Student Financial Aid: Need Determination Could Be Enhanced
through Improvements in Education's Estimate of Applicants' State
Tax Payments (21-JAN-05, GAO-05-105).
In 2003, the Department of Education (Education) proposed an
update to the state and other tax allowance, a part of the
federal need analysis for student financial aid. Most federal aid
as well as some state and institutional aid is awarded based on
the student's cost of attendance less the student's and/or
family's ability to pay these costs--known as the expected family
contribution (EFC). The allowance, which accounts for the amount
of state and other taxes paid by students and families,
effectively reduces the EFC. Given the potential impact of the
allowance on the awarding of aid, we determined what factors have
affected the updating of the tax data on which it is based, the
effects the proposed 2003 update would have had on financial
assistance for aid applicants, any limitations in the method for
deriving the allowance, and strategies available to address them.
-------------------------Indexing Terms-------------------------
REPORTNUM: GAO-05-105
ACCNO: A16016
TITLE: Student Financial Aid: Need Determination Could Be
Enhanced through Improvements in Education's Estimate of
Applicants' State Tax Payments
DATE: 01/21/2005
SUBJECT: Aid for education
Data integrity
Educational allowances
Federal funds
Federal grants
Internal controls
Student financial aid
Student loans
Taxes
Work-study programs
Department of Education PLUS Loan
Program
Dept. of Education Perkins Student Loan
Program
Dept. of Education Stafford Student Loan
Program
Dept. of Education Supplemental
Educational Opportunity Grants
Free Application for Federal Student Aid
Pell Grant
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GAO-05-105
United States Government Accountability Office
GAO
Report to Congressional Requesters
January 2005
STUDENT FINANCIAL AID
Need Determination Could Be Enhanced through Improvements in Education's
Estimate of Applicants' State Tax Payments
GAO-05-105
[IMG]
January 2005
STUDENT FINANCIAL AID
Need Determination Could Be Enhanced through Improvements in Education's
Estimate of Applicants' State Tax Payments
What GAO Found
While Education has been required to revise the allowance annually since
1993, prior to 2004 it attempted to update the allowance only twice-in
1993 and again in 2003-but the latter update was suspended. As a result,
the 1988 IRS tax data used for the 1993 update remained in effect. The
lack of updates is primarily because Education did not annually seek data
needed to update the allowance or establish effective internal control to
guide the updating process. Also, Education did not consider alternatives
when data were not readily available.
Had the update been implemented in 2004-2005, the allowance would have
decreased for most states; as a result, the EFC would have increased by
about $500, on average, for a majority of aid applicants. Of those with an
EFC increase, 38 percent would either have received less in Pell Grants
($144 less on average) or would have become ineligible for them; the
percentage of recipients affected would have varied by income. Overall
Pell Grant expenditures would have decreased by $290 million. Increases in
EFCs could also have affected other forms of aid, including state aid;
these effects in turn could have affected Stafford loans and Parent Loans
for Undergraduate Students. The impact of the proposed update on
Campus-Based, state, and institutional need-based aid would likely have
varied based on state and institutional aid awarding policies and changes
in state allowances.
Percentage of Recipients Who Would Have Seen a Pell Grant Reduction with
the Proposed Update, by Household Income
Household income (dollars)
0-25,000
25,001-50,000
0 20 40 60 80 100
Source: GAO analysis of the Free Application for Federal Student Aid
(FAFSA) applicant file.
Due to certain limitations of the IRS dataset with respect to calculating
the allowance, and problems with how Education uses this dataset, the
current allowance may not reflect the amount of taxes paid by students and
families. The dataset is limited because the taxpayers included in it are
generally not representative of aid applicants, it does not include all
state and other taxes paid by students and families, and the tax data are
several years older than the income information reported by applicants on
aid applications. In addition to these limitations, Education does not
make full use of the dataset to better reflect the varying tax rates paid
by taxpayers in different income groups.
Strategies we identified for addressing the limitations of the tax
allowance include (1) using IRS data with revisions to the method for
calculating the allowance, (2) substituting IRS data with one of several
alternative data sources, (3) using a standard allowance for all aid
applicants irrespective of state of residence, or (4) collecting tax
information directly from aid applicants. These could require modest to
substantial changes, would differ in their impact on applicants and
federal costs, and could require legislative changes.
United States Government Accountability Office
Contents
Letter
Results in Brief
Background
The Current Tax Allowance Is Based on 1988 Data Due In Part to
Education's Limited Efforts in Updating the Allowance
Education's Proposed Update Would Have Increased Expected
Family Contributions, Thereby Affecting the Allocation of
Federal Aid and Potentially State and Institutional Aid as Well
The Current Allowance May Not Capture the Taxes Paid Due to the
Type of Data and Methodology in Use
Four Strategies Might Address Some of the Limitations Associated
with the Tax Allowance and Would Yield a Variety of Effects on
Federal Spending and Aid Recipients
Conclusions
Recommendations for Executive Action
Agency Comments
1
3 6
11
15
27
31 39 39 40
Appendix I Scope and Methodology 44
Overview 44
Datasets 44
Estimation Methodology 45
Calculation of Estimated Tax Rates from Alternative Data Sources 50
Sampling Error 51
Appendix II State Selection Matrix-Ranking of Potential Impact of
Proposed Allowance, Listed by Category
Appendix III Average Tax Rates on Adjusted Gross Income, by State and
Income Level
Appendix IV Simulation of Tax Allowance Percentages under
Various Options, by State-Families with Adjusted
Gross Income of $15,000 or More 55
Appendix V Comments from the Department of Education 57
Appendix VI GAO Contacts and Staff Acknowledgments
61
GAO Contacts 61 Staff Acknowledgments 61
Tables
Table 1: State and Other Tax Allowance Established for Parents of
Dependents and for Independents with Children, Published in 1993
Table 2: State and Other Tax Allowance Established for Dependents and
Independents without Children, Published in 1993
Table 3: Proposed Allowance Changes and Estimated EFC Impacts by State
Table 4: Percentage with a Pell Grant Decrease and Average Decrease by
State, Including Those No Longer Eligible for the Award
Table 5: Estimated Impacts in Campus-Based Aid for Case Study Schools
Table 6: Estimated Impacts in State Need-Based Aid for Two States
Table 7: Publication Dates of SOI State and Local Tax Data
Table 8: Comparison of Income Distribution in 2001 of FAFSA Applicants and
Federal Income Tax Itemizers
Table 9: Framework for Evaluating Options Identified to Change the State
and Other Tax Allowance Relative to the Current Allowance in Use 12
13
17
19
25 26 29
30
37
Figures
Figure 1: Federal Student Need Analysis Methodology 7 Figure 2: Estimated
Amount of Student Aid Awarded in 2003-2004,
by Source of Aid 10 Figure 3: Percentage of Recipients with a Decrease in
Pell Award 21 Figure 4: Median Percentage Change in Amount of Pell Award
for
Those with a Decrease 22 Figure 5: Percentage of Students Likely to Have
Had a Change in Subsidized Stafford Loans 24
Figure 6: Framework for Evaluating the Alternative Datasets
Identified Relative to SOI Data
38
Abbreviations
ACSFA Advisory Committee on Student Financial Assistance
AGI adjusted gross income
ASEC Annual Social and Economic Supplement
AY award year
BEA Bureau of Economic Analysis
CEAD STAB Cost Estimation and Analysis Division Statistical Abstract
COA cost of attendance
CPS Current Population Survey
EFC expected family contribution
FAFSA Free Application for Federal Student Aid
FY fiscal year
HEA Higher Education Act
IM Institutional Methodology
IRS Internal Revenue Service
ITEP Institute on Taxation and Economic Policy
NSLDS National Student Loan Data System
PLUS Parent Loans for Undergraduate Students
SEOG Supplemental Educational Opportunity Grant
SOI Statistics of Income
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United States Government Accountability Office Washington, DC 20548
January 21, 2005
Congressional Requesters
In 2003-2004, an estimated $98 billion in financial aid was awarded to
students for postsecondary education through the Title IV federal student
aid programs, as well as state and institutional grant programs.1 Title IV
aid is currently awarded based on a formula specified in the Higher
Education Act (HEA); many states and postsecondary institutions also use
this formula to award their own student aid. A substantial portion of this
aid is awarded based on the difference between a student's cost of
attendance and an estimate of the student's and/or family's ability to pay
these costs- called the expected family contribution (EFC)-determined by
this formula. To apply for Title IV aid, students submit a Free
Application for Federal Student Aid (FAFSA) on which they report their own
and/or their families' income, assets, and federal income tax expenses.
State and other tax expenses, on the other hand, are not collected on the
FAFSA form. Rather, Education uses a rate specified in law, subject to
revision by Education-called the state and other tax allowance-to estimate
such taxes.
Congress incorporated the state and other tax allowance as a part of the
formula by including in the Higher Education Act a series of tables
listing the applicable allowance for students and families by state. The
tables list specific percentage values, or rates, that are used to exclude
a portion of students' and families' incomes in determining their EFC.
Thus, under the formula, the state and other tax allowance effectively
reduces the EFC for students and families. The allowances were originally
developed based on information compiled by the Department of Treasury's
Internal Revenue Service's (IRS)-Statistics of Income (SOI) Division,
specifically state and other taxes paid by taxpayers and reported on their
federal income tax returns.
1Title IV aid programs include Pell Grants, subsidized and unsubsidized
Stafford loans, and Parent Loans for Undergraduate Students (PLUS), as
well as Supplemental Educational Opportunity Grants (SEOG), Perkins loans,
and Work-Study aid funded by the federal government and administered by
participating institutions, commonly known as Campus-Based aid. About $68
billion in aid was provided under Title IV programs during fiscal year
2003-2004; in addition, the College Board estimates that about $29 billion
was provided under state and institutional aid programs during award year
2003-2004.
While the Department of Education (Education) is required by law to update
the state and other tax allowance, its proposal to do so in 2003 was met
with substantial concern because it was the first update in a number of
years and because the update would likely affect the EFC for students and
families and the amount of student aid received. In view of the
uncertainty and controversy that followed Education's proposed update and
Congress' decision to suspend the update for 1 year, you asked us to shed
light on issues associated with the tax allowance question and the
department's proposed 2003 update. This report examines (1) what tax data
form the basis of the current tax allowance and what factors have affected
regular updates, (2) the effect Education's proposed 2003 update would
have had in award year 2004-2005 on financial assistance for students and
families, (3) the extent to which current methods for determining the
allowance accurately measure how much students and families have paid in
state and other taxes, and (4) the strategies available to address any
problems in deriving the allowance.
To do our work, we reviewed federal laws governing how Education is to
update the state and other tax allowance and examined documents pertaining
to this process. We used Education's aid applicant sample file from the
2002-2003 award year to estimate changes to the expected family
contribution and Pell Grant awards nationally that would have resulted
from Education's proposed update. We analyzed Education's Cost Estimation
and Analysis Division's Statistical Abstract (CEAD STAB) data to estimate
the proportion of financial aid recipients who could have experienced a
change in their federal loans as a result of the proposed update. We
assessed the reliability of the aid applicant and CEAD STAB data and
determined that they were sufficiently reliable for our review. To obtain
estimates on changes in state-provided need-based aid programs, we
contacted two states, one with a likely high level of impact (Wisconsin)
and the other with a likely low level of impact (Tennessee). To illustrate
changes in students' receipt of Title IV aid and need-based aid provided
by schools, we relied on estimates from four schools-two public
institutions (University of Wisconsin-Madison and Middle Tennessee State
University) and two private nonprofit institutions (Marian College of Fond
du Lac and Carson-Newman College). To develop strategies to address the
allowance's limitations in measuring students' and parents' state and
other tax payments, we identified and analyzed alternative data sources
that have state and local tax information. Finally, to gain further
perspective on our objectives, we interviewed officials from the Advisory
Committee on
Student Financial Assistance (ACSFA) 2 and other federal officials, along
with state, school, and national association officials as well as other
student financial aid experts.
We conducted our review from October 2003 through November 2004 in
accordance with generally accepted government auditing standards. For a
more detailed explanation of our methodology, see appendix I.
Results in Brief
The current tax allowance is based on 1988 tax data due in part to
Education's limited efforts to update the allowance. Congress incorporated
the allowance into law in 1986 but did not establish a mechanism for
updating the allowance until 1992. In amending the Higher Education Act in
1992, Congress directed Education to annually revise the allowance tables
after reviewing the IRS' Statistics of Income file and determining the
percentage of income that each state's taxes represent for those
residents. While Education has published allowance tables annually since
1993, prior to 2004, it attempted to update the allowance tables
twice-once in 1993 and once in 2003-but the latter update was suspended.
As a result, the allowance-based on 1988 data that was first incorporated
into the allowance tables in 1993-continued to be based on 1988 data. One
reason the allowance was not updated more frequently was because Education
did not annually seek data needed to update the allowance. For example,
Education records indicate that it only sought data to update the
allowance for 6 years of the 11-year period from 1993 to 2003. Another
reason is that Education was unwilling to incur costs to acquire data and
therefore did not consider alternatives when data were unavailable
cost-free. Further, when the IRS did make more current tax data freely
available via the Internet, starting in 2000, Education did not become
aware of this fact and did not take steps to make use of the data until
2003. In addition, Education could not provide us with written procedures
guiding staff on the routine steps necessary to update the tax allowance,
nor did it maintain detailed records of its efforts to obtain data.
