GAO 

United States Government Accountability Office

Report to Congressional Requesters

VOCATIONAL 

REHABILITATION 

FUNDING FORMULA 

Options for Improving 

Equity in State Grants 

and Considerations 

for Performance 

Incentives 

September 2009 

GAO-09-798 
What GAO Found

United States Government Accountability Office

Why GAO Did This Study

Highlights

Accountability Integrity Reliability

September 2009

VOCATIONAL REHABILITATION FUNDING 

FORMULA 

Options for Improving Equity in State Grants and 

Considerations for Performance Incentives Highlights of GAO-09-798, a report to 

congressional requesters 

State vocational rehabilitation (VR) 

agencies play a crucial role in 

helping individuals with disabilities 

obtain employment. In fiscal year 

2008, the Department of Education 

(Education) distributed over $2.8 

billion in grants to state agencies, 

using a funding formula that was 

last revised in 1978. Questions have 

been raised about whether this 

formula is outdated, allocates 

funds equitably, and adequately 

accounts for state agencies’ 

performance. 

GAO was asked to: (1) examine the 

extent to which the current 

formula meets generally accepted 

equity standards, (2) present 

options for revising the formula, 

and (3) identify issues to consider 

with incorporating performance 

incentives into the formula. 

To address these objectives, GAO 

relied upon two equity standards 

commonly used to design and 

evaluate funding formulas: 

beneficiary equity, which stipulates 

that funds should be distributed so 

that each state can provide the 

same level of services to each 

person in need; and taxpayer 

equity, which stipulates that states 

should contribute about the same 

proportion of their resources to a 

given program. GAO analyzed data 

from Education, Department of the 

Treasury, Census Bureau, and 

other agencies; surveyed state VR 

agencies; interviewed agency 

officials and disability experts; and 

reviewed literature on performance 

incentives. 

GAO makes no recommendations 

in this report. 

The VR funding formula falls short of meeting equity standards because it uses 

imprecise measures of state needs and resources. The formula does not 

account for differences among states in the proportion of people with a 

disability or the costs of providing services. As a result, the amount of services 

that states can purchase per person with a disability varies, from $83 to $277 

(see figure). In addition, the formula uses only per capita income to measure a 

state’s ability to contribute to the program, excluding other taxable resources. 

GAO presents three options for revising the formula to illustrate a range of 

possibilities: the first distributes funds based on states’ disability populations, 

the second also accounts for costs of providing services, and the third further 

accounts for state resources beyond per capita income. Because any formula 

change would redistribute funds among states, potentially disrupting services 

to individuals, GAO also presents options for establishing a transition period. 

Including performance incentives in the funding formula has potential for 

improving performance but can also pose challenges. These include: 

effectively balancing the VR program’s multiple goals, rewarding agencies for 

meeting individuals’ specific needs, and basing awards on an agency’s 

performance rather than influences outside its control. GAO identified ways 

to mitigate these risks, such as using multiple performance measures to 

address different goals, and adjusting the performance level required for an 

agency to receive an incentive award. However, these approaches would still 

require careful consideration of several issues, such as how to account for 

clients’ varying disability levels and needs and provide appropriate incentives 

for achieving desired outcomes. 

Estimated State VR Allotments per Working-Aged Person with a Disability, Cost-Adjusted, 

Based on Fiscal Year 2008 Funding

Source: GAO analysis of data from Education, Census Bureau, Bureau of Labor Statistics, Department of Housing and Urban

Development, and responses to GAO survey; Map, Map Resources (presentation).

Less than $115

$115 - 128

$129 - 150

More than $150

Median: $128

D.C.

View GAO-09-798 or key components.

For more information, contact Daniel Bertoni, 

(202) 512-7215, bertonid@gao.gov. 
Page i GAO-09-798 

Contents 

Letter 1

Background 3 

The Current Formula Falls Short of Meeting Equity Standards for 

Beneficiaries and Taxpayers 6 

Greater Equity in VR Funding Could Be Accomplished in Several 

Ways 14 

Incorporating Financial Performance Incentives in the VR Formula 

Poses Challenges 19 

Concluding Observations 26 

Agency Comments and Our Evaluation 26 

Appendix I Objectives, Scope, & Methodology 28 

Appendix II Description of the Current Vocational Rehabilitation 

(VR) Funding Formula 51 

Appendix III Percentage of Population that Is Civilian Working 

Age with a Disability, 2006 and 2007 53 

Appendix IV Estimates of Differences among States in the Cost of 

Providing Vocational Rehabilitation (VR) Services 55 

Appendix V Vocational Rehabilitation (VR) Grant Allotments by 

State and Cost-Adjusted Allotments per WorkingAged Person with a Disability, Fiscal Year 2008 57 

Appendix VI Comparison of Per Capita Income and Total Taxable 

Resources (TTR), by State, 2004 to 2006 59 

 Vocational Rehabilitation 
Appendix VII Description of Formula Options 62 

Appendix VIII Funding Allocations under Three Vocational 

Rehabilitation Formula Options 64 

Appendix IX Responses to Selected Questions from GAO Survey of 

State Vocational Rehabilitation (VR) Agencies 66 

Appendix X GAO Contacts and Staff Acknowledgments 75 

Tables 

Table 1: Redistribution of Funds under Three Formula Options 16 

Table 2: Disability Questions from the American Community 

Survey, 2006 and 2007 30 

Table 3: Breakdown of the Total U.S. Population into Components 

of our Measure of the Need Population for the VR 

program, 2007 31 

Table 4: Summary Statistics for Wage Indices from Data Series 

Reviewed 37 

Table 5: Correlations between Wage Indices 38 

Table 6: Combining Education’s Expenditure Data and Survey Data 

to Estimate Weights for Inputs 41 

Table 7: Number of States Considered to Be Under Order of 

Selection by Type of VR Agency 47 

Table 8: Percentage of Population that Is Civilian Working Age with 

a Disability, 2006 and 2007 53 

Table 9: Estimates of Differences among States in the Cost of 

Providing VR Services 55 

Table 10: VR Grant Allotments and Cost-Adjusted Allotments per 

Working-Aged Person with a Disability 57 

Table 11: Comparison of Per Capita Income and TTR Per Capita for 

2004 to 2006, by State 59 

Table 12: Funding Allocations under Three VR Formula Options 64 

Page ii GAO-09-798 Vocational Rehabilitation
Figures 

Figure 1: Percentage of Each State’s Total Population that Is 

Working-Aged and Has a Disability, 2007 8 

Figure 2: Estimated State VR Allotments per Working-Aged Person 

with a Disability, Cost-Adjusted, Based on Fiscal Year 

2008 Funding 10 

Figure 3: Ratio of Per Capita Income to Total Taxable Resources 

Per Capita 12 

Figure 4: A 5-Year Phase-In Transition to a New Funding Formula 18 

Figure 5: Distribution of Average State Wages in the Education, 

Healthcare, and Social Assistance Industry Sector, 2005 to 

2007 39 

Figure 6: Distribution of Average State Rents, Fiscal Years 2007 to 

2009 40 

Figure 7: Distribution of the Cost of Services Index 43 

Figure 8: State Agency Officials’ Opinions about the 

Appropriateness or Inappropriateness of Factors 

Currently Included in the Funding Formula 67 

Figure 9: State VR Agency Officials’ Opinions about Options for 

Modifying the Formula 68 

Figure 10: State VR Agency Officials’ Opinions about Whether the 

Matching Requirement Should Vary to Account for States’ 

Total Financial Resources 69 

Figure 11: State VR Agency Officials’ Opinions about Incorporating 

Performance Awards in the VR Program 70 

Figure 12: State VR Agency Officials’ Opinions about Potential 

Results of Including Performance Awards in the VR 

Program 71 

Figure 13: State VR Agency Officials’ Opinions about Challenges of 

Incorporating Performance Awards into the VR Program 72 

Figure 14: VR Agencies’ Responses on Whether They Receive 

Funding from Their State based on Performance 73 

Figure 15: Current Use of Performance Awards by State VR 

Agencies 74 

Page iii GAO-09-798 Vocational Rehabilitation
Abbreviations 

ACS American Community Survey 

BLS Bureau of Labor Statistics 

CMS Centers for Medicare and Medicaid Services 

CPI-U Consumer Price Index for All Urban Consumers 

CSAVR Council of State Administrators of Vocational 

Rehabilitation 

CSE Child Support Enforcement 

Education Department of Education 

ERIC Education Resources Information Center 

FMR Fair Market Rents 

HUD Department of Housing and Urban Development 

JTPA Job Training Partnership Act 

NAICS North American Industry Classification System 

OES Occupational Employment Statistics 

QCEW Quarterly Census of Employment and Wages 

SOC Standard Occupational Classification 

SSA Social Security Administration 

SSDI Social Security Disability Insurance 

SSI Supplemental Security Income 

Treasury Department of the Treasury 

TTR Total Taxable Resources 

VR Vocational Rehabilitation 

WIA Workforce Investment Act 

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Page iv GAO-09-798 Vocational Rehabilitation
Page 1 GAO-09-798 

t in 

ce. As 

 

United States Government Accountability Office

Washington, DC 20548 

 

September 30, 2009 

The Honorable George Miller 

Chairman 

The Honorable John P. Kline 

Ranking Member 

Committee on Education and Labor 

House of Representatives 

The Honorable Howard P. “Buck” McKeon 

House of Representatives 

State vocational rehabilitation (VR) agencies, under the auspices of the 

Department of Education (Education), play a crucial role in helping 

individuals with disabilities prepare for and obtain employment.1

 In fiscal 

year 2008, Education distributed over $2.8 billion in grants to state VR 

agencies, using a funding formula that was last updated in 1978.2

Questions have been raised about whether this funding formula is 

outdated and allocates funds equitably. In addition, growing interes

program accountability has prompted some to ask whether the formula

should incorporate performance measures to reward high performan

currently constructed, the VR formula distributes funds according to the 

size of a state’s population, its per capita income, and the amount of VR 

funds the state received in 1978. States must match their federal grant 

allocations by contributing about $1 to their VR programs for each $4 they 

receive. 

1

In this report, unless otherwise noted, the term states or state VR agencies refers to VR 

agencies in the 50 states, the District of Columbia, and the territories of American Samoa, 

Guam, Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands. 

2

An additional $35 million in VR funds was set aside for American Indian Vocational 

Rehabilitation services in fiscal year 2008. This report does not discuss the American 

Indian set-aside funds, since they are not distributed through the funding formula. 

 Vocational Rehabilitation 
 

There are two standards concerning the concept of equity that have 

commonly been used to design and evaluate funding formulas.3

 The first—

known as beneficiary equity—stipulates that funds should be distributed 

to states according to the needs of their respective populations so that 

each state, with their federal allocation, can provide the same level of 

services to each person in need. The second standard—known as taxpayer 

equity—applies to programs, such as VR, in which states contribute funds. 

This standard also seeks to provide individuals in need with the same level 

of services, but in addition, considers a state’s ability to finance a program 

from its own resources. It stipulates that states should be able to provide 

comparable services to individuals, with each state contributing about the 

same proportion of their resources to the program. To achieve this 

standard, taxpayer equity formulas may allocate more funds to states with 

fewer taxable resources, set the contribution they are required to make at 

a lower level, or do both, so that poorer states do not contribute a larger 

share of their resources than wealthier states. To meet the taxpayer equity 

standard, a formula requires a reliable measure of a state’s ability to 

finance a program from its own resources. To meet both equity standards, 

a formula should use reliable and appropriate measures of the need 

population in each state and the cost of providing services in each state. 

In this context, you asked us to (1) examine the extent to which the 

current formula meets generally accepted equity standards, (2) present 

options for revising the formula to better meet these standards, and (3) 

identify issues to consider with incorporating performance incentives into 

the formula. 

To determine the extent to which the VR funding formula meets equity 

standards and to develop options for revising the formula, we examined 

data from a number of sources, namely Education’s data on state VR 

grants, Census Bureau data on state disability populations, Department of 

the Treasury (Treasury) data on state taxable resources, Bureau of Labor 

Statistics (BLS) data on wages, and Department of Housing and Urban 

 

3

These equity standards are not statutory requirements for the VR program, but are 

commonly used as standards in social science research to evaluate and design funding 

formulas. See, for example, GAO, Maternal and Child Health: Block Grant Funds Should 

Be Distributed More Equitably, GAO/HRD-92-5 (Washington, D.C.: Apr. 2, 1992); RAND 

Corporation, Review and Evaluation of the Substance Abuse and Mental Health Services 

Block Grant Allotment Formula, MR-533-HHS/DPRC, 1997; National Research Council, 

Statistical Issues in Allocating Funds by Formula, Panel on Formula Allocations, Thomas 

A. Louis, Thomas B. Jabine, and Marisa A. Gerstein, ed., Committee on National Statistics, 

(Washington, D.C., 2003). 

Page 2 GAO-09-798 Vocational Rehabilitation
 

Development (HUD) data on rents. In addition, we interviewed experts in 

the disability field and had key portions of our analyses formally reviewed 

by three disability experts. We also surveyed all 80 VR agencies in the 

states, territories, and District of Columbia to obtain their perspectives on 

the current formula, options for changing it, and views on the use of 

performance incentives in the VR program.4

 We received responses from 

74 (93 percent) of the agencies. We also conducted in-depth interviews 

with state VR officials at 11 agencies in 9 states, as well as with members 

of advisory councils to the VR agencies in 5 of these states. To further 

consider potential benefits and challenges of using performance incentives 

in the VR funding formula, we reviewed academic literature on the subject 

and spoke with officials in three federal programs that currently provide 

incentive awards. We conducted this performance audit from September 

2008 to September 2009, in accordance with generally accepted 

government auditing standards. Those standards require that we plan and 

perform the audit to obtain sufficient, appropriate evidence to provide a 

reasonable basis for our findings and conclusions based on our audit 

objectives. We believe that the evidence obtained provides a reasonable 

basis for our findings and conclusions based on our audit objectives. See 

appendix I for a detailed discussion of our scope and methodology. 

The Rehabilitation Act, as amended, sets out a formula for distributing VR 

grants to states and territories.5

 Through this formula, a portion of the 

funds appropriated for the VR program are distributed to states based 

upon the grant allotment they received for fiscal year 1978. States’ 1978 

allotments served to ensure that no state experienced a funding decrease 

when the formula was revised through a 1978 amendment to the 

Rehabilitation Act.6

 Of the remainder of the funds, one-half is distributed 

based upon states’ general population and a factor that compares their per 

capita income to the national per capita income, and the other one-half, 

Background 

 

4

Some states have two VR agencies – one that serves individuals who are blind, and another 

that serves individuals with other types of disabilities. Other states have one VR agency 

that serves people with all types of disabilities. 

5

The Rehabilitation Act was most recently reauthorized as part of the Workforce 

Investment Act (Pub. L. No. 105-220). The funding formula we describe is used to distribute 

federal funds to states. In states with two VR agencies, the division of a state’s allotment 

between the blind and general VR agency is determined by the state. 

6

Prior to 1978, funds were allotted based upon states’ populations and the square of the 

allotment percentage. See footnote 7 and appendix II for an explanation of the allotment 

percentage. 

Page 3 GAO-09-798 Vocational Rehabilitation
 

according to their population and the square of the per capita income 

factor. The larger a state’s population, the more funds it will receive. 

Conversely, the higher a state’s per capita income compared to the 

national level, the lower its allotment will be. The squaring of per capita 

income increases its influence on a state’s allotment. However, the 

formula mitigates the effect of per capita income for states with very high 

or very low per capita income levels by setting upper and lower limits. 7

Ultimately, the final allotment for a state cannot be less than 1/3 of 1 

percent of the total amount appropriated, or $3 million dollars, whichever 

is greater.8

 In fiscal year 2008, the minimum allotment was $9.5 million, 

and 6 states were allotted this amount.9

 See appendix II for further 

information on the funding formula. 

The Act requires states to share in funding the costs of the VR program. 

Specifically, the Act sets the federal share for the funding of a state’s VR 

program at 78.7 percent. As a result, in order to receive their full federal 

allotment, each state must contribute at least 21.3 percent of the funds for 

their VR programs.10 In cases where states do not meet this matching 

 

7

The allotment percentage, which is determined by comparing a state’s per capita income 

to the national per capita income, cannot be less than 33 1/3 percent or greater than 75 

percent. Default levels for the allotment percentage are set at 75 percent for the District of 

Columbia and U.S. territories. In fiscal year 2008, the limits on the allotment percentage 

affected only one state, Connecticut, whose allotment percentage was increased to 33 1/3 

percent. See appendix II for a further explanation. 

8

If a state’s allotment falls below this level, it is increased to this amount and the final 

allotments for all of the other states are decreased in proportion to their share of the total 

appropriation. The minimum allotment provision does not apply to U.S. territories, but it 

does apply to the District of Columbia. 

9

The six states were Alaska, Delaware, North Dakota, South Dakota, Vermont, and 

Wyoming. 

