United States General Accounting Office

GAO Report to Congressional Requesters

February 1997 SCHOOL FINANCE

State Efforts to Reduce

Funding Gaps Between

Poor and Wealthy

Districts

GAO/HEHS-97-31

GAO United States

General Accounting Office

Washington, D.C. 20548

Health, Education, and

Human Services Division

B-275105 

February 5, 1997

The Honorable Jeff Bingaman

The Honorable Christopher Dodd

The Honorable Carol Moseley-Braun

United States Senate

Children who come from poor families or live in poor communities often

have low levels of academic achievement and high dropout rates. In

addition, poor communities often lack the tax base to provide sufficient

funding for education programs, even when they tax themselves at high

rates. To counteract the adverse effects of poverty, the federal government

has funded education services for low achievers in poor areas through

specially targeted programs.1

 This federal effort, however, only

supplements the much larger role that state and local governments play.

Many states recognize the additional cost of educating poor students and

the struggle of poor districts to adequately fund the needs of their

students. States have used a variety of strategies to address these

problems. Given your interest in the issue, you asked us to determine

(1) the size of the gap in total (state and local combined) funding between

poor and wealthy school districts for each state, (2) the key factors that

affect the size of states’ funding gaps, and (3) the effect of states’ school

finance policies on the funding gap. In addition, you asked us to describe

the implications of this information for state policies.

To help answer these questions, we used school year 1991-92 district-level

data, the most recent available, to analyze each state except Hawaii.2

 We

supplemented this information by contacting education officials in the

states to determine the extent to which each state’s school finance system

had changed since the 1991-92 school year. We used standard school

finance measures and developed a new equity measure—implicit

foundation level—that accounts for the effects of state policies on the

funding levels of school districts. The implicit foundation level represents

the minimum total funding that a state’s districts could spend per student

if they were to make an equal local tax effort. Our approach helps explain

1

The Elementary and Secondary Education Act provides targeted programs to improve educational

opportunities for students such as those who are poor or who have disabilities or limited English

proficiency. Title I of this act is the largest federal education program for elementary and secondary

school children and is for those whose education attainment is below the level appropriate for their

age. It serves over 6 million children through supplemental instruction in reading, math, or language

arts.

2

We did not review state targeting in Hawaii because the entire state is one district.

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the structural forces that drive the inequities between wealthy and poor

districts. Unlike some other studies, our analyses account for geographic

differences in education costs and student need among districts3

 and use

income per pupil to measure districts’ ability to raise education revenues.4

Finally, we consulted with several school finance experts on the

methodology used in our review and the resulting information contained

in this report.5

 Appendixes I to V describe our methodology in greater

detail. See the glossary at the end of this report for definitions of key

terms. We conducted our work between March and December 1996 in

accordance with generally accepted government auditing standards.

Results in Brief Although most states pursued strategies to supplement the local funding of

poor school districts, wealthier districts in 37 states had more total (state

and local combined)6

 funding than poor districts in the 1991-92 school

year. This disparity existed even after adjusting for differences in

geographic and student need-related education costs.7

 On average, wealthy

districts had about 24 percent more total funding per weighted pupil than

poor districts.8

3

Because districts have different education costs, we adjusted all funding figures for geographic

differences in education costs by applying a recently developed teacher cost index. We also accounted

for differences in student need by adjusting the pupil count to give extra weight to those pupils who

were disabled or poor or by controlling for student need factors in our regressions.

4

Most school finance studies measure a district’s ability to raise revenues for education as district

wealth defined as property value per pupil. However, we used district income defined as resident

income per pupil, using total income data from the 1990 census, because we could not construct a

property value per pupil measure from the national district-level databases available. Furthermore,

beyond the field of school finance, income—as opposed to wealth—is the most commonly accepted

measure of the ability to raise revenue. The main limitation of our income measure is that it does not

include commercial or other nonresidential income and may therefore understate some districts’

ability to raise revenue.

5

School finance experts who reviewed our analyses and this report are Helen Ladd (Duke University),

Martin Orland (Department of Education’s National Center for Education Statistics (NCES)), and

Lawrence Picus (University of Southern California).

6

In this report, we refer to total funding as all revenue from local and state sources, including funds

used for capital expenditures and debt service. This excludes federal funding.

7

Unless otherwise noted, the figures in this report are in real dollars adjusted for cost and student need

differences within a state. App. V provides information on how to adjust each state’s figures to make

accurate national comparisons.

8

To account for differences in student need by district, disabled students were assigned a weight of 2.3

and poor students a weight of 1.2. These national weights were developed for the Department of

Education’s NCES. See app. II.

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Three factors affected the funding gap between a state’s poor and wealthy

districts.9

 First, the extent to which a state targeted funding to poor

districts affected the funding gap. Although targeting efforts typically

reduced funding gaps, they did not eliminate them. Second, a state’s share

of total funding can reduce the funding gap, even when the targeting effort

is low. Finally, the local tax effort to raise education funding affected the

funding gap. At the local level, the greater the tax effort that poor districts

were willing to make compared with wealthy districts, the smaller the gap

in funding between these two types of districts. Poor districts in 35 states

made a greater tax effort than wealthy districts.

Because all three of these factors can affect the funding gap, analyzing the

effects of state school finance policies (targeting and state share) required

excluding the effects of the local tax effort. To do this, we estimated the

foundation level that each state’s school finance policies implicitly

supported. This implicit foundation level estimates the minimum total

funding per pupil that districts could finance if they were to make the

same local tax effort.

Our resulting analysis showed wide variations in the implicit foundation

level that state school finance policies supported in school year 1991-92.

This variation ranged from $721 in New Hampshire to $5,415 in Alaska,

with a national average of $3,134 per weighted pupil.10 The implicit

foundation levels of almost all states were less than their state average

funding levels. In 14 states, the implicit foundation level was less than half

the state average funding level.11

Although the relative tax effort of poor and wealthy districts greatly

affects the funding gaps between these districts, higher implicit foundation

levels can help reduce the gaps. Therefore, states can further reduce the

9

For reporting purposes, we grouped the student population of each state into five groups. These

groups were determined by ranking the districts within a state according to increasing district income

and then dividing these districts into five groups, each with about the same student population. We

defined poor districts as those in the first group and wealthy districts as those in the fifth group.

Normally, each group consisted of about 20 percent of the student population. In some states,

however, the five groups may have differed greatly in the number of students because districts cannot

be statistically divided into smaller units. In a few states, one district (for example, New York City)

accounted for more than 20 percent of the student population and represented the entire group.

Nevada was divided into only four groups because of the distribution of the student population, with

the wealthiest group being group four.

10These amounts are adjusted nationally for differences in cost and need.

11The average is the maximum foundation level that is possible in a state given its total funding for

education. To achieve the maximum, states would have to optimize their policies to fund education

and target poor districts to enable all districts to finance the average funding level with an average tax

effort.

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funding gaps by increasing their targeting effort to poor districts,

increasing the state share of total funding, or increasing both. Officials in a

number of states reported making such changes between school years

1991-92 and 1995-96, although 25 states reported making little or no

changes in their targeting of poor districts or state share.

Background Until the 1800s, America’s schools were mainly private local entities. In the

mid-1800s, several states rewrote their constitutions to create statewide

public education systems and establish government responsibility for

financing schools.12 Today, all states have constitutional provisions on free

public education, and, based in part on these provisions, a number of state

courts have ruled that education is a fundamental right subject to equal

protection under the law.

The largest single federal elementary and secondary education grant

program is title I of the Elementary and Secondary Education Act. The

program, which began in 1965, continues to focus on providing

compensatory services to educationally disadvantaged children through

categorical, program-specific grants. The fiscal year 1997 appropriations

for title I compensatory education for the disadvantaged was $7.7 billion.

State and Local Funding

Varies

Federal aid, however, only provides about 7 percent of the funding for

elementary and secondary education. Nationwide, the other 93 percent is

about evenly split between state and local funding,13 although the state

share of total (state and local) funding for education varies by state.

Although states have increased their control over schools, state

contributions in the 1991-92 school year varied from 8 percent of total

funding in New Hampshire to 85 percent of total funding in New Mexico.14

States’ ability to fund education also varies. States with higher income

levels can provide more funding for their students. In the 1991-92 school

year, states’ average income per weighted pupil ranged from $41,385 in

Utah to $160,761 in New Jersey. States also vary in the number of students

with additional educational needs, such as poor or disabled students, who

tend to have education costs higher than average. For example, the

12Allan R. Odden and Lawrence O. Picus, School Finance: A Policy Perspective (New York:

McGraw-Hill, Inc., 1992), pp. 1-19.

13School Finance: Trends in U.S. Education Spending (GAO/HEHS-95-235, Sept. 15, 1995).

14Our analysis excludes Hawaii, where the state provided nearly 98 percent of the total funding,

exclusive of federal funding, in the 1991-92 school year.

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student poverty rate among states in 1989 ranged from about 33 percent in

Mississippi to under 8 percent in New Hampshire.

In addition, localities’ ability to raise revenues varies widely. Localities

raise revenues primarily through property taxes and, to a lesser extent,

through local sales and income taxes. However, a heavy reliance on local

property taxes as a major source of school revenue has produced funding

disparities because school districts’ property tax bases vary widely.

Localities with low property values usually have low funding per pupil

even with high tax rates; localities with high property values have high

funding per pupil even with low tax rates.15 Since the late 1960s, the

funding gaps arising from the continued reliance on local tax revenues

have led to litigation challenging the constitutionality of state school

finance systems, with varying results.

Achieving Equitable

School Finance Systems

Involves Complex Issues

Researchers concerned about the equity of school finance systems—that

is, the distribution of education funding—have focused on two important

definitions of equity: vertical equity and fiscal neutrality. Vertical equity

recognizes that legitimate differences occur among children and that some

students, such as those who are disabled, have low academic achievement,

or limited English proficiency, need additional educational services. After

adjusting the pupil count to give greater weight to those pupils who need

extra educational services and adjusting the funding for cost differences in

educational resources, some experts would argue that funding per

weighted pupil should be nearly equal among districts. Fiscal neutrality

asserts that no relationship should exist between educational spending per

pupil and local district property wealth per pupil (or some other measure

of fiscal capacity). That is, the quality of education should be a function

only of the entire state’s wealth, not of a locality’s. Unlike vertical equity,

which calls for nearly equal funding per weighted pupil among districts

after adjustments have been made, fiscal neutrality allows for differences

in funding as long as they are not related to the districts’ taxable wealth.

In addition to equity, researchers are also concerned about the adequacy

of educational resources. Education funding is termed adequate if it

enables each student to achieve some minimum level of academic

performance. Not much is known, however, about the level of funding

needed to achieve a certain level of performance. As a result, determining

an adequate level of funding for a district is difficult.

15Allan Odden, “School Finance in the 1990s,” Phi Delta Kappan, Vol. 73, No. 5 (1992), pp. 455-461.

Page 5 GAO/HEHS-97-31 Reducing Funding Gaps
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In response to legal and political pressures, states have sought to

equalize—that is, compensate for the differences in—districts’ abilities to

raise revenue for funding education. In general, states have used one or

both of the following equalization strategies: added new state or local

money to the school finance system to increase funding for poor districts

or redistributed the available funding to poor districts by modifying school

finance formulas. Redistributing education revenues may also include

recapturing the local revenues raised above an established level in wealthy

districts and giving them to poor districts.

One of the more common funding formulas used to equalize the ability of

districts to raise education revenues is the foundation program. A

foundation program sets an expenditure per pupil—the minimum

foundation—at a level that would provide at least a minimum-quality

education for every pupil. Usually, districts must put forth a minimum

local tax effort to receive state aid, which makes up the difference

between what localities raise by the required local tax effort and the

foundation amount. This funding formula results in states targeting more

state education funds, on a per pupil basis, to those districts with low tax

bases than to those with high tax bases.

Despite the seeming simplicity of this funding formula, equalizing school

finance systems is a complex and difficult undertaking. In a recent report,

we reviewed the experiences of three states that had used one or both of

the equalization strategies noted above.16 Although these states reported

reduced funding gaps, their legislative solutions reflected citizens’

concerns about increased taxes to raise more state revenues and concerns

of wealthy districts that wanted to maintain existing spending levels.

16School Finance: Three States’ Experiences With Equity in School Funding (GAO/HEHS-96-39,

Dec. 19, 1995).

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Wealthy Districts Had

More Education

Funding per Weighted

Pupil Than Poor

Districts in Most

States

Although most states pursued strategies to supplement the local funding in

their poorest districts, the strategies generally did not offset the advantage

of wealthy districts in raising local funds. These results occurred even

after adjusting for the geographic differences in education costs and

student needs within each state. In most states, the total funding per

weighted pupil17 in districts was still largely determined by districts’

income per weighted pupil.18 In other words, these states had not achieved

an income-based fiscal neutrality in their school finance system. On

average, wealthy districts had about 24 percent more total funding per

weighted pupil than poor districts.

Figure 1 ranks states according to the extent to which total funding of

school districts in school year 1991-92 was linked to district income. In

this figure, the center line, which equals a fiscal neutrality score of 0,

represents the goal of ensuring that education funding is unrelated to

differences in district income per weighted pupil. The figure shows that

the total funding of districts in 37 states favored wealthier districts; that is,

the total funding increased as the income of the district increased.19 In

three states the opposite occurred—the total funding decreased as district

income increased.20 Among the 37 states whose school funding favored

wealthier districts, the amount of funding available as district income

increased varied widely. At the high end of the 37 states, students in

Maryland had about $25 more in total funding for a $1,000 increase in

income per weighted pupil above the state average. At the low end,

students in Washington had only about $4 more for a $1,000 increase in

income per weighted pupil above the state average.21

17To account for differences in student need by district, disabled students were assigned a weight of

2.3 and poor students a weight of 1.2. These weights were developed for the Department of

Education’s NCES. See app. II.

18District income is a measure of a district’s ability to raise revenue for education, which we define as a

district’s income per pupil adjusted for within-state differences in geographic and student need-related

costs. This measure includes personal income but not commercial or nonresident income of a district.

Somewhat different fiscal neutrality scores may have resulted if these other income categories had

been included. See app. III for a discussion of this variable.

19However, another 8 states had positive fiscal neutrality scores that were not significantly different

from 0. These were Delaware, West Virginia, Utah, Iowa, Kansas, Mississippi, New Mexico, and Texas.

20However, one state—Wyoming—had a negative fiscal neutrality score that was not significantly

different from 0.

21Washington had the lowest positive fiscal neutrality score that was significantly different from 0.

Page 7 GAO/HEHS-97-31 Reducing Funding Gaps
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Figure 1: Wealthy Districts in Most States Had More Total Funding per Weighted Pupil Than Poor Districts, School Year

1991-92

Maryland

Massachusetts

Montana

Virginia

New York

South Dakota

Missouri

Illinois

Georgia

Ohio

Pennsylvania

Michigan

Alabama

Rhode Island

North Carolina

Idaho

Tennessee

Connecticut

Florida

New Hampshire

North Dakota

Arkansas

Louisiana

Maine

Vermont

New Jersey

Oregon

Colorado

Nebraska

Indiana

South Carolina

Arizona

Wisconsin

Kentucky

Minnesota

California

Delaware

West Virginia

Washington

Utah

Iowa

Kansas

Mississippi

New Mexico

Texas

Oklahoma

Wyoming

Alaska

Nevada

-0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6

Fiscal Neutrality Score

Poor Districts Benefit Wealthy Districts Benefit

a

a

a

a

a

a

a

a

a

(Figure notes on next page)

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Note: Fiscal neutrality = 0. In states with positive scores, total funding increased as district

income increased; in states with negative scores, total funding decreased as district income

increased. The fiscal neutrality score (which controls for differences in cost and need) is the

elasticity of total funding per weighted pupil relative to income per weighted pupil.

aThe neutrality score was not statistically different from 0.

Three Key Factors

Affected Funding Gap

Three key factors affected the size of the funding gap between poor and

wealthy districts. Two of these—targeting of state funds to poor districts

and the state’s share of overall education funding—represent states’

school equalization policies. The third factor—the relative local tax effort22

of poor districts to wealthy districts—stems mainly from choices made at

the local level. In general, increases in any one of these decreases the

funding gap between poor and wealthy districts.

Nationwide, the three factors accounted for 61 percent of the variation in

the income-related funding gap. Of the three factors, targeting was the

least important in explaining the variation in funding gaps between

wealthy and poor districts. The state’s share of total funding accounted for

more of the variation in the income-related funding gap than targeting. The

relative local tax effort of poor districts to wealthy districts accounted for

most of the variation (see app. III).

Targeting State Funds to

Poor Districts Helped

Reduce Funding Gap

State targeting efforts23 typically helped to reduce but did not eliminate the

gap in total funding between wealthy and poor districts. These results

occurred even after adjusting for geographic differences in education

costs and student need.24 For example, Connecticut’s wealthy districts had

over three times the amount of local funding as its poor districts in school

year 1991-92 (see table 1). In contrast, the state funding was over three

times higher in poor districts compared with wealthy districts; the wealthy

districts still had, however, about 34 percent more total funding per

weighted pupil than the poor districts. In Connecticut, the gap in total

22Relative local tax effort is a state’s elasticity of local tax effort relative to income per weighted pupil.

Local tax effort is a ratio of a district’s local revenue to its income.

23We define a state’s targeting effort as the elasticity of the district’s state funding per pupil to the

district’s income per pupil, while controlling for within-state differences in student need-related and

geographic costs. See app. V for a list of the states’ targeting effort and an explanation of the method

we used to calculate the effort.

24We adjusted for student need by including student poverty, disability, high school, and enrollment

variables in the regression formula we used to determine state targeting effort. See app. V.

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funding between the poor and wealthy districts was $2,559. Appendix III

provides similar data for all states.

Table 1: Example of the Effect of a

State’s Targeting on Total Funding per

Weighted Pupil (Connecticut), School

Year 1991-92

Average funding per weighted pupila

Funding source

Poor group of

students

Wealthy group of

students

Wealthy funding

relative to poor

fundingb

Local $2,540 $8,486 3.34

State $4,885 $1,500 .31

Total $7,426 $9,985 1.34

aThe poor and wealthy groups each represent about 20 percent of the student population.

Figures do not add due to rounding.

bWe calculated this ratio by dividing the wealthy districts’ funding by the poor districts’ funding,

that is, $8,486/$2,540.

Like Connecticut, most states (33 of 49) targeted more state funds to poor

districts to some degree on the basis of district income.25 Of the remaining

16 states, 14 provided approximately equal state funding to poor and

wealthy districts.26 Two states—Louisiana and North Dakota—provided

more state funding to wealthy districts than to poor districts.

Among the states that targeted more funds to poor districts, the additional

amount of state funding varied widely.27 For example, for a $1,000

decrease in district income below the state average, Nevada provided

about $42 more in state funding per weighted pupil;28 Indiana provided

about $6 more in state funding per weighted pupil.29 Appendix V provides

information on all the states’ targeting efforts.

25Somewhat different targeting efforts may have resulted if the measure of district income had

included nonresident and commercial income in addition to resident income. See app. III for our

definition of district income.

26Statistically, these 14 states’ targeting efforts were not significantly different from 0.

27Some states provide a minimum amount of state funding to all districts, regardless of district income.

When we excluded the wealthiest 15 percent of the student population from our analysis, we found

that the targeting effort substantially improved for 15 states; that is, the elasticity changed by –.15 or

more. (See app. V.)

28Unlike total funding per weighted pupil, state funding per weighted pupil reflects each state’s

individual weighting of student need factors. We included variables in our estimation of state targeting

that controlled for the student need-related costs associated with educating poor, disabled, and high

school students and large numbers of students. See app. V for further explanation.

29Nevada had a targeting elasticity of –1.007; Indiana had a targeting elasticity of –.099.

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A Higher State Share of

Overall Funding Offset

Funding Gap

A high state share of total education funding offsets income-related

funding gaps, even if the targeting effort is low. For example, Washington

had virtually no targeting effort but funded about 75 percent of the total

funding for education. The poorest districts in Washington had only

4 percent less ($229) to spend per weighted pupil than the wealthiest

districts. In contrast, Michigan had a relatively high targeting effort but

funded only about 33 percent of the total education funding in the state,

which was relatively low. As a result, the poorest districts in Michigan had

36 percent ($1,923) less to spend per weighted pupil than the wealthiest

districts (see figs. 2 and 3). Appendix V provides information on the state

share for all states.

Figure 2: Example of the Effect of a

Large State Share of Education Funds

on Minimum Targeting (Washington),

School Year 1991-92

Funding per Weighted Pupil

0

1000

2000

3000

4000

5000

6000

7000

Poorest

Wealthiest

Income Groups

Local Funding

State Funding

Note: Funding has been adjusted for differences in geographic and student need-related costs

within the state.

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Figure 3: Example of How Students in

Wealthy Districts May Have Had Much

More Funding Despite Extensive

Targeting (Michigan), School Year

1991-92

Funding per Weighted Pupil

0

1000

2000

3000

4000

5000

6000

7000

Poorest

Wealthiest

Income Groups

Local Funding

State Funding

Notes: Funding has been adjusted for differences in geographic and student need-related costs

within the state. Since school year 1991-92, Michigan has reported that its state share has

increased almost 45 percentage points, which could result in a different figure.

Relative Local Tax Effort

Affected Funding

The willingness of poor districts to tax themselves at a higher rate than

wealthy districts helped reduce the funding gap between poor and wealthy

districts. In 35 states, poor districts made a higher tax effort than wealthy

districts. The tax effort is defined as the ratio of district local funding to

district income.30 Poor districts must make a higher level of tax effort to

finance comparable education programs because the same tax effort

generates less revenue in poor districts than in wealthy districts. For

example, Kansas and Pennsylvania each targeted additional funds to poor

districts to about the same extent and funded about the same share of

total education funding. Kansas’ poor districts, however, taxed themselves

30Somewhat different local tax efforts may have resulted if the measure of district income had included

nonresident and commercial income in addition to resident income. See app. III for our definition of

district income.

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about 24 percent more than the state’s wealthy districts,31 while

Pennsylvania’s poor districts had about the same tax effort as its wealthy

districts. As a result, the gap in total funding between poor and wealthy

districts was smaller in Kansas than in Pennsylvania (see fig. 1).

State School Finance

Policies Reflected in

Implicit Foundation

Level and

Equalization Effort

To determine the effects of state school finance policies on the funding

gap between poor and wealthy districts, we analyzed states’ school finance

data. We developed a new equity measure, implicit foundation level, which

indicates the extent to which these policies enable districts to finance a

minimum quality education for each student with an equal tax effort. Then

we compared this level to the state average to determine states’

equalization efforts. This section describes how we developed these two

measures.

Implicit Foundation Level We determined the combined effects of state equalization policies

(targeting and state share), while excluding the effects of local tax effort.

To accomplish this, we viewed each state as if it were distributing state

funds according to a foundation program. In such a program, the state

ensures all districts the ability to finance a foundation or a minimum

amount of funding per pupil, provided that the districts make a minimum

local tax effort. Using a foundation funding model and assuming all

districts made an equal local tax effort, we estimated the implicit

foundation level that each state’s equalization policies in school year

1991-92 could have supported. This implicit foundation level is an estimate

of the minimum amount of total funding that states’ districts could spend

per student if districts were to make an equal minimum local tax effort.32

This new measure, for the first time, allows analysts to examine the extent

to which the funding gap between poor and wealthy districts is due to

state equalization policies (state share and state targeting) and the extent

to which it is due to local policies (relative differences in local tax efforts).

Appendix IV explains how we developed the implicit foundation level.

Figure 4 illustrates the implicit foundation level using a hypothetical

example of two districts in a state, one poor and one wealthy. For each

district, we graphed how much total funding per weighted pupil is

31However, since the 1992-93 school year, Kansas has allocated education funds through a new formula

that includes a statewide uniform tax rate for all districts.

32The implicit foundation level includes both state and local funds adjusted for within-state differences

in student need-related and geographic costs. After making such adjustments, the implicit foundation

level becomes total funding per weighted pupil. See apps. IV and V for a discussion of the methodology

we used to calculate the implicit foundation level.

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associated with a given level of tax effort.33 Since poor districts generally

receive more state funding per weighted pupil than wealthy districts, in

this example we assigned the poor district $2,500 in state funding per

weighted pupil, twice the amount the wealthy district was assigned.

Therefore, the line for the poor district starts out higher (the district has

more state money) on the graph than the line for the wealthy district

(which has less state money). As figure 4 shows, as both districts increase

their local tax effort, the wealthy district raises more local revenue than

the poor district for a given level of tax effort. For any given tax effort past

a certain point (where the lines cross on fig. 4), the wealthy district’s local

revenue more than offsets the additional state money that poor districts

receive—therefore, the total funding in wealthy districts exceeds total

funding in poor districts. The point at which the total funding lines cross is

the implicit foundation level and is the only point at which the two

districts have the same amount of total funding for the same tax effort.

33Since the student weights are relative to within-state differences, the student weight factors

associated with any state-level funding per pupil amount equal 1.

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Figure 4: Determining the Implicit Foundation Level

State Average

Minimum

Tax 

Effort

0 5 10 15 20

0

2,000

4,000

6,000

8,000

10,000

Tax Effort (Local Dollars per $1,000 of District Income)

Total Funding per Weighted Pupil (Dollars)

Wealthy District

Poor District

Implicit 

Foundation 

Level

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Equalization Effort We compared states’ implicit foundation levels with the maximum

foundation levels that would be possible given each state’s amount of total

funding devoted to education. We call this ratio a state’s equalization

effort. State average funding per weighted pupil is actually the maximum

foundation level (see app. IV for a mathematical explanation of this). A

state’s equalization effort is a measure of the extent to which districts in a

state can finance the state average with an average tax effort. To achieve

the maximum foundation level without changing the total funding for

education, a state could increase its effort to target funds to poor districts

or increase the state’s share of education funding or both.

States’ Implicit

Foundation Levels

and Equalization

Efforts Varied

States’ implicit foundation levels varied widely, averaging $3,134 per

weighted pupil, with levels ranging as low as $721 in New Hampshire to as

high as $5,415 in Alaska in school year 1991-92.34 In line with the purpose

of foundation programs, these implicit levels indicate the extent to which

states’ school finance policies ensure a level of funding assumed adequate

for districts to finance at least a minimum quality education for every

student with an equal local tax effort. Appendix V provides information on

the implicit foundation levels in each state.

States’ equalization efforts also varied. Only one state—Nevada—made the

maximum equalization effort given the total funding available for

education in the state. As a result, Nevada’s state school policies in school

year 1991-92 enabled each district to spend the state average on each

student with an average tax effort.35 The implicit foundation levels in the

other 48 states were less than their state averages, with equalization

efforts ranging from about 87 percent (Arkansas and Kentucky) to about

13 percent (New Hampshire). In 14 states, the implicit foundation level

was less than half the state average. Figure 5 summarizes the states’

equalization efforts in school year 1991-92.36

34These figures have been adjusted for national differences in geographic and student need-related

costs.

35In fact, Nevada targeted more state funds to poor districts than was necessary to allow districts to

spend the state average funding per weighted pupil with an average tax effort. As a result, poor

districts in Nevada were able to finance the state average funding level with a lower tax effort than

wealthy districts.

36In addition to targeting funds to poor districts, some states also provided the same minimum amount

of state funding to all districts, regardless of district income. Unlike funding for lower income districts,

such funding for wealthy districts was not part of the targeting effort because it was not sensitive to

district income. Consequently, we also estimated the state implicit foundation level and equalization

effort, assuming the goal was to have all students except for the 15 percent of students in the

wealthiest districts receive the implicit foundation level. Using this analysis, we found that 16 states

had a net increase of 10 percentage points or more in their equalization effort. See table V.9 in app. V

for the results of this analysis.

Page 16 GAO/HEHS-97-31 Reducing Funding Gaps
B-275105 

Figure 5: States’ Equalization Efforts, School Year 1991-92

Nevada

Arkansas

Kentucky

Florida

New Mexico

West Virginia

Minnesota

South Carolina

Oklahoma

California

Alaska

Colorado

Washington

Idaho

Delaware

Texas

Utah

Alabama

North Carolina

Georgia

New York

Rhode Island

Mississippi

Maine

Maryland

Louisiana

NATIONAL AVE.

Indiana

Wisconsin

Arizona

Connecticut

Kansas

Iowa

Pennsylvania

Virginia

Wyoming

Montana

Ohio

Michigan

North Dakota

New Jersey

Tennessee

Missouri

Vermont

Nebraska

Illinois

Massachusetts

Oregon

South Dakota

New Hampshire

0 10 20 30 40 50 60 70 80 90 100

Percentage

Page 17 GAO/HEHS-97-31 Reducing Funding Gaps
B-275105 

State Equalization Efforts

Helped Reduce Funding

Gaps

State equalization efforts, representing the combined effects of state

targeting and state share, have an important effect on reducing the funding

gap between poor and wealthy districts. When we controlled for the

differences in the tax effort of wealthy and poor districts in each state, we

found that states with higher equalization efforts tended to have smaller

funding gaps between poor and wealthy districts, as measured by their

fiscal neutrality scores (see app. V). However, differences in the tax effort

of wealthy and poor districts still accounted for more of the variation in

income-related funding gaps than did states’ equalization efforts.37 That is,

states’ finance policies, as measured by their equalization efforts, helped to

reduce the funding gap between poor and wealthy districts, but

differences in the tax effort of these districts continued to be the more

important determinant of the funding gap.

For example, Maryland had an above average equalization effort (about

63 percent), yet it also had the largest income-related funding gap (see fig.

1). This large gap can be explained in part by the relative local tax effort:

wealthy districts in Maryland made a tax effort that was about 53 percent

higher than the tax effort of poor districts, the highest such ratio in the

nation. Thus, despite Maryland’s substantial efforts to equalize funding, the

effort did not overcome the differences in local funding by district that

were due, in part, to the relatively high tax effort of wealthy districts (see

app. III).

Large Shifts in State

Targeting May Be

Necessary to

Maximize State

Equalization Efforts

To further reduce the funding gap between poor and wealthy districts,

states would need to increase their equalization effort by either increasing

their share of total funding, increasing their targeting effort to poor

districts, or increasing both. To illustrate the extent of the change that

would be needed to maximize a state’s equalization effort without any

increase in state funding, we analyzed state targeting in school year

1991-92, while holding the state share constant and assuming all districts

made an equal tax effort.38 Under this scenario, 48 states would have had

to reduce their funding of wealthy districts to increase their funding of

poor or middle-income districts39 or both. In many states, the magnitude of

the targeting change would have had to be significant to enable districts to

37Nationwide, equalization effort and relative local tax effort accounted for about 63 percent of the

variation in the income-related funding gap.

38In a forthcoming school finance report, we plan to more fully analyze how state targeting and state

share would need to change to reduce the funding gaps.

39We defined the middle-income districts as any one or more of the middle three income groups, which

combined represent about 60 percent of the student population.

Page 18 GAO/HEHS-97-31 Reducing Funding Gaps
B-275105 

spend the state average with an average tax effort. Relative to the

distribution needed to attain the state average for all students, 29 states

would have had to significantly shift their funding from wealthy districts to

poor or middle-income districts or both (see table 2).

Page 19 GAO/HEHS-97-31 Reducing Funding Gaps
B-275105 

Table 2: States That Would Have Had

to Significantly Shift Funds From

Wealthy Districts to Maximize

Equalization Efforts, School Year

1991-92

States needing to shift 35%

or more of state funds from

wealthy districts to poor or

middle-income districtsa

Would also have needed

to increase state funding

in poor districts by 35% or

more

Have changed school

finance system since

school year 1991-92 to

increase funding to

low-wealth districts

Arizona X

California

Colorado X

Connecticut X

Illinois X

Kansas X

Louisiana X

Maine

Maryland X X

Massachusetts X

Michigan X

Mississippi X

Missouri X X

Montana X X

Nebraska X X

New Hampshire X

New Jersey X

New York

North Dakota X

Ohio X

Oregon X X

Pennsylvania

Rhode Island X

South Dakota X

Tennessee X

Vermont X

Virginia

Wisconsin

Wyoming

aThe amount of shifting is based on a comparison of what state funding wealthy districts received

and the funding they would have received if all districts could have financed the state average

with an average tax effort and if no change had occurred in the state share or total funding for

education.

Page 20 GAO/HEHS-97-31 Reducing Funding Gaps
B-275105 

Detailed information on state equalization policies and changes in state

funding needed to enable districts to spend the state average for each

student with an average tax effort appears in the state profiles in this

report (see apps. VII through LV). Each profile provides information on

(1) the actual state and local funding distribution to districts in school year

1991-92 for districts in five groups of approximately equal student

population, according to increasing district income, and (2) how funding

would have been distributed among these groups if each district could

have financed the state’s average total funding per weighted pupil with an

average tax effort.40

Twenty-Five States

Reported Making

Little or No Changes

Since School Year

1991-92

We contacted state education officials to determine the extent to which

the states had changed their targeting effort and state share between

school years 1991-92 and 1995-96. Twenty-five states reported making little

or no changes to their targeting effort or state share. The remaining 24

states reported making targeting changes that may have increased their

implicit foundation levels. For example, education officials in Missouri

said that changes implemented in 1993 had increased targeting to

low-wealth districts and that the state’s new formula provides more state

funding to districts with both lower property wealth and higher tax

efforts.41 Six of the 24 states also reported making increases of

10 percentage points or more in their state share of education funding:

Tennessee (10), Colorado (11), Kansas (18), Utah (24), Oregon (30), and

Michigan (45).

In some cases, lawsuits challenging the constitutionality of a state’s school

finance system have prompted changes in targeting or state share. For

example, one lawsuit alleged that Tennessee’s school finance system

resulted in inequalities that violated the state constitution, and the state

has since significantly revised its system.42 Appendix LVI summarizes the

changes states have made between school years 1991-92 and 1995-96.

Of the 10 states noted in table 2 requiring the largest shifts in state funding

to poor districts, 5 reported making changes that provided more or much

40Critical data in each state profile include school year 1991-92 data on the state share of total funding,

the state targeting effort, the average total funding per weighted pupil, the implicit foundation level (in

dollars and as a percent of the average), the fiscal neutrality score, and state and group data for the

number of districts and pupils, poverty and disabled rates, income per pupil, and tax effort.

41We plan to analyze the effects of such increases in a forthcoming school finance report.

42For a discussion of Tennessee Small School System v. McWherter, 851 s.w.2d 139 (Tenn. 1993), see

GAO/HEHS-96-39, Dec. 19, 1995.

Page 21 GAO/HEHS-97-31 Reducing Funding Gaps
B-275105 

more state funding to low-wealth districts than in school year 1991-92. The

other five states reported making little or no changes to their school

finance system by school year 1995-96.43

Conclusions Recognizing the struggle of poor districts to adequately fund the education

needs of their students, states have used several strategies to reduce the

funding gap between poor and wealthy districts. States that want to

further reduce the funding gap between poor and wealthy districts would

have to continue to increase the state share of total funding, increase their

targeting effort to poor districts, or increase both. If targeting is increased,

poor and middle-income districts would receive more state funding, while

wealthy districts would receive less state funding. States may also increase

their state share of education funding. A higher state share can offset

income-related gaps even if the targeting effort is low, according to our

analysis. However, making such changes may be difficult because of

taxpayer concerns.

Decisionmakers and others can use the measures in this report—

particularly the fiscal neutrality score, implicit foundation level, and

equalization effort—to assess the equity effects of current and proposed

changes in state school finance policies. In addition, the implicit

foundation level, when compared to a standard like the state average, can

be used as a measure of the adequacy of funding provided by a state’s

school finance system. Moreover, these measures can be used to assess

progress over time in achieving more equity in school finance systems

within states.

Agency Comments The Department of Education reviewed a draft of this report and had no

comments.

As agreed with your office, unless you publicly announce its contents

earlier, we plan no further distribution of this report until 30 days from the

date of this letter. At that time, we will send copies to appropriate

congressional committees and all members of the Congress, the Secretary

of Education, and other interested parties.

43The five states that reported making changes as of school year 1995-96 to increase funding for

low-wealth districts were Maryland, Missouri, Montana, Nebraska, and Oregon. The five states that

reported making little or no changes since school year 1991-92 were Arizona, Illinois, New Hampshire,

South Dakota, and Vermont. South Dakota reported making a change that would target more funding

to low-wealth districts as of January 1997.

Page 22 GAO/HEHS-97-31 Reducing Funding Gaps
B-275105 

Please contact me on (202) 512-7014 or Eleanor L. Johnson, Assistant

Director, on (202) 512-7209 if you or your staff have any questions. GAO

contacts and staff acknowledgments appear in appendix LVII.

Carlotta C. Joyner

Director, Education and

 Employment Issues

Page 23 GAO/HEHS-97-31 Reducing Funding Gaps
Contents

Letter 1

Appendix I 

Scope and

Methodology

Overview

32

Scope 32

Data Sources 32

Methodology 33

Appendix II 

Adjusting for

Geographic and

Student Need-Related

Differences in

Education Costs

36

Adjusting for Differences in Educational Resource Costs 37

Adjusting for Differences in Student Need 38

Appendix III 

Analysis of Fiscal

Neutrality

43

Calculating Fiscal Neutrality Scores 43

Relationship Between Funding Gaps and State Share, State

Targeting, and Relative Local Tax Effort

53

Appendix IV 

Estimating States’

Targeting Efforts,

Implicit Foundation

Levels, and

Equalization Efforts

61

Equalizing School Funding With a Foundation Program 61

State Targeting Necessary to Achieve the Maximum Foundation

Level

63

State Targeting That Produces an Implicit Foundation Level

Below the State Average

66

Appendix V 

Estimating Equity

Measures

71

Calculating State Targeting Efforts 71

Calculating State Implicit Foundation Levels and Equalization

Effort

86

Funding Gaps, State Equalization Effort, and Relative Local Tax

Effort

96

Page 24 GAO/HEHS-97-31 Reducing Funding Gaps
Contents

Appendix VI 

Guide to State Profiles

98

Appendix VII 

State Profile: Alabama

100

Appendix VIII 

State Profile: Alaska

104

Appendix IX 

State Profile: Arizona

108

Appendix X 

State Profile:

Arkansas

113

Appendix XI 

State Profile:

California

117

Appendix XII 

State Profile:

Colorado

121

Appendix XIII 

State Profile:

Connecticut

125

Appendix XIV 

State Profile:

Delaware

130

Page 25 GAO/HEHS-97-31 Reducing Funding Gaps
Contents

Appendix XV 

State Profile: Florida

134

Appendix XVI 

State Profile: Georgia

138

Appendix XVII 

State Profile: Idaho

142

Appendix XVIII 

State Profile: Illinois

146

Appendix XIX 

State Profile: Indiana

151

Appendix XX 

State Profile: Iowa

155

Appendix XXI 

State Profile: Kansas

159

Appendix XXII 

State Profile:

Kentucky

163

Appendix XXIII 

State Profile:

Louisiana

167

Appendix XXIV 

State Profile: Maine

171

Page 26 GAO/HEHS-97-31 Reducing Funding Gaps
Contents

Appendix XXV 

State Profile:

Maryland

175

Appendix XXVI 

State Profile:

Massachusetts

179

Appendix XXVII 

State Profile:

Michigan

184

Appendix XXVIII 

State Profile:

Minnesota

189

Appendix XXIX 

State Profile:

Mississippi

194

Appendix XXX 

State Profile: Missouri

198

Appendix XXXI 

State Profile: Montana

202

Appendix XXXII 

State Profile:

Nebraska

207

Appendix XXXIII 

State Profile: Nevada

212

Page 27 GAO/HEHS-97-31 Reducing Funding Gaps
Contents

Appendix XXXIV 

State Profile: New

Hampshire

217

Appendix XXXV 

State Profile: New

Jersey

222

Appendix XXXVI 

State Profile: New

Mexico

227

Appendix XXXVII 

State Profile: New

York

232

Appendix XXXVIII 

State Profile: North

Carolina

237

Appendix XXXIX 

State Profile: North

Dakota

242

Appendix XL 

State Profile: Ohio

247

Appendix XLI 

State Profile:

Oklahoma

251

Page 28 GAO/HEHS-97-31 Reducing Funding Gaps
Contents

Appendix XLII 

State Profile: Oregon

255

Appendix XLIII 

State Profile:

Pennsylvania

260

Appendix XLIV 

State Profile: Rhode

Island

264

Appendix XLV 

State Profile: South

Carolina

268

Appendix XLVI 

State Profile: South

Dakota

272

Appendix XLVII 

State Profile:

Tennessee

276

Appendix XLVIII 

State Profile: Texas

280

Appendix XLIX 

State Profile: Utah

285

Appendix L 

State Profile: Vermont

289

Page 29 GAO/HEHS-97-31 Reducing Funding Gaps
Contents

Appendix LI 

State Profile: Virginia

294

Appendix LII 

State Profile:

Washington

299

Appendix LIII 

State Profile: West

Virginia

303

Appendix LIV 

State Profile:

Wisconsin

307

Appendix LV 

State Profile:

Wyoming

311

Appendix LVI 

State Survey Results

315

Appendix LVII 

GAO Contacts and

Staff

Acknowledgments

318

Glossary 319

Abbreviations

CCD Common Core of Data

NCES National Center for Education Statistics

TTR total taxable resources

Page 30 GAO/HEHS-97-31 Reducing Funding Gaps
Page 31 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix I 

Scope and Methodology Overview

The objectives of this study were to determine (1) the size of the gap in

total (state and local combined) funding between poor and wealthy school

districts for each state, (2) the key factors that affect the size of states’

funding gaps, and (3) the effect of states’ school finance policies on the

funding gaps. To help answer these questions, we used school year 1991-92

district-level data from the Department of Education, the most recent

available, and supplemented these data when key data were missing. We

used standard school finance measures and developed a new method to

measure the effect of state policies on the funding levels of school

districts.44 We supplemented our analysis by contacting education officials

in the states to determine the extent to which a state’s school finance

system had changed since school year 1991-92.