Education's proposed update would have decreased the state and other tax
allowance for most states, which, in turn, would have increased the
expected family contribution for a majority of student aid applicants; the
2ACSFA was established by Congress with the enactment of the 1986 HEA
amendments. The committee began its operation in 1988 by serving as a
source of advice and counsel to Congress and the Secretary of Education on
student financial aid policy.
increase in expected family contribution would have, in turn, affected the
allocation of federal aid and potentially state and institutional aid as
well. We estimate that the update to the state and other tax allowance
would have affected over half of the students applying for aid by
increasing their EFC by about $500 on average (or from an average of about
$9,620 to about $10,115) for those who would have had an EFC increase. The
amount of the EFC increase generally would have been larger for students
from states with a larger decrease in their state and other tax allowance.
For example, residents of Delaware, which would have had a 4 percentage
point decrease in its allowance for families-the largest decrease among
the states-would have experienced an EFC increase of about $830 on
average. With respect to Pell Grants, our national analysis shows that EFC
increases from the update would have likely resulted in a decrease in Pell
Grant awards for about 36 percent of students, and an additional 92,000
applicants (2 percent) would no longer have been eligible for the grant.
Because these EFC changes would have affected Pell and other grant aid,
Stafford and PLUS loan award amounts would in turn have been affected as
well. Our case studies show that as EFC would have increased, subsidized
Stafford loan awards would have decreased while unsubsidized Stafford loan
awards would have increased. However, these case studies also show that
most federal Campus-Based aid awards would have largely been unaffected by
changes in the EFC. The effect of EFC changes on state and institutional
grants would have varied because the EFC would have decreased in some
states more than in others and because aid policies vary across states and
institutions.
As a result of certain limitations of the SOI dataset for the purpose of
calculating the allowance and problems with how Education uses this
dataset, the current state and other tax allowance may not fully reflect
the amount of taxes paid by students and families. The dataset itself is
not ideally suited for calculating the allowance because it is limited to
financial data from those who itemize their taxes, does not include state
and local sales taxes, and is several years older than the income
information reported by students and families on the FAFSA. SOI tax
information may not be representative of families applying for financial
aid because SOI compiles state and local tax data only for those who
itemize their deductions, and itemizers may pay different effective tax
rates for a given level of income than nonitemizers. Also, while state and
local sales taxes were reflected in SOI data when Congress first
incorporated the tax allowance, subsequent tax reform legislation
eliminated the deductibility of sales taxes, effectively removing this
information from the SOI dataset. Although more recent legislation
provides taxpayers who itemize the choice of deducting either sales or
income taxes, the law allows this only for the 2004 and 2005 tax years.
Moreover, SOI tax data are generally released about 2 years after each tax
year, so it is not possible to match this information with the income
information that applicants report on the aid application. In addition to
the limitations of the SOI dataset, Education's calculation of the
allowance does not accurately consider the varying taxes paid by different
income groups. As a result, Education's calculation of the allowance is
overestimated for lower-income groups and underestimated for higherincome
groups.
We identified four strategies to address some of the limitations
associated with the tax allowance. While not exhaustive, these strategies
include (1) continuing to use SOI data but with a revised method for
calculating the allowance, (2) substituting SOI data with data from one of
several alternative sources, (3) using the same allowance for all aid
applicants without regard to state of residence, and (4) collecting
information directly from the aid applicants themselves. The calculation,
for example, might be modified to better reflect the taxes paid by
different income groups than the current methodology. An option that would
not require calculating an allowance would be to collect information about
actual taxes paid directly from aid applicants by adding questions to the
aid application, making it possible to collect income, asset, and tax
information for the same year. Selecting among these strategies would
require a number of considerations: the effect on federal expenditures,
the impact on aid applicants, and the availability and reliability of tax
data from alternative sources. These options could range in their impact
on federal expenditures for the Pell Grant and other federal programs. For
example, depending on the option chosen, the effect would range from a
$200 million decrease in Pell Grant expenditures to an increase of $400
million in the 2004-2005 award year.
In this report, we recommend that the Secretary of Education improve the
department's process for updating the state and other tax allowance by
formalizing procedures, and documenting them in writing, to ensure that
the Department of Education annually requests and obtains the most current
tax data from SOI and revise the methodology for calculating the state and
other tax allowance to more accurately consider the varying taxes paid by
students and families. In addition, we recommend that the Secretary
determine whether alternative methodologies and/or data- including those
identified in this report-would allow the department in the future to more
effectively calculate and update an allowance for state and other taxes.
Background The Higher Education Act specifies a formula, known as the
federal need analysis methodology, that is used to determine students'
eligibility for federal student aid. A variety of federal grants and loans
are available to assist students pay postsecondary expenses. While some
federal aid is allocated based on a student's need for financial aid that
is determined by the formula, other federal aid is allocated regardless of
need. Many states and institutions have their own student aid programs,
providing students an additional source of aid to help pay for
postsecondary expenses.
Federal Need Analysis Methodology
The federal need analysis methodology is used to determine a student's
need for financial aid by comparing a student's and/or family's expected
family contribution to the student's cost of attendance (COA). The EFC is
defined as the household financial resources that are considered available
to help pay for the student's postsecondary education expenses and is
calculated by reducing the household financial resources reported by aid
applicants on the Free Application for Federal Student Aid by certain
expenses and allowances, including a state and other tax allowance. A
student is classified as either financially dependent on his or her
parents or independent in the financial aid process. This classification
is important because it affects the factors used to determine a student's
EFC. For dependent students, the EFC is based on both the students and
parents' income and assets, as well as whether the family has other
children enrolled in college. For independent students, the EFC is based
on the student's and, if married, spouse's income and assets and whether
the student has any dependents other than a spouse, and the number of
family members enrolled in college.
To capture and reflect changes in students' and families' state and other
tax liabilities, Education is responsible for annually updating the state
and other tax allowance tables that were established in the HEA. Education
determines the state and other tax allowance based on state and local tax
information from federal tax returns filed with the Internal Revenue
Service and compiled by its Statistics of Income Division. For dependent
students and independent students without children, the allowance is
composed of state and local income taxes. For parents of dependent
students and independent students with children, personal property taxes
and real estate taxes are added to the allowance.
The costs of attending a postsecondary institution that a student faces
include tuition, fees, books, and living expenses. The student may be able
to receive financial aid to help cover costs of attendance depending on
where the student wants to enroll as well as the student's and family's
financial resources. If the price of attendance is greater than the
expected
family contribution, the difference between the two represents the
student's financial need. If the EFC is greater than the price of
attendance, the student is not eligible for federal need-based aid but may
still qualify for aid that is not based on need. (See fig. 1.)
Figure 1: Federal Student Need Analysis Methodology
Source: GAO analysis of the HEA.
Note: Not all assets are considered under the federal student need
analysis methodology. For example, the methodology does not include the
principal place of residence.
Postsecondary institutions are responsible for determining individual
student's eligibility for specific sources of financial aid and compiling
these sources to meet each student's need-a process known as packaging.
Part of this process involves deciding which types or sources of aid
should be awarded first-for example, grants or loans, federal or
nonfederal aid, need-based or non-need-based aid. In awarding aid,
institutions typically first package any grants for which the student is
eligible and then offer loans. Another factor considered in packaging aid
is
whether to reduce aid from any source in a student's package to offset an
aid award from another source.
Federal Aid Provided under Title IV of the Higher Education Act
Title IV of the HEA, as amended, authorizes the following federal aid
programs:
o Pell Grants-Pell Grants are grants to low- and middle-income
undergraduate students who have federally defined financial need and who
are enrolled in a degree or certificate program. In general, a student's
Pell Grant award is determined by subtracting a student and family's EFC
from either the maximum allowable Pell Grant award, currently $4,050, or
the COA, whichever is less.
o Stafford and PLUS Loans-These loans may be made by private lenders and
guaranteed by the federal government (guaranteed loans) or made directly
by the federal government through a student's school (direct loans).
o Subsidized Stafford Loans-Subsidized loans are made to students
enrolled at least half-time in an eligible program of study that have
federally defined financial need. The federal government pays the interest
costs on the loan while the student is in school. Subsidized loans are
subject to certain maximum loan limits and are awarded based on the
difference between a student's COA less EFC and other awards of student
aid including Pell Grants, state or institutional grants, etc. A change in
a student's EFC may-or may not-affect the amount of a subsidized loan
award depending on its effect on other components of the student's
financial aid package.
o Unsubsidized Stafford Loans-Unsubsidized Stafford loans are
nonneed-based loans made to students enrolled at least half-time in an
eligible program of study. Although the terms and conditions of the loan
(e.g., interest rates) are the same as those for subsidized loans,
students are responsible for paying all interest costs on the loan. While
Stafford unsubsidized loans are not need-based aid, a change in a
student's or family's EFC may nonetheless affect the amount a student may
borrow. Unsubsidized loans are awarded based on the difference between a
student's COA less other awards of student aid-including Pell Grants,
state and institutional grants, and subsidized loans. These loans are
subject to the combined maximum loan limits for subsidized and
unsubsidized loan awards. A change in a student's EFC that affects Pell
Grant, subsidized loan, or state or institutional grant awards may
therefore affect the amount of an unsubsidized loan award.
o PLUS Loans-PLUS loans are non-need-based loans made to creditworthy
parents of dependent undergraduate students enrolled at least half-time in
an eligible program of study. Borrowers are responsible for paying all
interest on the loan. Like unsubsidized loans, PLUS loans are generally
awarded based on the difference between a student's COA less other awards
of student aid including unsubsidized loan awards. As is the case with
unsubsidized loans, a change in a student's or family's EFC can affect the
amount of a PLUS loan that a parent may borrow.
Dependent students may borrow combined subsidized and unsubsidized
Stafford loans up to $2,625 in their first year of college, $3,500 in
their second year, and $5,500 in their third year and beyond. Independent
students and dependent students without access to PLUS loans can borrow
combined subsidized and unsubsidized Stafford loans up to $6,625 in their
first year, $7,500 in their second year, and $10,500 in their third year
and beyond. There are aggregate limits for an entire undergraduate
education of $23,000 for dependent students and $46,000 for independent
students and dependent students without access to PLUS loans.
o Campus-Based Aid-Participating institutions receive separate
allocations for three programs from Education. Funds are distributed to
institutions in part on the basis of the institution's previous allocation
levels and in part on the basis of the aggregate financial need of
eligible students in attendance. The institutions then award the following
aid to students:
o Supplemental Educational Opportunity Grants (SEOG)-SEOG grants are
grants for undergraduate students with federally defined financial need.
Priority for this aid is given to Pell Grant recipients. In general, an
annual SEOG award may not be less than $100 and may not exceed $4,000.
o Perkins Loans-Perkins loans are low-interest (5 percent) loans to
undergraduate and graduate students. Interest does not accrue while the
students are enrolled at least half-time in an eligible program. Priority
is given to students who have exceptional federally defined financial
need. Students can borrow up to $4,000 for any year of undergraduate
education with an aggregate limit of $20,000.
o Work-Study-Work-Study is employment in on- or off-campus jobs for
which students who have federally defined need earn at least the current
federal minimum wage. The institution or off-campus employer pays a
portion of their wages, while the federal government pays the
remainder. Work-study is awarded based on the difference between a
student's need less other aid awarded.
Students Received about Students received an estimated $98 billion in
financial aid in award year $98 Billion in Federal, 2003-2004 from the
Title IV federal aid programs as well as state and State and Institutional
Aid institutional grants, of which the federal government provided more
than in 2003-2004. two-thirds. Federal assistance is composed of both
loans and grants, and
most federal grant aid is need-based. States distributed about $6 billion
in student aid.3 Institutions provided about $23 billion in the forms of
needbased grant and merit-based aid. (See fig. 2.)
Figure 2: Estimated Amount of Student Aid Awarded in 2003-2004, by Source of Aid
3
Federal Campus-Based Aid State Grants
Federal Pell Grants
Institutional Grants
Federal Loans
In billions of dollars
Source: Department of Education, Fiscal Year 2005, Justifications of
Appropriation Estimates to the Congress, Volume II. College Board, Trends
in Student Aid, 2004.
Notes: Federal aid is based on fiscal year figures, and state and
institutional aid is based on award year amounts. Because of rounding, the
sum of aid awarded under the various programs in the figure above is less
than the actual total of $97.9 billion.
3The College Board estimates that about 75 percent of state aid was
need-based.
The Current Tax Allowance Is Based on 1988 Data Due In Part to Education's
Limited Efforts in Updating the Allowance
The current state and other tax allowance is based on 1988 tax data due in
part to Education's limited efforts in updating the allowance. While
Education has been required to revise the allowance tables annually since
1993, prior to 2004 it had attempted to update the allowance twice-once in
1993 and once in 2003-but the latter update was suspended. As a result,
the 1988 tax data used for the 1993 update are still in effect. The lack
of updates is primarily because Education did not annually seek data
needed to update the allowance and did not establish effective internal
control to guide the updating process. In addition, Education did not
consider alternatives when data were not readily available.
The Current Tax Allowance Is Based on 1988 Tax Data
While Education has published the allowance tables used to award Title IV
aid in the Federal Register annually since 1993, prior to 2003 these
tables had been based on 1988 tax return information compiled by SOI.
