewhat unexpectedly, the updates themselves have caused significant shifts in
allocation shares among states and regions. With the publication of each set of SAIPE estimates,
shifts in the estimated number of school-age children in poor families have generally been
relatively modest for most states, but there have always been a number of states (and LEAs) with
quite substantial estimated shifts over a one- or two-year period.
Annual Shifts in Poverty Estimates
Table 9 provides data from the last four series of SAIPE estimates that have been, or will be, used
to calculate Title I-A grants, those for income years 2003 (FY2006), 2004 (FY2007), 2005
(FY2008) and 2007 (FY2009). It provides each state’s estimated number of school-age children
in poor families, and the percentage change in this estimated number from the previous year.37
(...continued)
are not contiguous. While estimates of school-age children in poor families for LEAs were produced after the 1970,
1980, and 1990 Censuses, such LEA level estimates were considered to be insufficiently reliable to serve as a basis for
allocating funds under Title I-A. The FY1999 Title I-A grants were based on the initial set of SAIPE estimates for
LEAs, based on income in 1995 (previously, SAIPE published estimates only for states and counties).
36
The ACS is a relatively new annual sample survey intended to provide a wide range of demographic, housing, social
and economic data. For further information, see http://www.census.gov/acs/www/SBasics/What/What1.htm. Previous
to income year 2005 (the first year of full implementation of the ACS), the SAIPE program relied primarily on data
from the Annual Social and Economic Supplement to the Census Bureau’s ongoing Current Population Survey (CPS).
The CPS is an annual survey of a nationally representative sample of households. The CPS household sample is much
smaller than the sample surveyed with respect to income and poverty status in either a decennial census or the ACS.
37
The percentage change figures in Table 9 show the percentage change in each state’s estimated number of schoolage children in poor families. During periods when changes in the national aggregate estimate of school-age children in
poor families are relatively large, it may be more instructive to consider each state’s percentage share of the national
total estimated number of school-age children in poor families, and the percentage change in the percentage share. This
is because Title I-A grants are not entitlements, the level of which would adjust directly to changes in the number of
formula children, rather they are always subject to an annually set appropriations level. However, over the period
IY2003-IY2007, the aggregate change in the estimated number of school-age children in poor families was relatively
small, and state changes in percentage share are quite similar to state changes in the number of such children.
Congressional Research Service
35
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Table 9. State Estimated Number of School-Age Children in Poor Families, Income Years 2003-2007
Estimated
Children Aged
5-17 in Poor
Families,
IY2003
Estimated
Children Aged
5-17 in Poor
Families,
IY2004
Percentage
Change in
Estimated
Number,
IY2004 vs.
IY2003
Estimated
Children
Aged 5-17 in
Poor Families,
IY2005
Alabama
165,225
160,787
-2.7%
172,197
Alaska
14,396
14,841
3.1%
Arizona
214,052
214,962
Arkansas
104,883
California
Percentage
Change in
Estimated
Number,
IY2005 vs.
IY2004
Estimated
Children Aged
5-17 in Poor
Families,
IY2007
Percentage
Change in
Estimated
Number,
IY2007 vs.
IY2005
7.1%
174,665
1.4%
16,841
13.5%
13,787
-18.1%
0.4%
205,175
-4.6%
209,683
2.2%
95,393
-9.0%
108,273
13.5%
113,370
4.7%
1,292,920
1,225,762
-5.2%
1,197,835
-2.3%
1,062,605
-11.3%
Colorado
96,357
94,396
-2.0%
101,811
7.9%
114,762
12.7%
Connecticut
55,972
64,564
15.4%
62,095
-3.8%
58,597
-5.6%
Delaware
15,986
15,877
-0.7%
17,149
8.0%
18,289
6.6%
District of Columbia
21,775
19,536
-10.3%
19,634
0.5%
18,995
-3.3%
Florida
510,674
447,172
-12.4%
474,430
6.1%
437,055
-7.9%
Georgia
291,342
296,706
1.8%
304,220
2.5%
318,255
4.6%
Hawaii
26,812
19,121
-28.7%
23,729
24.1%
18,364
-22.6%
Idaho
36,037
33,487
-7.1%
39,106
16.8%
39,046
-0.2%
Illinois
333,218
369,244
10.8%
341,763
-7.4%
348,638
2.0%
Indiana
129,513
155,506
20.1%
166,214
6.9%
166,365
0.1%
Iowa
49,842
53,683
7.7%
57,449
7.0%
58,426
1.7%
Kansas
55,425
59,392
7.2%
60,203
1.4%
61,149
1.6%
Kentucky
137,877
135,287
-1.9%
146,404
8.2%
149,095
1.8%
Louisiana
207,713
201,957
-2.8%
220,555
9.2%
191,094
-13.4%
Maine
25,041
23,769
-5.1%
28,864
21.4%
27,487
-4.8%
Maryland
100,977
107,072
6.0%
98,407
-8.1%
92,601
-5.9%
Massachusetts
112,900
121,129
7.3%
129,183
6.6%
126,588
-2.0%
State
CRS-36
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Estimated
Children Aged
5-17 in Poor
Families,
IY2003
Estimated
Children Aged
5-17 in Poor
Families,
IY2004
Percentage
Change in
Estimated
Number,
IY2004 vs.
IY2003
Estimated
Children
Aged 5-17 in
Poor Families,
IY2005
Percentage
Change in
Estimated
Number,
IY2005 vs.
IY2004
Estimated
Children Aged
5-17 in Poor
Families,
IY2007
Percentage
Change in
Estimated
Number,
IY2007 vs.