Scope For this study, we conducted a district-level analysis of all states except

Hawaii.45 We wanted our analysis to examine state funding for regular

school districts with students in grades kindergarten to 12, so the analysis

excluded administrative districts and districts serving unique student

populations, such as vocational or special education schools.46 Our

analysis also excluded a number of small districts that had extreme

outlying values of income per pupil.47 Finally, we excluded districts that

lacked data for critical variables, such as poverty level. The 2,235 districts

excluded from the analysis had a total enrollment of 335,558. The final

database used in our analysis of the 49 states contained 14,425 districts

with a total of 41,204,610 students, representing 99.2 percent of the

students in 49 states.

Data Sources This study was based mainly on revenue and demographic data obtained

from the Department of Education’s Common Core of Data (CCD) for the

44Various school finance experts reviewed this new method. The following experts were involved in

early discussions and reviewed drafts of this report: Helen Ladd (Duke University), Martin Orland

(Department of Education’s National Center for Education Statistics), and Lawrence Picus (University

of Southern California).

45Hawaii’s state school system is considered one district, so no comparisons can be made about state

allocations to different districts. Similarly, the District of Columbia and five U.S. territories (American

Samoa, Guam, Northern Marianas, Puerto Rico, and Virgin Islands) have one-district systems and were

not included in our analysis.

46That is, we excluded districts in the Common Core of Data (CCD) with agency type codes 3 to 7 and

school district codes 4 to 7.

47A total of 49 districts were excluded as outliers using the method developed by David A. Belsley,

Edwin Kuh, and Roy E. Welsch, Regression Diagnostics: Identifying Influential Data and Sources of

Collinearity (New York: John Wiley and Sons, 1980), pp. 27-30. Specifically, we used their DFBETA

statistic as the basis for deleting outlying observations.

Page 32 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix I 

Scope and Methodology Overview

1991-92 school year, the most current data available for a national set of

districts. Data for the CCD were submitted by state education agencies and

edited by the Education Department. We obtained district per capita

income and population data directly from the 1990 census because they

were not available in the CCD.

For variables in our analysis that had missing or incomplete data, we

obtained the data directly from state education offices. For example, we

obtained district-level data for disabled students for school year 1991-92

directly from the state education offices for nine states because the CCD

either did not report the number of disabled students in the states or

reported a number substantially different from one reported by another

Education Department source.48 We made further edits on the basis of

consultations with Department of Education experts.

In some cases, we imputed critical data when they were missing and not

available from other sources. We imputed income per pupil data for 199

districts in California because the per capita income data needed to

compute this variable were not reported by these districts.49 We also

imputed cost index data for 310 districts, including 18 in Alaska and 72 in

New York (mainly Suffolk County).50 The imputation method we used to

impute cost index data was based on the recommendation of the school

finance expert who developed the cost index.

We conducted structured telephone interviews with state school finance

officials to determine the extent to which states had changed their school

finance systems since school year 1991-92. We did not, however, verify the

accuracy of the officials’ statements.

Methodology To measure the size of the gap in total funding between poor and wealthy

districts, we used the elasticity of total (state and local) funding in a

48The CCD did not report disabled student data for Kentucky, Ohio, Oklahoma, Pennsylvania, and

Virginia. The CCD provided data on disabled students for Illinois, Indiana, Louisiana, and New Jersey

that were at least 15 percent different than and at least 3,500 disabled students different from those

reported by the Department of Education’s Office of Special Education and Rehabilitative Services for

school year 1991-92.

49We developed a formula to predict the income per pupil of the missing districts by running a

regression between income per pupil and median housing value for districts in California whose

median housing value was at least $5,000.

50Cost index values for these districts were imputed using the value from a district with a similar

enrollment in the same or a similar county.

Page 33 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix I 

Scope and Methodology Overview

district relative to district income,51 a measure of a district’s ability to raise

revenue for education. In a regression model, we used dependent and

independent variables that were adjusted for differences in geographic

cost and student need within the state and put into index form52 (see app.

II). A district’s total funding per weighted pupil was the dependent

variable; a district’s income per weighted pupil was the independent

variable.53 Each observation was weighted by the district size to allow

districts with larger enrollments to have a greater effect on the results.

Appendix III describes this process in detail.

To determine the relationship between the total funding gaps and the key

factors affecting the size of the gaps, we conducted a regression analysis

using a state’s fiscal neutrality score (the elasticity of total funding to

district income) as the dependent variable and the following as

independent variables:

• a state’s share of total funding,

• a state’s targeting effort (described in this app.), and

• a state’s relative local tax effort (the elasticity of local tax effort relative to

district income—see app. III).

To measure the extent to which states targeted their education funds to

poor districts, we estimated the elasticity of state funding in a district

relative to district income.54 Using a regression model, we defined the

dependent variable as a district’s state funding per pupil and the key

independent variable as a district’s income per pupil. Both variables were

adjusted for differences in geographic cost within the state (see app. II).

To control for student need and economies of scale, we included four

additional independent variables: poor students, disabled students, high

school students, and district size. All variables in the analysis were put into

index form and were included in the regression. Each observation was

weighted by the district size to allow districts with larger enrollments to

have a greater effect on the results. We set certain constraints on the

regression coefficients. The resulting regression coefficient of the income

51This elasticity measures the average percent change in total funding for a 1-percent increase in a

district’s income.

52To derive the index form of each variable, we measured all variables as district rates and then divided

the district rate by its corresponding state average.

53A better income measure of a district’s ability to raise revenue for education would include

commercial and other nonresidential income in addition to personal income. However, such

district-level data are not available for all states in a national database. Therefore, we used total

income data from the 1990 census to determine income per pupil. App. III further explains this

measure of district income.

54This elasticity measures the average percent change in state funding for a 1-percent increase in a

district’s income.

Page 34 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix I 

Scope and Methodology Overview

per pupil variable is our measure of a state’s targeting effort and measures

the elasticity of state funding relative to district income. Appendix V

describes this methodology in greater detail.

We developed an equity measure—implicit foundation level—to assess the

state policies (targeting and state share) that affect the funding gap

between wealthy and poor districts. We calculated this measure using a

formula involving a state’s share of total funding, a state’s targeting effort,

and a state’s average total funding per weighted pupil. To calculate the

targeting effort in this formula, we used the same multivariate linear

regression as the one already described, except we imposed the restriction

that the income per pupil variable have a nonpositive coefficient.

Appendix IV explains the theory behind the equity measure we developed,

and appendix V explains the regression.

Appendixes VII through LV provide profiles of each state’s school finances

in school year 1991-92. The profiles provide summary information on the

total funding per weighted pupil, states’ share of education funding, states’

targeting effort, implicit foundation level, equalization effort, and fiscal

neutrality score. To report the state profiles for school year 1991-92, we

ranked each state’s districts according to increasing district income and

then divided the districts into five groups, each with about the same

number of students.55 We then calculated the mean state, local, and total

funding per weighted pupil for each group. These funding figures were

also adjusted for differences in geographic costs within the state (see app.

II). Appendix VI provides an overview of the state profiles.

Because we relied on state and local funding data from the 1991-92 school

year, we telephoned state school finance officials to determine what

changes had occurred in the school finance systems from school years

1991-92 through 1995-96. We specifically asked about changes in targeting

that would affect low-wealth districts and changes in the state’s share of

total funding. Appendix LVI presents interview results.

55Normally, each group consisted of about 20 percent of the student population. In some states,

however, the five groups may have had large differences in the number of students because our

analysis was at the district level and districts cannot be statistically divided into smaller units. In a few

states, one district (for example, in Las Vegas and New York City) accounted for more than 20 percent

of the student population and represented the entire group. Finally, Nevada was divided into only four

groups because of the distribution of the student population.

Page 35 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix II 

Adjusting for Geographic and Student

Need-Related Differences in Education

Costs

Education costs vary by school district in a state (and nationwide)

because of geographic differences in the cost of educational resources and

in the number of students with special needs. The cost of educational

resources may vary across districts for several reasons. For example, a

district may be able to hire a teacher of a given quality at a lower rate than

other districts because the district may have a lower cost of living or offer

certain amenities or working conditions that are more attractive to

teachers than the other districts. Also, districts with either large or small

student populations may face higher costs than other districts because of

the diseconomies of scale that can occur in providing services at these

levels.56

The cost of educating students also varies for a number of other reasons.

Districts with high proportions of students with special needs, such as the

disabled, the poor, and those with limited English proficiency, generally

have higher education costs than average because such students require

additional educational services. Furthermore, districts that largely serve

high school students tend to have higher per pupil education costs than

those that largely serve elementary students.57

As discussed in our previous report on equity measures,58 when estimating

comparable measures of funding levels or disparities among districts,

accounting for districts’ differences in educational resource costs and

student needs is useful. This appendix discusses how we made these

adjustments in our study.

56Allan R. Odden and Lawrence O. Picus, School Finance: A Policy Perspective (New York:

McGraw-Hill, Inc., 1992), pp. 235-238.

57However, one expert reviewer suggested that the cost of educating elementary students in the

primary grades may have increased compared with educating high school students because of recent

state efforts to lower the student-teacher ratio in these early elementary years.

58School Finance: Options for Improving Measures of Effort and Equity in Title I (GAO/HEHS-96-142,

Aug. 30, 1996).

Page 36 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix II 

Adjusting for Geographic and Student

Need-Related Differences in Education

Costs

Adjusting for

Differences in

Educational Resource

Costs

To adjust for geographic differences in resource costs by district, we used

a national district-level teacher cost index recently developed for the

National Center for Education Statistics (NCES).59 Although an index that

examines differences in the cost of living is available by district,60 the NCES

teacher cost index is better suited to comparing districts by considering

the purchasing power of districts in determining personnel-related costs, a

major cost to school districts.61 Our focus is on a 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 a state. For example, the cost of books,

instructional materials, and other supplies and equipment tends to vary

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

teacher cost index only to adjust the 84.8 percent of current expenditures

estimated to relate to personnel costs, including salaries, fringe benefits,

and some purchased services.62

Finally, we rescaled the NCES teacher cost index to create district-level

indexes for each state that reflect the education resource cost differences

in just one state rather than the differences nationwide. To rescale the

teacher cost index, we determined the average teacher cost index for the

state, then divided each district’s teacher cost index by the state average

to obtain the district-level teacher cost index adjusted for within-state

differences. A teacher cost index equal to 1.0 indicates a district with

average resource costs for the state. Table II.1 provides the average cost

index for each of the five income groups of districts in a state. In all states

except four (Alaska, Nevada, New York, and North Carolina), the range in

the average cost indexes across groups in the table was less than twice the

standard deviation of the district-level cost index. This suggests that states

59See Jay Chambers and William Fowler, Jr., Public School Teacher Cost Differences Across the United

States, Department of Education, NCES, Analysis/Methodology Report, No. 95-758 (Washington, D.C.:

Oct. 1995).

60McMahon and Chang have developed an estimating equation to predict cost of living in areas for

which the actual indexes are not available. See W. McMahon and S. Chang, “Geographical

Cost-of-Living Differences: Interstate and Intrastate, Update,” Center for the Study of Educational

Finance, MacArthur/Spencer Special Series (Normal, Ill.: 1991).

61Because of missing cost index data, we had to impute cost index data for 310 districts, including 18 in

Alaska and 72 in New York (mainly Suffolk County).

62This estimate was developed for NCES by Stephen M. Barro. See Cost of Education Differentials

Across the States, Department of Education, NCES, Working Paper No. 94-05 (Washington D.C.:

July 1994). In using this estimate, we assumed that all personnel costs, including noncertified

personnel costs, have patterns of cost variation similar to certified personnel.

Page 37 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix II 

Adjusting for Geographic and Student

Need-Related Differences in Education

Costs

may have had more variation in cost differences among individual districts

than across the income groups shown in the table.

Adjusting for

Differences in Student

Need

To account for the differences in student need by district, we made

adjustments that weighted poor students and disabled students according

to their need for additional services.63 Our analysis did not account for

limited English proficient students, generally recognized as a third group

of high-cost students, because we could not obtain accurate district-level

data on the number of such students.

To account for differences in student needs by district, students with

disabilities were given 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.64 We also assigned a

weight of 1.2 for children from poor families. This additional .2 weighting

for poor students stems from an estimate based on the average title I

allocation per student divided by average funding per student. We used a

set of weights developed for an NCES report.65

Using these weights, we developed a district-level need index adjusted for

differences within the state. We used the following equation to calculate

the need index for each district:

Equation II.1

where

63However, when we estimated the targeting effort and implicit foundation levels of states, we adjusted

for student-need factors by controlling for such factors in our regression analysis.

64This cost estimate is based on analysis of data from a nationally representative sample. For more

information, see M.T. Moore and others, Patterns in Special Education Service Delivery and Cost,

Decision Resources Corp. (Washington, D.C.: 1988). More recent studies have resulted in a similar

figure.

65Thomas Parrish, Christine Matsumoto, and William Fowler, Jr., Disparities in Public School District

Spending: 1989-90, Department of Education, NCES, Report No. 95-300 (Washington D.C.: Feb. 1995).

We also used these weights in GAO/HEHS-96-142, Aug. 30, 1996.

Page 38 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix II 

Adjusting for Geographic and Student

Need-Related Differences in Education

Costs

AdjMem = adjusted membership; a district’s fall membership + (1.3 x

students with Individual Education Plans) + (.2 x students below the

poverty line)

AdjStMem = adjusted membership in a state; the sum of AdjMem for all

districts in a state

Member = membership; a district’s fall membership

StMem = state membership; the sum of Member for all districts in a state.

Table II.2 provides the average need index for each of the five income

groups of districts in a state. In all states except three (Alaska, Maryland,

and New Mexico), the range in the average need indexes across groups in

the table was less than twice the standard deviation of the district-level

need index. This suggests that states may have had more variation in need

differences among individual districts than across the income groups

shown in the table.

Table II.1: Cost Index to Adjust for

Within-State Differences

Poorest Wealthiest

State average = 1.00

State Group 1 Group 2 Group 3 Group 4 Group 5

Alabama .96 .99 1.00 1.04 1.01

Alaska 1.07 1.02 .99 .97 .91

Arizona .99 1.01 1.01 .96 1.04

Arkansas .96 .98 .98 1.03 1.04

California .97 .98 1.05 1.00 1.00

Colorado .94 .98 1.02 1.02 1.03

Connecticut 1.00 1.00 .99 1.00 1.00

Delaware .96 .96 1.01 1.03 1.03

Florida .94 1.05 1.00 1.00 1.00

Georgia .93 .97 1.00 1.04 1.06

Idaho 1.00 .98 1.01 .99 1.01

Illinois .90 1.11 .92 .99 1.05

Indiana .99 .99 .98 1.02 1.02

Iowa .96 .98 1.00 1.00 1.05

Kansas 1.01 .97 .98 .98 1.06

Kentucky .96 .97 .99 1.02 1.05

Louisiana .98 .99 1.00 1.01 1.03

Maine .99 1.00 .99 .99 1.02

(continued)

Page 39 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix II 

Adjusting for Geographic and Student

Need-Related Differences in Education

Costs

Poorest Wealthiest

State average = 1.00

State Group 1 Group 2 Group 3 Group 4 Group 5

Maryland 1.03 .96 .99 .99 1.04

Massachusetts 1.00 1.00 .99 1.01 1.00

Michigan .99 .95 .99 1.01 1.05

Minnesota .92 .98 .98 1.03 1.08

Mississippi .98 .98 .99 1.01 1.04

Missouri .94 .95 1.01 1.02 1.09

Montana 1.02 .99 1.01 .99 .99

Nebraska .97 .98 1.00 1.05 1.00

Nevada 1.04 1.01 .95 .95 a

New Hampshire .98 .99 1.03 1.01 .98

New Jersey 1.01 .99 1.00 1.01 .99

New Mexico 1.00 .98 .98 1.02 1.02

New York .89 .91 1.13 .92 .98

North Carolina .95 .99 1.00 1.02 1.04

North Dakota .98 1.00 1.01 .99 1.03

Ohio .95 1.00 1.00 1.01 1.04

Oklahoma .98 .98 1.02 .99 1.03

Oregon .96 .99 .99 1.03 1.03

Pennsylvania .94 .97 1.04 1.00 1.04

Rhode Island 1.03 .99 1.00 1.00 .98

South Carolina .95 .98 1.01 1.03 1.03

South Dakota .98 .97 1.02 .97 1.04

Tennessee .97 .98 1.01 1.01 1.02

Texas .98 .97 .98 1.03 1.03

Utah .98 .96 1.00 1.02 1.02

Vermont 1.01 .99 .99 1.00 1.01

Virginia .94 .96 1.03 .98 1.09

Washington .94 1.00 .99 1.01 1.07

West Virginia .98 .99 1.00 1.02 1.01

Wisconsin .94 1.02 .99 1.01 1.04

Wyoming .99 1.01 1.00 .98 1.01

aNevada was divided into only four groups because of the distribution of the student population.

The wealthiest group is group 4.

Page 40 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix II 

Adjusting for Geographic and Student

Need-Related Differences in Education

Costs

Table II.2: Need Index to Adjust for

Within-State Differences

Poorest Wealthiest

State average = 1.00

State Group 1 Group 2 Group 3 Group 4 Group 5

Alabama 1.01 1.00 1.01 .99 .99

Alaska 1.04 1.00 .98 .99 .99

Arizona 1.04 1.00 .99 1.00 .98

Arkansas 1.03 1.00 1.00 .98 .99

California 1.01 1.00 1.01 1.00 .99

Colorado 1.01 1.02 .99 .97 1.01

Connecticut 1.04 1.00 .99 .99 .98

Delaware 1.01 1.01 1.00 .99 .98

Florida 1.01 1.00 1.00 .99 1.01

Georgia 1.02 1.02 .99 .99 .98

Idaho .99 1.01 1.00 1.00 1.00

Illinois 1.02 1.00 1.00 1.00 .98

Indiana 1.01 .99 1.00 1.01 .99

Iowa .99 .99 1.01 1.00 1.01

Kansas 1.01 .99 1.00 1.01 .99

Kentucky 1.03 1.00 .99 .98 .99

Louisiana 1.01 1.01 .99 .99 1.00

Maine 1.01 .99 1.00 1.00 1.00

Maryland 1.06 .99 .98 1.00 .97

Massachusetts 1.00 1.00 .99 1.02 .99

Michigan 1.03 1.00 .99 1.00 .98

Minnesota 1.00 .99 1.00 1.01 1.01

Mississippi 1.00 1.02 1.00 .99 .99

Missouri 1.02 1.02 .99 1.01 .96

Montana 1.02 .99 1.02 .99 .98

Nebraska .99 1.00 .99 1.01 1.01

Nevada 1.02 .99 1.02 1.01 a

New Hampshire .99 1.00 1.00 1.00 1.01

New Jersey 1.02 1.01 1.00 .99 .99

New Mexico 1.01 .99 1.00 1.01 .96

New York .99 .99 1.03 .98 .97

North Carolina 1.01 1.00 1.01 1.00 .99

North Dakota 1.01 1.01 1.01 .99 .98

Ohio 1.01 1.01 1.01 .99 .98

Oklahoma 1.02 .99 .98 .98 1.02

Oregon 1.01 1.01 1.00 .98 1.00

(continued)

Page 41 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix II 

Adjusting for Geographic and Student

Need-Related Differences in Education

Costs

Poorest Wealthiest

State average = 1.00

State Group 1 Group 2 Group 3 Group 4 Group 5

Pennsylvania 1.01 1.00 1.01 1.00 .98

Rhode Island 1.01 .98 1.00 1.01 .99

South Carolina 1.01 1.01 .98 1.00 1.00

South Dakota 1.03 .99 .98 .99 1.01

Tennessee 1.02 1.01 .99 1.00 .98

Texas 1.02 1.00 1.00 .99 .98

Utah 1.01 1.00 .98 .99 1.02

Vermont 1.01 1.00 1.00 1.00 .99

Virginia 1.00 .99 .99 1.01 1.00

Washington 1.02 1.00 1.01 .99 .98

West Virginia 1.03 1.01 .99 .98 .99

Wisconsin 1.00 1.03 .99 1.00 .98

Wyoming .99 .99 1.01 1.01 .99

aNevada was divided into only four groups because of the distribution of the student population.

The wealthiest group is group 4.

Page 42 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix III 

Analysis of Fiscal Neutrality

In our study, the goal of fiscal neutrality is achieved in a state when total

(state and local) funding per weighted pupil does not depend on

differences in districts’ income per weighted pupil. We measured the

extent of this dependency using the income elasticity of total funding per

weighted pupil and defined this elasticity as a state’s fiscal neutrality

score. A positive fiscal neutrality score would indicate that per pupil

funding rises with income; a fiscal neutrality score of 0 would indicate that

fiscal neutrality has been achieved (that is, no relationship exists between

per pupil funding and per pupil income); and a negative score would

indicate higher funding in low-income districts.

The first section of this appendix presents the method we used to estimate

each state’s fiscal neutrality score and the results of our analysis. The

second section shows how the variation in fiscal neutrality scores among

states is explained by differences in state equalization policies (state share

and state targeting) and by differences in the relative local tax effort of

wealthy and poor districts.

Calculating Fiscal

Neutrality Scores

We used a linear regression model to estimate the elasticity of total

funding in a district relative to district income. Both the dependent and

independent variables were adjusted for differences in geographic cost

and student need within the state and expressed as a percent of their

respective state averages.66 By expressing each variable as a percent of its

state average value, both the dependent and independent variables can be

interpreted as index numbers. A value below 1.00 signifies that a district

was below the state average for that variable; a value above 1.00 signifies

that a district was above the state average. With these adjustments the

regression model took the following form:

Equation III.1

Because both variables are measured relative to their respective state

averages, the regression coefficient (β1) represents the percent difference,

from the state average, in total funding relative to a percent difference,

66See app. II for more detailed information on the cost and student need adjustments.

Page 43 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix III 

Analysis of Fiscal Neutrality

from the state average, in district income. This is precisely the elasticity

we wanted to estimate and use as our fiscal neutrality score.67 A positive

coefficient implies that total funding per weighted pupil is higher in

wealthy districts, and a negative coefficient, the opposite. A coefficient

that is not statistically different from 0 implies that fiscal neutrality has

been achieved because no systematic differences exist in per pupil funding

between wealthy and poor districts.

We used a district’s total funding per weighted pupil as the dependent

variable. This variable included state and local funding for all purposes,

including maintenance and operations, transportation, and capital

expenditures and debt service.68 We divided the district’s total funding by

its fall membership to put the variable in per pupil form.

We used district income per weighted pupil as the independent variable,

our measure of a district’s ability to raise revenue for education. Because

we could not develop income per pupil data from the Common Core of

Data (CCD), we used district-level per capita income from the 1990 census

to construct the variable. We multiplied per capita income in a district by

district population, resulting in the total income in the district. We then

divided this amount by the total number of students in the district,

resulting in income per pupil.

Most school finance studies measure a district’s ability to raise revenue for

education as district wealth defined as property value per pupil. However,

we chose to use district income defined as resident income per pupil

because we could not construct a property-value-per-pupil measure at the

district level from the national databases that were available. Furthermore,

beyond the field of school finance, income—as opposed to wealth—is the

most commonly accepted measure of the ability to raise revenue.

A good income measure of a district’s ability to raise revenue for

education should be as comprehensive as possible. For example, the

Department of Treasury defines and compiles the total taxable resources

(TTR) for each state. TTR takes into account all income either received by

state residents or produced in a state. Either income measure, by itself, is

67An elasticity is, by definition, the percent change in a dependent variable associated with a 1-percent

change in an independent variable. In our model a unit change in the income index from the state

average is a percent change from the state average and the coefficient measures the associated

percentage change in per pupil funding. Because we have measured each variable as a percent of its

respective state averages, our elasticity measure is an elasticity evaluated at the state averages.

68Because the CCD does not report separate data on local funding at the district level devoted to

capital expenditures and debt service, we could not exclude these funding categories from our revenue

variable.

Page 44 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix III 

Analysis of Fiscal Neutrality

incomplete. Income received by state residents does not include business

income earned by nonresidents (undistributed corporate profits, for

example). Alternatively, income produced does not include income earned

by residents from out-of-state sources (residents who work out of state,

for example). Consequently, TTR includes both income received and

income produced to gauge a state’s total taxable resources. Unfortunately,

a comprehensive income measure such as the TTR is not available at the

school district level.

Our income measure is money income reported in the 1990 census. Its

major weakness is that it does not include commercial or nonresident

income that local school districts may be able to tax. It may therefore

understate the ability of districts with high concentrations of this type of

income to raise revenues for education. However, our measure does

include the largest income category—resident income—represented in

TTR. Although we would expect some differences in the results of our

analyses if all income from commercial and industrial property had been

included in the income variable, the general trends from our analyses

would still have held true.

Finally, the regression model in equation III.1 was estimated by weighting

each observation for membership size to better reflect the distribution of

state funding to students rather than to districts;69 thus, school districts

with larger enrollments had a greater effect in determining the estimated

coefficients of the model.

Analysis Results In most states, total funding per weighted pupil increased as district

income increased (the elasticity was positive). On average, wealthy

districts had about 24 percent more total funding per weighted pupil than

poor districts.

In 37 states, the income elasticity of total funding per weighted pupil was

positive. This means that as the districts’ income increased, the level of

total funding increased. However, the range in elasticity varied among the

states, with a high of .469 in Maryland and a low of .055 in Washington.

In three states—Alaska, Nevada, and Oklahoma—the elasticity was

negative, that is, total funding decreased as district income increased.

Elasticities for these three states ranged from –.556 in Nevada to –.053 in

69Without weighting, each district would carry the same weight in the analysis, regardless of size.

Weighting by students is a generally accepted practice in school finance analysis.

Page 45 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix III 

Analysis of Fiscal Neutrality

Oklahoma. The elasticity was not statistically different from 0 in the

remaining nine states. Table III.1 shows the elasticities of total funding to

district income and the R square for each state.70

Table III.1: State Elasticities of Total

Funding to District Income (Fiscal

Neutrality Scores) Adjusted for

Statewide Differences in Cost and

Need

State

Elasticity of total

funding to income

Adjusted R

square

Alabama +.290 .308

Alaska –.272 .072

Arizona +.141 .310

Arkansas +.220 .202

California +.073 .125

Colorado +.154 .051

Connecticut +.241 .460

Delawarea +.072 .014

Florida +.239 .432

Georgia +.323 .282

Idaho +.247 .256

Illinois +.338 .736

Indiana +.153 .120

Iowaa +.031 .000

Kansasa +.014 –.003

Kentucky +.126 .301

Louisiana +.216 .245

Maine +.176 .155

Maryland +.469 .702

Massachusetts +.447 .512

Michigan +.290 .416

Minnesota +.113 .080

Mississippia +.007 –.006

Missouri +.362 .170

Montana +.393 .337

Nebraska +.154 .045

Nevada –.556 .227

New Hampshire +.238 .226

New Jersey +.168 .380

New Mexicoa +.004 –.012

New York +.370 .248

(continued)

70The adjusted R square is the proportion in the variation of the dependent variable explained by the

independent variable(s).

Page 46 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix III 

Analysis of Fiscal Neutrality

State

Elasticity of total

funding to income

Adjusted R

square

North Carolina +.250 .307

North Dakota +.236 .055

Ohio +.315 .272

Oklahoma –.053 .009

Oregon +.166 .141

Pennsylvania +.300 .557

Rhode Island +.274 .193

South Carolina +.150 .101

South Dakota +.367 .171

Tennessee +.242 .149

Texasa +.003 –.001

Utaha +.036 –.022

Vermont +.176 .087

Virginia +.377 .608

Washington +.055 .021

West Virginiaa +.071 .037

Wisconsin +.129 .240

Wyominga –.196 .003

aElasticity not statistically different from 0.

In most states, the amount of total funding (state and local funding

combined) per weighted pupil available to wealthy districts exceeded such

funding available to poor districts. However, states varied widely in the

degree to which funding available for wealthy districts exceeded that of

poor districts. Table III.2 summarizes the gaps in total funding per

weighted pupil between wealthy and poor districts.

Tables III.3 and III.4 show the state averages for total funding per weighted

pupil and income per weighted pupil as well as the average index numbers

of these two variables for each of the five income groups of districts in a

state.

Page 47 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix III 

Analysis of Fiscal Neutrality

Table III.2: Total Funding Gaps

Between Poor and Wealthy Districts Total funding per weighted

pupila

State

State

average

For the

poor

group

For the

wealthy

group

Wealthy group funding

compared with poor

group fundingb

Alabama $3,277 $3,213 $3,795 1.18

Alaska 8,030 8,912 8,877 1.00

Arizona 4,507 4,146 5,473 1.32

Arkansas 3,784 3,747 4,282 1.14

California 4,543 4,407 4,965 1.13

Colorado 5,047 5,109 5,501 1.08

Connecticut 8,221 7,426 9,985 1.34

Delaware 5,576 5,316 5,817 1.09

Florida 5,555 5,286 6,264 1.18

Georgia 4,324 3,867 5,029 1.30

Idaho 3,504 3,246 4,075 1.26

Illinois 4,970 4,330 7,249 1.67

Indiana 4,993 4,804 5,299 1.10

Iowa 4,849 5,051 4,855 .96

Kansas 4,973 4,648 5,089 1.09

Kentucky 3,728 3,601 4,143 1.15

Louisiana 3,912 3,507 4,238 1.21

Maine 5,681 5,469 6,399 1.17

Maryland 6,039 4,686 7,728 1.65

Massachusetts 6,264 5,227 8,037 1.54

Michigan 5,851 5,275 7,198 1.36

Minnesota 5,646 5,613 6,212 1.11

Mississippi 2,831 3,034 2,974 .98

Missouri 3,972 2,912 4,937 1.70

Montana 4,835 4,006 6,942 1.73

Nebraska 5,148 5,367 5,614 1.05

Nevada 3,597 4,518 3,117 .69

New Hampshire 5,850 5,592 7,284 1.30

New Jersey 9,239 8,434 11,087 1.31

New Mexico 3,830 3,891 4,094 1.05

New York 7,787 8,309 10,950 1.32

North Carolina 4,424 4,183 4,919 1.18

North Dakota 4,079 4,006 4,709 1.18

Ohio 4,709 4,305 5,688 1.32

Oklahoma 3,623 3,735 3,528 .94

(continued)

Page 48 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix III 

Analysis of Fiscal Neutrality

Total funding per weighted

pupila

State

State

average

For the

poor

group

For the

wealthy

group

Wealthy group funding

compared with poor

group fundingb

Oregon 5,087 4,860 5,910 1.22

Pennsylvania 6,406 5,812 7,674 1.32

Rhode Island 5,939 5,507 6,553 1.19

South Carolina 4,112 3,840 4,151 1.08

South Dakota 3,756 3,297 4,228 1.28

Tennessee 3,329 3,038 3,671 1.21

Texas 4,603 4,689 4,691 1.00

Utah 3,177 3,333 3,301 .99

Vermont 7,722 6,478 8,454 1.31

Virginia 4,713 4,138 5,702 1.38

Washington 5,302 5,252 5,481 1.04

West Virginia 4,927 4,859 5,044 1.04

Wisconsin 5,865 5,974 6,455 1.08

Wyoming 5,920 6,573 5,514 .84

aAll funding figures have been adjusted for statewide differences in cost and need. We assigned

weights of 1.2 to poor students and 2.3 to disabled students.

bWe calculated this ratio by dividing the wealthy districts’ funding by the poor districts’ funding,

for example, $3,795/$3,213 in Alabama.

Table III.3: Total Funding per Weighted

Pupil Index Adjusted for Statewide

Differences in Cost and Need

Poorest Wealthiest

Average total funding per weighted pupil

index

State average = 1.00

State

Average total

funding per

weighted pupila

Group

1

Group

2

Group

3

Group

4

Group

5

Alabama $3,277 .98 .94 .93 1.00 1.16

Alaska 8,030 1.11 1.11 .95 .85 1.11

Arizona 4,507 .92 .91 1.00 .98 1.21

Arkansas 3,784 .99 .95 .95 .98 1.13

California 4,543 .96 .96 .98 1.00 1.09

Colorado 5,047 1.01 .94 .97 1.00 1.08

Connecticut 8,221 .90 .90 .97 1.02 1.21

Delaware 5,576 .95 .93 .99 1.06 1.04

Florida 5,555 .95 .94 .98 1.02 1.13

Georgia 4,324 .90 .91 1.00 1.03 1.17

(continued)

Page 49 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix III 

Analysis of Fiscal Neutrality

Poorest Wealthiest

Average total funding per weighted pupil

index

State average = 1.00

State

Average total

funding per

weighted pupila

Group

1

Group

2

Group

3

Group

4

Group

5

Idaho 3,504 .92 .97 .96 1.00 1.16

Illinois 4,970 .87 .85 .88 .93 1.46

Indiana 4,993 .96 .97 1.00 1.01 1.06

Iowa 4,849 1.03 1.00 .95 1.02 .99

Kansas 4,973 .92 1.05 1.04 .99 1.01

Kentucky 3,728 .97 .98 .97 .98 1.11

Louisiana 3,912 .90 .94 1.02 1.07 1.08

Maine 5,681 .96 .91 .96 1.04 1.12

Maryland 6,039 .77 .98 .97 1.05 1.27

Massachusetts 6,264 .83 .90 .93 1.05 1.28

Michigan 5,851 .91 .92 .96 .99 1.23

Minnesota 5,646 .99 .97 .94 1.00 1.10

Mississippi 2,831 1.07 .93 .93 1.02 1.05

Missouri 3,972 .74 .78 .90 1.34 1.25

Montana 4,835 .81 .86 .83 1.10 1.41

Nebraska 5,148 1.03 1.01 .97 .92 1.07

Nevada 3,597 1.26 .96 1.21 .87 b

New Hampshire 5,850 .95 .96 .88 .96 1.24

New Jersey 9,239 .91 .94 .94 1.01 1.20

New Mexico 3,830 1.01 1.02 .99 .98 1.06

New York 7,787 1.04 1.11 .70 1.14 1.37

North Carolina 4,424 .95 .94 .94 1.05 1.11

North Dakota 4,079 .97 .93 .99 .99 1.14

Ohio 4,709 .92 .93 .97 .98 1.21

Oklahoma 3,623 1.02 1.03 .96 1.02 .97

Oregon 5,087 .95 .92 .96 1.03 1.16

Pennsylvania 6,406 .91 .93 .91 1.05 1.20

Rhode Island 5,939 .92 1.05 .94 1.03 1.10

South Carolina 4,112 .93 1.01 1.00 1.06 1.01

South Dakota 3,756 .87 1.06 .96 1.02 1.11

Tennessee 3,329 .91 .86 1.05 1.07 1.10

Texas 4,603 1.01 1.03 1.00 .94 1.01

Utah 3,177 1.05 1.08 .97 .88 1.04

Vermont 7,722 .83 .93 1.06 1.09 1.09

(continued)

Page 50 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix III 

Analysis of Fiscal Neutrality

Poorest Wealthiest

Average total funding per weighted pupil

index

State average = 1.00

State

Average total

funding per

weighted pupila

Group

1

Group

2

Group

3

Group

4

Group

5

Virginia 4,713 .89 .90 .91 1.11 1.22

Washington 5,302 .99 .98 .99 1.01 1.03

West Virginia 4,927 .99 .98 .98 1.04 1.02

Wisconsin 5,865 1.02 .94 .99 .96 1.10

Wyoming 5,920 1.11 1.04 1.03 .89 .93

aAll funding figures have been adjusted for statewide differences in cost and need. We assigned

weights of 1.2 to poor students and 2.3 to disabled students.

bNevada was divided into only four groups because of the distribution of the student population.

The wealthiest group is group 4.