Congress incorporated the state and other tax allowance into the HEA in
1986 on the basis of 1983 SOI data but did not establish a mechanism to
update the basis of the allowance until 1992. Amending the Higher
Education Act in that year, Congress directed Education to "publish in the
Federal Register...revised table[s] of State and other tax allowances"
annually, and to "develop such revised table[s] after review of the
Department of the Treasury's Statistics of Income file and determination
of the percentage of income that each State's taxes represent" for those
residents. Education published the first updated tables of the allowance
in 1993 after reviewing SOI's 1988 tax data, the most recent data
available at that time. Tables 1 and 2 present these revised tax
allowances, by dependency status and state.
Table 1: State and Other Tax Allowance Established for Parents of
Dependents and for Independents with Children, Published in 1993
Income level (percentage) State of residence
Less than $15,000
$15,000 or more
Alaska, Nevada, Tennessee, Texas, Wyoming 3
Florida, Louisiana, South Dakota, Washington 4
Alabama, Mississippi 5
Arizona, Arkansas, Connecticut, Illinois, Indiana, Missouri,
New Mexico, North Dakota, Oklahoma, West Virginia 6
Colorado, Georgia, Idaho, Kansas, Kentucky, New
Hampshire, Pennsylvania 7
California, Delaware, Hawaii, Iowa, Montana, Nebraska, New Jersey, North
Carolina, Ohio, South Carolina, Utah, Vermont, Virginia 8
Maine, Maryland, Massachusetts, Michigan, Minnesota,
Rhode Island 9
District of Columbia, Oregon, Wisconsin 10
New York 11
Other areas 4
Source: 1993 Federal Register.
Table 2: State and Other Tax Allowance Established for Dependents and
Independents without Children, Published in 1993
State of residence
Percentage
Alaska, Nevada, South Dakota, Tennessee, Texas, Washington, Wyoming
Florida, New Hampshire
Connecticut, Illinois, Louisiana, North Dakota
Alabama, Arizona, Mississippi, Missouri, New Jersey, Pennsylvania
Arkansas, Colorado, Georgia, Indiana, Kansas, Michigan, Nebraska, New
Mexico, Oklahoma, Rhode Island, Vermont, Virginia, West Virginia
California, Delaware, Idaho, Iowa, Kentucky, Maine, Massachusetts,
Montana, North Carolina, Ohio, South Carolina, Utah, Wisconsin
Hawaii, Maryland, Minnesota, Oregon
District of Columbia, New York
Other areas
Source: 1993 Federal Register.
Although Education has published allowance tables annually since 1993, the
published allowances continued to be based on 1988 SOI data until 2003,
when new tables based on 2000 SOI tax data were published. Education
intended to use the new tables to award student aid in 2004- 2005 but did
not do so in light of legislation that prohibited it from doing so. As a
result, the state and other tax allowance used to award financial aid
continued to be based on 1988 tax data.4
4On December 23, 2004, about 6 months past the deadline specified by the
HEA for updating the allowance, Education published updated state and
other tax tables for award year 2005-2006 using 2002 SOI tax data.
According to Education, it delayed the publication of these tables in
order to complete a thorough review of available SOI information and to
consider the findings of a congressionally mandated review by the Advisory
Committee on Student Financial Assistance on the efficiency,
effectiveness, and fairness of current procedures to update formula
offsets and allowances.
Education Did Not Annually Seek Data to Update the Allowance, Consider
Alternatives when Such Data Were Not Readily Available, or Establish
Effective Internal Control to Guide the Updating Process
Prior to 2003, Education's efforts to update the allowance were limited:
It neither annually sought data to update the allowance nor pursued
alternatives when SOI data it had used previously were not readily
available. According to Education's records, the department only sought
data to update the allowance for 6 of the 11 years since it was first
directed to annually update the tax allowance.5 SOI records also document
that Education did not routinely request data. Even when Education did
request data, it is difficult to determine exactly what data were
requested because such requests were not made in writing. Rather,
Education's documentation consists of informal file notes of telephone
contacts with SOI officials that are minimal and do not describe the
substance of what was discussed. Furthermore, as of the end of our audit
work, Education could not provide us with written procedures guiding staff
on the routine steps necessary to update the tax allowance or to identify
what data would be needed to update the allowance.
After Education published the 1993 update to the allowance, on the basis
of 1988 SOI tax data, Education sporadically sought data from SOI to
develop subsequent updates. According to both Education and SOI officials,
however, SOI would not have provided these data on a cost-free basis.
According to SOI officials, the 1988 tax data was produced to illustrate
the type of information SOI could develop that clients, such as states,
might find useful and be willing to purchase in the future. SOI never
intended to produce the data as a regular series, and the fact that it was
useful for Education's purposes was coincidental. Education's records do
not indicate what actions the agency undertook when it first learned that
SOI would not provide data cost-free, including the extent to which it
considered paying for such data. Education officials told us, however,
that they never sought a cost estimate from SOI because they did not wish
to pay for the data.6 Moreover, Education officials told us that they did
not consider using data other than SOI data because they believed
Education did not have the discretion to do so under the law. Beginning in
2000, about 1 year after Education last contacted SOI, SOI began to
annually publish on its Web site data that Education could have used to
update the
5Education did not have records to show that it had requested SOI data in
1997, 1998, 2000, 2001, and 2002.
6According to SOI officials, Education had options in obtaining the data.
Requesting SOI to tabulate state and other taxes from all tax returns
would have been a lower-cost option because SOI already had the procedures
in place to make this tabulation.
Education's Proposed Update Would Have Increased Expected Family
Contributions, Thereby Affecting the Allocation of Federal Aid and
Potentially State and Institutional Aid as Well
allowance.7 However, Education was unaware of these data because it did
not contact SOI again until 2003 for the purpose of making its proposed
update that year.
As we have pointed out in numerous reports, weak internal control can be a
contributing factor to, or cause of, insufficient execution of agency
responsibilities. Collectively, internal controls are an integral
component of an organization's management intended to provide reasonable
assurance that, among other things, operations are effective and
efficient. Education's failure to fully document its attempts to update
the allowance over the past several years and its lack of written
procedures to guide staff efforts to ensure that they take the steps
necessary to update the allowance, such as a checklist, are indicative of
an ineffective system of internal control. Our Standards for Internal
Control in the Federal Government provides guidance to agencies to help
them assess, evaluate, and implement effective internal controls that can
be helpful in improving their operational processes.8
Under the proposed update, the state and other tax allowance would have
decreased for most states; the change in the allowance, in turn, would
have increased the amount that families are expected to contribute by
about $500 on average for a majority of student aid applicants. Of those
aid applicants with an increase in their EFC, some would have received
lower Pell Grant awards or would have become ineligible for Pell Grants.
Increases in EFCs would not only have affected Pell Grants but possibly
other forms of aid, and these effects in turn would have affected Stafford
and PLUS loan awards. The extent to which the proposed update would have
affected federal Campus-Based, state, and institutional aid would likely
have varied according to factors such as aid awarding policies and changes
in a state's allowance.
7SOI currently provides state and other tax data by state for tax years
1997 to 2002 on its Web site.
8GAO, Standards for Internal Control in the Federal Government,
GAO/AIMD-00-21.3.1 (Washington, D.C.: November 1999).
Under the Proposed Update, Expected Family Contributions Would Have
Increased by about $500, on Average, for a Majority of Student Aid
Applicants
Education's tax allowance update would generally have increased the dollar
amount that families would be expected to contribute to a student's
education, but the percentage of student aid applicants affected would
have varied by state and household income, and the size of the increase
would have varied by state. EFCs would increase by about $500 on average
for those with an increase (from an average of about $9,620 to about
$10,115), but aid applicants from states with larger decreases in their
tax allowance rates would have had a larger increase in their EFCs.9 Table
3 shows the proposed changes to the allowance and the estimated EFC
impacts, by state. For example, Delaware would have had a 4 percentage
point decrease in its tax allowance for families earning $15,000 or
more10-from 7 percent to 3 percent-and a 2 percentage point decrease for
individuals,11 resulting in an EFC increase of $834 on average, among
applicants in Delaware with an increase. In contrast, Nevada would have
had a 1 percentage point decrease in the allowance for families (and a 1
percentage point increase for individuals), and its residents would have
had an expected contribution increase of $186 on average. Similarly, the
percentage of applicants affected would have varied from state to state.
In Wisconsin, for example, the percentage of student aid applicants
affected would have been slightly over 80 percent, in contrast to
Connecticut, where just under 1 percent of applicants would have been
affected. With regard to household income, over 90 percent of families
earning more than $25,000 would have been expected to contribute more
under the update, while only about 20 percent of families earning $25,000
or less would have been expected to contribute more. Across all states, we
estimate that the update would have affected more than 60 percent of aid
applicants and would have resulted in an EFC increase of $3.5 billion
collectively in award year 2004-2005.
9The percentage of those with a decrease in the amount they are expected
to contribute is less than 1 percent.
10"Families" includes parents of dependent students and independent
students with children.
11"Individuals" includes dependent students and independent students
without children.
Table 3: Proposed Allowance Changes and Estimated EFC Impacts by State
Percentage point change Estimated
in the state and other tax percentage of Estimated average
allowance students with an EFC dollar
increase in their increase for
those
State Families Individuals EFC with an increase
Alabama -2 -1 59 311
Alaska -1 0 62 261
Arizona -2 0 47 385
Arkansas -3 -1 62 410
California -2 0 45 406
Colorado -3 -1 75 571
Connecticut 0 +2 1
Delaware -4 -2 80 834
District of -3 -1 60 485 Columbia
Florida -2 -1 64 298
Georgia -2 -1 67 384
Hawaii -4 -2 68 746
Idaho -2 -1 69 321
Illinois -2 0 60 459
Indiana -2 -1 75 406
Iowa -4 -2 78 781
Kansas -3 -1 77 531
Kentucky -2 -1 66 340
Louisiana -2 -1 61 415
Maine -3 -1 78 610
Maryland -2 -1 75 462
Massachusetts -3 -1 79 717
Michigan -4 -1 73 746
Minnesota -3 -2 81 673
Mississippi -2 -1 53 283
Missouri -2 0 60 425
Montana -3 -2 69 515
Nebraska -4 -1 79 716
Nevada -1 +1 50 186
New Hampshire -3 0 73 808
New Jersey -1 +1 63 263
New Mexico -3 -1 62 432
Percentage point change Estimated
in the state and other tax percentage of Estimated average
allowance students with an EFC dollar
increase in their increase for
those
State Families Individuals EFC with an increase
New York -3 -2 67 639
North Carolina -3 -1 68 493
North Dakota -4 -1 78 736
Ohio -3 -1 73 589
Oklahoma -2 -1 65 308
Oregon -3 -1 69 519
Pennsylvania -3 0 67 713
Rhode Island -3 0 60 697
South Carolina -4 -2 67 718
South Dakota -3 0 64 589
Tennessee -2 0 52 371
Texas -1 0 51 189
Utah -3 -1 73 345
Vermont -3 -1 80 614
Virginia -3 -1 73 623
Washington -2 0 53 429
West Virginia -3 -2 68 527
Wisconsin -4 -1 81 802
Wyoming -2 0 61 408
Source: GAO analysis.
Notes: Dependent students whose state of residence is different from that
of their parents were counted as being from their parents' state. Since
the EFC for a family is based upon both the parents' and the student's
income, the EFC changes reported above for each state may reflect not only
the change in the allowance for that state but also the change for the
state of residence for students attending school in another state. For
example, Connecticut, which has an increased allowance, may have families
with an EFC increase because the children of those families may be
attending school and residing in another state with a decreased allowance.
The sampling errors for the average EFC increase for Alaska, Connecticut,
Delaware, District of Columbia, Hawaii, Idaho, Maine, Montana, Nevada, New
Mexico, North Dakota, Rhode Island, South Dakota, Vermont, and Wyoming
vary from slightly over 5 percent (for Maine and New Mexico) to 34 percent
(for Connecticut). All others have a sampling error at or below 5 percent.
If Expected Family Contributions Had Increased, Some Aid Applicants Would
Have Received Lower Pell Grant Awards or Become Ineligible for Them
Had Education's proposed update been adopted, thus raising the expected
family contribution for aid applicants, 38 percent of recipients would
have either seen a decrease in their Pell Grant award or would have become
ineligible for the grant altogether; taken together, the average reduction
among those with a decrease in their amount would have been $144. In
particular, 36 percent of recipients would have seen a decrease of $133 on
average in their Pell Grant award but would have remained eligible for the
awards in award year 2004-2005. Another 92,000 recipients, or 2 percent of
those receiving Pell Grants, would no longer have been eligible and
typically would no longer have received the minimum Pell Grant award of
$400. As a result, the proposed update would have decreased overall
federal Pell Grant expenditures by $290 million. Students residing in
states with larger decreases in their allowances would have faced larger
decreases in Pell Grant amounts and are more likely to have become
ineligible for them. Table 4 shows the average decrease in Pell Grant
awards for those who would have seen a decrease in their Pell Grant award
or who would have become ineligible for them, by state.