10The Rehabilitation Act also includes a maintenance-of-effort requirement to encourage 

states to maintain their level of contribution to the VR program over time. If a state’s 

expenditures from nonfederal sources in the prior fiscal year is less than its expenditures 

from nonfederal sources for the fiscal year two years prior to the previous fiscal year, 

Education can reduce the state’s current year allotment by the difference between the two 

years’ expenditures. For example, if a state’s nonfederal expenditures in fiscal year 2007 

were less than its nonfederal expenditures in fiscal year 2005, Education could reduce its 

fiscal year 2008 allotment by the difference between the 2005 and 2007 nonfederal 

expenditures. Funds incurred from maintenance-of-effort penalties are redistributed to all 

other states. In fiscal year 2008, 1 state and 1 territory incurred maintenance-of-effort 

penalties totaling $364,421, or 0.01 percent of total federal VR funds. However, the Act 

specifies that under exceptional or uncontrollable circumstances affecting the state, the 

maintenance-of-effort requirement may be waived. Education officials informed us that 

such circumstances may include a serious economic downturn or natural disaster. 

Page 4 GAO-09-798 Vocational Rehabilitation
 

requirement, the unmatched federal funds are redistributed to other states 

near the end of the fiscal year.11 The Act also calls for annual funding 

increases to the VR program, overall, to be minimally pegged to the 

increase in the Consumer Price Index for All Urban Consumers (CPI-U). 

However, funding changes for an individual state may differ from the 

change to the CPI-U in any given year because state allocations are, 

ultimately, determined by the funding formula. In redistributing the funds, 

Education currently gives priority to those states that did not receive an 

inflation-adjusted increase over their prior year’s allotment. 

Under the VR program, state VR agencies are to provide vocational 

rehabilitation services for individuals with disabilities—consistent with 

the individual’s strengths, resources, priorities, abilities, interests, and 

informed choice—so that they may prepare for and engage in gainful 

employment. To do so, state agencies provide a variety of services to 

individuals such as job placement assistance, medical treatment, 

postsecondary education, occupational training, and assistive 

technologies. Individuals may be eligible for VR services if they have a 

physical or mental impairment that constitutes or results in a substantial 

impediment to employment, and if they need VR services to prepare for, 

secure, retain, or regain employment. According to the Rehabilitation Act, 

if state VR agencies determine that they will not have enough funding to 

serve all eligible individuals who apply for services, they may state the 

order in which they will select individuals for services. Agencies using 

such an “order of selection” process must develop criteria for ensuring 

that individuals with the most significant disabilities will be selected first 

for services. 

The current VR funding formula does not include factors for rewarding 

agency performance; however, pursuant to the Rehabilitation Act, 

Education evaluates state VR agencies’ performance using a set of 

 

11The redistribution process takes place through a memorandum that Education sends to 

each VR agency near the end of each fiscal year, asking them whether they will relinquish 

any funds or request additional ones. Education then redistributes the funds that states 

relinquished to other states who requested additional funds. In fiscal year 2008, 4 states and 

1 territory relinquished $17.8 million in funding, or 0.6 percent of total federal VR funds. 

The required 21.3 percent state contribution also applies to any additional funds that states 

receive through the redistribution process. 

Page 5 GAO-09-798 Vocational Rehabilitation
 

performance indicators.12 These indicators are designed to assess how 

well the agencies are helping individuals obtain, maintain, or regain highquality employment and, also, how well they are ensuring that individuals

from minority backgrounds have equal access to VR services.

Rehabilitation Act gives Education the authority to reduce or suspend 

payments to a state agency whose performance falls below a certain level 

and fails to enter into a program improvement plan or to substantially 

comply with the terms and conditions of such a plan. 

 The 

 

The Current Formula 

Falls Short of Meeting 

Equity Standards for 

Beneficiaries and 

Taxpayers 

The Formula Does Not 

Account for Varying 

Disability Rates and 

Service Costs 

The VR funding formula does not achieve equity for beneficiaries—the 

individuals likely to be served by the VR program—for two reasons. First, 

it does not recognize differences among states in the size of their 

populations potentially needing VR services. Second, it does not account 

for state differences in the costs of providing those services. 

By targeting funds based on a state’s general population, the formula 

assumes that the proportion of people needing services is largely the same 

from state to state. In fact, as shown in figure 1, the proportion of the 

general population that is working-aged and has a disability varies across 

states, from 5.6 percent (in New Jersey) to 12.8 percent (in West Virginia) 

12The performance indicators are established in 34 C.F.R. § 361.84. For additional 

background on Education’s oversight of state VR agency performance, see GAO, 

Vocational Rehabilitation: Better Measures and Monitoring Could Improve the 

Performance of the VR Program, GAO-05-865 (Washington, D.C.: Sept. 23, 2005). 

Page 6 GAO-09-798 Vocational Rehabilitation
 

in 2007.13 See appendix III for information on disability rates in each state. 

In effect, the formula treats alike any two states with similar population 

sizes, irrespective of the size of their working-aged disability population. 

For example, New Mexico has a slightly greater population than West 

Virginia (2.0 million and 1.8 million, respectively), and, therefore, would 

receive more funding under the current formula (all other things being 

equal) than West Virginia. However, working-aged people with disabilities 

comprise nearly 13 percent of West Virginia’s population, compared to 8.7 

percent in New Mexico. By not factoring in state disability populations, the 

formula does not account for West Virginia having over 60,000 more 

working-aged people with disabilities than New Mexico. 

 

13These disability rates are calculated as the civilian working-aged population of people 

with disabilities (ages 16-64) divided by the total state population. Our measure of the 

disability population is derived from five disability questions asked in the 2007 American 

Community Survey (ACS), conducted by the Census Bureau. We did not include data from 

a sixth disability question about whether a person has difficulty working at a job or 

business because of a physical, mental, or emotional condition lasting six months or more 

because this question was no longer included in the ACS, starting in 2008. We were not able 

to calculate the disability rates of U.S. territories. Data are available from the ACS on the 

population of people with disabilities in Puerto Rico, but are not available for other 

territories. For further information on our analysis of states’ disability populations, see 

appendix I. 

Page 7 GAO-09-798 Vocational Rehabilitation
 

Figure 1: Percentage of Each State’s Total Population that Is Working-Aged and 

Has a Disability, 2007 

Source: GAO analysis of Census Bureau’s ACS data; Map, Map Resources (presentation).

6.5 percent or less

6.6 to 7.6

7.7 to 8.7

8.8 percent or more

National: 7.6 percent

D.C.

Education officials and one expert we spoke with speculated that the 

formula’s use of per capita income might serve to target funds to states 

with higher rates of disability since people with disabilities have, on 

average, lower incomes. We found some correlation between states’ 

disability rates and their per capita income.14 As such, per capita income 

is, at best, an imprecise measure of states’ disability rates. 

 

Vocational Rehabilitation

 

14We calculated the correlation to be 0.53 between states’ disability rates and their per 

capita income, where 1 would be a perfect correlation between two variables and 0 would 

indicate a lack of correlation. 

Page 8 GAO-09-798 
 

The funding formula also fails to account for differences among states in 

the cost of providing VR services. Focusing on average wages and rents in 

each state, we estimated that the cost is 13 percent below the national 

average in Idaho, for example, while it is 13 percent above average in 

Massachusetts.15 This means that Massachusetts would need to pay $1.13 

for the same set of services that Idaho could purchase for $0.87. By not 

taking into account cost differences, VR allocations purchase fewer 

services in states that have higher costs. See appendix IV for a table of our 

estimates of state cost differences. Also, see appendix I for information on 

how we estimated state service costs. 

Not accounting for state differences in both disability populations and cost 

of services results in a substantial variation in the amount of services that 

states are able to purchase per person with a disability, from a low of $83 

in Connecticut, to a high of over three times as much—$277 in North 

Dakota. Figure 2 shows estimated state VR allotments, per working-aged 

person with a disability, based on fiscal year 2008 funding, adjusted for 

differences in costs of wages and rents between states.16 See appendix V 

for a state-by-state listing of VR grant allocations and cost-adjusted 

allotments per person with a disability. 

 

15We estimated the relative cost of providing services by estimating the costs of two inputs 

to providing VR services, labor and office space. Specifically, we used data on state average 

wages in the education, healthcare, and social assistance sector from BLS’ Quarterly 

Census of Employment and Wages, as well as data on fair market rents from HUD. To 

determine how much to weight wages and rents in our cost estimates, we used data 

obtained from our survey and Education’s data on expenditures. Although our cost index 

provides a reasonable approximation of basic cost differences among states, we were 

unable to develop a more precise estimate reflecting all possible inputs due to the lack of 

readily available data. For further information about our data sources and methodology, 

see appendix I. 

16Grant allotments used in this analysis are the initial allotments distributed to states using 

the funding formula. The allotments do not include any adjustments that occur due to 

states’ inability to match federal funds or the application of maintenance-of-effort 

penalties. 

Page 9 GAO-09-798 Vocational Rehabilitation
 

Figure 2: Estimated State VR Allotments per Working-Aged Person with a Disability, 

Cost-Adjusted, Based on Fiscal Year 2008 Funding 

Source: GAO analysis of data from Education, Census Bureau, BLS, HUD, and responses to GAO survey; Map, Map Resources

(presentation).

Less than $115

$115 - 128

$129 - 150

More than $150

Median: $128

D.C.

The Formula Does Not 

Capture Certain Taxable 

Resources 

While proper measures of need and cost are important for both beneficiary 

and taxpayer equity, the VR funding formula lacks equity for state 

taxpayers, in particular, because its measure of a state’s ability to 

contribute to the VR program is limited to per capita income and does not 

include all potentially taxable resources. Per capita income is based on the 

personal income in a state, including income received by state residents in 

the form of wages, rents, and interest income. However, using only this 

measure excludes certain categories of corporate income that are not 

received as income by state residents. For example, the formula does not 

factor in corporate income that is retained by corporations for investment 

Page 10 GAO-09-798 Vocational Rehabilitation
 

purposes, which could theoretically be subject to state taxation through 

corporate income taxes. The formula also excludes business income 

received by out-of-state residents, such as dividends, that are potentially 

taxable by the state. Although states may differ in their decisions about 

whether to tax these resources, the measure used in a funding formula to 

compare states’ ability to finance a program should capture all possible 

revenue resources and should not be affected by an individual state’s fiscal 

decisions. Treasury’s Total Taxable Resources provides more 

comprehensive data on the amount of resources that are potentially 

taxable in each state. Comparing states’ per capita income with their total 

taxable resources shows that, for most states, the two measures are 

similar. However, the formula’s use of per capita income particularly 

understates the taxable resources in certain states and overstates it in 

others (see figure 3). For example, the ratio of per capita income to total 

taxable resources per capita is 0.80 in Alaska, which suggests that the use 

of per capita income in the formula understates Alaska’s taxable resources 

by 20 percent.17 The formula’s use of per capita income especially 

understates the taxable resources in energy-exporting states, such as 

Alaska and Wyoming, and in states with numerous corporate 

headquarters, such as Delaware. The lack of precision in using per capita 

income is accentuated by the squaring of the per capita income factor in 

the formula.18 See appendix VI for a comparison of per capita income and 

total taxable resources in each state. Also, see appendix I for a more 

detailed explanation of our analyses of per capita income and total taxable 

resources data and appendix II for a detailed explanation of the current 

formula. 

 

17Specifically, we present ratios of a per capita income index to an index of total taxable 

resources per capita. The indexes were created by dividing a state’s per capita income and 

total taxable resource per capita by the U.S. averages for each. 

18Squaring of the per capita income factor (i.e., multiplying the per capita income factor by 

itself) increases the influence of per capita income in the formula. 

Page 11 GAO-09-798 Vocational Rehabilitation
 

Figure 3: Ratio of Per Capita Income to Total Taxable Resources Per Capita 

Source: GAO analysis of Department of Commerce data on per capita income and Treasury data on total taxable resources, 2004 to 

2006; Map, Map Resources (presentation).

Less than 0.95

0.95 to 0.99

1 to 1.05

Greater than 1.05

D.C.

Note: These are ratios of a per capita income index to an index of total taxable resources per capita. 

The indexes were created by dividing the per capita income and total taxable resource per capita 

levels by the U.S. averages for each. 

Over One-Quarter of Funds 

are Distributed Based on 

States’ 1978 Allotments 

In fiscal year 2008, 27 percent of federal VR funds were distributed to 

states based upon the amount of funds they received for fiscal year 1978. 

This provision of the formula served a purpose when the formula was last 

revised, in 1978, to ensure that no state experienced a funding decrease. 

However, most disability experts we spoke with considered this provision 

outdated and no longer an appropriate factor for distributing VR funds. 

The Congressional Research Service also reported that due to the 1978 

Page 12 GAO-09-798 Vocational Rehabilitation
 

allotment, VR funding allotments do not fully reflect population changes 

since the mid-1970s.19

Most State Agencies 

Indicated Satisfaction with 

the Formula, though Some 

Believe It Results in 

Inadequate Funding for 

their States 

Most state agencies that responded to our survey indicated satisfaction 

with the current formula. Of respondents, 62 percent (46 of 74) expressed 

the view that the current formula is appropriate, while 31 percent (23 of 

74) viewed it as inappropriate. When asked about specific parts of the 

formula, opinions varied. For example, 86 percent (64 of 74) considered 

the use of general population to be appropriate, while only 27 percent (20 

of 74) considered the 1978 allotment provision to be appropriate. See 

appendix IX for responses to our survey questions. However, in their 

comments to the survey and in interviews, some state agency officials 

asserted that the formula does not provide them with adequate funds. For 

instance, VR officials we spoke with in Massachusetts and Maryland said 

that due to current funding allotments, their agencies are on an “order of 

selection,” in which they give priority to individuals with significant 

disabilities and place other individuals on waiting lists. 

When we compared allotments per person with a disability against order 

of selection status, we found that states that receive less funding per 

person with a disability were somewhat more likely to report being under 

an order of selection than those states that receive relatively more 

funding.20 Specifically, we found in fiscal year 2008 that among states with 

lower than median allotments per person with a disability (adjusting for 

costs), 72 percent reported being under an order of selection, compared to 

52 percent of states above the median. However, the data do not explain 

whether or the extent to which the VR funding formula is causing states to 

 

19The Congressional Research Service found that states with the largest population growth 

since 1976 would have received larger funding allotments if the 1978 provision were not 

part of the VR funding formula, while states with lower rates of population growth since 

1976 benefit from this provision. Congressional Research Service, Vocational 

Rehabilitation Grants to States and Territories: Overview and Analysis of the Allotment 

Formula, RL34017 (Washington, D.C., January 2008). 

20In states with two VR agencies, we considered a state to be under an order of selection if 

either of its agencies reported being under an order of selection. In one state—Delaware—

the state VR agency for the blind was under an order of selection, but not the general 

agency. In all other states that we considered to be under an order of selection, either only 

the general agency reported being under an order of selection, or both the general and 

blind agencies did so. We did not include U.S. territories in this analysis due to lack of data 

that would allow us to determine the size of their allotments per working-aged person with 

a disability. 

Page 13 GAO-09-798 Vocational Rehabilitation
 

be under an order of selection. For example, many states above the 

median allotment are also under orders of selection. Further, in interviews 

state VR officials indicated that factors other than allotment levels could 

also influence a state’s decision to be under an order of selection, such as 

the level of state resources provided to the VR program, the effectiveness 

of the agency’s management of program costs, and the agency’s decisions 

about how to use existing funding. 

Greater Equity in VR 

Funding Could Be 

Accomplished in 

Several Ways 

Options for Introducing 

Greater Equity for 

Taxpayers or Beneficiaries 

There are a number of ways to redesign the VR funding formula to achieve 

greater equity for beneficiaries, taxpayers, or to balance equity for both. 

We present three options, or prototypes, to illustrate the range of options. 

See appendix VII for a more detailed description of each formula option. 

For each of these options, we have retained the minimum allotment that 

the current formula provides to ensure that each state would receive at 

least a certain level of funds for its VR program. 

• A partial beneficiary equity formula: This option bases allocations solely 

on the size of a state’s population potentially needing VR services. To 

measure the need population, this option would use data on the states’ 

civilian working-aged disability populations from the Census Bureau’s 

ACS. 

• A full beneficiary equity formula: This option also allocates funds based 

on states’ working-aged disability populations using Census data, but also 

includes estimates of the cost of providing VR services in each state. These 

cost estimates reflect differences among states with respect to two basic 

costs (i.e., wages and rents), which underlay the provision of many VR 

services. We developed estimates of state costs using data on wages from 

BLS and on rents from HUD. This option does not reflect differences in 

other types of basic costs for which reliable data may not be readily 

available. See appendix I for further information on the development of 

our cost estimates. 

• A taxpayer equity formula: This option also distributes funds based on 

states’ working-aged disability populations and the cost of providing VR 

Page 14 GAO-09-798 Vocational Rehabilitation
 

services, but it adds a third factor to the formula—a measure of each 

state’s ability to contribute to the VR program. More funds would be 

allocated to states with fewer taxable resources. To measure a state’s 

ability to finance the VR program, we utilized data from Treasury on a 

state’s total taxable resources, which includes per capita income as well as 

other sources of potentially taxable state income, such as corporate 

income produced within the state but not received by state residents. 