Table III.4: Income per Weighted Pupil

Index Adjusted for Statewide

Differences in Cost and Need

Poorest Wealthiest

Average income per weighted pupil index

State average = 1.00

State

Average income

per weighted

pupila

Group

1

Group

2

Group

3

Group

4

Group

5

Alabama $63,313 .69 .87 .96 1.06 1.44

Alaska 83,220 .48 .91 1.15 1.24 1.40

Arizona 98,442 .34 .62 .77 1.07 2.35

Arkansas 55,895 .63 .80 .92 1.12 1.54

California 121,872 .40 .63 .78 1.01 2.22

Colorado 81,879 .62 .79 .97 1.21 1.45

Connecticut 148,273 .54 .77 .90 1.06 1.76

Delaware 106,718 .60 .72 .84 1.18 1.71

Florida 98,373 .69 .83 .92 1.12 1.48

Georgia 73,340 .61 .81 .94 1.16 1.52

Idaho 51,724 .59 .80 .97 1.05 1.60

Illinois 134,121 .49 .58 .67 .93 2.37

Indiana 76,049 .68 .87 .98 1.06 1.42

Iowa 69,690 .75 .88 .95 1.08 1.34

Kansas 74,725 .68 .82 .93 1.08 1.48

Kentucky 63,691 .56 .78 .96 1.18 1.55

Louisiana 58,920 .67 .77 .96 1.15 1.54

Maine 76,336 .64 .76 .89 1.14 1.57

(continued)

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Appendix III 

Analysis of Fiscal Neutrality

Poorest Wealthiest

Average income per weighted pupil index

State average = 1.00

State

Average income

per weighted

pupila

Group

1

Group

2

Group

3

Group

4

Group

5

Maryland 114,832 .63 .79 .98 1.17 1.55

Massachusetts 133,452 .60 .78 .95 1.09 1.60

Michigan 80,367 .62 .75 .91 1.09 1.70

Minnesota 81,234 .62 .78 .89 1.10 1.62

Mississippi 51,017 .59 .75 .87 1.05 1.79

Missouri 79,570 .60 .76 .96 1.13 1.64

Montana 115,518 .42 .65 .78 1.09 2.12

Nebraska 94,845 .69 .83 .96 1.12 1.42

Nevada 86,827 .65 1.00 1.06 1.25 b

New Hampshire 106,978 .63 .79 .90 1.07 1.60

New Jersey 160,761 .39 .63 .86 1.11 2.06

New Mexico 54,999 .47 .81 .92 1.32 1.97

New York 114,397 .63 .85 .94 1.05 1.62

North Carolina 76,415 .67 .84 .92 1.14 1.42

North Dakota 58,094 .68 .88 .98 1.12 1.41

Ohio 80,781 .64 .79 .91 1.11 1.57

Oklahoma 64,014 .62 .81 .92 1.18 1.48

Oregon 85,350 .64 .78 .92 1.13 1.57

Pennsylvania 99,378 .63 .82 .91 1.08 1.58

Rhode Island 108,151 .73 .90 1.01 1.09 1.35

South Carolina 65,707 .67 .85 1.02 1.13 1.32

South Dakota 57,440 .64 .88 1.02 1.12 1.36

Tennessee 70,681 .64 .82 .93 1.14 1.46

Texas 62,842 .47 .81 1.01 1.18 1.55

Utah 41,385 .69 .87 .98 1.06 1.36

Vermont 112,652 .50 .74 .91 1.18 1.68

Virginia 93,199 .67 .81 .87 1.08 1.60

Washington 82,373 .61 .78 .89 1.07 1.70

West Virginia 58,725 .65 .82 .99 1.15 1.39

Wisconsin 82,555 .68 .81 .93 1.04 1.57

Wyoming 55,152 .69 .89 1.00 1.11 1.31

aAll income figures have been adjusted for statewide differences in cost and need. We assigned

weights of 1.2 to poor students and 2.3 to disabled students.

bNevada was divided into only four groups because of the distribution of the student population.

The wealthiest group is group 4.

Page 52 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix III 

Analysis of Fiscal Neutrality

Relationship Between

Funding Gaps and

State Share, State

Targeting, and

Relative Local Tax

Effort

We identified state share, state targeting, and relative local tax effort as the

three key factors affecting the size of school funding gaps between poor

and wealthy districts using the following rationale. First, we set aside the

effects of state share and state targeting by assuming that states do not

fund schools and that funding per pupil depends entirely on the revenue

from local tax bases. Under this assumption, the funding gap occurs

because wealthy districts can generate more local funding than poor

districts when the tax effort for all districts is equal. However, the gap in

funding between wealthy and poor districts would grow smaller as poor

districts increase their local tax effort relative to wealthy districts.

Therefore, in the absence of any state funding for education, the funding

gap between poor and wealthy districts would be completely determined

by the relative local tax effort of poor and wealthy districts.

A state can help offset the funding gap by providing a portion of the total

funding and targeting more state funds to poor districts. Consequently, the

size of the funding gap between wealthy and poor districts should depend

on both state equalization policies (state share and state targeting) and the

relative local tax effort of poor districts and wealthy districts.

To measure a state’s relative local tax effort, we estimated the income

elasticity of local tax effort. For each state, this elasticity measures the

percent change in local tax effort associated with a 1-percent increase in

district income per weighted pupil. As measured this way, the greater the

elasticity, the greater the tax effort in wealthy districts as compared with

poor districts. This elasticity is represented by the regression coefficient

(β1) in the following equation:

Equation III.2

where

local tax effort index = the ratio of a district’s local funding to its income

expressed as a percent of the average tax effort of all districts, represented

by the dependent variable above

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Appendix III 

Analysis of Fiscal Neutrality

elasticity of local tax effort = a state’s elasticity of local tax effort to

income per weighted pupil, represented by β1 in equation III.2

∈ = an error term that reflects the variation in the local tax effort that

cannot be accounted for by the other variables in the model.

To estimate the extent to which the three factors—elasticity of local tax

effort, state share, and state targeting (see table III.6)—accounted for the

variation in the funding gap between wealthy and poor districts, we

constructed a regression model that used these three factors to explain

cross-state differences in fiscal neutrality scores:

Equation III.3

where

fiscal neutrality score = a state’s elasticity of total funding per weighted

pupil relative to income per weighted pupil

state funding percentage = state funding as a percentage of total (state and

local) funding

state targeting effort = a state’s elasticity of state funding per weighted

pupil relative to income per weighted pupil

elasticity of local tax effort = a state’s elasticity of local tax effort relative

to income per weighted pupil

∈ = an error term that reflects the variation in funding gaps that cannot be

accounted for by the other variables in the model.

The results of this analysis showed that the three factors accounted for

about 61 percent of the variation in the income-related funding gaps.71

Although increases in both state targeting and state share led to decreases

71The adjusted R square for the analysis was .6054.

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Appendix III 

Analysis of Fiscal Neutrality

in states’ fiscal neutrality scores, state share had a relatively greater

impact on reducing income-related funding gaps than did states’ targeting

efforts. Increases in the elasticity of local tax effort were associated with

increases in the funding gap, meaning that as the wealthy districts’ tax

effort increased relative to the poor districts’ tax effort, the income-related

funding gap also increased. The elasticity of local tax effort factor of the

three factors in this equation accounted for most of the variation in the

fiscal neutrality scores (see table III.5). Table III.6 shows the state data

used in the regression analysis.

Table III.5: Regression Results (N=49) 

Factor

Regression

coefficient

Beta

coefficient t statistic

State targeting –.2265 –.3280 –3.278

State share –.4854 –.4064 –4.065

Elasticity of local tax effort .5583 .6578 6.849

Table III.6: State Results for Factors

Affecting Fiscal Neutrality

State

Fiscal

neutrality

score

State

targeting

efforta

State share of

total funding

(percent)

Elasticity of

local tax effortb

Alabama +.290 +.020 69.8 .027

Alaska –.272 +.068 76.4 –.808

Arizona +.141 –.232 46.8 –.468

Arkansas +.220 –.328 65.4 –.243

California +.073 –.119 68.9 –1.028

Colorado +.154 –.753 43.5 –.381

Connecticut +.241 –.430 38.8 –.066

Delaware +.072 –.070 70.2 –.235

Florida +.239 –.615 53.0 .234

Georgia +.323 –.242 54.6 .007

Idaho +.247 –.130 67.1 .011

Illinois +.338 –.230 33.2 –.179

Indiana +.153 –.099 54.1 –.511

Iowa +.031 –.104 49.0 –.772

Kansas +.014 –.241 43.8 –.448

Kentucky +.126 –.239 70.0 .274

Louisiana +.216 +.150 62.2 –.237

Maine +.176 –.287 49.4 –.172

Maryland +.469 –.566 40.4 .164

Massachusetts +.447 –.316 30.8 .077

Michigan +.290 –.475 32.9 –.031

(continued)

Page 55 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix III 

Analysis of Fiscal Neutrality

State

Fiscal

neutrality

score

State

targeting

efforta

State share of

total funding

(percent)

Elasticity of

local tax effortb

Minnesota +.113 –.499 53.5 –.104

Mississippi +.007 –.020 64.4 –.267

Missouri +.362 –.017 44.6 –.018

Montana +.393 –.126 44.2 –.469

Nebraska +.154 –.246 34.3 –.430

Nevada –.556 –1.007 56.9 –1.252

New Hampshire +.238 –.571 8.3 –.370

New Jersey +.168 –.104 43.1 –.203

New Mexico +.004 +.024 85.0 –1.776

New York +.370 –.578 42.6 .076

North Carolina +.250 –.016 67.7 .052

North Dakota +.236 +.173 48.0 –.451

Ohio +.315 –.180 41.9 –.276

Oklahoma –.053 –.102 71.1 –.473

Oregon +.166 –.043 31.1 –.393

Pennsylvania +.300 –.255 43.0 –.023

Rhode Island +.274 –.694 39.3 .045

South Carolina +.150 –.505 52.4 –.194

South Dakota +.367 +.116 29.5 –.164

Tennessee +.242 +.017 47.0 –.709

Texas +.003 –.522 47.4 –.234

Utah +.036 –.172 60.2 –.734

Vermont +.176 –.539 29.0 –.333

Virginia +.377 –.499 36.0 .096

Washington +.055 –.009 75.2 –.277

West Virginia +.071 –.127 72.5 –.230

Wisconsin +.129 –.270 46.2 –.160

Wyoming –.196 +.296 52.5 –1.645

aThis is the elasticity of state funding to district income. App. V describes how we calculated this

elasticity.

bThis is the income elasticity of local tax effort.

Another way to illustrate that state equalization policies (state share and

state targeting) reduced but did not eliminate the funding gap between

wealthy and poor districts is shown in table III.7. In most cases, the

addition of state funding to local funding caused total funding to be less

Page 56 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix III 

Analysis of Fiscal Neutrality

sensitive to district income than local funding. This is illustrated by the

fact that states’ income elasticities of total funding are usually less than

those of local funding. The elasticity of local tax effort accounted for most

of the variation in the fiscal neutrality scores. We compared the local tax

efforts of poor and wealthy districts in table III.8. In 35 states, poor

districts made a higher tax effort than wealthy districts.

Table III.7: Income Elasticities

Adjusted for Statewide Differences in

Cost and Need

Income elasticity of

State

Local

fundinga

State

fundingb

Total

fundingc

Alabama +1.301 +.020 +.290

Alaska –.420 +.068 –.272

Arizona +.486 –.232 +.141

Arkansas +1.503 –.328 +.220

California +.684 –.119 +.073

Colorado +.985 –.753 +.154

Connecticut +.889 –.430 +.241

Delaware +.429 –.070 +.072

Florida +1.239 –.615 +.239

Georgia +1.235 –.242 +.323

Idaho +1.240 –.130 +.247

Illinois +.687 –.230 +.338

Indiana +.533 –.099 +.153

Iowa +.408 –.104 +.031

Kansas +.344 –.241 +.014

Kentucky +1.473 –.239 +.126

Louisiana +.473 +.150 +.216

Maine +1.072 –.287 +.176

Maryland +1.271 –.566 +.469

Massachusetts +1.190 –.316 +.447

Michigan +1.171 –.475 +.290

Minnesota +1.105 –.499 +.113

Mississippi –.125 –.020 +.007

Missouri +.510 –.017 +.362

Montana +.549 –.126 +.393

Nebraska +.364 –.246 +.154

Nevada +.025 –1.007 –.556

New Hampshire +.319 –.571 +.238

New Jersey +.692 –.104 +.168

(continued)

Page 57 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix III 

Analysis of Fiscal Neutrality

Income elasticity of

State

Local

fundinga

State

fundingb

Total

fundingc

New Mexico –.265 +.024 +.004

New York +1.152 –.578 +.370

North Carolina +1.096 –.016 +.250

North Dakota +.626 +.173 +.236

Ohio +.670 –.180 +.315

Oklahoma +.585 –.102 –.053

Oregon +.710 –.043 +.166

Pennsylvania +1.080 –.255 +.300

Rhode Island +1.104 –.694 +.274

South Carolina +.620 –.505 +.150

South Dakota +.793 +.116 +.367

Tennessee +.208 +.017 +.242

Texas +.934 –.522 +.003

Utah +.797 –.172 +.036

Vermont +.376 –.539 +.176

Virginia +1.247 –.499 +.377

Washington +.488 –.009 +.055

West Virginia +.738 –.127 +.071

Wisconsin +1.083 –.270 +.129

Wyoming –1.836 +.296 –.196

aWe calculated the elasticity of local funding to district income the same way we calculated the

total funding elasticity.

bApp. V describes how we calculated the elasticity of state funding to district income.

cThis is the fiscal neutrality score.

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Appendix III 

Analysis of Fiscal Neutrality

Table III.8: Local Tax Effort Disparities

Between Poor and Wealthy Districts Tax efforta

State

State

average

For the

poor

group

For the

wealthy

group

Poor group tax

effort compared

with wealthy

group tax effortb

Alabama $15.52 $17.41 $16.76 1.04

Alaska 22.99 30.25 19.47 1.55

Arizona 24.35 47.63 18.56 2.57

Arkansas 23.40 26.81 25.04 1.07

California 11.79 18.65 9.35 1.99

Colorado 34.97 47.93 33.29 1.44

Connecticut 34.29 29.69 33.59 0.88

Delaware 15.44 12.92 12.21 1.06

Florida 26.48 22.60 29.37 0.77

Georgia 26.23 23.12 28.83 0.80

Idaho 22.34 24.35 24.86 0.98

Illinois 24.39 29.09 20.38 1.43

Indiana 30.13 37.13 26.22 1.42

Iowa 35.87 51.39 27.22 1.89

Kansas 37.62 40.78 32.90 1.24

Kentucky 17.42 14.04 20.80 0.68

Louisiana 25.11 23.86 19.12 1.25

Maine 37.61 46.46 38.04 1.22

Maryland 31.59 23.79 36.41 0.65

Massachusetts 32.62 25.58 32.36 0.79

Michigan 48.78 40.01 49.38 0.81

Minnesota 31.75 36.66 32.08 1.14

Mississippi 19.78 39.02 13.74 2.84

Missouri 27.41 22.71 27.10 0.84

Montana 23.94 42.44 18.64 2.28

Nebraska 36.38 51.44 30.73 1.67

Nevada 17.84 28.42 13.73 2.07

New Hampshire 50.35 70.96 40.24 1.76

New Jersey 32.93 34.85 24.58 1.42

New Mexico 10.51 27.48 9.67 2.84

New York 39.87 42.35 49.75 0.85

North Carolina 18.58 18.77 19.54 0.96

North Dakota 37.11 47.60 35.24 1.35

Ohio 33.75 37.27 33.55 1.11

Oklahoma 16.45 19.55 13.67 1.43

(continued)

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Appendix III 

Analysis of Fiscal Neutrality

Tax efforta

State

State

average

For the

poor

group

For the

wealthy

group

Poor group tax

effort compared

with wealthy

group tax effortb

Oregon 41.09 53.06 32.74 1.62

Pennsylvania 36.63 36.67 38.27 0.96

Rhode Island 33.60 31.54 32.86 0.96

South Carolina 29.70 30.40 26.48 1.15

South Dakota 46.52 50.90 41.36 1.23

Tennessee 24.82 29.77 22.13 1.35

Texas 38.73 44.82 37.74 1.19

Utah 30.43 45.72 26.86 1.70

Vermont 48.97 66.35 39.30 1.69

Virginia 31.55 28.65 32.15 0.89

Washington 15.84 17.72 13.44 1.32

West Virginia 23.03 25.84 22.05 1.17

Wisconsin 38.31 47.27 37.63 1.26

Wyoming 51.22 90.83 21.79 4.17

aLocal tax effort is the local funding per weighted pupil raised for $1,000 of income per weighted

pupil.

bWe calculated this ratio by dividing the poor districts’ tax effort by the wealthy districts’ tax effort,

for example, $17.41/$16.76 in Alabama.

Page 60 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IV 

Estimating States’ Targeting Efforts, Implicit

Foundation Levels, and Equalization Efforts

In this study, we developed a new equity measure to assess a state’s

equalization policies (state share and state targeting) that excludes the

effects of the local tax effort. To accomplish this, we viewed each state as

if it were distributing state funds according to a foundation program in

which the state ensures a foundation or minimum amount of funding per

pupil for a minimum local tax effort.72 Using a foundation formula and

assuming all districts made an equal minimum tax effort, we determined

each state’s implicit foundation level given the state’s equalization policies

in school year 1991-92. This implicit foundation level is an estimate of the

minimum amount of total funds (including both state and local funds) that

districts could spend per student given the state’s equalization policies and

provided all districts made an equal tax effort. The implicit foundation

level identifies a funding level per pupil at which an equal local tax effort

would produce equal funding per pupil among all districts in a state. This

appendix describes how foundation formulas work and how we calculated

three important summary measures for each state: targeting effort, implicit

foundation level,73 and equalization effort.

Equalizing School

Funding With a

Foundation Program

As mentioned, to calculate these three summary measures, we assumed

states behaved as if they used a foundation formula to distribute state

funds to districts.74 As will be shown in this appendix, foundation

equalization policy can result in states targeting more funds to districts

with lower tax bases. Because nearly all states do target more funds to

districts with low tax bases, it is reasonable to evaluate school finance

policies as if they followed an implicit foundation equalization policy.75 To

72We used a foundation equalization equation to model state school finance systems because it

accounts for most states’ equalization practices. For example, in school year 1990-91, the year

preceding the school year of the Common Core of Data (CCD) we used, the American Education

Finance Association reported that 38 of the 49 states in our study used a foundation program to

distribute at least part of their school funding. In addition, foundation equations can also explain the

funding distribution of the two states that provided flat grants to their pupils and the one state that

provided full funding. Finally, foundation programs share at least one important feature with the

district power equalization programs of the remaining eight states. Under district power equalization

programs, states guarantee districts the same dollar yield for the same tax effort. Although district

power equalization programs do not guarantee the same amount per pupil to each district as

foundation programs, both programs effectively target additional state funds to districts with low

(property) tax bases.

73In principle, the implicit foundation level could be adjusted for geographic or student need-related

differences in cost. We explain how such adjustments were made in app. V.

74A foundation program sets an expenditure per pupil—the minimum foundation—and usually requires

a minimum local tax effort as a condition of receiving state aid. State aid makes up for the difference

between what localities can raise with the required local tax effort and the foundation amount.

75States that do not target more funds to low tax base districts generally provide flat per pupil grants.

Even this policy can be interpreted as a special foundation equalization policy: all districts can finance

the foundation funding level with an equal tax effort of 0.

Page 61 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IV 

Estimating States’ Targeting Efforts, Implicit

Foundation Levels, and Equalization Efforts

model the state targeting needed to enable districts to spend the implicit

foundation amount on each student with a minimum tax effort, we used a

derivation of the following foundation formula:76

Equation IV.1

where

gi

 = state funding per pupil in a school district

e* = the implicit foundation level (including both state and local funds)

that results when all districts make an equal minimum tax effort given the

state’s equalization policies

t* = the minimum tax effort, a ratio of district’s local revenue to district’s

tax base value

vi

 = the tax base per pupil in a school district. In our study, we used

income per pupil.

One implication from the above equation is that if a state chose not to

target additional funding to poor districts and instead provided the same

funding per pupil to all students with no minimum required local tax effort

(t*

= 0), then the implicit foundation level for the state (e*) would equal the

average state funding per pupil. That is, each district’s state funding per

pupil (gi

) would equal the average state funding per pupil (g).77

Another implication of the equation is that if states require a minimum tax

effort (t*) greater than 0, states will have to target more funding to poor

districts than to wealthy districts to achieve the same implicit foundation

level (e*) for all districts. The implicit foundation level in this instance

would be greater than the average state funding per pupil (g) where,

without a required local tax effort, no extra state funding is targeted to

poor districts. From our analysis of school year 1991-92 school finance

76For the notation used in equations in this appendix, we used subscripts to represent district-level

data and superscripts to represent state-level data.

77This situation occurs with flat grant programs. Thus, states with flat grant policies can be interpreted

as providing foundation programs as well.

Page 62 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IV 

Estimating States’ Targeting Efforts, Implicit

Foundation Levels, and Equalization Efforts

data, we know that states do, in fact, vary in the extent to which they

target additional funding to poor districts. Consequently, our purpose was

to estimate the implicit foundation level that was possible in each state

given the degree to which a state targets more funds to poor districts.

We have divided the explanation into two parts. First, we explain how

state funding would have to be targeted to ensure that all students

received the state’s average total funding per pupil, provided that all local

districts made an average tax effort. Second, we modify our explanation to

allow for state targeting that results in an implicit foundation level that is

below the state average with districts making a minimum local tax effort.78

 On the basis of equations developed in this second part, we then describe

how we estimated state targeting efforts, implicit foundation levels, and

equalization efforts.

State Targeting

Necessary to Achieve

the Maximum

Foundation Level

Given the total amount of funding for education in a state, the maximum

foundation level possible in a state is the state’s average total funding per

pupil.79 This means that, in principle, if all districts were to make the

average tax effort to finance their local school programs, the state could

target its funds to ensure that all districts could fund the average total

funding per pupil. To demonstrate this, we began with an equation in

which the implicit foundation level equals the state’s average total funding

per pupil, and then we modified this equation to show how state funds

would have to be distributed.

Equation IV.2

where

78In this instance, the implicit foundation level (e*), which includes both local and state funds, would

be below the average total funding per pupil (e) but would exceed the average state funding per pupil

(g). If a state does not target additional funding to poor districts, then the implicit foundation level (e*)

is the average state funding per pupil (g).

79The highest implicit foundation level is the state’s average total funding per pupil provided that

districts all use the average tax effort. However, if states target more funding to poor districts than is

necessary to finance the average total funding level with average local tax rates, the effect is to allow

poor districts to finance the state average funding level with a tax effort that is less than the state

average, while wealthy districts finance the state average funding level with an above average effort.

Nevada is the one state in our study that fell in this category.

Page 63 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IV 

Estimating States’ Targeting Efforts, Implicit

Foundation Levels, and Equalization Efforts

gi = state funding per pupil in a school district

e = the state’s average total funding per pupil, which is also the implicit

foundation level in the state

t = the average tax effort of local school districts

vi

 = the tax base per pupil in a school district.

The local share of total funding per pupil, by definition, is local funding

expressed as a percent of total funding. This is expressed by the following

equation:

Equation IV.3

where

α = the local share of the total funding for education in the state

v = the average tax base per pupil in the state.

Rearranging terms in equation IV.3, we found that the equation for average

tax effort of local districts is t=(αe/v). Substituting this equation for t in

equation IV.2 and rearranging terms results in the following equation:

Equation IV.4

Equation IV.4 represents how state funding would have to be distributed if

all school districts were to finance the state average funding level,

provided that districts made an average tax effort to finance their local

schools.

Page 64 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IV 

Estimating States’ Targeting Efforts, Implicit

Foundation Levels, and Equalization Efforts

We chose to measure state targeting by the income elasticity of state

funding, where district income represents the tax base per pupil. The

income elasticity is the percent difference in state funding that results

from a 1-percent difference in district income. We can use the relationship

in equation IV.4 to measure this elasticity by dividing both sides of the

equation by the average state funding, that is, g=e(1-(αv/v))=(1-α)e. This

yields the following equation:

Equation IV.5

where

g = the average state funding per pupil, (1-α)e.

We note that a school district’s relative state funding per pupil (gi

/g)

depends on (1) the relative size of its tax base per pupil (measured as vi

/v)

and (2) the share of education funding financed at the local level (α) and

by implication the share of education funding financed with state funds

(1-α).

The slope parameter of equation IV.5 (α/1-α) can be interpreted as the

income elasticity of state funding and represents the state’s targeting effort

to achieve the maximum foundation level (providing all districts the

capacity to fund the state average funding level with an average tax

effort).80 The relationship also implies that the greater the local share of

total funding, and therefore the smaller the state share, the greater the

state’s targeting effort must be if it is to achieve the maximum foundation

level for all students.

Other important implications derive from this relationship:

80By definition, the income elasticity of state funding is the percent change in state funding associated

with a 1-percent difference in district income. Because both the independent and dependent variables

in equation IV.5 are measured relative to their respective state averages, they represent percent

differences from the state averages. Consequently, the slope represents the percent difference in

funding per pupil associated with a 1-percent difference in district income compared with the state

average. That is, the slope is the income elasticity of state funding evaluated at the state average.

Page 65 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IV 

Estimating States’ Targeting Efforts, Implicit

Foundation Levels, and Equalization Efforts

• A linear relationship must exist between a school district’s relative state

funding per pupil and the relative tax base per pupil.

• The intercept is the inverse of the state funding percentage (that is,

1/(1-α)).

• The slope and intercept will always sum to 1 (that is, (1/(1-α) + (-α/(1-α)))

= 1).81

State Targeting That

Produces an Implicit

Foundation Level

Below the State

Average

Although the state average represents the maximum foundation level

possible in a state if all districts were to make an average tax effort, most

states’ implicit foundation levels are likely less than the maximum. In this

section we develop the state targeting implications that produce an

implicit foundation level that is less than the maximum. We assume that all

districts make the same minimum tax effort and that the state still funds

the same share of total education funding.

If the implicit foundation level is less than the state average, it is because

the state targets its funds to low tax base districts to a lesser degree than

is required to achieve the maximum foundation level. To model this

condition, we introduced a new term—the equalizing factor (β)—into

equation IV.2. The value of the equalizing factor ranges from 0 to 1. When

the equalizing factor equals 1, the state’s targeting effort is at its maximum

level. When the equalizing factor equals 0, the state is not targeting funds

to poor districts, and every district receives the same state funding per

pupil. In this instance, the implicit foundation level is simply the average

state funding per pupil. An equalizing factor between 0 and 1 means the

state’s effort to target funds to poor districts is less than the maximum.

Introducing just the equalizing factor to the equation increases the size of

state funding to each district.82 However, since the total amount of state

funding has not changed, we had to introduce a scalar (γ) to ensure that

the sum of the state funding is still the same percentage of total funding.

The result of introducing these two new variables is shown in equation

IV.6:

81These equations were developed by J.C. Fastrup for “Fiscal Equalization and Access to Educational

Resources in the New England States,” Journal of Educational Finance (forthcoming in spring 1997).

82This would happen because the difference between the state average funding level (e) and the local

revenues that could be raised with an average tax effort (tvi) would become larger if the equalizing

factor (β) is less than 1.0 (see equation IV.6).

Page 66 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IV 

Estimating States’ Targeting Efforts, Implicit

Foundation Levels, and Equalization Efforts

Equation IV.6

where

β = the equalizing factor, that is, the fraction of the maximum targeting

effort that the state undertakes

γ = a scalar that ensures that the total sum of state funding equals the total

amount of state funds available for distribution.

The next few equations show that the scalar (γ) depends on the state share

of education funding (1-α) and the equalizing factor (β).

As stated earlier, the total amount of state funding equals the sum of all

the districts’ state funding. By multiplying both sides of equation IV.2 by

the total number of pupils in a district (Pi

) and summing both sides, we

created an equation for the total amount of state funding (Gs

).

Equation IV.7

where

Gs

 = the total sum of state funding available for distribution

Pi

 = the number of pupils in a district.

Because the total amount of state funding (Gs

) available has not changed,

it must be true that the sum of total state funding under maximum

targeting efforts is the same as when targeting efforts are less than the

maximum. This is represented in the following equation:

Page 67 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IV 

Estimating States’ Targeting Efforts, Implicit

Foundation Levels, and Equalization Efforts

Equation IV.8

Solving for the scalar (γ) yields equation IV.9:

Equation IV.9

By definition, the sum of (Pie) equals total funding and the sum of (Pitvi)

equals the total amount of local funding from all school districts. Dividing

both numerator and denominator by total funding yields the following

equation for the scalar (γ):

Equation IV.10

When the state’s targeting is at its maximum level, then the equalizing

factor (β) equals 1, and the scalar (γ) equals 1. If the state were to provide

flat funding per pupil to all districts, no targeting to poor districts would

occur, and the equalizing factor (β) would equal 0 and the scalar (γ) would

equal (1-α), the state’s share of total funding.

Targeting Effort As discussed earlier, we used the slope of equation IV.5 to determine how

much the state would have to target state funding to low tax base districts

to achieve an implicit foundation level equal to the state average. Revising

equation IV.6 produced a similar equation that shows how much state

funding would have to be targeted to low tax base districts to achieve an

Page 68 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IV 

Estimating States’ Targeting Efforts, Implicit

Foundation Levels, and Equalization Efforts

implicit foundation level below the state average. We modified equation

IV.6 by substituting (1-α)/(1-βα) for the scalar (γ) and substituting (αe/v)

for the average tax effort (t). Making these substitutions in equation IV.6

and rearranging terms yielded the following equation analogous to

equation IV.5:

Equation IV.11

This equation is the basis for running regressions, using actual district data

for state funding per pupil (gi

) and the tax base per pupil (vi). The slope

(βα/(1-βα)) represents the state’s targeting effort. When estimating this

equation, the slope and the intercept (1/(1-βα)) must be constrained so

that they sum to 1. After obtaining the regression coefficient for the tax

base per pupil, we can solve for the equalizing factor (β) because the local

share of funding (α) is known. When the state’s implicit foundation level is

less than the state average, the state’s equalizing factor (β) is less than 1

and the state’s targeting effort ((βα)/(1-βα)) is less than it would be at its

maximum value (α/(1-α)).

Implicit Foundation Level The term representing the implicit foundation level in equation IV.6 equals

the scalar (γ) times the state’s average total funding per pupil (e) or the

maximum foundation level. Substituting the expression in equation IV.10

for the scalar (γ) in equation IV.6, we expressed the implicit foundation

level in terms of the state’s average total funding per pupil, the local share

of school funding, and the equalizing factor as follows:

Equation IV.12

Page 69 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IV 

Estimating States’ Targeting Efforts, Implicit

Foundation Levels, and Equalization Efforts

Using equation IV.12 and knowing the local funding percentage (α), the

equalizing factor (β), and the state average funding level (e), we solved for

the state’s implicit foundation level.

Equalization Effort A state’s equalization effort is a ratio of the state’s implicit foundation level

to the maximum or average funding level. By rearranging terms in

equation IV.12, we showed that a state’s equalization effort, the ratio of the

implicit foundation level (e*) to the average funding level (e), equals the

scalar (γ) or (1-α)/(1-βα). Therefore, a state’s equalization effort reflects

the state’s share of education funding and a state’s targeting effort.

Appendix V describes how we used these equations to estimate each

state’s targeting effort, implicit foundation level, and equalization effort.

Page 70 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix V 

Estimating Equity Measures

This appendix describes the statistical models we used to estimate each

state’s targeting effort, implicit foundation level, and equalization effort. It

also presents the model results and the index data for some of the model

variables. In addition, it explains how the implicit foundation level for

each state can be adjusted to facilitate cross-state comparisons. Finally, it

describes how states’ estimated equalization efforts and relative local tax

efforts can explain the variation in state fiscal neutrality scores.

Calculating State

Targeting Efforts

In appendix IV, we developed a model to calculate a state’s implicit

foundation level that required knowing a state’s targeting effort, share of

education funding, and average total funding per pupil. To determine a

state’s targeting effort, we estimated the elasticity of state funding with

respect to district income (that is, districts’ tax bases) as measured by

income per pupil. The basic equation representing this relationship is

equation IV.11 from appendix IV, reproduced in this appendix as equation

V.1. The coefficient of the local tax base variable in this equation provided

an estimate of the elasticity of state funding relative to district income.83

Equation V.1

where

gi

 = state funding per pupil in a school district

g = the average state funding per pupil

α = the local share of the total funding for education in the state

83A regression coefficient measures the change in the dependent variable per unit change in the

independent variable. An elasticity is, by definition, the percent change in a dependent variable

associated with a 1-percent change in an independent variable. Because the dependent and

independent variables in this model are measured as percents of their respective state averages, the

regression coefficient (β1) can be interpreted as the percent difference in state funding per pupil

associated with a 1-percent difference in district income from the state average per pupil income. This,

by definition, is the elasticity of total per pupil funding relative to a district’s per pupil income,

evaluated at the mean of these variables.

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Appendix V 

Estimating Equity Measures

β = the equalizing factor, that is, the fraction of the maximum targeting

effort that the state undertakes

vi

 = the tax base per pupil in a school district (in our study, we used

income per pupil)

v = the average per pupil tax base in the state.

In the regression, both the dependent and independent variables were

adjusted for differences in geographic cost within the state by applying a

district-level teacher cost index to the dollar figures (see app. II). The

dependent variable was a district’s state funding per pupil, and the key

independent variable was a district’s income per pupil.

Our analyses included four other independent variables that controlled for

student-need factors that contribute to the cost of education. The first

three of these variables relate to the presence of high-cost student groups

in a district,84 and the fourth variable relates to cost differences due to

economies of scale. The four variables are

• the percent of district students who are poor (based on the percentage of

children who live in households that were below the poverty level in

1989);85

• the percent of district students who are disabled designated as special

education students under the Individuals With Disabilities Education Act

(part B) who have an Individual Education Plan;

• the percent of district students who are high school students (grades 9 to

12); and

• the total square of district enrollment (membership) on October 1, 1991.

We included these control variables in our model rather than use the

student need index developed in appendix II because we wanted to

account for actual state targeting policies to the extent possible rather

than use a uniform measure of student need that may not reflect actual

state policy.

All variables in the analysis were put into index form. Including all four

control variables yielded the following model of state targeting policies:

84Although students with limited English proficiency are considered to be a high-cost student group,

we did not include them in our analysis because we could not obtain accurate district-level data on the

number of such students.

85The average poverty threshold for a family of four was $12,674 in 1989.

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Appendix V 

Estimating Equity Measures

Equation V.2

where

ci

 = a district’s teacher cost index adjusted for statewide differences

MEMSQI86=a district’s student membership squared as a percent of the

district student membership (as a percent of the state average)

PovI = the percent of district students below the poverty level (as a

percent of the state average)

SNI = the percent of district students with an Individual Education Plan (a

measure of pupils with special education needs) also measured as a

percent of the state average

HSI = the percent of district students who are high school students (as a

percent of the state average)

∈ = error term measuring all other factors affecting the distribution of

state funding.

Each of the regression coefficients in the model depends on the

equalization factor and the local share of education funding (βα). An

additional coefficient (β1, β2, β3, and β4), unique to each variable, was

added so that the regression coefficients added to 1.0, as required by the

equalization model (see app. IV). The regression coefficients in the model

range from (β1/(1-βα)) to (β4/(1-βα)). The constant term (β0/(1-βα)) in the

model, in effect, serves as a control for the membership size of the

86The “I” at the end of each variable is to emphasize that each variable is measured as a percent of its

corresponding state average (that is, as an index).

Page 73 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix V 

Estimating Equity Measures

district.87

The model in equation V.2 was estimated by weighting each observation

for membership size to allow school districts with larger enrollments to

have a greater effect on determining the coefficients of the equation. This

prevents one or a few small school districts from unduly influencing the

estimated coefficients. The results are then more representative of the

effect that state funding targeting policies had on students in the state.

Because we were estimating the extent to which each state’s funding

targeting policy was consistent with providing an implicit foundation level

with a minimum tax effort, we also imposed the restriction that the three

student-need variables would have non-negative coefficients. We did not

specify the direction of the coefficient for the membership squared

variable because we did not have an expectation of how a state’s funding

targeting policy might reflect economies or diseconomies of size. Because

we wanted to determine the actual targeting efforts of states compared

with district income, we did not restrict the coefficient for the income per

pupil variable, allowing the coefficient to be any sign. We reported state

targeting efforts using the income per pupil coefficient obtained from this

effort.88

Results Table V.1 shows the targeting effort for state funds compared with district

income per pupil, the sampling error, and the overall R square.89 Negative

targeting efforts represent more targeting to poor than to wealthy districts;

positive targeting efforts represent more targeting to wealthy than to poor

districts. A targeting effort of 0 signifies no targeting of state funds to

either poor or wealthy districts.

Our analysis shows that 33 states targeted more state funds to districts as

district income declined. However, the degree of the targeting varied

widely, ranging from a high of –1.007 in Nevada to a low of –.099 in

Indiana. Fourteen states did not target state funds on the basis of district

87This can be seen by first multiplying both sides of equation V.2 by the average state funding per pupil

(g). This adjusts each coefficient in the equation by a constant. The dependent variable would then be

the funding per pupil of the district (gi). Multiplying this resulting equation by membership size would

make the intercept shown in equation V.2 the coefficient of district membership. Thus, the intercept

can be interpreted as the coefficient for membership.

88Because all variables are expressed in an index form, that is, they are a ratio of the variable’s district

rate to the corresponding state average, the regression coefficients of the variables automatically

represent elasticities.

89The adjusted R square is the proportion of the variation of the dependent variable explained by the

independent variable(s).

Page 74 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix V 

Estimating Equity Measures

income—the targeting effort was not statistically different from 0. Two

states—Louisiana and North Dakota—provided more state funding to

districts as district income increased.

The degree to which states targeted state funds on the basis of differences

in district income and student need also varied widely. In only 19 states,

district income and student need accounted for more than 50 percent of

the variation in state funding per pupil as noted by the R squared results.

In 3 of the 19 states—Kentucky, Maryland, and Virginia—more than

80 percent of the variation in state funding was explained. In the remaining

30 states, less than half of the variation in state funding per pupil was due

to differences in district income and student need.

Tables V.2 and V.3 provide the average income per pupil and average state

funding per pupil as well as the average index numbers of these two

variables according to groups of increasing district income. Tables V.4 to

V.7 provide the average index numbers for the four control variables

associated with student poverty, disabled students, high school students,

and district size according to groups of increasing district income.

Table V.1: Regression Results for

State Targeting State Targeting efforta Sampling error Overall R squared

Alabamab +.020 .045 .179

Alaskab +.068 .175 .487

Arizona –.232 .035 .410

Arkansas –.328 .031 .432

California –.119 .010 .331

Colorado –.753 .068 .512

Connecticut –.430 .055 .680

Delawareb –.070 .133 .424

Florida –.615 .077 .698

Georgia –.242 .065 .492

Idaho –.130 .051 .293

Illinois –.230 .015 .649

Indiana –.099 .030 .294

Iowa –.104 .028 .335

Kansas –.241 .095 .326

Kentucky –.239 .031 .845

Louisiana +.150 .068 .270

Maine –.287 .060 .329

Maryland –.566 .104 .873

(continued)

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Appendix V 

Estimating Equity Measures

State Targeting efforta Sampling error Overall R squared

Massachusetts –.316 .057 .664

Michigan –.475 .052 .573

Minnesota –.499 .031 .574

Mississippib –.020 .011 .285

Missourib –.017 .048 .577

Montana –.126 .047 .207

Nebraska –.245 .029 .142

Nevada –1.007 .329 .667

New Hampshire –.571 .132 .384

New Jersey –.104 .027 .534

New Mexicob +.024 .101 .066

New York –.578 .024 .686

North Carolinab –.016 .036 .479

North Dakota +.173 .043 .556

Ohio –.180 .025 .578

Oklahoma –.102 .029 .471

Oregonb –.043 .063 .122

Pennsylvania –.255 .019 .686

Rhode Island –.693 .184 .494

South Carolina –.505 .064 .625

South Dakotab +.116 .121 .440

Tennesseeb +.017 .032 .496

Texas –.522 .035 .595

Utahb –.172 .107 .405

Vermont –.539 .107 .280

Virginia –.499 .039 .835

Washingtonb –.009 .032 .226

West Virginiab –.127 .105 .357

Wisconsin –.270 .029 .445

Wyomingb +.296 .391 .242

aThis is the elasticity of state funding in a district relative to district income adjusted for statewide

differences in cost and need. An elasticity of 0 signifies no targeting of state funds to either poor

or wealthy districts; a negative effort indicates that more state funding is provided to poor

districts; a positive effort indicates that more state funding is provided to wealthy districts.

bStatistically, the targeting effort is not significantly different from 0.