IY2005
Michigan
250,954
276,639
10.2%
308,636
11.6%
308,714
0.0%
Minnesota
77,036
82,727
7.4%
87,697
6.0%
92,798
5.8%
Mississippi
139,285
142,059
2.0%
148,662
4.6%
144,806
-2.6%
Missouri
146,376
158,877
8.5%
170,436
7.3%
160,841
-5.6%
Montana
25,841
22,842
-11.6%
26,584
16.4%
25,988
-2.2%
Nebraska
32,497
32,859
1.1%
38,637
17.6%
39,327
1.8%
Nevada
59,385
60,862
2.5%
58,687
-3.6%
62,021
5.7%
New Hampshire
13,110
17,353
32.4%
17,856
2.9%
17,188
-3.7%
New Jersey
154,881
148,348
-4.2%
165,069
11.3%
154,235
-6.6%
New Mexico
85,364
75,513
-11.5%
82,630
9.4%
78,583
-4.9%
New York
639,014
638,113
-0.1%
594,230
-6.9%
576,131
-3.0%
North Carolina
247,890
252,410
1.8%
287,894
14.1%
275,164
-4.4%
North Dakota
11,284
10,712
-5.1%
11,872
10.8%
11,671
-1.7%
Ohio
258,469
288,329
11.6%
322,771
11.9%
323,397
0.2%
Oklahoma
116,879
103,472
-11.5%
120,814
16.8%
121,880
0.9%
Oregon
93,136
88,798
-4.7%
99,462
12.0%
91,925
-7.6%
Pennsylvania
274,501
289,566
5.5%
305,450
5.5%
293,616
-3.9%
Puerto Rico
400,212
399608
-0.2%
404,549
1.2%
389,831
-3.6%
Rhode Island
27,378
28,943
5.7%
28,272
-2.3%
25,763
-8.9%
South Carolina
138,184
143,249
3.7%
150,806
5.3%
142,963
-5.2%
South Dakota
19,212
20,000
4.1%
20,442
2.2%
20,625
0.9%
Tennessee
171,430
170,654
-0.5%
194,253
13.8%
206,308
6.2%
Texas
902,259
909,592
0.8%
983,654
8.1%
960,471
-2.4%
State
CRS-37
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Estimated
Children Aged
5-17 in Poor
Families,
IY2003
Estimated
Children Aged
5-17 in Poor
Families,
IY2004
Percentage
Change in
Estimated
Number,
IY2004 vs.
IY2003
Estimated
Children
Aged 5-17 in
Poor Families,
IY2005
Percentage
Change in
Estimated
Number,
IY2005 vs.
IY2004
Estimated
Children Aged
5-17 in Poor
Families,
IY2007
Percentage
Change in
Estimated
Number,
IY2007 vs.
IY2005
Utah
49,493
52,513
6.1%
51,517
-1.9%
55,841
8.4%
Vermont
9,667
8,424
-12.9%
10,753
27.6%
9,809
-8.8%
Virginia
148,985
143,376
-3.8%
153,431
7.0%
152,581
-0.6%
Washington
138,385
144,330
4.3%
145,368
0.7%
141,844
-2.4%
West Virginia
63,540
55,490
-12.7%
64,238
15.8%
56,406
-12.2%
Wisconsin
96,394
126,498
31.2%
114,754
-9.3%
120,571
5.1%
Wyoming
9,807
8,695
-11.3%
9,129
5.0%
9,461
3.6%
8,799,785
8,830,494
0.3%
9,170,090
3.8%
8,889,675
-3.1%
State
Total
Source: U.S. Census Bureau, Small Area Income and Poverty Estimates program.
Note: No data are shown above for IY2006 because SAIPE data for that year were not used in the calculation of ESEA Title I-A grants. Estimates for IY2005 were used to
calculate FY2008 Title I-A grants while IY2007 estimates will be used to calculate FY2009 grants. Thus, the change from IY2005 to IY2007 estimates represents a one year
change in terms of Title I-A allocations.
CRS-38
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
As seen in Table 9, for many states there is a substantial degree of year-to-year variation in these
poverty estimates. For IY2004 compared to IY2003, the national aggregate poverty estimate
increased by 0.3%, virtually no change at all, while the estimates for individual states ranged
from -28.7% to +32.4%. Comparing IY2005 with IY2004, while the national aggregate poverty
estimate increased by 3.8%, the estimates for individual states ranged from -9.3% to +27.6%.
Finally, comparing IY2007 with IY2005, the national poverty estimate declined by 3.1%, while
the estimates for individual states varied from -22.6% to +12.7%.
Not only is the range in annual shifts in SAIPE poverty estimates for the states overall quite large;
these estimates also fluctuate quite substantially from year to year for a number of individual
states. As is illustrated in Table 10, below, the estimates for several states have fluctuated widely
in recent years, at a time when the estimated aggregate change was relatively small. While several
of these are states with relatively small populations (e.g., Alaska, Montana, New Hampshire, and
Vermont), this group also includes such relatively large states as Florida and Wisconsin, as well
as the moderate size states of Hawaii and West Virginia.
Table 10. Estimated Annual Changes in Estimated Number of School-Age Children
in Poor Families, Income Years 2003-2007, Selected States
Percentage Change
in Estimated
Number of SchoolAge Children in Poor
Families, IY2004 vs.
IY2003
Percentage Change
in Estimated
Number of SchoolAge Children in Poor
Families, IY2005 vs.
IY2004
Percentage Change
in Estimated
Number of SchoolAge Children in Poor
Families, IY2007 vs.
IY2005
Alaska
3.1%
13.5%
-18.1%
Florida
-12.4%
6.1%
-7.9%
Hawaii
-28.7%
24.1%
-22.6%
Louisiana
-2.8%
9.2%
-13.4%
Montana
-11.6%
16.4%
-2.2%
New Hampshire
32.4%
2.9%
-3.7%
Vermont
-12.9%
27.6%
-8.8%
West Virginia
-12.7%
15.8%
-12.2%
Wisconsin
31.2%
-9.3%
5.1%
State
Source: Table prepared by CRS.