For the taxpayer equity option, an issue to consider is whether the 

matching requirement would be the same across all states, as is the case 

with the current formula, or would vary based upon a state’s ability to 

finance the VR program. To fully achieve taxpayer equity, the matching 

requirement would need to vary according to each state’s financing ability. 

If the matching requirement were the same for all states, those with fewer 

resources would receive more federal funds but would also need to 

provide more state funds for the match. This could result in poorer states 

having to contribute a greater share of their resources to the VR program 

than wealthier states. See appendix VII for an explanation of how a 

variable matching requirement could be incorporated into the taxpayer 

equity option. 

Table 1 shows the amount of funds redistributed among states, as well as 

the number of states gaining and losing funds, for each of the three 

formula options. For example, each of our three prototypes would 

redistribute approximately 4 to 6 percent of the VR funds, with about 20 

states receiving more funds and at least 20 states receiving less in funds 

than they do under the current formula. Between 5 and 11 states would 

experience a change in funding levels of 20 percent or more. See appendix 

VIII for a state-by-state table of allocations under our three formula 

options. 

Page 15 GAO-09-798 Vocational Rehabilitation
 

Table 1: Redistribution of Funds under Three Formula Optionsa

Partial 

beneficiary 

equity 

Full 

beneficiary 

equity

Taxpayer

 equity

Amount of funds that would be 

redistributed, in millions $103.9 $153.4 $138.3

Percentage of total allocation 3.8 5.6 5.0

Number of states receiving more funds 23 19 23

Number of states receiving less funds 22 26 22

Number of states with no changeb6 6 6

Number of states experiencing an 

increase in funds of 20 percent or more 2 4 4

Number of states experiencing a 

decrease in funds of 20 percent or more 3 7 7

Source: GAO analysis of data from Education on VR grants in fiscal year 2008, Census Bureau’s 2006 and 2007 ACS, Treasury’s data 

on total taxable resources, BLS’ Quarterly Census of Employment and Wages, HUD’s data on fair market rents, and responses to GAO 

survey. 

a

The options presented in Table 1 are cumulative, i.e., the second option presented (full beneficiary 

equity) includes the first option (partial beneficiary equity). The third option (taxpayer equity) includes 

both of the other options. 

b

The same six states—Alaska, Delaware, North Dakota, South Dakota, Vermont, and Wyoming—

experience no change in their allotment due to the fact that they receive the minimum allotment under 

the current formula and would continue to do so under each of our options. 

In our survey of state VR agencies, many respondents expressed 

reservations about options for revising the current funding formula. Our 

survey presented state agencies with three general approaches to revising 

the formula, roughly based on our three formula options.21 Most 

respondents expressed reservations about options that were generally 

based on partial beneficiary and taxpayer equity, and they were divided on 

the option generally based on full beneficiary equity. Specifically, 45 

percent of respondents expressed support for an approach that would 

distribute funds so that all states would receive funding to be able to 

provide the same level of services to each individual potentially eligible for 

VR services, taking into account certain differences in the cost of 

providing services, while 47 percent expressed disapproval of this 

approach, and the remainder expressed no opinion or preference. 

 

21State agencies were not provided with specific details of the options presented in this 

report because these were not finalized at the time of our survey. In asking state agencies 

to provide their views on three options, generally based upon the equity standards, we 

sought to minimize the effect of any perceptions that they might gain or lose funding as a 

result of a formula change; however, we do not know whether such perceptions ultimately 

influenced their responses. 

Page 16 GAO-09-798 Vocational Rehabilitation
 

Options for Phasing In 

Changes to Minimize 

Disruption to State 

Programs 

When a new federal formula is implemented, Congress often provides a 

transition period so that grant recipients have time to adjust, especially 

those recipients whose grants will be reduced. An abrupt reduction in 

funding level could disrupt a state agency’s ability to provide VR services. 

Transition periods allow for greater predictability and stability in state 

funding levels, which in turn, help avoid major disruptions to existing state 

services and allow states to develop long-range plans and program 

commitments. 

One way to ease the change to a new formula is to phase it in gradually 

over a number of years. During the phase-in period, the state allocations 

would be a combination of the old and new formulas, with a gradual 

increase in the portion of funding distributed through the new formula, 

until the phase-in period is complete. By way of example, figure 4 depicts a 

5-year transition period, under which the amount of money allocated 

under the old formula would be reduced by 20 percent each year, and the 

amount allocated under the new formula would be increased by 20 percent 

each year, until all of the allocations are made using the new formula. To 

further minimize the disruptive effects of a new formula, the phase-in 

period could be longer, although this would, of course, postpone full use 

of the new formula. 

Page 17 GAO-09-798 Vocational Rehabilitation
 

Figure 4: A 5-Year Phase-In Transition to a New Funding Formula 

Source: GAO analysis.

Increased

20%

each year

NEW

FORMULA

Reduced

20%

each year

OLD

FORMULA

40%

60%

80%

100%

Percentage of funding

20

40

60

80

100

Year 0 Year 1 Year 2 Year 3 Year 4 Year 5

100

80

60

40

20

0%

20%

40%

60%

80%

100%

0%

20%

Another approach to minimize disruption to state VR programs is to 

establish a hold harmless provision that limits the amount of funding that 

states could lose under a new formula. One example of this approach 

would be to hold states entirely harmless in the first year that the new 

formula is implemented, but would allow minimal decreases during the 

second and successive years, such as by 1 or 2 percent. Because state 

agencies could also have difficulties adjusting to large and sudden funding 

increases, limits could also be set on the increases that states would 

receive from one year to the next. This graduated approach would allow 

agencies to better plan for the additional funds and manage growth in their 

VR programs. It should be noted that use of a hold harmless provision 

would effectively reduce the amount of funds available for distribution 

through the new formula in the early years of a change because most of 

the funds would be allocated through the hold harmless provision. 

However, over time, as the total amount of funds appropriated for the VR 

Page 18 GAO-09-798 Vocational Rehabilitation
 

program increases, more of the funds would be allocated through the new 

formula.22

Some research and experiences suggest that providing financial incentive 

awards based on program performance has the potential to improve 

government programs, and a slight majority of VR agencies surveyed are 

open to using them in the VR program. Some federal programs currently 

provide incentive awards and officials we spoke with from three of these 

programs noted some benefits, such as motivating state and local agencies 

to improve performance. Of the state VR agency officials who responded 

to our survey, 59 percent were open to including some form of incentive 

awards in the VR program. Some state officials noted that doing so could 

reward high performing agencies, improve VR client success, or motivate 

agencies to focus on continuous improvement. 

Incorporating 

Financial 

Performance 

Incentives in the VR 

Formula Poses 

Challenges 

Nevertheless, there are challenges to incorporating incentive awards into 

the VR program, whether through its funding formula or outside it due, in 

part, to the multiple and potentially competing facets of the VR program’s 

mission. According to the Rehabilitation Act, state VR programs should 

help clients achieve employment by providing individualized services, 

while also prioritizing service to those with the most significant disabilities 

when agencies cannot provide services to all eligible applicants. VR 

stakeholders we spoke with, including state agency officials, state 

advisory council officials, representatives from private sector VR 

companies, and disability researchers, identified three main challenges to 

incorporating incentive awards into the VR program. To some extent, 

these challenges are already present in the VR program’s current 

performance measurement system and could be accentuated by linking 

program performance to incentive awards. These challenges are: 

 

22The amount of time it would take for the new formula to fully be in place would depend 

on the level of the hold harmless provision. For example, if the hold harmless provision did 

not allow any state to experience a decrease from the prior year’s allocation, we estimate 

that it would take 10 to 13 years before all states’ allocations were determined by the new 

formula. However, if the hold harmless provision allowed states to experience a decrease 

of up to 10 percent from the prior year’s allocation, we estimate that it would take 7 to 10 

years for all states’ allocations to be determined by the new formula. These estimates 

assume that the federal funds available to be distributed for the VR program would 

increase by 4 percent per year, and that states’ relative levels of need population, costs, and 

taxable resources would remain the same over time. 

Page 19 GAO-09-798 Vocational Rehabilitation
 

• Challenge of balancing potentially competing program goals: Unless 

carefully designed, a financial performance incentive system could run the 

risk of encouraging state VR agencies to focus on achieving certain 

program goals, at the expense of others. For example, 89 percent of state 

VR officials who responded to our survey thought it likely that providing 

state agencies with additional funds based on performance would result in 

agencies focusing more heavily on clients who were expected to positively 

impact agency performance. In interviews, many VR stakeholders 

expressed particular concern that if incentive awards were focused on 

achieving employment outcomes for clients, they could induce state 

agencies to concentrate on serving those most likely to obtain 

employment, at the expense of those with greater barriers, such as those 

with the most significant disabilities. This would run counter to the VR 

program requirement that state agencies serve individuals with the most 

significant disabilities first when operating under an order of selection. 

Similar concerns have arisen in other employment programs that have 

used incentive awards. For example, we previously reported that local 

agency officials in the Department of Labor’s Workforce Investment Act 

(WIA) Title IB programs may be reluctant to provide services to job 

seekers less likely to find and maintain a job.23

• Challenge of rewarding agencies for providing appropriate 

individualized services to clients: The VR program provides both longterm services, such as supporting youth with disabilities as they transition 

out of high school and pursue higher education, and short-term services, 

such as identifying job opportunities for people who already have skills 

and qualifications. Several VR stakeholders expressed concern that if 

incentive awards did not take into account some clients’ specialized needs 

for higher-cost or longer-term services, they could cause agencies to focus 

on providing short-term services. Officials from one state advisory council 

cautioned that incentive awards might encourage VR counselors to focus 

on providing short-term services, even if it resulted in low-paying jobs, 

instead of placing VR clients in higher education programs that could 

ultimately yield long-term, higher paying career positions. 

• Challenge of basing incentive awards on an agency’s performance, 

without accounting for factors outside its control: A variety of factors 

outside an agency’s control may influence performance outcomes, such as 

the state’s economy and the characteristics and needs of the individuals 

 

23GAO, Workforce Investment Act: Improvements Needed in Performance Measures to 

Provide a More Accurate Picture of WIA’s Effectiveness, GAO-02-275 (Washington D.C.: 

Feb. 1, 2002). 

Page 20 GAO-09-798 Vocational Rehabilitation
 

who seek rehabilitation services. If an agency’s performance cannot be 

distinguished from these factors, the provision or withholding of incentive 

awards would not necessarily reflect agency actions.24 Of state VR agency 

officials who responded to our survey, 77 percent stated that isolating an 

agency’s performance from factors outside its control would be a great or 

very great challenge to appropriately distributing incentive awards. For 

example, officials in one VR agency said that some parts of their state have 

20 percent unemployment, which decreases their ability to place clients in 

jobs.25 Another state agency official noted that his agency has had very 

high employment outcomes, in part because the state had one of the 

lowest unemployment rates in the country. He added that agencies in 

other states whose economies are weak have had poorer employment 

outcomes through no fault of their own. In addition, some state officials 

suggested that agencies operating under an order of selection would be at 

a competitive disadvantage compared to those that are not, because the 

caseload of the former would include a greater proportion of clients with 

the most significant disabilities and barriers to employment. 

Our research into the types of incentive awards used by other federal 

programs, as well as the views of VR stakeholders, revealed several ways 

to mitigate such challenges, but none are without potential pitfalls. 

Specifically, research on designing incentive award systems suggests the 

following options: 

• Using multiple measures of success: Using a range of performance 

measures to determine incentive awards could help motivate state 

 

24Prior GAO reports have noted that Education’s performance measures for the VR 

program do not account for factors such as the economic health and demographics of a 

state. GAO, Vocational Rehabilitation: Improved Information and Practices May 

Enhance State Agency Earnings Outcomes for SSA Beneficiaries, GAO-07-521

(Washington D.C.: May 23, 2007) and Vocational Rehabilitation: Better Measures and 

Monitoring Could Improve the Performance of the VR Program, GAO-05-865 (Washington 

D.C.: Sept. 23, 2005). 

25A 2004 report commissioned by the Department of Education found that poor labor 

market conditions, particularly high unemployment rates, were reported as being among 

the most influential hindrances to a VR agency’s performance. See RTI International, Study 

of Variables Related to State Vocational Rehabilitation Agency Performance (Revised 

Draft Final Report), (Research Triangle Park, N.C., October 2004).

Page 21 GAO-09-798 Vocational Rehabilitation
 

agencies to focus attention on all aspects of the VR program’s mission.26

For example, the performance of state VR agencies might be measured in 

terms of both the proportion of people with the most significant 

disabilities who find employment, and the proportion of all clients who 

achieve this outcome. Another option that could encourage agencies to 

provide long-term services, when appropriate, is to establish intermediate 

measures of client achievement or the services provided that have 

increased a client’s prospect for employment. Such an intermediate 

measure could be the number of VR clients who successfully complete 

training programs or college degrees. Nevertheless, there are challenges to 

developing appropriate measures. For example, although Education 

already uses a measure for the VR program focused on people with 

significant disabilities, it may be difficult to develop a measure specifically 

on people with the most significant disabilities because the Rehabilitation 

Act allows states to individually define the term, and our past work found 

that state agencies’ definitions vary.27 Although Education uses multiple 

measures to evaluate state VR agencies’ performance, an issue to consider 

is whether or not the current measures would be appropriate to use for 

distributing incentive awards. Our prior work on the VR program found 

that the current measures do not consider agencies’ success in assisting 

individuals who have not yet exited the program and do not specifically 

track outcomes for youth transitioning out of high school. As a result, we 

recommended that Education reevaluate its performance measures to 

determine whether they reflect the agency’s goals and values.28

 

26According to our past work, one key attribute of a successful performance measure 

system is its coverage of all activities that an entity is expected to perform to support the 

intent of the program. GAO, Tax Administration: IRS Needs to Further Refine Its Tax 

Filing Season Performance Measures, GAO-03-143 (Washington D.C.: Nov. 22, 2002). Also, 

researchers of performance incentives have noted that the exclusion of measures for some 

key program goals can lead agencies to focus on goals that are measured, to the detriment 

of those that are not. 

27Under the Rehabilitation Act, a significant disability is defined as one that seriously limits 

one or more functional capacities and can be expected to require multiple VR services over 

an extended period of time. In the VR program, “significant disability” is a separate and 

broader category than “most significant disability.” For more information on our prior work 

related to the definition of most significant disability, see GAO-05-865.

28GAO-05-865. For example, GAO recommended that Education consider additional 

measures (e.g., to better reflect special needs populations, such as transitioning students) 

and accounting for factors outside of its control. Education generally agreed with our 

findings. Since then, Education has developed a draft strategic plan that proposes longterm performance goals, objectives, and measures for use in its performance monitoring 

activities. This draft plan includes measures of agency success in serving youth 

transitioning out of high school, individuals with significant disabilities, and individuals 

with significant disabilities who receive public financial support at the time of application 

to the VR program. 

Page 22 GAO-09-798 Vocational Rehabilitation
 

• Adjusting performance standards to account for differences in local 

economies and program clients: The level of performance required of 

each state VR agency to receive an incentive award could be adjusted to 

account for the challenges they face.29 For instance, the performance 

standard required to receive an incentive award may be set lower for 

agencies in states with poor economies than for states with better 

economies.30 These adjustments could be made using a mathematical 

model, negotiations between federal and state agencies, or a combination 

of the two approaches. For example, the Job Training Partnership Act 

program (JTPA) used mathematical models to quantify the relative effect 

of participants and economies on agency outcomes. Some researchers of 

the JTPA program found that this approach was perceived to “level the 

playing field” for agencies and had lessened the perverse incentives to 

focus more heavily on the most promising clients.31 However, the research 

also suggests that it is difficult to identify and measure all the external 

 

29For more detail about potential approaches to adjusting performance standards, see 

Pascal Courty, Carolyn Heinrich and Gerald Marschke, “Setting the Standard in 

Performance Measurement Systems,” International Public Management Journal 8:3 

(2005); Joe Siedlecki and Christopher T. King, “Approaches to Adjusting Workforce 

Development Performance Measures,” Ray Marshall Center for the Study of Human 

Resources, Lyndon B. Johnson School of Public Affairs, The University of Texas at Austin 

Occasional Brief Series 1:2 (2005); and Carolyn J. Heinrich and Burt S. Barnow, “One 

Standard Fits All? The Pros and Cons of Performance Standard Adjustments,” La Follette 

School Working Paper, 2008-023. These articles discuss adjusting performance standards 

based on mathematical models; negotiation among local, state and federal agencies; or 

approaches that use both. 

30Incentive award decisions could also be based on the extent to which an agency improved 

over its past performance. While this approach allows agencies to be measured against 

their own progress rather than general standards applied to all states regardless of their 

circumstances, it can also pose challenges because the circumstances within a state may 

change from year to year. For example, if a state enters a recession, improving 

performance from previous years may not be feasible. In addition, setting performance 

goals in this way may create perverse incentives for officials to limit performance gains in a 

given year in order to decrease the performance level required in future years. 