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Appendix V 

Estimating Equity Measures

Table V.2: Income per Pupil Index Adjusted for Statewide Differences in Cost

Poorest Wealthiest

Average income per pupil index numbers

State average = 1.00

State

Average income

per pupil Group 1 Group 2 Group 3 Group 4 Group 5

Alabama $63,313 .69 .87 .97 1.05 1.42

Alaska 83,220 .49 .91 1.12 1.23 1.38

Arizona 98,442 .35 .62 .76 1.07 2.30

Arkansas 55,895 .64 .81 .93 1.10 1.52

California 121,872 .40 .63 .79 1.01 2.18

Colorado 81,879 .63 .81 .96 1.17 1.46

Connecticut 148,273 .56 .77 .88 1.05 1.73

Delaware 106,718 .61 .73 .84 1.17 1.68

Florida 98,373 .69 .83 .92 1.11 1.49

Georgia 73,340 .62 .82 .94 1.15 1.49

Idaho 51,724 .59 .81 .97 1.05 1.59

Illinois 134,121 .49 .59 .68 .93 2.30

Indiana 76,049 .69 .87 .98 1.07 1.40

Iowa 69,690 .74 .87 .95 1.08 1.35

Kansas 74,725 .69 .82 .93 1.10 1.46

Kentucky 63,691 .57 .78 .95 1.16 1.53

Louisiana 58,920 .67 .78 .95 1.14 1.53

Maine 76,336 .64 .76 .89 1.14 1.57

Maryland 114,832 .66 .78 .95 1.17 1.50

Massachusetts 133,452 .60 .77 .94 1.11 1.58

Michigan 80,367 .63 .75 .90 1.08 1.66

Minnesota 81,234 .61 .77 .89 1.11 1.62

Mississippi 51,017 .59 .76 .87 1.04 1.79

Missouri 79,570 .61 .77 .95 1.13 1.54

Montana 115,518 .43 .64 .79 1.07 2.07

Nebraska 94,845 .69 .83 .95 1.13 1.43

Nevada 86,827 .66 .99 1.07 1.27 a

New Hampshire 106,978 .63 .78 .90 1.07 1.61

New Jersey 160,761 .40 .63 .86 1.09 2.02

New Mexico 54,999 .48 .80 .91 1.34 1.90

New York 114,397 .63 .84 .96 1.02 1.57

North Carolina 76,415 .68 .84 .93 1.14 1.40

North Dakota 58,094 .68 .88 .99 1.11 1.39

Ohio 80,781 .65 .80 .91 1.09 1.55

(continued)

Page 77 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix V 

Estimating Equity Measures

Poorest Wealthiest

Average income per pupil index numbers

State average = 1.00

State

Average income

per pupil Group 1 Group 2 Group 3 Group 4 Group 5

Oklahoma 64,014 .62 .80 .90 1.16 1.51

Oregon 85,350 .65 .79 .92 1.12 1.56

Pennsylvania 99,378 .64 .82 .92 1.07 1.55

Rhode Island 108,151 .74 .88 1.01 1.10 1.34

South Carolina 65,707 .68 .86 1.00 1.13 1.33

South Dakota 57,440 .66 .87 1.01 1.10 1.37

Tennessee 70,681 .65 .83 .93 1.13 1.43

Texas 62,842 .48 .82 1.01 1.18 1.53

Utah 41,385 .69 .87 .96 1.05 1.39

Vermont 112,652 .50 .74 .91 1.17 1.66

Virginia 93,199 .67 .80 .86 1.09 1.61

Washington 82,373 .62 .78 .90 1.06 1.67

West Virginia 58,725 .66 .83 .98 1.13 1.37

Wisconsin 82,555 .68 .84 .92 1.04 1.53

Wyoming $55,152 .68 .89 1.01 1.12 1.30

aNevada was divided into only four groups because of the distribution of the student population.

The wealthiest group is group 4.

Table V.3: State Funding per Pupil Index Adjusted for Statewide Differences in Cost

Poorest Wealthiest

Average state funding per pupil index numbers

State average = 1.00

State

Average state

funding per pupil Group 1 Group 2 Group 3 Group 4 Group 5

Alabama $2,287 1.07 1.01 .96 .96 .99

Alaska 6,137 1.29 1.03 .84 .84 1.08

Arizona 2,109 1.20 1.08 1.02 1.04 .62

Arkansas 2,476 1.14 1.05 1.02 .93 .87

California 3,131 1.12 1.03 1.14 .92 .79

Colorado 2,194 1.20 1.24 .95 .94 .67

Connecticut 3,186 1.59 1.17 1.04 .74 .46

Delaware 3,916 1.15 1.04 .96 .94 .92

Florida 2,946 1.27 1.07 1.01 .96 .66

Georgia 2,361 1.19 1.13 .99 .90 .79

Idaho 2,350 1.05 1.06 .99 1.04 .86

(continued)

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Appendix V 

Estimating Equity Measures

Poorest Wealthiest

Average state funding per pupil index numbers

State average = 1.00

State

Average state

funding per pupil Group 1 Group 2 Group 3 Group 4 Group 5

Illinois 1,652 1.42 1.10 1.11 .79 .63

Indiana 2,703 1.06 1.01 .97 1.03 .93

Iowa 2,375 1.01 1.02 1.01 .99 .97

Kansas 2,181 1.14 1.17 1.06 .95 .68

Kentucky 2,609 1.21 1.09 1.00 .91 .80

Louisiana 2,433 1.06 1.00 1.01 .93 1.03

Maine 2,807 1.14 1.12 1.08 1.02 .66

Maryland 2,438 1.19 1.16 1.05 .90 .65

Massachusetts 1,932 1.65 1.04 .79 .86 .66

Michigan 1,925 1.70 1.19 .94 .69 .38

Minnesota 3,019 1.23 1.09 1.05 .98 .65

Mississippi 1,823 1.02 1.04 1.03 .98 .94

Missouri 1,773 1.02 .94 .83 1.25 .98

Montana 2,137 .88 .93 .95 1.07 1.17

Nebraska 1,768 1.15 1.12 .96 .95 .81

Nevada 2,049 1.43 .94 1.28 .79 a

New Hampshire 486 1.77 1.07 .86 .67 .63

New Jersey 3,985 1.57 1.20 .80 .65 .79

New Mexico 3,254 .98 1.01 .98 1.03 .92

New York 3,320 1.55 1.20 .81 .97 .64

North Carolina 2,995 1.08 1.01 1.00 .97 .94

North Dakota 1,957 1.08 .98 1.02 .97 .95

Ohio 1,971 1.19 1.11 1.04 .88 .78

Oklahoma 2,575 1.15 1.06 .97 .96 .86

Oregon 1,584 1.20 1.01 1.04 .79 .97

Pennsylvania 2,753 1.26 1.05 1.09 .93 .68

Rhode Island 2,333 1.29 .98 1.02 .82 .78

South Carolina 2,153 1.16 1.09 1.01 .90 .85

South Dakota 1,109 1.21 1.16 .87 .94 .85

Tennessee 1,566 1.07 1.01 .99 1.02 .92

Texas 2,180 1.53 1.13 1.01 .83 .50

Utah 1,911 1.06 1.10 1.03 .93 .92

Vermont 2,243 1.19 1.33 1.17 .80 .51

Virginia 1,695 1.35 1.21 .98 .94 .50

Washington 3,988 1.10 1.01 1.00 .98 .89

West Virginia 3,574 1.10 1.05 1.00 .95 .91

(continued)

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Appendix V 

Estimating Equity Measures

Poorest Wealthiest

Average state funding per pupil index numbers

State average = 1.00

State

Average state

funding per pupil Group 1 Group 2 Group 3 Group 4 Group 5

Wisconsin 2,707 1.21 1.22 1.01 .90 .65

Wyoming $3,111 1.01 .69 .90 1.13 1.26

aNevada was divided into only four groups because of the distribution of the student population.

The wealthiest group is group 4.

Table V.4: Poverty Index

Poorest Wealthiest

Average poverty rate index numbers

State average = 1.00

State

Average poverty

rate (percent) Group 1 Group 2 Group 3 Group 4 Group 5

Alabama 23.8 1.43 .87 1.15 .64 .83

Alaska 11.2 1.90 .82 .64 .82 .53

Arizona 21.0 1.74 .91 .75 .84 .74

Arkansas 24.6 1.37 1.06 .99 .72 .86

California 18.4 1.41 .93 1.28 .76 .61

Colorado 14.8 1.40 1.17 .76 .45 1.26

Connecticut 10.4 2.67 .75 .73 .38 .48

Delaware 12.2 1.35 1.24 .85 .82 .75

Florida 18.6 1.17 1.22 .99 .79 .80

Georgia 19.6 1.40 1.11 .82 1.07 .57

Idaho 15.8 1.02 1.21 1.02 .90 .85

Illinois 16.4 1.14 2.00 .79 .56 .37

Indiana 13.5 1.32 .83 .83 1.20 .81

Iowa 13.8 1.03 .96 1.19 .86 .95

Kansas 13.8 1.36 .89 .92 1.01 .83

Kentucky 25.1 1.63 1.06 .84 .71 .77

Louisiana 31.8 1.17 1.08 .93 1.04 .72

Maine 13.7 1.31 .96 .97 .92 .83

Maryland 11.3 2.38 .79 .72 .59 .51

Massachusetts 13.3 1.91 .85 .54 1.20 .49

Michigan 17.4 1.94 1.14 .72 .63 .42

Minnesota 12.1 1.29 .80 .82 1.04 1.05

Mississippi 32.9 1.36 1.12 .91 .80 .82

Missouri 17.0 1.39 .98 .80 1.01 .84

(continued)

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Appendix V 

Estimating Equity Measures

Poorest Wealthiest

Average poverty rate index numbers

State average = 1.00

State

Average poverty

rate (percent) Group 1 Group 2 Group 3 Group 4 Group 5

Montana 19.5 1.36 .95 .93 .92 .85

Nebraska 12.9 1.16 .94 .67 1.37 .83

Nevada 13.3 .93 1.09 .67 .88 a

New Hampshire 7.6 1.35 .87 1.07 1.05 .67

New Jersey 11.3 2.57 1.07 .53 .39 .45

New Mexico 27.5 1.57 1.01 1.06 .70 .47

New York 18.5 .91 .72 1.65 .41 .31

North Carolina 17.1 1.56 .97 .93 .82 .74

North Dakota 16.4 1.42 1.06 .87 .82 .82

Ohio 16.9 1.32 1.22 1.13 .76 .57

Oklahoma 20.9 1.27 1.08 .82 .76 1.07

Oregon 15.2 1.28 1.10 .97 .65 1.02

Pennsylvania 15.2 1.33 .92 1.47 .90 .39

Rhode Island 12.8 2.10 .39 .78 .60 .57

South Carolina 20.8 1.43 1.07 .71 .79 .97

South Dakota 18.2 1.60 1.13 .88 .78 .62

Tennessee 20.4 1.11 .95 1.31 .86 .76

Texas 24.4 1.73 .98 .70 .87 .72

Utah 12.1 1.10 1.08 .64 1.01 1.29

Vermont 11.8 1.21 .96 .90 .89 1.03

Virginia 13.4 1.52 1.15 .78 1.12 .45

Washington 14.3 1.45 .86 1.01 .93 .73

West Virginia 25.6 1.47 1.08 .89 .73 .82

Wisconsin 14.1 1.14 1.84 .74 .77 .51

Wyoming 13.8 1.06 .94 1.01 1.04 .96

aNevada was divided into only four groups because of the distribution of the student population.

The wealthiest group is group 4.

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Table V.5: Disabled Index

Poorest Wealthiest

Average disabled rate index numbers

State average = 1.00

State

Average disabled

rate (percent) Group 1 Group 2 Group 3 Group 4 Group 5

Alabama 13.5 .92 1.04 1.04 1.06 .95

Alaska 13.5 1.14 1.00 .90 .95 .99

Arizona 8.9 1.11 1.00 .94 1.06 .88

Arkansas 9.7 1.09 1.01 1.04 .94 .92

California 8.8 .93 1.00 1.02 1.05 .99

Colorado 9.6 1.01 1.15 .93 .89 1.05

Connecticut 12.8 1.07 1.05 .94 1.00 .94

Delaware 10.6 .98 1.08 1.03 .98 .90

Florida 11.9 1.01 .92 1.01 .99 1.10

Georgia 9.0 1.05 1.12 .96 .89 .99

Idaho 10.4 .94 1.05 1.01 .98 1.03

Illinois 13.0 1.08 .84 1.06 1.08 .97

Indiana 11.6 1.03 .98 1.00 1.05 .94

Iowa 12.6 .92 .96 1.02 1.05 1.05

Kansas 10.2 1.00 .94 1.01 1.12 .95

Kentucky 12.4 1.03 1.00 .97 .97 1.02

Louisiana 10.7 .99 1.08 .94 .92 1.09

Maine 11.9 .99 .95 1.00 1.04 1.03

Maryland 12.0 1.23 .98 .88 1.02 .84

Massachusetts 15.9 .90 1.01 .99 1.09 1.00

Michigan 9.9 .98 .99 1.00 1.08 .95

Minnesota 10.7 .94 .95 1.02 1.05 1.05

Mississippi 12.0 .83 1.12 1.03 1.02 .99

Missouri 10.0 1.12 1.15 .98 1.08 .68

Montana 9.8 1.05 .96 1.18 .95 .85

Nebraska 12.3 .92 .99 .97 1.03 1.09

Nevada 9.4 1.17 .90 1.23 1.13 a

New Hampshire 11.4 .92 .99 .99 1.01 1.09

New Jersey 16.1 .94 1.06 1.04 .99 .98

New Mexico 12.2 .89 .90 .95 1.17 .90

New York 11.0 .98 .99 1.05 .95 .95

North Carolina 11.4 .98 .97 1.08 1.01 .96

North Dakota 10.4 .97 1.06 1.08 .97 .90

Ohio 11.3 .99 1.06 1.03 .95 .98

(continued)

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Poorest Wealthiest

Average disabled rate index numbers

State average = 1.00

State

Average disabled

rate (percent) Group 1 Group 2 Group 3 Group 4 Group 5

Oklahoma 11.4 1.07 .91 .92 .95 1.16

Oregon 9.3 1.07 1.02 1.01 .93 .97

Pennsylvania 10.8 1.05 1.01 1.00 1.00 .93

Rhode Island 14.7 .92 .94 1.05 1.09 1.00

South Carolina 10.9 .98 1.05 .89 1.04 1.04

South Dakota 9.8 1.10 .88 .90 .97 1.16

Tennessee 11.9 1.10 1.08 .87 1.02 .94

Texas 9.9 .91 1.05 1.08 1.00 .96

Utah 10.6 1.05 .98 .92 .89 1.14

Vermont 10.4 1.05 .98 1.05 .99 .92

Virginia 11.3 .94 .92 .96 1.07 1.13

Washington 9.6 1.07 .99 1.09 .92 .92

West Virginia 13.4 1.05 1.06 .96 .97 .97

Wisconsin 11.0 .99 1.05 1.00 1.03 .93

Wyoming 10.3 .93 .95 1.09 1.08 .95

aNevada was divided into only four groups because of the distribution of the student population.

The wealthiest group is group 4.

Table V.6: High School Index

Poorest Wealthiest

Average high school student index numbers

State average = 1.00

State Group 1 Group 2 Group 3 Group 4 Group 5

Alabama 1.02 1.02 1.00 1.01 .96

Alaska .93 .99 1.03 1.02 1.08

Arizona .77 .67 .76 .81 2.08

Arkansas .99 1.00 1.01 .99 1.01

California .80 .79 .92 .85 1.64

Colorado .97 1.00 1.01 1.03 .99

Connecticut .89 .99 .99 1.02 1.11

Delaware 1.03 .99 .99 1.02 .94

Florida 1.00 1.01 .99 .99 1.02

Georgia 1.01 .99 1.01 .96 1.03

Idaho 1.02 1.01 1.02 .98 .97

Illinois .87 .87 .84 .46 1.97

(continued)

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Poorest Wealthiest

Average high school student index numbers

State average = 1.00

State Group 1 Group 2 Group 3 Group 4 Group 5

Indiana 1.02 1.01 1.02 .96 .99

Iowa .99 1.01 1.01 1.03 .96

Kansas .96 1.06 1.02 1.01 .96

Kentucky 1.00 1.01 1.02 .98 .99

Louisiana .98 .97 1.03 1.01 1.01

Maine 1.15 1.10 .98 .88 .88

Maryland .86 1.03 1.06 1.03 1.02

Massachusetts .97 .99 1.04 1.07 .91

Michigan .94 1.00 1.03 .99 1.05

Minnesota 1.05 1.04 1.01 .96 .93

Mississippi .97 .98 1.02 1.03 1.00

Missouri 1.04 1.03 .98 .95 .99

Montana .02 .04 .04 1.42 3.55

Nebraska 1.05 1.02 .99 .90 1.05

Nevada 1.00 1.00 1.04 1.00 a

New Hampshire 1.16 1.18 1.22 .88 .57

New Jersey .87 .91 .94 .86 1.42

New Mexico 1.02 .98 1.01 1.00 1.00

New York .97 .98 .98 1.02 1.07

North Carolina 1.01 1.02 1.00 1.01 .96

North Dakota 1.02 1.06 1.00 .98 .93

Ohio 1.02 1.00 .96 1.01 1.02

Oklahoma 1.09 1.03 1.04 .98 .85

Oregon 1.00 .96 .95 .83 1.29

Pennsylvania 1.00 1.01 .98 1.00 1.02

Rhode Island .95 1.07 .97 1.04 1.00

South Carolina .99 1.02 1.03 1.03 .95

South Dakota .93 .97 .99 .99 1.12

Tennessee 1.11 1.05 .97 .96 .92

Texas 1.02 1.01 1.01 .97 .99

Utah 1.04 1.02 .99 1.00 .97

Vermont 1.11 .60 .55 .97 1.75

Virginia 1.03 1.02 .94 .95 1.06

(continued)

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Poorest Wealthiest

Average high school student index numbers

State average = 1.00

State Group 1 Group 2 Group 3 Group 4 Group 5

Washington 1.03 1.00 .96 1.00 1.01

West Virginia 1.01 .99 .99 1.00 1.01

Wisconsin 1.00 .88 1.04 1.02 1.06

Wyoming .95 .99 1.05 1.01 .99

aNevada was divided into only four groups because of the distribution of the student population.

The wealthiest group is group 4.

Table V.7: Membership Squared Index

Poorest Wealthiest

Average membership squared index numbers

State average = 1.00

State Group 1 Group 2 Group 3 Group 4 Group 5

Alabama .20 .37 2.19 1.15 .95

Alaska .26 .51 .16 2.09 .08

Arizona .26 .52 1.77 1.73 .58

Arkansas .30 .42 .50 1.53 2.23

California .21 .17 4.16 .33 .13

Colorado .13 .51 .72 2.23 1.46

Connecticut 2.24 .85 .61 .56 .75

Delaware .43 .51 .79 1.58 1.45

Florida .25 2.23 .80 .86 .66

Georgia .16 .26 .79 1.57 2.26

Idaho .38 .44 1.12 1.01 2.05

Illinois .04 4.08 .07 .07 .04

Indiana .60 .51 .47 1.84 1.52

Iowa .17 .41 1.18 .61 2.54

Kansas .67 .16 .39 .50 3.23

Kentucky .26 .21 .29 .31 3.90

Louisiana .32 .34 .87 1.71 1.80

Maine .61 1.25 .93 1.00 1.21

Maryland 1.16 .31 1.25 .97 1.42

Massachusetts 1.13 .60 .33 2.53 .38

Michigan 3.23 .24 .22 .40 .36

Minnesota .16 1.07 .87 1.28 1.61

Mississippi 1.93 .58 .63 .91 .94

(continued)

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Estimating Equity Measures

Poorest Wealthiest

Average membership squared index numbers

State average = 1.00

State Group 1 Group 2 Group 3 Group 4 Group 5

Missouri .20 .28 .79 1.83 1.93

Montana .28 .32 1.89 1.69 .75

Nebraska .18 .23 .55 2.58 1.38

Nevada .05 1.48 .07 .45 a

New Hampshire .43 .68 2.08 1.42 .40

New Jersey 2.51 1.14 .60 .48 .27

New Mexico .20 .17 .34 2.49 .33

New York .02 .02 2.68 .01 .01

North Carolina .40 .77 .60 .61 2.53

North Dakota .30 .81 1.15 1.23 1.57

Ohio .29 1.41 1.07 1.27 .97

Oklahoma .13 .45 .84 .56 2.98

Oregon .19 .40 .94 1.02 2.53

Pennsylvania .12 .14 4.20 .36 .19

Rhode Island 1.85 .49 .73 1.13 .31

South Carolina .57 .42 .74 .80 2.30

South Dakota .19 .21 1.53 .42 2.35

Tennessee .22 .24 2.25 .39 1.66

Texas .57 .40 .39 2.24 1.41

Utah .50 .22 1.53 1.99 .45

Vermont 1.04 1.20 .63 .95 1.20

Virginia .30 .33 1.34 .31 2.63

Washington .43 .66 1.03 1.20 1.71

West Virginia .53 .48 .86 .94 2.07

Wisconsin .10 3.47 .33 .65 .42

Wyoming .40 .74 .51 1.66 1.72

aNevada was divided into only four groups because of the distribution of the student population.

The wealthiest group is group 4.

Calculating State

Implicit Foundation

Levels and

Equalization Effort

In appendix IV we demonstrated that to calculate the implicit foundation

level we must know the state’s targeting effort, the local share of total

funding, the state’s average total funding per weighted pupil, and the

equalizing factor. Because the equalization theory underlying the implicit

foundation level implies state funding is targeted to poor districts, when

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Estimating Equity Measures

we determined the targeting effort for calculating the implicit foundation

level, we constrained the coefficient of the tax base variable to be less

than or equal to 0. Then, having calculated the state’s targeting effort (that

is, the coefficient of the tax base variable, βα/(1-βα)) and knowing the

local share of education funding (α) and average total funding per

weighted pupil (e), we can solve for the equalizing factor (β). Finally,

knowing the equalizing factor, we can calculate the state’s implicit

foundation level using equation IV.12 from appendix IV (reproduced here

as equation V.3). The results for each state are reported in table V.8.

Equation V.3

where

e = the state’s average total funding per weighted pupil.

The implicit foundation level available to all students in a state depends

upon the state’s average total funding per weighted pupil, targeting effort,

and share of total funding. Two states with the same average total funding

per weighted pupil can have very different implicit foundation levels

depending on their state equalization policies. For example, Alaska and

Connecticut had about the same average funding level. However, Alaska’s

state share was about twice that of Connecticut’s. Consequently, Alaska’s

implicit foundation level ($6,137) was much more than Connecticut’s

($4,556), even though Connecticut’s targeting effort was greater than

Alaska’s effort.

Once we know the implicit foundation level, we can calculate the state’s

equalization effort. This is a measure of the implicit foundation level as a

percent of the state average. Since the state average is the maximum

foundation level that is possible in a state given the total funding devoted

to education, the equalization effort is a measure of how close a state

comes to reaching the maximum level.

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Results States’ implicit foundation levels varied widely. The average implicit

foundation level was $3,090 per weighted pupil in school year 1991-92,

with levels ranging as low as $764 in New Hampshire to as high as $6,137

in Alaska.90

States’ equalization efforts also varied widely. Only one state—Nevada—

reached the state average for each student.91 The equalization effort in the

other 48 states was less than the state average, ranging from 87 percent

(Arkansas and Kentucky) to 13 percent (New Hampshire) of their state

average. In 14 states, districts could finance less than half the state average

with a minimum local tax effort.

Table V.8 summarizes the critical data used to determine the implicit

foundation level and equalization effort for all states.

Table V.8: State Targeting, State Share, and Funding Levels

State

State targeting

efforta (βα/(1-βα))

State’s share as a

percent of total

funding (1-α)

State average

funding levelb (e)

Implicit

foundation level

(e*)

Equalization

effortc (e*/e)

Alabama .000 69.8 $3,277 $2,287 69.8

Alaska .000 76.4 8,030 6,137 76.4

Arizona –.232 46.8 4,507 2,598 57.7

Arkansas –.328 65.4 3,784 3,289 86.9

California –.119 68.9 4,543 3,504 77.1

Colorado –.753 43.5 5,047 3,847 76.2

Connecticut –.430 38.8 8,221 4,556 55.4

Delaware –.070 70.2 5,576 4,190 75.1

Florida –.615 53.0 5,555 4,759 85.7

Georgia –.242 54.6 4,324 2,932 67.8

Idaho –.130 67.1 3,504 2,654 75.7

Illinois –.230 33.2 4,970 2,031 40.9

Indiana –.099 54.1 4,993 2,970 59.5

Iowa –.104 49.0 4,849 2,622 54.1

Kansas –.241 43.8 4,973 2,706 54.4

Kentucky –.239 70.0 3,728 3,232 86.7

Louisiana .000 62.2 3,912 2,433 62.2

(continued)

90These figures have not been adjusted for national differences in geographic and student need-related

costs. See table V.10 for the nationally adjusted figures.

91In fact, Nevada targeted more state funds to poor districts than was necessary for districts to finance

the state average with all districts making an equal tax effort. As a result, poor districts in Nevada were

able to finance the state average funding level with a lower tax effort than wealthy districts.

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Estimating Equity Measures

State

State targeting

efforta (βα/(1-βα))

State’s share as a

percent of total

funding (1-α)

State average

funding levelb (e)

Implicit

foundation level

(e*)

Equalization

effortc (e*/e)

Maine –.287 49.4 5,681 3,612 63.6

Maryland –.566 40.4 6,039 3,819 63.2

Massachusetts –.316 30.8 6,264 2,542 40.6

Michigan –.475 32.9 5,851 2,839 48.5

Minnesota –.499 53.5 5,646 4,524 80.1

Mississippi –.020 64.4 2,831 1,860 65.7

Missouri –.017 44.6 3,972 1,802 45.4

Montana –.126 44.2 4,835 2,407 49.8

Nebraska –.246 34.3 5,148 2,203 42.8

Nevadad –1.007 56.9 3,597 3,597 100.0

New Hampshire –.571 8.3 5,850 764 13.1

New Jersey –.104 43.1 9,239 4,399 47.6

New Mexico .000 85.0 3,830 3,254 85.0

New York –.578 42.6 7,787 5,240 67.3

North Carolina –.016 67.7 4,424 3,043 68.8

North Dakota .000 48.0 4,079 1,957 48.0

Ohio –.180 41.9 4,709 2,325 49.4

Oklahoma –.102 71.1 3,623 2,838 78.3

Oregon –.043 31.1 5,087 1,652 32.5

Pennsylvania –.255 43.0 6,406 3,455 53.9

Rhode Island –.694 39.3 5,939 3,953 66.6

South Carolina –.505 52.4 4,112 3,239 78.8

South Dakota .000 29.5 3,756 1,109 29.5

Tennessee .000 47.0 3,329 1,566 47.0

Texas –.522 47.4 4,603 3,318 72.1

Utah –.172 60.2 3,177 2,240 70.5

Vermont –.539 29.0 7,722 3,453 44.7

Virginia –.499 36.0 4,713 2,541 53.9

Washington –.009 75.2 5,302 4,025 75.9

West Virginia –.127 72.5 4,927 4,028 81.8

Wisconsin –.270 46.2 5,865 3,439 58.6

Wyoming .000 52.5 5,920 3,111 52.5

(Table notes on next page)

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aThis is the elasticity of state funding relative to district income adjusted for statewide differences

in cost and need. An elasticity of 0 signifies no targeting. States with a .000 have had their income

coefficient constrained.

bThe state average is the average total (state and local) funding per weighted pupil in the state

and represents the state’s maximum possible foundation level given the total funding devoted to

education in the state.

cThis is equal to the implicit foundation level as a percent of the state average.

dNevada targeted more state funds to poor districts than was necessary for districts to finance the

state average with all districts making the same tax effort. As a result, poor districts in Nevada

were able to finance the state average funding level with a lower tax effort than wealthy districts.

Sensitivity Analysis In addition to targeting additional funds to poor districts, some states

provided the same minimum amount of state funding to all districts,

regardless of district income. Unlike funding for lower income districts,

such funding for wealthy districts in some states was not part of the state’s

targeting effort because it was not sensitive to district income.

Consequently, we also estimated the state implicit foundation level and

equalization effort, assuming the goal was to have all students except for

the 15 percent of students in the wealthiest districts receive the implicit

foundation level. Using this analysis, we found that 16 states had a net

increase of 10 percentage points or more in their equalization effort, that

is, in the extent to which they achieved the state average. Table V.9

provides the results of this analysis.

Table V.9: Implicit Foundation Level and Equalization Effort for 85 Percent of Students in Each State

State

State average funding

level for 85 percent of

studentsa

Implicit foundation

level for 85 percent of

students

Equalization effort for

85 percent of the

studentsb

Equalization effort for

all studentsc

Alabama $3,237 $2,286 70.6 69.8

Alaska 8,001 6,893 86.1 76.4

Arizona 4,284 2,468 57.6 57.7

Arkansas 3,783 3,296 87.1 86.9

California 4,456 4,002 89.8 77.1

Colorado 5,016 4,251 84.8 76.2

Connecticut 7,614 5,354 70.3 55.4

Delaware 5,499 4,154 75.5 75.1

Florida 5,418 4,252 78.5d 85.7

Georgia 4,241 2,659 62.7d 67.8

Idaho 3,504 2,654 75.7 75.7

Illinois 4,275 2,701 63.2 40.9

(continued)

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Estimating Equity Measures

State

State average funding

level for 85 percent of

studentsa

Implicit foundation

level for 85 percent of

students

Equalization effort for

85 percent of the

studentsb

Equalization effort for

all studentsc

Indiana 4,960 3,054 61.6 59.5

Iowa 4,833 2,610 54.0d 54.1

Kansas 4,955 3,098 62.5 54.4

Kentucky 3,727 3,294 88.4 86.7

Louisiana 3,912 2,433 62.2 62.2

Maine 5,631 4,109 73.0 63.6

Maryland 5,526 4,464 80.8 63.2

Massachusetts 5,451 3,657 67.1 40.6

Michigan 5,636 4,028 71.5 48.5

Minnesota 5,539 4,478 80.8 80.1

Mississippi 2,828 2,141 75.7 65.7

Missouri 3,887 2,311 59.4 45.4

Montana 4,141 1,993 48.1d 49.8

Nebraska 5,076 3,092 60.9 42.8

Nevada 3,597 3,597 100.0 100.0

New Hampshire 5,474 1,175 21.5 13.1

New Jersey 8,683 7,897 91.0 47.6

New Mexico 3,826 3,255 85.1 85.0

New York 7,111 7,111 100.0 67.3

North Carolina 4,418 3,014 68.2d 68.8

North Dakota 4,074 1,957 48.0 48.0

Ohio 4,550 2,673 58.7 49.4

Oklahoma 3,621 2,885 79.7 78.3

Oregon 5,043 2,432 48.2 32.5

Pennsylvania 6,084 4,119 67.7 53.9

Rhode Island 5,846 5,439 93.0 66.6

South Carolina 4,112 3,239 78.8 78.8

South Dakota 3,756 1,108 29.5 29.5

Tennessee 3,329 1,567 47.1 47.0

Texas 4,588 3,600 78.5 72.1

Utah 3,177 2,240 70.5 70.5

Vermont 7,367 3,036 41.2d 44.7

Virginia 4,342 2,994 69.0 53.9

Washington 5,228 4,350 83.2 75.9

West Virginia 4,927 4,028 81.8 81.8

Wisconsin 5,764 4,987 86.5 58.6

Wyoming $5,920 3,111 52.5 52.5

(Table notes on next page)

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aThe state average is the average total (state and local) funding per weighted pupil in the state

and represents the state’s maximum possible foundation level given the total funding devoted to

education in the state.

bThis is equal to the implicit foundation level as a percent of the state average for 85 percent of

the students.

cFrom table V.8.

dThe state achieved a higher percentage when all students were included, indicating that state

funding was sensitive to district income across the entire range of district income.

Cross-State Comparisons

of Implicit Foundation

Levels

To facilitate cross-state comparisons of the implicit foundation levels, we

adjusted the implicit foundation levels reported in table V.8 for interstate

differences in costs and student needs. We used a teacher cost index

available from the National Center for Education Statistics (NCES) for the

states to adjust funding data for national differences in cost, and we

created a nationwide need index for the states in the same way we created

other indexes (see app. II). To compare states, we divided the funding data

from a state by the product of the nationwide cost and need indexes of

that state. Using this method, we calculated the nationally adjusted

implicit foundation level for each state (see table V.10 and fig. V.1). Table

V.11 lists the original nationwide teacher cost index we obtained from

NCES, an adjusted nationwide index that applies only to teacher costs, and

the nationwide need index for each state.

Table V.10: Nationally Adjusted

Implicit Foundation Levels

State

Adjusted implicit

foundation levela

Alabama $2,447

Alaska 5,415

Arizona 2,712

Arkansas 3,698

California 3,324

Colorado 3,953

Connecticut 4,051

Delaware 4,175

Florida 4,917

Georgia 3,215

Idaho 2,827

Illinois 1,883

Indiana 3,029

Iowa 2,827

(continued)

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State

Adjusted implicit

foundation levela

Kansas 3,067

Kentucky 3,460

Louisiana 2,744

Maine 3,485

Maryland 3,698

Massachusetts 2,170

Michigan 2,751

Minnesota 4,626

Mississippi 2,078

Missouri 1,913

Montana $2,564

Nebraska $2,397

Nevada 4,409

New Hampshire 721

New Jersey 3,789

New Mexico 3,441

New York 4,648

North Carolina 3,227

North Dakota 2,175

Ohio 2,281

Oklahoma 3,171

Oregon 1,685

Pennsylvania 3,311

Rhode Island 3,509

South Carolina 3,524

South Dakota 1,260

Tennessee 1,683

Texas 3,542

Utah 2,339

Vermont 3,469

Virginia 2,642

Washington 3,919

West Virginia 4,398

Wisconsin 3,497

Wyoming 3,517

National average 3,134

aAdjusted for differences in cost and need nationwide.

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Figure V.1: Nationally Adjusted Implicit Foundation Levels (Ranked)

Alaska

Florida

New York

Minnesota

Nevada

West Virginia

Delaware

Connecticut

Colorado

Washington

New Jersey

Arkansas

Maryland

Texas

South Carolina

Wyoming

Rhode Island

Wisconsin

Maine

Vermont

Kentucky

New Mexico

California

Pennsylvania

North Carolina

Georgia

Oklahoma

NATIONAL AVE.

Kansas

Indiana

Iowa

Idaho

Michigan

Louisiana

Arizona

Virginia

Montana

Alabama

Nebraska

Utah

Ohio

North Dakota

Massachusetts

Mississippi

Missouri

Illinois

Oregon

Tennessee

South Dakota

New Hampshire

0 1,000 2,000 3,000 4,000 5,000 6,000

Funding per Weighted Pupil (Dollars)

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Table V.11: Nationwide State Cost and

Need Indexes

State

State teacher cost

indexa

Adjusted state

teacher cost

indexb State need index

Alabama 88.27 .9005 1.0381

Alaska 113.56 1.1150 1.0164

Arizona 97.07 .9752 .9823

Arkansas 87.22 .8916 .9974

California 109.39 1.0796 .9765

Colorado 99.26 .9937 .9791

Connecticut 113.80 1.1170 1.0069

Delaware 102.08 1.0176 .9863

Florida 94.91 .9568 1.0115

Georgia 91.70 .9296 .9811

Idaho 93.86 .9480 .9903

Illinois 106.76 1.0573 1.0201

Indiana 97.74 .9808 .9995

Iowa 90.28 .9176 1.0104

Kansas 87.77 .8963 .9843

Kentucky 89.22 .9086 1.0282

Louisiana 84.57 .8691 1.0201

Maine 103.94 1.0334 1.0029

Maryland 103.84 1.0326 1.0002

Massachusetts 114.06 1.1192 1.0466

Michigan 105.34 1.0453 .9873

Minnesota 98.89 .9906 .9872

Mississippi 83.86 .8631 1.0371

Missouri 94.59 .9541 .9871

Montana 93.92 .9484 .9895

Nebraska 89.87 .9141 1.0054

Nevada 94.90 .9567 .9748

New Hampshire 108.71 1.0739 .9874

New Jersey 113.02 1.1104 1.0454

New Mexico 90.34 .9181 1.0300

New York 114.82 1.1257 1.0014

North Carolina 92.91 9399 1.0033

North Dakota 89.19 .9084 .9907

Ohio 102.06 1.0174 1.0015

Oklahoma 86.60 .8864 1.0098

Oregon 100.42 1.0036 .9772

(continued)

Page 95 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix V 

Estimating Equity Measures

State

State teacher cost

indexa

Adjusted state

teacher cost

indexb State need index

Pennsylvania 105.97 1.0506 .9931

Rhode Island 110.76 1.0912 1.0324

South Carolina 90.00 .9152 1.0043

South Dakota 87.08 .8904 .9879

Tennessee 90.29 .9176 1.0140

Texas 92.66 .9377 .9992

Utah 96.58 .9710 .9862

Vermont 101.42 1.0120 .9836

Virginia 95.96 .9658 .9960

Washington 105.84 1.0496 .9786

West Virginia 86.01 .8813 1.0393

Wisconsin 98.76 .9895 .9937

Wyoming 87.99 .8981 .9848

aThis state index has been rounded to two decimal places. See Jay Chambers and William

Fowler, Public School Teacher Cost Differences Across the United States, Department of

Education, NCES, Analysis/Methodology Report, No. 95-758 (Washington, D.C.: Oct. 1995).

bWe have adjusted the state index to make 1.00 the average for the nation rather than 100 and to

reflect differences in teacher costs that represent only 84.8 percent of current education

expenditures.

Funding Gaps, State

Equalization Effort,

and Relative Local

Tax Effort

After calculating the state equalization effort, a measure that accounts for

the combined effects of state targeting and state share in state equalization

policies, we used it together with relative local tax effort to explain

cross-state variation in funding gaps. In equation V.4, the dependent

variable was the state fiscal neutrality scores reported in table III.1; the

two independent variables were the state equalization efforts, reported in

table V.8 and the elasticity of local tax effort reported in table III.6.

Equation V.4

Page 96 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix V 

Estimating Equity Measures

The results of this analysis showed that the two factors accounted for

63 percent of the variation in the funding gaps.92 The elasticity of local tax

effort accounted for more of the variation in funding gaps than did state

equalization efforts (see table V.12).

Table V.12: Regression Results 

(N = 49) 

Factor

Regression

coefficient Beta coefficient t statistic

State equalization effort –.4457 –.4340 –4.890

Elasticity of local tax effort .2687 .6178 6.962

92The adjusted R square for the analysis was .6293.