Table 4: Percentage with a Pell Grant Decrease and Average Decrease by
State, Including Those No Longer Eligible for the Award
Percentage Average Percentage Average
with a dollar with a dollar
decrease in decrease in decrease decrease
State Pella Pellb State in Pella in Pellb
Alabama 38 -111 Montana 48 -174
Alaska 28 -83 Nebraska 54 -216
Arizona 34 -115 Nevada 25 -80
Arkansas 42 -160 New Hampshire 51 -175
California 29 -121 New Jersey 26 -90
Colorado 47 -156 New Mexico 42 -155
Connecticut 0c -100 New York 45 -175
Delaware 58 -194 North Carolina 46 -162
District of 39 -174 North Dakota 48 -229 Columbia
Florida 40 -107 Ohio 46 -163
Georgia 43 -104 Oklahoma 41 -115
Hawaii 47 -216 Oregon 44 -163
Idaho 42 -123 Pennsylvania 46 -179
Illinois 38 -118 Rhode Island 41 -162
Indiana 46 -119 South Carolina 49 -194
Iowa 57 -224 South Dakota 41 -176
Percentage Average Percentage Average
with a dollar with a dollar
decrease in decrease in decrease decrease
State Pella Pellb State in Pella in Pellb
Kansas 53 -168 Tennessee 36 -110
Kentucky 41 -118 Texas 24 -83
Louisiana 35 -113 Utah 47 -148
Maine 54 -174 Vermont 49 -161
Maryland 46 -112 Virginia 47 -170
Massachusetts 48 -172 Washington 34 -115
Michigan 47 -199 West Virginia 47 -168
Minnesota 57 -181 Wisconsin 54 -226
Mississippi 35 -120 Wyoming 40 -134
Missouri 40 -122 Total USA 38 -144
Source: GAO analysis.
aThe sampling errors for Alaska, Delaware, District of Columbia, Vermont,
and Wyoming vary from 5.2 percentage points (for Delaware) to 5.6
percentage points (for Alaska). All others are at or below 5 percentage
points.
bThe average reflects the reduction for those with a decrease as well as
those who would have lost eligibility. The sampling errors for Alaska,
Delaware, District of Columbia, Hawaii, Idaho, Maine, Montana, Nebraska,
Nevada, North Dakota, New Hampshire, Rhode Island, South Dakota, Vermont,
and Wyoming vary from slightly over 5 percent (for Nebraska) to 15 percent
(for Alaska). All others are at or below 5 percent.
cThe actual figure for Connecticut is 0.1 percent, which rounds to 0
percent for the purposes of this table.
Students with relatively higher household incomes would have been more
likely to face a decrease and would have faced substantially greater
decreases in their Pell Grant awards than those with lower household
incomes.12 On the other hand, the impact of the proposed update would not
seem to have varied much by whether students are financially independent
of their families. Figures 3 and 4 show the proportion of those facing a
decrease in Pell awards and the median amount of such decreases, by income
group.
12High-income families would very rarely have qualified for Pell Grants
and thus would not have been affected.
Figure 3: Percentage of Recipients with a Decrease in Pell Award
100 93.9 96.2
90
80
70
60
50
40
30
20
10
0 25,000 or less 25,001-50,000 50,001-100,000 Household income (dollars)
Dependents Independents Source: GAO analysis of the FAFSA applicant file.
Figure 4: Median Percentage Change in Amount of Pell Award for Those with
a Decrease
0.0
-2.5
-5.0
-7.5
-10.0
-12.5
-15.0
-17.5
-20.0
-22.5
-25.0 25,000 or less 25,001-50,000 50,001-100,000 Household income (dollars)
Dependents Independents
Source: GAO analysis of the FAFSA applicant file.
Note: The sampling error for Independents earning $50,001 to $100,000 is 7
percentage points. The error for all other categories is 5 percentage
points or less.
Changes in EFCs Could Have Affected Stafford and PLUS Loan Awards
Stafford and PLUS loans could have been affected due to EFC changes as
well. Those applicants for whom a change in EFC would have resulted in a
change in other aid received-including Pell, state, and institutional
grants-would likely have seen a change in their federal loans. This is
because federal loan amounts depend, in part, on the amount of other aid
received. However, even if a change in EFC would not have changed other
aid received,13 some students may still have seen a change in their
subsidized Stafford loan amount.14 Among those currently receiving federal
13Because some states and institutions do not use the federal EFC to award
state and institutional aid, a change in the federal EFC may not affect
the amount of such aid.
14Subsidized Stafford loan amounts, unlike unsubsidized Stafford and PLUS
loan amounts, are directly determined by the EFC, subject to an annual
maximum.
loans, we estimate that over 20 percent of subsidized and unsubsidized
Stafford loan holders and about 85 percent of PLUS loan holders could have
seen a change in their loan amount due to their EFC increase. (See app. I
for an explanation of our estimation methodology.) Figure 5 shows the
proportion of undergraduate Stafford loan recipients who could have had a
change in their subsidized loan amounts, by income and dependency status.
Our case studies of students at selected schools for whom a change in EFC
would have resulted in a change in their federal loans show that as the
EFC would have increased, subsidized loans would have decreased, and
unsubsidized loans would have increased in response to the decreases in
subsidized loans and other forms of financial aid. In addition, PLUS loans
could have made up for these decreases as well.15
15PLUS loans were not packaged by our case study schools. However, because
families can borrow up to their EFC (plus any remaining or "unmet" need)
using PLUS loans and because EFCs typically would have increased under the
proposed update, we estimate that PLUS loan amounts could have increased
as well. Furthermore, in cases where a student is already receiving the
maximum unsubsidized loan amount, PLUS loans could have compensated for
decreases in other forms of financial aid.
Figure 5: Percentage of Students Likely to Have Had a Change in Subsidized
Stafford Loans
50
45
43.1
While changes in the EFC could have affected Campus-Based awards,
institutions have some discretion in allocating federal Campus-Based aid;
as a result, the effects of the proposed update would have likely varied
across institutions. The effect of the update on state and institutional
needbased aid would also have varied based on differences in state and
institutional aid awarding policies and on how much the tax allowance
would have changed for each state.
Our case studies of students at the four selected schools show that even
though the EFC for the majority of students would have changed,
Campus-Based awards would tend not to have been affected by the proposed
update. However, some students would have been affected, and the effect
would have varied across schools, due in part to differences in award
policies. Specifically, had the proposed allowance been implemented for
2004-2005, we estimate that less than 15 percent on average of case study
students receiving Supplemental Educational Opportunity Grants and
45.3
>100,000 40
35
30
25
20
15
31.8 31.6 10.9
10 5
0 25,000 or less 25,001-50,000 50,001-100,000 Household income (dollars)
Dependents Independents
Source: GAO analysis of CEAD STAB data.
The Extent to Which the Proposed Update Would Have Affected the Allocation
of Federal Campus-Based, State, and Institutional Need-Based Aid Would
Likely Have Varied
Institutions Have Discretion in Allocating Federal Campus-Based Aid, So
the Effects of the Proposed Update Would Likely Have Varied
Work-Study aid would have faced a lower award.16 The effects would have
varied significantly by school because of differences in schools'
eligibility criteria for Campus-Based awards and the maximum awards
provided. For example, eligibility for SEOG at one case study school is
capped at an EFC of $3,850, whereas eligibility at another is at an EFC of
$2,800, so a student whose EFC increased from $2,700 to $2,900 would have
become ineligible for an SEOG at one school but not the other. As another
example, one school offers $3,000 in Work-Study, and another limits the
amount to $1,000, thereby demonstrating the different amounts involved.
With regard to Perkins loans, we estimate that about 20 percent of
students at the case study schools on average would have seen a decrease
in their loan amount due to the proposed update. For students who see
decreases in their Perkins loans, the decrease would have been about
$1,200 on average but would have varied significantly by school due to
differences in eligibility criteria. Table 5 shows the case study results
of changes in these three school-administered federal programs.
Table 5: Estimated Impacts in Campus-Based Aid for Case Study Schools
Average dollar
Percentage with decrease for
Form of Campus-Based aid a decrease those affected
Supplemental Educational Opportunity Grants 11
Work-Study 14 1,200
Perkins Loans 21 1,200
The Effect of the Proposed Update on State Need-Based Aid Would Have
Varied Based on State Policies and Changes in the Tax Allowance
Source: GAO analysis of case study results.
Note: Dollar figures were rounded to the nearest $100. While an increase
in EFC may result in decreases in Campus-Based awards for some recipients,
the amount of such decreases would become available for redistribution to
others.
The majority of states use the federal need analysis methodology to
allocate state need-based aid; as a result, the proposed update could have
affected the amount of and the extent to which students receive state
grants. The effect would have varied by state due to, among other factors,
differences in changes to the tax allowance by state and differences in
state award policies. In Wisconsin, for example, we estimate that over 50
percent of state aid award recipients in our case study would have seen
16Three of the four case study schools reported SEOG information, and all
four schools reported Work-Study and Perkins information.
a decrease in their state award. In contrast, in Tennessee, just over 10
percent of recipients in our case study would have seen a decrease in
their state award. The average reduction for Wisconsin students would have
been less than that for Tennessee students due to the differences in how
the states compute awards: Wisconsin's computation decreases aid for each
dollar increase in EFC by less than Tennessee's computation. (See table
6.)
Table 6: Estimated Impacts in State Need-Based Aid for Two States
Percentage with a lower amount Average dollar decrease
Wisconsin 53 -115
Tennessee 13 -220
The Effect of the Proposed Update on Institutional Need-Based Aid Would
Vary Based on Institutional Policies and Changes in the EFC and Other
Factors
Source: GAO analysis of case study results.
Note: Dollar figures are rounded to the nearest $5.
As with state aid, the effect of the proposed update on the need-based aid
provided by schools themselves would have varied significantly across
schools due to, among other factors, differences in institutional award
policies and changes in the EFC of students attending the institutions.
However, the impact would be limited to schools that use the federal
methodology to award aid. Since institutional aid may change as a result
of both changes in the EFC and changes in other aid awarded, the effect of
the increased EFC on institutional aid cannot be easily determined. For
example, a school that bases its award solely on EFC might decrease its
award as a result of an EFC increase, while a school that bases
institutional aid on other aid awarded might increase the institutional
award for some students. At the two private nonprofit schools included in
our case studies,17 our results show that while more than 20 percent of
students at each school would have faced a decrease in institutional
needbased aid under the proposed allowance, more than 10 percent of
students at these same schools would have received more institutional aid.
Overall, case study students attending one private nonprofit school would
have seen a decrease in institutional aid of almost $800 on average,
whereas
17The two public schools do not offer need-based institutional aid.
students at the other school would have seen a decrease of over $425 on
average.18
The Current Allowance May Not Capture the Taxes Paid Due to the Type of
Data and Methodology in Use
As a result of certain limitations of the SOI dataset for the purpose of
calculating the allowance and problems with how Education uses this
dataset, the current state and other tax allowance may not reflect the
amount of taxes paid by students and families. The dataset is limited for
this purpose because the taxpayers included in it are generally not
representative of financial aid applicants, the tax data it provides do
not include all state and other taxes paid by students and families, and
the tax data are several years older than the income information reported
by students and families on the FAFSA. In addition to the limitations of
the SOI dataset, Education does not make full use of the dataset to
account for the varying tax rates paid by taxpayers in different income
groups.
The Tax Data Used for the Allowance May Not Represent Those Taxes Paid by
Financial Aid Applicants
The tax allowance calculated by Education may not reflect the taxes paid
by most financial aid applicants because it is drawn only from those who
itemize deductions on federal income tax returns-filers who may be taxed
at a different rate than those who do not itemize. Because many FAFSA
applicants have lower income-and taxpayers in lower income groups tend not
to itemize-many applicants may not itemize. Specifically, we estimate that
about 63 percent of FAFSA applicants do not itemize.19 Further, itemizers
and nonitemizers within the same gross income group may have different
state and other tax rates. On the one hand, for example, itemizers may be
more likely to own a home than nonitemizers and thus would have a higher
state and local tax liability due to real estate taxes. Conversely, those
who itemize on their federal tax return may be more likely to itemize on
their state return-and therefore have larger deductions, a lower state
taxable income, and thus a lower state income tax than those who do not
itemize on their federal return.
18Case studies show that the majority of aid recipients would have seen a
decrease in their need-based aid equal to or less than their EFC increase.
However, for about 8 percent of aid recipients, the decrease in need-based
aid would have been more than 150 percent of their EFC increase.
19This estimate is made using 2001 SOI data on the percentage of tax
returns itemized by various income groups and FAFSA Applicant File data on
the income distribution in 2001 of FAFSA applicants. To make this
estimate, we assumed that FAFSA applicants within the income groups
specified by SOI have the same likelihood of itemizing their tax return as
overall taxpayers do.
Data Used for the Current Allowance No Longer Include State and Local
Sales Taxes
Although sales taxes were included in SOI data when Congress formally
provided for a tax allowance in the 1986 HEA amendments,20 tax reform
legislation subsequently disallowed the deduction of state and local sales
taxes, effectively eliminating them from this dataset. Therefore, the data
collected by SOI for tax year 1987 and beyond have not reflected all state
and other taxes. Excluding sales taxes may cause the allowance to be lower
than it otherwise would be, especially for students and families who
reside in states where sales taxes compose a significant portion of state
and local revenue. In October 2004, Congress passed and the President
signed the American Jobs Creation Act of 2004, which provides taxpayers
who itemize deductions the choice of claiming a state and local tax
deduction for either sales or income taxes, but only for tax years 2004
and 2005. As a result, the data collected by SOI for tax years 2004 and
2005 will likely include a mix of sales and income tax deductions
reflecting the choices made by tax filers. Were these data used to update
the allowance, the deductibility of sales taxes could increase the
allowance for students and families, especially for those who reside in
states where sales taxes compose a significant portion of state and local
revenue. Regardless, the SOI data will not reflect both state and local
sales and income taxes paid by individual taxpayers, as was the case prior
to tax year 1987.
