United States Government Accountability Office

GAO Report to Congressional Requesters

UNEMPLOYMENT 

INSURANCE 

More Guidance and 

Evaluation of WorkerProfiling Initiative 

Could Help Improve 

State Efforts 

June 2007 

 

GAO-07-680 
What GAO Found

United States Government Accountability Office

Why GAO Did This Study

Highlights

Accountability Integrity Reliability

June 2007

UNEMPLOYMENT INSURANCE 

More Guidance and Evaluation of WorkerProfiling Initiative Could Help Improve 

State Efforts 

Highlights of GAO-07-680, a report to 

congressional requesters 

Changes to the U.S. economy have

led to longer-term unemployment. 

Many unemployed workers receive 

Unemployment Insurance (UI), 

which provided about $30 billion in 

benefits in 2006. In 1993, Congress

established requirements—now 

known as the Worker Profiling and 

Reemployment Services (WPRS) 

initiative—for state UI agencies to

identify claimants who are most 

likely to exhaust their benefits, and 

then refer such claimants to 

reemployment services. 

To assess the implementation and

effect of the initiative, GAO 

examined (1) how states identify 

claimants who are most likely to

exhaust benefits, (2) to what extent

states provide reemployment 

services as recommended by the 

Department of Labor (Labor), and 

(3) what is known about the 

effectiveness of the initiative in 

accelerating reemployment. To 

answer these questions, we used a 

combination of national data; 

review of seven states, including 

visits to local service providers in 

four states; and existing studies 

and interviews with Labor and 

subject matter experts. 

What GAO Recommends

GAO recommends that Labor 

reevaluate worker-profiling data 

collection, take a more active role 

in ensuring the accuracy of state

models, encourage states to adhere

to Labor’s vision for reemployment

services, and consider evaluating 

the impact of the program. The 

Secretary of Labor generally agreed

with our findings and 

recommendations. 

Forty-five of the 53 states and territories use statistical models that facilitate 

the ranking of claimants by their likelihood to exhaust benefits, while 

7 states use more limited screening tools that do not facilitate a ranking. 

Florida delegates the selection of profiling tools to local areas in the state. 

Factors used to determine the probability of exhaustion include a claimant’s 

education, occupation, and job tenure. Many states have not regularly 

maintained their models, and as a result, the models in some states may not 

be accurately identifying claimants who are likely to exhaust benefits. 

Although Labor data provide a limited picture of states’ implementation of 

the worker-profiling initiative, 6 of the 7 states we studied did not provide 

the in-depth approach to services as recommended by Labor. Overall, an 

average of 15 percent of profiled UI claimants were referred to 

reemployment services, and 11 percent completed these services between 

2002 and 2006. Six of the 7 states we contacted referred claimants to 

services, held them accountable for attending the services, and provided an 

orientation. However, only 1 of the 7 states provided individualized needs

assessments, and developed service plans, as recommended. 

Little is known about the effectiveness of the worker-profiling initiative as it

is currently operating. Although studies using data from the 1990s generally 

indicated that claimants who were referred to services had reduced reliance 

on UI, there are no more up-to-date studies. Further, some of the program 

data collected by Labor are not reliable, and the data are not being used by 

Labor or states to evaluate the initiative. 

Profiling Techniques Used in the United States

Source: GAO analysis of U.S. Department of Labor data; (Map) Map Resources.

Characteristic screens

Statistical model with variables beyond

those recommended by Labor

Statistical model

Delegates profiling to local areas

Alaska

Hawaii

Virgin Islands

Puerto Rico

www.gao.gov/cgi-bin/getrpt?GAO-07-680.

To view the full product, including the scope 

and methodology, click on the link above. 

For more information, contact Sigurd Nilsen at 

(202) 512-7215 or nilsens@gao.gov. 
Contents 

Letter 1

Results in Brief 2

Background 4

Most States Use Statistical Models to Identify Claimants Likely to 

Exhaust Benefits, but Many Have Not Updated Them to Account 

for Changing Economic Conditions 9 

Most Study States Did Not Take the In-Depth Approach 

Recommended by Labor to Ensure That Profiled Claimants 

Obtain Reemployment Services 19 

Little Is Known about Program’s Effectiveness because There Are 

No Current Studies and Labor’s Data Are of Limited Usefulness 24 

Conclusions 29

Recommendations for Executive Action 30 

Agency Comments 31 

Appendix I Objectives, Scope, and Methodology 32 

Appendix II Average Percentage of Claimants Profiled, Referred 

to, and Completing Services for 2002-2006 and Average 

Claimant Outcomes for 2002-2005, by State 36 

Appendix III Bibliography of Research Studies on the WorkerProfiling Initiative—Exhaustive List Identified 

from the Literature Review 38 

Appendix IV Summary of the Impact of Referral to Services on 

Claimant Outcomes from the Literature Review 39 

Appendix V Comments from the Department of Labor 40 

Appendix VI GAO Contacts and Acknowledgments 42 

Page i GAO-07-680 Unemployment Insurance
Related GAO Products 43 

Tables 

Table 1: Labor-Recommended Factors 10 

Table 2: Selected Types of Variables Used in State Models beyond 

Federally Recommended Variables 15 

Table 3: Research Studies Included in Our Literature Review 25 

Table 4: Summary of Research Study Findings on the Effect of 

Referral to Services on Claimant Outcomes 26 

Table 5: National Averages and Ranges of State Averages on 

Outcomes for Claimants Profiled and Referred to Services, 

2002 to 2005 28 

Figures 

Figure 1: Process for Profiling, Referring, and Providing 

Reemployment Services to Claimants 7 

Figure 2: Profiling Techniques Used in the States 12 

Figure 3: States’ Adjustments of Model Coefficients 17 

Figure 4: Passage of Time since States Adjusted Models by 

Changing Variables 18 

Figure 5: Percentage of Claimants Referred to Services, of 

Those Profiled 20 

Figure 6: Percentage of Claimants Completing Services, of 

Those Profiled 21 

Page ii GAO-07-680 Unemployment Insurance
Abbreviations 

ETA Employment and Training Administration 

UI Unemployment Insurance 

WIA Workforce Investment Act 

This is a work of the U.S. government and is not subject to copyright protection in the 

United States. It may be reproduced and distributed in its entirety without further 

permission from GAO. However, because this work may contain copyrighted images or 

other material, permission from the copyright holder may be necessary if you wish to 

reproduce this material separately. 

Page iii GAO-07-680 Unemployment Insurance
United States Government Accountability Office

Washington, DC 20548 

June 14, 2007 

The Honorable Jerry Weller 

Ranking Member 

Subcommittee on Income Security and Family Support 

Committee on Ways and Means 

House of Representatives 

The Honorable Jerry Weller 

Ranking Member 

Subcommittee on Income Security and Family Support 

Committee on Ways and Means 

House of Representatives 

The Honorable Wally Herger 

House of Representatives 

Changes to the U.S. economy—including the contraction of entire 

industries as a result of changes in technology and overseas competition—

have led to increases in the length of unemployment. Unemployed workers 

are now less likely to be rehired by their previous employers and are at a 

greater risk of long-term unemployment than in the past. Over the past five

decades, the average duration of unemployment has been gradually 

increasing, so that during 2006, periods of unemployment grew to an 

average of 15 weeks, compared with 11 weeks during the 1950s. Many 

unemployed workers receive temporary, partial wage replacement 

through the Unemployment Insurance (UI) program. Under most state 

programs, claimants can obtain regular benefits for up to 26 weeks. In 

order to help facilitate workers’ return to work, Congress established 

requirements now known as the Worker Profiling and Reemployment 

Services initiative in 1993. Under this initiative, state UI agencies are 

required to identify those who are most likely to exhaust their benefits, a 

process known as profiling, and refer them to reemployment services. 