Page 97 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix VI 

Guide to State Profiles

Appendixes VII through LV contain profiles for 49 states. Each profile

provides the critical data resulting from our analysis of state school

finance policies. In addition, each profile provides information in tabular

and graphic form on (1) the actual distribution of state and local funding

to regular school districts in school year 1991-92 and (2) how the funding

would have been distributed if the state share of total funding had

remained the same and the targeting of state funding had been changed so

that districts could spend the state average of total funding on each

student with an average tax effort. All funding data in the profiles were

adjusted for differences in geographic cost and student need within the

state. The profiles show averages for districts within the state in five

groups according to increasing income per pupil based on student

population.93 For example, the poorest group of districts typically contains

about 20 percent of a state’s student population and has the lowest

incomes per pupil.

In the stacked bar graphs (the first two figures in each profile), the height

of the bars shows how state funding that has been adjusted for cost and

need is equalized among districts. If the state fully equalized funding, all

the bars are the same height. To assess the targeting of state funds,

examine the shaded area within each bar, which represents the state’s

share of total funding. Where state funding was targeted to poor districts,

the shaded portion is highest for the poorest districts and becomes smaller

as the per pupil income of a district increases.

The first figure in each profile shows how total funding per weighted pupil

changed as district income per pupil increased. Typically, the local funding

increased with increasing per pupil income, often at a faster rate than the

decline in state funding. Thus, total funding typically was greatest for the

wealthiest districts.

The second figure in each profile shows how state and local funding would

have been distributed if all districts could have spent the average total

funding per weighted pupil (the total funding level is the same across all

groups) with an average tax effort. This figure assumes that the state

optimized its targeting effort without changing the state share or the total

funding for education.

93Each of the five groups typically had about the same student population. In some states, however, the

groups may have had large differences in the number of students because districts cannot be divided

into smaller units. Nevada’s districts were divided into four groups because of the distribution of the

student population.

Page 98 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix VI 

Guide to State Profiles

The third figure in each profile compares the state funding in the first

figure with the state funding in the second figure. The third figure

illustrates which groups of districts would have received more or less than

what they needed if the state had targeted its funds so that each district

could have spent the state average of total funding on each student with an

average tax effort.

The data used in each of the figures appear in tables in each profile. The

numbers in the tables may not add due to rounding.

Data used in the profiles were based mainly on the Department of

Education’s Common Core of Data (CCD) for school districts for the

1991-92 school year. In some cases, we obtained data directly from state

education offices, and we imputed income and cost data for a district

when the data were missing from the source. Income per pupil data were

adjusted for differences in cost within a state. Funding per pupil data were

adjusted for differences in student need and geographic costs within a

state. Funding data included all state and local revenue for all purposes,

including maintenance and operations, transportation, and capital

expenditures and debt service.94

94Because the CCD does not report separate data on local funding at the district level devoted to

capital expenditures and debt service, we could not exclude these funding categories from our

analysis.

Page 99 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix VII 

State Profile: Alabama

Actual Education

Funding Distribution

in School Year 1991-92

As table VII.1 shows, in school year 1991-92, the state provided about

70 percent of the total funding to Alabama’s school districts. Total funding

(state and local funds combined) per weighted pupil in Alabama averaged

$3,277 with an implicit foundation level of $2,287 for each student, which

is about 70 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was .000, indicating that state education

funds were not targeted to poor or wealthy districts.95 (To compare this

score with those of other states, see table V.1 in app. V.) The fiscal

neutrality score was .290, indicating that total funding increased as district

income increased. (To compare this score with those of other states, see

fig. 1.) An Alabama education official reported that the state had changed

its school finance system since school year 1991-92 to increase funding to

poor districts compared with wealthy districts (see app. LVI). To put the

state’s school finance system in perspective, table VII.2 presents

demographic data for school year 1991-92 for five groups of districts of

increasing district income.

Table VII.1: Summary Data for Alabama

in School Year 1991-92

Average total funding per weighted pupila $3,277

State share of total funding (percent) 69.8

Targeting score (state funds)b .000

Implicit foundation levelc $2,287

Equalization effortd 69.8

Fiscal neutrality scoree .290

aThe average is the maximum foundation level possible in a state.

bThis is the constrained score (elasticity of state funding relative to district income) used to

calculate the state’s implicit foundation level. The actual targeting elasticity is .020, which is not

statistically different from 0.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

95This is the constrained targeting score used to calculate the state’s implicit foundation level. This

differs from the actual targeting score found in table V.1 in app. V.

Page 100 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix VII 

State Profile: Alabama

Table VII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 128 48 30 16 15 19

Total pupils 719,789 140,612 149,556 165,837 115,330 148,454

Poverty rate (percent) 23.8 34.1 20.7 27.5 15.2 19.8

Disabled rate (percent) 13.5 12.4 14.1 14.1 14.3 12.8

Per pupil income $63,313 $43,762 $54,973 $61,497 $66,632 $89,685

Tax efforta $15.52 $17.41 $13.56 $13.94 $16.25 $16.76

aLocal funding raised for every $1,000 of district income.

Table VII.3 presents data on how state and local funding was distributed

among the five groups of Alabama districts. Alabama’s equalization

policies reduced the funding disparity between the poor and wealthy

groups from about 93 percent to about 18 percent. Figure VII.1 provides

table information in graphic form.

Table VII.3: State and Local Funding Distribution in Alabama, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State mean Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $989 $766 $746 $868 $1,077 $1,482 1.93

State 2,287 2,447 2,326 2,185 2,208 2,313 0.95

Total $3,277 $3,213 $3,072 $3,053 $3,285 $3,795 1.18

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 101 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix VII 

State Profile: Alabama

Figure VII.1: State and Local Funding

Distribution in Alabama, School Year

1991-92

Local Funding

State Funding

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table VII.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure VII.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure VII.3.

Table VII.4: How State and Local Funding Would Have Been Distributed If Each District in Alabama Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State mean Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $993 $682 $860 $950 $1,048 $1,428 2.09

State 2,284 2,594 2,417 2,327 2,229 1,849 0.71

Totalc $3,277 $3,277 $3,277 $3,277 $3,277 $3,277 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 102 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix VII 

State Profile: Alabama

Figure VII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Alabama Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure VII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Alabama

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Actual State Funding

State Funding if Each Student Received the Average

Page 103 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix VIII 

State Profile: Alaska

Actual Education

Funding Distribution

in School Year 1991-92

As table VIII.1 shows, in school year 1991-92, the state provided about

76 percent of the total funding to Alaska’s school districts. Total funding

(state and local funds combined) per weighted pupil in Alaska averaged

$8,030 with an implicit foundation level of $6,137 for each student, which

is about 76 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was .000, indicating that state education

funds were not targeted to poor or wealthy districts.96 (To compare this

score with those of other states, see table V.1 in app. V.) The fiscal

neutrality score was –.272, indicating that total funding increased as

district income decreased. (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table VIII.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table VIII.1: Summary Data for Alaska

in School Year 1991-92

Average total funding per weighted pupila $8,030

State share of total funding (percent) 76.4

Targeting score (state funds)b .000

Implicit foundation levelc $6,137

Equalization effortd 76.4

Fiscal neutrality scoree –.272

aThe average is the maximum foundation level possible in a state.

bThis is the constrained score (elasticity of state funding relative to district income) used to

calculate the state’s implicit foundation level. The actual targeting elasticity is .068, which is not

statistically different from 0.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

96This is the constrained targeting score used to calculate the state’s implicit foundation level. This

differs from the actual targeting score found in table V.1 in app. V.

Page 104 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix VIII 

State Profile: Alaska

Table VIII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 52 20 12 8 1a 11

Total pupils 117,331 23,505 30,666 8,889 44,749 9,522

Poverty rate (percent) 11.2 21.4 9.2 7.2 9.2 6.0

Disabled rate (percent) 13.5 15.4 13.5 12.2 12.9 13.3

Per pupil income $83,220 $40,791 $75,327 $93,327 $102,123 $115,112

Tax effortb $22.99 $30.25 $34.75 $25.80 $16.00 $19.47

aAnchorage was the only district in this group.

bLocal funding raised for every $1,000 of district income.

Table VIII.3 presents data on how state and local funding was distributed

among the five groups of Alaska districts. Alaska’s equalization policies

essentially eliminated the funding disparity between the poor and wealthy

groups. Figure VIII.1 provides table information in graphic form.

Table VIII.3: State and Local Funding Distribution in Alaska, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,893 $1,279 $2,608 $2,358 $1,617 $2,217 1.73

State 6,137 7,633 6,307 5,239 5,210 6,660 0.87

Total $8,030 $8,912 $8,915 $7,598 $6,828 $8,877 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 105 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix VIII 

State Profile: Alaska

Figure VIII.1: State and Local Funding

Distribution in Alaska, School Year

1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

10,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table VIII.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure VIII.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure VIII.3.

Table VIII.4: How State and Local Funding Would Have Been Distributed If Each District in Alaska Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,906 $907 $1,721 $2,171 2,347 $2,652 2.92

State 6,123 7,123 6,309 5,859 5,683 5,378 0.76

Totalc $8,030 $8,030 $8,030 $8,030 $8,030 $8,030 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 106 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix VIII 

State Profile: Alaska

Figure VIII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Alaska Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

10,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure VIII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Alaska

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 107 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IX 

State Profile: Arizona

Actual Education

Funding Distribution

in School Year 1991-92

As table IX.1 shows, in school year 1991-92, the state provided about

47 percent of the total funding to Arizona’s school districts. Total funding

(state and local funds combined) per weighted pupil in Arizona averaged

$4,507 with an implicit foundation level of $2,598 for each student, which

is about 58 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.232, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .141,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) To put the state’s

school finance system in perspective, table IX.2 presents demographic

data for school year 1991-92 for five groups of districts of increasing

district income.

Table IX.1: Summary Data for Arizona

in School Year 1991-92

Average total funding per weighted pupila $4,507

State share of total funding (percent) 46.8

Targeting score (state funds)b –.232

Implicit foundation levelc $2,598

Equalization effortd 57.7

Fiscal neutrality scoree .141

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 108 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IX 

State Profile: Arizona

Table IX.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 193 78 32 27 17 39

Total pupils 647,354 130,672 122,347 134,103 140,306 119,926

Poverty rate (percent) 21.0 36.6 19.1 15.7 17.7 15.6

Disabled rate (percent) 8.9 9.9 8.9 8.4 9.4 7.9

Per pupil income $98,442 $34,011 $60,599 $74,605 $105,171 $226,036

Tax efforta $24.35 $47.63 $29.86 $31.49 $20.89 $18.56

aLocal funding raised for every $1,000 of district income.

Table IX.3 presents data on how state and local funding was distributed

among the five groups of Arizona districts. Arizona’s equalization policies

reduced the funding disparity between the wealthy and poor groups from

about 144 percent to about 32 percent. Figure IX.1 provides table

information in graphic form.

Table IX.3: State and Local Funding Distribution in Arizona, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,398 $1,681 $1,803 $2,314 $2,197 $4,108 2.44

State 2,109 2,465 2,312 2,205 2,216 1,365 0.55

Total $4,507 $4,146 $4,115 $4,520 $4,413 $5,473 1.32

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 109 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IX 

State Profile: Arizona

Figure IX.1: State and Local Funding

Distribution in Arizona, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table IX.4 provides data on the distribution of state and local funding if all

districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure IX.2 provides

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure IX.3.

Page 110 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IX 

State Profile: Arizona

Table IX.4: How State and Local Funding Would Have Been Distributed If Each District in Arizona Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,424 $805 $1,484 $1,843 $2,561 $5,634 7.00

State 2,083 3,702 3,023 2,664 1,946 –1,127c –0.30

Totald $4,507 $4,507 $4,507 $4,507 $4,507 $4,507 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe state would have had to recapture this amount of local funding from these districts for

distribution to other districts.

dThe average is the maximum foundation level possible in a state.

Figure IX.2: How State and Local

Funding Would Have Been Distributed

If Each District in Arizona Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest (2,000)

(1,000)

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 111 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix IX 

State Profile: Arizona

Figure IX.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Arizona

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest (2,000)

(1,000)

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 112 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix X 

State Profile: Arkansas

Actual Education

Funding Distribution

in School Year 1991-92

As table X.1 shows, in school year 1991-92, the state provided about

65 percent of the total funding to Arkansas’s school districts. Total funding

(state and local funds combined) per weighted pupil in Arkansas averaged

$3,784 with an implicit foundation level of $3,289 for each student, which

is about 87 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.328, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .220,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) To put the state’s

school finance system in perspective, table X.2 presents demographic data

for school year 1991-92 for five groups of districts of increasing district

income.

Table X.1: Summary Data for Arkansas

in School Year 1991-92

Average total funding per weighted pupila $3,784

State share of total funding (percent) 65.4

Targeting score (state funds)b –.328

Implicit foundation levelc $3,289

Equalization effortd 86.9

Fiscal neutrality scoree .220

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 113 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix X 

State Profile: Arkansas

Table X.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 316 105 69 75 39 28

Total pupils 430,420 86,533 84,141 86,293 86,708 86,745

Poverty rate (percent) 24.6 33.8 26 24.3 17.8 21.1

Disabled rate (percent) 9.7 10.6 9.8 10.1 9.2 9.0

Per pupil income $55,895 $36,020 $45,048 $51,705 $61,445 $84,862

Tax efforta $23.40 $26.81 $22.31 $20.85 $22.45 $25.04

aLocal funding raised for every $1,000 of district income.

Table X.3 presents data on how state and local funding was distributed

among the five groups of Arkansas districts. Arkansas’ equalization

policies reduced the funding disparity between the wealthy and poor

groups from about 111 percent to about 14 percent. Figure X.1 provides

table information in graphic form.

Table X.3: State and Local Funding Distribution in Arkansas, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,308 $990 $1,008 $1,082 $1,355 $2,094 2.11

State 2,476 2,756 2,594 2,531 2,362 2,188 0.79

Total $3,784 $3,747 $3,602 $3,613 $3,717 $4,282 1.14

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 114 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix X 

State Profile: Arkansas

Figure X.1: State and Local Funding

Distribution in Arkansas, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table X.4 provides data on the distribution of state and local funding if all

districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure X.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure X.3.

Table X.4: How State and Local Funding Would Have Been Distributed If Each District in Arkansas Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,315 $824 $1,052 $1,207 $1,465 $2,020 2.45

State 2,469 2,960 2,732 2,577 2,319 1,764 0.60

Totalc $3,784 $3,784 $3,784 $3,784 $3,784 $3,784 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 115 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix X 

State Profile: Arkansas

Figure X.2: How State and Local

Funding Would Have Been Distributed

If Each District in Arkansas Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure X.3: Comparison of Actual State

Funding With State Funding Assuming

Each District in Arkansas Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 116 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XI 

State Profile: California

Actual Education

Funding Distribution

in School Year 1991-92

As table XI.1 shows, in school year 1991-92, the state provided about

69 percent of the total funding to California’s school districts. Total

funding (state and local funds combined) per weighted pupil in California

averaged $4,543 with an implicit foundation level of $3,504 for each

student, which is about 77 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.119,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .073, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table XI.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table XI.1: Summary Data for

California in School Year 1991-92

Average total funding per weighted pupila $4,543

State share of total funding (percent) 68.9

Targeting score (state funds)b –.119

Implicit foundation levelc $3,504

Equalization effortd 77.1

Fiscal neutrality scoree .073

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 117 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XI 

State Profile: California

Table XI.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 971 263 192 69 144 303

Total pupils 4,978,164 995,837 996,457 996,425 996,127 993,318

Poverty rate (percent) 18.4 26.1 17.1 23.7 14.0 11.2

Disabled rate (percent) 8.8 8.2 8.8 9.0 9.2 8.7

Per pupil income $121,872 $49,081 $76,553 $95,830 $122,991 $265,332

Tax efforta $11.79 $18.65 $15.48 $9.97 $13.60 $9.35

aLocal funding raised for every $1,000 of district income.

Table XI.3 presents data on how state and local funding was distributed

among the five groups of California districts. California’s equalization

policies reduced the funding disparity between the wealthy and poor

groups from about 166 percent to about 13 percent. Figure XI.1 provides

table information in graphic form.

Table XI.3: State and Local Funding Distribution in California, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,411 $921 $1,182 $967 $1,668 $2,448 2.66

State 3,131 3,486 3,221 3,525 2,906 2,518 0.72

Total $4,543 $4,407 $4,404 $4,492 $4,574 $4,965 1.13

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 118 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XI 

State Profile: California

Figure XI.1: State and Local Funding

Distribution in California, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XI.4 provides data on the distribution of state and local funding if all

districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XI.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XI.3.

Table XI.4: How State and Local Funding Would Have Been Distributed If Each District in California Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,421 $564 $889 $1,098 $1,430 $3,312 5.56

State 3,121 3,979 3,654 3,445 3,113 1,411 0.35

Totalc $4,543 $4,543 $4,543 $4,543 $4,543 $4,543 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 119 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XI 

State Profile: California

Figure XI.2: How State and Local

Funding Would Have Been Distributed

If Each District in California Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XI.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in California

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 120 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XII 

State Profile: Colorado

Actual Education

Funding Distribution

in School Year 1991-92

As table XII.1 shows, in school year 1991-92, the state provided about

44 percent of the total funding to Colorado’s school districts. Total funding

(state and local funds combined) per weighted pupil in Colorado averaged

$5,047 with an implicit foundation level of $3,847 for each student, which

is about 76 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.753, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .154,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) A Colorado

education official reported that the state had changed its school finance

system since school year 1991-92 to increase funding to poor districts

compared with wealthy districts (see app. LVI). To put the state’s school

finance system in perspective, table XII.2 presents demographic data for

school year 1991-92 for five groups of districts of increasing district

income.

Table XII.1: Summary Data for

Colorado in School Year 1991-92

Average total funding per weighted pupila $5,047

State share of total funding (percent) 43.5

Targeting score (state funds)b –.753

Implicit foundation levelc $3,847

Equalization effortd 76.2

Fiscal neutrality scoree .154

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 121 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XII 

State Profile: Colorado

Table XII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 174 101 31 23 8 11

Total pupils 592,435 118,643 111,334 134,003 118,013 110,442

Poverty rate (percent) 14.8 20.8 17.4 11.3 6.7 18.7

Disabled rate (percent) 9.6 9.7 11.0 8.9 8.5 10.1

Per pupil income $81,879 $51,188 $65,989 $78,606 $96,107 $119,635

Tax efforta $34.97 $47.93 $31.11 $36.25 $31.40 $33.29

aLocal funding raised for every $1,000 of district income.

Table XII.3 presents data on how state and local funding was distributed

among the five groups of Colorado districts. Colorado’s equalization

policies reduced the funding disparity between the wealthy and poor

groups from about 63 percent to about 8 percent. Figure XII.1 provides

table information in graphic form.

Table XII.3: State and Local Funding Distribution in Colorado, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,853 $2,481 $2,095 $2,810 $2,939 $4,031 1.63

State 2,194 2,629 2,700 2,120 2,127 1,470 0.56

Total $5,047 $5,109 $4,794 $4,930 $5,066 $5,501 1.08

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 122 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XII 

State Profile: Colorado

Figure XII.1: State and Local Funding

Distribution in Colorado, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XII.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XII.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XII.3.

Table XII.4: How State and Local Funding Would Have Been Distributed If Each District in Colorado Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,861 $1,768 $2,260 $2,776 $3,439 $4,127 2.33

State 2,186 3,279 2,787 2,271 1,608 921 0.28

Totalc $5,047 $5,047 $5,047 $5,047 $5,047 $5,047 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 123 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XII 

State Profile: Colorado

Figure XII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Colorado Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Colorado

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 124 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XIII 

State Profile: Connecticut

Actual Education

Funding Distribution

in School Year 1991-92

As table XIII.1 shows, in school year 1991-92, the state provided about

39 percent of the total funding to Connecticut’s school districts. Total

funding (state and local funds combined) per weighted pupil in

Connecticut averaged $8,221 with an implicit foundation level of $4,556 for

each student, which is about 55 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.430,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .241, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) A Connecticut education official reported that the state

had changed its school finance system since school year 1991-92 to

increase funding to poor districts compared with wealthy districts (see

app. LVI). To put the state’s school finance system in perspective, table

XIII.2 presents demographic data for school year 1991-92 for five groups of

districts of increasing district income.

Table XIII.1: Summary Data for

Connecticut in School Year 1991-92

Average total funding per weighted pupila $8,221

State share of total funding (percent) 38.8

Targeting score (state funds)b –.430

Implicit foundation levelc $4,556

Equalization effortd 55.4

Fiscal neutrality scoree .241

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 125 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XIII 

State Profile: Connecticut

Table XIII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 159 16 27 28 42 46

Total pupils 462,403 92,149 92,783 91,748 92,447 93,276

Poverty rate (percent) 10.4 27.7 7.8 7.6 4.0 5.0

Disabled rate (percent) 12.8 13.7 13.4 12.0 12.8 12.0

Per pupil income $148,273 $82,380 $114,150 $130,956 $155,668 $257,018

Tax efforta $34.29 $29.69 $32.40 $35.61 $39.26 $33.59

aLocal funding raised for every $1,000 of district income.

Table XIII.3 presents data on how state and local funding was distributed

among the five groups of Connecticut districts. Connecticut’s equalization

policies reduced the funding disparity between the wealthy and poor

groups from 234 percent to about 34 percent. Figure XIII.1 provides table

information in graphic form.

Table XIII.3: State and Local Funding Distribution in Connecticut, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $5,035 $2,540 $3,707 $4,602 $6,047 $8,486 3.34

State 3,186 4,885 3,739 3,367 2,388 1,500 0.31

Total $8,221 $7,426 $7,446 $7,969 $8,435 $9,985 1.34

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 126 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XIII 

State Profile: Connecticut

Figure XIII.1: State and Local Funding

Distribution in Connecticut, School

Year 1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

10,000

12,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XIII.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XIII.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XIII.3.

Page 127 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XIII 

State Profile: Connecticut

Table XIII.4: How State and Local Funding Would Have Been Distributed If Each District in Connecticut Could Have Spent

the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $5,072 $2,710 $3,870 $4,510 $5,347 $8,880 3.28

State 3,149 5,511 4,351 3,711 2,874 –659c –0.12

Totald $8,221 $8,221 $8,221 $8,221 $8,221 $8,221 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe state would have had to recapture this amount of local funding from these districts for

distribution to other districts.

dThe average is the maximum foundation level possible in a state.

Figure XIII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Connecticut Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest (2,000)

0

2,000

4,000

6,000

8,000

10,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 128 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XIII 

State Profile: Connecticut

Figure XIII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Connecticut

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest (1,000)

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 129 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XIV 

State Profile: Delaware

Actual Education

Funding Distribution

in School Year 1991-92

As table XIV.1 shows, in school year 1991-92, the state provided about

70 percent of the total funding to Delaware’s school districts. Total funding

(state and local funds combined) per weighted pupil in Delaware averaged

$5,576 with an implicit foundation level of $4,190 for each student, which

is about 75 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.070, indicating that state education

funds were targeted to poor districts.97 (To compare this score with those

of other states, see table V.1 in app. V.) The fiscal neutrality score was

.072, indicating that total funding increased as district income increased.98

(To compare this score with those of other states, see fig. 1.) To put the

state’s school finance system in perspective, table XIV.2 presents

demographic data for school year 1991-92 for five groups of districts of

increasing district income.

Table XIV.1: Summary Data for

Delaware in School Year 1991-92

Average total funding per weighted pupila $5,576

State share of total funding (percent) 70.2

Targeting score (state funds)b –.070

Implicit foundation levelc $4,190

Equalization effortd 75.1

Fiscal neutrality scoree .072

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income. The score is not significantly

different from 0.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income. The score is not

significantly different from 0.

97However, this score is not significantly different from 0.

98See footnote 97.

Page 130 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XIV 

State Profile: Delaware

Table XIV.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 16 5 5 3 2 1a

Total pupils 97,986 17,221 22,073 14,423 29,809 14,460

Poverty rate (percent) 12.2 16.5 15.2 10.4 10.0 9.2

Disabled rate (percent) 10.6 10.5 11.5 11.0 10.4 9.6

Per pupil income $106,718 $64,681 $77,905 $89,875 $125,350 $179,156

Tax effortb $15.44 $12.92 $14.95 $19.33 $17.42 $12.21

aWilmington was the only district in this group.

bLocal funding raised for every $1,000 of district income.

Table XIV.3 presents data on how state and local funding was distributed

among the five groups of Delaware districts. Delaware’s equalization

policies reduced the funding disparity between the wealthy and poor

groups from about 156 percent to about 9 percent. Figure XIV.1 provides

table information in graphic form.

Table XIV.3: State and Local Funding Distribution in Delaware, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,660 $840 $1,182 $1,739 $2,170 $2,149 2.56

State 3,916 4,476 4,022 3,773 3,732 3,668 0.82

Total $5,576 $5,316 $5,204 $5,512 $5,903 $5,817 1.09

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 131 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XIV 

State Profile: Delaware

Figure XIV.1: State and Local Funding

Distribution in Delaware, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XIV.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XIV.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XIV.3.

Table XIV.4: How State and Local Funding Would Have Been Distributed If Each District in Delaware Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,668 $1,001 $1,197 $1,397 $1,966 $2,835 2.83

State 3,908 4,575 4,379 4,179 3,610 2,741 0.60

Totalc $5,576 $5,576 $5,576 $5,576 $5,576 $5,576 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 132 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XIV 

State Profile: Delaware

Figure XIV.2: How State and Local

Funding Would Have Been Distributed

If Each District in Delaware Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XIV.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Delaware

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 133 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XV 

State Profile: Florida

Actual Education

Funding Distribution

in School Year 1991-92

As table XV.1 shows, in school year 1991-92, the state provided 53 percent

of the total funding to Florida’s school districts. Total funding (state and

local funds combined) per weighted pupil in Florida averaged $5,555 with

an implicit foundation level of $4,759 for each student, which is about

86 percent of the average and represents the state’s equalization effort. (To

compare this effort with those of other states, see fig. 5.) The targeting

score for state funding was –.615, indicating that state education funds

were targeted to poor districts. (To compare this score with those of other

states, see table V.1 in app. V.) The fiscal neutrality score was .239,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) To put the state’s

school finance system in perspective, table XV.2 presents demographic

data for school year 1991-92 for five groups of districts of increasing

district income.

Table XV.1: Summary Data for Florida

in School Year 1991-92

Average total funding per weighted pupila $5,555

State share of total funding (percent) 53.0

Targeting score (state funds)b –.615

Implicit foundation levelc $4,759

Equalization effortd 85.7

Fiscal neutrality scoree .239

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 134 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XV 

State Profile: Florida

Table XV.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 67 38 3 7 10 9

Total pupils 1,929,239 380,985 433,922 350,723 415,513 348,096

Poverty rate (percent) 18.6 21.9 22.6 18.5 14.7 14.9

Disabled rate (percent) 11.9 12.1 10.9 12.0 11.8 13.2

Per pupil income $98,373 $67,959 $81,583 $90,995 $109,511 $146,728

Tax efforta $26.48 $22.60 $25.31 $27.03 $25.93 $29.37

aLocal funding raised for every $1,000 of district income.

Table XV.3 presents data on how state and local funding was distributed

among the five groups of Florida districts. Florida’s equalization policies

reduced the funding disparity between the wealthy and poor groups from

about 181 percent to about 18 percent. Figure XV.1 provides table

information in graphic form.

Table XV.3: State and Local Funding Distribution in Florida, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,609 $1,546 $2,057 $2,461 $2,815 $4,341 2.81

State 2,946 3,740 3,183 2,979 2,849 1,922 .51

Total $5,555 $5,286 $5,239 $5,440 $5,664 $6,264 1.18

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 135 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XV 

State Profile: Florida

Figure XV.1: State and Local Funding

Distribution in Florida, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XV.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XV.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XV.3.

Table XV.4: How State and Local Funding Would Have Been Distributed If Each District in Florida Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,610 $1,793 $2,174 $2,413 $2,931 $3,861 2.15

State 2,946 3,762 3,382 3,143 2,624 1,694 0.45

Totalc $5,555 $5,556 $5,556 $5,556 $5,556 $5,556 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 136 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XV 

State Profile: Florida

Figure XV.2: How State and Local

Funding Would Have Been Distributed

If Each District in Florida Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XV.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Florida

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 137 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XVI 

State Profile: Georgia

Actual Education

Funding Distribution

in School Year 1991-92

As table XVI.1 shows, in school year 1991-92, the state provided about

55 percent of the total funding to Georgia’s school districts. Total funding

(state and local funds combined) per weighted pupil in Georgia averaged

$4,324 with an implicit foundation level of $2,932 for each student, which

is about 68 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.242, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .323,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) To put the state’s

school finance system in perspective, table XVI.2 presents demographic

data for school year 1991-92 for five groups of districts of increasing

district income.

Table XVI.1: Summary Data for Georgia

in School Year 1991-92

Average total funding per weighted pupila $4,324

State share of total funding (percent) 54.6

Targeting score (state funds)b –.242

Implicit foundation levelc $2,932

Equalization effortd 67.8

Fiscal neutrality scoree .323

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 138 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XVI 

State Profile: Georgia

Table XVI.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 183 75 56 20 19 13

Total pupils 1,177,358 234,753 227,823 244,138 252,333 218,311

Poverty rate (percent) 19.6 27.5 21.8 16.1 21.1 11.3

Disabled rate (percent) 9.0 9.4 10.1 8.7 8.1 8.9

Per pupil income $73,340 $45,588 $60,087 $68,588 $84,522 $109,402

Tax efforta $26.23 $23.12 $20.65 $28.29 $27.39 $28.83

aLocal funding raised for every $1,000 of district income.

Table XVI.3 presents data on how state and local funding was distributed

among the five groups of Georgia districts. Georgia’s equalization policies

reduced the funding disparity between the wealthy and poor groups from

about 189 percent to about 30 percent. Figure XVI.1 provides table

information in graphic form.

Table XVI.3: State and Local Funding Distribution in Georgia, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,962 $1,073 $1,261 $1,921 $2,296 $3,104 2.89

State 2,361 2,794 2,664 2,391 2,166 1,924 0.69

Total $4,324 $3,867 $3,924 $4,312 $4,462 $5,029 1.30

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 139 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XVI 

State Profile: Georgia

Figure XVI.1: State and Local Funding

Distribution in Georgia, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XVI.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XVI.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XVI.3.

Table XVI.4: How State and Local Funding Would Have Been Distributed If Each District in Georgia Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,970 $1,198 $1,584 $1,854 $2,280 $2,974 2.48

State 2,354 3,126 2,740 2,469 2,044 1,350 0.43

Totalc $4,324 $4,324 $4,324 $4,324 $4,324 $4,324 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 140 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XVI 

State Profile: Georgia

Figure XVI.2: How State and Local

Funding Would Have Been Distributed

If Each District in Georgia Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding Per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XVI.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Georgia

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 141 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XVII 

State Profile: Idaho

Actual Education

Funding Distribution

in School Year 1991-92

As table XVII.1 shows, in school year 1991-92, the state provided about

67 percent of the total funding to Idaho’s school districts. Total funding

(state and local funds combined) per weighted pupil in Idaho averaged

$3,504 with an implicit foundation level of $2,654 for each student, which

is about 76 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.130, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .247,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) An Idaho

education official reported that the state had changed its school finance

system since school year 1991-92 to increase funding to poor districts

compared with wealthy districts (see app. LVI). To put the state’s school

finance system in perspective, table XVII.2 presents demographic data for

school year 1991-92 for five groups of districts of increasing district

income.

Table XVII.1: Summary Data for Idaho

in School Year 1991-92

Average total funding per weighted pupila $3,504

State share of total funding (percent) 67.1

Targeting score (state funds)b –.130

Implicit foundation levelc $2,654

Equalization effortd 75.7

Fiscal neutrality scoree .247

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 142 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XVII 

State Profile: Idaho

Table XVII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 108 30 29 11 26 12

Total pupils 216,503 45,299 41,300 44,163 42,438 43,303

Poverty rate (percent) 15.8 16.1 19.1 16.0 14.2 13.5

Disabled rate (percent) 10.4 9.8 10.9 10.5 10.3 10.7

Per pupil income $51,724 $30,589 $41,813 $50,172 $54,189 $82,453

Tax efforta $22.34 $24.35 $21.51 $20.98 $19.18 $24.86

aLocal funding raised for every $1,000 of district income.

Table XVII.3 presents data on how state and local funding was distributed

among the five groups of Idaho districts. Idaho’s equalization policies

reduced the funding disparity between the wealthy and poor groups from

about 177 percent to about 26 percent. Figure XVII.1 provides table

information in graphic form.

Table XVII.3: State and Local Funding Distribution in Idaho, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Wealth funding

compared with

poor fundinga

Local $1,155 $740 $910 $1,054 $1,034 $2,048 2.77

State 2,350 2,506 2,485 2,327 2,467 2,027 0.81

Total $3,504 $3,246 $3,395 $3,381 $3,501 $4,075 1.26

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 143 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XVII 

State Profile: Idaho

Figure XVII.1: State and Local Funding

Distribution in Idaho, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XVII.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XVII.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XVII.3.

Table XVII.4: How State and Local Funding Would Have Been Distributed If Each District in Idaho Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,155 $687 $923 $1,119 $1,215 $1,842 2.68

State 2,349 2,817 2,581 2,385 2,289 1,662 0.59

Totalc $3,504 $3,504 $3,504 $3,504 $3,504 $3,504 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 144 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XVII 

State Profile: Idaho

Figure XVII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Idaho Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XVII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Idaho Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 145 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XVIII 

State Profile: Illinois

Actual Education

Funding Distribution

in School Year 1991-92

As table XVIII.1 shows, in school year 1991-92, the state provided about

33 percent of the total funding to Illinois’ school districts. Total funding

(state and local funds combined) per weighted pupil in Illinois averaged

$4,970 with an implicit foundation level of $2,031 for each student, which

is about 41 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.230, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .338,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) To put the state’s

school finance system in perspective, table XVIII.2 presents demographic

data for school year 1991-92 for five groups of districts of increasing

district income.

Table XVIII.1: Summary Data for Illinois

in School Year 1991-92

Average total funding per weighted pupila $4,970

State share of total funding (percent) 33.2

Targeting score (state funds)b –.230

Implicit foundation levelc $2,031

Equalization effortd 40.9

Fiscal neutrality scoree .338

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 146 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XVIII 

State Profile: Illinois

Table XVIII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 934 256 16 219 211 232

Total pupils 1,821,061 301,035 426,836 361,247 367,907 364,036

Poverty rate (percent) 16.4 18.8 32.9 13.0 9.2 6.0

Disabled rate (percent) 13.0 14.1 11.0 13.8 14.1 12.7

Per pupil income $134,121 $66,174 $78,601 $90,547 $124,521 $308,349

Tax efforta $24.39 $29.09 $29.91 $27.57 $26.55 $20.38

aLocal funding raised for every $1,000 of district income.

Table XVIII.3 presents data on how state and local funding was distributed

among the five groups of Illinois districts. Illinois’s equalization policies

reduced the funding disparity between the wealthy and poor groups from

about 215 percent to about 67 percent. Figure XVIII.1 provides table

information in graphic form.

Table XVIII.3: State and Local Funding Distribution in Illinois, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $3,318 $1,955 $2,363 $2,504 $3,304 $6,153 3.15

State 1,652 2,375 1,867 1,881 1,331 1,097 0.46

Total $4,970 $4,330 $4,230 $4,384 $4,635 $7,249 1.67

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 147 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XVIII 

State Profile: Illinois

Figure XVIII.1: State and Local Funding

Distribution in Illinois, School Year

1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XVIII.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XVIII.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XVIII.3.

Page 148 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XVIII 

State Profile: Illinois

Table XVIII.4: How State and Local Funding Would Have Been Distributed If Each District in Illinois Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $3,358 $1,616 $1,935 $2,236 $3,088 $7,852 4.86

State 1,612 3,354 3,035 2,734 1,882 –2,882c –0.86

Totald $4,970 $4,970 $4,970 $4,970 $4,970 $4,970 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe state would have had to recapture this amount of local funding from these districts for

distribution to other districts.

dThe average is the maximum foundation level possible in a state.

Figure XVIII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Illinois Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest (4,000)

(2,000)

0

2,000

4,000

6,000

8,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 149 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XVIII 

State Profile: Illinois

Figure XVIII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Illinois

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest (3,000)

(2,000)

(1,000)

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 150 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XIX 

State Profile: Indiana

Actual Education

Funding Distribution

in School Year 1991-92

As table XIX.1 shows, in school year 1991-92, the state provided about

54 percent of the total funding to Indiana’s school districts. Total funding

(state and local funds combined) per weighted pupil in Indiana averaged

$4,993 with an implicit foundation level of $2,970 for each student, which

is about 60 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.099, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .153,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) An Indiana

education official reported that the state had changed its school finance

system since school year 1991-92 to increase funding to poor districts

compared with wealthy districts (see app. LVI). To put the state’s school

finance system in perspective, table XIX.2 presents demographic data for

school year 1991-92 for five groups of districts of increasing district

income.

Table XIX.1: Summary Data for Indiana

in School Year 1991-92

Average total funding per weighted pupila $4,993

State share of total funding (percent) 54.1

Targeting score (state funds)b –.099

Implicit foundation levelc $2,970

Equalization effortd 59.5

Fiscal neutrality scoree .153

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 151 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XIX 

State Profile: Indiana

Table XIX.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 294 90 74 66 33 31

Total pupils 952,639 191,981 190,297 182,032 196,761 191,568

Poverty rate (percent) 13.5 17.8 11.1 11.2 16.1 10.8

Disabled rate (percent) 11.6 11.9 11.4 11.6 12.2 11.0

Per pupil income $76,049 $52,389 $65,870 $74,174 $81,358 $106,199

Tax efforta $30.13 $37.13 $31.81 $32.04 $27.87 $26.22

aLocal funding raised for every $1,000 of district income.

Table XIX.3 presents data on how state and local funding was distributed

among the five groups of Indiana districts. Indiana’s equalization policies

reduced the funding disparity between the wealthy and poor groups from

about 40 percent to about 10 percent. Figure XIX.1 provides table

information in graphic form.

Table XIX.3: State and Local Funding Distribution in Indiana, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,290 $1,966 $2,082 $2,367 $2,293 $2,751 1.40

State 2,703 2,838 2,740 2,649 2,749 2,548 0.90

Total $4,993 $4,804 $4,822 $5,015 $5,042 $5,299 1.10

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 152 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XIX 

State Profile: Indiana

Figure XIX.1: State and Local Funding

Distribution in Indiana, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XIX.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XIX.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XIX.3.

Table XIX.4: How State and Local Funding Would Have Been Distributed If Each District in Indiana Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,297 $1,565 $1,998 $2,244 $2,427 $3,247 2.07

State 2,695 3,428 2,995 2,748 2,565 1,746 0.51

Totalc $4,993 $4,993 $4,993 $4,993 $4,993 $4,993 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 153 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XIX 

State Profile: Indiana

Figure XIX.2: How State and Local

Funding Would Have Been Distributed

If Each District in Indiana Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XIX.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Indiana

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 154 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XX 

State Profile: Iowa

Actual Education

Funding Distribution

in School Year 1991-92

As table XX.1 shows, in school year 1991-92, the state provided 49 percent

of the total funding to Iowa’s school districts. Total funding (state and

local funds combined) per weighted pupil in Iowa averaged $4,849 with an

implicit foundation level of $2,622 for each student, which is about

54 percent of the average and represents the state’s equalization effort. (To

compare this effort with those of other states, see fig. 5.) The targeting

score for state funding was –.104, indicating that state education funds

were targeted to poor districts. (To compare this score with those of other

states, see table V.1 in app. V.) The fiscal neutrality score was .031,

indicating that total funding increased as district income increased.99 (To

compare this score with those of other states, see fig. 1.) To put the state’s

school finance system in perspective, table XX.2 presents demographic

data for school year 1991-92 for five groups of districts of increasing

district income.