SOI Tax Data Are Several Years Older than Reported Income Information
SOI data available for any given award year are several years older than
the income information reported by aid applicants on the FAFSA. For
example, in its proposed update for award year 2004-2005 that was
published in May 2003, Education used 2000 SOI data, the most recent
available at the time of its data request. Because applicants would report
2003 income information for award year 2004-2005, had the allowance been
implemented, there would have been a mismatch of 3 years between the tax
data and the income data.21 Table 7 shows when SOI publishes the state and
local tax data after the end of a tax year. Some time lag between the end
of a tax year and when SOI publishes data for that year is expected
because returns are collected after the end of the tax year and because of
the time needed for processing those returns. This time lag could be
extended when there are unexpected difficulties in processing the returns.
For example, 2002 tax data were published after about 2 years, while 2000
and 2001 were published in 15 months. Further, SOI officials reported that
201983 SOI tax data was used in establishing the tax allowance when it was
first incorporated in the HEA amendments.
21The FAFSA requires applicants to report asset information as of the date
of the application.
the agency may be unable to publish the 2003 tax tables because it has
been experiencing technical problems in processing returns from that
year.22
Table 7: Publication Dates of SOI State and Local Tax Data
Tax year Publication date Elapsed time in months
1997 June 2000
1998 February 2001
1999 July 2001
2000 April 2002
2001 April 2003
2002 October 2004
Source: Interviews with SOI officials and GAO analysis.
Education's Calculation of the Allowance Does Not Fully Consider Varying
Tax Levels Paid by Different Income Groups
Education's method of calculating the state and other tax allowance does
not accurately capture the amount in taxes paid by students and families.
While Education calculates an allowance for each of the two income
categories established by Congress-those earning less than $15,000 and
those earning $15,000 or more23-its methodology does not take into account
the varying level of taxes paid by these two groups. To determine the
allowance for families with income less than $15,000, Education uses the
total of state and local taxes paid by all tax itemizers regardless of
income, despite the fact that the SOI data provide separate information
for 12 different income groups.24 Education's methodology likely
22According to an SOI official, while SOI has made a commitment to fix
technical problems with its 2003 master files containing the state and
other tax data, it is uncertain whether it can provide the level of detail
needed to update the allowance or when it could release such information.
23In contrast, the Institutional Methodology (IM) used by the College
Board has 12 income categories for families, which some experts told us
allows for more refined estimates of state and other taxes paid by
financial aid applicants.
24To determine the allowance for this group, the methodology involves
taking the sum of the state and other taxes claimed as income tax
deductions divided by the adjusted gross income (AGI). AGI is the amount
used in the calculation of an individual's income tax liability and one's
income after certain adjustments are made, but before standardized and
itemized deductions and personal exemptions are made. The sum of the taxes
paid includes taxes such as state and local income taxes, personal
property taxes, and real estate taxes. For the dependents and independents
without children, the methodology involves dividing the state and local
income tax by AGI.
overestimates the taxes paid by the lower-income group for two reasons.
First, higher-income individuals generally face higher tax rates than
lowerincome individuals. Our analysis of 2001 SOI tax data shows that
those with an income below $20,000 have a state and other tax liability of
about 3 percent on average, while those with an income of $20,000 or more
have an average 5 percent tax liability. (See app. III.) Second,
higher-income individuals are also more highly represented in the SOI data
than lowerincome individuals. For example, our analysis of the 2001 income
distribution of financial aid applicants and of itemizers shows that about
35 percent of aid applicants have an income of less than $20,000, while
less than 10 percent of itemizers have incomes in that range. (See table
8.)
Table 8: Comparison of Income Distribution in 2001 of FAFSA Applicants and
Federal Income Tax Itemizers Dollars
0.01 10,000 20,000 30,000 50,000 75,000 100,000 150,000 200,000 500,000 million
0 or to to to to to to to to to to or
Less 9,999 19,999 29,999 49,999 74,999 99,999 149,999 199,999 499,999 999,999 more
Percentage
of FAFSA
applicants 2.51 15.44 16.76 15.50 18.60 13.95 8.40 6.45 1.51 0.81 0.06 0.01
Percentage
of
itemizers 0.76 2.07 5.12 7.85 20.70 24.85 16.27 12.87 4.12 4.25 0.73 0.40
Sources: GAO analysis of Education's 2002-2003 sample of FAFSA applicants
and data from the Internal Revenue Service's Statistics of Income
Division.
Note: The 12 income groups shown in this table are those used by SOI to
display state and local tax information.
To calculate the allowance for the higher-income group, Education deducts
a percentage point from the rate it calculates for the lower income group,
a process that fails to account for the fact that higher-income
individuals face higher tax rates than lower-income individuals. Since the
estimate for the lower-income group reflects more of the taxes paid by
those with higher income, this methodology likely underestimates the taxes
paid by this higher-income group.
Four Strategies Might Address Some of the Limitations Associated with the
Tax Allowance and Would Yield a Variety of Effects on Federal Spending and
Aid Recipients
We have identified four strategies for addressing the limitations of the
tax allowance that range from modest to more substantial changes to the
process: (1) continue to use SOI data but with a revised method for
calculating the allowance, (2) substitute SOI data with one of several
alternative data sources, (3) use the same allowance for all aid
applicants without regard to state of residence, or (4) collect
information directly from the aid applicants themselves. Except for the
first option, use of these strategies would require legislative changes.
Also, these four strategies differ in their impacts on federal costs and
on aid applicants.
Use SOI Data with a Revised Methodology
The first strategy would be to make better use of SOI data to calculate
the tax allowance, such as by modifying how the allowance is calculated
and coordinating with SOI to ensure that the most recently available data
are used. Education could use the SOI data on separate income bands to
calculate the allowance for families rather than using the aggregate
totals that SOI publishes.25 This would ensure that tax rates for
different income bands are based on information more representative of
those groups. With regard to coordinating with SOI, Education obtained SOI
data for tax year 2000 for its update in 2003 about 3 months before SOI
published data for tax year 2001. Thus, when Education published its
proposed update in 2003, it was not based on the most recently available
data. Coordinating with SOI could reduce the mismatch between the year of
the income data collected from applicants and the tax data collected from
SOI from 3 to 2 years. Education officials acknowledged that in the
future, they may have the flexibility to wait for more recently available
SOI data and still meet their schedule for publishing notice of a proposed
update to the state and other tax allowance. Appendix IV shows what the
tax allowance would be under this strategy for each state.
25The income categories established by Congress differ from those
published by SOI. Congress established income categories of $0 to less
than $15,000 and $15,000 and above, while SOI data income categories are
different. Education could have SOI data customized to provide the
required categories or could use the data on the income groups that best
match the established categories.
Replace SOI Data with One of Several Other Datasets
The second strategy would be to discontinue use of SOI tax data and to
replace it with publicly available data, such as the following:
o Bureau of Economic Analysis Personal Income and U.S. Census Bureau Tax
Tables
o Description-The Bureau of Economic Analysis (BEA) annually publishes
"Personal Income" tables, which cover aggregate household income, by state
and are based on data from federal and state government programs, such as
state unemployment insurance programs.26 The U.S. Census Bureau annually
publishes "State
Government Tax Collections" tables, which include overall state figures
for individual income taxes, real estate taxes levied by states but not
local governments, property taxes, and sales taxes for both individuals
and businesses. This information is gathered by the U.S. Census Bureau
through a mail canvass of appropriate state government offices that are
directly involved with state-administered taxes; locally collected and
retained tax amounts are not included in the survey. Both sets of tables
and related documentation are available via the Internet.27
o Use-Education could calculate the allowance by combining the
information from both sets of tables. This approach has three potential
advantages over using SOI data: The BEA data includes income from the
entire population, including both filers and nonfilers, and the census
data covers all tax filers instead of only itemizers, whereas SOI data
only include itemizers, sales taxes are included in the tax collections
tables-although they include taxes paid by businesses- and information is
available 4 months after the end of a year.28 This allows income data
reported by aid applicants and tax information corresponding to the prior
year to be used to develop the allowance. A disadvantage of census data as
compared with SOI data is that property
26In the BEA tax tables, household income includes wage and salary
disbursements,
supplements to wages and salaries, proprietors' income with inventory
valuation and
capital consumption adjustments, rental income of persons with capital
consumption
adjustment, personal dividend income, personal interest income, and
personal current
transfer receipts, less contributions for government social insurance.
27 BEA: Methodology-http://www.bea.gov/bea/regional/articles/spi2002
Reliability
assessment-http://www.bea.gov/bea/papers/Reliability_SPI_Estimates.PDF.
Census:
Methodology-http://www.census.gov/govs/www/statetaxtechdoc2003.html.
Reliability assessment - none available.
28These tables are also available on a quarterly basis. However, GAO used
the annual
publication to develop the alternative allowances for this report.
tax information is more limited. Like the SOI data, the tables published
by the BEA and the U.S. Census Bureau reflect aggregate measures of taxes
and income and would not necessarily reflect the experiences of the
typical family. Also, because the BEA and the U.S. Census Bureau report
information in the aggregate-whereas SOI data are separated into different
income bands-Education would need to make adjustments to differentiate tax
rates by income.
o U.S. Census Bureau-Current Population Survey (CPS)-Annual Social and
Economic Supplement (ASEC)
o Description-The Census Bureau annually publishes the Annual Social and
Economic Supplement to the Current Population Survey, which includes
income, estimated state income taxes, and estimated real estate taxes. The
CPS household income information is gathered through a survey of 100,000
households. State income tax information is estimated by the U.S. Census
Bureau based on reported income and filing status information and review
of state income tax regulations. Real estate tax information is generated
in a similar manner. Household characteristics are matched to the Census
Bureau's American Housing Survey to provide simulated real estate and
property taxes. The CPS dataset and related documentation are available
via the Internet.
o Use-Education could use CPS household-level data to generate tax
allowances by income. An advantage of using the CPS is that it allows
Education to estimate the taxes paid by the typical family rather than the
taxes paid in aggregate, and CPS data also reflect the entire
population-itemizers, nonitemizers, and nonfilers. Two disadvantages are
that although we have assessed the information collected by the U.S.
Census Bureau in generating the CPS to be reliable, the CPS tax
information is not based on actual taxes paid but rather on U.S. Census
Bureau tax models and is therefore subject to error and that the CPS does
not include sales taxes. In addition, CPS data are available only somewhat
sooner than SOI data, and because of the size of its sample, a 3-year
average must be taken to generate reliable state-level information.
o Institute on Taxation and Economic Policy (ITEP)-Who Pays? A
Distributional Analysis of the Tax Systems in All 50 States
o Description-ITEP is a nonprofit research and education organization
that has published two reports on state taxes, one in 1996 and one in
2003, both entitled Who Pays? A Distributional Analysis of the Tax
Systems in All 50 States. According to an ITEP official, ITEP plans to
publish future updates every 3 years. These reports present estimated
state information on income, real estate, property, and sales tax rates.
The ITEP state tax tables are based on the 1988 public-use SOI sample of
365,000 federal tax returns, stratified so that they are representative at
the state level and aged to reflect the most recent statistics on general
population and tax filer characteristics published by the IRS and the U.S.
Census Bureau. These returns and state tax regulations are analyzed to
estimate state, local, real estate, property, and sales taxes paid based
on household characteristics. Adjustments are made to reflect potential
nonfilers as well. These reports are available via the Internet.
o Use-Were Education to determine ITEP data reliable, Education could
use the ITEP tax figures to generate tax allowances by income band.29 Two
advantages of ITEP data are that they include sales taxes
and that an adjustment is made to estimate what nonfilers pay in sales
taxes, whereas SOI data do not reflect sales taxes and do not account for
nonfilers. A disadvantage is that ITEP's income bands are not consistent
across states and do not match those established by Congress.
While these publications are publicly available, Education could also
contract with any of these organizations to customize a dataset for the
purpose of developing the tax allowance.
Apply a Standard Allowance to All Aid Applicants, Regardless of State of
Residence
The third strategy would be to apply the same allowance to all aid
applicants, regardless of their state of residence. This would involve
creating a standard allowance based on the CPS that reflects the median
taxes paid by all households.30 This strategy would have the advantage of
simplifying the need analysis methodology, but a disadvantage is that it
would not account for the variation in taxes paid across states or income
bands. For example, using a standard allowance may on average
underestimate the taxes paid by those from high-tax states but may
overestimate the taxes paid by those from low-tax states.
29As explained in appendix I, we were unable to determine the reliability
of the ITEP data.
30Education could use any data source, including those discussed above
that provides household-level information to generate the income and taxes
paid by the median household.
Collect Tax Information Directly from Aid Applicants
The fourth strategy would be to collect tax information directly from aid
applicants by adding questions to the financial aid application form.