During the initial period of use of the SAIPE poverty estimates, special provisions were added to
FY1997-2001 appropriations legislation for Title I-A to limit the impact of the updates. As was
discussed above, in all years, the Title I-A authorizing statute provides for “hold harmless” rates
of 85-95% of the previous year grant, applied at the LEA level. The FY1997-2001 appropriations
acts for ED provided for higher 100% hold harmless rates, applied either at the state or the state
plus LEA levels.38
38
Separately, for FY1996 only, a 100% hold harmless rate for LEAs was provided under the 1994 ESEA
reauthorization legislation. Also note that the FY2001 appropriations provisions were somewhat complex, but
ultimately amounted to a 100% hold harmless rate.
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
These high hold harmless rates were applied during a period when there was little or no growth in
aggregate Title I-A funding and substantial shifts in the estimated number of school-age children
in poor families for many states and LEAs. As a result of 100% hold harmless rates and little
growth in total appropriations, state and LEA funding shares remained quite static during this
FY1997-2001 period.
Beginning with FY2002, the 100% hold harmless rates were dropped from annual appropriations
acts for Title I-A. This shift was facilitated by a combination of significantly increased total
funding (an increase of 18% for FY2002 compared to FY2001), and initial funding of two
formulas (the Targeted Grant and EFIG formulas) that resulted in each state (although not each
LEA) receiving an increase in Title I-A funds for FY2002. As the rate of annual appropriations
increases declined over the period of FY2003-2007, not only a substantial number of LEAs, but
also (beginning with FY200439) a number of states experienced annual reductions in Title I-A
grants. Finally, for FY2008, Title I-A appropriations rose by 8.3%, and only one state received a
smaller allocation for FY2008 than for FY2007.
Selected Alternatives to Use of Only the Most Current Poverty Estimates
Concern about the variability of the SAIPE poverty estimates for many states may lead to
proposals to limit resulting decreases in Title I-A grants, beyond the effects of the statutory hold
harmless provisions for LEAs. The remainder of this section of the report provides a discussion
and analysis of four possible options for limiting year-to-year reductions in Title I-A grants
resulting from fluctuations in poverty estimates.
Option 1: Higher Hold Harmless Rates
One option might be a return to higher (100%) hold harmless rates in annual appropriations
legislation, applied at either the LEA or state level, as occurred between FY1997 and 2001. This
would have the effect of eliminating reductions in Title I-A grants overall, while limiting
increases to states or LEAs with rising estimated numbers of school-age children in poor families.
If there were little or no increase in total Title I-A appropriations, this would result in a static
geographic distribution of funds, as occurred between FY1997 and FY2001.
A variation of this option would address the particular problems of LEAs that have experienced
dramatic shifts in funding from one year to the next as their school-age child poverty rate varies
by small amounts around the Targeted Grant and EFIG formula child eligibility threshold of
5.0%. Large swings in funding make it exceptionally difficult to use Title I-A funds efficiently.
The four-year phase-out of hold-harmless provisions, now applied only to Concentration Grants,
might be extended to Targeted and EFIG grants.
39
For FY2003, three states were initially projected to lose funds under Title I-A in comparison to FY2002. However,
the Emergency Supplemental Appropriations Act, 2003, provided for the transfer of an additional $4,353,368 in
unobligated FY2003 funds from a variety of ED programs to Title I-A. These funds were allocated to the three states
for which the initial FY2003 allocations were less than their FY2002 allocation; the amount transferred brought the
FY2003 allocation for each of these states up to its FY2002 level.
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Option 2: Use of the Average of the Latest and Second Latest Poverty Estimates
for All LEAs
A second alternative for limiting the impact of large variations in annual poverty estimates would
be to combine the most recent poverty estimates with the estimates for one or more immediately
preceding years, in order to make the transition to the most recent estimates more gradual for
states or LEAs where estimated changes are relatively large. This could be accomplished by using
the average of the poverty estimates for the last two or even three years in the Title I-A allocation
formulas. Table 11, below, illustrates the estimated impact of this approach on grants for FY2008.
Actual FY2008 Title I-A grants under current law (i.e., based on IY2005 poverty estimates) are
compared to estimates under an alternative formula using the average of the latest and the second
most recent poverty estimates (i.e., those for IY2005 and IY2004) as the poverty population
factor. The estimated FY2008 grants based on the average (two-year) poverty estimates are
compared to actual grants for FY2008 (Column E) and FY2007 (Column G), along with a
comparison of actual grants for FY2008 compared to FY2007 (Col. F).
As mentioned earlier, with a relatively substantial (8.3%) funding increase for FY2008 over
FY2007, under current law only one state (Wisconsin) received a lower grant for FY2008 than for
FY2007 (a reduction of 1.3%). For the other states, the rate of increase for FY2008 over FY2007
ranged from 0.1% to 20.8% (Column F). As seen in Table 11 (Column G), under the alternative
formula, all states are estimated to have received higher grants for FY2008 compared to FY2007,
with increases ranging from 1.8% to 16.1%. Thus, as expected, the range in variation from
previous year (FY2007) grants is somewhat less under the alternative formula (1.8% to 16.1%)
than under current law (-1.3% to 20.8%). Comparing estimated FY2008 grants under the
alternative formula to actual FY2008 grants (Column E of Table 11), estimated differences range
from -4.3% (Maine) to 5.9% (Nevada).
Option 3: Use of the Greater of the Latest or the Average of the Latest and
Second Latest Poverty Estimates for Each LEA
A third approach, illustrated in Table 12, would be to use the greater of: (i) the latest poverty
estimate, or (ii) the average of the latest and the previous year estimate for each LEA. Under this
alternative, if the latest poverty estimate is higher than the one for the previous year for an LEA,
then only the latest estimate is used in calculating grants. Alternatively, if the latest poverty
estimate for an LEA is lower than the one for the previous year, then the average of the latest and
the immediately preceding estimate is used. As a result, areas with estimated increases in poverty
receive “credit” for that increase, while losses are cushioned for LEAs with estimated decreases
in poverty. This would have a more limited impact on grants than the use of the average of the
poverty estimates for the last two years for all LEAs.
