United States General Accounting Office

GAO Report to Congressional Requesters

August 1996 SCHOOL FINANCE

Options for Improving

Measures of Effort and

Equity in Title I

G O A

years

1921 - 1996

GAO/HEHS-96-142

GAO United States

General Accounting Office

Washington, D.C. 20548

Health, Education, and

Human Services Division

B-274117 

August 30, 1996

The Honorable Jeff Bingaman

The Honorable Christopher Dodd

The Honorable Carol Moseley-Braun

The Honorable Paul Simon

United States Senate

Disparities in per pupil funding for elementary and secondary education

within each state have long been a concern of parents, teachers, state

officials, the courts, and federal officials. Since the early 1970s, these

disparities have led poor districts in more than 40 states to challenge the

constitutionality of their states’ school finance systems. More than half of

the state systems have been challenged since 1989.1

Since the 1960s, federal education funds have been allocated to areas with

high levels of need for additional educational services, such as

compensatory education or bilingual education. During the 1980s this need

increased as the nation’s school-age population became increasingly poor,

racially and ethnically diverse, and at risk of school failure.2

 Successfully

educating at-risk populations depends, in part, upon adequate and

equitable funding. Schools have been addressing the needs of at-risk

children through a variety of compensatory and education reform efforts,

some of which use federal education funds.

The largest single federal elementary and secondary education grant

program to local school districts—$6.7 billion in fiscal year 19963

—is title I

of the Elementary and Secondary Education Act (ESEA) of 1965.4

 The

purpose of title I is to improve the educational opportunities of

educationally deprived children by helping them succeed in regular

programs, attain grade-level proficiency, and improve achievement in

basic and more advanced skills. As reauthorized by P.L. 103-382 in

October 1994, these title I educational services may be financed by four

funding formulas for this common purpose. The four formulas cover basic

1

School Finance: Three States’ Experiences With Equity in School Funding (GAO/HEHS-96-39, Dec. 19,

1995).

2

School-Age Children: Poverty and Diversity Challenge Schools Nationwide (GAO/HEHS-94-132,

Apr. 29, 1994).

3

Under P.L. 104-134, however, about $1.3 billion of this $6.7 billion will not be available for fiscal year

1996 awards (school year 1996-97) until Oct. 1, 1996.

4

We use the term title I to refer to title I, part A, Improving Basic Programs Operated by Local

Educational Agencies, of ESEA, as added by the Improving America’s Schools Act of 1994, P.L.

103-382.

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grants, concentration grants, targeted grants, and Education Finance

Incentive Program grants.5

 The 1994 legislation, for the first time,

authorized funding for the Education Finance Incentive Program

beginning in fiscal year 1996, although no funding was specified in fiscal

year 1996 appropriations for that program or for targeted grants. (See app.

I for a description of these grant programs.)

Many complex policy and technical issues surround policymakers’

decisions about whether to provide title I funding through the Education

Finance Incentive Program formula in future years. The Clinton

administration proposed not funding this program for fiscal year 1997

because “the formula would reward states that make a high effort and are

highly equalized, but it would not consistently target funds on states with

high concentrations of poor children.”6

 Those who support the Education

Finance Incentive Program suggest that if a state’s spending for education

increases and spending disparities among a state’s districts decrease, the

federal government is able to more effectively allocate title I funds to

provide truly supplemental educational resources to disadvantaged

children.7

Title I’s Education Finance Incentive Program would provide additional

funds to states with high levels of “fiscal effort” for education (that is, high

state spending relative to the state’s ability to pay) and equity in per pupil

spending.8

 In our June 1994 correspondence,9 we identified potential

weaknesses in the proposed measures of effort and equity used in the title

I program. In addition, Members of Congress have also called for

improvements in these measures. Consequently, you asked us to provide a

more in-depth analysis of these measures and provide options for

improving them. Specifically, this report

5

The basic grant formula allocates grants on the basis of the number of poor children, while

concentration grants are allocated to areas with concentrations of poor children—those with a poverty

rate over 15 percent or more than 6,500 poor children. Targeted grants further focus grants on the

highest poverty areas by allocating the greatest per pupil funding to areas with the highest poverty

rates or number of children in poverty.

6

See Department of Education, Justifications of Appropriation Estimates to the Congress: Fiscal Year

1997, Vol. I, p. B-20.

7

For a discussion of related title I (formerly known as chapter 1) issues, see Commission on Chapter 1,

Making Schools Work for Children in Poverty: A New Framework Prepared by the Commission on

Chapter 1 (Washington, D.C.: Dec. 1992).

8

An individual state, however, may be relatively high on one measure and relatively low on the other.

For example, Tennessee has achieved a high level of equity in per pupil funding but exerts a low level

of fiscal effort for education.

9

Title I Formula in S. 1513 (GAO/HEHS-94-190R, June 7, 1994).

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• examines the measures now included in title I’s Education Finance

Incentive Program to reflect state fiscal effort for education and equity in

per pupil spending,

• proposes several options for improving these measures,

• describes the characteristics of states with higher levels of effort and

equity under both the current definitions and the options we developed,

and

• proposes alternative ways the options we developed could be used in

allocating funds under the Education Finance Incentive Program.

For our evaluation of the effort and equity factors, we reviewed the

relevant school finance literature and consulted with school finance

experts. On the basis of this review, we developed the following criteria to

assess the quality of the effort factor. The effort factor should (1) include

an indicator of states’ ability to pay that is comprehensive, reflecting all

sources of potential revenue-raising capacity states may use to fund

education; (2) avoid using indicators that are not directly related to state

fiscal effort; and (3) provide a direct incentive for increased effort.

To assess the quality of the equity factor, we adopted the following

criteria: (1) the measure of spending disparities should be comprehensive,

(2) the measure of students’ needs should be as comprehensive as

possible, (3) spending differences should be adjusted for differences in

purchasing power across school districts, and (4) the equity factor should

provide an incentive for states to further reduce spending disparities.

We consulted with experts to review the measures and options we

formulated.10 See appendix II for a full discussion of scope and

methodology. We conducted our review from May 1995 through June 1996

in accordance with generally accepted government auditing standards.

Results in Brief The measures of both effort and equity that are used in the Education

Finance Incentive Program could be improved. Improved measures would

more efficiently reward states that increase their level of fiscal effort in

raising education revenue or successfully diminish spending disparities

among districts.

10The following experts were involved in initial discussions or reviewed drafts of this report: Michael

Compson (Department of the Treasury), William Fowler (Department of Education’s National Center

for Education Statistics [NCES]), Frank Johnson (NCES), Martin Orland (NCES), Lawrence Picus

(University of Southern California), Wayne Riddle (Congressional Research Service), William

Sonnenberg (NCES), Stephanie Stullich (Department of Education), and Deborah Verstegen

(University of Virginia).

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Under title I, the effort factor measures each state’s spending per pupil

relative to its ability to pay, relative to this ratio for the nation as a whole.

A strength of this factor is that it considers a state’s ability to pay when

assessing its effort in raising revenue for education. We found, however,

that the measures included in the effort factor could be improved. We

developed three alternative ways to measure effort that are more

comprehensive and do not penalize states with high proportions of

school-age children. Two of these alternatives also reward states for

improving their level of effort over time. One of these two provides a

further incentive for low-effort states to increase their effort.

Similarly, the equity factor could also be improved. The current definition

of equity has two components: a measure of spending disparities and a

measure of student needs. The measure of spending disparities among a

state’s districts takes into account spending in every district in the state

and rewards states for being equitable. The measure of student needs,

however, does not adjust for all major differences in student needs across

school districts. For example, it adjusts for the extra costs associated with

educating poor students but does not adjust for the extra costs associated

with students who have disabilities or limited English proficiency. In

addition, the current measure does not adjust for differences in purchasing

power among a state’s districts (for example, differences in the costs of

services, such as teacher salaries, that affect how much a state’s dollars

can buy). Furthermore, the equity definition could more effectively reward

states for improving their level of equity over time. We developed five

alternative ways to address equity that are based on two different

measures of spending disparities. These alternatives take into account

differences in student needs and purchasing power. Three of these

alternatives also more effectively reward states for improving their level of

equity over time.

Current definitions of effort and equity are more strongly related to certain

demographic characteristics than are the alternatives we developed. For

example, the options we developed do not penalize states with high levels

of child poverty the way the current effort factor does.

The current formula for title I’s Education Finance Incentive Program

allocates funds to states using, in addition to the effort and equity factors,

the state’s total number of school-age children, rather than children in

poverty—those who are the focus of all other title I allocation formulas.

Consequently, some states could benefit from the Education Finance

Incentive Program even though they do not have high levels of poverty. We

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constructed four alternative allocation formulas using the alternative

effort and equity factors we developed. Two of the four alternatives we

present are based on numbers of poor children, rather than all school-age

children.

Background Total expenditures in all U.S. elementary and secondary schools in school

year 1993-94 reached an estimated $285 billion. Education is the largest

single expenditure category in state budgets, accounting for about 20

percent of total state spending in fiscal year 1994. Elementary and

secondary schools receive most of their funds from state and local

revenues. Federal aid has mainly focused on providing services to

educationally disadvantaged children through categorical,

program-specific grants. In school year 1992-93, state and local shares of

total education spending were roughly equal, estimated at 45.6 percent

($113 billion) for states and 47.4 percent ($118 billion) for local

educational agencies (LEA). The federal share was 6.9 percent

($17 billion).11

Although most of the activities promoting equity in education take place

within states, the federal role in supporting equity has been discussed

since the 1960s, when concern was voiced over states’ inappropriate use of

federal funds intended to improve equity on behalf of disadvantaged

children. In summer 1993 the Senate held hearings on the federal role in

school finance equalization.12 Subsequently, the Congress amended ESEA to

further help disadvantaged children by improving the targeting of title I

funds to local education agencies and schools with relatively high levels of

poor students.

Title I is a federal program that provides remedial education services to

low-achieving students in high-poverty elementary and secondary schools.

Title I funds are intended to supplement, not supplant, local and state

education funding. Until ESEA was amended by the Improving America’s

Schools Act (IASA) of 1994, title I grants to local education agencies were

distributed under two formulas—the basic grant formula and the

concentration grant formula. In an effort to increase the amount of aid

going to the neediest children, between 1988 and 1994 the statute required

that 10 percent of the appropriations to LEAs were to be distributed using

the concentration grant formula. That formula generally allocated funds

11School Finance: Trends in U.S. Education Spending (GAO/HEHS-95-235, Sept. 15, 1995).

12See, for example, William L. Taylor, Testimony Before the Subcommittee on Education, Arts and the

Humanities, Senate Committee on Labor and Human Resources, Aug. 3, 1993.