Table XX.1: Summary Data for Iowa in

School Year 1991-92

Average total funding per weighted pupila $4,849

State share of total funding (percent) 49.0

Targeting score (state funds)b –.104

Implicit foundation levelc $2,622

Equalization effortd 54.1

Fiscal neutrality scoree .031

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income. The score is not

significantly different from 0.

99However, this score is not significantly different from 0.

Page 155 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XX 

State Profile: Iowa

Table XX.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 419 144 95 59 75 46

Total pupils 487,004 96,685 98,192 96,775 92,677 102,675

Poverty rate (percent) 13.8 14.2 13.3 16.3 11.9 13.1

Disabled rate (percent) 12.6 11.5 12.1 12.8 13.2 13.3

Per pupil income $69,690 $51,544 $60,642 $66,301 $75,108 $93,734

Tax efforta $35.87 $51.39 $40.36 $33.60 $35.00 $27.22

aLocal funding raised for every $1,000 of district income.

Table XX.3 presents data on how state and local funding was distributed

among the five groups of Iowa districts. Iowa’s equalization policies

increased the funding that poor districts had compared with wealthy

districts from 2 percent to about 4 percent. Figure XX.1 provides table

information in graphic form.

Table XX.3: State and Local Funding Distribution in Iowa, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,474 $2,621 $2,432 $2,244 $2,637 $2,568 0.98

State 2,375 2,431 2,435 2,399 2,357 2,287 0.94

Total $4,849 $5,051 $4,867 $4,643 $4,994 $4,855 0.96

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 156 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XX 

State Profile: Iowa

Figure XX.1: State and Local Funding

Distribution in Iowa, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XX.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XX.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XX.3.

Table XX.4: How State and Local Funding Would Have Been Distributed If Each District in Iowa Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,476 $1,851 $2,168 $2,338 $2,663 $3,319 1.79

State 2,373 2,998 2,681 2,511 2,186 1,530 0.51

Totalc $4,849 $4,849 $4,849 $4,849 $4,849 $4,849 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 157 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XX 

State Profile: Iowa

Figure XX.2: How State and Local

Funding Would Have Been Distributed

If Each District in Iowa Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XX.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Iowa Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 158 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXI 

State Profile: Kansas

Actual Education

Funding Distribution

in School Year 1991-92

As table XXI.1 shows, in school year 1991-92, the state provided about

44 percent of the total funding to Kansas’ school districts. Total funding

(state and local funds combined) per weighted pupil in Kansas averaged

$4,973 with an implicit foundation level of $2,706 for each student, which

is about 54 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.241, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .014,

indicating that total funding increased as district income increased.100 (To

compare this score with those of other states, see fig. 1.) A Kansas

education official reported that the state had changed its school finance

system since school year 1991-92 to increase funding to poor districts

compared with wealthy districts (see app. LVI). To put the state’s school

finance system in perspective, table XXI.2 presents demographic data for

school year 1991-92 for five groups of districts of increasing district

income.

Table XXI.1: Summary Data for Kansas

in School Year 1991-92

Average total funding per weighted pupila $4,973

State share of total funding (percent) 43.8

Targeting score (state funds)b –.241

Implicit foundation levelc $2,706

Equalization effortd 54.4

Fiscal neutrality scoree .014

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income. The score is not

significantly different from 0.

100However, this score is not significantly different from 0.

Page 159 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXI 

State Profile: Kansas

Table XXI.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 304 69 100 70 57 8

Total pupils 437,033 87,100 86,292 89,096 85,852 88,693

Poverty rate (percent) 13.8 18.7 12.3 12.6 13.8 11.5

Disabled rate (percent) 10.2 10.2 9.6 10.3 11.4 9.7

Per pupil income $74,725 $51,423 $60,923 $69,640 $81,926 $109,173

Tax efforta $37.62 $40.78 $43.96 $41.04 $34.52 $32.90

aLocal funding raised for every $1,000 of district income.

Table XXI.3 presents data on how state and local funding was distributed

among the five groups of Kansas districts. Kansas’ equalization policies

reduced the funding disparity between the wealthy and poor groups from

about 68 percent to about 9 percent. Figure XXI.1 provides table

information in graphic form.

Table XXI.3: State and Local Funding Distribution in Kansas, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,793 $2,113 $2,652 $2,855 $2,867 $3,555 1.68

State 2,181 2,534 2,630 2,375 2,103 1,534 0.61

Total $4,973 $4,648 $5,282 $5,230 $4,969 $5,089 1.09

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 160 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXI 

State Profile: Kansas

Figure XXI.1: State and Local Funding

Distribution in Kansas, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXI.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XXI.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XXI.3.

Table XXI.4: How State and Local Funding Would Have Been Distributed If Each District in Kansas Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,798 $1907 $2,302 $2,607 $3,023 $4,129 2.17

State 2,176 3,066 2,672 2,366 1,951 845 0.28

Totalc $4,973 $4,973 $4,973 $4,973 $4,973 $4,973 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 161 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXI 

State Profile: Kansas

Figure XXI.2: How State and Local

Funding Would Have Been Distributed

If Each District in Kansas Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XXI.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Kansas

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 162 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXII 

State Profile: Kentucky

Actual Education

Funding Distribution

in School Year 1991-92

As table XXII.1 shows, in school year 1991-92, the state provided

70 percent of the total funding to Kentucky’s school districts. Total

funding (state and local funds combined) per weighted pupil in Kentucky

averaged $3,728 with an implicit foundation level of $3,232 for each

student, which is about 87 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.239,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .126, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table XXII.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table XXII.1: Summary Data for

Kentucky in School Year 1991-92

Average total funding per weighted pupila $3,728

State share of total funding (percent) 70.0

Targeting score (state funds)b –.239

Implicit foundation levelc $3,232

Equalization effortd 86.7

Fiscal neutrality scoree .126

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 163 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXII 

State Profile: Kentucky

Table XXII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 175 43 52 38 37 5

Total pupils 633,901 126,077 127,755 124,667 127,649 127,753

Poverty rate (percent) 25.1 40.9 26.5 21.2 17.7 19.4

Disabled rate (percent) 12.4 12.9 12.4 12.1 12.1 12.7

Per pupil income $63,691 $36,511 $49,602 $60,505 $73,669 $97,742

Tax efforta $17.42 $14.04 $16.06 $16.01 $16.95 $20.80

aLocal funding raised for every $1,000 of district income.

Table XXII.3 presents data on how state and local funding was distributed

among the five groups of Kentucky districts. Kentucky’s equalization

policies reduced the funding disparity between the wealthy and poor

groups from about 283 percent to about 15 percent. Figure XXII.1 provides

table information in graphic form.

Table XXII.3: State and Local Funding Distribution in Kentucky, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,119 $528 $798 $959 $1,229 $2,020 3.83

State 2,609 3,072 2,846 2,660 2,414 2,123 0.69

Total $3,728 $3,601 $3,644 $3,618 $3,644 $4,143 1.15

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 164 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXII 

State Profile: Kentucky

Figure XXII.1: State and Local Funding

Distribution in Kentucky, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXII.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XXII.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XXII.3.

Table XXII.4: How State and Local Funding Would Have Been Distributed If Each District in Kentucky Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,126 $626 $871 $1,076 $1,318 $1,730 2.76

State 2,603 3,103 2,858 2,653 2,410 1,999 0.64

Totalc $3,728 $3,728 $3,728 $3,728 $3,728 $3,728 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 165 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXII 

State Profile: Kentucky

Figure XXII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Kentucky Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XXII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Kentucky

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 166 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXIII 

State Profile: Louisiana

Actual Education

Funding Distribution

in School Year 1991-92

As table XXIII.1 shows, in school year 1991-92, the state provided about

62 percent of the total funding to Louisiana’s school districts. Total

funding (state and local funds combined) per weighted pupil in Louisiana

averaged $3,912 with an implicit foundation level of $2,433 for each

student, which is about 62 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was .000, indicating

that state education funds were not targeted to poor or wealthy districts.101

 (To compare this score with those of other states, see table V.1 in app. V.)

The fiscal neutrality score was .216, indicating that total funding increased

as district income increased. (To compare this score with those of other

states, see fig. 1.) A Louisiana education official reported that the state had

changed its school finance system since school year 1991-92 to increase

funding to poor districts compared with wealthy districts (see app. LVI).

To put the state’s school finance system in perspective, table XXIII.2

presents demographic data for school year 1991-92 for five groups of

districts of increasing district income.

Table XXIII.1: Summary Data for

Louisiana in School Year 1991-92

Average total funding per weighted pupila $3,912

State share of total funding (percent) 62.2

Targeting score (state funds)b .000

Implicit foundation levelc $2,433

Equalization effortd 62.2

Fiscal neutrality scoree .216

aThe average is the maximum foundation level possible in a state.

bThis is the constrained score (elasticity of state funding relative to district income) used to

calculate the state’s implicit foundation level. The actual targeting elasticity is .150.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

101This is the constrained targeting score used to calculate the state’s implicit foundation level. This

differs from the actual targeting score found in table V.1 in app. V.

Page 167 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXIII 

State Profile: Louisiana

Table XXIII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 65 24 23 10 5 3

Total pupils 753,188 149,900 153,216 150,781 175,284 124,007

Poverty rate (percent) 31.8 37.3 34.4 29.4 33.0 22.9

Disabled rate (percent) 10.7 10.6 11.5 10.0 9.9 11.6

Per pupil income $58,920 $39,718 $45,820 $55,695 $67,411 $90,238

Tax efforta $25.11 $23.86 $27.49 $27.21 $28.66 $19.12

aLocal funding raised for every $1,000 of district income.

Table XXIII.3 presents data on how state and local funding was distributed

among the five groups Louisiana districts. Louisiana’s equalization policies

reduced the funding disparity between the wealthy and poor groups from

about 80 percent to about 21 percent. Figure XXIII.1 provides table

information in graphic form.

Table XXIII.3: State and Local Funding Distribution in Louisiana, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,480 $956 $1,277 $1,499 $1,919 $1,717 1.80

State 2,433 2,551 2,395 2,489 2,271 2,521 .99

Total $3,912 $3,507 $3,672 $3,988 $4,190 $4,238 1.21

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 168 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXIII 

State Profile: Louisiana

Figure XXIII.1: State and Local Funding

Distribution in Louisiana, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXIII.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XXIII.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XXIII.3.

Table XXIII.4: How State and Local Funding Would Have Been Distributed If Each District in Louisiana Could Have Spent

the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,483 $991 $1,137 $1,415 $1,704 $2,276 2.30

State 2,429 2,922 2,775 2,497 2,208 1,637 0.56

Totalc $3,912 $3,912 $3,912 $3,912 $3,912 $3,912 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 169 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXIII 

State Profile: Louisiana

Figure XXIII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Louisiana Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XXIII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Louisiana

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 170 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXIV 

State Profile: Maine

Actual Education

Funding Distribution

in School Year 1991-92

As table XXIV.1 shows, in school year 1991-92, the state provided about

50 percent of the total funding to Maine’s school districts. Total funding

(state and local funds combined) per weighted pupil in Maine averaged

$5,681 with an implicit foundation level of $3,612 for each student, which

is about 64 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.287, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .176,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) To put the state’s

school finance system in perspective, table XXIV.2 presents demographic

data for school year 1991-92 for five groups of districts of increasing

district income.

Table XXIV.1: Summary Data for Maine

in School Year 1991-92

Average total funding per weighted pupila $5,681

State share of total funding (percent) 49.4

Targeting score (state funds)b –.287

Implicit foundation levelc $3,612

Equalization effortd 63.6

Fiscal neutrality scoree .176

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 171 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXIV 

State Profile: Maine

Table XXIV.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 227 53 23 38 48 65

Total pupils 211,295 43,274 43,198 40,379 40,807 43,637

Poverty rate (percent) 13.7 17.9 13.1 13.3 12.6 11.4

Disabled rate (percent) 11.9 11.8 11.3 11.9 12.4 12.3

Per pupil income $76,336 $48,731 $57,869 $67,998 $87,059 $119,681

Tax efforta $37.61 $46.46 $35.13 $35.84 $34.79 $38.04

aLocal funding raised for every $1,000 of district income.

Table XXIV.3 presents data on how state and local funding was distributed

among the five groups of Maine districts. Maine’s equalization policies

reduced the total funding disparity between the wealthy and poor groups

from about 100 percent to about 17 percent. Figure XXIV.1 provides table

information in graphic form.

Table XXIV.3: State and Local Funding Distribution in Maine, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,875 $2,276 $2,017 $2,434 $3,038 $4,554 2.00

State 2,807 3,193 3,192 3,056 2,862 1,845 0.58

Total $5,681 $5,469 $5,210 $5,490 $5,901 $6,399 1.17

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 172 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXIV 

State Profile: Maine

Figure XXIV.1: State and Local

Funding Distribution in Maine, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXIV.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XXIV.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XXIV.3.

Table XXIV.4: How State and Local Funding Would Have Been Distributed If Each District in Maine Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,878 $1,828 $2,197 $2,567 $3,273 $4,513 2.47

State 2,803 3,853 3,484 3,115 2,409 1,168 0.30

Totalc $5,681 $5,681 $5,681 $5,681 $5,681 $5,681 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 173 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXIV 

State Profile: Maine

Figure XXIV.2: How State and Local

Funding Would Have Been Distributed

If Each District in Maine Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XXIV.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Maine Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 174 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXV 

State Profile: Maryland

Actual Education

Funding Distribution

in School Year 1991-92

As table XXV.1 shows, in school year 1991-92, the state provided about

40 percent of the total funding to Maryland’s school districts. Total funding

(state and local funds combined) per weighted pupil in Maryland averaged

$6,039 with an implicit foundation level of $3,819 for each student, which

is about 63 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.566, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .469,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) A Maryland

education official reported that the state had changed its school finance

system since school year 1991-92 to increase funding to poor districts

compared with wealthy districts (see app. LVI). To put the state’s school

finance system in perspective, table XXV.2 presents demographic data for

school year 1991-92 for five groups of districts of increasing district

income.

Table XXV.1: Summary Data for

Maryland in School Year 1991-92

Average total funding per weighted pupila $6,039

State share of total funding (percent) 40.4

Targeting score (state funds)b –.566

Implicit foundation levelc $3,819

Equalization effortd 63.2

Fiscal neutrality scoree .469

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 175 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXV 

State Profile: Maryland

Table XXV.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 24 6 8 4 4 2

Total pupils 736,238 147,982 144,665 141,124 190,872 111,595

Poverty rate (percent) 11.3 26.9 9.0 8.1 6.6 5.7

Disabled rate (percent) 12.0 14.8 11.8 10.5 12.3 10.2

Per pupil income $114,832 $76,344 $89,714 $109,357 $134,053 $172,482

Tax efforta $31.59 $23.79 $34.67 $30.58 $31.37 $36.41

aLocal funding raised for every $1,000 of district income.

Table XXV.3 presents data on how state and local funding was distributed

among the five groups of Maryland districts. Maryland’s equalization

policies reduced the funding disparity between the wealthy and poor

groups from about 217 percent to about 65 percent. Figure XXV.1 provides

table information in graphic form.

Table XXV.3: State and Local Funding Distribution in Maryland, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $3,601 $1,919 $3,089 $3,271 $4,185 $6,091 3.17

State 2,438 2,767 2,843 2,630 2,208 1,636 0.59

Total $6,039 $4,686 $5,931 $5,901 $6,393 $7,728 1.65

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 176 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXV 

State Profile: Maryland

Figure XXV.1: State and Local Funding

Distribution in Maryland, School Year

1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXV.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XXV.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XXV.3.

Table XXV.4: How State and Local Funding Would Have Been Distributed If Each District in Maryland Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $3,627 $2,269 $2,835 $3,511 $4,225 $5,577 2.46

State 2,413 3,771 3,205 2,528 1,814 462 0.12

Totalc $6,039 $6,039 $6,039 $6,039 $6,039 $6,039 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 177 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXV 

State Profile: Maryland

Figure XXV.2: How State and Local

Funding Would Have Been Distributed

If Each District in Maryland Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XXV.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Maryland

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 178 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVI 

State Profile: Massachusetts

Actual Education

Funding Distribution

in School Year 1991-92

As table XXVI.1 shows, in school year 1991-92, the state provided about

31 percent of the total funding to Massachusetts’ school districts. Total

funding (state and local funds combined) per weighted pupil in

Massachusetts averaged $6,264 with an implicit foundation level of $2,542

for each student, which is about 41 percent of the average and represents

the state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.316,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .447, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) A Massachusetts education official reported that the

state had changed its school finance system since school year 1991-92 to

increase funding to poor districts compared with wealthy districts (see

app. LVI). To put the state’s school finance system in perspective, table

XXVI.2 presents demographic data for school year 1991-92 for five groups

of districts of increasing district income.

Table XXVI.1: Summary Data for

Massachusetts in School Year 1991-92

Average total funding per weighted pupila $6,264

State share of total funding (percent) 30.8

Targeting score (state funds)b –.316

Implicit foundation levelc $2,542

Equalization effortd 40.6

Fiscal neutrality scoree .447

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 179 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVI 

State Profile: Massachusetts

Table XXVI.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 265 25 46 63 38 93

Total pupils 738,672 148,207 148,084 144,468 150,204 147,709

Poverty rate (percent) 13.3 25.3 11.2 7.2 15.9 6.5

Disabled rate (percent) 15.9 14.3 16.1 15.8 17.4 16.0

Per pupil income $133,452 $80,285 $103,188 $124,984 $147,482 $211,155

Tax efforta $32.62 $25.58 $35.56 $34.70 $33.18 $32.36

aLocal funding raised for every $1,000 of district income.

Table XXVI.3 presents data on how state and local funding was distributed

among the five groups of Massachusetts districts. Massachusetts’

equalization policies reduced the funding disparity between the wealthy

and poor groups from about 228 percent to about 54 percent. Figure

XXVI.1 provides table information in graphic form.

Table XXVI.3: State and Local Funding Distribution in Massachusetts, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $4,332 $2,059 $3,664 $4,290 $4,992 $6,761 3.28

State $1,932 3,169 2,003 1,543 1,618 1,276 0.40

Total $6,264 $5,227 $5,667 $5,833 $6,610 $8,037 1.54

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 180 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVI 

State Profile: Massachusetts

Figure XXVI.1: State and Local

Funding Distribution in

Massachusetts, School Year 1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

10,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXVI.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XXVI.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XXVI.3.

Page 181 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVI 

State Profile: Massachusetts

Table XXVI.4: How State and Local Funding Would Have Been Distributed If Each District in Massachusetts Could Have

Spent the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $4,342 $2,607 $3,359 $4,106 $4,703 $6,935 2.66

State $1,921 3,657 2,905 2,158 1,561 –671c –0.18

Totald $6,264 $6,264 $6,264 $6,264 $6,264 $6,264 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe state would have had to recapture this amount of local funding from these districts for

distribution to other districts.

dThe average is the maximum foundation level possible in a state.

Figure XXVI.2: How State and Local

Funding Would Have Been Distributed

If Each District in Massachusetts

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest (2,000)

0

2,000

4,000

6,000

8,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 182 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVI 

State Profile: Massachusetts

Figure XXVI.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in

Massachusetts Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest (1,000)

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 183 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVII 

State Profile: Michigan

Actual Education

Funding Distribution

in School Year 1991-92

As table XXVII.1 shows, in school year 1991-92, the state provided about

33 percent of the total funding to Michigan’s school districts. Total funding

(state and local funds combined) per weighted pupil in Michigan averaged

$5,851 with an implicit foundation level of $2,839 for each student, which

is about 49 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.475, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .290,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) A Michigan

education official reported that the state had changed its school finance

system since school year 1991-92 to increase funding to poor districts

compared with wealthy districts (see app. LVI). To put the state’s school

finance system in perspective, table XXVII.2 presents demographic data

for school year 1991-92 for five groups of districts of increasing district

income.

Table XXVII.1: Summary Data for

Michigan in School Year 1991-92

Average total funding per weighted pupila $5,851

State share of total funding (percent) 32.9

Targeting score (state funds)b –.475

Implicit foundation levelc $2,839

Equalization effortd 48.5

Fiscal neutrality scoree .290

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 184 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVII 

State Profile: Michigan

Table XXVII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 558 131 134 131 87 75

Total pupils 1,619,705 383,231 263,756 320,904 331,100 320,714

Poverty rate (percent) 17.4 33.8 19.8 12.5 10.9 7.4

Disabled rate (percent) 9.9 9.7 9.8 10.0 10.7 9.4

Per pupil income $80,367 $50,990 $60,070 $72,329 $86,839 $133,525

Tax efforta $48.78 $40.01 $50.86 $52.09 $51.37 $49.38

aLocal funding raised for every $1,000 of district income.

Table XXVII.3 presents data on how state and local funding was

distributed among the five groups of Michigan districts. Michigan’s

equalization policies reduced the funding disparity between the wealthy

and poor groups from about 208 percent to about 36 percent. Figure

XXVII.1 provides table information in graphic form.

Table XXVII.3: State and Local Funding Distribution in Michigan, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $3,926 $2,093 $3,063 $3,738 $4,449 $6,444 3.08

State 1,925 3,182 2,288 1,832 1,325 754 0.24

Total $5,851 $5,275 $5,351 $5,570 $5,774 $7,198 1.36

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 185 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVII 

State Profile: Michigan

Figure XXVII.1: State and Local

Funding Distribution in Michigan,

School Year 1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXVII.4 provides data on the distribution of state and local funding

if all districts could have spent the average total funding per weighted

pupil with an average tax effort. This assumes the state optimized its

targeting effort without changing the state share or the total funding for

education. Under this scenario, the implicit foundation level equals the

maximum possible foundation level (the state average). Figure XXVII.2

provides this information in graphic form. The difference between how

state funding was actually distributed and how it would have been

distributed if districts could have financed the average is shown in figure

XXVII.3.

Page 186 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVII 

State Profile: Michigan

Table XXVII.4: How State and Local Funding Would Have Been Distributed If Each District in Michigan Could Have Spent

the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $3,954 $2,430 $2,932 $3,565 $4,268 $6,681 2.75

State 1,897 3,421 2,919 2,286 1,583 –830c –0.24

Totald $5,851 $5,851 $5,851 $5,851 $5,851 $5,851 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe state would have had to recapture this amount of local funding from these districts for

distribution to other districts.

dThe average is the maximum foundation level possible in a state.

Figure XXVII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Michigan Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest (2,000)

0

2,000

4,000

6,000

8,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 187 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVII 

State Profile: Michigan

Figure XXVII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Michigan

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest (1,000)

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 188 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVIII 

State Profile: Minnesota

Actual Education

Funding Distribution

in School Year 1991-92

As table XXVIII.1 shows, in school year 1991-92, the state provided about

54 percent of the total funding to Minnesota’s school districts. Total

funding (state and local funds combined) per weighted pupil in Minnesota

averaged $5,646 with an implicit foundation level of $4,524 for each

student, which is about 80 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.499,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .113, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) A Minnesota education official reported that the state

had changed its school finance system since school year 1991-92 to

increase funding to poor districts compared with wealthy districts (see

app. LVI). To put the state’s school finance system in perspective, table

XXVIII.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table XXVIII.1: Summary Data for

Minnesota in School Year 1991-92

Average total funding per weighted pupila $5,646

State share of total funding (percent) 53.5

Targeting score (state funds)b –.499

Implicit foundation levelc $4,524

Equalization effortd 80.1

Fiscal neutrality scoree .113

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 189 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVIII 

State Profile: Minnesota

Table XXVIII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 404 166 79 71 47 41

Total pupils 741,835 148,475 147,144 149,452 149,247 147,517

Poverty rate (percent) 12.1 15.7 9.7 10.0 12.6 12.8

Disabled rate (percent) 10.7 10.0 10.2 10.9 11.2 11.3

Per pupil income $81,234 $49,929 $62,803 $71,975 $89,893 $131,745

Tax efforta $31.75 $36.66 $33.36 $29.23 $29.25 $32.08

aLocal funding raised for every $1,000 of district income.

Table XXVIII.3 presents data on how state and local funding was

distributed among the five groups of Minnesota districts. Minnesota’s

equalization policies reduced the funding disparity between the wealthy

and poor groups from 133 percent to about 11 percent. Figure XXVIII.1

provides table information in graphic form.

Table XXVIII.3: State and Local Funding Distribution in Minnesota, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,627 $1,827 $2,074 $2,101 $2,646 $4,256 2.33

State 3,019 3,785 3,383 3,230 3,003 1,956 0.52

Total $5,646 $5,613 $5,457 $5,331 $5,649 $6,212 1.11

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 190 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVIII 

State Profile: Minnesota

Figure XXVIII.1: State and Local

Funding Distribution in Minnesota,

School Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXVIII.4 provides data on the distribution of state and local funding

if all districts could have spent the average total funding per weighted

pupil with an average tax effort. This assumes the state optimized its

targeting effort without changing the state share or the total funding for

education. Under this scenario, the implicit foundation level equals the

maximum possible foundation level (the state average). Figure XXVIII.2

provides this information in graphic form. The difference between how

state funding was actually distributed and how it would have been

distributed if districts could have financed the average is shown in figure

XXVIII.3.

Page 191 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVIII 

State Profile: Minnesota

Table XXVIII.4: How State and Local Funding Would Have Been Distributed If Each District in Minnesota Could Have Spent

the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,627 $1,622 $2,053 $2,333 $2,889 $4,243 2.62

State 3,019 4,024 3,593 3,313 2,757 1,403 0.35

Totalc $5,646 $5,646 $5,646 $5,646 $5,646 $5,646 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Figure XXVIII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Minnesota Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 192 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXVIII 

State Profile: Minnesota

Figure XXVIII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Minnesota

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 193 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXIX 

State Profile: Mississippi

Actual Education

Funding Distribution

in School Year 1991-92

As table XXIX.1 shows, in school year 1991-92, the state provided about

64 percent of the total funding to Mississippi’s school districts. Total

funding (state and local funds combined) per weighted pupil in Mississippi

averaged $2,831 with an implicit foundation level of $1,860 for each

student, which is about 66 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.020,

indicating that state education funds were targeted to poor districts.102 (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .007, indicating that total funding increased as

district income increased.103 (To compare this score with those of other

states, see fig. 1.) A Mississippi education official reported that the state

had changed its school finance system since school year 1991-92 to

increase funding to poor districts compared with wealthy districts (see

app. LVI). To put the state’s school finance system in perspective, table

XXIX.2 presents demographic data for school year 1991-92 for five groups

of districts of increasing district income.

Table XXIX.1: Summary Data for

Mississippi in School Year 1991-92

Average total funding per weighted pupila $2,831

State share of total funding (percent) 64.4

Targeting score (state funds)b –.020

Implicit foundation levelc $1,860

Equalization effortd 65.7

Fiscal neutrality scoree .007

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income. The score is not significantly

different from 0.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income. The score is not

significantly different from 0.

102However, this score is not significantly different from 0.

103See footnote 102.

Page 194 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXIX 

State Profile: Mississippi

Table XXIX.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 148 31 37 32 28 20

Total pupils 496,277 99,428 97,200 100,261 107,073 92,315

Poverty rate (percent) 32.9 44.8 36.9 29.9 26.2 27.0

Disabled rate (percent) 12.0 10.0 13.5 12.4 12.3 12.0

Per pupil income $51,017 $30,029 $38,911 $44,232 $52,892 $91,561

Tax efforta $19.78 $39.02 $19.60 $17.25 $20.92 $13.74

aLocal funding raised for every $1,000 of district income.

Table XXIX.3 presents data on how state and local funding was distributed

among the five groups of Mississippi districts. Mississippi’s equalization

policies eliminated the funding disparity between the wealthy and poor

groups, with poor districts receiving about 2 percent more total funding

than wealthy districts. Figure XXIX.1 provides table information in graphic

form.

Table XXIX.3: State and Local Funding Distribution in Mississippi, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,008 $1,169 $779 $763 $1,098 $1,245 1.07

State 1,823 1,866 1,862 1,887 1,800 1,729 0.93

Total $2,831 $3,034 $2,642 $2,650 $2,898 $2,974 0.98

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 195 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXIX 

State Profile: Mississippi

Figure XXIX.1: State and Local

Funding Distribution in Mississippi,

School Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXIX.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XXIX.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XXIX.3.

Table XXIX.4: How State and Local Funding Would Have Been Distributed If Each District in Mississippi Could Have Spent

the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,008 $595 $753 $875 $1,056 $1,809 3.04

State 1,823 2,236 2,078 1,956 1,775 1,022 0.46

Totalc $2,831 $2,831 $2,831 $2,831 $2,831 $2,831 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 196 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXIX 

State Profile: Mississippi

Figure XXIX.2: How State and Local

Funding Would Have Been Distributed

If Each District in Mississippi Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XXIX.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Mississippi

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 197 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXX 

State Profile: Missouri

Actual Education

Funding Distribution

in School Year 1991-92

As table XXX.1 shows, in school year 1991-92, the state provided about

45 percent of the total funding to Missouri’s school districts. Total funding

(state and local funds combined) per weighted pupil in Missouri averaged

$3,972 with an implicit foundation level of $1,802 for each student, which

is about 45 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.017, indicating that state education

funds were targeted to poor districts.104 (To compare this score with those

of other states, see table V.1 in app. V.) The fiscal neutrality score was

.362, indicating that total funding increased as district income increased.

(To compare this score with those of other states, see fig. 1.) A Missouri

education official reported that the state had changed its school finance

system since school year 1991-92 to increase funding to poor districts

compared with wealthy districts (see app. LVI). To put the state’s school

finance system in perspective, table XXX.2 presents demographic data for

school year 1991-92 for five groups of districts of increasing district

income.

Table XXX.1: Summary Data for

Missouri in School Year 1991-92

Average total funding per weighted pupila $3,972

State share of total funding (percent) 44.6

Targeting score (state funds)b –.017

Implicit foundation levelc $1,802

Equalization effortd 45.4

Fiscal neutrality scoree .362

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income. The score is not significantly

different from 0.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

104However, this score is not significantly different from 0.

Page 198 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXX 

State Profile: Missouri

Table XXX.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 538 173 164 105 45 51

Total pupils 822,099 165,035 164,035 169,117 155,397 168,515

Poverty rate (percent) 17.0 23.6 16.6 13.7 17.1 14.2

Disabled rate (percent) 10.0 11.2 11.5 9.8 10.7 6.8

Per pupil income $79,570 $48,589 $61,069 $75,587 $90,076 $122,231

Tax efforta $27.41 $22.71 $23.31 $27.78 $34.09 $27.10

aLocal funding raised for every $1,000 of district income.

Table XXX.3 presents data on how state and local funding was distributed

among the five groups of Missouri districts. Missouri’s equalization

policies reduced the funding disparity between the wealthy and poor

groups from 181 percent to about 70 percent. Figure XXX.1 provides table

information in graphic form.

Table XXX.3: State and Local Funding Distribution in Missouri, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,200 $1,131 $1,446 $2,083 $3,097 $3,179 2.81

State 1,773 1,781 1,644 1,485 2,175 1,758 0.99

Total $3,972 $2,912 $3,090 $3,568 $5,272 $4,937 1.70

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 199 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXX 

State Profile: Missouri

Figure XXX.1: State and Local Funding

Distribution in Missouri, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXX.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XXX.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XXX.3.

Table XXX.4: How State and Local Funding Would Have Been Distributed If Each District in Missouri Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,240 $1,313 $1,664 $2,118 $2,477 $3,610 2.75

State 1,733 2,660 2,308 1,854 1,495 363 0.14

Totalc $3,972 $3,972 $3,972 $3,972 $3,972 $3,972 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 200 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXX 

State Profile: Missouri

Figure XXX.2: How State and Local

Funding Would Have Been Distributed

If Each District in Missouri Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XXX.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Missouri

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 201 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXI 

State Profile: Montana

Actual Education

Funding Distribution

in School Year 1991-92

As table XXXI.1 shows, in school year 1991-92, the state provided about

44 percent of the total funding to Montana’s school districts. Total funding

(state and local funds combined) per weighted pupil in Montana averaged

$4,835 with an implicit foundation level of $2,406 for each student, which

is about 50 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.126, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .393,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) A Montana

education official reported that the state had changed its school finance

system since school year 1991-92 to increase funding to poor districts

compared with wealthy districts (see app. LVI). To put the state’s school

finance system in perspective, table XXXI.2 presents demographic data for

school year 1991-92 for five groups of districts of increasing district

income.

Table XXXI.1: Summary Data for

Montana in School Year 1991-92

Average total funding per weighted pupila $4,835

State share of total funding (percent) 44.2

Targeting score (state funds)b –.126

Implicit foundation levelc $2,406

Equalization effortd 49.8

Fiscal neutrality scoree .393

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 202 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXI 

State Profile: Montana

Table XXXI.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 480 114 87 45 135 99

Total pupils 154,488 30,656 30,001 33,496 29,426 30,909

Poverty rate (percent) 19.5 26.5 18.6 18.1 17.9 16.6

Disabled rate (percent) 9.8 10.2 9.4 11.6 9.3 8.3

Per pupil income $115,518 $49,344 $74,493 $91,295 $123,824 $239,311

Tax efforta $23.94 $42.44 $30.36 $22.14 $25.07 $18.64

aLocal funding raised for every $1,000 of district income.

Table XXXI.3 presents data on how state and local funding was distributed

among the five groups of Montana districts. Although Montana provided

more state funding to wealthy districts than to poor districts, Montana’s

equalization policies moderated the funding disparity between the wealthy

and poor groups from about 104 percent to about 73 percent. Figure

XXXI.1 provides table information in graphic form.

Table XXXI.3: State and Local Funding Distribution in Montana, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,698 $2,136 $2,248 $2,056 $3,077 $4,365 2.04

State 2,137 1,870 2,010 2,019 2,353 2,577 1.38

Total $4,835 $4,006 $4,258 $4,075 $5,430 $6,942 1.73

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 203 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXI 

State Profile: Montana

Figure XXXI.1: State and Local

Funding Distribution in Montana,

School Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXXI.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XXXI.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XXXI.3.

Page 204 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXI 

State Profile: Montana

Table XXXI.4: How State and Local Funding Would Have Been Distributed If Each District in Montana Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,730 $1,145 $1,754 $2,098 $2,948 $5,726 5.00

State 2,105 3,690 3,081 2,737 1,886 –891c –0.24

Totald $4,835 $4,835 $4,835 $4,835 $4,835 $4,835 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe state would have had to recapture this amount of local funding from these districts for

distribution to other districts.

dThe average is the maximum foundation level possible in a state.

Figure XXXI.2: How State and Local

Funding Would Have Been Distributed

If Each District in Montana Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest (1,000)

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 205 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXI 

State Profile: Montana

Figure XXXI.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Montana

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest (1,000)

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 206 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXII 

State Profile: Nebraska

Actual Education

Funding Distribution

in School Year 1991-92

As table XXXII.1 shows, in school year 1991-92, the state provided about

34 percent of the total funding to Nebraska’s school districts. Total funding

(state and local funds combined) per weighted pupil in Nebraska averaged

$5,148 with an implicit foundation level of $2,203 for each student, which

is about 43 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.246, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .154,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) A Nebraska

education official reported that the state had changed its school finance

system since school year 1991-92 to increase funding to poor districts

compared with wealthy districts (see app. LVI). To put the state’s school

finance system in perspective, table XXXII.2 presents demographic data

for school year 1991-92 for five groups of districts of increasing district

income.

Table XXXII.1: Summary Data for

Nebraska in School Year 1991-92

Average total funding per weighted pupila $5,148

State share of total funding (percent) 34.3

Targeting score (state funds)b –.246

Implicit foundation levelc $2,203

Equalization effortd 42.8

Fiscal neutrality scoree .154

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 207 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXII 

State Profile: Nebraska

Table XXXII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 678 150 96 87 51 294

Total pupils 276,085 55,219 55,181 55,320 58,772 51,593

Poverty rate (percent) 12.9 15.0 12.1 8.6 17.7 10.7

Disabled rate (percent) 12.3 11.2 12.1 11.9 12.6 13.4

Per pupil income $94,845 $64,972 $78,825 $90,020 $107,093 $135,169

Tax efforta $36.38 $51.44 $41.86 $37.79 $29.19 $30.73

aLocal funding raised for every $1,000 of district income.

Table XXXII.3 presents data on how state and local funding was

distributed among the five groups of Nebraska districts. Nebraska’s

equalization policies reduced the total funding disparity between the

wealthy and poor groups from about 27 percent to about 5 percent. Figure

XXXII.1 provides table information in graphic form.

Table XXXII.3: State and Local Funding Distribution in Nebraska, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $3,380 $3,309 $3,291 $3,364 $3,164 $4,191 1.27

State 1,768 2,058 1,993 1,723 1,668 1,422 0.69

Total $5,148 $5,367 $5,284 $5,087 $4,832 $5,614 1.05

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 208 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXII 

State Profile: Nebraska

Figure XXXII.1: State and Local

Funding Distribution in Nebraska,

School Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXXII.4 provides data on the distribution of state and local funding

if all districts could have spent the average total funding per weighted

pupil with an average tax effort. This assumes the state optimized its

targeting effort without changing the state share or the total funding for

education. Under this scenario, the implicit foundation level equals the

maximum possible foundation level (the state average). Figure XXXII.2

provides this information in graphic form. The difference between how

state funding was actually distributed and how it would have been

distributed if districts could have financed the average is shown in figure

XXXII.3.

Page 209 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXII 

State Profile: Nebraska

Table XXXII.4: How State and Local Funding Would Have Been Distributed If Each District in Nebraska Could Have Spent

the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $3,384 $2,342 $2,819 $3,247 $3,772 $4,809 2.05

State 1,764 2,806 2,329 1,901 1,376 339 0.12

Totalc $5,148 $5,148 $5,148 $5,148 $5,148 $5,148 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Figure XXXII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Nebraska Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 210 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXII 

State Profile: Nebraska

Figure XXXII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Nebraska

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 211 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIII 

State Profile: Nevada

Actual Education

Funding Distribution

in School Year 1991-92

As table XXXIII.1 shows, in school year 1991-92, the state provided about

57 percent of the total funding to Nevada’s school districts. Total funding

(state and local funds combined) per weighted pupil in Nevada averaged

$3,597 with the same implicit foundation level, achieving an equalization

effort of 100 percent.105 (To compare this effort with those of other states,

see fig. 5.) The targeting score for state funding was –1.007, indicating that

state education funds were targeted to poor districts. (To compare this

score with those of other states, see table V.1 in app. V.) The fiscal

neutrality score was –.556, indicating that total funding increased as

district income decreased. (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table XXXIII.2 presents demographic data for 1991-92 for four groups of

districts of increasing district income. Nevada was divided into four

groups rather than five because of its student population distribution.

Table XXXIII.1: Summary Data for

Nevada in School Year 1991-92

Average total funding per weighted pupila $3,597

State share of total funding (percent) 56.9

Targeting score (state funds)b –1.007

Implicit foundation levelc $3,597

Equalization effortd 100.0

Fiscal neutrality scoree –.556

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

105Nevada actually targeted more state funds to poor districts than was necessary to achieve the

average as an implicit foundation level.