As seen in Table 12 (Column G), under this alternative formula, all states are estimated to have
received higher grants for FY2008 compared to FY2007, with increases ranging from 0.5% to
19.9%. This range of variation falls in between the wider range under current law (-1.3% to
20.8%—Column F) and the somewhat more narrow range under the alternative formula discussed
in option 2 (1.8% to 16.1%). Comparing estimated FY2008 grants under the alternative formula
to actual FY2008 grants (Column E of Table 12), estimated differences fall within the relatively
narrow range of -1.5% (Puerto Rico) to 2.5% (Connecticut).
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Table 11. State Total Grants under Title I-A, ESEA: Actual Grants for FY2007 and FY2008 Compared to Estimated Grants
Based on the Average of IY2004 and IY2005 Estimates of School-Age Children in Poor Families
A
B
C
D
E
F
G
State
FY2007 Actual Grant
FY2008 Actual Grant
FY2008 Estimated Grant Using
Averaged Poverty Estimates
Col. D Col. C, %
Col. CCol. B, %
Col. D Col. B, %
$12,706,341,000
$13,755,995,000
$13,755,995,000
0.0%
8.3%
8.3%
Alabama
$194,251,000
$215,192,000
$212,462,000
-1.3%
10.8%
9.4%
Alaska
$34,025,000
$38,846,000
$38,452,000
-1.0%
14.2%
13.0%
Arizona
$263,204,000
$274,777,000
$278,525,000
1.3%
4.4%
5.8%
Arkansas
$122,031,000
$144,268,000
$140,185,000
-2.8%
18.2%
14.9%
California
$1,643,496,000
$1,698,808,000
$1,724,902,000
1.6%
3.4%
5.0%
Colorado
$123,928,000
$135,392,000
$134,102,000
-0.9%
9.2%
8.2%
Connecticut
$111,879,000
$115,562,000
$116,648,000
0.9%
3.3%
4.3%
Delaware
$34,110,000
$38,380,000
$38,173,000
-0.5%
12.5%
11.9%
District of Columbia
$46,026,000
$47,295,000
$47,981,000
1.4%
2.8%
4.2%
Florida
$589,157,000
$656,255,000
$662,416,000
1.0%
11.4%
12.4%
Georgia
$410,011,000
$446,271,000
$450,508,000
1.0%
8.8%
9.9%
Hawaii
$39,639,000
$44,337,000
$42,678,000
-3.7%
11.9%
7.7%
Idaho
$41,327,000
$46,662,000
$45,938,000
-1.6%
12.9%
11.2%
Illinois
$593,136,000
$593,980,000
$604,850,000
1.9%
0.1%
2.0%
Indiana
$230,085,000
$247,109,000
$243,299,000
-1.5%
7.4%
5.7%
Iowa
$69,214,000
$72,717,000
$72,075,000
-0.8%
5.1%
4.1%
Kansas
$88,061,000
$95,359,000
$98,042,000
2.7%
8.3%
11.3%
Kentucky
$185,854,000
$208,551,000
$205,444,000
-1.5%
12.2%
10.5%
Louisiana
$277,650,000
$294,843,000
$291,151,000
-1.2%
6.2%
4.9%
Maine
$43,870,000
$51,525,000
$49,360,000
-4.3%
17.4%
12.5%
United States
CRS-42
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
A
B
C
D
E
F
G
State
FY2007 Actual Grant
FY2008 Actual Grant
FY2008 Estimated Grant Using
Averaged Poverty Estimates
Col. D Col. C, %
Col. CCol. B, %
Col. D Col. B, %
Maryland
$188,034,000
$192,239,000
$201,638,000
4.8%
2.2%
7.2%
Massachusetts
$211,607,000
$233,354,000
$229,240,000
-1.9%
10.3%
8.3%
Michigan
$460,302,000
$527,255,000
$510,710,000
-3.1%
14.5%
11.0%
Minnesota
$114,583,000
$126,936,000
$125,733,000
-0.9%
10.8%
9.7%
Mississippi
$174,679,000
$187,346,000
$187,871,000
0.2%
7.3%
7.6%
Missouri
$201,452,000
$225,205,000
$223,161,000
-0.9%
11.8%
10.8%
Montana
$38,635,000
$43,555,000
$42,545,000
-2.3%
12.7%
10.1%
Nebraska
$50,662,000
$60,246,000
$57,667,000
-4.2%
18.9%
13.8%
Nevada
$80,299,000
$80,755,000
$85,544,000
5.9%
0.6%
6.5%
New Hampshire
$34,248,000
$38,198,000
$38,196,000
-0.0%
11.5%
11.5%
New Jersey
$252,409,000
$286,765,000
$275,943,000
-3.8%
13.6%
9.3%
New Mexico
$103,847,000
$113,156,000
$111,672,000
-1.3%
9.0%
7.5%
New York
$1,210,071,000
$1,226,786,000
$1,267,983,000
3.3%
1.4%
4.8%
North Carolina
$301,104,000
$358,570,000
$347,188,000
-3.2%
19.1%
15.3%
North Dakota
$29,825,000
$33,742,000
$33,306,000
-1.3%
13.1%
11.7%
Ohio
$449,255,000
$511,797,000
$496,022,000
-3.1%
13.9%
10.4%
Oklahoma
$128,266,000
$148,406,000
$142,748,000
-3.9%
15.7%
11.3%
Oregon
$121,425,000
$139,987,000
$136,136,000
-2.7%
15.3%
12.1%
Pennsylvania
$516,459,000
$565,518,000
$561,609,000
-0.7%
9.5%
8.7%
Puerto Rico
$455,589,000
$510,525,000
$528,108,000
3.4%
12.1%
15.9%
Rhode Island
$50,390,000
$52,978,000
$53,402,000
0.8%
5.1%
6.0%
South Carolina
$187,902,000
$205,597,000
$206,275,000
0.4%
9.4%
9.8%
South Dakota
$37,274,000
$41,539,000
$41,607,000
0.2%
11.4%
11.6%
Tennessee
$205,728,000
$239,071,000
$232,300,000
-2.9%
16.2%
12.9%
$1,169,500,000
$1,299,356,000
$1,276,395,000
-1.8%
11.1%
9.1%
Texas
CRS-43
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
A
B
C
D
E
F
G
State
FY2007 Actual Grant
FY2008 Actual Grant
FY2008 Estimated Grant Using
Averaged Poverty Estimates
Col. D Col. C, %
Col. CCol. B, %
Col. D Col. B, %
Utah
$58,197,000
$60,019,000
$61,594,000
2.6%
3.1%
5.8%
Vermont
$27,199,000
$32,862,000
$31,571,000
-3.9%
20.8%
16.1%
Virginia
$204,733,000
$226,096,000
$225,253,000
-0.3%
10.4%
10.0%
Washington
$182,795,000
$191,853,000
$194,708,000
1.5%
5.0%
6.5%
West Virginia
$89,221,000
$99,607,000
$96,055,000
-3.5%
11.6%
7.7%
Wisconsin
$201,601,000
$199,030,000
$205,173,000
3.1%
-1.3%
1.8%
Wyoming
$28,094,000
$31,516,000
$31,453,000
-0.2%
12.2%
12.0%
Source: Actual FY2007 and FY2008 grants under current law are provided by the U.S. Department of Education. Estimated FY2008 grants based on the average of IY2004
and IY2005 poverty estimates were prepared by CRS. Table prepared by CRS.