Changes to the U.S. economy—including the contraction of entire 

industries as a result of changes in technology and overseas competition—

have led to increases in the length of unemployment. Unemployed workers 

are now less likely to be rehired by their previous employers and are at a 

greater risk of long-term unemployment than in the past. Over the past five

decades, the average duration of unemployment has been gradually 

increasing, so that during 2006, periods of unemployment grew to an 

average of 15 weeks, compared with 11 weeks during the 1950s. Many 

unemployed workers receive temporary, partial wage replacement 

through the Unemployment Insurance (UI) program. Under most state 

programs, claimants can obtain regular benefits for up to 26 weeks. In 

order to help facilitate workers’ return to work, Congress established 

requirements now known as the Worker Profiling and Reemployment 

Services initiative in 1993. Under this initiative, state UI agencies are 

required to identify those who are most likely to exhaust their benefits, a 

process known as profiling, and refer them to reemployment services. 

Statistics on the UI program underscore the importance of addressing 

benefit exhaustion. In 2006 about 7 million claimants received UI 

payments, totaling about $30 billion. Of those claimants, about 35 percent 

used all the benefits available to them. If they had used 1 week less of 

benefits, it would have saved the state UI trust funds roughly $600 million. 

Statistics on the UI program underscore the importance of addressing 

benefit exhaustion. In 2006 about 7 million claimants received UI 

payments, totaling about $30 billion. Of those claimants, about 35 percent 

used all the benefits available to them. If they had used 1 week less of 

benefits, it would have saved the state UI trust funds roughly $600 million. 

You asked us to assess how the worker-profiling initiative has been 

implemented, and its effect on shortening the length of unemployment. 

Specifically, you wanted to know: 

You asked us to assess how the worker-profiling initiative has been 

implemented, and its effect on shortening the length of unemployment. 

Specifically, you wanted to know: 

1. How do states identify unemployment claimants who are most 

likely to exhaust benefits? 

1. How do states identify unemployment claimants who are most 

likely to exhaust benefits? 

Page 1 GAO-07-680 Unemployment Insurance
2. To what extent do states provide reemployment services as 

recommended by Labor? 

3. What is known about the effectiveness of the worker-profiling 

initiative in accelerating the reemployment of unemployment 

insurance claimants? 

To answer these questions, we used a combination of national data, indepth site visits, existing studies, and interviews with subject matter 

experts. We analyzed national data collected by the Department of Labor

(Labor) from states on the worker-profiling initiative, including data on the 

50 states, as well as the District of Columbia, Puerto Rico, and the Virgin

Islands from a 2006 Labor-sponsored survey on models states use to 

profile. We also analyzed data on profiling, reemployment services, and 

outcomes that states report to Labor using the reemployment service 

activity and outcomes reports maintained by Labor’s Employment and 

Training Administration. In addition, we interviewed state officials in 

seven states: California, Delaware, Illinois, Kentucky, Texas, Washington,

and Wisconsin. We selected the seven states to include the range of 

approaches states take to identify and serve those likely to exhaust 

benefits. We visited local service providers in four of these states. Our site 

visit states were selected to provide a range of state experiences with the 

worker-profiling initiative and to ensure variation in geography and 

population size. We identified six studies examining the impact of the 

worker-profiling programs and, after evaluating the methodological 

soundness and the validity of the results and conclusions, determined that 

five of the six studies were sufficiently rigorous to use in this report. 

Further, we interviewed Labor officials and other experts on worker 

profiling and UI and reviewed other reports, including academic and Labor 

research on profiling systems, best practices, and the outcomes of profiled 

UI claimants. We performed our work in accordance with generally 

accepted government auditing standards between August 2006 and April 

2007. 

The large majority of states use statistical models to identify claimants 

who are most likely to exhaust their unemployment benefits. However, 

many states have not recently adjusted these models to ensure predictive

accuracy. Forty-five of the 53 states and territories use statistical models 

to identify clients likely to exhaust benefits, while 7 states use more 

limited screening tools that do not enable states to rank claimants by 

probability of exhausting benefits. One state—Florida---allows the local 

areas in the state to select the profiling technique. The size and complexity 

Results in Brief 

Page 2 GAO-07-680 Unemployment Insurance
of the statistical models used by the 45 states vary considerably. For 

example, 11 of the 45 states reported using models that include the 

5 variables recommended by the Department of Labor, while 34 states 

reported using additional variables. In our site visits, we learned that these 

additional variables can be limited to just 1 or 2, as in California, to over 

50 variables used by Kentucky. We further found that many states do not 

regularly update their models. A 2006 Labor-sponsored survey of the states 

revealed that many states continue to use models that have not been 

adjusted in a decade or more. For example, 30 states have not revised their 

models since implementing them in the mid-1990s. This raises concerns 

because Labor officials, state officials, and other modeling experts have 

stated that a model may lose predictive accuracy if it is not revised every 

few years to adjust for changes to the labor market and other economic 

conditions. For example, a 2003 California study found that the state’s 

model underestimated benefit exhaustion and recommended an update to

the model, a process California has begun. Officials in states we contacted 

explained that they face a number of obstacles to regularly updating the

models. For example, updating and maintaining the statistical models can 

be impeded by technical and data difficulties, and other priorities for 

limited UI administrative funds and staff resources. Although Labor 

provides technical assistance to states requesting it, the agency does not 

regularly monitor state efforts to adjust their models. 

It is difficult to determine the extent to which all states are providing 

reemployment services to claimants because some of Labor’s data are 

unreliable. However, we determined that 6 of the 7 states we studied did 

not provide the in-depth services that Labor originally recommended. 

Nationally, according to Labor’s data, 15 percent of the profiled claimants

were referred to services between 2002 and 2006. These referrals ranged 

from as few as 1 percent in Wyoming to as many as 52 percent in 

Washington. We could not determine the services received by those 

referred for all states because Labor’s data on services were not 

sufficiently reliable. In the states we studied, the services provided were 

only some of those recommended by Labor. Six of the 7 states referred 

claimants to services, enforced consequences for failure to attend these 

services, and provided one or more sessions that included orientation to 

services and instruction on various job search skills. However, only 1 state 

performed in-depth individual assessments and created individualized 

reemployment plans, both of which are recommended in Labor’s guidance. 

State officials cited various challenges to providing these reemployment 

services to UI claimants. These included the discontinuation of federal 

grants that some states had used to fund services and the difficulty of 

serving a disparate clientele that ranged from people in upper 

Page 3 GAO-07-680 Unemployment Insurance
management to laborers. Although Labor recognizes these constraints, 

officials said the program’s purpose is to target the funding that does exist 

to those who need it most. 

Little is known about the current effectiveness of the worker-profiling 

initiative. The few early studies, which all used data from 1994 to 1996, 

generally indicated that claimants who were referred to services received

less in unemployment benefits and collected them for shorter lengths of 

time than comparable groups of claimants that did not receive services. 