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only to those LEAs in counties where eligible children13 equaled either at

least 6,500 or 15 percent of the total population aged 5 through 17. The rest

of the appropriation was distributed under the basic grant formula (which

is based on numbers of poor school-age children multiplied by a cost

factor reflecting a state’s per pupil spending).

In 1994, the Congress sought to provide greater targeting of title I aid

although opinions varied as to the best way of doing it. In the end, IASA

made some technical changes to the basic and concentration grants and

added two more title I funding streams—targeted grants and the

Education Finance Incentive Program. The targeted grant formula may use

money appropriated for title I in excess of the fiscal year 1995 level.

Targeted grants are similar to basic grants except that poor and other

children counted in the targeted formula are assigned weights based on

the county’s or LEA’s child poverty rate and the number of poor school-age

children. This formula generally reflects the recommendations for using

weighted pupil formulas in title I made by the Commission on Chapter 1,

the RAND Corporation, and GAO.

14 Under the targeted grant formula, the

higher the poverty rate or number of poor children in the county or LEA,

the higher the title I grants per formula child.15

The 1994 reauthorization of title I included an effort and equity

bonus—additional dollars—through a new Education Finance Incentive

Program to encourage states to have more equitable education finance

systems. Although part of title I, this program is funded separately. The

1994 reauthorization authorized $200 million for the Education Finance

Incentive Program for fiscal year 1996.16 As of July 1996, however, no

funding has been appropriated. (See app. I for more background

information related to title I and appropriation issues.)

13Known as “formula children,” these were children aged 5 through 17 (1) in poor families, according to

the latest decennial census and applying the Bureau of the Census’s standard poverty income

thresholds; (2) in families above the poverty income level for a family of four but receiving Aid to

Families With Dependent Children (AFDC) payments; and (3) in certain institutions for neglected or

delinquent children. Poor children constitute approximately 96 percent of the formula children.

14Commission on Chapter 1, Making Schools Work for Children in Poverty; Iris C. Rotberg and James J.

Harvey, Federal Policy Options for Improving the Education of Low-Income Students (Santa Monica,

Calif.: The RAND Corporation, 1993); Remedial Education: Modifying Chapter 1 Formula Would Target

More Funds to Those Most in Need (GAO/HRD-92-16, July 28, 1992). For a discussion of these weights,

see Wayne C. Riddle, Education for the Disadvantaged: Analysis of 1994 ESEA Title I Amendments

Under P.L. 103-382, Report for Congress No. 94-968 EPW (Washington, D.C.: Congressional Research

Service, Nov. 18, 1994).

15Riddle, Education for the Disadvantaged.

16For fiscal years 1997 through 1999, no specific authorization limits have been set.

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The Education Finance Incentive Program defines effort as the ratio of

state spending for elementary and secondary education per pupil to the

per capita income of state residents. The effort factor, however, can be no

less than 95 percent and no more than 105 percent of the national average.

Per capita income is used as a proxy for a state’s ability to pay for

education spending. Thus, the effort factor measures each state’s actual

spending as a percentage of its ability to spend.

The equity factor measures the variation in per pupil spending across a

state’s districts divided by the state’s average per pupil spending.

Additional weight is given to the number of poor pupils to reflect the

higher cost of educating these children. The equity factor is subtracted

from 1.3 for use in the allocation formula.

Improving Effort

Measures

One of the strengths of the effort factor used in the Education Finance

Incentive Program is that it considers a state’s ability to pay when

determining the level of effort. However, the current effort factor could be

improved for three reasons. First, its measure of ability to pay—per capita

personal income—is not as comprehensive as another that is available:

total taxable resources (TTR). Second, because its measure of spending,

which is per student, is related to a measure of ability to pay which is per

capita, the factor penalizes states with high proportions of school-age

children. Third, the effort factor does not adequately reward states for

improving their level of effort over time.

The effort factor’s measure of ability to pay is not as comprehensive as it

could be because per capita income excludes many taxable resources that

states are able to use for financing education. To the extent these

additional sources of funding capacity are not equally available in all

states, the per capita income measure overstates the funding capacity of

some states and understates it for others.

The current effort factor also penalizes states with high percentages of

school-age children in their populations. It measures the ratio of state

spending, expressed on a per pupil basis, and state funding capacity,

expressed on a per capita basis. This calculation introduces the

percentage of the state’s school-age population into the measure of state

effort. The effect is to inappropriately penalize states with a high

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percentage of school-age children because the percentage of a state’s

population that is school-age is unrelated to its level of effort.17

Moreover, the current effort factor could more effectively encourage

states to increase their level of effort over time by (1) including a bonus

based on rate of increase or decrease in effort over time and

(2) eliminating the current requirement that the effort factor be at least

95 percent and no more than 105 percent of the average effort of all states.

A fiscal incentive, or bonus, would reward states for increasing their level

of educational effort over time, rather than rewarding only those that

already have high effort. The 95-percent floor undermines the incentive for

low-effort states to increase their effort in funding elementary and

secondary education. Under current law, states with very low effort may

increase their level of effort considerably, yet receive no additional

dollars.

Two of the three alternative effort factors we developed include a bonus

based on the rate of increase or decrease in effort over time, in addition to

other modifications we have made to address the potential drawbacks of

the current effort factor (see app. III). One of these two alternatives also

eliminates the requirement that the effort factor be at least 95 percent and

no more than 105 percent of the average effort of all states.

Table 1 compares the characteristics that define the current measure of

effort in title I with the measures we propose as options A, B, and C.

Option B is more comprehensive than option A because it considers both

the current level of effort and the change in effort for each state over time.

Option C is the same as option B, except that the effort factor is not

constrained by the current requirement to be between 95 and 105 percent

of the average effort. For a state-by-state breakout on each of these

options, see appendix III.

17Researchers have noted that states with a large percentage of their population that is school-age may

have a more difficult time raising needed resources for education than those with a smaller percentage

that is school-age. “All else being equal, states who are able to spread their educational costs across a

larger population base (i.e., those with higher population to pupil ratios), can more easily generate a

given level of per pupil spending than can states with greater numbers of students relative to their

population,” according to Martin Orland and Carol Cohen, Meeting the Challenge of Devolution: How

Changing Demographic and Fiscal Contexts Affect State Investments in Education (Washington, D.C.:

The Finance Project, Feb. 1996), p. 2.

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Table 1: Comparison of Current Title I

Effort Definitions With Alternative

Definitions

Definitions

Characteristic Title I Option A Option B Option C

Includes a comprehensive

measure of states’ ability to

pay

X X X

Is not biased against states

with a high proportion of

school-age children

X X X

Provides a direct incentive for

improvement in effort over

time

X X

Provides an incentive for

low-effort states to increase

their effort (no minimum)

X

Improving Equity

Measures

The equity definition in title I’s Education Finance Incentive Program

contains two components. Of the two, the measure of spending disparities

is more comprehensive than the measure of student needs. The measure of

spending disparities18 is a good overall measure because it takes into

account per pupil spending in all of each state’s school districts. The

measure of student needs, however, only explicitly takes into account the

greater needs of one type of pupil—those who are poor—in determining

per pupil expenditures. Although the definition allows other types of

higher needs students to be considered, such as students with disabilities

or limited English proficiency, they are not explicity included.

Table 2 compares the current equity measure and the five options we

developed on the following characteristics: (1) the comprehensiveness of

the measures of variation in education spending levels among districts in

the state, that is, whether they include all districts and consider

low-spending districts; (2) the ability of measures of student needs to take

into account the cost differences of educating different target populations

(students who are poor, have limited English proficiency, or have

disabilities); (3) the inclusion of a comprehensive measure of purchasing

power; (4) the inclusion of a direct incentive for states to improve their

levels of equity over time; and (5) the presence of minimum and maximum

limits.

18The coefficient of variation (COV) is the standard deviation (a common statistical measure of

variation) of state and local per pupil spending for primary and secondary education within the state,

divided by the average level of per pupil spending in the state.

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Of the five options we provide, E, G, and H are the more comprehensive.

Each considers both the current level of equity a state has achieved and

the recent progress the state has made toward achieving equity in

education spending. To the extent possible within the limitations of the

data currently available, we took into account differences in student needs

related to numbers of students who were poor, had limited English

proficiency, or had disabilities.19 Whether policymakers prefer option E or

option G depends on their interest in measuring variation in spending

levels for all school districts in the state (option E), or focusing on a state’s

ability to bring low-spending school districts up to the median (option G).

Option H is the same as option E, except that it does not contain the limits

each of the other equity options we developed does.20 (For more

information on each of these options, see app. IV.)

19In five states data were not available on the number of pupils with disabilities; however, it is

expected that data will be provided for all but two states when data become available for 1993-94 from

the Common Core of Data collected by NCES. Moreover, the number of pupils with limited English

proficiency is based on the decennial census and may underestimate the current number.

20For the other equity options, we used limits of at least 0.95 and no more than 1.30.

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Table 2: Comparison of Title I Equity

Definition With Alternative Definitions Definitions

Characteristic Title I Option D Option E Option F Option G Option H

Considers spending

levels for all districts

in the state

X X X X

Considers extent to

which district

spending levels fall

below the median

X X

Considers differences

in student needs

Poor X X X X X X

Limited English

proficiency

X X X X X

Disabilities X X X X X

Includes a

comprehensive

measure of

differences in

purchasing power

X X X X X

Provides a direct

incentive for

improvement in equity

X X X

Includes limits

(minimum and

maximum)

X X X X

Characteristics of

States With Higher

Levels of Effort and

Equity

We examined the demographic characteristics of states with higher levels

of effort and equity under the current title I definition and under the new

definitions we developed. We looked at the relationship between these

effort and equity factors and (1) state median household income,

(2) variations in median household income among districts, (3) state

percentage of school-age children in poverty, and (4) variations in

percentage of school-age children in poverty among districts.

Under the current effort factor, we found that states with higher levels of

child poverty rates do significantly less well than those states with lower

levels of child poverty. There was no significant relationship between a

state’s rate of child poverty and the options we developed; thus, the

options we developed do not penalize high-poverty states the way the

current effort factor does. For further discussion of these analyses, see

appendix III.

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When we examined the correlation between the various equity factors and

variability in median household income among districts, we found that the

lower the variability in median household income across districts in the

state, the higher the equity factor, and vice versa. The strength of the

association was strongest, however, for the current equity factor and

weakest for the three measures that considered improvement in equity

over time—options E, G, and H (see app. IV, table IV.2).

Improving the

Education Finance

Incentive Program

Formula

The current formula for title I’s Education Finance Incentive Program

allocates funds to a state based on the effort factor and the equity factor

multiplied by the state’s total number of school-age children, rather than

the number of children in poverty—those who are the focus of all other

title I allocation formulas. Consequently, some states could benefit from

the Education Finance Incentive Program even though they do not have

high levels of poverty.