Note: The estimated FY2008 grants are provided solely to assist in comparisons of the relative impact of alternative formulas and funding levels in the legislative process.
They are not intended to predict specific amounts that states will receive.
CRS-44
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Table 12. ESEA Title I, Part A, Actual Grants for FY2007 and FY2008 Compared to Estimated FY2008 Grants Using the
Greater of: (i) Poverty Estimates for Income Year 2005 (FY2008) or (ii) the Average of Poverty Estimates for Income Years
2004 (FY2007) and 2005 (FY2008) for Each LEA
A
C
D
E
F
G
FY2007 Actual Grant
FY2008 Actual Grant
FY2008 Estimated Grant
Using Modified Poverty
Estimates
Col. D Col. C, %
Col. C Col. B, %
Col. D Col. B, %
$12,706,341,000
$13,755,995,000
$13,755,995,000
0.0%
8.3%
8.3%
Alabama
$194,251,000
$215,192,000
$213,686,000
-0.8%
10.8%
10.0%
Alaska
$34,025,000
$38,846,000
$38,648,000
-0.5%
14.2%
13.6%
Arizona
$263,204,000
$274,777,000
$278,205,000
1.2%
4.4%
5.7%
Arkansas
$122,031,000
$144,268,000
$142,369,000
-1.3%
18.2%
16.7%
California
$1,643,496,000
$1,698,808,000
$1,704,364,000
0.4%
3.4%
3.7%
Colorado
$123,928,000
$135,392,000
$133,860,000
-1.1%
9.2%
8.0%
Connecticut
$111,879,000
$115,562,000
$118,434,000
2.5%
3.3%
5.9%
Delaware
$34,110,000
$38,380,000
$38,188,000
-0.5%
12.5%
12.0%
District of Columbia
$46,026,000
$47,295,000
$46,971,000
-0.7%
2.8%
2.1%
Florida
$589,157,000
$656,255,000
$650,338,000
-0.9%
11.4%
10.4%
Georgia
$410,011,000
$446,271,000
$446,194,000
0.0%
8.8%
8.8%
Hawaii
$39,639,000
$44,337,000
$43,935,000
-0.9%
11.9%
10.8%
Idaho
$41,327,000
$46,663,000
$46,569,000
-0.2%
12.9%
12.7%
Illinois
$593,136,000
$593,980,000
$606,656,000
2.2%
0.1%
2.3%
Indiana
$230,085,000
$247,109,000
$247,784,000
0.3%
7.4%
7.7%
Iowa
$69,214,000
$72,717,000
$72,487,000
-0.3%
5.1%
4.7%
Kansas
$88,061,000
$95,359,000
$96,331,000
0.9%
8.3%
9.4%
Kentucky
$185,854,000
$208,551,000
$207,191,000
-0.6%
12.2%
11.5%
Louisiana
$277,650,000
$294,843,000
$291,772,000
-1.0%
6.2%
5.1%
Maine
$43,870,000
$51,525,000
$51,186,000
-0.7%
17.4%
16.7%
State
United States
CRS-45
B
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
A
C
D
E
F
G
FY2007 Actual Grant
FY2008 Actual Grant
FY2008 Estimated Grant
Using Modified Poverty
Estimates
Col. D Col. C, %
Col. C Col. B, %
Col. D Col. B, %
Maryland
$188,034,000
$192,239,000
$195,258,000
1.5%
2.2%
3.8%
Massachusetts
$211,607,000
$233,354,000
$234,399,000
0.3%
10.3%
10.8%
Michigan
$460,302,000
$527,255,000
$522,951,000
-0.8%
14.5%
13.6%
Minnesota
$114,583,000
$126,936,000
$126,864,000
-0.0%
10.8%
10.7%
Mississippi
$174,679,000
$187,346,000
$187,220,000
-0.1%
7.3%
7.2%
Missouri
$201,452,000
$225,205,000
$224,749,000
-0.2%
11.8%
11.6%
Montana
$38,635,000
$43,555,000
$43,468,000
-0.2%
12.7%
12.5%
Nebraska
$50,662,000
$60,246,000
$59,471,000
-1.3%
18.9%
17.4%
Nevada
$80,299,000
$80,755,000
$82,146,000
1.7%
0.6%
2.3%
New Hampshire
$34,248,000
$38,198,000
$38,255,000
0.1%
11.5%
11.7%
New Jersey
$252,409,000
$286,765,000
$286,417,000
-0.2%
13.6%
13.5%
New Mexico
$103,847,000
$113,156,000
$111,977,000
-1.0%
9.0%
7.8%
New York
$1,210,071,000
$1,226,786,000
$1,248,212,000
1.7%
1.4%
3.2%
North Carolina
$301,104,000
$358,570,000
$353,723,000
-1.3%
19.1%
17.5%
North Dakota
$29,825,000
$33,742,000
$33,530,000
-0.6%
13.1%
12.4%
Ohio
$449,255,000
$511,797,000
$510,172,000
-0.3%
13.9%
13.6%
Oklahoma
$128,266,000
$148,406,000
$146,612,000
-1.3%
15.7%
14.3%
Oregon
$121,425,000
$139,987,000
$138,357,000
-1.1%
15.3%
13.9%
Pennsylvania
$516,459,000
$565,518,000
$562,552,000
-0.5%
9.5%
8.9%
Puerto Rico
$455,589,000
$510,525,000
$503,311,000
-1.5%
12.1%
10.5%
Rhode Island
$50,390,000
$52,978,000
$53,371,000
0.7%
5.1%
5.9%
South Carolina
$187,902,000
$205,598,000
$203,574,000
-1.0%
9.4%
8.3%
South Dakota
$37,274,000
$41,539,000
$41,559,000
0.0%
11.4%
11.5%
Tennessee
$205,728,000
$239,072,000
$235,834,000
-1.4%
16.2%
14.6%
State
CRS-46
B
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
A
C
D
E
F
G
FY2007 Actual Grant
FY2008 Actual Grant
FY2008 Estimated Grant
Using Modified Poverty
Estimates
Col. D Col. C, %
Col. C Col. B, %
Col. D Col. B, %
Texas
$1,169,500,000
$1,299,356,000
$1,294,962,000
-0.3%
11.1%
10.7%
Utah
$58,197,000
$60,019,000
$60,150,000
0.2%
3.1%
3.4%
Vermont
$27,199,000
$32,862,000
$32,609,000
-0.8%
20.8%
19.9%
Virginia
$204,733,000
$226,096,000
$224,376,000
-0.7%
10.4%
9.6%
Washington