These studies found that those referred to services received $55 to 

$320 less in benefits and remained on unemployment insurance for 0.2 to 

4 weeks less. Since 1999, Labor has not published any studies on the effect

of the initiative and, according to Labor officials, has no plans to study the 

effects of profiling. Although Labor collects data on the outcomes of those 

profiled and referred to services, only some of the data were reliable 

enough to report. For example, on average about 40 percent of claimants 

who were referred to services exhausted their benefits between 2002 and 

2005. Furthermore, although Labor and some states make limited use of 

the data, the data are not consistently being used to evaluate the initiative.

According to Labor officials, the data were intended for states to evaluate

the effectiveness of the initiative. However, officials from 4 of the 7 states 

we studied said they did not use Labor’s data primarily because they do 

not meet their management needs. For example, data are aggregated at the 

state level, and some state officials said they would prefer local-level data.

In this report, we recommend that the Secretary of Labor ensure that the 

Employment and Training Administration reevaluate data collection for 

the worker-profiling initiative to determine whether it is sufficient for its 

intended purpose, take a more active role in ensuring the accuracy of state 

profiling models, encourage states to adhere to Labor’s vision for 

reemployment services, and evaluate the impact of the worker-profiling 

program. In responding to a draft of this report, Labor generally agreed 

with our findings and recommendations. 

Labor also provided technical comments on the draft report, which we 

have incorporated where appropriate. 

Beginning in the mid-1970s, major structural changes took place in the 

American economy, as advances in technology, international competition, 

plant closings, and corporate streamlining resulted in the dislocation of 

thousands of workers from their jobs. Some of these individuals possessed 

skills that were no longer in demand; others suffered from a lack of job 

Background 

Page 4 GAO-07-680 Unemployment Insurance
search skills. In the 1980s and early 1990s, demonstration projects were 

conducted in New Jersey, Nevada, Minnesota, and Washington. The New 

Jersey and Minnesota projects showed the efficacy of using statistical 

methods and administrative data to identify those who are likely to 

experience long periods of joblessness. For example, the New Jersey 

demonstration project screened claimants with various eligibility 

requirements and found that the screening allowed the state to direct 

services to those who generally faced reemployment difficulties.1

 Further, 

results from all four states showed that providing more intensive job 

search assistance to this population reduced the duration of insured 

unemployment and UI expenditures.2

In response to these events, the Clinton administration proposed 

legislation to implement worker profiling in 1993. In the same year, 

Congress enacted the Unemployment Compensation Amendments, 

amending the Unemployment Insurance program legislation. 3 The law 

requires that states establish and utilize a system of profiling all new 

claimants for UI regular compensation. The system must identify those 

claimants that will be likely to exhaust regular compensation and refer 

them to reemployment services, such as job search assistance services. 

Typically, such claimants receive services at one of the local “one-stop” 

employment services centers that exist throughout the nation. States are 

required to collect information on the type of services claimants receive,

their participation, and their subsequent employment outcomes. The last 

could include such information as whether referred claimants obtained 

new jobs and the related wage levels. 

In 1994, Labor issued guidance to help states establish profiling tools and 

provide necessary reemployment services. In profiling claimants, Labor 

required that states consider factors that include whether the claimant has

a date for being recalled to work, union status, first unemployment benefit

payment, and previous industry or occupation of employment. Labor 

 1

Walter Corson, Paul T. Decker, Shari Mill Dunstan, and Anne R. Gordon, “The New Jersey 

Unemployment Insurance Reemployment Demonstration Project” (April 1989). 

2

Randall Eberts, “The Use of Profiling in the United States for Early Identification and 

Referral of Less Employable Unemployment Insurance Recipients,” Employability:

Concepts and Policies (May 1999). 

3

Unemployment Compensation Amendments of 1993 (Pub. L. No. 103-152). 

Page 5 GAO-07-680 Unemployment Insurance
recommended also considering some additional factors such as claimants’ 

education, tenure at previous job, and the state unemployment rate.4

Labor outlined recommended processes for providing reemployment 

services to referred claimants, including (1) an orientation session for 

claimants that would, among other things, explain the availability and 

benefit of reemployment services; (2) an assessment of the specific needs 

of each claimant, if appropriate; and (3) based on the assessment, 

development of an individual plan for services that would guide a 

claimant’s further services. (See fig. 1.) Under the law, states must also 

require that claimants who have been referred to reemployment services 

participate in those services as a condition of eligibility for receiving 

compensation. 

 4

Labor also prohibited the use of certain data elements, such as age, race or ethnic group, 

sex, disability, and religion, as Labor determined that use of such characteristics would be 

in violation of federal law. 

Page 6 GAO-07-680 Unemployment Insurance
Figure 1: Process for Profiling, Referring, and Providing Reemployment Services to

Claimants 

Provide referred 

claimants with an:

· orientation session

· individual assessment, 

 if appropriate, and

· individual service plan.

Track referred 

claimants

Hold claimants

ineligible for benefits

Source: Unemployment Insurance Program Letter 41-94: Unemployment Insurance Program Requirements for the Worker Profiling and 

Reemployment Services Program System, Employment and Training Administration, U.S. Department of Labor, August 16, 1994.

Subject to profiling Not subject to 

profiling

Referred Not referred

All UI claimants

Labor may withhold UI administrative grants from a state if Labor finds, 

after notice and an opportunity for a hearing, that a state has failed to 

comply with worker-profiling requirements. These include identifying 

claimants most likely to exhaust benefits, referring claimants to 

reemployment services, and collecting follow-up information on services 

received and subsequent employment outcomes. 

The law required that Labor report to Congress on the operation and 

effectiveness of the profiling system within three years of its enactment. 

Labor issued a report to Congress in March 1997, and published a final 

report in 1999 on the program’s implementation and operation nationwide 

and the effectiveness in six early implementation states. Labor has 

published no studies on the effectiveness of the initiative since then. The

agency’s strategic plan for fiscal years 2006 through 2011, in providing an

Page 7 GAO-07-680 Unemployment Insurance
overview of program evaluation, includes no ongoing or future research 

topics addressing the impact of the worker-profiling initiative. Labor has 

conducted impact evaluations as part of its program evaluations in the 

past.5

 In fiscal year 2007, Labor was appropriated $17.7 million for pilots, 

demonstrations, and research. 

Funding for the worker-profiling program is provided from a variety of 

sources. Federal funding for the creation and maintenance of profiling 

models can come from UI administrative funds, which are financed by a 

federal UI tax on employers.6

 Reemployment services can be funded 

through a variety of sources. For example, states can use Wagner-Peyser 

Employment Services grants as well as other state sources of funding to 

provide reemployment services to profiled UI claimants.7

 From 2001 to 

2005, Labor also provided Reemployment Services grants to all states in 

 5

Many researchers consider impact evaluations to be the best method for determining the

extent to which the program itself, rather than other factors, is causing participant 

outcomes. Impact evaluations can be designed in several ways, but fall into two basic 

design categories: experimental and quasi-experimental. Experimental designs randomly 

assign eligible individuals either to a group that will receive services from the program 

being studied or to a group that will not receive services from the program. If random 

assignment is successful, the only difference between the two groups is their access to 

program services. The relevant outcomes of these two groups are measured and compared,

and any differences found between the two can be attributed to the programs. When

randomly assigning individuals to a control group is not a feasible option, quasiexperimental impact evaluations can be used to compare the outcomes of program 

participants to those of individuals not in the program. In a quasi-experimental design, 

methods other than random assignment are used to create a comparison group. A

comparison group can be developed in a variety of ways. One way is to use a set of 

individuals who have similar characteristics as the group receiving the program services 

under study. Although quasi-experimental studies do not use random assignment, it is still 

possible to determine the impact of a program through statistical methods or other

research design techniques. 