The alternative allocation formulas we developed not only use the

alternative effort and equity factors we developed, but also propose using

the number of children in poverty. Two of the four alternatives we present

are based on the number of poor school-age children, rather than all

school-age children. (For illustrative alternative allocation formulas using

the effort and equity measures we developed, see app. V.21) Eight of the 10

poorest states would receive greater funding using the two alternative

formulas we propose that are based on children in poverty than they

would under the most targeted of title I formulas, the targeted grant

formula.

Conclusions The definitions of effort and equity in title I’s Education Finance Incentive

Program could be improved in a number of ways. The definition of effort

used in this program could be improved by (1) using a more

comprehensive measure of ability to pay, (2) eliminating the bias against

states with high proportions of school-age children, (3) providing a direct

incentive for states to improve their level of effort over time, and

(4) eliminating the lower limit for the effort factor. The definition of equity

used in current law could be improved by (1) more fully considering

differences in students’ needs among districts, (2) considering differences

in purchasing power among a state’s districts, and (3) rewarding states for

improving their level of equity in education spending, not just for already

21These measures also have implications for another federal program, Impact Aid, title VIII of IASA, the

purpose of which is to help pay the operating costs of LEAs that are affected by federal activities. (See

app. VI.)

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being equitable. The formula for allocating funds under this program

would better target funds to states with higher proportions of children in

poverty if it were based on the numbers of poor children rather than all

school-age children.

Matters for

Congressional

Consideration

Should the Congress decide to fund title I’s Education Finance Incentive

Program, it may want to improve the effort and equity measures and the

way they are used in the allocation formula by considering the options we

have presented in this report. Specifically, we believe that the Congress

may wish to consider

• reducing the floor on the effort factor so that low-effort states are

rewarded for increased effort;

• modifying the effort factor to eliminate the penalty on states where a high

percentage of the population is school-age;

• using, in the effort factor, a more comprehensive measure of states’

revenue raising capacity, such as the total taxable resources indicator

published by the Secretary of the Treasury;

• including in the effort and equity factors a bonus for improvement over

time;

• expanding the needs component of the equity factor to include children

with limited English proficiency and children with disabilities;

• adjusting the equity factor for differences in the cost of educational

services across each state’s districts; and

• basing the allocation formula on the number of poor school-age children

rather than all school-age children.

Agency Comments

and Our Evaluation

The Department of Education provided written comments on a draft of

this report (see app. VII). The Department expressed concern about our

analysis of the impact of the Education Finance Incentive Program on the

targeting of title I funds and whether the incentive formula can be

expected to provide a meaningful incentive for states to change their

school funding systems.

The Department of Education was concerned that the Education Finance

Incentive Program, even with the refinements we proposed, would tend to

redistribute title I funds away from many higher poverty states and school

districts. They stated that the Education Finance Incentive Program

formula has a devastating impact on targeting because of a combination of

factors, including (1) states with low fiscal effort tend to be high-poverty

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states with fewer resources, (2) the equity factor draws funds away from

some high-poverty states while benefiting some low-poverty states, and

(3) the incentive formula allocates funds based on the total number of

school-age children rather than numbers of poor children.

Regarding the Department’s first point (that states with low fiscal effort

tend to be high-poverty states), we found that although this was true using

the current effort measure, it is not true using the measures of effort we

developed. Our analysis shows that while there is a significant negative

correlation between the current effort measure and a state’s poverty level

(that is, poorer states would get fewer dollars), this is not the case with

each of the three effort options we developed.

Contrary to the Department’s second point (that the equity factor draws

funds away from some high-poverty states while benefiting some

low-poverty states), as our report points out, we found no correlation

between a state’s score on the current equity measure and a state’s poverty

level. We did find, however, that states with high levels of variation in

income levels and poverty rates across their districts did less well using

the current equity measure than states with lower levels of variation; our

equity measure options ameliorated this problem somewhat.

With regard to the third point (that the incentive formula allocates funds

based on the total number of school-age children rather than on the

number of poor children as in the other title I formulas), we agree that this

is true with the current formula. In our draft report, however, one of the

three allocation alternatives we identified uses numbers of poor, rather

than all, school-age children as a basis for allocating funds under the

Education Finance Incentive Program. We have also added a fourth

allocation alternative that uses numbers of poor children. Both of those

allocation alternatives would target more dollars for poor states such as

Alabama, Arkansas, Kentucky, Mississippi, New Mexico, South Carolina,

Tennessee, and West Virginia—8 of the 10 poorest states—than would the

targeted grant formula.

The Department also stated that the report sidesteps the issue of whether

the Education Finance Incentive Grant formula can be expected to

provide a meaningful incentive for states to change their school funding

systems. Although this issue was not the focus of our study, we state in

our report that some experts question whether the level of funding that

may or may not be appropriated for the Education Finance Incentive

Program would be of sufficient size to have any effect on the plans of state

Page 14 GAO/HEHS-96-142 Effort and Equity Measures
B-274117 

or local educational agencies to provide greater levels of effort or equity

(see app. I).

We concur with the Department’s comment that the provisions restricting

a state’s effort factor to between 95 and 105 percent of the national

average result in weakening the incentive for states to increase their level

of effort. In response to the Department’s comment, we developed another

option for the effort measure that does not include these minimum and

maximum constraints, and included this in our analysis. This fourth

alternative allocation formula based on the number of poor school-age

children also includes this unconstrained effort option as well as an

unconstrained equity option. This allocation alternative, as previously

noted, would result in targeting more dollars to 8 of the 10 highest poverty

states than would the targeted grant formula.

We are sending copies of this report to the Secretary of Education,

appropriate congressional committees, and other interested parties. If you

wish to discuss the contents of this report, please call me on

(202) 512-7014 or Eleanor Johnson, Assistant Director, on (202) 512-7209.

Major contributors to this report are listed in appendix VIII.

Carlotta C. Joyner

Director, Education and

 Employment Issues

Page 15 GAO/HEHS-96-142 Effort and Equity Measures
Contents

Letter 1

Appendix I 

Background

18

Appropriation Issues Related to Title I’s Education Finance

Incentive Program

18

Definition of Effort in Title I’s Education Finance Incentive

Program

20

Definition of Equity in Title I’s Education Finance Incentive

Program

21

Appendix II 

Scope and

Methodology

23

Appendix III 

Measuring Effort

24

Effort Factor in Current Law Could Be Improved 24

Alternative Title I Effort Factors 24

Correlations Between Current and Alternative Effort Factors and

Demographic Characteristics

27

Appendix IV 

Measuring Equity

29

Methodology for Developing Alternatives 30

Development of Alternative Definitions of Equity 31

Correlations Between Equity and Demographic Characteristics 37

Appendix V 

Illustrative Alternative

Allocations Using

New Measures

39

Appendix VI 

Implications for

Impact Aid

43

Overview of the Impact Aid Program 43

Ways to Determine Equalization 43

Page 16 GAO/HEHS-96-142 Effort and Equity Measures
Contents

Appendix VII 

Comments From the

Department of

Education

45

Appendix VIII 

GAO Contacts and

Acknowledgments

46

Tables Table 1: Comparison of Current Title I Effort Definitions With

Alternative Definitions

9

Table 2: Comparison of Title I Equity Definition With Alternative

Definitions

11

Table III.1: Current and Alternative Effort Factors 26

Table III.2: Correlations Between the Effort Factors and State

Demographic Characteristics

28

Table IV.1: Current and Alternative Title I Equity Factors 36

Table IV.2: Correlations Between the Equity Factors and State

Demographic Characteristics

38

Table V.I: Illustrative State Allocations Under Current and

Alternative Title I Formulas—Education Finance Incentive

Program and Targeted Grants

40

Figures Figure I.1: Formula for Determining State Share 20

Figure V.1: Formula for Determining State Share 39

Figure V.2: Examples of Alternative Formulas 40

Abbreviations

AFDC Aid to Families With Dependent Children

COV coefficient of variation

ESEA Elementary and Secondary Education Act

IASA Improving America’s Schools Act

LEA local educational agency

NCES National Center for Education Statistics

TTR total taxable resources

Page 17 GAO/HEHS-96-142 Effort and Equity Measures
Appendix I 

Background

Under title I, federal funds are authorized to school districts to provide

supplementary educational services for low achievers in areas with

children in poverty. As reauthorized by P.L. 103-382 in October 1994, these

title I educational services may be financed by four funding formulas for

this common purpose. The four funding formulas are for basic grants,

concentration grants, targeted grants, and Education Finance Incentive

Program grants. In fiscal year 1996, approximately $6.7 billion was

appropriated for two of these funding formulas: basic grants and

concentration grants.22 No funds have been appropriated for either

targeted grants or the Education Finance Incentive Program for fiscal year

1996.

Basic grants are generally allocated based on numbers of poor school-age

children multiplied by a “cost factor”—a measure based on a state’s

average per pupil spending.23 Concentration grants are based on numbers

of school-age children in areas with high concentrations of

poverty—where over 6,500 or 15 percent of the children are poor—and a

measure of per pupil spending. Targeted grants provide an even greater

focus on allocating funds to the highest poverty areas because they target

the greatest per pupil funding to the areas with the highest poverty rates or

numbers of children in poverty.

Appropriation Issues

Related to Title I’s

Education Finance

Incentive Program

Many complex policy and technical issues surround congressional

policymakers’ decisions about whether to provide some title I funding

through the Education Finance Incentive Program formula. It remains

unclear whether additional title I funds will be appropriated in the near

future and, if so, whether they will be made available for the two title I

formulas created in the 1994 reauthorization: targeted grants and

Education Finance Incentive Program grants.24 Funds appropriated in

excess of the fiscal year 1995 title I appropriation may be spent for

targeted grants. However, in part because the excess amounted to only 0.5

percent of the basic and concentration grant appropriations for fiscal year

22However, under P.L. 104-134, about $1.3 billion of these basic and concentration grant funds will not

be available for fiscal year 1996 awards (school year 1996-97) until Oct. 1, 1996.

23In a previous review of the title I formula, we noted that the current cost factor needs improvement

as it rewards states for spending more on education without considering differences across states in

their ability to spend on education. See Remedial Education: Modifying Chapter 1 Formula Would

Target More Funds to Those Most in Need (GAO/HRD-92-16, July 28, 1992).

24For more information on the title I basic, concentration, and targeted grant formulas, see Wayne

Riddle, Education for the Disadvantaged: Analysis of 1994 ESEA Title I Amendments Under P.L.