$182,795,000
$191,853,000
$192,495,000
0.4%
5.0%
5.3%
West Virginia
$89,221,000
$99,607,000
$98,225,000
-1.4%
11.6%
10.1%
Wisconsin
$201,601,000
$199,030,000
$202,654,000
1.8%
-1.3%
0.5%
Wyoming
$28,094,000
$31,516,000
$31,375,000
-0.4%
12.2%
11.7%
State
B
Source: Actual FY2007 and FY2008 grants under current law are provided by the U.S. Department of Education. Estimated FY2008 grants based on the greater of IY2004
and IY2005 poverty estimates were prepared by CRS. Table prepared by CRS.
Note: The estimated FY2008 grants are provided solely to assist in comparisons of the relative impact of alternative formulas and funding levels in the legislative process.
They are not intended to predict specific amounts that states will receive.
CRS-47
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Those concerned about the impact of frequent, sometimes quite large, variations in poverty
estimates and subsequent Title I-A grants on program operations might support the use of twoyear averages for poverty data, as reflected in the alternative formulas of Tables 11 and 12.
Given the underlying reliance of the SAIPE estimation process on sample survey data, the
reliability of the estimates should be increased through combination of estimates for multiple
years. The most recent poverty estimates would still be used, but introduced more gradually.
States and LEAs would be allowed more time to adjust to either increases or decreases in
allocations, and program stability would be enhanced.
However, opponents of a shift from the current practice of always using the latest available
poverty estimates would argue that averaging poverty estimates over two years, or choosing the
greater of the latest estimates or a two-year average for each LEA, would delay implementation
of updates. Under current practice, estimates based on income for calendar year 2007 will be
applied to grants for FY2009, the 2009-2010 school year; thus, there is a two- to three-year lag
between the income year and the program year. Use of one of the alternatives discussed above
under Options 2 and 3 would add, in part, another year to this time lag. Further, the most severe
negative impacts of reductions in poverty estimates are already limited by the LEA hold harmless
provisions, under which grants may not fall below 85-95% of the previous year amount, with
high poverty LEAs offered the greatest degree of protection. Finally, if the SAIPE process is
deemed to provide reliable poverty estimates, that are preferable to those from other sources,
some ask why should not the latest available estimates be used in calculating Title I-A grants?
Option 4: Limit the Degree of Annual Decreases in Poverty Estimates
Another option, given that annual shifts in poverty estimates have thus far been especially large
for a small number of states, would be to place a limit on the size of these shifts. Either a floor, or
a floor and ceiling, might be placed on the annual percentage change in either each state’s
estimated number, or on each state’s share of the national total estimated number, of school-age
children in poor families. For example, it might be provided that no state’s percentage share of the
national total estimated number of school-age children in poor families could decline by more
than 10% compared to the previous year. If the estimated decline were greater than 10%, the
estimate used in the Title I-A allocation formulas would be set at the level representing a 10%
percentage share reduction. This example is based on state percentage shares, rather than the
estimated number, of school-age children in poor families in order to adjust for nationwide
increases or decreases in these estimates. Also, as mentioned earlier (footnote 37), given a fixed
annual total appropriation for Title I-A, changes in each state’s percentage share of the total
estimated number of school-age children in poor families are more closely related to trends in
allocations than are changes in the estimated number of such children.
Such a provision—a 10% limit on reductions in state share of poverty estimates—would have
affected one state for FY2005, four states for FY2006, nine states for FY2007, and four states for
FY2008. Grants to those states would have increased, while those to most other states would have
declined.
Has the Targeting of Title I-A Funds on High Poverty LEAs
Increased Since 2001?