31The JTPA was the predecessor to the Department of Labor’s WIA Title IB employment 

and training programs for adults, youth and dislocated workers which were authorized in 

1998. For more information, see Heinrich and Barnow, 2008 and Pascal Courty, Do Han 

Kim, and Gerald Marschke, “Curbing Cream-Skimming: Evidence on Enrollment 

Incentives,” Forschungsinstitut zur Zukunft der Arbeit Institute for the Study of Labor, 

Discussion Paper No. 3909, (December 2008). Courty, Kim, and Marschke found that the 

JTPA agencies responded to the adjustment model by increasing the proportion of clients 

in the program from demographic groups estimated to have more barriers to employment. 

However, they also found that JTPA program staff continued to select the individuals who 

were most likely to find employment from within these demographic groups. While this 

shows continued evidence of a perverse reaction to the performance award system, the 

authors described it as a much smaller problem than if these adjustments had not occurred. 

Page 23 GAO-09-798 Vocational Rehabilitation
 

factors that can undermine or lessen agency performance. If key factors 

are missing from mathematical models, the adjusted performance 

standards may lead to inaccurate estimates.32 Taking a different approach, 

WIA Title IB employment and training programs set performance 

standards by negotiating with state agencies. Although advocates of this 

approach say that it increases agency involvement and may better capture 

qualitative factors that affect agency performance, we and others have 

criticized the WIA negotiation approach as unsystematic and inconsistent 

across states.33 Specifically, we have suggested using an approach that 

combines negotiations with mathematical models. In a prior report, we 

recommended that Labor develop an adjustment model or other 

systematic method to account for different populations and local 

economies when negotiating performance levels.34 Labor officials 

generally agreed with our recommendation and told us recently that

are starting to provide states with adjustment models to inform t

negotiation process. Finally, some researchers and public officials 

identified concerns about adjusting performance standards, regardless of 

the method. For example, some researchers have expressed concern that 

adjusting performance standards may be unfair to clients because it allows 

agencies to settle for less desirable outcomes for harder-to-serve 

populations. 

 they 

he 

 

Beyond these risks, there are a number of considerations involved in 

deciding to incorporate incentive awards directly into the VR funding 

formula itself. First, it would be important to consider whether or not 

states should be required to match the additional funds allocated for 

performance, and if not, whether those funds could be treated as part of 

the state’s matching contribution. Another consideration is that rewarding 

high performance through the funding formula would, in effect, penalize 

other states insofar as it reduces the total funding available for distribution 

to all agencies based on other formula factors. Some state VR agency 

officials we spoke with suggested that incentive awards should not result 

in any decrease to base funding allocations. HUD’s Public Housing Capital 

32For more information, see Arthur C. Brooks, “The Use and Misuse of Adjusted 

Performance Measures,” Journal of Policy Analysis and Management, 19:2 (Spring 2000) 

and Heinrich and Barnow, 2008. 

33GAO, Workforce Investment Act: States and Local Areas Have Developed Strategies to 

Assess Performance, but Labor Could Do More to Help, GAO-04-657 (Washington, D.C: 

June 1, 2004) and GAO-02-275. 

34GAO-04-657. 

Page 24 GAO-09-798 Vocational Rehabilitation
 

Fund program, which provides incentive awards through its funding 

formula, includes provisions that minimize the impact of the awards on 

states’ funding.35 However, HUD officials we spoke with still expressed 

concern that this system penalizes housing authorities that may need 

additional funds if they are to improve their performance. 

Alternatively, incentive awards could be distributed independently of the 

VR funding formula to avoid these inherent penalties. Options for 

distributing funds outside the main VR funding formula include providing 

incentive awards as grants, as occurs in the WIA Title IB programs, or 

through a separate incentive award formula, as occurs in the Child 

Support Enforcement program.36 Of the state VR officials who responded 

to our survey, 51 percent supported providing incentive awards distributed 

independently of formula-determined funds, while only 22 percent 

supported providing the incentive awards through the formula.37

Finally, regardless of whether incentive awards are provided through the 

VR funding formula or independent of it, there are still other 

considerations involved in designing and carrying out an incentive award 

system. For instance, it is important that incentive awards are based on 

reliable data about agency performance. It is also important to consider 

the extent to which an incentive award system will allow for future 

modifications should there be changes in program priorities or available 

 

35High performing local public housing authorities receive a 5 percent increase in their base 

formula allocation, with the stipulation that no public housing authority will lose more than 

5 percent of its formula allocation due to the redistribution of funds for incentive awards. 

36For more information on the process for distributing WIA performance incentive awards 

as grants, see Employment and Training Administration, Training and Employment 

Guidance Letter No. 9-07, Revised Incentive and Sanction Policy for Workforce 

Investment Act Title IB Programs (Washington D.C., Oct. 10, 2007). For more information 

on the process for distributing Child Support Enforcement Program performance incentive 

awards through a specific formula, see Congressional Research Service, Child Support 

Enforcement Program Incentive Payments: Background and Policy Issues, RL 34203 

(Washington D.C., October 2007). 

37Specifically, officials from 14 percent of the agencies that responded to our survey 

supported incentive awards, regardless of whether they were provided inside or outside the 

formula; 38 percent only supported incentive awards outside the formula; and 8 percent 

only supported incentive awards within the formula. Also, 41 percent did not support, or 

had no opinion regarding, using incentive awards either within or outside the funding 

formula. These numbers total to greater than 100 percent due to rounding. 

Page 25 GAO-09-798 Vocational Rehabilitation
 

data, or if perverse and unanticipated results ensue. Our earlier work 

discusses these and other, related considerations.38

Although the measures currently used to allocate VR funds may have been 

the best available when the formula was last revised in 1978, better data 

are now available for factoring in both the potential need for and ability to 

support a program. Improved information offers policymakers the 

opportunity to update the formula to more closely align funding with the 

need for services, as well as with each state’s ability to contribute to the 

program. In deciding whether a revision to the formula is warranted, 

policymakers will likely want to consider how to strike a balance among 

all important factors—need, the cost of providing services, and the extent 

to which state resources are available. Certainly, revising the funding 

formula poses challenges because any formula change will result in 

funding decreases for some states, along with increases for others. 

However, there are ways to ease the transition to a new formula, so as to 

minimize disruption to VR programs and the people they serve. On the 

other hand, incorporating performance incentives into the formula might 

introduce more complexity and risk. While there are mechanisms to 

mitigate these challenges, the potential benefits for the VR program would 

need to be carefully weighed against the potential risks. 

Concluding 

Observations 

We provided a draft of this report to Education for review and comment. 

Education provided technical comments and we modified the report, as 

appropriate, to address these comments. 

Agency Comments 

and Our Evaluation 

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

relevant congressional committees, and other interested parties. The 

report will also be available at no charge on GAO’s Web site at 

http://www.gao.gov. 

 

38GAO, Grants Management: Enhancing Performance Accountability Provisions Could 

Lead to Better Results, GAO-06-1046 (Washington D.C.: Sept. 29, 2006). 

Page 26 GAO-09-798 Vocational Rehabilitation
 

If you or your staffs have any questions about our report, please contact 

me at (202) 512-7215 or bertonid@gao.gov. Contact points for our Offices 

of Congressional Relations and Public Affairs may be found on the last 

page of the report. Key contributors to this report are listed in appendix X. 

Director, Education, Workforce, 

ecurity Issues 

Daniel Bertoni 

 and Income S

Page 27 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology Appendix I: Objectives, Scope, & 

Methodology 

Our objectives were to: (1) assess the extent to which the funding formula 

meets generally accepted equity standards, (2) develop options for revising 

the formula to better meet these standards, and (3) identify issues to 

consider with incorporating performance incentives into the formula. We 

used two generally accepted formula design standards intended to achieve 

equity for beneficiaries and taxpayers.1

 To meet both equity standards, a 

formula should use reliable and appropriate measures of the need 

population in each state and the cost of providing services in each state. A 

taxpayer equity formula additionally requires a reliable measure of a 

state’s ability to finance a program from its own resources. In the 

following sections, we describe how we measured the need population, 

cost of providing services, and financing capacity in each state, and how 

we analyzed the extent to which the current formula meets equity 

standards and developed various formula options.2

 To address all three 

objectives, we also surveyed the 80 vocational rehabilitation (VR) agencies 

in the states, territories, and District of Columbia and conducted in-depth 

interviews with 11 VR agencies in 9 states. Finally, for the third objective, 

we reviewed literature on performance incentives and obtained the 

opinions of officials at 3 federal government programs that use incentive 

awards, which we describe in more detail in the last section. 

We conducted this performance audit from September 2008 to September 

2009, in accordance with generally accepted government auditing 

standards. Those standards require that we plan and perform the audit to 

obtain sufficient, appropriate evidence to provide a reasonable basis for 

our findings and conclusions based on our audit objectives. We believe 

that the evidence obtained provides a reasonable basis for our findings 

and conclusions based on our audit objectives. 

 

1

As noted earlier, beneficiary equity stipulates that funds should be distributed to states 

according to the needs of their respective populations, so that each state, with its federal 

allocation, can provide the same level of services to each person in need. Taxpayer equity 

stipulates that funds are distributed so that states can provide individuals comparable 

services using both state and federal funds, while each state contributes about the same 

proportion of its resources to a given federal program. 

2

The following experts reviewed our analysis of need population and cost of providing 

services: Andrew Houtenville, Associate Professor of Economics and Research Director of 

the Institute on Disability, University of New Hampshire; Mitchell LaPlante, Associate 

Adjunct Professor of Social and Behavioral Sciences and Director of the Disability 

Statistics Center, University of California San Francisco; and David Stapleton, Senior 

Fellow and Director, Center for Studying Disability Policy, Mathematica Policy Research, 

Inc. 

Page 28 GAO-09-798 Vocational Rehabilitation 
Appendix I: Objectives, Scope, & Methodology 

Data that directly measure the number of people in a state who potentially 

need VR services do not exist. Although state VR agencies have data on the 

size of their own caseloads, these data are not appropriate for use in a 

funding formula for two reasons. First, caseloads may be influenced by 

state funding levels. For example, an agency’s caseload may be relatively 

small because of limited funds, not because of limited demand for 

services. Second, data that can be controlled by state agency officials 

should not be used in a funding formula because they could introduce 

some “undesirable incentives” into the program. For instance, if a state’s 

allotment were determined by the size of its caseload, a state agency might 

be rewarded for taking inappropriate actions, such as enrolling individuals 

into the VR program who do not require VR services or, in the case of an 

agency under an order of selection, enrolling individuals who do not meet 

its criteria for receiving priority for services. 

Measuring State Need 

Populations 

There are, however, several national surveys that provide estimates of the 

number of people with disabilities by state. These surveys are conducted 

by statistical agencies such as the Census Bureau and Bureau of Labor 

Statistics (BLS). We reviewed several of these surveys: (1) the Census 

Bureau’s American Community Survey (ACS), (2) the Decennial Census,3

(3) the Current Population Survey’s Basic Monthly Survey, (4) the Current 

Population Survey’s Annual Social and Economic Supplement, and (5) the 

Center for Disease Control’s Behavioral Risk Factor Surveillance System. 

We sought to identify data on the populations with all types of disabilities 

in each state.4

We ultimately selected the Census Bureau’s ACS to use as a measure of 

state populations potentially in need of VR services for several reasons. 

First, the ACS provides data on states’ disability populations on an annual 

basis. Second, the ACS has a large sample size (with about 3 million 

housing units surveyed across all 50 states, the District of Columbia, and 

Puerto Rico), which would allow for more accurate estimates of the need 

 

3

The Department of Transportation’s New Freedom program, which provides funds to 

support public transportation services and alternatives beyond those required by the 

Americans with Disabilities Act, uses a formula that allocates funds based on a locality’s 

population of people with disabilities. The Department of Transportation measures the 

disability populations of large urbanized areas, small urbanized areas, and rural and small 

urban areas with populations less than 50,000 using data from the 2000 Decennial Census. 

4

We did not separately identify data on blind populations in each state. In a state with two 

VR agencies, the state determines how to divide federal VR funds among the agency for the 

blind and the general VR agency. 

Page 29 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

population in each state. Third, the ACS surveys people in more types of 

group quarters than any of the other surveys, such as those living in 

college dormitories, group homes, prisons, and nursing care facilities. This 

is significant, since about 10 percent of VR clients exiting the program in 

2006 and 2007 lived in group quarters such as group homes or 

rehabilitation facilities when they applied to receive VR services, 

according to Education’s data. Fourth, the ACS asks six questions that are 

designed to capture a wide variety of disabilities (see table 2), and these 

questions are asked consistently across all states. One limitation of the 

ACS for purposes of allocating VR funds, however, is that the data are not 

available for U.S. territories, with the exception of Puerto Rico. 

Table 2: Disability Questions from the American Community Survey, 2006 and 2007 

Disability question 

1. Does this person have any of the following long-lasting conditions: 

Blindness, deafness, or a severe vision or hearing impairment? 

2. Does this person have any of the following long-lasting conditions: 

A condition that substantially limits one or more basic physical activities such as walking, 

climbing stairs, reaching, lifting, or carrying? 

3. Because of a physical, mental, or emotional condition lasting 6 months or more, does 

this person have any difficulty in doing any of the following activities: 

Learning, remembering, or concentrating? 

4. Because of a physical, mental, or emotional condition lasting 6 months or more, does 

this person have any difficulty in doing any of the following activities: 

Dressing, bathing, or getting around inside the home? 

5. Because of a physical, mental, or emotional condition lasting 6 months or more, does 

this person have any difficulty in doing any of the following activities: 

Going outside the home alone to shop or visit a doctor’s office? 

6. Because of a physical, mental, or emotional condition lasting 6 months or more, does 

this person have any difficulty in doing any of the following activities: 

Working at a job or business? 

Source: Census Bureau. 

We analyzed the data produced by only 5 of the 6 disability questions from 

the 2006 and 2007 ACS. We did not use data from the sixth question 

regarding the difficulty of working (question 6 in table 2) because the 

Census Bureau had removed this question in 2008 at the recommendation 

of an inter-agency task force. The 2008 ACS data is expected to be released 

in the fall of 2009 and was not available to use for this study. Since this 

question will not be included on future surveys, we sought to produce an 

analysis that would more closely reflect future available data. However, 

because changes were also made to each of the five other ACS questions 

Page 30 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

for the 2008 survey, we cannot say whether our analysis of 2006 and 2007 

data will be predictive of conditions in 2008 or thereafter.5

We measured each state’s disability population by counting the number of 

civilians of working age (16 to 64) who responded “yes” to any of the five 

disability questions. By excluding the difficulty working question, our 

measure excluded 12.5 percent of the population who responded “yes” to 

the difficulty working question. The remaining 87.5 percent of those who 

responded “yes” to this question were people who also responded “yes” to 

one or more of the five other disability questions. As a result, they were 

included in our measure. 

Table 3 provides a breakdown of the total U.S. population into the 

different components of our measure of the need population for the VR 

program. As shown in the table, our measure—the civilian working-aged 

population with a disability—comprises 7.6 percent of the total U.S. 

population. 

Table 3: Breakdown of the Total U.S. Population into Components of our Measure 

of the Need Population for the VR program, 2007 

Population 

Percentage of total

population

Total U.S. 301,621,159 100

Civilian working-aged (16 to 64) 197,630,139 65.5

Civilian working-aged with a disabilitya (16 to 64) 22,886,919 7.6

Source: GAO analysis of data from the Census Bureau’s ACS. 

a

For purposes of this study, the population of people with disabilities is based upon data from five 

disability questions asked in the 2007 ACS. We did not include data from a sixth question on difficulty 

working. 

 

5

Each of the other five disability questions in the ACS were changed, starting in 2008. For 

example, question 1 on blindness, deafness, or severe vision or hearing impairment was 

made into two separate questions—one specifically on deafness or serious difficulty 

hearing, and another one on blindness or serious difficulty seeing even when wearing 

glasses. Question 2 about difficulty with physical activities such as walking, climbing stairs, 

reaching, lifting, or carrying was changed to ask whether the person has a serious difficulty 

walking or climbing stairs. Question 3 about difficulty learning, remembering, or 

concentrating was changed to ask about difficulty concentrating, remembering, or making 

decisions. Question 4 about difficulty dressing, bathing, or getting around inside the home 

was changed to ask whether the person has difficulty dressing or bathing. Finally, Question 

5 about difficulty going outside the home alone to shop or visit a doctor’s office was 

changed to ask about difficulty doing errands alone, such as visiting a doctor’s office or 

shopping. 

Page 31 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

We assessed the reliability and validity of ACS data by interviewing Census 

Bureau officials and disability experts, reviewing documentation and 

literature, and conducting comparisons with other disability data. 

Specifically, we compared the ACS data with data from the Social Security 

Administration (SSA) on recipients of two types of disability benefits, 

Social Security Disability Insurance (SSDI) and Supplemental Security 

Income (SSI) benefits. For individuals to receive SSDI or SSI benefits, SSA 

or a state agency must first determine that they have a disability that 

prevents them from working. We compared the proportion of state 

populations with disabilities, according to ACS data, with the proportion 

of their populations receiving SSA disability benefits and found a high 

correlation—0.872 for SSDI and 0.788 for SSI. This indicates that ACS data 

and the SSA data showed similar trends; states with higher rates of 

disability according to ACS data also tended to have higher proportions of 

their population receiving SSA disability benefits. We had our work on 

identifying a measure of need population reviewed by three disability 

experts, and they concurred that ACS data provide a reasonable measure 

of the size of a state’s population potentially needing VR services. 