Under this strategy, applicants would report state and other taxes along
with their federal taxes paid, information that could be used to reduce
available household financial resources directly, making an allowance
unnecessary. While documentation would likely be available for aid
applicants to use in reporting their state income and property taxes,
documentation concerning sales taxes may not be as readily available.
Independent of this report, the Advisory Committee on Student Financial
Assistance is currently assessing this strategy in the context of
simplifying the financial aid application process and is expected to
release its report in early 2005. One of the options considered by the
Advisory Committee on Student Financial Assistance is to have the FAFSA
questions tailored to the applicant, where applicants from different
states (and with different financial circumstances) would answer different
questions, and questions not relevant to an applicant would not be asked.
Education officials expressed concern with this strategy because it might
add to the administrative burden of students, schools, and Education. For
example, Education's current guidance directs applicants to specific line
items from their federal tax returns for their federal taxes paid, and it
would be difficult to do the same with state taxes, given the variations
among state tax forms. Because institutions are required, on a limited
basis, to verify information reported by students and families on the
FAFSA, Education officials noted that having students and families report
additional information on the FAFSA could increase the burden on
institutions of verifying such information.
Strategies Would Differ in Terms of Their Effects on Federal Student Aid
Expenditures and Financial Aid Applicants
These various strategies would have differed in their impacts on federal
expenditures and on financial aid applicants if they were applied to the
2004-2005 award year.31 First, each strategy would have changed federal
expenditures for grant and loan programs, for acquiring data, and for
other administrative activities. For example, we estimate that Pell Grant
program expenditures could have increased by as much as $400 million or
decreased by as much as $200 million were the different options adopted
and used to allocate aid for 2004-2005. Second, each strategy would have
affected the amount of federal, state, and institutional aid that
financial aid applicants receive and the number of applicants receiving
such aid. For Pell Grants, using a standard allowance of 4 percent would
have caused about 83,000 recipients to become ineligible for the program,
but the other options would have affected fewer recipients. Table 9 shows
the potential merits of each option in terms of federal expenditures for
the Pell Grant program and the impact on expected family contribution, and
table 1032 shows the extent to which the tax allowances calculated under
each strategy would accurately reflect state and local taxes paid by
students and families.
31Our estimates on the impacts are limited to changes in the EFC and Pell
Grant program. We were not able to assess the impact for federal Stafford
loans and Campus-Based, state, or institutional aid programs. As
previously mentioned, estimating the impact on federal Stafford loans
would require data on the extent to which the amount of other forms of aid
changed as a result of a change in EFC, and such data are not available at
a national level. Because schools vary in the way they award Campus-Based
aid, we were similarly unable to assess the potential effects on these
programs nationally. With respect to state and institutional aid, there is
no central repository of information on state and institutional awarding
policies, which prevented us from estimating changes in state and
institutional aid.
32As previously discussed, recent legislation providing taxpayers who
itemize deductions the choice of claiming a state and local tax deduction
for either sales or income taxes would affect the data collected by SOI.
Because these effects would be limited to 2 tax years-2004 and 2005-and
the effects could not be estimated, we did not consider them in our
comparisons.
Table 9: Framework for Evaluating Options Identified to Change the State
and Other Tax Allowance Relative to the Current Allowance in Use
Proposed Strategy I
Strategy II Alternative data sources Strategy III Strategy IV
Proposed 2004-2005 tables
SOI with revised
a
methodology
BEA / Censusb
CPS (ASEC)c ITEPd
Standard
allowance (4%)e
Add question to FAFSAf
Change in federal - 0.3 + 0.1 + 0.2 - 0.2 + 0.4 - 0.2
Pell
Grant expenditureg billion billion billion billion billion billion -
Percentage of
students
facing a reduction
in
Pell Grant award 38 19 11 32 2 29 -
Percentage
retaining
eligibility 36 19 11 31 2 27 -
Percentage not
retaining
eligibility (number 2 <1 <1 1 <1 2
of students
affected)h (92,000) (26,000) (22,000) (62,000) (1,000) (83,000) -
Average dollar
change
in Pell Grant award
for
those with a - 144 - 103 - 135 - 118 - 90 - 177 -
decrease i
Change in expected + 3.5 + 0.4 - 0.9 + 2.3 - 3.9 + 2.8
family billion billion billion billion billion billion -
contributionj
Percentage of
students
facing an increase
in
EFC 62 38 22 59 4 48 -
Average dollar
change
in EFC for those
with an
increase k 493 295 471 338 242 616 -
Source: GAO analysis.
Notes: All alternatives are based on what information would have been
available to Education as of January of 2003 for publication in the May
2003 Federal Register.
aThe "SOI with Revised Methodology" figures are based on 2000 SOI data and
were calculated (by income band) by dividing the aggregate total taxes
paid deduction by the aggregate adjusted gross income for families and by
dividing the aggregate state and local income taxes by the aggregate
adjusted gross income for individuals.
bThe "BEA/Census" figures are based on 2001 BEA and U.S. Census data and
were calculated by dividing the sum of property taxes, general sales and
gross receipts, and individual income taxes from the U.S. Census by
personal income from the BEA for families and by dividing the sum of
general sales and gross receipts and individual income taxes from the U.S.
Census by personal income from the BEA for individuals. Note that BEA and
U.S. Census data are not provided separately by income band.
cThe "CPS" figures were generated based on a 3-year average of the median
effective tax rate, by state, across 1999, 2000, and 2001 CPS data, as
prescribed by CPS documentation for the study of state-based information
in the CPS. The median effective tax rate reflects the median across
households of the sum of state income taxes paid and household property
taxes divided by total personal income for families and of state income
taxes paid divided by total personal income for individuals.
dThe "ITEP" figures are based on ITEP's analysis of tax data and were
calculated for each income band by summing general sales tax rates, other
sales and excise tax rates, property tax rates, and personal income tax
rates for families and by summing general sales tax rates, other sales and
excise tax rates, and personal income tax rates for individuals. As
explained in appendix I, we were unable to determine the reliability of
the ITEP data.
eThe standard allowance of 4 percent is based on an estimate of the median
household across states using CPS data.
fThe impacts of adding a question to the FAFSA could not be estimated.
gThe estimated expenditure of the Pell Program in award year 2004-2005 is
about $13 billion under the current allowance.
hThe sampling errors for those not retaining eligibility for SOI
(Revised), Census/BEA, and ITEP range from 6 percent (SOI) to 27 percent
(ITEP). All others have a sampling error of 5 percent or less. Figures for
the number of students not retaining eligibility are rounded to the
nearest 1,000.
iThe estimated average Pell award for award year 2004-2005 is about $2,440
under the current allowance.
jThe estimated sum of EFCs across all FAFSA applicants in award year
2004-2005 is about $75 billion under the current allowance.
kThe estimated average EFC in award year 2004-2005 is about $6,450 under
the current allowance.
Figure 6: Framework for Evaluating the Alternative Datasets Identified
Relative to SOI Data
Data quality BEA/Census CPS (ASEC) ITEP FAFSA
Timelinessa b
Data accuracyc d e
Relevancef g
Completenessh
Would improve on SOI data Would not improve on SOI data Would be worse
than SOI data Undetermined
Source: GAO analysis
Notes: The data quality categories are based upon those described in the
Office of Management and Budget (OMB) guidelines for assessing data
quality. Please see OMB document "Statistical Policy Working Paper 31 -
Measuring and Reporting Sources of Error in Surveys."
aThe assessment of "timeliness" is based on whether Education would be
able to base its published allowance tables on more recent data than under
SOI or not.
bFor years in which ITEP publishes updated tax rates, Education would be
able to use more recent data in calculating the allowance than SOI data
would allow, but in other years ITEP data would not yield an advantage
over SOI data and may in fact be based on data older than what SOI would
provide.
Conclusions
Recommendations for Executive Action
cThe assessment of "data accuracy" is based on whether the allowance for
state, local, property, real estate, and other taxes is based on a
population more representative of financial aid applicants and whether a
current reliability assessment is available for review.
dThe CPS property tax data are based on a Census model. Since this model
has not been assessed for accuracy since 1992, the accuracy of the CPS tax
data is undetermined. If the data proved to be accurate, then this data
source would be an improvement compared with SOI data.
eAs explained in appendix I, we were unable to determine the reliability
of the ITEP data.
fThe assessment of "relevance" is based on whether state, local, and sales
taxes are included in the calculation.
gBecause property taxes reported by the U.S. Census Bureau are limited and
because sales taxes include both those paid by individuals and
corporations, we were unable to determine the relevance of U.S. Census
Bureau tax data.
hThe assessment of "completeness" is based on whether data are provided on
an individual basis and whether the appropriate income bands are
represented.
Millions of students rely on federal, state, and institutional aid every
year to help pay for their postsecondary education. These awards are
distributed to students and their families based in part on estimates
about what they can afford to pay out of their own pockets. Yet if these
estimates are considerably incorrect, the awards may not be distributed as
equitably as they could be. Because state and local tax rates may have
changed over the past decade, and Education has updated the allowance only
once and given the limited way in which Education uses SOI data, it is
very likely that the federal government may have been making an allowance
for more taxes than were actually paid, or in other cases,
undercompensating for taxes that were paid. Although Education has taken
some recent steps to update the allowance, these efforts have not been
successful. An inaccurate allowance could yield adverse effects for the
federal government and students and their families. On the one hand,
students and families could erroneously gain eligibility, which would
cause federal funds to be misdirected. On the other, students and families
could inappropriately lose eligibility for aid. Because state and
institutional aid programs also make use of the federal need analysis
methodology, such losses may be compounded for students and families.
To ensure that relevant tax data from the Statistics of Income are
requested systematically and that the most recent data are obtained, we
recommend, in the short run, that the Secretary of Education develop
formalized updating procedures and document such procedures in writing.
Such procedures could include (1) making annual written requests to the
Internal Revenue Service for state and local tax information and
documenting those requests and (2) coordinating with the IRS to make
Agency Comments
sure Education knows when SOI data will be publicly released and to ensure
that the most currently available data are used.
To better capture the amount of taxes paid by students and families, we
also recommend, in the short run, that Education revise its methodology
for calculating the state and other tax allowance. Revisions could include
using tax figures reflective of the different income groups to calculate
the allowance rather than figures based on all itemized tax returns.
To determine whether alternative methodologies and data would better
enable Education to annually update the allowance, we recommend, in the
longer run, that Education assess the cost and reliability of available
data, including the alternative data sources identified in this report. If
Education determines that statutory changes are needed to implement more
effective alternatives, it should seek such changes from Congress.
In written comments on our draft report Education generally agreed with
our reported findings and recommendations. In its letter, Education
offered a number of suggestions and observations. Education requested that
we refer to the state tax rates as "`proposed state tax rates under the
HEA' in the final report rather than using the label `proposed state tax
rates of the Department,'" because it believes it does not have the
authority to "ignore the clear statutory requirement to perform the
update." Because we explain in our report that the Congress incorporated
the state and other tax allowance in the HEA and required Education to
annually revise the allowance, we do not believe our characterization of
the state tax rates leads to any confusion. Accordingly, we did not change
how we refer to the state tax rates.
Education also commented on the strategies we identified that address some
of the limitations associated with the tax allowance and noted that it
would review each of the alternative data sources discussed in our report
that could be used to substitute for the SOI file data, as we recommended.
Education noted that it believed all four strategies we identified in our
report would likely require congressional action. We agree that those
strategies that involve using alternative data sources to substitute for
the SOI file data would require legislative changes, as we noted in our
report. We also agree with Education's comment that using income bands
other than those specified by Congress would likely require legislative
change. We disagree that congressional action is required for Education to
continue to use SOI data but with a revised method for calculating the
allowance-one of the strategies identified in our report. While the HEA
directs Education to use the SOI file to revise the allowance, and
establishes the income categories for which the allowance should be
calculated for parents of dependent students and independent students with
dependents other than a spouse (which we define as "families" in this
report), the HEA does not specify a particular method to calculate the
allowance. Therefore, we believe that Education could revise its
methodology, as we recommended, without congressional action. Education
also echoed some of the disadvantages we discussed in our report
associated with applying the same allowance to all applicants and
collecting tax information directly from aid applicants by adding
questions to the application form.
Education also stated that it generally agreed with our assessment of the
impact of the revised allowance tables on Pell Grant recipients but noted
that we could have provided additional information concerning applicants
who would no longer have been eligible for Pell Grants. As we stated in
the report, these applicants typically would no longer have received the
minimum Pell Grant award, reflecting that such applicants typically have
higher incomes than those who would have continued to receive Pell Grants.
Additionally, we show that Pell Grant recipients with household income
over $25,000 would have been significantly more likely to have either
received less in Pell Grants or become ineligible for them. Education also
suggested in its letter that it would be helpful to clarify that a change
in EFC would not necessarily cause an identical change to a student's
award amount with respect to federal student loans, Campus-Based aid, and
state and institutional financial aid programs: "in other words," the
department noted, "include a brief explanation of potential interactive
effects." As noted in our report, our case studies of students at selected
schools showed that as the EFC would have increased, subsidized loans
would have decreased, and unsubsidized loans would have increased in
response to the decreases in other forms of financial aid. In response to
Education's comment, however, we added information concerning how EFC
changes would have affected need-based aid overall with respect to our
case study schools. Education also noted that it understood why we chose
to analyze the effects of the proposed 2003 update had it been implemented
in 2004-2005. (Soon after we had submitted our draft report to Education
for comment, the department published, on December 23, 2004, an updated
allowance for the 2005-2006 award year.) In its letter, Education includes
the results from its preliminary analysis of the effects of the 2004
update for 2005-2006. Education's results are generally consistent with
the results from our analysis. We did not, however, verify the accuracy of
Education's estimates.