6

In 2002 the federal government distributed $8 billion of the unemployment tax revenue it 

had held in reserve. This was known as a Reed Act distribution. As long as a state has a 

specific appropriation for its legislature, it could use the funds for administrative costs of 

state UI. 

7

The Wagner Peyser-funded activities are an integral part of the nation’s one-stop delivery 

system that provides employment-related services so that workers, job seekers, and 

businesses can access the services they need in a central location. 

Page 8 GAO-07-680 Unemployment Insurance
order to enhance and target services to claimants through the nation’s 

network of one-stop employment service centers.8

 

The large majority of states use statistical models to identify 

unemployment recipients who are most likely to exhaust benefits. 

However, many states have not recently adjusted their models, risking the 

possibility that these models may lose predictive accuracy over time. 

Forty-five states use statistical models to identify and rank clients by their

likelihood to exhaust benefits, while 7 states use characteristic screens 

that do not rank claimants. One state—Florida—allows the local areas to 

decide whether to use statistical models or screening tools. Among the 

states using statistical models, the detailed specifications of these models 

vary considerably from state to state. Further, many states do not regularly 

update their models, a fact that can lead to a loss of predictive accuracy 

over time. A survey of the states reveals that many have not revised or 

updated their models in many years. Officials in states we contacted 

explained that they face a number of impediments to doing so. 

Under worker profiling, state UI agencies are to identify claimants who are 

most likely to exhaust benefits in two steps. States screen claimants in 

order to eliminate claimants who are unemployed but job-attached or 

would otherwise not qualify for referral to services from the profiling 

process.9

 After the initial screening, states profile remaining claimants—

that is, they consider a range of personal and economic variables related 

to a claimant and determine whether or not he or she is likely to exhaust 

benefits. Although states have considerable flexibility in determining what 

variables to use, Labor has recommended the use of five variables, as 

outlined in table 1.10

Most States Use 

Statistical Models to 

Identify Claimants 

Likely to Exhaust 

Benefits, but Many 

Have Not Updated 

Them to Account for 

Changing Economic 

Conditions 

Most States Use Statistical 

Models instead of More 

Limited Characteristic 

Screens 

 8

Reemployment Services grants could be used to fund services and are different from the

Reemployment Eligibility and Assessment (REA) grants awarded by Labor to some states. 

REA grants are to be used by one-stop centers to conduct in-person interviews of certain 

UI recipients to assess their continuing eligibility for benefits and need for reemployment 

services. They cannot be used to fund services, according to Labor officials.

9

Labor requires that states screen out claimants who will be recalled to work or who have a 

union hiring hall agreement. It also requires that states exclude claimants who do not

receive a first payment for total unemployment and those who receive first payment for 

only partial claims. Some states also exclude other claimants from profiling, such as 

interstate claimants, and seasonal workers. 

10Labor also developed a prototype statistical model that some states substantially adopted. 

Page 9 GAO-07-680 Unemployment Insurance
Table 1: Labor-Recommended Factors 

Factor

a

Impact on unemployment 

Education Claimants with less education are more likely to exhaust benefits. 

Job tenure Claimants with long attachment to a specific employer have more 

difficulty in finding equivalent employment elsewhere. 

Industrya Claimants who worked in industries that are declining, relative to 

others in a state, experience greater difficulty in finding new 

employment than claimants who worked in expanding industries. 

OccupationaWorkers in low demand occupations experience greater reemployment 

difficulty than workers in occupations with high demand. 

Unemployment

rate 

Reemployment difficulty is closely related to economic conditions, and 

in areas of high unemployment, workers will have greater difficulty 

becoming reemployed than workers in areas of low unemployment. 

Source: U.S. Department of Labor, Employment and Training Administration, Unemployment Insurance Program Letter No. 41-94, 

August 1994.

a

Labor requires that state profiling models consider either a claimant’s industry or occupation. The 

other factors are recommended but optional. 

We found that states used one of two methods to identify claimants who 

are most likely to exhaust benefits—the statistical model or 

characteristics screening. Both of these look at a range of personal and 

economic factors that help predict exhaustion. 

Forty-five of the 53 states and territories use statistical models to identify 

clients likely to exhaust benefits. (See fig. 2.) Using various statistical 

techniques, these models consider the combined quantitative influence of

various personal and labor market characteristics and produce a 

measurement of a claimant’s likelihood to exhaust. In statistical models, 

each characteristic—commonly referred to as a variable—is associated 

with a specific mathematical weight that quantifies the variable’s 

contribution to the claimant’s probability of exhaustion. If, for example, a 

claimant’s last job was in a steeply declining industry, the industry variable 

would have a positive effect on the score, indicating a claimant’s 

likelihood to exhaust. Conversely, if a claimant’s last job was in an 

expanding industry, it would have the opposite effect. Essentially a 

statistical model produces a weighted average of the effect of all the 

variables combined. As a result, states that use statistical models can rank

claimants from greatest to least likelihood of exhaustion, and target 

reemployment services to claimants with the greatest likelihood of 

exhausting. According to an official of the Upjohn Institute for 

Page 10 GAO-07-680 Unemployment Insurance
Employment Research,11 such models, if properly developed and 

maintained, are a powerful and effective means of identifying particular 

populations for a range of social service programs.12

 11The Upjohn Institute for Employment Research is a not-for-profit, nonpartisan research

organization founded to conduct research into the causes and effects of unemployment and 

measures for the alleviation of unemployment. 

12Programs using a statistical method for early identification of those most likely to have

long spells of unemployment have been used in other countries, such as Australia and 

Canada, as well. 

Page 11 GAO-07-680 Unemployment Insurance
Figure 2: Profiling Techniques Used in the States 

Source: GAO analysis of U.S. Department of Labor data; (Map) Map Resources.

Characteristic screens

Statistical model

Statistical model with variables beyond those recommended by Labor

Delegates profiling to local areas

Alaska

Hawaii

Calif.

Vt.

N.H.

Mass.

R.I.

Conn.

N.J.

Del.

Md.

D.C.

Ala.

Ariz.

Ga.

Ind.

Iowa

Kans.

La.

Maine

Mo.

Nebr.

N.Mex.

N.Y.

N.Dak.

Oreg.

Pa.

Tex.

Wisc.

Fla.

Miss.

N.C.

Ohio

Okla.

S.Dak.

Wyo.

Idaho

Mont.

Wash.

Nev.

Utah

Colo.

Mich.

Va.

W.

Va.

Ky.

S.C.

Tenn.

Ark.

Ill.

Minn.

Virgin Islands

Puerto Rico

Seven of the 8 remaining states use characteristic screens that do not 

allow them to rank claimants. One state, Florida, delegates the selection of

profiling tools to the local areas because state officials believe profiling 

can be done more accurately at that level. Like statistical models, 

characteristic screens may consider various factors associated with the 

Page 12 GAO-07-680 Unemployment Insurance
likelihood to exhaust benefits, but treat them as yes-no decision points. 