It is difficult to estimate differences among states in the costs of providing 

VR services. Although one approach for estimating cost differences is to 

estimate the costs for the same basket of goods in different states, 

attempting to do this for VR services would be extremely costly and laborintensive because of the wide array of services that VR agencies provide, 

including assessment, counseling, higher education, occupational training, 

medical diagnosis and treatment, and transportation. Another challenge is 

finding a reliable data source on cost. State agencies’ data on 

expenditures, in part, reflect cost of services, but using these data in a 

formula runs the risk of allowing undesirable incentives to be introduced 

into the program. For example, a state agency that efficiently manages its 

program will be able to provide the same quality of services at a lower cost 

than an agency with less efficient management. In this case, if the formula 

provided higher allocations to states with higher reported costs, it could 

reward agencies that are more inefficient. In addition, expenditures data 

are of limited use in measuring state cost differences because they reflect 

many other factors besides costs. For example, the amount of funds that 

agencies spend per client reflects the level of funds they receive from state 

and federal sources, as well as the types of clients they serve and the types 

of services they provide. For example, some agencies may choose to 

provide more intensive, higher-cost services to a smaller number of 

clients, while other agencies may choose to serve a larger number of 

clients with lower-cost services. 

Measuring State Cost 

Differences 

Page 32 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

To address these challenges, we developed and used measures for the 

costs of resources—or inputs—that go into providing services, which are 

beyond the direct control of state agencies. Specifically, we focused on 

two basic inputs—labor and office space—that are needed to provide the 

different types of VR services. Where wages or rents are higher because 

the general cost of living is high, state agencies must pay more for workers 

or office space to provide services. In the following subsections, we 

describe in detail how we developed a cost index to reflect differences in 

costs for these two types of inputs, labor and office space. There are many 

other resources used to provide VR services, such as equipment and 

supplies, but data are not readily available on them. Obtaining such data 

would be time-intensive and costly, requiring detailed surveys of the 

specific services that each VR agency provides and the particular 

resources that go into each service. As a result, our cost index may not 

capture differences in the cost of some key inputs. For example, due to 

lack of data, our index would not capture transportation costs, which 

could be higher in states that have geographically dispersed populations. 

While our index has some limitations, we believe it is a reasonable proxy 

that can reflect general differences across states in the cost of providing 

VR services. Because any cost index will only be an approximation of true 

cost differences, the index we developed is based on what we believe are 

reasonable assumptions that avoid overstating or exaggerating cost 

differences among states. We believe our measure allows us to at least 

partially recognize real cost differences among the states, while avoiding 

inappropriate incentives. A similar cost of services index is used in the 

funding formulas for the Community Mental Health Services and the 

Substance Abuse Prevention and Treatment block grants. 

In the following subsections, we describe: (1) our work to identify a data 

source for estimating wages in each state, (2) the data source we used to 

estimate rental costs in each state, (3) our methodology for estimating 

how much to weight wages and rents in the cost index, and (4) how we 

combined our weights with the data on wages and rents to develop a cost 

of services index for each state. Since the purpose of our cost index is to 

help distribute federal VR funds among states, we did not examine cost 

differences between agencies for the blind and general VR agencies. In 

states with two VR agencies, the state determines how to divide the 

federal grant allocation among the agencies. 

Page 33 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

A measure of state labor costs should reflect the wages of all types of 

workers potentially involved in the VR program, including those directly 

employed by state VR agencies, as well as those employed by public or 

private-sector organizations that VR agencies have contracted with to 

provide VR services. To obtain an understanding of the types of workers 

who may be involved in state VR programs, we first reviewed data from 

Education’s Annual Vocational Rehabilitation Program/Cost Report (RSA2), which provides information on state agencies’ expenditures on various 

types of services, both those provided by state agency employees and 

those provided through contracts or purchases from other organizations.6

The data indicate the proportion of expenditures state agencies spent on 

the following types of services in fiscal year 2007: 

Identifying a Proxy for 

Wages in the VR Program 

• 7 percent on postsecondary education 

• 14 percent on occupational and vocational, job readiness, and all other 

training 

• 13 percent on assessment, counseling, guidance, and placement 

• 7 percent on diagnosis and treatment of physical and mental impairments 

• 4 percent on rehabilitation technology 

• 1 to 2 percent each on other types of services, such as income support, 

transportation, and personal assistance services 

Once we obtained information on the types of services that the VR 

program provides, we reviewed sources of data from BLS on average 

annual wages in each state for various industries and occupations, as well 

as wage data from the Centers for Medicare and Medicaid Services (CMS) 

that are used to adjust payments to healthcare providers. Specifically, we 

examined BLS data from the Quarterly Census of Employment and Wages 

(QCEW) and Occupational Employment Statistics (OES). The QCEW data, 

which come from employer filings for unemployment insurance, cover 

nearly all civilian employment. It classifies wages and employment levels 

by industry, using the North American Industry Classification System 

 

6

The RSA-2 data showed that 46 percent of state agencies’ expenditures were spent on 

services that were contracted out or purchased. The data did not, however, allow us to 

determine the extent to which each specific type of service was provided by state agency 

employees or was contracted out or purchased from other organizations. 

Page 34 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

(NAICS). We examined private sector wages, but also included public 

sector wages for state government employees. In addition, we also 

reviewed data on specific occupations related to the VR industry from the 

OES. The OES classifies occupations according to the Standard 

Occupational Classification (SOC) system. Finally, we examined wage 

indices used to allocate funds in the Medicare program for skilled nursing 

and inpatient rehabilitation facilities. The specific data series we reviewed 

are listed below: 

• BLS, Quarterly Census of Employment and Wages 

• Vocational rehabilitation services industry, private sector (NAICS 

6243) 

• Social assistance industries, private sector (NAICS 624) 

• Healthcare and social assistance industries, private sector (NAICS 62) 

• Education, healthcare, and social assistance industries, private sector 

(QCEW industry code 1025) 

• Service-providing industries, private sector (QCEW industry code 102) 

• State government sector (QCEW industry code 10, state government) 

• BLS, Occupational Employment Statistics 

• Rehabilitation counselors (SOC 21-1015) 

• Substance abuse and behavioral disorder counselors (SOC 21-1011) 

• Educational, vocational, and school counselors (SOC 21-1012) 

• Community and social services occupations (SOC 21) 

• Wage indices for Medicare’s Prospective Payment System 

• Inpatient Rehabilitation Facilities 

• Skilled Nursing Facilities 

We determined that the data for the most narrowly-defined industries and 

occupations— the QCEW data for the vocational rehabilitation services 

industry, and the OES data on rehabilitation counselors—were less 

suitable for use in a cost index after examining the data and speaking with 

officials from BLS. The QCEW data on the vocational rehabilitation 

industry showed some peculiar values. For example, the wages in Vermont 

were the highest in the nation in the vocational rehabilitation services 

industry, but they were not among the highest in other data series we 

examined. We contacted BLS officials to better understand these data. 

They informed us that Vermont’s data for the vocational rehabilitation 

services industry come from a small number of employers, and as a result, 

could be affected by two factors: possible differences in the types of work 

Page 35 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

performed and in the number of hours worked per week. The average 

annual wage in the QCEW is calculated by including both employees who 

worked full-time and part-time. If the proportion of VR employees working 

part-time varies substantially across states, this could cause state annual 

wages to vary. At a broader industry level, this is less likely to be a 

problem because the data cover more employers and employees. With 

regard to the OES data on rehabilitation counselors, the data were 

incomplete. There were no published wages for Alaska and Utah. 

The remaining data series could serve as reasonable proxies for state 

wages in the VR program, but we selected the QCEW data for the 

education, healthcare, and social assistance industry sector for our proxy 

because it covers the wide array of services that the VR program provides. 

These include training, healthcare-related services, and social services. In 

addition, this industry had the smallest range for wage differences across 

states—the state with the lowest wage in this industry was 17 percent 

below the average, and the state with the highest wage was 25 percent 

above average. As a result, compared to the other industries, the 

education, healthcare, and social assistance industry would produce the 

more conservative results. Table 4 shows the median, minimum, and 

maximum values for each of the data series we examined for which data 

were available for all 50 states and the District of Columbia. To compare 

wages across states and across data series, we used wage indices. A value 

of 1 is equal to the national average. Values greater than 1 are above the 

national average, and values less than 1 are below the national average. 

Page 36 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

Table 4: Summary Statistics for Wage Indices from Data Series Reviewed 

Data 

source Industry/occupation Minimum Median Maximum

QCEW Vocational rehabilitation services industry 

(NAICS 6243) 0.66 0.94 1.47

Social assistance industries (NAICS 624) 0.70 0.92 1.84

Healthcare and social assistance 

industries (NAICS 62) 0.83 0.95 1.31

Education, healthcare, and social 

assistance industries (QCEW 1025) 0.83 0.95 1.25

Service-providing industries (QCEW 102) 0.67 0.87 1.63

State government (QCEW 10, state 

government) 0.73 0.95 1.32

OES Community and social services 

occupations (SOC 21) 0.72 0.95 1.19

Medicare Inpatient rehabilitation facilities 0.74 0.93 1.25

Skilled nursing facilities 0.74 0.93 1.27

Source: GAO analysis of BLS and CMS data. 

Table 5 presents correlations of the various wage indices. It shows that the 

various wage data we reviewed are correlated with each other, which 

suggests that the different data series would generally produce similar 

results in funding allocations. The vocational rehabilitation services 

industry (NAICS 6243), in the first row, has the lowest level of correlation 

with the other indices. Its highest correlation coefficient is 0.63 with the 

social assistance industry (NAICS 624), while no two other wage indices 

have a correlation coefficient less than 0.65. 

Page 37 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

Table 5: Correlations between Wage Indices 

QCEW, 

Social 

assistance 

QCEW, 

Healthcare 

and social 

assistance 

QCEW, 

Education, 

healthcare, 

and social 

assistance

QCEW, 

ServiceprovidingQCEW, State 

government

OES, 

Community 

and social 

services 

occupations 

Medicare, 

Inpatient 

rehabilitation 

facilities

Medicare, 

Skilled 

nursing 

facilities

QCEW 

Vocational 

rehabilitation 

services 0.63 0.51 0.52 0.61 0.49 0.50 0.49 0.48

Social assistance 0.80 0.78 0.84 0.69 0.69 0.66 0.65

Healthcare and 

social assistance 0.99 0.81 0.66 0.79 0.72 0.72

Education, 

healthcare and 

social assistance 0.83 0.67 0.79 0.72 0.72

Service-providing 0.72 0.74 0.68 0.66

State government 0.75 0.72 0.71

OES 

Community and 

social services 0.82 0.82

Medicare 

Inpatient 

rehabilitation 

facilities 1.00

Source: GAO analysis of BLS and CMS data. 

The distribution of values for the education, healthcare, and social 

assistance wage index is shown in figure 5. Values for more than half of 

the states lie between 0.9 and 1.1, which suggests that most states have 

similar wages in this industry sector. 

Page 38 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

Figure 5: Distribution of Average State Wages in the Education, Healthcare, and 

Social Assistance Industry Sector, 2005 to 2007 

Number of states

Source: GAO analysis of data from BLS’ Quarterly Census of Employment and Wages.

State wage index

0

2

4

6

8

10

12

14

16

18

20

0.75 0.85 0.90 1.00 1.10 1.15 1.25 1.65

Identifying a Proxy for 

Commercial Rents 

State-by-state data on the cost of office space are not available. As a result, 

we used as a proxy residential rental rates. The Department of Housing 

and Urban Development (HUD) annually collects the rental cost of 

housing for 530 metropolitan areas and 2,045 non-metropolitan counties 

across the nation. These Fair Market Rents (FMR) data are used by several 

programs to set housing subsidies. The FMR data are also used in 

Medicare’s physician fee schedule as a measure of office rents. 

Since the FMR provides data on a local level, we aggregated the data to 

statewide averages and used an index to compare rental costs across 

states. The distribution of rents is shown in figure 6. Similar to figure 5, a 

value of 1 is equal to the national average. Values greater than 1 are above 

the national average, and values less than 1 are below the national 

average. Unlike the wage index, the rental cost index shows that over half 

of the states have a rental index of 0.85 or less, while 11 states have a 

rental index of 1.15 or higher. This suggests that rental costs vary 

substantially among states. 

Page 39 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

Figure 6: Distribution of Average State Rents, Fiscal Years 2007 to 2009 

Number of states

Source: GAO analysis of HUD data.

State rent index

0

2

4

6

8

10

12

14

16

18

0.75 0.85 0.90 1.00 1.10 1.15 1.25 1.65

Weighting of Inputs To determine how much to weight the wage and rental costs, we first 

surveyed state VR agencies to learn what proportion of their fiscal year 

2007 and 2008 expenditures was spent on wages and rents. Because many 

agencies contract out or purchase services, our survey asked them first to 

report how much of their expenditures were for contractors or purchased 

services, and how much was spent in-house. Then we asked them to 

report how much of their in-house expenditures went to wages and rents. 

We used these responses to compute average proportions, which we then 

applied to categories of expenditures using RSA-2 data. In doing so, we 

assumed that the proportions of expenditures on wages and rents that 

state agencies reported for in-house expenditures was the same as the 

proportions for contracts and purchased services.7

 With regard to the RSA2 data, we examined state VR agencies’ spending in three broad categories: 

administration, individual services, and group services. 

 

7

We were not able to identify data that could be used to estimate the proportion of contract 

expenditures that went to wages and rents. Further, state agency officials who tested our 

survey informed us that they would not be able to estimate the amount of contract 

expenditures that went to wages and rents. 

Page 40 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

Table 6 shows the results of our analyses of the survey responses and the 

RSA-2 data, as well as how we combined these results to develop the 

weights for wages, rents, and other inputs in the cost index. In table 6, the 

first column shows the expenditure categories from the RSA-2 data. The 

second column shows the average proportion of expenditures that went to 

administration, individual, and group services, according to the RSA-2 

data. The third through fifth columns show our survey results on the 

average proportion of expenditures that went to labor costs, rents, and 

other inputs. We assumed that for administration and individual services, 

expenditures went to labor, rents, and other inputs in the precise 

proportions that the survey results suggested. For example, we assumed 

that 69 percent of expenditures for administration and individual services 

were spent on wages, 5.6 percent on rents, and the remainder for “other,” 

such as materials and supplies. However, group services can include 

activities such as construction of a community rehabilitation program. It is 

not clear what comprises these services. As a result, its input costs were 

assigned entirely to the “other” category. Finally, the last three columns 

multiply the prior columns, and the sum of the columns yields some 

preliminary weights. 

Table 6: Combining Education’s Expenditure Data and Survey Data to Estimate Weights for Inputs 

Input cost proportions (from survey) Input cost weights 

VR expenditure 

categories 

VR expenditure 

breakdown (from 

RSA-2 data) Labor Rents Other Labor Rents Other

Administrative 0.106 0.690 0.056 0.254 0.073 0.006 0.027

Individual services 0.862 0.690 0.056 0.254 0.595 0.048 0.219

Group services 0.032 0.000 0.000 1.000 0.000 0.000 0.032

Total 1.000 0.668 0.054 0.278

Source: GAO analysis of Education’s RSA-2 data and GAO survey. 

Once we obtained the results shown in table 6, we rounded the weights to 

the nearest 5 percent. Ultimately, we estimated the weights to be 0.65 for 

wages, 0.05 for rents, and 0.30 for all other inputs. 

Constructing the Cost 

Index 

We then constructed the index, using the following formula: 

Cost index = 0.65 Wages + 0.05 Rent + 0.30 Other 

Page 41 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

With this formula, we calculated a cost index for each state, using each 

state’s average wage from 2005 to 2007 in the education, healthcare, and 

social assistance sector, according to QCEW data, and its average rental 

cost from fiscal years 2007 to 2009, according to the FMR data. The cost 

for “other” inputs besides wages and rents was assigned a weight of 0.30 

and assumed to be constant for all states. We made this assumption to 

simplify the construction of the cost index because we were unable to 

readily or reliably capture differences in the costs of these inputs among 

states. As noted earlier, estimating these costs would be difficult because 

identifying the various materials and supplies used to provide the wide 

variety of VR services would be costly and labor-intensive. In addition, it is 

unlikely that there would be nationally available data on the costs of any 

materials or supplies we could identify. The assumption that the cost of 

“other” inputs is the same across states may be reasonable because some 

materials and supplies are likely to be purchased by state VR agencies 

from a national market and, therefore, the geographical variation in these 

costs would be limited. 

Figure 7 shows the distribution of the cost index. If a state’s cost index is 

1, its costs are estimated to be the same as the national average. If a state’s 

index is greater than 1, its costs are estimated to be above the national 

average. Finally, if a state’s index is less than 1, its costs are estimated to 

be below the national average. Values for 36 of the states lie between 0.9 

and 1.1. See appendix IV for a listing of the cost index for each state. 