Education also expressed concern that we misinterpreted the department's
intentions with respect to updating the allowance for the 2005-2006 award
year. While we understood the department's intentions, we made technical
clarifications to the report to address Education's concern.
With respect to our recommendation that the department establish formal
procedures to ensure that it annually requests and obtains the most
current tax data from the IRS, Education stated that it had such
procedures in place as "evidenced by the update published in the spring of
2003." However, as noted in our report, Education could not provide us
with written procedures guiding staff on the routine steps necessary to
update the tax allowance or to identify what data would be needed to
update the allowance. In response to the department's comment, we
clarified that our recommendation included documenting formalized
procedures in writing. Lastly, Education provided technical comments,
which we incorporated as appropriate. Education's written comments appear
in appendix V.
As agreed with your offices, unless you publicly announce its contents
earlier, we plan no further distribution of this report until 7 days from
its
date. At that time we will send copies of this report to the Secretary of
Education, appropriate congressional committees, and other interested
parties. In addition, the report will be available at no charge on GAO's
Web
site at http://www.gao.gov.
If you or your staff have any questions about this report, please call me
on
(202) 512-8403 or Jeff Appel, Assistant Director, on (202) 512-9915. You
may also reach us by e-mail at [email protected] or [email protected].
Other contacts and staff acknowledgments are listed in appendix VI.
Cornelia M. Ashby
Director, Education, Workforce,
and Income Security Issues
Congressional Requesters
The Honorable Edward M. Kennedy Ranking Minority Member Committee on
Health, Education,
Labor, and Pensions United States Senate
The Honorable Christopher J. Dodd United States Senate
The Honorable Tom Harkin United States Senate
The Honorable Barbara A. Mikulski United States Senate
The Honorable James M. Jeffords United States Senate
The Honorable Jeff Bingaman United States Senate
The Honorable Patty Murray United States Senate
The Honorable Jack Reed United States Senate
The Honorable Hillary Rodham Clinton United States Senate
The Honorable Jon S. Corzine United States Senate
Appendix I: Scope and Methodology
Overview The objectives of this study were to determine (1) what tax data
form the basis of the current tax allowance and what factors have affected
regular updates, (2) the effect the Department of Education's (Education)
proposed update would have had in award year 2004-2005 on financial
assistance for students and families, (3) the extent to which current
methods for determining the allowance accurately measure how much students
and families have paid in state and other taxes, and (4) the strategies
available to address any problems in deriving the allowance.
To carry out the objectives, we analyzed Education's 2002-2003 aid
applicant sample file and Education's Cost Estimation and Analysis
Division's Statistical Abstract (CEAD STAB), the most current versions
available at the time of our review. We worked closely with financial aid
officials from two states-Tennessee and Wisconsin-and four colleges- one
public and one private nonprofit school in each of the two states. We
interviewed officials from the U.S. Department of Education, Advisory
Committee on Student Financial Assistance (ACSFA), and U.S. Department of
the Treasury's Internal Revenue Service-Statistics of Income (SOI)
Division-as well as officials from the states and schools we contacted. We
also interviewed officials from associations representing institutions,
including the American Association of State Colleges and Universities
(AASCU), National Association of Independent Colleges and Universities
(NAICU) and the College Board, as well as other experts. In addition, we
reviewed and analyzed the statutory requirements and legislative history
of the state and other tax allowance. Furthermore, we reviewed and
analyzed state and other tax data from SOI, Bureau of the Census, Bureau
of Economic Analysis, and the Institute on Taxation and Economic Policy.
We performed our work in accordance with generally accepted government
auditing standards between October 2003 and November 2004.
Datasets In estimating how Education's proposed update would affect
students' and their families' eligibility for financial assistance, we
analyzed two datasets. We used Education's aid applicant sample file from
the 2002-2003 award year to estimate changes in (a) expected family
contribution and Pell awards nationally, (b) state need-based aid for
Wisconsin and Tennessee, (c) Supplemental Educational Opportunity Grants
(SEOG), Perkins loans and Work-Study, and (d) institutional need-based aid
for the four institutions. This dataset is a randomly drawn, nationally
representative sample of over 450,000 aid applicants. To estimate the
percentage of Stafford subsidized and unsubsidized and Parent Loans for
Undergraduate Students (PLUS) recipients that are likely to have their
loan award
Appendix I: Scope and Methodology
changed, we used Education's CEAD STAB. CEAD STAB is a randomly drawn,
representative sample of 1.8 million borrowers (about 7 million loans)
from the National Student Loan Data System (NSLDS), which is a
comprehensive national database of Title IV loan and grant recipients. Our
analysis of the CEAD STAB focused on Stafford subsidized and unsubsidized
and PLUS borrowers who originated loans from July 2002 to June 2004. We
assessed the reliability of both datasets by conducting electronic testing
of key variables for obvious problems in accuracy and completeness,
interviewing appropriate Education officials, and reviewing related
documentation. Based on these tests and reviews, we determined that the
samples were sufficiently reliable for our purposes.
Estimation Methodology
EFC and Pell Grants
To estimate changes in expected family contribution (EFC) and Pell Grant
awards nationally, our analysis followed Education's approach to
estimating EFC and Pell awards in the 2004-2005 award year. To do this,
the 2002-2003 aid applicant sample file was converted to better reflect
aid applicants in the 2004-2005 award year by adjusting all income and
asset amounts for inflation and changing the weights assigned to each
sample applicant so that the sample takes into account projected changes
in the number and type of applicants. We reviewed Education's approach to
converting the sample file to the 2004-2005 award year and calculating EFC
and Pell awards for accuracy and interviewed Education officials about the
approach's reliability. We determined that Education's approach was
sufficiently reliable for our purposes.
EFC and Pell awards in the 2004-2005 award year were estimated for each
sample aid applicant using both the current 2004-2005 state and other tax
allowance, which is based on 1988 SOI data, and the proposed 2004-2005
state and other tax allowance, which is based on 2000 SOI data. To assess
the impact of the update on EFC and Pell Grant awards, these amounts were
compared. We also examined how these impacts vary by family income,
dependency status, and state of residence. We designated student state of
residence as the state of residence of the parent(s) when they differed.
Stafford and PLUS Loans Our methodology for obtaining national-level
estimates on the percentage of loan recipients who could have had their
loan award affected involved the steps listed below.
Appendix I: Scope and Methodology
1. Using the aid applicant sample file, we estimated the percentage of
applicants in award year 2004-2005 who would have had their EFC changed
because of the proposed update for each combination of dependency status,
state of residence, and specified income group.
2. We used the resulting percentages to estimate the likelihood that each
CEAD-STAB sample borrower's EFC would have been changed due to the update.
3. We estimated the likelihood that each individual borrower would have
had his or her Stafford subsidized and unsubsidized loan award affected as
equal to this percentage if the recipient borrowed less than the maximum
allowed by law. We estimated as zero the likelihood that each individual
borrower would have had his or her Stafford subsidized and unsubsidized
loan award affected if the recipient borrowed the maximum allowed by law.
4. For PLUS recipients, the likelihood that each recipient would have had
his or her aid award affected was estimated as equal to the percentage who
would have had their EFC changed because of the proposed update that we
estimated from our analysis of the aid applicant sample file.
Estimating whether students would have seen a change in their loan amounts
because of the proposed update is complex largely because these loan
amounts depend on the extent to which all other financial aid
awards-including Campus-Based, state, and institutional aid-would have
been affected, and no complete information is available on the specific
awarding policies of all states and institutions for these types of aid.
To compensate for this lack of information, we made several assumptions
regarding how Stafford and PLUS loans would have been affected, which may
either over- or underestimate what the actual changes would have been.
However, these assumptions may somewhat offset each other, and we believe
our estimates are informative of the percentage of borrowers whose loan
awards could have been affected.
Stafford and PLUS loan estimates may be biased upward for the following
reasons. Stafford loan estimates may be biased upward because we assumed
that all borrowers who currently receive less than the maximum allowed and
whose EFC would have changed under the proposed update would have had
their loan award amount changed as well, yet this is not always the case.
For example, because the subsidized loan award equals the cost of
attendance less EFC and other financial aid awards, subject to the loan
limits, subsidized Stafford loan amounts would not have been
Appendix I: Scope and Methodology
affected if the decrease in other financial aid awards exactly offset the
EFC increase resulting from the proposed update. Because the unsubsidized
Stafford loan award equals the cost of attendance less other financial aid
awards (including subsidized loan awards), subject to the loan limits,
unsubsidized loan amounts would not have been affected if other aid awards
did not change because of the update.1 Furthermore, we assumed that all
PLUS borrowers whose EFC would have changed because of the update would
have had their loan award affected, but, similar to unsubsidized Stafford
loans, this would not have occurred had other aid awards not changed
because of the update. It is difficult to know the size of this upward
bias because the dataset does not include information on the extent to
which other financial aid awards would have been affected.
Our estimates for Stafford loans may be biased downward because we assumed
that all borrowers who receive the maximum allowed would not have had
their loan award affected, which also is not always the case. For
unsubsidized Stafford loans, this bias appears to be very small because
unsubsidized loans would only decrease if students have a cumulative net
increase in their other financial aid awards, which case studies and
expert interviews show to be unlikely. For subsidized Stafford loans, this
bias may be larger, yet we believe that it is still relatively small.
Subsidized Stafford loan awards that are currently at the maximum would
only decrease when the EFC plus other aid increase enough to cause the
student to lose eligibility for the maximum loan amount, and analysis of
the National Postsecondary Student Aid Survey (NPSAS) shows that most
students are not likely to face this circumstance.2
We also assumed that the borrowers in award year 2004-2005, the year of
the proposed update, are from the same states, have the same incomes, and
have the same costs of attendance as the most recent CEAD-STAB borrowers,
and the extent to which they differ would cause our estimates to be less
accurate. For example, if we underestimate the number of students in
likely high-impact states, our estimates would likely
1This could occur for students whose other financial aid awards do not
depend on the federal methodology.
2Our analysis of NPSAS suggests that over 70 percent of subsidized
Stafford loan borrowers would be eligible to borrow an additional $500 or
more were it not for the maximum loan cap. Since the average EFC change is
less than $500, the vast majority of these students would not lose
eligibility for the maximum under the proposed update.
Appendix I: Scope and Methodology
underestimate the overall proportion of students who could face a change
in their loan award.
To complement this national-level loan analysis, we determined the
percentage of students at our case study schools who would have
experienced a change in their subsidized and unsubsidized loans, along
with the size and direction of the changes. We could not determine this
information for PLUS loans for our case study schools since the schools
did not package PLUS loans for the purpose of estimating potential impacts
of the proposed update.
State and Institutional Need-Based Aid and Campus-Based Aid
To provide illustrative examples of how the proposed update can affect
state and institutional need-based aid and Campus-Based aid, we worked
closely with two states-Wisconsin and Tennessee-and four colleges,
including one public and one private nonprofit institution in each of the
two states. We chose these states because they use the Higher Education
Act (HEA) federal methodology to disburse state aid, are geographically
dispersed, and represent high- and low-impact states, based on an index we
calculated for the following components: (1) the average EFC change
resulting from Education's update, (2) the percentage of full-time
undergraduates receiving grant aid, and (3) the average state need-based
grant per undergraduate. We averaged the three components to generate an
index of the overall average impact. The 44 states and the District of
Columbia that use the federal methodology were then sorted in descending
index order and separated into three groups of 15, with the highest index
group being designated "high-impact states," the next group being
designated "medium-impact states," and the last group being designated
"low-impact states." For the components and index value we estimated for
each state, see appendix II. The institutions we chose include the
University of Wisconsin at Madison, Wisconsin's Marian College, Middle
Tennessee State University, and Tennessee's Carson-Newman College. We
chose schools within the two selected states based on the following
criteria: (1) use of the HEA federal methodology to disburse aid, (2)
participation in the federal Campus-Based aid program, (3) provision of
institutional need-based aid,3 (4) number of students with household
income between $25,000 and $75,000, and (5) willingness and capacity to
calculate estimated impacts on need-based aid.
3We were unable to gain the collaboration of a public institution that
offers institutional need-based aid in either of these two states.
Appendix I: Scope and Methodology
For each of these two states and four institutions, we generated a
subsample from Education's aid applicant sample file that reflects the
students who attended school in these two states and the students who
attended school at the four institutions in the 2002-2003 award year. For
each student, the dataset contained information on the student's estimated
EFC under the current and proposed allowance and the student's dependency
status. Using these subsamples, examples of the effect of the proposed
update on state, institutional, and Campus-Based aid were calculated.
While the aid applicant sample file is a nationally representative sample,
it may not be representative of the aid applicants who attend school in
these specific states or at these specific institutions. The subsamples
had the following number of observations:
o Wisconsin: 7,469,
o Tennessee: 8,385,
o University of Wisconsin at Madison: 580,
o Wisconsin's Marian College: 54,
o Middle Tennessee State University: 533, and
o Tennessee's Carson-Newman College: 62.