103-382, Report for Congress No. 94-968 EPW (Washington, D.C.: Congressional Research Service,

Nov. 18, 1994).

Page 18 GAO/HEHS-96-142 Effort and Equity Measures
Appendix I 

Background

1996, no funds were spent for targeted grants for fiscal year 1996.25 In

addition, no funds were earmarked for the Education Finance Incentive

Program, although $200 million was authorized for fiscal year 1996. If

funding for title I increases in future years, it remains unclear whether the

Congress will appropriate funds for targeted grants or the Education

Finance Incentive Program.

For fiscal year 1997, the Clinton administration has proposed funding

targeted grants at $1 billion, while decreasing funds for basic grants by

about $500 million. The proposal is intended to enhance the ability of the

poorest communities to provide supplementary instructional services to

disadvantaged students. The administration proposes not to fund the

Education Finance Incentive Program for fiscal year 1997 because “the

formula would reward states that make a high effort and are highly

equalized, but it would not consistently target funds on states with high

concentrations of poor children.”26 In addition, some experts question

whether the level of funding that may or may not be appropriated for the

Education Finance Incentive Program would be of sufficient size to have

any effect on the plans of state or local educational agencies to provide

greater levels of effort or equity.

Those who support funding the Education Finance Incentive Program may

note that title I funds are seen as supplementing a basic level of state and

local funding for instructional services to compensate for the additional

educational needs that accompany concentrations of poverty.27 If,

however, there are spending disparities among a state’s school districts,

title I funding “may only help make up some of the gap in resources

available to disadvantaged children compared to those received by the

advantaged.”28 To the extent that a state’s spending for education

increases and spending disparities among a state’s districts decrease, the

federal government is able to more effectively target funds to provide truly

supplemental educational resources to disadvantaged children.

25See Wayne Riddle, Title I, ESEA: Current Status and Issues, Report for Congress No. 96-380 EPW

(Washington, D.C.: Congressional Research Service, Apr. 26, 1996).

26See Department of Education, Justifications of Appropriation Estimates to the Congress: Fiscal Year

1997, Vol. I, p. B-20.

27For a discussion of related title I (formerly known as chapter 1) issues, see Commission on

Chapter 1, Making Schools Work for Children in Poverty: A New Framework Prepared by the

Commission on Chapter 1 (Washington, D.C.: Dec. 1992).

28See Riddle, Education for the Disadvantaged, p. 17.

Page 19 GAO/HEHS-96-142 Effort and Equity Measures
Appendix I 

Background

If funds are appropriated for the Education Finance Incentive Program in

the future, under current law each state’s share would be determined by

the formula in figure I.1.

Figure I.1: Formula for Determining

State Share

Total School-Age Population Effort Factor

(1.3 Equity Factor)

x

x – State Share =

Notes: This formula differs from other title I, part A, formulas in two ways: (1) it uses school-age

population, not poor school-age population, as a basis for allocation; and (2) it does not include

an expenditure factor, as other formulas do, that rewards high-spending states. For more

information, see Riddle, Education for the Disadvantaged.

Throughout the rest of this report, we will use the term “equity factor” to refer to the “1.3 minus the

equity factor.”

Funds would then be allocated to districts within each state based on their

share of the total of other title I funds for school districts: basic grants,

concentration grants, and targeted grants. Each state is to be allotted at

least 0.25 percent of the total appropriation. The effort and equity factors

in the Education Finance Incentive Program are intended to provide

additional dollars to those states that have relatively high fiscal effort (in

order to provide adequate levels of funding for education) and those states

with relatively low disparities in per pupil funding across districts.

Definition of Effort in

Title I’s Education

Finance Incentive

Program

The Education Finance Incentive Program defines effort using two

components: state spending for education and state ability to pay (see app.

III). The measure for state spending for education is the state’s average per

pupil expenditure for public elementary and secondary education. The

measure of the state’s ability to pay for services is the state’s average per

capita income.29 Those states with high effort, that is, high state spending

relative to their ability to pay, are rewarded for this under the Education

Finance Incentive Program.

A state’s level of effort is compared with that for the nation as a whole to

develop an “effort factor” to be used in the Education Finance Incentive

29Under current law, averages used to calculate the effort factor are determined using 3 years of data

to minimize the effect of changes from year to year.

Page 20 GAO/HEHS-96-142 Effort and Equity Measures
Appendix I 

Background

Program formula. If the index is 1.00, the state’s level of spending for

education, relative to its per capita income, is the same as it is for the

nation as a whole. Those states with spending for education relative to

their ability to pay that is greater than that for the nation receive a factor

higher than 1.00; those with spending relative to ability to pay that is lower

than that for the nation receive a factor lower than 1.00. No state,

however, may have an effort factor higher than 1.05 or lower than 0.95.

Limiting the range from 0.95 to 1.05 limits the degree to which states

receive a smaller share because of their much lower effort or a larger

share because of their much higher level of effort.

Definition of Equity in

Title I’s Education

Finance Incentive

Program

The definition of equity used in title I’s Education Finance Incentive

Program includes two components: a measure of spending disparities and

a measure of student needs. The law also contains a number of other

adjustments that take into account complexities arising from various types

of school districts (for example, elementary, secondary, and unified),

extremely small school districts, and other factors (see app. IV).

The first component measures the level of disparity in current per pupil

expenditures across the state’s school districts. There are a variety of ways

to measure spending disparities; title I uses the coefficient of variation

(COV). The COV is the standard deviation (a common statistical measure of

variation) in spending per student among all districts within the state,

divided by the average level of spending per student in the state.

The second component is a partial accounting, through use of a weighting

factor, for differences in student needs across districts within the state; it

specifically focuses on differences in the number of poor students.

Students with no need for additional services are weighted by a factor of

1.0; poor students are weighted by a factor of 1.4.30 Such a weighting

system recognizes that it may not be best to have equal spending per pupil

across districts if the needs of the children in those districts are not equal.

For example, additional local, state, and federal dollars might be targeted

to districts with high concentrations of poor children to provide services

to compensate for their greater educational needs.

30In addition, the law allows the Secretary of Education to take into account the needs of other types

of pupils, such as pupils with limited English proficiency or disabilities. While data were not available

on numbers of children with disabilities for eight states at the time the law was passed, data will soon

be available for all but two states. The law also allows the Secretary to consider differences in

purchasing power across the states’ districts when determining the level of equity. Indexes on

differences in purchasing power across the states’ districts were not available at the time the law was

enacted but have been developed recently.

Page 21 GAO/HEHS-96-142 Effort and Equity Measures
Appendix I 

Background

The equity factor is then constructed by subtracting the measure of

spending disparities—the COV adjusted by a weighting component for poor

students—from 1.3.31 For most states, the equity factor ranges from 1.2 to

1.0. One state, Hawaii, has only one school district and, therefore, no

variation in spending, so it receives an equity factor of 1.3. For similar

reasons, Washington, D.C., and Puerto Rico also receive an equity factor of

1.3.32 Current law also includes a provision that those states that meet the

disparity standard under Impact Aid33—Alaska, Kansas, and New

Mexico—receive an equity factor of 1.2.

31The law also allows the Secretary to incorporate other valid and accepted methods to measure equity

not reflected in the COV method.

32One expert suggested that Hawaii, Washington, D.C., and Puerto Rico receive an undeserved

advantage because of this situation and that they should receive an average score on the equity factor,

rather than the highest score.

33See app. VI for a discussion of the Impact Aid program.

Page 22 GAO/HEHS-96-142 Effort and Equity Measures
Appendix II 

Scope and Methodology

We reviewed the formula used in title I’s Education Finance Incentive

Program, focusing on the components of the formula related to effort and

equity, which the Congress refers to as effort and equity factors. Our study

was designed to answer the following questions: (1) How can the current

effort factor be improved? (2) How can the current equity factor be

improved? (3) How are state demographic characteristics, such as poverty

rate or median income, related to state scores on the effort and equity

factors? (4) How can the options we developed be used in alternative ways

to allocate funds under the Education Finance Incentive Program?

To answer these questions, we analyzed the strengths and weaknesses of

title I’s effort and equity factors using criteria we developed after

reviewing the literature and consulting with experts. On the basis of our

review of the literature and consultation with experts, we developed

alternative effort factors for possible use in the Education Finance

Incentive Program using a universe sample of school district data from the

Department of Education’s National Center for Education Statistics (NCES)

for school year 1991-92. School district spending data were collected by

the Bureau of the Census for NCES. We also developed alternative equity

factors that include two different measures of spending disparities and

consider differences in purchasing power across a state’s school districts.

See appendixes III and IV for a description of the methods used to produce

the alternatives for the effort and equity factors for title I’s Education

Finance Incentive Program.34 To the extent possible within the limitations

of the data currently available, we took into account differences in student

needs related to numbers of students who were poor, had limited English

proficiency, or had disabilities.35 We also developed illustrative state

allocations under current and alternative title I Education Finance

Incentive Program formulas as well as under the targeted grant formula

(see app. V).36

34See app. VI for a discussion of some of the methodological strengths and weaknesses of the

definition of equalization used in Impact Aid.

35In five states, data were not available to take into account the number of pupils with disabilities;

however, it is expected that data will be provided for all but two states when data become available for

school year 1993-94. Moreover, the number of pupils with limited English proficiency is based on the

decennial census and underestimates the current number.

36Although existing NCES data are sufficient for the purposes of illustrating the general effects of

changes in the effort and equity factors, should the Congress wish to pursue these strategies, NCES

may need to address a number of cases of missing data or irregularities in the school district database.

Page 23 GAO/HEHS-96-142 Effort and Equity Measures
Appendix III 

Measuring Effort

The effort factor in the Education Finance Incentive Program provides

additional title I aid to those states with education spending relative to

their ability to pay that is higher than other states. Current law defines this

factor as the state’s average per pupil expenditure divided by the state’s

average per capita income relative to that for the nation as a whole. In the

current law, averages are determined using 3 years of data to minimize the

effect of changes from year to year. However, no state’s effort factor can

be less than 95 percent of the nation’s average or more than 105 percent.

Under P.L. 103-382, funds are to be allocated to states based on the state’s

number of children aged 5 through 17 multiplied by both the effort factor

and the equity factor. Each state is to be allotted at least 0.25 percent of

the total appropriation.

Effort Factor in

Current Law Could Be

Improved

The effort factor in the current law, which considers states’ education

spending relative to their ability to pay, could be improved. First, the

measure of ability to pay used in the law, per capita income, is not as

comprehensive as the one we used: total taxable resources (TTR). Second,

the current effort factor penalizes states with high proportions of

school-age children. Finally, the existing effort factor could more directly

reward states for increasing their level of effort, not just for having high

effort.