Either the claimant has the attribute or does not. The relative importance 

of any one variable in relation to others is not considered. Claimants 

selected through this process must have each of the screening criteria. For 

example, the characteristic screen used by Delaware considers whether or 

not a claimant meets specific criteria relating to industry, occupation, and

job tenure. In Delaware, a claimant passes the job tenure screen if he or 

she has 2 or more years of tenure with his or her last employer. However, 

since claimants cannot be ranked, states using screens must develop a 

method, such as random assignment, to refer identified claimants to 

services if they are unable to serve all claimants that pass the screens. For 

example, Delaware used to refer claimants who passed the screen on a 

random basis, but now refers all claimants who pass the screen. Labor 

encourages the use of statistical models over characteristic screens 

because they are more efficient and precise in identifying claimants likely 

to exhaust. 

Statistical Models Vary in 

Key Elements 

Although all statistical models are supposed to identify claimants who are 

likely to exhaust benefits, the states can vary in how they specifically

define this exhaustion. The model originally proposed by Labor is 

designed to predict the probability of exhaustion as a yes-or-no outcome—

exhaustion or no exhaustion—and the claimant’s profiling score would 

reflect the probability of the yes outcome. Most states have adopted this 

definition. However, as Labor explained in 1998 guidance, this approach 

does not distinguish between claimants who almost exhaust benefits and

those who do not come close to exhausting benefits.13 This is significant, 

because the claimant with nearly exhausted benefits may be in greater 

need of reemployment services than the clamant who uses a 

comparatively small portion of his or her benefits. Consequently, some 

states predict exhaustion as the amount of benefits a claimant will 

potentially use. For example, the profiling score produced by Kentucky’s 

model produces a number between 1 and 20. A claimant with a score of 

20 is likely to use 95 to 100 percent of benefits; a claimant with a score of 

19 is likely to use 90 to 95 percent of benefits, and so on. 

 13Marisa L. Kelso, “Worker Profiling and Reemployment Services Profiling Methods: 

Lessons Learned,” U.S. Department of Labor, Unemployment Insurance Occasional Paper 

99-5, June 1998. 

Page 13 GAO-07-680 Unemployment Insurance
State models can differ considerably in how they define similar variables, 

including those corresponding to the factors recommended by Labor. For 

example, California uses six categories to measure the job tenure variable,

ranging from 1 year or less on the low end to more than 15 years on the 

high end. In contrast, Texas uses only two categories—job tenure of less 

than 1 year on the low side and tenure of more than 10 years on the high

end. The Kentucky model, on the other hand, measures job tenure on a 

continuous scale—specifically, the length of time that a claimant held his 

or her last job. The definitions of variables associated with education, 

industry, and other variables can also differ among state models. For 

example, Kentucky includes “completed vocational education” as part of 

its education variable, while Wisconsin does not. 

The number and nature of the additional variables can also differ 

significantly by state. The large majority of states using statistical models 

(34 of 45) use models that consider factors in addition to the five factors 

recommended by Labor, while about one-quarter do not. (See fig. 2.) 

Among the 6 states that we contacted that use statistical models, the 

number of additional variables used ranged from 1 in California to over 

50 in Kentucky. For example, 2 of the 7 states we contacted—Texas and

Illinois—consider the time lapse between the loss of a job and the 

application for UI benefits. According to Texas officials and Labor, delays 

in filing a claim are indicative of a difficult job search, thus increasing the 

likelihood of benefit exhaustion. 

Page 14 GAO-07-680 Unemployment Insurance
Table 2: Selected Types of Variables Used in State Models beyond Federally Recommended Variables 

State 

Variable category Calif. Ill. Ky. Tex. Wash. Increased likelihood of exhaustion

Delay in filing of claim z z Claimants who delay filing claims, indicating an unsuccessful 

job search 

Potential duration z z Claimants with short duration of eligibility for benefits 

Exhaustion rate by sub-state region z Claimants who live in areas of the state that have a high rate of 

exhaustion 

Past wages (base period wages) z z z Claimants with higher past wages 

Prior UI recipient z Claimants who have prior UI claims 

Reason for unemployment z Claimants who have been discharged from work for reasons 

other than being laid off 

Number of recent employers z Claimants with more than one employer 

Employer’s history of layoffsa z Claimants whose employer has a high propensity to lay off 

workers 

Source: GAO document review and analyses of interviews with state officials. 

Note: This table does not include two of the seven states we contacted. The Wisconsin profiling 

model uses only the five variables recommended by Labor, and Delaware uses a characteristic 

screen that uses three of the five recommended variables. 

a

An employer’s propensity to lay off workers serves as the basis of an employer’s unemployment 

insurance tax rate, and is known as an experience rating. 

Although Models Require 

Periodic Maintenance to 

Ensure Predictive 

Accuracy, Many States 

Have Not Updated Their 

Models since 2000 or 

Before 

While Labor has recommended that states update models periodically to

reflect changes in economic conditions, many states have not done so in 

many years. If not periodically updated, statistical models can lose 

predictive accuracy over time because of changes in the labor market, the 

general economy, or other factors. Labor has emphasized the importance 

of updating models, and noted in 1998 guidance that models represent the 

historical period in which they were developed, and that old models 

become increasingly unrealistic and less useful over time. Labor has 

further recommended that models be assessed, and if necessary adjusted, 

approximately every 3 years. Officials in some of the 7 states we contacted

also stressed the importance of updating models from time to time. For 

example, Washington officials noted that although a 2002 analysis of their 

model update showed that it accurately identified the majority of 

claimants who exhausted, this adjustment of their model was based on 

data collected in 1999 and 2000, and subsequent changes in their labor 

market and the general economy have made the model outdated. Also, a 

2003 California study found that the state’s model underestimated benefit 

exhaustion and recommended an update to the model. Similarly, an 

official of the Upjohn Institute for Employment Research told us that the 

institute’s analysis of 1 state’s model found that before the model was 

Page 15 GAO-07-680 Unemployment Insurance
updated, its results were little better than random selection of claimants. 

Officials in Washington and California told GAO that the models would be 

updated in the next year. 

Models can be adjusted by modifying the mathematical weights associated 

with specific variables, and by adding, deleting, or redefining variables to 

enhance a model’s predictive power. This is necessary over time because,

although a particular variable—such as a claimant’s industry—can remain 

an important predictor of exhaustion, its relative importance in the model 

can change significantly. For example, if a variable’s weight was estimated 

based on data from a historical period of large changes of employment 

levels in a particular industry or industries, the model might produce 

misleading results if used in a period of greater industrial and employment 

stability. Similarly, a variable that once served as an important predictor in 

a model may lose predictive value as the labor market and economic 

circumstances change, and conversely, other variables that may not have 

been relevant in one time period may become important at another time. 

For example, Texas deleted education as a variable from the model used 

in that state. According to a Texas official, statistical work performed for 

the model update revealed that the education variable did not measurably 

add to its predictive power. 

Factors other than the labor market and general economy can affect the 

reliability of models as well. For example, in the past 10 years 

standardized coding used to identify both industries and occupations has 

changed, 14 and some of the states we contacted had not updated their 

model to reflect this change. Illinois’ analysis of its model showed that 

while the model had generally retained predictive accuracy, areas of 

concern existed. For example, as a result of outdated occupational codes,

certain occupations associated with greater likelihood of exhaustion were 

no longer being targeted, while others not associated with exhaustion 

were. 