For many years, a primary issue regarding the Title I-A allocation formulas has been the extent to
which funds are targeted on high-poverty LEAs. Over 90% of the nation’s LEAs receive grants
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
under ESEA Title I-A, largely because the eligibility thresholds for three of the four allocation
formulas, as described above, are relatively low. In general, all LEAs receive Title I-A grants
except those that have extraordinarily low school-age poverty rates or have extremely few
pupils.40 A few LEAs (including certain charter schools that are treated as separate LEAs under
state law) are eligible for relatively small Title I-A grants, but choose not to participate in the
program, at least in part because the responsibilities accompanying participation are perceived to
exceed the value of the prospective grants.
Table 13, below, presents the distribution of Title I-A grants among LEAs grouped by poverty
rate quintile. 41 Each quintile contains LEAs with one-fifth of the nation’s total estimated number
of school-age children in poor families, on the basis of the Census Bureau IY2005 population
estimates used in calculating FY2008 grants. Table 13 lists the percentage share (of the national
total) of Title I-A grants that are allocated to LEAs in each poverty quintile. These data are
provided separately for each of the four Title I-A allocation formulas, as well as for total grants
for FY2008.42
As illustrated in Table 13 and Figure 1, below, the share of Title I-A funds allocated to LEAs in
various poverty rate ranges varies significantly among the four allocation formulas. For Basic
Grants, the share is similar for each quintile of LEAs, varying only within the narrow range of
19.2%-21.1%. For Concentration Grants, the share of funds allocated to LEAs in each poverty
rate range is again similar, with the exception of the lowest-poverty quintile, which receives a
much lower share (4.0% of total grants vs. 23.1%-25.2% for the other four quintiles). This
reflects the eligibility threshold for Concentration Grants (formula child rate of at least 15% or
6,500 formula children). Overall, the primary pattern for both Basic and Concentration Grants is
relatively constant shares of funds for all quintiles of LEAs meeting minimum eligibility
thresholds. In other words, grants per poor and other child counted in the Title I-A allocation
formulas are approximately the same for all LEAs meeting the initial eligibility criteria for Basic
and Concentration Grants, whether those LEAs have high, average, or somewhat below average
school-age child poverty rates.
The pattern of distribution of grants under the Targeted and EFIG formulas is somewhat different.
Under each of these formulas, the share of total grants increases steadily from the lowest to the
second-highest poverty rate quintile, then is approximately constant for the 4th and 5th quintiles.
While this partly reflects the slightly higher eligibility threshold for these formulas in comparison
to Basic Grants (5% vs. 2% formula child rate), it primarily results from the structure of these
formulas. Under both the Targeted and EFIG (within-state) formulas, the grant per formula child
continuously increases as either the LEA’s school-age child poverty rate, or its total number of
children counted in the Title I-A formulas, increases. The share of funds going to LEAs in the 5th
quintile (highest poverty rates) under each of these formulas is not substantially higher than the
share going to LEAs with the second highest poverty rates (4th quintile) primarily because of the
40
According to program data for FY2008, approximately 80% of the LEAs receiving no Title I-A grants have an
estimated total number of school-age children of fewer than 100.
41
For the LEA-level analyses in this report, “poverty rates” are based on estimated school-age children in poor families
divided by total school-age population.
42
It should be noted that this analysis is based on LEA grants as calculated by the U.S. Department of Education. It
does not take into consideration the adjustments that SEAs may make to these grants (reservations for state
administration and program improvement, reallocation of funds among small LEAs in selected states, and adjustments
for charter schools and LEA boundary changes). In the aggregate, the impact of this limitation should be quite small.
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
strong influence of high numbers of formula children on the allocation of funds,43 the influence of
the expenditure factor,44 and the cap placed on Targeted Grant formula population weights for
Puerto Rico.45
Table 13. Share of ESEA Title I-A Funds Allocated to LEAs by LEA Poverty Rate
Quintile, FY2008
Poverty Rate Quintile
Title I-A
Formula
1
2
3
4
5
(Poverty
Rates of
13.59% or
Below)
(Poverty
Rates At or
Above
13.59% But
Below
18.64%)
(Poverty
Rates At or
Above
18.64% But
Below
25.73%)
(Poverty
Rates At or
Above
25.73% But
Below
31.37%)
(Poverty
Rates At or
Above
31.37%)
All LEAs
Percentage Share of Total Grants
Total Title I-A
Grants, FY2008
16.5%
19.3%
19.0%
22.9%
22.3%
100.0%
Basic Grants (48%
of FY2008
appropriations)
21.1%
19.7%
19.2%
20.5%
19.5%
100.0%
Concentration
Grants (10% of
FY2008
appropriations)
4.0%
23.1%
23.9%
25.2%
23.9%
100.0%
Targeted Grants
(21% of FY2008
appropriations)
14.5%
18.4%
17.9%
24.8%
24.3%
100.0%
Education Finance
Incentive Grants
(21% of FY2008
appropriations)
14.1%
17.4%
17.6%
25.4%
25.6%
100.0%
Source: Table prepared by CRS.
Notes: Table reads (for example): The quintile of LEAs with the highest school-age child poverty rates received
22.3% of total FY2008 ESEA Title I-A grants, 19.5% of all funds allocated as Basic Grants for FY2008, 23.9% of
Concentration Grants, 24.3% of Targeted Grants, and 25.6% of Education Finance Incentive Grants.
43
With the exception of Puerto Rico, LEAs with the largest numbers of school-age children in poor families tend to
have higher than average, but not among the highest, school-age child poverty rates.
44
LEAs with the highest school-age child poverty rates are frequently located in states with relatively low expenditure
factors.
45
As mentioned in a previous footnote, a cap is placed on the aggregate formula child weighting factor for Puerto Rico,
reducing the share of Targeted Grant funds allocated to this LEA with a very high poverty rate (the highest poverty
quintile).
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Figure 1. Share of ESEA Title I-A Funds Allocated to LEAs by Poverty Rate Quintile, FY2008
Percentage Share of Formula Grants
30%
Q u in tile 1 (lo w e s t)
Q u in tile 2
Q u in tile 3
Q u in tile 4
Q u in tile 5 ( h ig h e s t)
20%
10%
0%
T o ta l T itle I-A G r a n ts
B a s ic G ra n ts
C o n c e n tra tio n G ra n ts
F o r m u la
Source: Figure prepared by CRS.