Page 42 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

Figure 7: Distribution of the Cost of Services Index 

Number of states

Source: GAO analysis of data from Education, BLS, HUD, and responses to GAO survey.

Cost of services index

0

5

10

15

20

25

0.75 0.85 0.90 1.00 1.10 1.15 1.25 1.65

We had our work on the cost of services index reviewed by three external 

experts in the disability field. They generally concurred with our 

methodology for developing the cost index using existing data. However, 

each noted that our index does not capture certain key inputs or costs 

underlying the provision of VR services, such as higher education, 

transportation, contracted services, and tax rates. We generally agree that 

it would be preferable to reflect all key cost differences that affect the 

provision of VR services; however, to do so requires reliable data from VR 

agencies (to determine average costs and develop weights for each input), 

and from independent sources (to estimate cost differences for those 

inputs among states). Either one or the other, or both, were not readily 

available. For example, with respect to transportation costs, data were not 

readily available from VR agencies that would allow us to develop average 

costs and weights, and we are not aware of independent data on 

Page 43 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

transportation cost differences among states.8 Similarly, data were not 

readily available from VR agencies to identify the specific services that 

agencies contracted for and to determine the inputs that are used to 

provide those services. Finally, one of the experts noted that high tax rates 

in certain states may result in higher wages and rents, and suggested we 

incorporate states’ tax rates into our cost index. We agree that tax rates 

may influence wages and rents; however, research suggests that many 

factors affect state differences in wages and rents, and determining the 

relative significance of state tax rates would be a highly complex 

analytical undertaking. In summary, although data were not readily 

available to reliably reflect cost differences for additional inputs suggested 

by our experts, these experts generally agreed that we appropriately 

accounted for cost differences in two basic inputs, i.e., wages and rents. 

A taxpayer equity standard stipulates that funds are distributed so that 

states can provide individuals comparable services using both state and 

federal funds, while each state contributes about the same proportion of 

their resources to a given federal program. This equity standard requires a 

formula to include an indicator of each state’s ability to finance a given 

program from its own sources. In a funding formula, a good indicator of a 

state’s financing ability would measure all types of taxable resources and 

would not be affected by an individual state’s actual fiscal decisions. 

Measuring State 

Financing Capacity 

We used Total Taxable Resources (TTR), as reported by Treasury, to 

measure state resources. The Treasury, as required by federal law, 

provides annual estimates of TTR in order to estimate states’ financing 

ability. The estimates are used in formulas to allocate federal funds among 

 

8

Some of the experts also suggested that we include states’ postsecondary education costs 

in our cost index. Although VR agencies track education expenditures that would allow us 

to develop weights, and data are available on states’ postsecondary education costs (such 

as average tuition and fees), we did not include the data in our cost index for two main 

reasons. First, due to the availability of financial aid, we could not readily determine the 

extent to which these data would reflect actual costs incurred by state VR agencies. 

Second, costs of public higher education institutions are, in part, determined by states’ 

funding decisions, and as a result, including these costs in our index may reward or 

penalize states based upon their fiscal decisions. Although we did not directly account for 

cost differences in higher education, the wage data we used for the education, healthcare, 

and social assistance industry may partly capture differences in education costs because it 

includes workers in education industries. 

Page 44 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

states for the Community Mental Health Services and the Substance Abuse 

Prevention and Treatment block grants. TTR is a more comprehensive 

measure of financing ability than per capita income because it includes 

personal income received by state residents, types of corporate income 

and capital gains that per capita excludes, as well as income produced 

within a state that is received by individuals who reside out-of-state. 

For our first objective, we reported state-level information on the 

proportion of the population of working age with a disability, allotments 

per person with a disability (adjusting for costs), and ratio of per capita 

income to total taxable resources. In addition, we analyzed the extent to 

which state per capita income is correlated with state disability rates in 

order to determine whether the current use of per capita income in the 

funding formula adequately accounts for a state’s need population. Finally, 

we examined whether agencies in states with below median levels of 

funding per person with a disability were more often on an order of 

selection, compared to states above the median. For each of the above 

analyses, we examined only the 50 states and the District of Columbia. We 

did not analyze the U.S. territories because complete data were not 

available on the territories from the various data series we used. This 

section describes each of the analyses we conducted for our first 

objective. 

Analysis of the Extent 

to which the Current 

Formula Meets Equity 

Standards 

Proportion of states’ population that is civilian, of working age, and 

with a disability: To determine the proportion of each state’s general 

population that is civilian, of working age, and has a disability, we 

analyzed 2007 ACS data to obtain the number of civilians in each state 

from age 16 to 64 who responded “yes” to at least one of five disability 

questions. As discussed above, we did not include individuals who 

responded “yes” to the question on difficulty working because this 

question was eliminated from the ACS, starting in 2008. We then divided 

the working-aged disability population numbers by the total population 

(all ages) for each state, which we also obtained from the 2007 ACS. These 

proportions are presented in appendix III. 

Correlation between states’ disability populations and their per capita 

income: To test whether the formula’s use of per capita income is a 

reasonable proxy for states’ disability rates, we analyzed the correlation 

between their disability rates and their “allotment percentage,” which is 

the part of the formula that includes per capita income. As discussed 

above, we determined a state’s disability rate as the proportion of a state’s 

total population that is civilian, of working age, and has a disability. For 

Page 45 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

the per capita income factor, we calculated each state’s “allotment 

percentage,” which according to the formula, is one minus one-half of a 

state’s per capita income level divided by the national per capita income 

level (see appendix II for a further explanation of the allotment 

percentage). We then obtained the correlation coefficient between states’ 

disability rates and their allotment percentages. 

Allotments per working-aged person with a disability (cost-adjusted):

To determine for each state the allotment per working-aged person with a 

disability, as adjusted for the costs of providing services, we used 

Education data on the VR grant allotments that states received in fiscal 

year 2008, ACS data on state disability populations in 2007 (using the five 

disability questions, as described earlier), and the cost index, as described 

earlier. Specifically, we used the allotments that Education initially 

calculated for each state for fiscal year 2008.9

 To calculate the allotments 

per working-aged person with a disability while adjusting for costs, we 

divided each state’s grant allotment by the product of the cost index and 

the state’s 2007 working-aged disability populations. See appendix V for a 

state-by-state listing of allotments per working-aged person with a 

disability, as adjusted for costs of services. 

We tested the reliability of Education’s data on VR grant allotments by 

replicating Education’s formula calculations and interviewing Education 

officials knowledgeable about the data. Our replications of the formula 

calculations produced results that were virtually identical to Education’s. 

As a result, we determined that the data are sufficiently reliable for our 

purposes. 

Order of Selection Status: We examined whether agencies in those states 

with below median allotments per working-aged person with a disability 

(adjusting for costs) more often reported being under an order of selection 

than those states whose allotments were above the median.10 To obtain 

information on states’ order of selection status, we used Education’s RSA-

 

9

The allotments data we used did not include any adjustments made to states’ allotments at 

the end of the fiscal year, such as funds that state agencies returned because they could not 

fully match them or additional funds that agencies received through the reallotment 

process. 

10The state with the median allotment per working-aged person with a disability, adjusted 

for costs (Arizona) was excluded from the analysis so that our analysis was specifically of 

the 25 states (including the District of Columbia) above the median and the 25 states below 

it. 

Page 46 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

113 data, which are quarterly data that states submit on their caseloads. 

For states with two VR agencies, we considered a state to be under an 

order of selection if either of its agencies reported being under an order of 

selection. Table 7 shows the number of states that we considered under an 

order of selection, by type of VR agency. 

Table 7: Number of States Considered to Be Under Order of Selection by Type of 

VR Agency 

States with one VR agency (combined) under order of selection 16

States with two VR agencies, both general and blind agencies 

under order of selection 4

States with two VR agencies, only general agency under order of 

selection 10

States with two VR agencies, only blind agency under order of 

selection 1

Total states with an agency under order of selection 31

Source: GAO analysis of Education data. 

We assessed the reliability of RSA-113 data by interviewing Education 

officials knowledgeable about the data and conducting edit checks. 

Education officials informed us that when a state agency reports being 

under an order of selection, the Department verifies that the state agency 

has documented in its state plan its intention to provide services on an 

“order of selection” basis. However, Education officials also informed us 

that the RSA-113 data on a state’s order of selection status do not 

necessarily indicate whether state agencies are currently operating on this 

basis by actively limiting services to individuals. For example, they noted, 

and we subsequently confirmed through our own review of the data, that 

some states reported being under an order of selection, but reported 

having no individuals on a waiting list. As a result, we determined that the 

RSA-113 data on order of selection was sufficiently reliable to provide 

information on the number of states reporting they were on an order of 

selection, but we cannot say whether these states were actually operating 

under their order. Our analysis also did not allow us to conclude whether 

there is any causal link between states’ funding levels and their order of 

selection status. 

Comparison of per capita income and total taxable resources: We 

analyzed how per capita income compares with TTR in each state. To do 

this, we obtained data on per capita income from the Department of 

Commerce and TTR data from Treasury from 2004 to 2006, the latest years 

for which data from both sources were available. We took 3-year averages 

Page 47 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

(2004, 2005, and 2006) of the per capita income and total taxable resources 

levels for each state in order to limit the effects of any year-to-year 

fluctuations. We then calculated the total taxable resources per capita for 

each state by dividing the average total taxable resource amount by the 

state’s average population from 2004 to 2006. Next, we created indices by 

dividing each state’s per capita income and total taxable resources per 

capita by the U.S. averages of per capita income and total taxable 

resources per capita, respectively. To compare states’ per capita income 

with their total taxable resources, we divided each state’s per capita 

income index by its index of total taxable resources per person to obtain 

ratios. See appendix VI for a state-by-state listing of indices of per capita 

income and total taxable resources per capita, as well as their ratios. 

For our second objective, we developed three formula options based upon 

equity standards commonly used to design and evaluate funding formulas. 

See appendix VII for detailed descriptions of the formula options. We also 

estimated the grant allotments that each state would receive under each 

formula option, using data on states’ disability populations from the ACS, 

our cost index, and TTR data from Treasury. See appendix VIII for a table 

of our estimates of the grant allotments. Specifically, we used for states’ 

need populations, the average of their 2006 and 2007 populations of people 

of working age with a disability in order to limit the effects of any year-toyear fluctuations. As described above, we used the five disability questions 

from the ACS. As a measure of cost of services, we used the cost index 

that we developed, also described above. As a measure of state resources, 

we used the average of states’ total taxable resources from 2004 to 2006. 

We conducted a Web-based survey of VR agencies in states, territories, 

and the District of Columbia to gather information on agency officials’ 

opinions regarding the current formula, potential modifications to the 

formula, and the incorporation of performance incentives into the formula. 

In addition, we used the survey to obtain data on agency expenditures that 

we needed to develop our cost index. The Web-based survey was 

conducted using a self-administered electronic questionnaire posted on 

the Web. This Web-based survey was compatible with computer software 

that makes Web sites accessible to people with visual impairments. We 

received completed surveys from 74 of 80 VR agencies, for a response rate 

of 93 percent. 

Analysis of Formula 

Options 

Survey of State VR 

Agencies 

We took steps in the development of the questionnaire, the data collection, 

and the data analysis to minimize nonsampling errors. The practical 

Page 48 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

difficulties of conducting any survey may introduce errors, commonly 

referred to as nonsampling errors. For example, difficulties in how a 

particular question is interpreted, in the sources of information that are 

available to respondents, or in how the data are entered into a database or 

were analyzed can all introduce unwanted variability into survey results. 

To minimize such nonsampling errors, a social science survey specialist 

designed the initial questionnaire, in collaboration with GAO staff who had 

subject matter expertise. The draft questionnaire was pretested with 

officials from 5 state VR agencies to ensure that the questions were 

relevant, clearly stated, and easy to comprehend. When the data were 

analyzed, an independent analyst checked all answers using a statistical 

program. Since the survey was a Web-based survey, respondents entered 

their answers directly into the electronic questionnaire, thereby 

eliminating the need to have the data keyed into a database and avoiding 

data entry errors. See appendix IX for selected responses to our survey. 

To learn more about state agency officials’ opinions on all three of our 

research objectives, we spoke with VR agency officials from 3 states when 

we designed our methodology and we followed our survey work by 

interviewing officials from 8 agencies in 6 states. In selecting these 8 

agencies, we identified states with a diversity of characteristics in terms of 

their: (1) disability population rates; (2) per capita income levels; (3) 

geographic dispersion; and (4) order of selection status. In addition, we 

sought to interview both state agencies that serve individuals with a wide 

variety of disabilities and agencies that primarily serve blind individuals. In 

5 states, we also spoke with representatives from the state rehabilitation 

councils, which are advisory councils for state VR agencies. 

Interviews with 

Experts and Agency 

Officials 

We also spoke with officials from: (1) Education’s Rehabilitation Services 

Administration to obtain relevant programmatic data and perspectives on 

the VR program; (2) SSA regarding data on the population receiving Social 

Security disability benefits; (3) the Census Bureau regarding ACS disability 

data; (4) BLS regarding data on wages; and, (5) the Department of 

Transportation regarding the use of Census data on disability that was 

used in a formula to distribute funds for the Department’s New Freedom 

program. 

In addition, we conducted about a dozen interviews with researchers 

having expertise in disability data and the VR program and with advocacy 

groups. We also attended the fall 2008 conference of the Council of State 

Administrators of Vocational Rehabilitation (CSAVR) to learn more about 

matters of interest to VR stakeholders and to obtain the views of the 

Page 49 GAO-09-798 Vocational Rehabilitation
Appendix I: Objectives, Scope, & Methodology 

council’s executive committee members. Also, we spoke with 

representatives from four private sector companies that provide 

vocational rehabilitation services, in order to learn about their experiences 

with performance incentives in the private sector. We chose these four 

companies based on the recommendations of a trade organization official 

familiar with the fields of disability insurance and private vocational 

rehabilitation. 

To identify issues to consider when incorporating performance incentives 

into the VR formula, we reviewed literature produced by academic 

experts, think tanks, and government agencies such as the Congressional 

Research Service. We also reviewed prior GAO studies dealing with 

performance accountability in government programs.11 We identified 

relevant literature by reviewing research databases, such as EconLit and 

the Education Resources Information Center (ERIC). We were also 

referred to literature through citations in other literature and by the 

recommendations of GAO staff and the external experts we interviewed. 

In conducting our search and review, we endeavored to collect a diverse 

body of literature that offered different views about the use of incentive 

awards. 

Review of Literature 

on Performance 

Incentives 

Aside from conducting a general review of literature on performance 

incentives, we also identified and reviewed literature specific to four 

federal programs in order to understand their experiences and identify 

issues related to providing incentive awards. These programs are the 

Workforce Investment Act (WIA), Child Support Enforcement (CSE), 

Public Housing Capital Fund, and the Job Training Partnership Act (JTPA) 

programs. The latter was discontinued and replaced by WIA Title IB 

programs, authorized in 1998. We also obtained the views of federal 

officials in the Departments of Labor, Health and Human Services, and 

HUD, which are responsible, respectively, for the WIA, CSE, and Capital 

Fund programs. 

 

11GAO, Grants Management: Enhancing Performance Accountability Provisions Could 

Lead to Better Results, GAO-06-1046 (Washington D.C.: Sept. 26, 2006). 

Page 50 GAO-09-798 Vocational Rehabilitation
Appendix II: De

Vocatio

Formula 

scription of the Current 

nal Rehabilitation (VR) Funding 

Page 51 GAO-09-798 

Appendix II: Description of the Current 

Vocational Rehabilitation (VR) Funding 

Formula 

The current VR funding formula allocates federal funds to states annually, 

based on three factors: (1) the amount of federal funds they received for 

their VR program for fiscal year 1978, (2) their population size, and (3) 

their per capita income level, as compared with the national per capita 

income. 

States’ fiscal year 1978 allotments became part of the formula when it was 

revised through a 1978 amendment to the Rehabilitation Act.1

 This 

provision ensured that no state experienced a funding decrease with the 

formula change. As currently constructed, the formula first provides states 

with the amount of federal funds that they were allotted for their VR 

program in fiscal year 1978. 

The remaining funds appropriated for the VR program are then distributed 

based on a state’s population and its “allotment percentage.” The allotment 

percentage is calculated using the ratio of a state’s per capita income to 

the national per capita income, according to the following formula: 

Allotment percentage = 1 - 0.50 x State per capita income 

U.S. per capita income 

The allotment percentage is designed to be higher for poorer states. For 

example, a state that has a per capita income level equal to the national 

level will have an allotment percentage of 0.50. If a state’s per capita 

income is lower than the national level, its allotment percentage will be 

above 0.50. If a state’s per capita income is higher than the national level, 

its allotment percentage will be lower than 0.50. However, to mitigate the 

influence of per capita income for states with very high or very low per 

capita income levels, the Rehabilitation Act sets both a floor and a ceiling 

on the allotment percentage—it cannot be less than 33 1/3 percent or 

greater than 75 percent. Further, the allotment percentage is set at 75 

percent for U.S. territories and the District of Columbia. Federal law 

requires the Department of Education (Education) to calculate the 

allotment percentages in even-numbered years, using the average of the 

three most recent years of available data on per capita income. Education 

 

1

Prior to 1978, funds were allotted based upon states’ populations and the square of its 

allotment percentage. 