We estimated the impacts on Wisconsin's state need-based aid using the
Wisconsin subsample, along with the state aid award methodologies provided
to us by the Wisconsin Higher Educational Aids Board. The state need-based
aid programs that we analyzed were the Wisconsin Higher Education Grant
and the Wisconsin Tuition Grant programs.
The Tennessee Student Assistance Corporation, the agency responsible for
determining state aid in Tennessee, performed its own analysis of the
impact on state need-based aid using the Tennessee subsample and then
shared the results with us. The aid program analyzed was the Tennessee
Student Assistance Award. To verify the validity of the Tennessee aid
determination, we verified that the aid awarded fell within the maximum
award limit and that those within an EFC range received similar award
amounts; that is, that those with a lower EFC received a higher award
amount.
To estimate the impacts on institutional need-based and Campus-Based aid,
financial aid directors or financial aid specialists at each of the four
selected schools calculated the impacts using their relevant subsample.
While the focus was on need-based institutional aid and Campus-Based aid,
three institutions also calculated the effect on Stafford loans. To check
the validity of these simulations, we checked (1) the order in which
Appendix I: Scope and Methodology
different forms of aid were awarded to see if they were consistent with
common aid packaging protocols, (2) the formulas used to calculate
remaining need at each stage of the award packaging process to make sure
they were accurate, (3) the range of aid levels awarded to make sure they
fell within bounds defined by regulation, (4) the total aid awarded to
make sure it did not exceed financial need, and (5) the relationship
between aid awarded and EFC levels to make sure that those with lower EFCs
were provided more aid than those with higher EFCs.
Calculation of Estimated Tax Rates from Alternative Data Sources
Methodology For the purposes of this report, we define "families" to
include parents of dependent children (students) and independent students
with dependents other than a spouse, and we define "individuals" to
include dependent students and independent students without dependents
other than a spouse. The specific methodologies used for each source are
described in the footnotes to table 9.
Reliability Assessment
In assessing the reliability of state personal income estimates from the
U.S. Bureau of Economic Analysis (BEA), we reviewed information available
online from the BEA Web site on its data quality assurance processes and
interviewed relevant officials. On the basis of the results of our
document review and discussions with relevant officials, we concluded that
the BEA data we used were reliable for our purposes for this analysis.
In assessing the reliability of state government tax collections estimates
from the U.S. Census Bureau, we interviewed relevant officials, who stated
that there was no published data reliability documentation. Thus, we were
unable to determine if the Census data we used were reliable for our
purposes for this analysis.
In assessing the reliability of data from the U.S. Census Bureau's Annual
Social and Economic Supplement, we reviewed information available online
from the U.S. Census Bureau Web site on its data quality assurance
processes and interviewed relevant officials. On the basis of the results
of
Appendix I: Scope and Methodology
our document review and discussions with relevant officials, we have
determined that the information collected by the U.S. Census Bureau in
generating the Current Population Survey (CPS) is reliable, but we were
unable to determine whether the CPS tax data we used, which is not
collected directly but rather generated from U.S. Census Bureau tax
models, were reliable for our purposes for this analysis.
In assessing the reliability of data from the Institute on Taxation and
Economic Policy's Who Pays publication, we interviewed a relevant official
and reviewed available documentation. However, we were unable to reach a
determination as to the reliability of the data, primarily because of a
lack of sufficient documentation.
Because our analysis relied on samples of aid applicants and borrowers,
our estimates are subject to sampling errors. Sampling errors are often
represented as a 95 percent confidence interval: an interval that 95 times
out of 100 will contain the true population value. For the percentages and
numbers presented in this report on the EFC, Pell award, Stafford loan,
and PLUS loan impacts, we are 95 percent confident that the results we
would have obtained had the entire population been studied are within plus
or minus 5 percent of the results, unless otherwise noted. The results for
state and institutional need-based aid and Campus-Based aid are not
necessarily based on representative samples and therefore should be
considered as case study findings, or illustrative examples. Thus, we did
not calculate sampling errors for these three categories of aid.
Sampling Error
Appendix II: State Selection Matrix-Ranking of Potential Impact of Proposed
Allowance, Listed by Category
Estimated
Percentage of average need-
Overall average students based aid
EFC dollar receiving need-amount per Impact State changea based aid
undergraduate levelb
Minnesota 542 15.01 4,420 High
Vermont 489 34.99 1,749 High
Massachusetts 570 36.22 1,176 High
Illinois 273 28.93 2,998 High
Iowa 611 13.97 2,712 High
Wisconsin 647 27.24 1,098 High
New Jersey 150 30.73 2,701 High
Maine 477 32.72 960 High
Michigan 547 15.26 2,012 High
Indiana 303 19.84 2,612 High
South Carolina 484 21.70 1,228 High
Virginia 456 16.00 1,791 High
Washington 226 23.14 2,007 High
Colorado 430 14.32 1,981 High
California 181 12.55 3,109 High
West Virginia 357 17.24 1,850 Medium
Kentucky 224 27.90 1,246 Medium
Maryland 345 15.56 1,788 Medium
Arkansas 253 19.54 1,736 Medium
North Carolina 335 12.71 2,065 Medium
Delaware 668 2.97 1,370 Medium
New Mexico 268 9.63 2,436 Medium
Nebraska 565 13.09 747 Medium
New Hampshire 591 8.34 884 Medium
Rhode Island 418 15.92 706 Medium
Kansas 411 7.62 1,466 Medium
Connecticut -58 19.21 2,328 Medium
Texas 96 13.45 2,190 Medium
North Dakota 574 7.54 564 Medium
Montana 354 16.08 526 Medium
Tennessee 194 14.10 1,419 Low
Hawaii 509 1.00 1,329 Low
Missouri 255 9.09 1,530 Low
Appendix II: State Selection Matrix-Ranking of Potential Impact of
Proposed Allowance, Listed by Category
Estimated
Percentage of average need-
Overall average students based aid
EFC dollar receiving need-amount per Impact State changea based aid
undergraduate levelb
Oklahoma 199 15.06 1,168 Low
Florida 192 15.36 1,074 Low
Nevada 67 6.50 2,138 Low
District of Columbia 291 3.18 1,149 Low
Utah 251 4.70 749 Low
Wyoming 247 1.06 773 Low
Arizona 181 1.49 966 Low
Georgia 258 0.98 667 Low
Idaho 221 3.70 457 Low
Louisiana 254 1.74 501 Low
Mississippi 151 1.52 940 Low
Alabama 184 1.11 577 Low
Alaska 163 0.00 0 N/A
New York 430 49.10 1,968 N/A
Ohio 431 24.96 1,201 N/A
Oregon 359 15.98 1,070 N/A
Pennsylvania 476 32.89 2,331 N/A
South Dakota 376 0.00 0 N/A
Sources: EFC Change and Impact Category-GAO analysis of Education's
2002-2003 aid applicant sample file and the proposed taxallowance.
Need-Based Aid Information-"National Association of State Student Grant
and Aid Programs' 33rd Annual Survey Report on State-Sponsored Student
Financial Aid, 2001-02 Academic Year.
aThe sampling errors for Alaska, Connecticut, Delaware, District of
Columbia, Hawaii, Idaho, Maine, Montana, Nevada, New Hampshire, New
Mexico, North Dakota, Rhode Island, South Dakota, Utah, Vermont, West
Virginia, and Wyoming vary from slightly over 5 percentage points (for New
Hampshire, Utah, and West Virginia) to just under 15 percentage points
(for District of Columbia). All others have sampling errors at or below 5
percentage points.
bOnly states that use the HEA federal methodology were given a ranking.
Thus, the ranking does not apply to the six states listed last.
Appendix III: Average Tax Rates on Adjusted Gross Income, by State and Income
Level
Tax rate by income level (percentage)
Tax rate by income level (percentage)
State < $20,000 > $20,000 State < $20,000 > $20,000
Alabama 1 3 Montana 2
Alaska 2 2 Nebraska 1
Arizona 1 4 Nevada 1
Arkansas 0 4 New Hampshire 2
California 2 7 New Jersey 3
Colorado 1 4 New Mexico 1
Connecticut 2 6 New York 2
Delaware 1 4 North Carolina 1
District of Columbia 1 7 North Dakota 0
Florida 1 2 Ohio 1
Georgia 1 5 Oklahoma 1
Hawaii 1 5 Oregon 3
Idaho 1 a5 Other areas 5
Illinois 1 4 Pennsylvania 1
Indiana 1 4 Rhode Island 2
Iowa 1 5 South Carolina 1
Kansas 1 5 South Dakota 0
Kentucky 1 5 Tennessee 0 1
Louisiana 0 2 Texas 1 2
Maine 1 6 Utah 1 5
Maryland 2 7 Vermont 1 5
Massachusetts 2 6 Virginia 1 5
Michigan 1 5 Washington 1 2
Minnesota 1 6 West Virginia 0 3
Mississippi 0 3 Wisconsin 2 7
Missouri 1 4 Wyoming 0 1
Source: GAO analysis of SOI data for tax year
2000.
Notes: Taxes include state and local income taxes, real estate taxes,
personal property taxes, and taxes paid to a foreign country or U.S.
possession.
a"Other Areas" includes American Samoa, Federal States of Micronesia,
Guam, Marshall Islands, Northern Marianas, Palau, Puerto Rico, Virgin
Islands, and other U.S. states and territories.
Appendix IV: Simulation of Tax Allowance Percentages under Various Options, by
State-Families with Adjusted Gross Income of $15,000 or More
Current Proposed Strategy I Strategy II Strategy III
State
Tables published in 1993
Proposed 2004- 2005 tables
SOI with revised methodology
BEA / Census CPS ITEP
Standard allowance (4%)
Alabama 4 2 3 5 3 7
Alaska 2 1 2 1 1 2
Arizona 5 3 4 5 4 7
Arkansas 5 2 4 7 5 8
California 7 5 7 7 5 8
Colorado 6 3 4 4 4 7
Connecticut 5 5 6 6 4 8
Delaware 7 3 4 4 6 5
District of Columbia 9 6 7 9 8 8
Florida 3 1 2 4 1 5
Georgia 6 4 5 5 5 8
Hawaii 7 3 5 9 13 8
Idaho 6 4 5 6 5 8
Illinois 5 3 4 5 4 8
Indiana 5 3 4 5 4 8
Iowa 7 3 5 6 7 8
Kansas 6 3 5 6 4 9
Kentucky 6 4 5 7 5 8 4
Louisiana 3 1 2 5 2 7 4
Maine 8 5 6 7 6 9 4
Maryland 8 6 7 5 7 8 4
Massachusetts 8 5 6 6 7 8 4
Michigan 8 4 5 6 6 8 4
Minnesota 8 5 6 7 6 9 4
Mississippi 4 2 3 7 3 7 4
Missouri 5 3 4 5 4 8 4
Montana 7 4 5 5 5 6 4
Nebraska 7 3 5 5 5 8 4
Nevada 2 1 2 5 1 4 4
New Hampshire 6 3 4 3 2 4 4
New Jersey 7 6 7 5 7 9 4
New Mexico 5 2 4 7 3 8 4
New York 10 7 8 6 7 9 4
Appendix IV: Simulation of Tax Allowance Percentages under Various
Options, by State-Families with Adjusted Gross Income of $15,000 or More
Current Proposed Strategy I Strategy II Strategy III Tables published in 1993
Proposed 2004- 2005 tables
SOI with revised methodology
BEA / Census CPS ITEP
Standard allowance (4%)
State
North Carolina 7 4 6 6 6 8
North Dakota 5 1 2 5 3 6
Ohio 7 4 6 5 5 9
Oklahoma 5 3 4 5 5 9
Oregon 9 6 7 5 8 9
Other Areas 3 2 2 5 4 6
Pennsylvania 6 3 5 5 4 7
Rhode Island 8 5 7 6 5 9
South Carolina 7 3 5 6 5 8
South Dakota 3 0 1 4 2 5
Tennessee 2 0 1 4 1 5
Texas 2 1 2 4 1 5
Utah 7 4 5 7 6 8
Vermont 7 4 5 8 5 8
Virginia 7 4 5 5 6 7
Washington 3 1 2 6 1 6
West Virginia 5 2 3 7 4 8
Wisconsin 9 5 7 7 810 4
Wyoming 2 0 1404 4
Source: GAO analysis.
Notes: (1) The CPS tax rates were generated based on a 3-year average of
1999, 2000, and 2001 CPS data. The standard allowance of 4 percent was
calculated as the median across states of this three-year average; and (2)
"Families" are defined to include parents of dependent students and
independent students with dependents other than a spouse.
Appendix V: Comments from the Department of Education
Appendix V: Comments from the Department of Education
Appendix V: Comments from the Department of Education
Appendix VI: GAO Contacts and Staff Acknowledgments
GAO Contacts
Staff Acknowledgments
(130308)
Jeff Appel, Assistant Director (202) 512-9915 Tranchau Nguyen,
Analyst-in-Charge (202) 512-2660
In addition to those named above, the following people made significant
contributions to this report: Jeff Weinstein, Cynthia Decker, Bob Parker,
Sue Bernstein, Amy Buck, James Wozny, and Melba Edwards.
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