Page 212 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIII 

State Profile: Nevada

Table XXXIII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4

Total districts 17 11 1b 2 3

Total pupils 211,810 29,577 129,233 12,402 40,598

Poverty rate (percent) 13.3 12.4 14.4 8.9 11.7

Disabled rate (percent) 9.4 11.1 8.5 11.6 10.6

Mean income per pupil $86,827 $57,218 $85,716 $93,306 $109,952

Tax efforta $17.84 $28.42 $17.81 $18.51 $13.73

aLocal funding raised for every $1,000 of district income.

bLas Vegas was the only district in this group.

Table XXXIII.3 presents data on how state and local funding was

distributed among the four groups of districts. Nevada’s equalization

policies increased the funding that poor districts had compared with

wealthy districts, resulting in wealthy districts having 31 percent less

funding than poor districts. Figure XXXIII.1 provides table information in

graphic form.

Table XXXIII.3: State and Local Funding Distribution in Nevada, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4

Funding of

wealthiest group

compared with

poorest groupa

Local $1,549 $1,654 $1,513 $1,756 $1,526 0.92

State 2,049 2,865 1,943 2,579 1,591 0.56

Total $3,597 $4,518 $3,455 $4,335 $3,117 0.69

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

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Appendix XXXIII 

State Profile: Nevada

Figure XXXIII.1: State and Local

Funding Distribution in Nevada,

School Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXXIII.4 provides data on the distribution of state and local funding

if all districts could have spent the average total funding per weighted

pupil with an average tax effort. This assumes the state optimized its

targeting effort without changing the state share or the total funding for

education. Under this scenario, the implicit foundation level equals the

maximum possible foundation level (the state average). Figure XXXIII.2

provides this information in graphic form. The difference between how

state funding was actually distributed and how it would have been

distributed if districts could have financed the average is shown in figure

XXXIII.3.

Page 214 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIII 

State Profile: Nevada

Table XXXIII.4: How State and Local Funding Would Have Been Distributed If Each District in Nevada Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,549 $1,003 $1,543 $1,635 $1,940 1.93

State 2,048 2,594 2,055 1,962 1,657 0.64

Totalc $3,597 $3,597 $3,597 $3,597 $3,597 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Figure XXXIII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Nevada Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 215 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIII 

State Profile: Nevada

Figure XXXIII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Nevada

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 216 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIV 

State Profile: New Hampshire

Actual Education

Funding Distribution

in School Year 1991-92

As table XXXIV.1 shows, in school year 1991-92, the state provided about

8 percent of the total funding to New Hampshire’s school districts. Total

funding (state and local funds combined) per weighted pupil in New

Hampshire averaged $5,850 with an implicit foundation level of $764 for

each student, which is about 13 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.571,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .238, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table XXXIV.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table XXXIV.1: Summary Data for New

Hampshire in School Year 1991-92

Average total funding per weighted pupila $5,850

State share of total funding (percent) 8.3

Targeting score (state funds)b –.571

Implicit foundation levelc $764

Equalization effortd 13.1

Fiscal neutrality scoree .238

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 217 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIV 

State Profile: New Hampshire

Table XXXIV.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 158 29 19 13 26 71

Total pupils 173,044 34,720 34,262 35,559 32,753 32,750

Poverty rate (percent) 7.6 10.3 6.6 8.1 7.9 5.0

Disabled rate (percent) 11.4 10.5 11.4 11.3 11.6 12.5

Per pupil income $106,978 $66,877 $83,834 $96,242 $114,078 $172,277

Tax efforta $50.35 $70.96 $61.21 $49.30 $46.67 $40.24

aLocal funding raised for every $1,000 of district income.

Table XXXIV.3 presents data on how state and local funding was

distributed among the five groups of New Hampshire districts. New

Hampshire’s equalization policies reduced the funding disparity between

the wealthy and poor groups from 48 percent to about 30 percent. Figure

XXXIV.1 provides table information in graphic form.

Table XXXIV.3: State and Local Funding Distribution in New Hampshire, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $5,364 $4,718 $5,117 $4,741 $5,337 $6,981 1.48

State 486 874 526 425 324 303 0.35

Total $5,850 $5,592 $5,643 $5,166 $5,661 $7,284 1.30

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 218 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIV 

State Profile: New Hampshire

Figure XXXIV.1: State and Local

Funding Distribution in New

Hampshire, School Year 1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

10,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXXIV.4 provides data on the distribution of state and local funding

if all districts could have spent the average total funding per weighted

pupil with an average tax effort. This assumes the state optimized its

targeting effort without changing the state share or the total funding for

education. Under this scenario, the implicit foundation level equals the

maximum possible foundation level (the state average). Figure XXXIV.2

provides this information in graphic form. The difference between how

state funding was actually distributed and how it would have been

distributed if districts could have financed the average is shown in figure

XXXIV.3.

Page 219 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIV 

State Profile: New Hampshire

Table XXXIV.4: How State and Local Funding Would Have Been Distributed If Each District in New Hampshire Could Have

Spent the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $5,362 $3,380 $4,222 $4,833 $5,714 $8,586 2.54

State 486 2,470 1,628 1,017 136 –2,736c –1.11

Totald $5,850 $5,850 $5,850 $5,850 $5,850 $5,850 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe state would have had to recapture this amount of local funding from these districts for

distribution to other districts.

dThe average is the maximum foundation level possible in a state.

Figure XXXIV.2: How State and Local

Funding Would Have Been Distributed

If Each District in New Hampshire

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest (4,000)

(2,000)

0

2,000

4,000

6,000

8,000

10,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 220 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIV 

State Profile: New Hampshire

Figure XXXIV.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in New

Hampshire Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest (3,000)

(2,000)

(1,000)

0

1,000

2,000

3,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 221 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXV 

State Profile: New Jersey

Actual Education

Funding Distribution

in School Year 1991-92

As table XXXV.1 shows, in school year 1991-92, the state provided about

43 percent of the total funding to New Jersey’s school districts. Total

funding (state and local funds combined) per weighted pupil in New

Jersey averaged $9,239 with an implicit foundation level of $4,399 for each

student, which is about 48 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.104,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .168, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) A New Jersey education official reported that the state

had changed its school finance system since school year 1991-92 to

increase funding to poor districts compared with wealthy districts (see

app. LVI). To put the state’s school finance system in perspective, table

XXXV.2 presents demographic data for school year 1991-92 for five groups

of districts of increasing district income.

Table XXXV.1: Summary Data for New

Jersey in School Year 1991-92

Average total funding per weighted pupila $9,239

State share of total funding (percent) 43.1

Targeting score (state funds)b –.104

Implicit foundation levelc $4,399

Equalization effortd 47.6

Fiscal neutrality scoree .168

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 222 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXV 

State Profile: New Jersey

Table XXXV.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 550 35 64 98 139 214

Total pupils 1,085,033 216,539 215,008 219,560 216,787 217,139

Poverty rate (percent) 11.3 29.0 12.1 6.0 4.4 5.0

Disabled rate (percent) 16.1 15.2 17.0 16.7 15.9 15.8

Per pupil income $160,761 $63,855 $101,685 $137,619 $175,659 $324,425

Tax efforta $32.93 $34.85 $38.74 $40.47 $39.11 $24.58

aLocal funding raised for every $1,000 of district income.

Table XXXV.3 presents data on how state and local funding was

distributed among the five groups of New Jersey districts. New Jersey’s

equalization policies reduced the funding disparity between the wealthy

and poor groups from 247 percent to about 31 percent. Figure XXXV.1

provides table information in graphic form.

Table XXXV.3: State and Local Funding Distribution in New Jersey, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $5,255 $2,267 $3,982 $5,555 $6,777 $7,867 3.47

State 3,985 6,167 4,733 3,189 2,601 3,220 0.52

Total $9,239 $8,434 $8,715 $8,744 $9,377 $11,087 1.31

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 223 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXV 

State Profile: New Jersey

Figure XXXV.1: State and Local

Funding Distribution in New Jersey,

School Year 1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

10,000

12,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXXV.4 provides data on the distribution of state and local funding

if all districts could have spent the average total funding per weighted

pupil with an average tax effort. This assumes the state optimized its

targeting effort without changing the state share or the total funding for

education. Under this scenario, the implicit foundation level equals the

maximum possible foundation level (the state average). Figure XXXV.2

provides this information in graphic form. The difference between how

state funding was actually distributed and how it would have been

distributed if districts could have financed the average is shown in figure

XXXV.3.

Page 224 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXV 

State Profile: New Jersey

Table XXXV.4: How State and Local Funding Would Have Been Distributed If Each District in New Jersey Could Have Spent

the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $5,314 $2,056 $3,293 $4,522 $5,831 $10,849 5.28

State 3,925 7,183 5,947 4,718 3,408 –1,609c –0.22

Totald $9,239 $9,239 $9,239 $9,239 $9,239 $9,239 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe state would have had to recapture this amount of local funding from these districts for

distribution to other districts.

dThe average is the maximum foundation level possible in a state.

Figure XXXV.2: How State and Local

Funding Would Have Been Distributed

If Each District in New Jersey Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest (2,000)

0

2,000

4,000

6,000

8,000

10,000

12,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 225 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXV 

State Profile: New Jersey

Figure XXXV.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in New Jersey

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest (2,000)

0

2,000

4,000

6,000

8,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 226 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVI 

State Profile: New Mexico

Actual Education

Funding Distribution

in School Year 1991-92

As table XXXVI.1 shows, in school year 1991-92, the state provided

85 percent of the total funding to New Mexico’s school districts. Total

funding (state and local funds combined) per weighted pupil in New

Mexico averaged $3,830 with an implicit foundation level of $3,254 for

each student, which is 85 percent of the average and represents the state’s

equalization effort. (To compare this effort with those of other states, see

fig. 5.) The targeting score for state funding was .000, indicating that state

education funds were not targeted to poor or wealthy districts.106 (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .004, indicating that total funding increased as

district income increased.107 (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table XXXVI.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table XXXVI.1: Summary Data for New

Mexico in School Year 1991-92

Average total funding per weighted pupila $3,830

State share of total funding (percent) 85.0

Targeting score (state funds)b .000

Implicit foundation levelc $3,254

Equalization effortd 85.0

Fiscal neutrality scoree .004

aThe average is the maximum foundation level possible in a state.

bThis is the constrained score (elasticity of state funding relative to district income) used to

calculate the state’s implicit foundation level. The actual targeting elasticity is .024, which is not

statistically different from 0.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income. The score is not

significantly different from 0.

106This is the constrained targeting score used to calculate the state’s implicit foundation level. This

differs from the actual targeting score found in table V.1 in app. V.

107However, this score is not significantly different from 0.

Page 227 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVI 

State Profile: New Mexico

Table XXXVI.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 88 31 26 16 12 3

Total pupils 308,772 61,705 61,908 64,577 103,740 16,842

Poverty rate (percent) 27.6 43.4 27.8 29.3 19.3 13.1

Disabled rate (percent) 12.2 10.9 11.0 11.6 14.4 11.1

Per pupil income $54,999 $26,342 $44,108 $50,207 $73,453 $104,736

Tax efforta $10.51 $27.48 $13.46 $11.36 $5.72 $9.67

aLocal funding raised for every $1,000 of district income.

Table XXXVI.3 presents data on how state and local funding was

distributed among the five groups of New Mexico districts. New Mexico’s

equalization policies reduced the funding disparity between the wealthy

and poor groups from about 33 percent to about 5 percent. Figure XXXVI.1

provides table information in graphic form.

Table XXXVI.3: State and Local Funding Distribution in New Mexico, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $576 $733 $586 $568 $424 $976 1.33

State 3,254 3,159 3,328 3,227 3,353 3,118 0.99

Total $3,830 $3,891 $3,914 $3,795 $3,776 $4,094 1.05

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 228 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVI 

State Profile: New Mexico

Figure XXXVI.1: State and Local

Funding Distribution in New Mexico,

School Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXXVI.4 provides data on the distribution of state and local funding

if all districts could have spent the average total funding per weighted

pupil with an average tax effort. This assumes the state optimized its

targeting effort without changing the state share or the total funding for

education. Under this scenario, the implicit foundation level equals the

maximum possible foundation level (the state average). Figure XXXVI.2

provides this information in graphic form. The difference between how

state funding was actually distributed and how it would have been

distributed if districts could have financed the average is shown in figure

XXXVI.3.

Page 229 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVI 

State Profile: New Mexico

Table XXXVI.4: How State and Local Funding Would Have Been Distributed If Each District in New Mexico Could Have

Spent the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $577 $273 $469 $528 $762 $1,138 4.17

State 3,253 3,557 3,362 3,302 3,068 2,693 0.76

Totalc $3,830 $3,830 $3,830 $3,830 $3,830 $3,830 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Figure XXXVI.2: How State and Local

Funding Would Have Been Distributed

If Each District in New Mexico Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 230 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVI 

State Profile: New Mexico

Figure XXXVI.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in New Mexico

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 231 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVII 

State Profile: New York

Actual Education

Funding Distribution

in School Year 1991-92

As table XXXVII.1 shows, in school year 1991-92, the state provided about

43 percent of the total funding to New York’s school districts. Total

funding (state and local funds combined) per weighted pupil in New York

averaged $7,787 with an implicit foundation level of $5,240 for each

student, which is about 67 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.578,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .370, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table XXXVII.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table XXXVII.1: Summary Data for New

York in School Year 1991-92

Average total funding per weighted pupila $7,787

State share of total funding (percent) 42.6

Targeting score (state funds)b –.578

Implicit foundation levelc $5,240

Equalization effortd 67.3

Fiscal neutrality scoree .370

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 232 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVII 

State Profile: New York

Table XXXVII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 693 302 144 1a 46 200

Total pupils 2,608,699 520,956 447,934 962,269 156,803 520,737

Poverty rate (percent) 18.5 16.7 13.3 30.5 7.6 5.8

Disabled rate (percent) 11.0 10.8 11.0 11.6 10.5 10.5

Mean income per pupil $114,397 $71,624 $96,585 $109,889 $116,663 $180,157

Tax effortb $39.87 $42.35 $49.54 $25.53 $50.04 $49.75

aNew York City was the only district in this group.

bLocal funding raised for every $1,000 of district income.

Table XXXVII.3 presents data on how state and local funding was

distributed among the five groups of New York districts. New York’s

equalization policies reduced the funding disparity between the wealthy

and poor groups from about 189 percent to 32 percent. Figure XXXVII.1

provides table information in graphic form.

Table XXXVII.3: State and Local Funding Distribution in New York, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $4,467 $3,017 $4,738 $2,879 $5,692 $8,719 2.89

State 3,320 5,292 4,116 2,688 3,376 2,231 0.42

Total $7,787 $8,309 $8,853 $5,567 $9,068 $10,950 1.32

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 233 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVII 

State Profile: New York

Figure XXXVII.1: State and Local

Funding Distribution in New York,

School Year 1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

10,000

12,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXXVII.4 provides data on the distribution of state and local funding

if all districts could have spent the average total funding per weighted

pupil with an average tax effort. This assumes the state optimized its

targeting effort without changing the state share or the total funding for

education. Under this scenario, the implicit foundation level equals the

maximum possible foundation level (the state average). Figure XXXVII.2

provides this information in graphic form. The difference between how

state funding was actually distributed and how it would have been

distributed if districts could have financed the average is shown in figure

XXXVII.3.

Page 234 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVII 

State Profile: New York

Table XXXVII.4: How State and Local Funding Would Have Been Distributed If Each District in New York Could Have Spent

the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $4,489 $2,816 $3,819 $4,181 $4,676 $7,250 2.58

State 3,298 4,971 3,968 3,606 3,111 537 0.11

Totalc $7,787 $7,787 $7,787 $7,787 $7,787 $7,787 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Figure XXXVII.2: How State and Local

Funding Would Have Been Distributed

If Each District in New York Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

10,000

12,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 235 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVII 

State Profile: New York

Figure XXXVII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in New York

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 236 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVIII 

State Profile: North Carolina

Actual Education

Funding Distribution

in School Year 1991-92

As table XXXVIII.1 shows, in school year 1991-92, the state provided about

68 percent of the total funding to North Carolina’s school districts. Total

funding (state and local funds combined) per weighted pupil in North

Carolina averaged $4,424 with an implicit foundation level of $3,043 for

each student, which is about 69 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.016,

indicating that state education funds were targeted to poor districts.108 (To

compare this score with those of other states, see table V.1 in app. V.) A

North Carolina education official reported that the state had changed its

school finance system since school year 1991-92 to increase funding to

poor districts compared with wealthy districts (see app. LVI). The fiscal

neutrality score was .250, indicating that total funding increased as district

income increased. (To compare this score with those of other states, see

fig. 1.) To put the state’s school finance system in perspective, table

XXXVIII.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table XXXVIII.1: Summary Data for

North Carolina in School Year 1991-92

Average total funding per weighted pupila $4,424

State share of total funding (percent) 67.7

Targeting score (state funds)b –.016

Implicit foundation levelc $3,043

Equalization effortd 68.8

Fiscal neutrality scoree .250

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income. The score is not significantly

different from 0.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

108However, this score is not significantly different from 0.

Page 237 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVIII 

State Profile: North Carolina

Table XXXVIII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 132 42 29 27 24 10

Total pupils 1,082,899 210,835 221,949 215,571 209,004 225,540

Poverty rate (percent) 17.1 26.6 16.6 15.8 13.9 12.6

Disabled rate (percent) 11.4 11.2 11.1 12.3 11.6 11.0

Per pupil income $76,415 $51,667 $64,236 $70,911 $86,835 $107,140

Tax efforta $18.58 $18.77 $17.51 $16.62 $19.88 $19.54

aLocal funding raised for every $1,000 of district income.

Table XXXVIII.3 presents data on how state and local funding was

distributed among the five groups of North Carolina districts. North

Carolina’s equalization policies reduced the funding disparity between the

wealthy and poor groups from about 110 percent to about 18 percent.

Figure XXXVIII.1 provides table information in graphic form.

Table XXXVIII.3: State and Local Funding Distribution in North Carolina, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,429 $983 $1,120 $1,188 $1,719 $2,068 2.10

State 2,995 3,200 3,047 2,984 2,935 2,851 0.89

Total $4,424 $4,183 $4,167 $4,171 $4,654 $4,919 1.18

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 238 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVIII 

State Profile: North Carolina

Figure XXXVIII.1: State and Local

Funding Distribution in North Carolina,

School Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXXVIII.4 provides data on the distribution of state and local

funding if all districts could have spent the average total funding per

weighted pupil with an average tax effort. This assumes the state

optimized its targeting effort without changing the state share or the total

funding for education. Under this scenario, the implicit foundation level

equals the maximum possible foundation level (the state average). Figure

XXXVIII.2 provides this information in graphic form. The difference

between how state funding was actually distributed and how it would have

been distributed if districts could have financed the average is shown in

figure XXXVIII.3.

Page 239 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVIII 

State Profile: North Carolina

Table XXXVIII.4: How State and Local Funding Would Have Been Distributed If Each District in North Carolina Could Have

Spent the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

(percent)

Localb $1,433 $955 $1,207 $1,316 $1,632 $2,029 2.13

State 2,991 3,469 3,217 3,107 2,791 2,395 0.69

Totalc $4,424 $4,424 $4,424 $4,242 $4,424 $4,424 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Figure XXXVIII.2: How State and Local

Funding Would Have Been Distributed

If Each District in North Carolina Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 240 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXVIII 

State Profile: North Carolina

Figure XXXVIII.3: Comparison of

Actual State Funding With State

Funding Assuming Each District in

North Carolina Could Have Spent the

Average, School Year 1991-92

State Funding if Each Student Received the Average

Actual State Funding

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Page 241 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIX 

State Profile: North Dakota

Actual Education

Funding Distribution

in School Year 1991-92

As table XXXIX.1 shows, in school year 1991-92, the state provided

48 percent of the total funding to North Dakota’s school districts. Total

funding (state and local funds combined) per weighted pupil in North

Dakota averaged $4,079 with an implicit foundation level of $1,957 for

each student, which is 48 percent of the average and represents the state’s

equalization effort. (To compare this effort with those of other states, see

fig. 5.) The targeting score for state funding was .000, indicating that state

education funds were not targeted to poor or wealthy districts.109 (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .236, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) A North Dakota education official reported that the state

had changed its school finance system since school year 1991-92 to

increase funding to poor districts compared with wealthy districts (see

app. LVI). To put the state’s school finance system in perspective, table

XXXIX.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table XXXIX.1: Summary Data for

North Dakota in School Year 1991-92

Average total funding per weighted pupila $4,079

State share of total funding (percent) 48.0

Targeting score (state funds)b .000

Implicit foundation levelc $1,957

Equalization effortd 48.0

Fiscal neutrality scoree .236

aThe average is the maximum foundation level possible in a state.

bThis is the constrained score (elasticity of state funding relative to district income) used to

calculate the state’s implicit foundation level. The actual targeting elasticity is .173.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

109This is the constrained targeting score used to calculate the state’s implicit foundation level. This

differs from the actual targeting score found in table V.1 in app. V.

Page 242 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIX 

State Profile: North Dakota

Table XXXIX.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 251 72 42 37 39 61

Total pupils 117,927 23,694 23,535 23,412 27,694 19,592

Poverty rate (percent) 16.4 23.3 17.3 14.3 13.4 13.5

Disabled rate (percent) 10.4 10.1 11.0 11.3 10.1 9.4

Per pupil income $58,094 $39,424 $51,292 $57,268 $64,658 $80,555

Tax efforta $37.11 $47.60 $37.25 $36.34 $33.97 $35.24

aLocal funding raised for every $1,000 of district income.

Table XXXIX.3 presents data on how state and local funding was

distributed among the five groups of North Dakota districts. North

Dakota’s equalization policies reduced the funding disparity between the

wealthy and poor groups from about 48 percent to about 18 percent.

Figure XXXIX.1 provides table information in graphic form.

Table XXXIX.3: State and Local Funding Distribution in North Dakota, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,122 $1,893 $1,927 $2,094 $2,178 $2,793 1.48

State 1,957 2,112 1,924 2,006 1,935 1,916 0.91

Total $4,079 $4,006 $3,851 $4,100 $4,113 $4,709 1.18

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 243 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIX 

State Profile: North Dakota

Figure XXXIX.1: State and Local

Funding Distribution in North Dakota,

School Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XXXIX.4 provides data on the distribution of state and local funding

if all districts could have spent the average total funding per weighted

pupil with an average tax effort. This assumes the state optimized its

targeting effort without changing the state share or the total funding for

education. Under this scenario, the implicit foundation level equals the

maximum possible foundation level (the state average). Figure XXXIX.2

provides this information in graphic form. The difference between how

state funding was actually distributed and how it would have been

distributed if districts could have financed the average is shown in figure

XXXIX.3.

Page 244 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIX 

State Profile: North Dakota

Table XXXIX.4: How State and Local Funding Would Have Been Distributed If Each District in North Dakota Could Have

Spent the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,131 $1,439 $1,859 $2,080 $2,385 $2,997 2.08

State 1,948 2,641 2,220 1,999 1,694 1,082 0.41

Totalc $4,079 $4,079 $4,079 $4,079 $4,079 $4,079 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Figure XXXIX.2: How State and Local

Funding Would Have Been Distributed

If Each District in North Dakota Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 245 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XXXIX 

State Profile: North Dakota

Figure XXXIX.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in North

Dakota Could Have Spent the Average,

School Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 246 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XL 

State Profile: Ohio

Actual Education

Funding Distribution

in School Year 1991-92

As table XL.1 shows, in school year 1991-92, the state provided about

42 percent of the total funding to Ohio’s school districts. Total funding

(state and local funds combined) per weighted pupil in Ohio averaged

$4,709 with an implicit foundation level of $2,325 for each student, which

is about 49 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.180, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .315,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) An Ohio

education official reported that the state had changed its school finance

system since school year 1991-92 to increase funding to poor districts

compared with wealthy districts (see app. LVI). To put the state’s school

finance system in perspective, table XL.2 presents demographic data for

school year 1991-92 for five groups of districts of increasing district

income.

Table XL.1: Summary Data for Ohio in

School Year 1991-92

Average total funding per weighted pupila $4,709

State share of total funding (percent) 41.9

Targeting score (state funds)b –.180

Implicit foundation levelc $2,325

Equalization effortd 49.4

Fiscal neutrality scoree .315

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 247 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XL 

State Profile: Ohio

Table XL.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 607 194 130 97 94 92

Total pupils 1,774,710 354,716 357,256 355,695 352,452 354,591

Poverty rate (percent) 16.9 22.4 20.6 19.1 12.9 9.6

Disabled rate (percent) 11.3 11.1 12.0 11.6 10.7 11.0

Per pupil income $80,781 $52,436 $64,691 $73,820 $88,110 $125,043

Tax efforta $33.75 $37.27 $33.27 $34.01 $32.51 $33.55

aLocal funding raised for every $1,000 of district income.

Table XL.3 presents data on how state and local funding was distributed

among the five groups of Ohio districts. Ohio’s equalization policies

reduced the funding disparity between the wealthy and poor groups from

about 110 to 32 percent. Figure XL.1 provides table information in graphic

form.

Table XL.3: State and Local Funding Distribution in Ohio, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,738 $1,969 $2,182 $2,529 $2,826 $4,132 2.10

State 1,971 2,336 2,164 2,030 1,766 1,556 0.67

Total $4,709 $4,305 $4,346 $4,559 $4,592 $5,688 1.32

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 248 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XL 

State Profile: Ohio

Figure XL.1: State and Local Funding

Distribution in Ohio, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XL.4 provides data on the distribution of state and local funding if all

districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XL.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XL.3.

Table XL.4: How State and Local Funding Would Have Been Distributed If Each District in Ohio Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,751 $1,765 $2,168 $2,487 $3,031 $4,311 2.44

State 1,958 2,944 2,541 2,222 1,678 398 0.14

Totalc $4,709 $4,709 $4,709 $4,709 $4,709 $4,709 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 249 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XL 

State Profile: Ohio

Figure XL.2: How State and Local

Funding Would Have Been Distributed

If Each District in Ohio Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XL.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Ohio Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 250 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLI 

State Profile: Oklahoma

Actual Education

Funding Distribution

in School Year 1991-92

As table XLI.1 shows, in school year 1991-92, the state provided about

71 percent of the total funding to Oklahoma’s school districts. Total

funding (state and local funds combined) per weighted pupil in Oklahoma

averaged $3,623 with an implicit foundation level of $2,838 for each

student, which is about 78 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.102,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was –.053, indicating that total funding increased as

district income decreased. (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table XLI.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table XLI.1: Summary Data for

Oklahoma in School Year 1991-92

Average total funding per weighted pupila $3,623

State share of total funding (percent) 71.1

Targeting score (state funds)b –.102

Implicit foundation levelc $2,838

Equalization effortd 78.3

Fiscal neutrality scoree –.053

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 251 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLI 

State Profile: Oklahoma

Table XLI.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 565 184 124 77 122 58

Total pupils 583,670 116,050 117,306 114,866 116,972 118,476

Poverty rate (percent) 20.9 26.6 22.6 17.1 15.9 22.4

Disabled rate (percent) 11.4 12.2 10.4 10.5 10.8 13.2

Per pupil income $64,014 $39,994 $51,158 $57,806 $73,948 $96,483

Tax efforta $16.45 $19.55 $19.51 $16.19 $16.53 $13.67

aLocal funding raised for every $1,000 of district income.

Table XLI.3 presents data on how state and local funding was distributed

among the five groups of Oklahoma districts. Oklahoma’s equalization

policies eliminated the 69 percent funding disparity between the wealthy

and poor groups, resulting in poor districts having about 6 percent more

funding than wealthy districts. Figure XLI.1 provides table information in

graphic form.

Table XLI.3: State and Local Funding Distribution in Oklahoma, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,047 $796 $989 $920 $1,204 $1,349 1.69

State 2,575 2,939 2,769 2,569 2,529 2,179 0.74

Total $3,623 $3,735 $3,758 $3,489 $3,732 $3,528 0.94

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 252 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLI 

State Profile: Oklahoma

Figure XLI.1: State and Local Funding

Distribution in Oklahoma, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XLI.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XLI.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XLI.3.

Table XLI.4: How State and Local Funding Would Have Been Distributed If Each District in Oklahoma Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,048 $644 $846 $963 $1,232 $1,547 2.40

State 2,574 2,979 2,777 2,660 2,391 2,076 0.70

Totalc $3,623 $3,623 $3,623 $3,623 $3,623 $3,623 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 253 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLI 

State Profile: Oklahoma

Figure XLI.2: How State and Local

Funding Would Have Been Distributed

If Each District in Oklahoma Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XLI.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Oklahoma

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

Groups of Districts

Funding Per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 254 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLII 

State Profile: Oregon

Actual Education

Funding Distribution

in School Year 1991-92

As table XLII.1 shows, in school year 1991-92, the state provided about

31 percent of the total funding to Oregon’s school districts. Total funding

(state and local funds combined) per weighted pupil in Oregon averaged

$5,087 with an implicit foundation level of $1,652 for each student, which

is about 33 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.043, indicating that state education

funds were targeted to poor districts.110 (To compare this score with those

of other states, see table V.1 in app. V.) The fiscal neutrality score was

.166, indicating that total funding increased as district income increased.

(To compare this score with those of other states, see fig. 1.) An Oregon

education official reported that the state had changed its school finance

system since school year 1991-92 to increase funding to poor districts

compared with wealthy districts (see app. LVI). To put the state’s school

finance system in perspective, table XLII.2 presents demographic data for

school year 1991-92 for five groups of districts of increasing district

income.

Table XLII.1: Summary Data for Oregon

in School Year 1991-92

Average total funding per weighted pupila $5,087

State share of total funding (percent) 31.1

Targeting score (state funds)b –.043

Implicit foundation levelc $1,652

Equalization effortd 32.5

Fiscal neutrality scoree .166

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income. The score is not significantly

different from 0.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

110However, this score is not significantly different from 0.

Page 255 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLII 

State Profile: Oregon

Table XLII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 286 91 51 31 37 76

Total pupils 497,341 100,064 98,967 100,194 104,705 93,411

Poverty rate (percent) 15.2 19.4 16.7 14.7 9.9 15.5

Disabled rate (percent) 9.3 10.0 9.6 9.5 8.7 9.0

Per pupil income $85,350 $55,212 $67,246 $78,331 $95,185 $133,320

Tax efforta $41.09 $53.06 $45.46 $40.97 $42.27 $32.74

aLocal funding raised for every $1,000 of district income.

Table XLII.3 presents data on how state and local funding was distributed

among the five groups of Oregon districts. Oregon’s equalization policies

reduced the funding disparity between the wealthy and poor groups from

about 46 to 22 percent. Figure XLII.1 provides table information in graphic

form.

Table XLII.3: State and Local Funding Distribution in Oregon, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $3,503 $2,972 $3,073 $3,211 $3,957 $4,351 1.46

State 1,584 1,888 1,602 1,664 1,285 1,559 0.83

Total $5,087 $4,860 $4,675 $4,875 $5,242 $5,910 1.22

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 256 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLII 

State Profile: Oregon

Figure XLII.1: State and Local Funding

Distribution in Oregon, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XLII.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XLII.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XLII.3.

Page 257 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLII 

State Profile: Oregon

Table XLII.4: How State and Local Funding Would Have Been Distributed If Each District in Oregon Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $3,515 $2,236 $2,748 $3,216 $3,975 $5,505 2.46

State 1,571 2,850 2,339 1,871 1,112 –418c –0.15

Totald $5,087 $5,087 $5,087 $5,087 $5,087 $5,087 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe state would have had to recapture this amount of local funding from these districts for

distribution to other districts.

dThe average is the maximum foundation level possible in a state.

Figure XLII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Oregon Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest (1,000)

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 258 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLII 

State Profile: Oregon

Figure XLII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Oregon

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest (1,000)

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 259 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLIII 

State Profile: Pennsylvania

Actual Education

Funding Distribution

in School Year 1991-92

As table XLIII.1 shows, in school year 1991-92, the state provided

43 percent of the total funding to Pennsylvania’s school districts. Total

funding (state and local funds combined) per weighted pupil in

Pennsylvania averaged $6,406 with an implicit foundation level of $3,455

for each student, which is about 54 percent of the average and represents

the state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.255,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .300, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table XLIII.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table XLIII.1: Summary Data for

Pennsylvania in School Year 1991-92

Average total funding per weighted pupila $6,406

State share of total funding (percent) 43.0

Targeting score (state funds)b –.255

Implicit foundation levelc $3,455

Equalization effortd 53.9

Fiscal neutrality scoree .300

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 260 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLIII 

State Profile: Pennsylvania

Table XLIII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 500 158 118 51 77 96

Total pupils 1,663,264 332,301 332,621 331,441 333,339 333,562

Poverty rate (percent) 15.2 20.3 14.0 22.4 13.8 5.9

Disabled rate (percent) 10.8 11.4 10.9 10.8 10.8 10.0

Per pupil income $99,378 $63,705 $81,640 $91,116 $106,597 $153,601

Tax efforta $36.63 $36.67 $37.64 $30.99 $39.05 $38.27

aLocal funding raised for every $1,000 of district income.

Table XLIII.3 presents data on how state and local funding was distributed

among the five groups of Pennsylvania districts. Pennsylvania’s

equalization policies reduced the funding disparity between the wealthy

and poor groups from about 142 to 32 percent. Figure XLIII.1 provides

table information in graphic form.

Table XLIII.3: State and Local Funding Distribution in Pennsylvania, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $3,653 $2,371 $3,071 $2,859 $4,154 $5,733 2.42

State 2,753 3,441 2,907 2,975 2,576 1,941 0.56

Total $6,406 $5,812 $5,978 $5,833 $6,730 $7,674 1.32

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 261 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLIII 

State Profile: Pennsylvania

Figure XLIII.1: State and Local Funding

Distribution in Pennsylvania, School

Year 1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XLIII.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XLIII.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XLIII.3.

Table XLIII.4: How State and Local Funding Would Have Been Distributed If Each District in Pennsylvania Could Have

Spent the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $3,672 $2,311 $3,007 $3,312 $3,935 $5,788 2.50

State $2,734 4,095 3,399 3,094 2,471 618 0.15

Totalc $6,406 $6,406 $6,406 $6,406 $6,406 $6,406 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 262 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLIII 

State Profile: Pennsylvania

Figure XLIII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Pennsylvania Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XLIII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in

Pennsylvania Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 263 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLIV 

State Profile: Rhode Island

Actual Education

Funding Distribution

in School Year 1991-92

As table XLIV.1 shows, in school year 1991-92, the state provided about

39 percent of the total funding to Rhode Island’s school districts. Total

funding (state and local funds combined) per weighted pupil in Rhode

Island averaged $5,939 with an implicit foundation level of $3,953 for each

student, which is about 67 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.694,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .274, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) A Rhode Island education official reported that the state

had changed its school finance system since school year 1991-92 to

increase funding to poor districts compared with wealthy districts (see

app. LVI). To put the state’s school finance system in perspective, table

XLIV.2 presents demographic data for school year 1991-92 for five groups

of districts of increasing district income.

Table XLIV.1: Summary Data for Rhode

Island in 1991-92

Average total funding per weighted pupila $5,939

State share of total funding (percent) 39.3

Targeting score (state funds)b –.694

Implicit foundation levelc $3,953

Equalization effortd 66.6

Fiscal neutrality scoree .274

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 264 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLIV 

State Profile: Rhode Island

Table XLIV.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 37 5 6 6 5 15

Total pupils 141,364 37,661 19,662 28,335 29,743 25,963

Poverty rate (percent) 12.8 26.7 5.0 9.9 7.7 7.3

Disabled rate (percent) 14.7 13.6 13.9 15.4 16.0 14.8

Per pupil income $108,151 $79,842 $95,443 $109,764 $118,827 $144,847

Tax efforta $33.60 $31.54 $41.78 $29.66 $35.48 $32.86

aLocal funding raised for every $1,000 of district income.

Table XLIV.3 presents data on how state and local funding was distributed

among the five groups of Rhode Island districts. Rhode Island’s

equalization policies reduced the funding disparity between the wealthy

and poor groups from about 85 to 19 percent. Figure XLIV.1 provides table

information in graphic form.

Table XLIV.3: State and Local Funding Distribution in Rhode Island, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $3,606 $2,546 $3,901 $3,264 $4,239 $4,719 1.85

State 2,333 2,961 2,325 2,365 1,904 1,834 0.62

Total $5,939 $5,507 $6,226 $5,629 $6,144 $6,553 1.19

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 265 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLIV 

State Profile: Rhode Island

Figure XLIV.1: State and Local Funding

Distribution in Rhode Island, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XLIV.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XLIV.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XLIV.3.

Table XLIV.4: How State and Local Funding Would Have Been Distributed If Each District in Rhode Island Could Have

Spent the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $3,610 $2,639 $3,253 $3,653 $3,940 $4,865 1.84

State 2,329 3,300 2,686 2,286 1,998 1,074 0.33

Totalc $5,939 $5,939 $5,939 $5,939 $5,939 $5,939 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 266 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLIV 

State Profile: Rhode Island

Figure XLIV.2: How State and Local

Funding Would Have Been Distributed

If Each District in Rhode Island Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XLIV.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Rhode

Island Could Have Spent the Average,

School Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Student Received the Average

Actual State Funding

Page 267 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLV 

State Profile: South Carolina

Actual Education

Funding Distribution

in School Year 1991-92

As table XLV.1 shows, in school year 1991-92, the state provided about

52 percent of the total funding to South Carolina’s school districts. Total

funding (state and local funds combined) per weighted pupil in South

Carolina averaged $4,112 with an implicit foundation level of $3,239 for

each student, which is about 79 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.505,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .150, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table XLV.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table XLV.1: Summary Data for South

Carolina in School Year 1991-92

Average total funding per weighted pupila $4,112

State share of total funding (percent) 52.4

Targeting score (state funds)b –.505

Implicit foundation levelc $3,239

Equalization effortd 78.8

Fiscal neutrality scoree .150

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 268 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLV 

State Profile: South Carolina

Table XLV.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 91 36 24 15 11 5

Total pupils 625,839 127,515 125,497 122,407 110,791 139,629

Poverty rate (percent) 20.8 29.8 22.2 14.7 16.4 20.2

Disabled rate (percent) 10.9 10.7 11.5 9.7 11.4 11.4

Per pupil income $65,707 $44,530 $56,351 $65,417 $73,981 $87,143

Tax efforta $29.70 $30.40 $31.82 $29.03 $32.92 $26.48

aLocal funding raised for every $1,000 of district income.

Table XLV.3 presents data on how state and local funding was distributed

among the five groups of South Carolina districts. South Carolina’s

equalization policies reduced the funding disparity between the wealthy

and poor groups from about 69 to 8 percent. Figure XLV.1 provides table

information in graphic form.

Table XLV.3: State and Local Funding Distribution in South Carolina, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,959 $1,371 $1,807 $1,854 $2,429 $2,317 1.69

State 2,153 2,470 2,328 2,242 1,949 1,834 0.74

Total $4,112 $3,840 $4,136 $4,096 $4,378 $4,151 1.08

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 269 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLV 

State Profile: South Carolina

Figure XLV.1: State and Local Funding

Distribution in South Carolina, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XLV.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XLV.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XLV.3.