 Vocational Rehabilitation 
Appendix II: Description of the Current 

Vocational Rehabilitation (VR) Funding 

Formula 

obtains the data from the Department of Commerce’s Bureau of Economic 

Analysis. 

The portion of the formula used to distribute funds after each state is 

allocated its 1978 allotment allocates half of the remaining funds based 

upon a state’s population and allotment percentage, and the other half 

based upon its population and the square of its allotment percentage. The 

squaring of the allotment percentage magnifies its effect. Education is 

required to determine state populations annually, using the most recently 

available data from the Department of Commerce. The following is the 

formula for calculating states’ funding allotments: 

(Population x Allotment percentage)

(Population x Allotment percentage)

x

x Excess amount

(Population x Allotment percentage2)

(Population x Allotment percentage2)

Allotment = FY1978 Allotment 

∑

∑

+

+

where:

Excess amount = FYAppropriation - ∑FY1978 Allotments

2

Excess amount

2

Finally, the Rehabilitation Act also stipulates a minimum level of funding 

for each state. Specifically, no state may receive less than $3 million or 1/3 

of 1 percent of the total federal funds appropriated to the VR program that 

fiscal year, whichever is greater.2

 If a state’s allotment is calculated to fall 

below this amount, its allotment is increased to that level, and the 

allotments of other states are decreased proportionately. 

 

2

This minimum allotment does not apply to the U.S. territories, but it does apply to the 

District of Columbia. 

Page 52 GAO-09-798 Vocational Rehabilitation
Appendix III: Percentage of Population that 

Is Civilian Working Age with a Disability, 

2006 and 2007 

Table 8 below shows the proportion of each state’s total population that is 

civilian, of working age (16 to 64), and with a disability. See appendix I for 

further information on our data source and methodology for determining 

these proportions. 

Table 8: Percentage of Population that Is Civilian Working Age with a Disability, 

2006 and 2007 

State 2006 2007

Alabama 10.8 11.1

Alaska 9.2 9.3

Arizona 6.7 6.8

Arkansas 11.3 11.1

California 6.4 6.5

Colorado 6.9 6.7

Connecticut 6.3 6.3

Delaware 7.5 7.2

District of Columbia 7.1 7.5

Florida 7.5 6.9

Georgia 7.7 7.5

Hawaii 5.8 6.1

Idaho 8.0 7.4

Illinois 6.2 6.1

Indiana 7.8 8.1

Iowa 7.0 7.3

Kansas 7.4 7.1

Kentucky 12.0 11.4

Louisiana 9.9 9.6

Maine 10.5 10.6

Maryland 6.4 6.6

Massachusetts 6.8 6.9

Michigan 8.5 8.5

Minnesota 6.1 6.3

Mississippi 11.1 10.9

Missouri 8.8 8.9

Montana 9.3 8.0

Nebraska 6.8 6.3

Nevada 6.3 6.4

New Hampshire 7.4 6.9

Appendix III: Percentage of Population that 

Is Civilian Working Age with a Disability, 2006 

and 2007 

Page 53 GAO-09-798 Vocational Rehabilitation 
Appendix III: Percentage of Population that 

Is Civilian Working Age with a Disability, 

2006 and 2007 

State 2006 2007

New Jersey 5.8 5.6

New Mexico 8.8 8.7

New York 6.7 7.0

North Carolina 8.7 8.7

North Dakota 6.8 6.0

Ohio 8.3 8.4

Oklahoma 10.4 10.1

Oregon 8.7 8.5

Pennsylvania 8.0 8.1

Rhode Island 7.9 8.1

South Carolina 9.1 8.7

South Dakota 6.4 7.5

Tennessee 10.2 10.0

Texas 7.7 7.4

Utah 6.3 6.1

Vermont 9.5 8.2

Virginia 7.2 6.8

Washington 8.6 8.5

West Virginia 12.7 12.8

Wisconsin 6.7 6.9

Wyoming 8.3 8.1

National 7.7 7.6

Source: GAO analysis of data from the Census Bureau’s ACS. 

Note: Our measure of state disability populations is derived from five disability questions asked in the 

2006 and 2007 ACS. See table 2 in appendix I for the disability questions on the ACS. We did not 

include data from a sixth disability question—about whether a person has difficulty working at a job or 

business because of a physical, mental, or emotional condition lasting six months or more—because 

this question was no longer included in the ACS, starting in 2008. 

Page 54 GAO-09-798 Vocational Rehabilitation
Appendix IV: Estimates of Differences among 

States in the Cost of Providing Vocational 

Rehabilitation (VR) Services 

Table 9 provides a cost index for each state, designed to estimate the 

differences among states in the cost of providing VR services. The index is 

a weighted average of the costs of two primary resources needed to 

provide VR services, labor and office space. See appendix I for further 

information on the development of our cost index. The average cost 

nationally is represented by an index of 1.00. A state with an index above 

1.00 is estimated to have costs greater than average, while a state with an 

index below 1.00 is estimated to have costs less than average. For 

example, with a cost index of 0.95, Alabama is estimated to have costs 5 

percent below the national average. 

Table 9: Estimates of Differences among States in the Cost of Providing VR 

Services 

State Cost index

Alabama 0.95

Alaska 0.98

Arizona 1.04

Arkansas 0.88

California 1.12

Colorado 1.01

Connecticut 1.09

Delaware 1.07

District of Columbia 1.19

Florida 1.02

Georgia 1.01

Hawaii 1.03

Idaho 0.87

Illinois 1.01

Indiana 0.94

Iowa 0.88

Kansas 0.89

Kentucky 0.93

Louisiana 0.89

Maine 0.93

Maryland 1.06

Massachusetts 1.13

Michigan 0.98

Minnesota 0.99

Mississippi 0.90

Appendix IV: Estimates of Differences among 

States in the Cost of Providing Vocational 

Rehabilitation (VR) Services 

Page 55 GAO-09-798 Vocational Rehabilitation 
Appendix IV: Estimates of Differences among 

States in the Cost of Providing Vocational 

Rehabilitation (VR) Services 

State Cost index

Missouri 0.95

Montana 0.87

Nebraska 0.93

Nevada 1.10

New Hampshire 1.04

New Jersey 1.09

New Mexico 0.89

New York 1.04

North Carolina 0.93

North Dakota 0.89

Ohio 0.94

Oklahoma 0.88

Oregon 0.98

Pennsylvania 1.00

Rhode Island 0.99

South Carolina 0.93

South Dakota 0.92

Tennessee 1.01

Texas 0.96

Utah 0.91

Vermont 0.92

Virginia 1.00

Washington 0.97

West Virginia 0.88

Wisconsin 0.97

Wyoming 0.89

National average 1.00

Source: GAO analysis of BLS’ Quarterly Census of Employment and Wages, HUD data on fair market rents, Education data on VR 

expenditures, and responses to GAO survey. 

Page 56 GAO-09-798 Vocational Rehabilitation
Appendix V: Vocational Rehabilitation (VR) 

Grant Allotments by State and Cost-Adjusted 

Allotments per Working-Aged Person with a 

Disability, Fiscal Year 2008 

Page 57 GAO-09-798 Vocational Rehabilitation 

Table 10 shows the amount of federal funds each state received for fiscal 

year 2008, and the amount of services each state would be able to 

purchase per working-aged person with a disability with those funds. The 

per person allotments were adjusted to take into account differences 

among states in the cost of wages and rents, using the cost index shown in 

appendix IV. See appendix I for more information about our data sources 

and methodologies. 

Table 10: VR Grant Allotments and Cost-Adjusted Allotments per Working-Aged 

Person with a Disability 

State 

FY 2008 

grant allotmenta

Allotments per working-aged 

person with a disability (cost 

adjusted)b

Alabama 55,816,789 114 

Alaska 9,463,837 153

Arizona 57,950,200 128

Arkansas 35,809,204 130 

California 275,593,209 104

Colorado 36,013,729 109

Connecticut 19,947,115 83

Delaware 9,463,837 141

District of Columbia 12,618,252 240

Florida 152,844,034 119

Georgia 92,258,790 127

Hawaii 11,052,823 138

Idaho 15,867,655 165

Illinois 105,254,070 133

Indiana 66,660,094 139

Iowa 31,155,664 162

Kansas 26,929,144 154

Kentucky 51,743,094 114

Louisiana 56,383,213 154

Maine 15,030,202 116

Maryland 38,114,000 97

Massachusetts 45,530,340 90

Michigan 97,347,491 115

Minnesota 43,124,084 133

Mississippi 41,288,450 144

Missouri 62,037,506 125

Appendix V: Vocational Rehabilitation (VR) Grant 

Allotments by State and Cost-Adjusted Allotments per 

Working-Aged Person with a Disability, Fiscal Year 2008 
Appendix V: Vocational Rehabilitation (VR) 

Grant Allotments by State and Cost-Adjusted 

Allotments per Working-Aged Person with a 

Disability, Fiscal Year 2008 

Page 58 GAO-09-798 Vocational Rehabilitation 

State 

FY 2008 

grant allotmenta

Allotments per working-aged 

person with a disability (cost 

adjusted)b

Montana 10,762,027 161

Nebraska 17,356,124 167

Nevada 17,931,565 99

New Hampshire 10,736,013 114

New Jersey 55,184,632 104

New Mexico 22,684,862 149

New York 147,351,564 105

North Carolina 92,812,979 126

North Dakota 9,463,837 277

Ohio 120,400,886 133

Oklahoma 40,628,883 126

Oregon 35,175,174 113

Pennsylvania 121,101,676 122

Rhode Island 10,051,281 118

South Carolina 50,734,708 143

South Dakota 9,463,837 174

Tennessee 65,575,720 106

Texas 217,749,584 129

Utah 28,030,439 191

Vermont 9,463,837 202

Virginia 62,084,119 118

Washington 51,125,448 97

West Virginia 25,312,666 125

Wisconsin 55,246,877 148

Wyoming 9,463,837 250

Source: GAO analysis of data from Education on VR grants in fiscal year 2008, Census Bureau’s 2007 ACS, BLS’ Quarterly Census of 

Employment and Wages, HUD’s Fair Market Rents, and responses to GAO survey. 

a

Grant allotments listed are the initial allotments distributed to states using the funding formula. The 

allotments do not include any adjustments that occur due to states’ inability to match federal funds or 

the application of maintenance of effort penalties. 

b

The denominator in these calculations is the state’s civilian working-aged population with a disability, 

according to data from the 2007 ACS. 
Appendix VI: Comparison of Per Capita 

Income and Total Taxable Resources (TTR), 

by State, 2004 to 2006 

Table 11 illustrates the difference between each state’s financial resources 

as measured by per capita income and TTR. The second column shows, 

for each state, its per capita income indexed to national per capita income, 

and the third column shows each state’s TTR per capita indexed to 

national TTR per capita. These indices are based on averages of three 

years of data from 2004 to 2006. They were created by dividing each state’s 

three-year average by the national average. States with income or TTR per 

capita levels that are higher than the national averages have indices that 

are greater than 1, and states with levels that are below the national 

averages have indices that are less than 1. For example, the TTR per capita 

index for Alabama is 0.79, meaning that the state’s TTR per capita is 21 

percent below the national average. The final column in the table shows 

the ratio of each state’s per capita income index to its TTR per capita 

index. States in which the formula’s use of per capita income understates 

its potentially taxable resources have ratios that are less than 1. States in 

which the use of per capita income overstates its potentially taxable 

resources have ratios above 1. For example, the ratio is 0.80 for Alaska, 

meaning that the formula’s use of per capita income understates Alaska’s 

taxable resources by 20 percent. See appendix I for further information 

regarding our analysis of per capita income and TTR. 

Table 11: Comparison of Per Capita Income and TTR Per Capita for 2004 to 2006, by 

State 

State 

Index of per capita 

income 

Index of TTR per 

capita 

Ratio of per capita 

income index to TTR 

per capita indexa

Alabama 0.84 0.79 1.07

Alaska 1.04 1.30 0.80

Arizona 0.88 0.87 1.00

Arkansas 0.78 0.74 1.04

California 1.08 1.07 1.01

Colorado 1.08 1.08 1.00

Connecticut 1.39 1.42 0.98

Delaware 1.06 1.59 0.67

District of 

Columbia 

1.57 1.71 0.92

Florida 1.00 1.00 1.00

Georgia 0.89 0.91 0.98

Hawaii 1.00 1.01 0.99

Idaho 0.83 0.80 1.03

Illinois 1.05 1.05 1.01

Appendix VI: Comparison of Per Capita 

Income and Total Taxable Resources (TTR), 

by State, 2004 to 2006 

Page 59 GAO-09-798 Vocational Rehabilitation 
Appendix VI: Comparison of Per Capita 

Income and Total Taxable Resources (TTR), 

by State, 2004 to 2006 

State 

Index of per capita 

income 

Index of TTR per 

capita 

Ratio of per capita 

income index to TTR 

per capita indexa

Indiana 0.88 0.89 1.00

Iowa 0.91 0.93 0.97

Kansas 0.93 0.93 1.00

Kentucky 0.81 0.79 1.03

Louisiana 0.81 0.94 0.86

Maine 0.89 0.83 1.08

Maryland 1.20 1.17 1.03

Massachusetts 1.25 1.20 1.05

Michigan 0.93 0.85 1.09

Minnesota 1.07 1.07 1.01

Mississippi 0.73 0.68 1.08

Missouri 0.90 0.88 1.02

Montana 0.84 0.79 1.06

Nebraska 0.94 0.96 0.98

Nevada 1.06 1.18 0.90

New Hampshire 1.09 1.08 1.01

New Jersey 1.27 1.27 1.00

New Mexico 0.80 0.83 0.96

New York 1.17 1.19 0.99

North Carolina 0.89 0.94 0.95

North Dakota 0.89 0.90 0.98

Ohio 0.91 0.90 1.02

Oklahoma 0.87 0.82 1.06

Oregon 0.92 0.93 0.98

Pennsylvania 1.00 0.94 1.06

Rhode Island 1.03 1.05 0.98

South Carolina 0.82 0.79 1.04

South Dakota 0.91 0.97 0.94

Tennessee 0.88 0.87 1.02

Texas 0.95 0.98 0.97

Utah 0.79 0.83 0.96

Vermont 0.95 0.91 1.05

Virginia 1.09 1.14 0.96

Washington 1.05 1.05 1.00

West Virginia 0.76 0.72 1.06

Page 60 GAO-09-798 Vocational Rehabilitation
Appendix VI: Comparison of Per Capita 

Income and Total Taxable Resources (TTR), 

by State, 2004 to 2006 

State 

Index of per capita 

income 

Index of TTR per 

capita 

Ratio of per capita 

income index to TTR 

per capita indexa

Wisconsin 0.94 0.92 1.02

Wyoming 1.12 1.34 0.84

Source: GAO analysis based on data from the Department of Commerce and Treasury. 

a

Dividing a state’s index in the second column by its index in the third column may not result in the 

ratio provided in the fourth column due to rounding. 

Page 61 GAO-09-798 Vocational Rehabilitation
Appendix VII: Description of Formula Options 

Page 62 GAO-09-798 

Appendix VII: Description of Formula 

Options 

This appendix provides detailed information on three formula options or 

prototypes for revising the VR funding formula: (1) a partial beneficiary 

equity formula that distributes funds based only on the size of a state’s 

population potentially needing services, (2) a full beneficiary equity 

formula with the addition of a cost of services factor, and (3) a taxpayer 

equity formula with the addition of a measure of state resources. 

The following is the Partial Beneficiary Equity Formula Option: 

State allocation = Appropriation x Need population

∑Need population ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

where:

 • ∑ Need population = sum of the need population across states, or the total need 

 population nationally

This formula would allocate funds based on each state’s share of the total 

need population nationally. It would only partially achieve beneficiary 

equity because it does not account for differences among states in the cost 

of providing services. 

The following is the Full Beneficiary Equity Formula Option: 

State allocation = Appropriation x Cost adjusted need population

∑Cost adjusted need population ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

 where:

 • Cost adjusted need population = Need population x Cost index

 • ∑ Cost adjusted need population = Sum of the cost adjusted need population

 across states

This formula would achieve full beneficiary equity because it accounts for 

both states’ need populations and costs of providing services. The cost 

index in the formula estimates each state’s cost of providing services. 

 Vocational Rehabilitation 
Appendix VII: Description of Formula Options 

The final option is the Taxpayer Equity Formula Option: 

State allocation = Appropriation x Cost adjusted need population x allotment percentage

∑Cost adjusted need population x allotment percentage ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

where:

 • Cost adjusted need population = Need population x Cost index

 • Allotment percentage = 1- 0.20

Need population

TTR

Cost adjusted need population TTR

 

⎟

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎜

⎝

⎛

∑ ∑

This formula would achieve taxpayer equity by basing allotments on a 

state’s need population, adjusted for the cost of providing services, and its 

ability to fund program services. In this option, the formula includes an 

“allotment percentage” to account for a state’s ability to contribute funding 

to the VR program. A state with fewer taxable resources compared to 

other states would have a larger allotment percentage and, therefore, a 

larger final allotment (all else being equal). “TTR” is used to indicate a 

measure of state’s financing ability, since we regard Treasury’s Total 

Taxable Resources (TTR) data to be a comprehensive measure of a state’s 

taxable resources. The 0.20 in the allotment percentage equation indicates 

that, nationally, states’ required contribution to the VR program is 

approximately 20 percent. If the matching requirement were to vary for 

each state, then an individual state’s matching rate would simply be 

determined by its allotment percentage. 