Alternative Title I

Effort Factors

We developed three alternative effort factors for title I’s Education

Finance Incentive Program using TTR as a measure of a state’s ability to

finance services. TTR, defined and compiled by the Department of the

Treasury, considers both personal income and the gross state product for

each state. TTR takes into account all income produced within a state,

whether received by residents or nonresidents, or retained by business

corporations. TTR is a more comprehensive indicator of taxable resources

than personal income alone, in part because it also considers income

produced in a state but received by nonresidents.

In our alternative effort factors, we consider both spending and ability to

pay per student, rather than spending per student and ability to pay per

capita, as the current law does. The ability to pay per student is a better

measure of a state’s ability to finance educational services for students

than ability to pay per capita. Moreover, using ability to pay per capita,

rather than per student, results in lower Education Finance Incentive

grants for states with high proportions of school-age children—those

states usually intended to benefit from education-related grants.

Page 24 GAO/HEHS-96-142 Effort and Equity Measures
Appendix III 

Measuring Effort

In one of the alternatives we developed, option B, we increase the level of

the reward to states that increase their level of effort over time. For

example, two states may have the same level of effort in the current year.

But while one state increased its level of effort from the previous year, the

other state decreased its level of effort. In the first of the alternatives we

present, option A, these two states would have the same effort factor

because they each currently have the same level of effort—as would

happen under current law. In the second alternative, option B, the state

that increased its level of effort from the previous year would have a

higher score than the state that decreased its level of effort. Option C is

similar to B but without the limits of 0.95 and 1.05, so that low-effort states

would have a greater incentive to increase their effort.

The details of the three alternative effort factors we developed are as

follows. The first alternative, which we refer to as option A, is based on

state and local funding for elementary and secondary public education

(kindergarten through grade 12) divided by the state’s TTR.

37 To develop an

index, we divided the state figure by a comparable figure for the nation as

a whole. This effort index, as is the case for the current law index, is

limited to no less than 0.95 and no more than 1.05. Option A is based on

data for school year 1992-93.

The second alternative, which we refer to as option B, is an index that also

considers the rate of change in effort over time. We determined the rate of

change in effort over time by comparing option A with a similar effort

factor for the previous school year, 1991-92. For example, if the state’s

effort factor was 1.01 under option A, and it had improved by 3 percent

from the previous year, under option B its effort factor would be 1.01

multiplied by 1.03 (1 plus 0.03), or 1.04. In contrast, if the state’s effort

factor was 1.01 under option A, but its effort had decreased by 3 percent

from the previous year, under option B its effort factor would be 1.01

multiplied by 0.97 (1 minus 0.03) or 0.98. Again, the factors were limited

within the bounds of 0.95 and 1.05.

The third option we developed, option C, is similar to option B in that it

provides an additional incentive for change over time. In addition, option

C eliminates the lower limit of 0.95 and the upper limit of 1.05. We allowed

only half of the index to vary, however, because otherwise the gap

between the extremes would be too wide. In other words, option C equals

0.5 multiplied by an unconstrained effort factor, plus a constant of 0.5.

Under option C, the effort factor would range from a low of 0.72 for the

37This is mathematically equivalent to dividing a state’s spending per pupil by the state’s TTR per pupil.

Page 25 GAO/HEHS-96-142 Effort and Equity Measures
Appendix III 

Measuring Effort

District of Columbia to a high of 1.21 for West Virginia. Table III.1

compares current and alternative effort factors.

Table III.1: Current and Alternative

Effort Factors Alternative effort factors

State

Current effort

factora Option A Option B Option C

Alabama 0.95 0.95 0.95 0.90

Alaska 1.05 1.05 1.01 1.11

Arizona 0.95 1.05 1.04 1.02

Arkansas 0.95 1.01 1.01 1.01

California 0.95 0.95 0.95 0.94

Colorado 0.95 0.97 0.98 0.99

Connecticut 1.05 0.99 0.97 0.98

Delaware 1.05 0.95 0.95 0.88

District of Columbia 1.05 0.95 0.95 0.78

Florida 1.00 0.95 0.95 0.94

Georgia 0.95 0.96 1.02 1.01

Hawaii 0.95 0.95 0.96 0.91

Idaho 0.95 1.01 0.97 0.98

Illinois 0.96 0.95 0.95 0.94

Indiana 1.02 1.05 1.05 1.09

Iowa 0.98 1.05 1.05 1.07

Kansas 0.96 1.03 1.03 1.02

Kentucky 0.98 0.99 0.98 0.99

Louisiana 0.98 0.95 0.95 0.94

Maine 1.05 1.05 1.05 1.17

Maryland 1.05 0.97 0.97 0.98

Massachusetts 1.05 0.95 0.95 0.94

Michigan 1.05 1.05 1.05 1.16

Minnesota 1.00 1.05 1.04 1.02

Mississippi 0.95 0.95 0.95 0.92

Missouri 0.95 0.95 0.95 0.95

Montana 1.05 1.05 1.00 1.09

Nebraska 0.95 1.03 1.05 1.04

Nevada 0.95 0.95 0.95 0.89

New Hampshire 0.95 1.00 1.00 1.00

New Jersey 1.05 1.05 1.04 1.09

New Mexico 0.95 1.05 1.03 1.02

New York 1.05 1.05 1.04 1.05

North Carolina 0.95 0.95 0.95 0.90

(continued)

Page 26 GAO/HEHS-96-142 Effort and Equity Measures
Appendix III 

Measuring Effort

Alternative effort factors

State

Current effort

factora Option A Option B Option C

North Dakota 0.95 0.96 0.95 0.97

Ohio 1.05 1.05 1.05 1.09

Oklahoma 0.95 1.05 1.05 1.03

Oregon 1.05 1.05 1.05 1.11

Pennsylvania 1.05 1.05 1.04 1.03

Puerto Rico 0.95 0.95b 0.95b 0.78b

Rhode Island 1.05 1.05 1.05 1.05

South Carolina 0.98 1.02 1.01 1.00

South Dakota 0.95 0.95 0.97 0.97

Tennessee 0.95 0.95 0.99 0.86

Texas 0.95 1.04 1.00 1.00

Utah 0.95 1.05 1.05 1.08

Vermont 1.05 1.05 0.98 1.11

Virginia 0.95 0.95 0.95 0.96

Washington 0.95 1.05 1.05 1.04

West Virginia 1.05 1.05 1.05 1.21

Wisconsin 1.05 1.05 1.05 1.11

Wyoming 1.05 1.05 0.96 1.09

aLiane White, Education Finance Incentive Grant Under ESEA Title I, Report for Congress 95-963

EPW (Washington, D.C.: Congressional Research Service, Sept. 12, 1995).

bComparable data for our comprehensive measure of states’ ability to pay, TTR, developed by the

Department of Treasury, were not available for Puerto Rico. Therefore, we gave Puerto Rico the

same score under options A, B, and C that it would receive under the definition in the current

law—the lowest effort factor calculated for any state.

Correlations Between

Current and

Alternative Effort

Factors and

Demographic

Characteristics

We examined the correlations between effort and states’ demographic

characteristics such as state median income, within-state deviations in

median household income, state percentage of school-age children in

poverty, and within-state deviations in percentage of school-age children

in poverty. We examined the extent to which title I’s current effort factor

and the alternative effort factors we developed were related to these

demographic factors.

We found that states with higher levels of child poverty rates do

significantly less well with the current effort factor than those states with

lower levels of child poverty. However, there was no significant

relationship between a state’s rate of child poverty and the options we

Page 27 GAO/HEHS-96-142 Effort and Equity Measures
Appendix III 

Measuring Effort

developed. Thus, the options we developed do not penalize high-poverty

states the way the current effort factor does.

When we examined the correlation between the various effort factors and

variability in median household income across a state’s districts, we found

that the variable “within-state deviations in median household income”

was positively correlated with the current effort factor.38 That is, the

higher the variability in median household income across districts in the

state, the higher the current effort factor, and vice versa. There was no

significant correlation, however, between this variable and the options we

developed (see table III.2). Moreover, neither the current effort factor nor

the options we developed were significantly correlated with state median

household income or within state deviations in child poverty levels.

Table III.2: Correlations Between the

Effort Factors and State Demographic

Characteristics Characteristic

Current

measure Option A Option B Option C

State median household

income –0.06 –0.22 –0.16 –0.21

Within-state deviations in

median household income 0.29a 0.09 0.08 0.10

Percentage of school-age

children in poverty –0.34a –0.20 –0.15 –0.21

Within-state deviations in

percentage of school-age

children in poverty 0.03 0.05 0.09 0.04

aSignificant at the 0.05 level.

38Two variables, state median household income and within-state deviations in median household

income, were adjusted for differences in purchasing power.

Page 28 GAO/HEHS-96-142 Effort and Equity Measures
Appendix IV 

Measuring Equity

The equity factor of the Education Finance Incentive Program formula

provides that additional title I aid go to those states with relatively low

disparities in per pupil expenditures among local educational agencies

(LEA).39 The particular statistical measure used to determine the level of

spending disparities in each state under current law is the coefficient of

variation (COV). The COV is defined as the standard deviation divided by the

mean. Assuming a normal distribution, approximately two-thirds of all

school districts will fall within one standard deviation of the mean, or

average. For example, if the state’s average per pupil spending is $6,000

and the standard deviation is $2,000, then approximately two-thirds of

districts in the state will be spending between $4,000 and $8,000 per pupil.

However, average spending levels vary greatly from state to state. To

provide fair comparisons across the states, each state’s standard deviation

is divided by its average spending level.40 Using this example, the COV is

$2,000 divided by $6,000 or 0.33.

In addition to defining the measure of equity as the COV, the law specifies

that the COV should be weighted by the number of poor children in each

school district for each state. The Congressional Research Service has

pointed out that “the effect of the additional weighting for poor children is

that expenditure disparities in favor of LEAs with relatively large numbers

of poor children would reduce a State’s measured COV, while expenditure

disparities in favor of LEAs with relatively low numbers of poor children

would increase a State’s COV.”41

To provide a simplified example of how weighting might work, assume a

state has two school districts—one with only poor students and another

with no poor students. Also assume that the per pupil spending is the same

for the two districts, except that 40 percent more funding per poor student

is provided to fund additional services. Such a state would appear to have

a significant spending disparity. However, a weighted COV takes into

account the differences in student needs.

In the current law, the 1.4 weighting per poor student stems, in part, from

title I, which authorizes an additional 40 percent in per pupil spending to

39To simplify, we have used the term “equity factor” rather than “1.3 minus the equity factor” in this and

subsequent appendixes.