CRS-51
T a rg e te d G r a n ts
E d u c a tio n F in a n c e
In c e n tiv e G ra n ts
Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Overall, the share of funds allocated to LEAs in the top two poverty rate quintiles is substantially
higher under the Concentration (49.1%), Targeted (49.1%), and especially the EFIG (51.0%)
Grant formulas than under the Basic Grant formula (40.0%). As a result, as long as all additional
funds (i.e., amounts in excess of the previous year appropriation) continue to be allocated under
the Targeted and EFIG Grant formulas, as has been the case each year from FY2002-2009, the
degree of targeting on high poverty LEAs for total Title I-A grants would increase. Thus, overall
targeting on high poverty LEAs has increased since the enactment of the NCLB.
While noteworthy, at least by historical standards, these shifts are nevertheless relatively
marginal. For example, the share of total Title I-A funds allocated to LEAs in the two highest
poverty rate quintiles rose from 42.3% for FY2002 (when Targeted and EFIG Grants were first
funded and Basic Grants constituted 69% of total Title I-A LEA grant appropriations) to 45.2%
for FY2008 (when Basic Grants constitute 48% of total Title I-A LEA grant appropriations).
Another way to evaluate trends in targeting is to compare the share of grants actually allocated to
LEAs in the top two poverty rate quintiles for FY2008 with an estimate of this share if FY2008
funds were allocated in the same manner as in the last pre-NCLB year of FY2001, when 84% of
Title I-A appropriations was allocated under the Basic Grant formula and 16% under
Concentration Grants. Applying that fund distribution from FY2001, 40.6% of FY2008 funds
would have gone to LEAs in the top two poverty rate quintiles versus 45.2% for FY2008 actual
grants.
A partial reason why increases in targeting, measured as above, are relatively marginal is that
allocations under the Targeted and EFIG Grant formulas are highly influenced by the number, as
well as the percentage, of formula children in each LEA, while this sort of targeting analysis
identifies high poverty LEAs only in terms of their percentage of formula children. If “high
poverty” LEAs were defined as those with either high percentages or high numbers of Title I-A
formula children, the estimated increase in targeting would be slightly greater. For example,
defining “high poverty” LEAs as those in one of the top two quintiles in the statutory Targeted
and EFIG Grant formulas (i.e., 7,852 or more formula children, or a formula child percentage of
30.16% or higher), 53.4% of actual FY2008 grants went to such “high poverty” LEAs compared
to an estimated 47.9% under the FY2001 distribution (84% Basic Grants and 16% Concentration
Grants). This difference, of 5.5 percentage points, is slightly higher than the 4.6 percentage point
differential based on poverty rates alone.
Finally, while debates regarding the targeting of Title I-A funds have primarily focused on
shifting fund distribution toward areas with the greatest concentrations of poverty, some have
been concerned about declines in the share of funds going to relatively low poverty LEAs. While
low poverty LEAs may be assumed to have less need for Title I-A assistance in general, they are
experiencing declines in funding at a time when they are subject to substantial and increasing
requirements applicable to all LEAs that participate in Title I-A. In particular, LEAs with a
school-age child poverty rate of between 2.0% and 5.0% are generally eligible only for Basic
Grants, funding for which has declined by 8.0% in nominal terms since enactment of the NCLB,
from $7,169,471,000 for FY2001 to $6,597,946,000 for FY2008.
Congressional Research Service
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Education for the Disadvantaged: Analysis of ESEA Title I-A Allocation Formulas
Should the Population Weighting Factors of the Targeted and EFIG
Formulas Be Modified to More Equally Favor LEAs With Large
Numbers of School-Age Children in Poor Families and LEAs With
High Poverty Rates?
As is discussed above, both the Targeted and the EFIG Grant formulas are designed to allocate to
LEAs increased amounts of aid per formula child as either their school-age child poverty rate or
their total number of formula children rises. The scales of steadily increasing weights applied to
LEA formula child counts would appear to favor LEAs with high poverty rates, because relatively
higher weights are assigned to LEAs with high poverty rates than to those with high numbers of
formula children. For example, in the Targeted Grant formula, the highest weight assigned on the
basis of numbers is 3.0 while the maximum weight assigned on the basis of poverty rates is 4.0.
However, in practice, these formulas tend to favor LEAs with either high numbers of formula
children as well as those with high poverty rates, and in some respects may seem to favor LEAs
with moderately large numbers of formula children over those with moderately high poverty
rates. The major reasons for this effect are that (a) a very large LEA will have a much larger share
of its formula children weighted at the highest point in the scale than will a LEA with a very high
school-age child poverty rate, and (b) LEAs with moderately large numbers of formula children
are treated at least as favorably as LEAs with marginally lower numbers of formula children but
much higher school-age child poverty rates.
One way to view the level of targeting provided under the Targeted and EFIG Grant formulas is
to examine the average grant per formula child for high poverty LEAs versus state averages.
Table 14, below, provides the Title I-A grant per formula child, by formula, for the 15 LEAs in
the nation with the largest number of formula children for FY2008. The table also provides these
statistics for the LEA with the highest poverty rate in these states plus the state average grants per
formula child, by formula. LEAs are compared with others in the same state to adjust for
variations in grants per child arising from statewide factors including the expenditure factor used
in all formulas plus the effort and equity factors of the EFIG formula.
As seen in Table 14, Basic and Concentration Grants per formula child are approximately the
same for all LEAs in the same state (assuming minimum LEA eligibility criteria are met);
variations in grants per formula child result primarily from hold harmless effects. However, LEAs
that are among the 15 largest in the nation receive much higher grants per formula child than
other LEAs in the same state under the Targeted and EFIG Grant formulas. Targeted Grants per
formula child are in many cases more than
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