Page 63 GAO-09-798 Vocational Rehabilitation
Appendix VIII: Funding Allocations under 

Three Vocational Rehabilitation Formula 

Options 

Table 12 shows the allocations for each state and the percentage change 

from their fiscal year 2008 allocations under the three formula options 

(which are described in detail in appendix VII). For each of these options, 

we retained the minimum allotment that the current formula provides, 1/3 

of 1 percent of the total federal funds appropriated to the VR program, or 

$9,463,837 for fiscal year 2008. 

Table 12: Funding Allocations under Three VR Formula Options 

Funding allocations under each formula option

Percentage change from current formula 

allocations 

State 

Current 

allocationa

(2008) 

Partial 

beneficiary 

equity

Full 

beneficiary 

equity

Taxpayer 

equity

Partial 

beneficiary 

equity 

Full 

beneficiary 

equity

Taxpayer 

equity

Alabama 55,816,789 60,474,140 57,792,826 63,890,152 8.3 3.5 14.5

Alaska 9,463,837 9,463,837 9,463,837 9,463,837 0.0 0.0 0.0

Arizona 57,950,200 50,637,184 53,231,144 54,419,676 -12.6 -8.1 -6.1

Arkansas 35,809,204 37,745,777 33,384,156 36,944,930 5.4 -6.8 3.2

California 275,593,209 281,848,929 316,454,689 306,280,311 2.3 14.8 11.1

Colorado 36,013,729 39,237,548 39,789,523 38,041,490 9.0 10.5 5.6

Connecticut 19,947,115 26,435,688 29,061,990 24,834,700 32.5 45.7 24.5

Delaware 9,463,837 9,463,837 9,463,837 9,463,837 0.0 0.0 0.0

District of 

Columbia 12,618,252 9,463,837 9,463,837 9,463,837 -25.0 -25.0 -25.0

Florida 152,844,034 155,945,283 159,610,063 158,513,829 2.0 4.4 3.7

Georgia 92,258,790 85,813,700 87,120,651 89,613,060 -7.0 -5.6 -2.9

Hawaii 11,052,823 9,463,837 9,463,837 9,463,837 -14.4 -14.4 -14.4

Idaho 15,867,655 13,590,279 11,904,099 12,214,799 -14.4 -25.0 -23.0

Illinois 105,254,070 94,868,688 96,486,772 89,701,873 -9.9 -8.3 -14.8

Indiana 66,660,094 59,852,987 56,580,945 57,833,670 -10.2 -15.1 -13.2

Iowa 31,155,664 25,509,633 22,527,433 21,748,645 -18.1 -27.7 -30.2

Kansas 26,929,144 23,901,732 21,497,454 20,923,115 -11.2 -20.2 -22.3

Kentucky 51,743,094 59,192,108 55,614,304 61,905,089 14.4 7.5 19.6

Louisiana 56,383,213 49,964,835 44,807,381 46,381,939 -11.4 -20.5 -17.7

Maine 15,030,202 16,621,731 15,516,400 16,878,542 10.6 3.2 12.3

Maryland 38,114,000 43,538,487 46,623,678 43,151,763 14.2 22.3 13.2

Massachusetts 45,530,340 52,850,766 60,263,074 57,419,144 16.1 32.4 26.1

Michigan 97,347,491 102,640,869 101,655,273 107,105,165 5.4 4.4 10.0

Minnesota 43,124,084 38,337,539 38,187,943 35,046,524 -11.1 -11.5 -18.7

Mississippi 41,288,450 38,318,781 34,709,706 38,861,081 -7.2 -15.9 -5.9

Appendix VIII: Funding Allocations under 

Three Vocational Rehabilitation Formula 

Options 

Page 64 GAO-09-798 Vocational Rehabilitation 
Appendix VIII: Funding Allocations under 

Three Vocational Rehabilitation Formula 

Options 

Funding allocations under each formula option

Percentage change from current formula 

allocations 

State 

Current 

allocationa

(2008) 

 Partial 

beneficiary 

equity

Full 

beneficiary 

equity

Taxpayer 

equity

Partial 

beneficiary 

equity 

Full 

beneficiary 

equity

Taxpayer 

equity

Missouri 62,037,506 62,009,758 59,133,917 62,083,180 0.0 -4.7 0.1

Montana 10,762,027 9,819,094 9,463,837 9,463,837 -8.8 -12.1 -12.1

Nebraska 17,356,124 13,861,787 12,978,945 12,302,501 -20.1 -25.2 -29.1

Nevada 17,931,565 19,284,243 21,323,149 20,057,472 7.5 18.9 11.9

New 

Hampshire 10,736,013 11,253,039 11,765,675 11,439,120 4.8 9.6 6.6

New Jersey 55,184,632 59,366,303 65,132,995 55,977,949 7.6 18.0 1.4

New Mexico 22,684,862 20,433,059 18,374,225 19,274,803 -9.9 -19.0 -15.0

New York 147,351,564 158,395,726 165,414,325 153,342,264 7.5 12.3 4.1

North Carolina 92,812,979 93,532,116 87,623,917 90,647,005 0.8 -5.6 -2.3

North Dakota 9,463,837 9,463,837 9,463,837 9,463,837 0.0 0.0 0.0

Ohio 120,400,886 114,324,378 107,741,843 110,803,992 -5.1 -10.5 -8.0

Oklahoma 40,628,883 44,144,467 39,257,904 42,324,327 8.7 -3.4 4.2

Oregon 35,175,174 38,181,743 37,519,882 39,024,885 8.6 6.7 10.9

Pennsylvania 121,101,676 118,988,284 119,170,356 121,867,201 -1.8 -1.6 0.6

Rhode Island 10,051,281 10,186,243 10,174,087 10,128,252 1.3 1.2 0.8

South Carolina 50,734,708 46,262,110 43,300,526 46,345,994 -8.8 -14.7 -8.7

South Dakota 9,463,837 9,463,837 9,463,837 9,463,837 0.0 0.0 0.0

Tennessee 65,575,720 73,518,535 74,726,613 81,366,285 12.1 14.0 24.1

Texas 217,749,584 212,890,595 205,105,733 204,243,635 -2.2 -5.8 -6.2

Utah 28,030,439 19,126,893 17,574,143 17,143,931 -31.8 -37.3 -38.8

Vermont 9,463,837 9,463,837 9,463,837 9,463,837 0.0 0.0 0.0

Virginia 62,084,119 64,168,621 64,512,140 60,687,435 3.4 3.9 -2.2

Washington 51,125,448 65,447,069 63,657,218 64,260,364 28.0 24.5 25.7

West Virginia 25,312,666 27,640,419 24,406,947 27,506,549 9.2 -3.6 8.7

Wisconsin 55,246,877 45,317,537 44,300,827 43,478,226 -18.0 -19.8 -21.3

Wyoming 9,463,837 9,463,837 9,463,837 9,463,837 0.0 0.0 0.0

Total 2,761,189,401 2,761,189,401 2,761,186,401 2,761,189,401 

Source: GAO analysis of Education data on VR grants in fiscal year 2008, Census Bureau’s 2006 and 2007 ACS, BLS’ Quarterly 

Census of Employment and Wages, HUD data on fair market rents, Treasury data on total taxable resources, and responses to GAO 

survey. 

a

These funding allocations are based on the initial allocations distributed to states using the funding 

formula. The allocations do not include any adjustments that occur due to states’ inability to match 

federal funds or the application of maintenance of effort penalties. 

Page 65 GAO-09-798 Vocational Rehabilitation
Appendix IX: Responses to Selected 

Questions from GAO Survey of State Appendix IX: Responses to Selected Vocational Rehabilitation (VR) Agencies 

Questions from GAO Survey of State 

Vocational Rehabilitation (VR) Agencies 

As part of our study, we distributed a Web-based survey to all 80 VR 

agencies in the states, territories, and District of Columbia to obtain 

agency officials’ views regarding the current formula, potential 

modifications to the formula, and the possibility of incorporating 

performance incentives into the formula. In addition, we used the survey 

to obtain data on agency expenditures that were needed to develop our 

cost index. We received completed surveys from 74 of 80 VR agencies, for 

a response rate of 93 percent. The following figures show responses to all 

closed-ended questions, except for those questions concerning agency 

expenditures, which are discussed in appendix I. For more information 

about our methodology for designing and distributing the survey, see 

appendix I. 

Page 66 GAO-09-798 Vocational Rehabilitation 
Appendix IX: Responses to Selected 

Questions from GAO Survey of State 

Vocational Rehabilitation (VR) Agencies 

Figure 8: State Agency Officials’ Opinions about the Appropriateness or Inappropriateness of Factors Currently Included in 

the Funding Formula 

Percentage based on response from 74 VR agencies

The funding formula as a whole

The state’s general population

The state’s per capita income relative to national per capita income

The state’s 1978 VR funding allotment

The state funding match of 21.3%

The minimum funding level for small states

Squaring of state per capita income relative to national per

capita income

Very appropriate

Somewhat appropriate

Neither appropriate nor inappropriate

Somewhat inappropriate

Very inappropriate

No opinion or no basis to judge

Source: GAO analysis of survey results, questions 2 and 3.

0 10 20 30 40 50 60 70 80 90 100

Note: One agency did not respond to the question about the appropriateness or inappropriateness of 

the 21.3% state matching rate. For other questions, responses may not total 100% due to rounding. 

Page 67 GAO-09-798 Vocational Rehabilitation
Appendix IX: Responses to Selected 

Questions from GAO Survey of State 

Vocational Rehabilitation (VR) Agencies 

Figure 9: State VR Agency Officials’ Opinions about Options for Modifying the Formula 

Percentages based on responses from 74 VR agencies

Funds should be distributed so that all states would contribute

about the same proportion of their total state financial resources

(e.g., states’ tax base plus other revenues) to provide VR services.

Funds should be distributed so that all states would receive

funding to provide the same level of services per individual

potentially eligible for VR services by the formula taking into

account certain differences in the cost of services among states. 

Funds should be distributed so that all states would receive the

same amount of funds per individual potentially eligible for

VR services.

Definitely yes

Probably yes

No preference

Probably no

Definitely no

No opinion or no basis to judge

Source: GAO analysis of survey results, question 5.

0 10 20 30 40 50 60 70 80 90 100

Note: Responses may not total 100 percent due to rounding. 

Page 68 GAO-09-798 Vocational Rehabilitation
Appendix IX: Responses to Selected 

Questions from GAO Survey of State 

Vocational Rehabilitation (VR) Agencies 

Figure 10: State VR Agency Officials’ Opinions about Whether the Matching 

Requirement Should Vary to Account for States’ Total Financial Resources 

7%

8%

26%

50%

3%

No opinion or no basis to judge

Definitely yes

Probably yes

7% No preference

Probably no

Definitely no

Percentage based on responses from 74 VR agencies

Source: GAO analysis of survey results, question 6.

Note: Responses total to greater than 100 percent due to rounding. 

Page 69 GAO-09-798 Vocational Rehabilitation
Appendix IX: Responses to Selected 

Questions from GAO Survey of State 

Vocational Rehabilitation (VR) Agencies 

Figure 11: State VR Agency Officials’ Opinions about Incorporating Performance Awards in the VR Program 

Percentages based on responses from 74 VR agencies

Do you think that VR agencies should receive additional funding

based on agency performance through a mechanism outside

the funding formula?

Do you think that VR agencies should receive additional funding

based on agency performance through the funding formula?

Is it possible to develop measures of performance across agencies

that are both fact-based and fair that could be used to distribute

funds to VR agencies?

Definitely yes

Probably yes

No preference

Probably no

Definitely no

No opinion or no basis to judge

Source: GAO analysis of survey results, questions 9, 11, and 12.

0 10 20 30 40 50 60 70 80 90 100

Note: Responses may not total 100 percent due to rounding. 

Page 70 GAO-09-798 Vocational Rehabilitation
Appendix IX: Responses to Selected 

Questions from GAO Survey of State 

Vocational Rehabilitation (VR) Agencies 

Figure 12: State VR Agency Officials’ Opinions about Potential Results of Including Performance Awards in the VR Program 

Percentages based on response from 74 VR agencies

 Competition between VR agencies would increase, potentially

resulting in less sharing of best practices among agencies

VR agencies would have difficulty estimating future budgets

VR agencies operating under order of selection may have difficulty

obtaining the performance-based funds

VR agencies most in need of additional resources would have

difficulty obtaining the performance-based funds

VR agencies would strengthen management practices

VR agencies would be less likely to serve individuals with

significant disabilities

VR agencies would be less likely to serve individuals who are

unlikely to positively impact performance measures

VR agencies would focus on clients who are likely to positively

impact performance measures

Outcomes for VR clients would improve

VR agencies would be appropriately rewarded

Very likely

Somewhat likely

Would have no effect

Somewhat unlikely

Very unlikely

No opinion or no basis to judge

Source: GAO analysis of survey results, question 14.

0 10 20 30 40 50 60 70 80 90 100

Note: For three questions, 73 agencies provided responses. These questions asked about the 

following results: (1) “Outcomes for VR clients would improve;” (2) “VR agencies would focus on 

clients who are likely to positively impact performance measures;” and (3) “Competition between VR 

agencies would increase, potentially resulting in less sharing of best practices among agencies.” For 

other questions, responses may not total 100 percent due to rounding. 

Page 71 GAO-09-798 Vocational Rehabilitation
Appendix IX: Responses to Selected 

Questions from GAO Survey of State 

Vocational Rehabilitation (VR) Agencies 

Figure 13: State VR Agency Officials’ Opinions about Challenges of Incorporating Performance Awards into the VR Program 

Percentages based on response from 74 VR agencies

Accounting for differences in the populations served by

state VR agencies

Isolating agency performance from factors outside the control

of the VR agency (such as the economic conditions in the state)

Designing measures that appropriately capture performance

Ensuring the reliability of data used to determine funds

for performance

Time gaps between when performance occurred and when the

performance is rewarded with funding, due to timing of data

collection

Very great challenge

Great challenge

Moderate challenge

Slight challenge

Not a challenge at all

No opinion or no basis to judge

Source: GAO analysis of survey results, question 16.

0 20 40 60 80 100

Note: One agency did not provide a response regarding the extent to which data reliability would be a 

challenge. For other questions, responses may not total 100 percent due to rounding. 

Page 72 GAO-09-798 Vocational Rehabilitation
Appendix IX: Responses to Selected 

Questions from GAO Survey of State 

Vocational Rehabilitation (VR) Agencies 

Figure 14: VR Agencies’ Responses on Whether They Receive Funding from Their 

State based on Performance 

5%

93%

Percentage based on responses from 74 VR agencies

1%

Not sure

Yes

No

Source: GAO analysis of survey results, questions 2 and 3.

Note: Responses total to less than 100 percent due to rounding. 

Page 73 GAO-09-798 Vocational Rehabilitation
Appendix IX: Responses to Selected 

Questions from GAO Survey of State 

Vocational Rehabilitation (VR) Agencies 

Figure 15: Current Use of Performance Awards by State VR Agencies 

Percentages based on responses from 74 VR agencies

VR district offices, field offices, or local service delivery centers

External entities such as contractors, partners, and community

rehabilitation organizations

VR managers

VR counselors

Awards provided to all

Awards proved to some

Awards not provided

Source: GAO analysis of survey results, question 20.

0 10 20 30 40 50 60 70 80 90 100

Note: For two questions, 73 agencies provided responses. These questions asked whether agencies 

provided awards for (1) VR managers, and (2) external entities such as contractors, partners, and 

community rehabilitation organizations. For other questions, responses may not total 100 percent due 

to rounding. 

Page 74 GAO-09-798 Vocational Rehabilitation
Appendix X: 

A

GAO Contacts and Staff 

cknowledgments 

Page 75 GAO-09-798 

Appendix X: GAO Contacts and Staff 

Acknowledgments 

Daniel Bertoni, Director, (202) 512-7215 or bertonid@gao.gov. 

Michele Grgich, Assistant Director; Yunsian Tai, Analyst-in-Charge; 

Gregory Dybalski, Thanh Lu; Karine McClosky; and Barbara Steel-Lowney 

made significant contributions to all aspects of this report. Susan 

Bernstein provided writing assistance. Other advisers included Joanna 

Chan, Robert Dinkelmeyer, Ronald Fecso, DuEwa Kamara, Stuart 

Kaufman, Jacqueline Nowicki, Patricia Owens, Max Sawicky, and Roger 

Thomas. 

 Vocational Rehabilitation 

GAO Contact 

Acknowledgments 

(130887) 
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