40This measure also helps to provide comparability over time. For example, if we wanted to examine

the level of disparity of many years ago, when spending levels in nominal dollars were half of what

they are now, such figures would be comparable. For example, if the state mean had been half of what

it is now, $3,000, and, similarly, the standard deviation was $1,000, also half, the COV would be $1,000

divided by $3,000 or 0.33, the same as above.

41Riddle, Education for the Disadvantaged, p. 16.

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Appendix IV 

Measuring Equity

provide services to educationally disadvantaged children in high poverty

areas. However, appropriations for title I have generally been less than

half of what is authorized. As a result, in a recent study, researchers used

1.2 as a weighting for poor students.42

The law also contains a number of other adjustments that take into

account complexities arising from various types of LEAs (for example,

elementary, secondary, and unified), extremely small LEAs, and other

factors. Under current law, separate COVs are used for elementary,

secondary, and unified school districts. A statewide COV is then determined

by calculating a weighted average based on the number of weighted

students (that is, counting poor students as 1.4) for each type of district

occurring within the state. Some states have only unified school districts

serving students from kindergarten through grade 12; other states have

elementary, secondary, and unified school districts. The law excludes

spending in extremely small school districts, such as those in remote

areas, because spending in these school districts may be atypical.

Methodology for

Developing

Alternatives

Our work is based on statistical analyses of fiscal and demographic data

from the nation’s school districts for school years 1991-92 and 1989-90, the

latest years for which expenditure data for the universe of school districts

were available. In determining alternative equity factors, we also treated

the various types of school districts—elementary, secondary, and

unified—separately and computed a statewide weighted average. As is the

case under current law, we excluded school districts with fewer than 200

students enrolled and districts that reported they had no schools. We also

excluded districts with expenditures that were likely to be atypical, such

as those devoted primarily to vocational or special education. In

examining expenditure equity, we used total current expenditures, which

do not include expenditures for debt services or capital outlay.

Data limitations include an underreporting of the number of children who

have limited English proficiency and those with disabilities. Although NCES

data are sufficient for the purposes of illustrating alternatives to the

current effort and equity factors, NCES may want to address a number of

cases of missing data or irregularities in the school district database. The

data available to us on school district finances and numbers of special

needs children by school district were compiled by NCES and the Bureau of

the Census. Data on numbers of children with limited English proficiency

42For more information, see Thomas B. Parrish, Christine S. Matsumoto, and William J. Fowler,

Disparities in Public School District Spending: 1989-90, Statistical Analysis Report No. 95-300

(Washington, D.C.: National Center for Education Statistics, Feb. 1995).

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Measuring Equity

came from parents’ reports to the Bureau of the Census about whether

their children speak English “not well” or “not at all.” In addition, five

states in school year 1991-92 and eight states in school year 1989-90 did

not provide numbers of children with disabilities.43 In developing an equity

factor for these states without data, we were not able to take into account

differences among school districts in the number of children with

disabilities.

Development of

Alternative

Definitions of Equity

To improve the current measures of equity used in the Education Finance

Incentive Program, we examined (1) the comprehensiveness of the various

measures of equity available, (2) the comprehensiveness of the measures

accounting for differences in student needs across districts, (3) the effect

of including a measure of purchasing power across districts, and (4) the

effect of including a direct incentive for states to improve their levels of

equity over time.

The Comprehensiveness of

Various Equity Measures

We reviewed literature related to measures of school finance equity, most

particularly a set of expert papers prepared for the Department of

Education in 1992 to evaluate whether the measures of equity used in the

Department’s Impact Aid program could be improved.44 Although focused

on Impact Aid (see app. VI), these papers informed the discussion related

to equity measures used in title I as well.

Some of these experts generally agreed that an equity measure would be

better if it took into account a large portion of each state’s school districts

in determining the disparity in per pupil spending across the state, as the

COV does. Robert Berne and Leanna Stiefel also suggested that another

measure of spending disparities be used—the McLoone Index.

The COV takes into account per pupil spending in all of each state’s school

districts and, therefore, is a comprehensive measure of equity. Another

measure of equity, the McLoone Index, focuses on equity for school

43We use the term children with disabilities to refer to children with an individualized educational plan

under the Individuals With Disabilities Education Act. Data on numbers of such children were not

available for five states in 1991-92: Kentucky, Ohio, Oklahoma, Pennsylvania, and Virginia. In 1989-90,

data were not available for Alaska, Kansas, Vermont, and Washington, in addition to Kentucky, Ohio,

Oklahoma, and Pennsylvania. In 1993-94, data will be available for all but two states: Kentucky and

Ohio.

44These papers, published in a special issue of the Journal of Education Finance, Vol. 18, No. 1

(Summer 1992), were written by the following experts on equity measures in school finance: Robert

Berne and Leanna Stiefel, K. Forbis Jordan, Allan Odden, and Richard Salmon. Joel Sherman provided

a summary article as editor for the special issue.

Page 31 GAO/HEHS-96-142 Effort and Equity Measures
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Measuring Equity

districts that spend less than the median.45 This index is the ratio of the

sum of expenditures for districts below the median to what the

expenditures in these districts would be if they were able to spend at the

median level per pupil. Where per pupil expenditures are equal for all the

districts in the state that are at or below the median, the McLoone Index

is 1.0.

The Comprehensiveness of

Measures of Differences in

Student Needs

Experts suggested that taking into account student needs would improve

current measures of equity. For example, if one district in a state has many

pupils that are poor, have limited English proficiency, or otherwise need

special educational services, it may be appropriate for the state to provide

more aid for that district than for districts without high proportions of

these at-risk pupils. Therefore, it may be necessary to make adjustments to

consider that one district has greater student needs by weighting its

students according to their need for additional services. If, for example,

the cost of educating a student with limited English proficiency is, on

average, 20 percent more than the cost of educating a student without

additional needs, these students would then be weighted 1.2. If the district

were able to spend at the level needed to cover these additional services,

its expenditures per weighted pupil would show that it was spending at a

level comparable with districts with fewer students with additional needs.

We chose to use a set of weights developed for the NCES report, Disparities

in Public School District Spending: 1989-90, that takes into account

differences in student needs across school districts.46 The researchers

assigned students with disabilities a weight of 2.3 because the cost of

educating such children is generally 2.3 times the cost of educating

children who do not need special educational services, although the cost

of educating children with specific types of disabilities varies widely.47 The

report used weights of 1.2 for children from poor families or those who

have limited English proficiency. This additional 0.2 weighting for students

in poverty stems from an estimate based on the average title I allocation

per student divided by average revenues per student. The rationale for

using a weight of 1.2 for children with limited English proficiency is based

on an expectation that they will need additional educational services,

45It is also possible to construct a modified McLoone Index that examines all districts with spending

below, for example, the 75th or 80th percentiles rather than below the 50th percentile, or median.

46Parrish, Matsumoto, and Fowler, Disparities in Public School District Spending: 1989-90.

47This cost estimate is based on analysis of data from a nationally representative sample. For more

information, see M.T. Moore, E.W. Strang, M. Schwartz, and M. Braddock, Patterns in Special

Education Service Delivery and Cost, Contract No. 3000-84-0257 (Washington, D.C.: Decision

Resources Corp., 1988). More recent studies have resulted in a similar figure.

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Measuring Equity

comparable with those for poor children, although school districts may

generally spend less than this currently.

We also consulted with the Congressional Research Service on the issue of

whether to use 1.2 or 1.4 as a weight for the number of poor children and

those with limited English proficiency. While the current equity measure

uses the higher weight of 1.4 to adjust for the greater needs of poor

children, it does not adjust for the greater needs of other students needing

additional services, such as students with disabilities or limited English

proficiency. But because we were taking into account the additional costs

associated with educating these students and because there may be some

double counting, that is, students may be weighted twice if they are both

poor and have limited English proficiency (or have disabilities and limited

English proficiency), we decided the weight of 1.2 was more appropriate

in this case.48 More precise estimates are not available on the cost of

educating students who may have multiple types of special needs;

moreover, data currently available do not allow us to estimate numbers of

such children by school district.

Adjusting for Differences

in Purchasing Power

We believe that adjusting for differences in purchasing power across a

state’s districts is useful in providing more comparable measures of

spending levels, or spending disparities, across districts. For example,

district A may be able to hire teachers of the same quality at 80 percent of

the cost of district B because district A may be in a part of the state that

offers lower housing costs, greater availability of desirable services, or

better weather. If each district spends $4,000 per pupil, district B will not

be able to provide the same level of services to its students as district A.

Therefore, to provide greater comparability, we adjusted the spending

levels of the various districts to take into account differences in

purchasing power reflected in the cost of hiring and retaining teachers.

We used a teacher cost index recently developed for the National Center

for Education Statistics.49 While an index that examines differences in the

48We note, however, that the pros and cons of using specific weights are debated by some experts and

program officials. For example, some experts would argue that a higher weight of 1.4 would be

appropriate for both poor students and those with limited English proficiency. (See, for example,

Deborah Verstegen and Kent McGuire, “The Dialectic of Reform,” Educational Policy, Vol. 5, No. 4,

pp. 386-411.) One program official suggested that it may be more appropriate to use a lower weight for

students with limited English proficiency than for poor students, in part because of the double

counting.

49See Jay Chambers and William Fowler, Public School Teacher Cost Differences Across the United

States, Analysis/Methodology Report No. 95-758 (Washington, D.C.: National Center for Education

Statistics, Oct. 1995).

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Measuring Equity

cost of living is also available by district, we believe that the NCES teacher

cost index is better suited to our purpose of providing comparability

across districts because it considers the purchasing power of districts in

determining personnel-related costs, a major cost to school districts. Our

focus is on the district’s ability to provide comparable educational services

to its students, rather than on whether teachers’ salaries are adequate

given the cost of living in their area.

Not all costs, however, vary within the state. For example, the costs of

books, instructional materials, and other supplies and equipment tend to

vary little within a state or, for some items, the nation. Therefore, we used

the teacher cost index to adjust only the portion of expenditures generally

estimated to be related to personnel costs.50 We used an estimate

developed by Stephen Barro for NCES; he calculated that 84.8 percent of

total current expenditures are personnel costs, including salaries, fringe

benefits, and some purchased services.51

Inclusion of a Bonus for

Improving Equity Over

Time

In two of the five alternative measures of equity we developed, options D

and F, states are rewarded solely on the basis of their current level of

equity, as is the case under current law. Another way to compare states is

to include a measure of whether and to what extent states have improved

their level of equity in recent years. Our three other alternative measures

of equity, options E, G, and H, take into account rate of change in the level

of equity from school year 1989-90 to school year 1991-92, the most recent

comprehensive data available on school district level finances.