Table XLV.4: How State and Local Funding Would Have Been Distributed If Each District in South Carolina Could Have

Spent the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,964 $1,319 $1,669 $1,998 $2,216 $2,589 1.96

State 2,148 2,793 2,444 2,115 1,897 1,523 0.55

Totalc $4,112 $4,112 $4,112 $4,112 $4,112 $4,112 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 270 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLV 

State Profile: South Carolina

Figure XLV.2: How State and Local

Funding Would Have Been Distributed

If Each District in South Carolina

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XLV.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in South

Carolina Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

3,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 271 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLVI 

State Profile: South Dakota

Actual Education

Funding Distribution

in School Year 1991-92

As table XLVI.1 shows, in school year 1991-92, the state provided about

30 percent of the total funding to South Dakota’s school districts. Total

funding (state and local funds combined) per weighted pupil in South

Dakota averaged $3,756 with an implicit foundation level of $1,109 for

each student, which is about 30 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was .000, indicating

that state education funds were not targeted to poor or wealthy districts.111

 (To compare this score with those of other states, see table V.1 in app. V.)

The fiscal neutrality score was .367, indicating that total funding increased

as district income increased. (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table XLVI.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table XLVI.1: Summary Data for South

Dakota in School Year 1991-92

Average total funding per weighted pupila $3,756

State share of total funding (percent) 29.5

Targeting score (state funds)b .000

Implicit foundation levelc $1,109

Equalization effortd 29.5

Fiscal neutrality scoree .367

aThe average is the maximum foundation level possible in a state.

bThis is the constrained score (elasticity of state funding relative to district income) used to

calculate the state’s implicit foundation level. The actual targeting elasticity is .116, which is not

statistically different from 0.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

111This is the constrained targeting score used to calculate the state’s implicit foundation level. This

differs from the actual targeting score found in table V.1 in app. V.

Page 272 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLVI 

State Profile: South Dakota

Table XLVI.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 161 55 47 24 20 15

Total pupils 124,665 25,208 22,748 31,388 20,232 25,089

Poverty rate (percent) 18.2 29.1 20.6 16.0 14.3 11.2

Disabled rate (percent) 9.8 10.8 8.7 8.8 9.5 11.5

Per pupil income $57,440 $37,717 $50,120 $57,730 $63,374 $78,745

Tax efforta $46.52 $50.90 $54.34 $46.47 $44.77 $41.36

aLocal funding raised for every $1,000 of district income.

Table XLVI.3 presents data on how state and local funding was distributed

among the five groups of South Dakota districts. South Dakota’s

equalization policies reduced the funding disparity between the wealthy

and poor groups from about 66 to 28 percent. Figure XLVI.1 provides table

information in graphic form.

Table XLVI.3: State and Local Funding Distribution in South Dakota, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,648 $1,977 $2,698 $2,642 $2,807 $3,276 1.66

State 1,109 1,320 1,305 994 1,069 952 0.72

Total $3,756 $3,297 $4,003 $3,636 $3,876 $4,228 1.28

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 273 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLVI 

State Profile: South Dakota

Figure XLVI.1: State and Local Funding

Distribution in South Dakota, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XLVI.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XLVI.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XLVI.3.

Table XLVI.4: How State and Local Funding Would Have Been Distributed If Each District in South Dakota Could Have

Spent the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,658 $1,705 $2,339 $2,703 $2,954 $3,608 2.12

State 1,099 2,052 1,418 1,053 802 148 0.07

Totalc $3,756 $3,756 $3,756 $3,756 $3,756 $3,756 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 274 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLVI 

State Profile: South Dakota

Figure XLVI.2: How State and Local

Funding Would Have Been Distributed

If Each District in South Dakota Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XLVI.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in South

Dakota Could Have Spent the Average,

School Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

State if Each Student Received the Average

Actual State Funding

Page 275 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLVII 

State Profile: Tennessee

Actual Education

Funding Distribution

in School Year 1991-92

As table XLVII.1 shows, in school year 1991-92, the state provided

47 percent of the total funding to Tennessee’s school districts. Total

funding (state and local funds combined) per weighted pupil in Tennessee

averaged $3,329 with an implicit foundation level of $1,566 for each

student, which is 47 percent of the average and represents the state’s

equalization effort. (To compare this effort with those of other states, see

fig. 5.) The targeting score for state funding was .000, indicating that state

education funds were not targeted to poor or wealthy districts.112 (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .242, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) A Tennessee education official reported that the state

had changed its school finance system since school year 1991-92 to

increase funding to poor districts compared with wealthy districts (see

app. LVI). To put the state’s school finance system in perspective, table

XLVII.2 presents demographic data for school year 1991-92 for five groups

of districts of increasing district income.

Table XLVII.1: Summary Data for

Tennessee in School Year 1991-92

Average total funding per weighted pupila $3,329

State share of total funding (percent) 47.0

Targeting score (state funds)b .000

Implicit foundation levelc $1,566

Equalization effortd 47.0

Fiscal neutrality scoree .242

aThe average is the maximum foundation level possible in a state.

bThis is the constrained score (elasticity of state funding relative to district income) used to

calculate the state’s implicit foundation level. The actual targeting elasticity is .017, which is not

statistically different from 0.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

112This is the constrained targeting score used to calculate the state’s implicit foundation level. This

differs from the actual targeting score found in table V.1 in app. V.

Page 276 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLVII 

State Profile: Tennessee

Table XLVII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 134 45 38 16 26 9

Total pupils 830,038 162,495 168,648 175,240 137,994 185,661

Poverty rate (percent) 20.4 22.8 19.4 26.8 17.6 15.4

Disabled rate (percent) 11.9 13.1 12.9 10.4 12.1 11.2

Per pupil income $70,681 $45,784 $58,753 $65,648 $80,007 $101,123

Tax efforta $24.82 $29.77 $21.53 $29.62 $24.32 $22.13

aLocal funding raised for every $1,000 of district income.

Table XLVII.3 presents data on how state and local funding was

distributed among the five groups of Tennessee districts. Tennessee’s

equalization policies reduced the funding disparity between the wealthy

and poor groups from about 59 to 21 percent. Figure XLVII.1 provides

table information in graphic form.

Table XLVII.3: State and Local Funding Distribution in Tennessee, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,763 $1,386 $1,276 $1,934 $1,941 $2,202 1.59

State 1,566 1,653 1,580 1,567 1,601 1,469 0.89

Total $3,329 $3,038 $2,856 $3,501 $3,541 $3,671 1.21

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 277 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLVII 

State Profile: Tennessee

Figure XLVII.1: State and Local

Funding Distribution in Tennessee,

School Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XLVII.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XLVII.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XLVII.3.

Table XLVII.4: How State and Local Funding Would Have Been Distributed If Each District in Tennessee Could Have Spent

the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,770 $1,125 $1,452 $1,647 $2,004 $2,566 2.28

State 1,559 2,205 1,877 1,682 1,325 763 0.35

Totalc $3,329 $3,329 $3,329 $3,329 $3,329 $3,329 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 278 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLVII 

State Profile: Tennessee

Figure XLVII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Tennessee Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XLVII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Tennessee

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 279 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLVIII 

State Profile: Texas

Actual Education

Funding Distribution

in School Year 1991-92

As table XLVIII.1 shows, in school year 1991-92, the state provided about

47 percent of the total funding to Texas’ school districts. Total funding

(state and local funds combined) per weighted pupil in Texas averaged

$4,603 with an implicit foundation level of $3,318 for each student, which

is about 72 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.522, indicating that state education

funds were targeted to poor districts. (To compare this score with those of

other states, see table V.1 in app. V.) The fiscal neutrality score was .003,

indicating that total funding increased as district income increased.113 (To

compare this score with those of other states, see fig. 1.) A Texas

education official reported that the state had changed its school finance

system since school year 1991-92 to increase funding to poor districts

compared with wealthy districts (see app. LVI). To put the state’s school

finance system in perspective, table XLVIII.2 presents demographic data

for school year 1991-92 for five groups of districts of increasing district

income.

Table XLVIII.1: Summary Data for

Texas in School Year 1991-92

Average total funding per weighted pupila $4,603

State share of total funding (percent) 47.4

Targeting score (state funds)b –.522

Implicit foundation levelc $3,318

Equalization effortd 72.1

Fiscal neutrality scoree .003

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income. The score is not

significantly different from 0.

113However, this score is not significantly different from 0.

Page 280 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLVIII 

State Profile: Texas

Table XLVIII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 1,046 222 326 256 80 162

Total pupils 3,462,964 693,672 691,190 700,596 692,550 684,956

Poverty rate (percent) 24.4 42.2 23.8 17.2 21.2 17.6

Disabled rate (percent) 9.9 9.1 10.4 10.7 9.9 9.5

Per pupil income $62,842 $30,006 $51,336 $63,427 $73,839 $95,988

Tax efforta $38.73 $44.82 $44.48 $38.37 $34.41 $37.74

aLocal funding raised for every $1,000 of district income.

Table XLVIII.3 presents data on how state and local funding was

distributed among the five groups of Texas districts. Texas’ equalization

policies eliminated the funding disparity between the wealthy and poor

groups. Figure XLVIII.1 provides table information in graphic form.

Table XLVIII.3: State and Local Funding Distribution in Texas, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupilighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,423 $1,373 $2,293 $2,424 $2,527 $3,566 2.60

State 2,180 3,316 2,500 2,230 1,851 1,126 0.34

Total $4,603 $4,689 $4,792 $4,654 $4,379 $4,691 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 281 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLVIII 

State Profile: Texas

Figure XLVIII.1: State and Local

Funding Distribution in Texas, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XLVIII.4 provides data on the distribution of state and local funding

if all districts could have spent the average total funding per weighted

pupil with an average tax effort. This assumes the state optimized its

targeting effort without changing the state share or the total funding for

education. Under this scenario, the implicit foundation level equals the

maximum possible foundation level (the state average). Figure XLVIII.2

provides this information in graphic form. The difference between how

state funding was actually distributed and how it would have been

distributed if districts could have financed the average is shown in figure

XLVIII.3.

Page 282 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLVIII 

State Profile: Texas

Table XLVIII.4: How State and Local Funding Would Have Been Distributed If Each District in Texas Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,437 $1,136 $1,975 $2,459 $2,864 $3,765 3.31

State 2,166 3,467 2,628 2,144 1,739 837 0.24

Totalc $4,603 $4,603 $4,603 $4,603 $4,603 $4,603 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Figure XLVIII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Texas Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 283 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLVIII 

State Profile: Texas

Figure XLVIII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Texas Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 284 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLIX 

State Profile: Utah

Actual Education

Funding Distribution

in School Year 1991-92

As table XLIX.1 shows, in school year 1991-92, the state provided about

60 percent of the total funding to Utah’s school districts. Total funding

(state and local funds combined) per weighted pupil in Utah averaged

$3,177 with an implicit foundation level of $2,240 for each student, which

is about 71 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was –.172, indicating that state education

funds were targeted to poor districts.114 (To compare this score with those

of other states, see table V.1 in app. V.) The fiscal neutrality score was

.036, indicating that total funding increased as district income increased.115

 (To compare this score with those of other states, see fig. 1.) A Utah

education official reported that the state had changed its school finance

system since school year 1991-92 to increase funding to poor districts

compared with wealthy districts (see app. LVI). To put the state’s school

finance system in perspective, table XLIX.2 presents demographic data for

school year 1991-92 for five groups of districts of increasing district

income.

Table XLIX.1: Summary Data for Utah

in School Year 1991-92

Average total funding per weighted pupila $3,177

State share of total funding (percent) 60.2

Targeting score (state funds)b –.172

Implicit foundation levelc $2,240

Equalization effortd 70.5

Fiscal neutrality scoree .036

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income. The score is not significantly

different from 0.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income. The score is not

significantly different from 0.

114However, this score is not significantly different from 0.

115See footnote 114.

Page 285 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLIX 

State Profile: Utah

Table XLIX.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 40 16 12 2 1a 9

Total pupils 456,552 105,334 47,601 123,040 80,330 100,247

Poverty rate (percent) 12.1 13.3 13.1 7.8 12.2 15.6

Disabled rate (percent) 10.6 11.2 10.4 9.8 9.5 12.2

Per pupil income $41,385 $28,599 $35,986 $39,903 $43,367 $57,616

Tax effortb $30.43 $45.72 $37.21 $27.55 $23.50 $26.86

aSalt Lake City was the only district in this group.

bLocal funding raised for every $1,000 of district income.

Table XLIX.3 presents data on how state and local funding was distributed

among the five groups of Utah districts. Utah’s equalization policies

eliminated the funding disparity between the wealthy and poor groups,

resulting in poor districts having 1 percent more funding than wealthy

districts. Figure XLIX.1 provides table information in graphic form.

Table XLIX.3: State and Local Funding Distribution in Utah, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,266 $1,318 $1,338 $1,081 $1,006 $1,583 1.20

State 1,911 $2,015 $2,103 $2,001 $1,804 $1,718 0.85

Total $3,177 $3,333 $3,441 $3,082 $2,809 $3,301 0.99

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 286 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLIX 

State Profile: Utah

Figure XLIX.1: State and Local Funding

Distribution in Utah, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table XLIX.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure XLIX.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure XLIX.3.

Table XLIX.4: How State and Local Funding Would Have Been Distributed If Each District in Utah Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,265 $870 $1,102 $1,242 $1,344 $1,724 1.98

State 1,911 2,307 2,075 1,935 1,833 1,453 0.63

Totalc $3,177 $3,177 $3,177 $3,177 $3,177 $3,177 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 287 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix XLIX 

State Profile: Utah

Figure XLIX.2: How State and Local

Funding Would Have Been Distributed

If Each District in Utah Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure XLIX.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Utah Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

500

1,000

1,500

2,000

2,500

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 288 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix L 

State Profile: Vermont

Actual Education

Funding Distribution

in School Year 1991-92

As table L.1 shows, in school year 1991-92, the state provided 29 percent of

the total funding to Vermont’s school districts. Total funding (state and

local funds combined) per weighted pupil in Vermont averaged $7,722 with

an implicit foundation level of $3,453 for each student, which is about

45 percent of the average and represents the state’s equalization effort. (To

compare this effort with those of other states, see fig. 5.) The targeting

score for state funding was –.539, indicating that state education funds

were targeted to poor districts. (To compare this score with those of other

states, see table V.1 in app. V.) The fiscal neutrality score was .176,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) To put the state’s

school finance system in perspective, table L.2 presents demographic data

for school year 1991-92 for five groups of districts of increasing district

income.

Table L.1: Summary Data for Vermont

in School Year 1991-92

Average total funding per weighted pupila $7,722

State share of total funding (percent) 29.0

Targeting score (state funds)b –.539

Implicit foundation levelc $3,453

Equalization effortd 44.7

Fiscal neutrality scoree .176

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 289 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix L 

State Profile: Vermont

Table L.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 236 39 44 56 52 45

Total pupils 92,491 18,516 17,861 19,128 17,890 19,096

Poverty rate (percent) 11.8 14.2 11.4 10.6 10.5 12.2

Disabled rate (percent) 10.4 11.0 10.3 11.0 10.4 9.6

Per pupil income $112,652 $56,715 $83,165 $102,725 $131,592 $186,672

Tax efforta $48.97 $66.35 $50.78 $54.05 $50.74 $39.30

aLocal funding raised for every $1,000 of district income.

Table L.3 presents data on how state and local funding was distributed

among the five groups of Vermont districts. Vermont’s equalization

policies reduced the funding disparity between the wealthy and poor

groups from about 91 to 31 percent. Figure L.1 provides table information

in graphic form.

Table L.3: State and Local Funding Distribution in Vermont, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $5,479 $3,800 $4,212 $5,577 $6,656 $7,273 1.91

State 2,243 2,677 3,019 2,657 1,825 1,180 0.44

Total $7,722 $6,478 $7,231 $8,233 $8,481 $8,454 1.31

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 290 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix L 

State Profile: Vermont

Figure L.1: State and Local Funding

Distribution in Vermont, School Year

1991-92

Poorest Wealthiest

0

2,000

4,000

6,000

8,000

10,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table L.4 provides data on the distribution of state and local funding if all

districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure L.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure L.3.

Page 291 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix L 

State Profile: Vermont

Table L.4: How State and Local Funding Would Have Been Distributed If Each District in Vermont Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $5,507 $2,736 $4,063 $4,983 $6,439 $9,198 3.36

State 2,214 4,986 3,659 2,739 1,283 –1,476c –0.30

Totald $7,722 $7,722 $7,722 $7,722 $7,722 $7,722 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe state would have had to recapture this amount of local funding from these districts for

distribution to other districts.

dThe average is the maximum foundation level possible in a state.

Figure L.2: How State and Local

Funding Would Have Been Distributed

If Each District in Vermont Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest (2,000)

0

2,000

4,000

6,000

8,000

10,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 292 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix L 

State Profile: Vermont

Figure L.3: Comparison of Actual State

Funding With State Funding Assuming

Each District in Vermont Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest (2,000)

0

2,000

4,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 293 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LI 

State Profile: Virginia

Actual Education

Funding Distribution

in School Year 1991-92

As table LI.1 shows, in school year 1991-92, the state provided 36 percent

of the total funding to Virginia’s school districts. Total funding (state and

local funds combined) per weighted pupil in Virginia averaged $4,713 with

an implicit foundation level of $2,541 for each student, which is about

54 percent of the average and represents the state’s equalization effort. (To

compare this effort with those of other states, see fig. 5.) The targeting

score for state funding was –.499, indicating that state education funds

were targeted to poor districts. (To compare this score with those of other

states, see table V.1 in app. V.) The fiscal neutrality score was .377,

indicating that total funding increased as district income increased. (To

compare this score with those of other states, see fig. 1.) To put the state’s

school finance system in perspective, table LI.2 presents demographic data

for school year 1991-92 for five groups of districts of increasing district

income.

Table LI.1: Summary Data for Virginia

in School Year 1991-92

Average total funding per weighted pupila $4,713

State share of total funding (percent) 36.0

Targeting score (state funds)b –.499

Implicit foundation levelc $2,541

Equalization effortd 53.9

Fiscal neutrality scoree .377

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 294 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LI 

State Profile: Virginia

Table LI.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 133 40 37 9 34 13

Total pupils 1,017,948 205,812 201,384 223,676 185,625 201,451

Poverty rate (percent) 13.4 20.3 15.4 10.5 14.9 6.0

Disabled rate (percent) 11.3 10.6 10.4 10.8 12.1 12.8

Per pupil income $93,199 $62,643 $74,607 $80,465 $101,389 $149,596

Tax efforta $31.55 $28.65 $28.34 $31.86 $34.66 $32.15

aLocal funding raised for every $1,000 of district income.

Table LI.3 presents data on how state and local funding was distributed

among the five groups of Virginia districts. Virginia’s equalization policies

reduced the funding disparity between the wealthy and poor groups from

about 168 to 38 percent. Figure LI.1 provides table information in graphic

form.

Table LI.3: State and Local Funding Distribution in Virginia, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $3,018 $1,802 $2,100 $2,537 $3,555 $4,828 2.68

State 1,695 2,336 2,110 1,718 1,612 874 0.37

Total $4,713 $4,138 $4,210 $4,255 $5,167 $5,701 1.38

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 295 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LI 

State Profile: Virginia

Figure LI.1: State and Local Funding

Distribution in Virginia, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table LI.4 provides data on the distribution of state and local funding if all

districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure LI.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure LI.3.

Page 296 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LI 

State Profile: Virginia

Table LI.4: How State and Local Funding Would Have Been Distributed If Each District in Virginia Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $3,014 $2,026 $2,434 $2,634 $3,248 $4,813 2.38

State 1,699 2,687 2,279 2,079 1,465 –$100c –0.04

Totald $4,713 $4,713 $4,713 $4,713 $4,713 $4,713 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe state would have had to recapture this amount of local funding from these districts for

distribution to other districts.

dThe average is the maximum foundation level possible in a state.

Figure LI.2: How State and Local

Funding Would Have Been Distributed

If Each District in Virginia Could Have

Spent the Average, School Year

1991-92

Poorest Wealthiest (1,000)

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Page 297 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LI 

State Profile: Virginia

Figure LI.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Virginia

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest (500)

0

500

1,000

1,500

2,000

2,500

3,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 298 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LII 

State Profile: Washington

Actual Education

Funding Distribution

in School Year 1991-92

As table LII.1 shows, in school year 1991-92, the state provided about

75 percent of the total funding to Washington’s school districts. Total

funding (state and local funds combined) per weighted pupil in

Washington averaged $5,302 with an implicit foundation level of $4,025 for

each student, which is about 76 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.009,

indicating that state education funds were targeted to poor districts.116 (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .055, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table LII.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table LII.1: Summary Data for

Washington in School Year 1991-92

Average total funding per weighted pupila $5,302

State share of total funding (percent) 75.2

Targeting score (state funds)b –.009

Implicit foundation levelc $4,025

Equalization effortd 75.9

Fiscal neutrality scoree .055

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income. The score is not significantly

different from 0.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

116However, this score is not significantly different from 0.

Page 299 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LII 

State Profile: Washington

Table LII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 290 104 50 45 43 48

Total pupils 860,198 176,414 166,660 179,429 170,415 167,280

Poverty rate (percent) 14.3 20.8 12.3 14.5 13.3 10.4

Disabled rate (percent) 9.6 10.3 9.5 10.4 8.8 8.8

Per pupil income $82,373 $50,688 $64,265 $73,890 $87,323 $137,883

Tax efforta $15.84 $17.72 $17.93 $17.14 $15.96 $13.44

aLocal funding raised for every $1,000 of district income.

Table LII.3 presents data on how state and local funding was distributed

among the five groups of Washington districts. Washington’s equalization

policies reduced the funding disparity between the wealthy and poor

groups from about 99 to 4 percent. Figure LII.1 provides table information

in graphic form.

Table LII.3: State and Local Funding Distribution in Washington, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,314 $915 $1,147 $1,279 $1,379 $1,824 1.99

State 3,988 4,337 4,094 4,013 4,003 3,657 0.84

Total $5,302 $5,252 $,5241 $5,292 $5,382 $5,481 1.04

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 300 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LII 

State Profile: Washington

Figure LII.1: State and Local Funding

Distribution in Washington, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table LII.4 provides data on the distribution of state and local funding if all

districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure LII.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure LII.3.

Table LII.4: How State and Local Funding Would Have Been Distributed If Each District in Washington Could Have Spent

the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,320 $797 $1,031 $1,169 $1,408 $2,233 2.80

State 3,981 4,505 4,271 4,132 3,894 3,069 0.68

Totalc $5,302 $5,302 $5,302 $5,302 $5,302 $5,302 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 301 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LII 

State Profile: Washington

Figure LII.2: How State and Local

Funding Would Have Been Distributed

If Each District in Washington Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure LII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Washington

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 302 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LIII 

State Profile: West Virginia

Actual Education

Funding Distribution

in School Year 1991-92

As table LIII.1 shows, in school year 1991-92, the state provided about

73 percent of the total funding to West Virginia’s school districts. Total

funding (state and local funds combined) per weighted pupil in West

Virginia averaged $4,927 with an implicit foundation level of $4,028 for

each student, which is about 82 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.127,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .071, indicating that total funding increased as

district income increased.117 (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table LIII.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table LIII.1: Summary Data for West

Virginia in School Year 1991-92

Average total funding per weighted pupila $4,927

State share of total funding (percent) 72.5

Targeting score (state funds)b –.127

Implicit foundation levelc $4,028

Equalization effortd 81.8

Fiscal neutrality scoree .071

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income. The score is not

significantly different from 0.

117However, this score is not significantly different from 0.

Page 303 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LIII 

State Profile: West Virginia

Table LIII.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 55 15 17 12 6 5

Total pupils 320,249 61,797 66,219 69,242 52,010 70,981

Poverty rate (percent) 25.6 37.7 27.5 22.8 18.6 21.1

Disabled rate (percent) 13.4 14.0 14.2 12.8 12.9 13.0

Per pupil income $58,725 $38,898 $48,913 $57,314 $66,647 $80,711

Tax efforta $23.03 $25.84 $22.84 $21.44 $25.09 $22.05

aLocal funding raised for every $1,000 of district income.

Table LIII.3 presents data on how state and local funding was distributed

among the five groups of West Virginia districts. West Virginia’s

equalization policies reduced the funding disparity between the wealthy

and poor groups from about 70 to 4 percent. Figure LIII.1 provides table

information in graphic form.

Table LIII.3: State and Local Funding Distribution in West Virginia, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $1,353 $1,032 $1,130 $1,216 $1,645 $1,759 1.70

State 3,574 3,827 3,698 3,624 3,462 3,284 0.86

Total $4,927 $4,859 $4,828 $4,840 $5,107 $5,044 1.04

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 304 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LIII 

State Profile: West Virginia

Figure LIII.1: State and Local Funding

Distribution in West Virginia, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table LIII.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure LIII.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure LIII.3.

Table LIII.4: How State and Local Funding Would Have Been Distributed If Each District in West Virginia Could Have Spent

the Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $1,358 $874 $1,114 $1,335 $1,561 $1,882 2.15

State 3,569 4,053 3,813 3,592 3,367 3,045 0.75

Totalc $4,927 $4,927 $4,927 $4,927 $4,927 $4,927 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 305 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LIII 

State Profile: West Virginia

Figure LIII.2: How State and Local

Funding Would Have Been Distributed

If Each District in West Virginia Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure LIII.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in West

Virginia Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 306 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LIV 

State Profile: Wisconsin

Actual Education

Funding Distribution

in School Year 1991-92

As table LIV.1 shows, in school year 1991-92, the state provided about

46 percent of the total funding to Wisconsin’s school districts. Total

funding (state and local funds combined) per weighted pupil in Wisconsin

averaged $5,865 with an implicit foundation level of $3,439 for each

student, which is about 59 percent of the average and represents the

state’s equalization effort. (To compare this effort with those of other

states, see fig. 5.) The targeting score for state funding was –.270,

indicating that state education funds were targeted to poor districts. (To

compare this score with those of other states, see table V.1 in app. V.) The

fiscal neutrality score was .129, indicating that total funding increased as

district income increased. (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table LIV.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table LIV.1: Summary Data for

Wisconsin in School Year 1991-92

Average total funding per weighted pupila $5,865

State share of total funding (percent) 46.2

Targeting score (state funds)b –.270

Implicit foundation levelc $3,439

Equalization effortd 58.6

Fiscal neutrality scoree .129

aThe average is the maximum foundation level possible in a state.

bThis is the elasticity of state funding relative to district income.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income.

Page 307 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LIV 

State Profile: Wisconsin

Table LIV.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 426 168 47 79 42 90

Total pupils 813,614 162,519 163,918 160,381 164,659 162,137

Poverty rate (percent) 14.1 16.0 25.8 10.4 10.8 7.2

Disabled rate (percent) 11.0 10.9 11.6 11.0 11.4 10.2

Per pupil income $82,555 $56,430 $68,951 $75,869 $85,530 $126,089

Tax efforta $38.31 $47.27 $32.46 $40.43 $36.99 $37.63

aLocal funding raised for every $1,000 of district income.

Table LIV.3 presents data on how state and local funding was distributed

among the five groups of Wisconsin districts. Wisconsin’s equalization

policies reduced the funding disparity between the wealthy and poor

groups from about 74 to about 8 percent. Figure LIV.1 provides table

information in graphic form.

Table LIV.3: State and Local Funding Distribution in Wisconsin, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $3,157 $2,673 $2,297 $3,049 $3,158 $4,647 1.74

State 2,707 3,301 3,234 2,777 2,457 1,808 0.55

Total $5,865 $5,974 $5,531 $5,825 $5,615 $6,455 1.08

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 308 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LIV 

State Profile: Wisconsin

Figure LIV.1: State and Local Funding

Distribution in Wisconsin, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table LIV.4 provides data on the distribution of state and local funding if

all districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure LIV.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure LIV.3.

Table LIV.4: How State and Local Funding Would Have Been Distributed If Each District in Wisconsin Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $3,176 $2,158 $2,571 $2,921 $3,278 $4,954 2.30

State 2,689 3,707 3,294 2,944 2,586 911 0.25

Totalc $5,865 $5,865 $5,865 $5,865 $5,865 $5,865 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 309 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LIV 

State Profile: Wisconsin

Figure LIV.2: How State and Local

Funding Would Have Been Distributed

If Each District in Wisconsin Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure LIV.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Wisconsin

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 310 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LV 

State Profile: Wyoming

Actual Education

Funding Distribution

in School Year 1991-92

As table LV.1 shows, in school year 1991-92, the state provided about

53 percent of the total funding to Wyoming’s school districts. Total funding

(state and local funds combined) per weighted pupil in Wyoming averaged

$5,920 with an implicit foundation level of $3,111 for each student, which

is about 53 percent of the average and represents the state’s equalization

effort. (To compare this effort with those of other states, see fig. 5.) The

targeting score for state funding was .000, indicating that state education

funds were not targeted to poor or wealthy districts.118 (To compare this

score with those of other states, see table V.1 in app. V.) The fiscal

neutrality score was –.196, indicating that total funding increased as

district income decreased.119 (To compare this score with those of other

states, see fig. 1.) To put the state’s school finance system in perspective,

table LV.2 presents demographic data for school year 1991-92 for five

groups of districts of increasing district income.

Table LV.1: Summary Data for

Wyoming in School Year 1991-92

Average total funding per weighted pupila $5,920

State share of total funding (percent) 52.5

Targeting score (state funds)b .000

Implicit foundation levelc $3,111

Equalization effortd 52.5

Fiscal neutrality scoree –.196

aThe average is the maximum foundation level possible in a state.

bThis is the constrained score (elasticity of state funding relative to district income) used to

calculate the state’s implicit foundation level. The actual targeting elasticity is .296, which is not

statistically different from 0.

cThis is the minimum amount of total funding the state’s equalization policies would enable

districts to spend for each student, assuming all districts had made the same minimum tax effort.

dThis is the implicit foundation as a percent of the average.

eThis is the elasticity of total (state and local) funding relative to district income. The score is not

significantly different from 0.

118This is the constrained targeting score used to calculate the state’s implicit foundation level. This

differs from the actual targeting score found in table V.1 in app. V.

119However, this score is not significantly different from 0.

Page 311 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LV 

State Profile: Wyoming

Table LV.2: Demographic Context in School Year 1991-92

Poorest Wealthiest

State Group 1 Group 2 Group 3 Group 4 Group 5

Total districts 49 17 10 13 5 4

Total pupils 101,017 20,293 19,411 21,327 19,421 20,565

Poverty rate (percent) 13.8 14.5 12.9 13.9 14.3 13.2

Disabled rate (percent) 10.3 9.5 9.7 11.2 11.0 9.7

Per pupil income $55,152 $37,739 $48,824 $55,741 $61,767 $71,450

Tax efforta $51.22 $90.83 $82.84 $59.54 $28.88 $21.79

aLocal funding raised for every $1,000 of district income.

Table LV.3 presents data on how state and local funding was distributed

among the five groups of Wyoming districts. Wyoming’s equalization

policies resulted in wealthy districts having 16 percent less funding than

poor districts. Figure LV.1 provides table information in graphic form.

Table LV.3: State and Local Funding Distribution in Wyoming, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Local $2,810 $3,405 $4,015 $3,355 $1,801 $1,546 0.45

State 3,111 3,169 2,148 2,782 3,516 3,968 1.25

Total $5,920 $6,573 $6,163 $6,137 $5,317 $5,514 0.84

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

Page 312 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LV 

State Profile: Wyoming

Figure LV.1: State and Local Funding

Distribution in Wyoming, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

How Funding Would

Have Been

Distributed If Districts

Could Have Spent the

Average on Each

Student

Table LV.4 provides data on the distribution of state and local funding if all

districts could have spent the average total funding per weighted pupil

with an average tax effort. This assumes the state optimized its targeting

effort without changing the state share or the total funding for education.

Under this scenario, the implicit foundation level equals the maximum

possible foundation level (the state average). Figure LV.2 provides this

information in graphic form. The difference between how state funding

was actually distributed and how it would have been distributed if districts

could have financed the average is shown in figure LV.3.

Table LV.4: How State and Local Funding Would Have Been Distributed If Each District in Wyoming Could Have Spent the

Average, School Year 1991-92

Poorest Wealthiest

Mean funding per weighted pupil

Funding source State Group 1 Group 2 Group 3 Group 4 Group 5

Funding of

wealthiest group

compared with

poorest groupa

Localb $2,811 $1,939 $2,509 $2,811 $3,117 $3,667 1.89

State 3,109 3,981 3,411 3,109 2,803 2,253 0.57

Totalc $5,920 $5,920 $5,920 $5,920 $5,920 $5,920 1.00

aThis ratio is determined by dividing the wealthiest districts’ funding by the poorest districts’

funding.

bThis is the local funding that could have been raised assuming all districts had made the same

average tax effort.

cThe average is the maximum foundation level possible in a state.

Page 313 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LV 

State Profile: Wyoming

Figure LV.2: How State and Local

Funding Would Have Been Distributed

If Each District in Wyoming Could

Have Spent the Average, School Year

1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

Local Funding

State Funding

Figure LV.3: Comparison of Actual

State Funding With State Funding

Assuming Each District in Wyoming

Could Have Spent the Average, School

Year 1991-92

Poorest Wealthiest

0

1,000

2,000

3,000

4,000

5,000

Groups of Districts

Funding per Weighted Pupil (Dollars)

State Funding if Each Student Received the Average

Actual State Funding

Page 314 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LVI 

State Survey Results

In this report, we relied on state and local funding data from the 1991-92

school year. However, many states have made subsequent changes to their

school finance system in response to legal changes or to concerns about

equity. We telephoned officials in the 49 states to determine what changes

had been implemented in the school finance system from school years

1991-92 through 1995-96. We specifically asked about changes in targeting

that would affect low-wealth districts and changes in a state’s share of

total funding.120 These two factors affect the implicit foundation level that

all districts in a state can finance with the same minimum tax effort—the

greater the targeting effort to low-wealth districts or the greater the state

share, or both, the greater the implicit foundation level.

Education officials in over half the states (25) said their state had not

increased the targeting of state funds to low-wealth districts since school

year 1991-92. Officials in the other 24 states reported that their state was

targeting more or many more state funds to low-wealth districts. We did

not verify the statements of the state officials.

Fewer states had increased the state share of total funding significantly.

Officials in eight states reported an increase of 6 percentage points or

more in the state share. Officials in 38 states reported that their state’s

share of total funding had a net increase or decrease of 5 percentage

points or less, and 3 states reported a decrease of 6 percentage points or

more.121

Among the states that had changed their finance system were Missouri and

Michigan. These states reported using different approaches to raise

revenue and target more funds to low-wealth districts. Missouri’s state

share declined slightly, but changes implemented in 1993 resulted in

increased targeting to low-wealth districts. The state developed a new

formula that rewards districts for tax effort—the lower the property

wealth and the higher the tax rate, the more state funding a district

receives. In Michigan, the state share increased almost 45 percentage

points between school years 1991-92 and 1994-95 as statewide property

and sales taxes replaced the local property tax as the principal source of

funding. Since 1994 (the year the new system was implemented), the

lowest wealth districts have experienced an increase of about 50 percent

in state funding; the highest wealth districts, however, have had to raise

120Not all states had school year 1995-96 data available: seven states reported changes as of school year

1994-95, and two states reported changes as of school year 1993-94.

121Because not all state officials knew the local contribution for capital expenditures and debt service,

we asked state officials to estimate their state’s share of total funding exclusive of these categories.

Page 315 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LVI 

State Survey Results

their local property taxes to maintain former spending levels. Table LVI.1

summarizes our findings of the changes states have made.

Table LVI.1: Summary of Changes to State School Finance Systems, School Years 1991-92 to 1995-96

1995-96 targeting to low-wealth districts compared with 1991-92

State

Change in state

share (percentage

points) Much more More Same Less

Alabama 3.2 X

Alaska –0.8 X

Arizona 2.0 X

Arkansas 6.0 X

Californiaa –9.7 X

Colorado 11.2 X

Connecticutb –1.4 X

Delaware –1.6 X

Florida –0.3 X

Georgia 2.2 X

Idahob 0.4 X

Illinoisa –1.1 X

Indianab 2.2 X

Iowa 0.8 X

Kansas 17.6 X

Kentucky 2.4 X

Louisiana –6.0 X

Maine –5.0 X

Maryland –1.1 X

Massachusetts 8.0 X

Michiganb 44.9 X

Minnesota 0.4 X

Mississippi 2.2 X

Missouri –1.3 X

Montana –4.9 X

Nebraska 0.2 X

Nevada –6.9 X

New Hampshire –1.0 X

New Jersey –5.0 X

New Mexico 0.0 X

New York –3.2 X

North Carolina –1.0 X

North Dakota –4.0 X

(continued)

Page 316 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LVI 

State Survey Results

1995-96 targeting to low-wealth districts compared with 1991-92

State

Change in state

share (percentage

points) Much more More Same Less

Ohiob –0.4 X

Oklahomab 3.0 X

Oregon 30.0 X

Pennsylvania –1.1 X

Rhode Island 0.8 X

South Carolina –1.7 X

South Dakota –0.4 X

Tennessee 10.0 X

Texas 1.1 X

Utah 24.0 X

Vermont –3.4 X

Virginiab 2.1 X

Washington –2.7 X

West Virginia –4.0 X

Wisconsin 3.7 X

Wyoming 0.7 X

aChange as of school year 1993-94.

bChange as of school year 1994-95.

Page 317 GAO/HEHS-97-31 Reducing Funding Gaps
Appendix LVII 

GAO Contacts and Staff Acknowledgments

GAO Contacts Eleanor L. Johnson, Assistant Director, (202) 512-7209

Barbara A. Billinghurst, Senior Evaluator, (206) 287-4867

Jerry C. Fastrup, Supervisory Economist, (202) 512-7211

Staff

Acknowledgments

Peter J. Bylsma, Evaluator-in-Charge, (206) 287-4881

Nancy Purvine, Evaluator

Virginia Vanderlinde, Evaluator

Page 318 GAO/HEHS-97-31 Reducing Funding Gaps
Glossary

Elasticity The percent change in one variable relative to a 1-percent change in

another variable.

Equalization In the context of this report, a state’s effort to compensate for differences

in districts’ abilities to raise education revenues.

Equalization effort The ratio of a state’s implicit foundation level to the maximum foundation

level (the state average).

Equity Equity in school finances is concerned with the distribution of education

funding or resources. To determine the equity of school finance systems,

experts recommend considering the following four issues: (1) who is to

benefit (taxpayers or public school students); (2) what objects are to be

equally distributed, such as revenues or key resources (for example,

curriculum and instruction), or outcomes (for example, student

achievement); (3) what principle is to be used for determining whether

distribution is equitable (such as vertical equity or fiscal neutrality); and

(4) the statistic used to measure the degree of equity.

Fiscal neutrality A definition of equity that asserts that no relationship should exist

between educational spending per pupil and local district income per pupil

(or some other measure of fiscal capacity). In this study, a fiscal neutrality

score of 0 indicates that no relationship exists between district funding

and district income.

Fiscal neutrality score The elasticity of total (state and local) funding relative to district income.

Implicit foundation level The minimum amount of total funding per weighted pupil that a state’s

equalization policies implicitly enable districts to spend with the same

minimum local tax effort.

Maximum foundation level The average amount of total funding per weighted pupil in a state.

Tax effort In this study, the tax effort is a ratio of a district’s local education revenue

to its income.

(104846) Page 319 GAO/HEHS-97-31 Reducing Funding Gaps
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