Although Labor has taken a number of actions to encourage and assist 

states in updating their profiling models, some states have not done so for 

many years. Labor has noted the importance of updating models in written 

guidance, sponsored occasional seminars where best modeling practices 

 14Specifically, the Standard Industrial Code system has been replaced by the North 

American Industrial Classification System, and the Dictionary of Occupational Titles has

been replaced by Standard Occupational Classification System. 

Page 16 GAO-07-680 Unemployment Insurance
are shared with state staff, and provides on-demand technical assistance

to states. However, Labor has not established requirements for updating 

models, and has not undertaken ongoing monitoring of state models.15 A 

recent Labor-commissioned survey revealed that many states have not

updated their profiling models in recent years.16 (See figs. 3 and 4.) For 

example, although 21 states reported taking actions such as adjusting 

variable weights since 2003, many others have not. Specifically, 18 states 

have not done so since 1999 or before, and 12 of these reported never 

having done so. 

Figure 3: States’ Adjustments of Model Coefficients 

0

5

10

15

20

25

Number of states

Source: GAO analysis of U.S. Department of Labor data.

Last update of model

1994-

1996

Never 1997-

1999

2000-

2002

2003-

2006

12

3 3

7

21

Note: Number of states and territories does not total 53 because 7 states did not respond to this 

query. 

 15The Unemployment Compensation Amendments of 1993 (Pub. L. No. 103-152) do not 

require this type of monitoring of state performance. 

16In 2004, Labor commissioned a study of state profiling models, the goals of which 

included determining the effectiveness of current models, and developing guidance on best 

practices in operating and maintaining worker profiling models. Labor conducted a survey

of states in 2006 and expects to publish this report in 2007. 

Page 17 GAO-07-680 Unemployment Insurance
According to Labor’s survey results, states have been even less inclined to

adjust their models by taking actions such as changing or redefining 

variables in the models. As figure 4 shows, 30 states reported that they had 

not made such changes since implementation, and 23 states reported 

having done so. Only 11 of these 23 states reported having done so since 

2003. 

Figure 4: Passage of Time since States Adjusted Models by Changing Variables 

0

5

10

15

20

25

30

35

Number of states

Source: GAO analysis of U.S. Department of Labor data.

Last update of model

1994-

1996

2000-

2001

2002-

2003

2004-

2006

30

4

8

11

Note: No states adjusted models between 1997 and 1999. 

Labor’s survey did not inquire about factors influencing the frequency with 

which states update their models, but our contacts with 7 states reveal a 

variety of reasons that some states have not updated their models. 

Officials in California said that they had more pressing priorities for UI 

administrative funds, and thus would have difficulty funding model 

updates. Wisconsin officials said that revising the models required 

expertise that they did not have, either in-house or from other sources, 

such as a state university. Although Labor provides technical guidance and 

advice, and has offered seminars on updating models, state officials 

indicated they still need more continuous access to expertise in order to 

keep models updated. A Texas official said that sometimes historical data 

needed to determine a variable’s impact on exhaustion of benefits are not 

available, and so the variable cannot be included in the model. Relatedly, if

Page 18 GAO-07-680 Unemployment Insurance
the necessary data on claimants are not collected, or cannot be

transmitted and used by the model, the related variable cannot be used. 

For example, a Texas official told us that certain variables, such as the 

number of a claimant’s dependents or spousal income, might be good 

predictive variables. However, the standard Texas application form for UI 

benefits does not ask about the number of dependents or spousal income,

so these variables cannot be used. 

Labor data provide a limited picture of states’ implementation of worker 

profiling, and some aspects of these data were not reliable. Further, 6 of 

our 7 study states did not offer the in-depth approach to services 

prescribed by Labor. These states generally referred claimants to services, 

held them accountable for attending the services, and provided them with 

an orientation and some instruction on job search skills. However, 6 of the 

7 states did not adhere to Labor’s guidance recommending an in-depth 

individual needs assessment and a tailored reemployment service plan for 

referred UI claimants. 

Between 2002 and 2006, about 94 percent of the UI claimants who received 

a first payment were profiled.17 To the extent that reemployment services 

are available, Labor requires that states refer profiled claimants to these 

services. Of those profiled, an average of 15 percent were referred to 

services, with states ranging from 5-year averages of 1 percent (Wyoming) 

to 52 percent (Washington) (See fig. 5.) While 3 states referred between 

29 and 52 percent of profiled claimants to services, 28 states referred 14 

percent or fewer. Further, of those claimants profiled, an average of 11 

percent completed services, with states ranging from 1 percent (Arkansas, 

Colorado, Idaho, Michigan, and Wyoming) to 39 percent (Texas). (See fig. 

6.)18 In 2 states, more than 27 percent of profiled claimants completed 

services. However, in 33 states, 13 percent or fewer of claimants did so. 

Most Study States Did 

Not Take the In-Depth 

Approach 

Recommended by 

Labor to Ensure That 

Profiled Claimants 

Obtain Reemployment 

Services 

Data Collected by Labor 

Provided a Limited Picture 

of States’ Implementation 

of Reemployment Services 

 17The total number of claimants profiled can exceed the total number of claimants who 

receive a first UI benefit payment because some states profile claimants at the initial claim, 

and these claimants may never receive a payment. 

18Labor collects these data from the states on Form ETA 9048, Worker Profiling and 

Reemployment Services Activity. Appendix I contains a description of how we derived

these summary statistics using the raw data from Labor. 

Page 19 GAO-07-680 Unemployment Insurance
See appendix II for the average percentages of profiled claimants referred 

to and completing services by state from 2002 to 2006. 

Figure 5: Percentage of Claimants Referred to Services, of Those Profiled

0

5

10

15

20

25

30

Number of states

Source: GAO analysis of U.S. Department of Labor data.

Percentage of profiled claimants referred to services

1-14 15-28 29-52

28

17

3

Page 20 GAO-07-680 Unemployment Insurance
Figure 6: Percentage of Claimants Completing Services, of Those Profiled 

0

5

10

15

20

25

30

35

Number of states

Source: GAO analysis of U.S. Department of Labor data.

Percentage of profiled claimants who completed services

1-13 14-26 27-39

33

13

2

Labor’s data are not sufficiently reliable to provide any information on the 

specific services provided to claimants—such as orientation, counseling, 

job search workshops, or job clubs. Specifically, Labor and state officials 

told us that definitions of these services can vary across states and within 

states over time as they change the content of their programs. For 

example, California officials told us that the state’s definitions of services 

provided were established over 10 years ago and that the nature of the 

services may have changed since then. 

Six of Seven States We

Studied Referred 

Claimants and Enforced 

Compliance with Referrals 

We found that 6 of the 7 study states had, as required by Labor, referred 

profiled claimants to services and made claimants ineligible for benefits if 

they failed to attend reemployment services. In contrast, officials in 1 state 

told us that referrals had been delegated to local workforce areas, and that 

they did not know whether claimants were being referred to services 

statewide. We subsequently contacted some local workforce development 

offices in this state and learned that several had not been referring UI 

profilees to reemployment services for years. In addition, officials in this 

state told us that there are no consequences for those who fail to attend 

reemployment services. They further said they do not track information at 

the state level on whether claimants attend services. While Labor requires

that states hold claimants ineligible for benefits for any week in which 

Page 21 GAO-07-680 Unemployment Insurance
they fail to attend services, Delaware goes further and holds the UI 

benefits of claimants who do not attend services until they reschedule. 