Our first alternative, option D, uses a COV, as the current title I equity

measure does. In addition, option D takes into account the needs of

students with limited English proficiency or disabilities as well as those

who are poor. We used weights of 1.2 for poor students and those with

limited English proficiency, and 2.3 for students with disabilities, rather

than the weighting of 1.4 for only poor students as in the current measure

of equity. We also used a teacher cost index to adjust for purchasing

power differences across school districts. Like the current measure, we

subtracted this adjusted COV from 1.3 so that the two measures are

50Data on district level teacher costs were not available in Oregon for school districts comprising about

27 percent of students enrolled in the state; cost data were also not available for districts enrolling

about 15 percent of students in Alaska, about 8 percent of students in New York, and about 6 percent

in Maryland and New Jersey. Since our analysis was completed, we have been informed by NCES that

data correcting these problems are now, or will soon be, available.

51Stephen M. Barro, Cost-of-Education Differentials Across the States, Working Paper No. 94-05,

(Washington, D.C.: National Center for Education Statistics, July 1994).

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Appendix IV 

Measuring Equity

comparable. We limited this measure, along with three of the other four

we developed, so that no state’s measure is less than 0.95 or more than 1.3.

(The current equity factor presently ranges from 0.99 to 1.3; see table IV.1.)

This limitation affected few states and resulted in relatively minor

changes.

Option E is a variation of option D that takes into account a state’s

improvement in equity over time, from school year 1989-90 to school year

1991-92. First we calculated a factor similar to option D, using 1989-90

data, and determined the rate of change from 1989-90 to 1991-92. We then

multiplied option D by 1 plus the rate of change. Thus, for example, if the

state’s equity factor improved by 3 percent over that time, option E would

yield a 3-percent increase in the factor over option D. If a state’s level of

equity decreased by 3 percent, option E would be 3 percent lower than

option D. For example, if a state currently had an equity factor of 1.10

under option D and it improved by 3 percent, option E would be equal to

1.10 multiplied by 1.03, or 1.13. If, instead, it decreased by 3 percent over

this time, option E would be equal to 1.10 multiplied by 0.97, or 1.07.

We also developed two options, F and G, based on the McLoone Index,

which measures the extent to which the state brings up the expenditures

of those districts spending below the median. Option F is based on the

McLoone Index and includes the same adjustments for differences in

student needs and purchasing power across a state’s school districts.

Under the current law, states that are fully equalized receive a score of

1.30; states that are fully equalized using the McLoone Index receive a

score of 1.00. To ensure that the equity factors we developed were

comparable with the current equity factor, option F is equal to the

adjusted McLoone Index plus 0.30. (The 0.30 is determined by subtracting

1.00 from 1.30.) In this way, states that are fully equalized would receive a

score of 1.30, just as they currently do under the existing equity factor.

We also developed an equity factor based on the McLoone Index that takes

into account the rate of change in equity over time, which we refer to as

option G. We used the option F method to calculate indexes using data for

school years 1989-90 and 1991-92. Again, states that increase their level of

equity over time receive an increase in their equity factor under option G,

while those whose level of equity declines receive a lower score under

option G than option F.

As noted earlier, options D through G include limits such that the equity

factor cannot drop below 0.95 or rise above 1.30; the use of these limits

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Appendix IV 

Measuring Equity

affected few states. We also developed option H, which is identical to

option E except that it uses no limits. As shown in table IV.1, the equity

factors for options E and H are identical except for four states: California,

Louisiana, New York, and Rhode Island.

Table IV.1: Current and Alternative

Title I Equity Factors Alternative equity factors

State

Current equity

factora

Option

D

Option

E

Option

F

Option

G

Option

H

Alabama 1.17 1.19 1.18 1.21 1.20 1.18

Alaska 1.20b 0.99 1.03 1.02 0.95 1.03

Arizona 1.20 1.04 1.08 1.12 1.17 1.08

Arkansas 1.17 1.13 1.12 1.19 1.18 1.12

California 1.18 0.95 0.95 1.07 1.04 0.83

Colorado 1.18 1.12 1.11 1.18 1.18 1.11

Connecticut 1.16 1.02 1.01 1.05 1.06 1.01

Delaware 1.23 1.22 1.25 1.24 1.26 1.25

District of Columbiac 1.30 1.30 1.30 1.30 1.30 1.30

Florida 1.22 1.09 1.10 1.12 1.12 1.10

Georgia 1.14 1.16 1.15 1.19 1.19 1.15

Hawaiic 1.30 1.30 1.30 1.30 1.30 1.30

Idaho 1.17 1.07 1.07 1.16 1.13 1.07

Illinois 1.11 1.00 1.00 1.24 1.23 1.00

Indiana 1.18 1.15 1.16 1.19 1.19 1.16

Iowa 1.22 1.15 1.15 1.22 1.23 1.15

Kansas 1.20b 1.05 1.06 1.21 1.24 1.06

Kentucky 1.19 1.18 1.20 1.18 1.16 1.20

Louisiana 1.18 1.04 0.95 1.21 1.20 0.92

Maine 1.19 1.14 1.14 1.19 1.19 1.14

Maryland 1.14 1.20 1.22 1.19 1.19 1.22

Massachusetts 1.07 0.97 0.97 1.08 1.08 0.97

Michigan 1.09 1.14 1.16 1.21 1.20 1.16

Minnesota 1.17 1.12 1.13 1.21 1.27 1.13

Mississippi 1.18 1.17 1.17 1.22 1.21 1.17

Missouri 0.99 1.02 0.98 1.18 1.19 0.98

Montana 1.14 1.10 1.10 1.21 1.22 1.10

Nebraska 1.17 1.09 1.10 1.14 1.11 1.10

Nevada 1.21 1.16 1.18 1.30 1.30 1.18

New Hampshire 1.14 1.10 1.10 1.16 1.17 1.10

New Jersey 1.14 0.97 0.99 1.02 1.03 0.99

(continued)

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Appendix IV 

Measuring Equity

Alternative equity factors

State

Current equity

factora

Option

D

Option

E

Option

F

Option

G

Option

H

New Mexico 1.20b 1.01 1.01 1.06 1.02 1.01

New York 1.05 1.05 1.16 1.18 1.06 1.26

North Carolina 1.21 1.20 1.21 1.23 1.25 1.21

North Dakota 1.17 1.11 1.12 1.21 1.22 1.12

Ohio 1.07 1.09 1.08 1.16 1.14 1.08

Oklahoma 1.20 1.11 1.12 1.21 1.19 1.12

Oregon 1.16 1.09 1.09 1.15 1.15 1.09

Pennsylvania 1.10 1.09 1.10 1.16 1.15 1.10

Puerto Ricoc 1.30 1.30 1.30 1.30 1.30 1.30

Rhode Island 1.19 0.95 0.95 0.95 0.95 0.92

South Carolina 1.19 1.19 1.19 1.23 1.22 1.19

South Dakota 1.16 1.12 1.16 1.23 1.25 1.16

Tennessee 1.15 1.16 1.16 1.19 1.20 1.16

Texas 1.18 0.95 0.95 1.06 1.09 0.95

Utah 1.19 1.19 1.19 1.24 1.21 1.19

Vermont 1.12 1.10 1.10 1.18 1.21 1.10

Virginia 1.08 1.17 1.16 1.25 1.27 1.16

Washington 1.22 1.08 1.09 1.15 1.14 1.09

West Virginia 1.24 1.23 1.24 1.26 1.29 1.24

Wisconsin 1.18 1.13 1.13 1.18 1.17 1.13

Wyoming 1.15 1.12 1.12 1.25 1.28 1.12

aLiane White, Education Finance Incentive Grant Under ESEA Title I, Report for Congress No.

95-963 EPW (Washington, D.C.: Congressional Research Service, Sept. 12, 1995).

bThe current law provides that those states that qualify as equitable under the Impact Aid

program will receive a minimum equity factor of 1.20. Without this 1.20 minimum, the equity

factors would be 0.95 for Alaska, 1.16 for Kansas, and 1.16 for New Mexico.

cThe current equity factor for the District of Columbia, Hawaii, and Puerto Rico is 1.30 because

they each have only one school district and, therefore, no spending disparities across school

districts. For the same reason, these states receive a score of 1.30 under the alternatives we

developed.

Correlations Between

Equity and

Demographic

Characteristics

We examined the correlations between equity and states’ demographic

characteristics, such as state median income, within-state deviations in

median household income, state percentage of school-age children in

poverty, and within-state deviations in percentage of school-age children

in poverty. We examined the extent to which title I’s current equity factor

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Appendix IV 

Measuring Equity

and the alternative equity factors we developed were related to these

demographic factors.52

When we examined the correlation between the various equity factors and

variability in median household income across a state’s districts, we found

that the variable “within state deviations in median household income”

was negatively correlated with each equity factor.53 That is, the lower the

variability in median household income across districts in the state, the

higher the equity factor, and vice versa. The association was strongest,

however, for the current equity factor and weakest for the three

alternatives that consider improvement in equity over time—options E, G,

and H (see table IV.2).

Table IV.2: Correlations Between the

Equity Factors and State Demographic

Characteristics Characteristic

Current

measure

Option

D

Option

E

Option

F

Option

G

Option

H

State median

household income –0.11 –0.03 –0.04 –0.09 –0.01 –0.05

Within-state

deviations in median

household income –0.57a –0.50a –0.43a –0.48a –0.45a –0.36a

Percentage of

school-age children

in poverty 0.13 0.07 –0.01 0.13 0.08 –0.02

Within-state

deviations in

percentage of

school-age children

in poverty –0.37a –0.44a –0.40a –0.42a –0.37a –0.35a

aSignificant at the 0.05 level.

Each of the equity factors we developed, however, as well as the current

one, was negatively correlated with the variable “within-state deviations in

percentage of school-age children in poverty.” We found no correlation

between a state’s percentage of school-age children in poverty and the five

alternative equity factors we developed; similarly, there was no correlation

for the current equity factor. In addition, there was no significant

correlation between a state’s median household income and the current or

alternative equity factors.

52We did not include the District of Columbia, Hawaii, or Puerto Rico in any of the correlations, as they

each comprise only one school district.

53Two variables, state median household income and within-state deviations in median household

income, were adjusted for differences in purchasing power.

Page 38 GAO/HEHS-96-142 Effort and Equity Measures
Appendix V 

Illustrative Alternative Allocations Using

New Measures

To show how improved measures might be used, this appendix provides

illustrative allocations using the current formula for the Education

Finance Incentive Program along with alternative formulas we developed;

we also provide a state-by-state estimate of allocations under the targeted

grant formula for comparison purposes. While NCES data are sufficient for

the purposes of illustrating the general effects of changes in the effort and

equity factors, NCES may want to address a number of cases of missing

data or irregularities in the school district databases.