Some of the study states took additional steps to ensure compliance with

service referrals, while others did not. Of the states that referred claimants

to services, Delaware and Washington required that claimants reschedule

if they failed to attend required services, while Texas and Wisconsin 

attempted to reschedule claimants in some cases and the remaining states

did not do so.

 19 Officials in Delaware reported that they go so far as to 

have staff call claimants early during the week of their scheduled 

orientation to remind them to attend; officials in Washington said that 

some local workforce centers do this. Officials cited the large flow of 

claimants into the program, the complexity of the rescheduling process, 

and the scarcity of staff resources as reasons they did not reschedule 

referred claimants. 

Six of Seven States We

Studied Provided Limited 

Reemployment Services 

and Did Not Develop 

Individual Assessments 

and Service Plans 

The reemployment services offered in the states we contacted generally

did not conform to the robust service process originally outlined by Labor. 

Labor’s 1994 guidance states that after initial orientation, the service 

provider should determine the specific needs of each worker through an 

assessment process, such as vocational testing.20 Only one of our study 

states, Delaware, required that case managers conduct an initial 

assessment to determine what services claimants might need, such as 

Workforce Investment Act (WIA) training, depending on their job 

readiness level. Washington and Wisconsin required that claimants 

complete a self-assessment. For example, claimants at one one-stop center 

were expected to complete a one-page self-assessment that asks questions, 

including what educational level they attained, whether they had a current 

résumé, and whether they had difficulty filling out a job application. The 

4 other states we studied required no assessment of any kind.

According to state officials, our study states also generally did not require, 

as recommended by Labor, that local offices develop or document a 

reemployment services plan that could serve as the basis for determining 

satisfactory participation. Only Delaware required case managers to 

 19At the time of our contact, a Washington official said that the state sometimes 

rescheduled claimants for services, but that effective April 2, 2007, the state would require 

that claimants be rescheduled for services. 

20U.S. Department of Labor, Employment and Training Administration, Field Memorandum

No. 35-94, March 1994. 

Page 22 GAO-07-680 Unemployment Insurance
develop service plans and meet with claimants on a monthly basis after 

each claimant’s assessment. In California and Wisconsin, claimants 

developed their own plans, which involved selecting an additional service

session on a topic the claimants felt would be most helpful. For example, 

California required that UI claimants attend an orientation and choose an 

additional service, such as a WIA service or job club, that would constitute 

their individual reemployment plan.

All 7 study states cited lack of or declining funding as an issue that 

affected the provision of reemployment services. Specifically, some states 

mentioned the loss of Labor’s Reemployment Services grants, which had 

been awarded to all states between 2001 and 2005 to enhance and target 

integrated core services to claimants through the one-stop centers and 

were used by some states to fund program-related services. A Wisconsin 

official said that when the grant funds end in summer 2007, the state 

would only be providing worker profiling services in 6 to 12 of its 75 local 

workforce development offices. State officials also mentioned continuing

declines in Wagner-Peyser, or Employment Services, funding. A local 

workforce manager in Washington said that there is a vast gap between 

the need for services and the resources and that the state only has 

resources for about 5 percent of the 50,000 to 60,000 UI claimant 

population. In order to help address this issue, officials in Washington told 

us that a special surtax is applied to UI taxes, and a small portion of this is 

diverted to worker-profiling service activities. While state officials were 

concerned with the availability of funding, Labor officials said that the 

purpose of the worker-profiling initiative is to target the funding that does 

exist to those claimants who need it most and that the program does not 

mandate that states serve any claimants they did not serve prior to its 

implementation. 

Officials also cited various day-to-day challenges in providing effective 

reemployment services. A single services session can include claimants 

ranging from former upper management employees to construction and

factory production workers, according to a Kentucky official. The same 

official said that pitching the class so that it is effective for both types of 

claimants can be difficult. Claimants’ language skills also can be a 

challenge. However, California addresses this by excusing non-English 

speakers from the session, and directing them to job service centers or 

community-based partners that provide reemployment services in their 

own language, unless the orientation is available in their native language. 

Page 23 GAO-07-680 Unemployment Insurance
Little is known about the current effectiveness of the worker-profiling 

initiative. Research studies, while generally finding that profiling and a 

referral to services had a positive impact on claimants, used data from the 

early implementation of the initiative—1994 to 1996. Although Labor 

collects data on the outcomes of those profiled and referred to services, 

we found portions of it to be unreliable.21 In addition, state officials said 

they do not use Labor’s data for evaluation purposes. 

Five methodologically sound studies looking at the impacts of the workerprofiling initiative after it was first implemented found that the program 

had some desired effects. Examining data from 1994 to 1996, the studies 

generally indicated that a referral to services under worker profiling led to 

a reduction in claimants’ duration on UI, a reduction in the amount of UI 

benefits that were paid out, and an increase in subsequent employment 

earnings. Though the methodologies varied, all the studies evaluated the 

impacts of the referral to services using statistical analyses to compare the 

outcomes of claimants who were referred to services against those of 

claimants who were not.22 As table 3 indicates, these studies cover a total

of only 7 states, and no national study exists. Further, no study using 

current data exists. Labor sponsored the two multistate studies published 

in 1997 and 1999, but has not published any subsequent studies.23

According to Labor officials, the agency has no current plans to study the 

effects of profiling. Because data in all the studies were from the period 

when worker profiling was first implemented, the profiling process and 

Little Is Known about 

Program’s 

Effectiveness because 

There Are No Current 

Studies and Labor’s 

Data Are of Limited 

Usefulness 

Early Research Showed 

Some Positive Outcomes 

for Those Referred to 

Services, but There Are No 

Current Studies 

 21The claimant outcomes data are descriptive data only and do not indicate the effect of the 

worker-profiling program. Experimental and quasi-experimental research studies that 

evaluate the impact of the worker-profiling program may indicate how claimant outcomes 

differ due to program participation. 

22These studies controlled for a variety of factors such as location; profiling score; time 

period; personal characteristics, such as age, race, sex, and education; and employment 

characteristics, such as base period earnings, job tenure, industry, and previous 

occupation. 

23Texas, Washington, and Wisconsin officials said that state-sponsored impact studies 

conducted on various aspects of the worker-profiling initiative in their states were not 

complete or not yet published. California state officials conducted an impact evaluation 

study of worker profiling in the state, which was published in 2003, but the methodology 

was not sufficiently rigorous to include in our report. 

Page 24 GAO-07-680 Unemployment Insurance
reemployment services provided then may not reflect what states are 

currently offering.24

Table 3: Research Studies Included in Our Literature Review 

Research study Data: states and time framea 

Kentucky studies 

Black and others 2003 Kentucky, 1994-1996 

Black and others 2007 Kentucky, 1994-1996 

Noel 1998b Kentucky, 1994-1996 

Multistate studies 

Dickinson and others 

1997 

Delawarec, Kentucky, New Jersey, 1994-1995 

Dickinson and others 

1999 

Connecticut, Illinois, Kentucky, Maine, New Jersey, South 

Carolina, 1995-1996 

Source: GAO analysis of relevant studies. See bibliography for full citations. 

a

Dates indicate when claimants filed their UI claim or received their first UI benefit payment. 

b

Unpublished dissertation. 

c

Delaware was included in this study, but its sample size was too small to detect any significant

impacts. 