As noted earlier, if funds were appropriated for the Education Finance

Incentive Program, each state’s grant would be determined by the formula

in figure V.1.

Figure V.1: Formula for Determining

State Share

Total School-Age Population

x x Effort Factor Equity Factor State Share =

We noted earlier that two of the effort factor options we developed,

options B and C, have several benefits compared with the current effort

factor. For example, options B and C (1) are more comprehensive, (2) are

not biased against states with high proportions of school-age children, and

(3) include an incentive for states that improve their level of effort over

time. Equity options E, G, and H also have several benefits compared with

the current equity factor: (1) they consider the additional education costs

related to numbers of students with limited English proficiency or

disabilities, in addition to poor students; (2) they consider differences in

purchasing power across districts; and (3) they include a bonus for states

that become more equitable over time. Preferences for options E or H

versus option G depend on interest in measuring variation in spending

levels for all school districts in the state (options E or H) or focusing on a

state’s ability to bring low-spending school districts up to the median

(option G).

Figure V.2 shows the three illustrative alternative formulas based, in part,

on the alternative effort and equity factors we developed.

Page 39 GAO/HEHS-96-142 Effort and Equity Measures
Appendix V 

Illustrative Alternative Allocations Using

New Measures

Figure V.2: Examples of Alternative

Formulas

Total School-Age Population Effort Option B

Equity Option E

x

x Alternative 1 =

Total School-Age Population Effort Option B

Equity Option G

x

x

Alternative 2 =

Poor School-Age Population Effort Option B

Equity Option E

x

x

Alternative 3 =

Poor School-Age Population Effort Option C

Equity Option H

x

x

Alternative 4 =

Table V.I: Illustrative State Allocations Under Current and Alternative Title I Formulas—Education Finance Incentive

Program and Targeted Grants

Alternative

Dollars in Thousands

State Current formula 1 2 3a 4a

Targeted

grantsb

Alabama 3,099 3,275 3,135 4,525 4,306 3,498

Alaska 612 529 500 500 500 458

Arizona 3,225 3,344 3,437 3,492 3,439 3,210

Arkansas 1,850 1,993 1,986 2,741 2,753 2,146

California 23,378 19,839 20,539 19,728 17,177 26,812

Colorado 2,808 2,860 2,869 2,104 2,135 1,706

Connecticut 2,428 2,055 2,022 1,182 1,199 1,404

Delaware 573 554 527 500 500 476

District of Columbia 500 500 500 545 500 552

Florida 10,034 9,030 8,668 8,311 8,260 8,044

Georgia 5,174 5,937 5,781 6,219 6,184 4,414

Hawaii 922 981 925 609 579 500

Idaho 996 985 982 766 777 500

Illinois 8,261 7,726 8,982 7,627 7,579 10,766

Indiana 4,565 4,897 4,734 3,806 3,968 2,410

Iowa 2,309 2,450 2,480 1,858 1,901 1,012

Kansas 2,082 2,090 2,301 1,597 1,588 1,092

(continued)

Page 40 GAO/HEHS-96-142 Effort and Equity Measures
Appendix V 

Illustrative Alternative Allocations Using

New Measures

Alternative

Dollars in Thousands

State Current formula 1 2 3a 4a

Targeted

grantsb

Kentucky 2,953 3,143 2,850 4,328 4,391 3,594

Louisiana 3,715 3,047 3,637 5,500 5,269 6,242

Maine 1,014 1,029 1,011 759 849 500

Maryland 3,787 3,928 3,607 2,321 2,355 2,350

Massachusetts 4,027 3,464 3,643 2,485 2,469 3,306

Michigan 7,426 8,341 8,128 8,325 9,237 8,964

Minnesota 3,824 4,045 4,264 2,671 2,631 1,914

Mississippi 2,205 2,286 2,243 4,413 4,292 4,268

Missouri 3,377 3,505 4,022 3,286 3,300 3,168

Montana 763 742 772 746 817 580

Nebraska 1,289 1,419 1,344 1,044 1,039 664

Nevada 1,069 1,099 1,144 597 562 500

New Hampshire 819 878 877 500 500 492

New Jersey 5,771 5,222 5,133 3,224 3,394 3,648

New Mexico 1,457 1,395 1,332 1,976 1,965 1,812

New York 12,276 14,243 12,268 16,092 17,645 21,120

North Carolina 5,097 5,388 5,232 4,794 4,561 2,994

North Dakota 512 513 530 500 500 500

Ohio 8,296 8,817 8,772 8,513 8,876 7,896

Oklahoma 2,607 2,850 2,847 3,189 3,142 2,186

Oregon 2,503 2,465 2,447 1,833 1,946 1,444

Pennsylvania 8,658 9,025 8,928 7,816 7,775 8,306

Puerto Rico 3,757 3,959 3,732 8,000 8,000 6,928

Rhode Island 752 633 597 500 500 534

South Carolina 2,830 3,066 2,968 3,609 3,589 2,386

South Dakota 608 653 663 702 705 518

Tennessee 3,618 4,026 3,907 4,567 3,984 3,140

Texas 14,941 13,372 14,505 17,091 17,194 19,694

Utah 1,985 2,296 2,204 1,393 1,439 810

Vermont 500 500 500 500 500 460

Virginia 4,167 4,705 4,832 3,339 3,388 2,320

Washington 4,184 4,379 4,302 3,032 3,016 2,412

West Virginia 1,491 1,573 1,539 2,341 2,709 1,810

Wisconsin 4,406 4,449 4,354 3,404 3,614 3,054

Wyoming 500 500 500 500 500 482

(Table notes on next page)

Page 41 GAO/HEHS-96-142 Effort and Equity Measures
Appendix V 

Illustrative Alternative Allocations Using

New Measures

aFor alternatives 3 and 4, Puerto Rico’s allocation has been set to a maximum of $8 million.

bThese estimates of allocations for targeted grants are based on estimates in Riddle, Education

for the Disadvantaged, pp. 19-22. While we adjusted the estimates to account for allocating

$200 million rather than $100 million, we have not updated these estimates, for example, to take

into account state per pupil spending data that have become available in the past year. However,

we do not anticipate major shifts in allocations from one year to the next.

Page 42 GAO/HEHS-96-142 Effort and Equity Measures
Appendix VI 

Implications for Impact Aid

In addition to an overview of the Impact Aid program and the way that

equalization is defined for this program, this appendix discusses some of

the strengths and weaknesses of that definition.

Overview of the

Impact Aid Program

The Impact Aid program is intended to compensate school districts for

either a loss of tax revenues, because federal property is tax exempt, or

increased expenditures because of federal activity, for example, the cost

of educating the children of military personnel. Under the Impact Aid

program, if a state meets a certain equalization level, it may reduce state

aid payments to offset the Impact Aid received by school districts.54 In this

way, these states can ensure that Impact Aid funds will not contribute to

creating greater inequalities within the state. If the state does not pass

Impact Aid’s test of equalization, it may not consider federal Impact Aid

payments to its localities in determining state aid (which would be likely

to result in decreasing state aid to those districts) because the Impact Aid

payments are meant for localities, not states.

Ways to Determine

Equalization

Prior to the reauthorization of the Impact Aid program in 1994, the

Department of Education asked education finance experts to examine the

way that equalization is determined in the program.55 These experts

suggested, among other things, two improvements: (1) use measures of

spending disparities that are more comprehensive than the Federal Range

Ratio, and (2) consider differences in purchasing power and student needs

more systematically. Both issues are still relevant.

The measure currently used to determine the level of equalization in per

pupil spending in the Impact Aid program, the Federal Range Ratio, is the

difference in per pupil expenditures between two districts—a

high-spending district (95th percentile) and a low-spending district (5th

percentile)—divided by the per pupil expenditure of the low-spending

district. One major drawback of this measure is that it does not consider

spending in a majority of each state’s school districts; it only considers

spending in two of the state’s school districts (at the 95th and 5th

percentiles). Consequently, two states with fairly different spending

patterns may have similar Federal Range Ratio scores. For example, one

54However, states that qualify as equalized can only consider the Impact Aid as local revenues “in

proportion to the share that local revenues covered under a state equalization program are of total

local revenues.”

55These experts included Robert Berne and Leanna Stiefel, K. Forbis Jordan, Allan Odden, and Richard

Salmon.

Page 43 GAO/HEHS-96-142 Effort and Equity Measures
Appendix VI 

Implications for Impact Aid

state may have per pupil spending clustered around the average spending

level with little variation between the two extremes of the 95th and 5th

percentiles, while another state may have per pupil spending that varies

greatly between these two points.

Also, the Impact Aid program’s system for determining a state’s level of

equalization does not consider the additional funds states may provide to

high-need areas. For example, some states provide additional funds to

take into account the greater needs of some types of students (such as

those who are poor or have limited English proficiency or disabilities) or

some types of districts (such as those in sparsely populated areas). On the

one hand, not including such funds is a strength of the way that

equalization is measured because states that contribute additional funds to

high-need areas are not penalized for these greater spending disparities.

On the other hand, the overall method of determining equalization is

weakened by not considering such funds (and making related

adjustments) because it may not adequately take into account the

circumstances of districts in high-need areas.

A number of implications arise from an analysis of the current method for

determining equalization under the Impact Aid program. First, the measure

of spending disparities may be misleading. Second, the way in which states

treat districts in high-need areas is not fully addressed. Third, few states

qualify as equalized under this measure. Fourth, to the extent that Impact

Aid may allow some districts to be compensated twice for the “impact” of

a federal presence—once by the federal government and once by the state

government—it may actually contribute to creating less, rather than more,

equalization in the state.56

56See James Fox, “The Equity and Efficiency of Intergovernmental Grants: The Case of State

Equalization Plans and Impact Aid,” paper prepared for the Annual Conference of the American

Education Finance Association (Salt Lake City, Utah: Mar. 20-23, 1996), p. 2.

Page 44 GAO/HEHS-96-142 Effort and Equity Measures
Appendix VII 

Comments From the Department of

Education

Page 45 GAO/HEHS-96-142 Effort and Equity Measures
Appendix VIII 

GAO Contacts and Acknowledgments

GAO Contacts Eleanor Johnson, Assistant Director, (202) 512-7209

Ellen Kehoe Schwartz, Evaluator-in-Charge, (202) 512-7052

Veronica Scott, Evaluator, (202) 512-7039

Staff

Acknowledgments

Robert Dinkelmeyer, Senior Analyst; Wayne Dow, Supervisory Operations

Research Analyst; Jerry Fastrup, Supervisory Economist; and Deborah

McCormick, Senior Social Science Analyst, provided technical advice

regarding statistical and school finance issues.

(104857) Page 46 GAO/HEHS-96-142 Effort and Equity Measures
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