While these early studies showed positive impacts for referred claimants 

with regard to reducing duration, reducing amount of UI benefits, and 

increasing employment earnings, there were mixed results for whether the 

program reduced the percentage of claimants who exhausted their 

benefits or improved subsequent employment rates (See table 4.)25

According to the studies, claimants who were referred to services had a 

decreased UI duration and received lower total amounts of UI benefits.26

Most of the studies found that claimants who were referred to services 

increased earnings in the year following the UI claim. However, the largest 

multistate study was unable to draw any conclusions about the impact on 

 24The reemployment services received by claimants in these studies typically included an 

orientation and then on average between one and two additional services after orientation. 

25See appendix IV for more detailed information on the claimant outcome effects broken 

out by research study. 

26Typically, a claimant can receive a maximum of 26 weeks of regular UI benefits in a 

benefit year, though this duration can lengthen due to partial benefits receipt or federally 

funded extensions in periods of high unemployment rates. The amount of UI benefits 

received varies depending on a claimant’s previous employment earnings and state UI laws. 

Page 25 GAO-07-680 Unemployment Insurance
earnings because of contradictory data. Evidence that a referral to 

services reduced the percentage of claimants who exhausted their UI 

benefits was mixed. For example, one study showed a decrease in the 

percentage of claimants who exhausted their UI benefits in 3 states, but an 

increase in 2 states. The effect of a referral to services on employment 

rates was also inconclusive. According to the two multistate studies, the 

effect was minimally positive for one state, but the other 6 states showed 

insignificant or contradictory results. Most of the studies, however, did not 

examine subsequent employment rates. 

Table 4: Summary of Research Study Findings on the Effect of Referral to Services 

on Claimant Outcomes

Claimant outcome Range of effect found in research studies 

Duration of UI receipt Reduced by 0.2 to 4 weeks 

Amount of UI benefits received Reduced by $55 to $320 

Lessened likelihood of UI benefit 

exhaustion 

Inconclusive 

Earnings following UI claim Increased by $218 to $1,054a

Employment rates following UI claim Inconclusive 

Source: GAO analysis of relevant studies. 

a

Claimant earnings subsequent to the UI claim may be underreported because not all employers are 

covered by the UI system, and claimant earnings are not tracked if the claimant moves to another 

state. 

Research studies of other work search programs corroborate the generally

favorable results found in the impact evaluation studies of the workerprofiling initiative. 27 Though the methodologies varied, these studies 

demonstrated that work search assistance reduced the duration claimants 

received UI benefits, among other beneficial impacts. In two 

demonstration projects, UI claimants who received job search assistance 

received fewer weeks of UI benefits. The reemployment services offered 

in these demonstration projects, however, were more robust; for example, 

in one study, claimants were required to attend an orientation, testing, a 

 27The research studies include the following: D. H. Klepinger, T. R. Johnson, and J. M.

Joesch. “Effects of Unemployment Insurance Work-Search Requirements: The Maryland 

Experiment.” Industrial and Labor Relations Review, Vol. 56, No. 1. (October 2002), and 

P. T. Decker, R. B. Olsen, L. Freeman, and D. H. Klepinger. “Assisting Unemployment 

Insurance Claimants: The Long-Term Impacts of the Job Search Assistance 

Demonstration.” U.S. Department of Labor, Employment and Training Administration 

(February 2000). Both research studies used data from the mid-1990s. 

Page 26 GAO-07-680 Unemployment Insurance
job search workshop, and a one-on-one assessment interview. As such, 

they may not reflect what is offered through the states’ worker-profiling 

programs currently. 

Even though they were unable to provide supporting data, officials from 

our study states said that worker profiling was a useful program for UI 

claimants. They said it had enabled states to advertise their job search and

training services and target claimants who are most likely to exhaust their 

UI benefits. In the process of referring claimants to services, states are 

also educating the community on the many services and resources 

available at the one-stop service centers. They also said the initiative was a 

way to focus resources on those who would benefit from job search 

assistance the most. 

Outcomes Data Collected 

by Labor Are Limited and 

Not Consistently Used for 

Evaluation Purposes 

Due to reliability issues, Labor’s claimant outcomes data are of limited 

value. Labor’s claimant outcomes data28 were sufficiently reliable for us to 

report only certain outcomes, including benefits exhaustion, weeks of 

benefit receipt, and reemployment. 29 Those data showed that less than half 

of profiled claimants exhausted benefits, that on average they received 

benefits for about two-thirds of the typical maximum time allowed, and 

that about half found employment within 1 year of the referral to services 

(see table 5). 

 28Labor collects claimant outcomes data from the states on Form ETA 9049, Worker 

Profiling and Reemployment Services Outcomes.

29Three states and two territories were dropped from our analyses due to large amounts of

missing data. Also, as previously mentioned, we limited our analysis to data collected since

2002, as Labor instituted data edit checks that year. Despite the edit checks, we still found 

inaccuracies in the outcomes data collected since 2002. For example, seven states have 

been improperly reporting the claimants’ wage data based on Labor’s definition and 

relative to the rest of the states. To the extent possible, we estimated missing or incorrect

data. See appendix I for a detailed description of our methodology. 

Page 27 GAO-07-680 Unemployment Insurance
Table 5: National Averages and Ranges of State Averages on Outcomes for 

Claimants Profiled and Referred to Services, 2002 to 2005 

Claimant outcome National average Range of state averagesa

Claimants who exhausted their UI 

benefits 

40 percent 13 percent to 60 percent 

Number of weeks that claimants 

received UI benefitsb

17 weeks 7 to 27 weeks 

Claimants who found employment at 

some point during the year subsequent 

to the referral to services 

53 percent 22 percent to 87 percent 

Source: GAO analysis of U.S. Department of Labor data. 

Note: Data on claimant outcomes are for the four quarters after the referral to services or for the 

benefit year. See appendix I for a description of the methodology used to calculate national and state 

averages. 

a

Individual states averages were approximately evenly distributed around the national average. 

b

Typically, a claimant can receive a maximum of 26 weeks of regular UI benefits in a benefit year, 

though this duration can lengthen due to partial benefits receipt or federally funded extensions in 

periods of high unemployment rates. 

In addition to reliability issues, other characteristics, such as the lack of a 

comparison group and long time lags, limit the usefulness of both the 

reemployment services data and claimant outcomes data for states. First, 

the outcomes data reflected only the experience of those who were 

referred to services, and did not include an adequate point of comparison. 

It was therefore impossible to know if these outcomes were different than

they would have been had the claimants not been referred to or completed 

reemployment services.30 Second, according to Labor officials, the data 

were originally intended for states to evaluate the effectiveness of the 

worker-profiling initiative. However, we found that neither Labor nor the 

states used the data for this purpose.31 Several state officials said the time 

lag and aggregated nature of the data were insufficient for program 

management purposes. The claimant outcomes data were not reported for 

 30Data for all UI claimants, which would include those profiled and referred to services, 

show that between 2002 and 2005, on average claimants received 16 weeks of benefits and 

41 percent of claimants exhausted benefits. According to a Labor official, in 2007, the

Department of Labor began collecting data on the percentage of all UI claimants who find 

employment, and not all states have submitted the data. 

31Labor officials said they made limited use of the data. For example, Labor used the data 

to verify that states comply with the statutory requirements to profile and refer claimants, 

and they have used the data for special project needs that have not included evaluating the 

effectiveness of profiling and reemployment services. 

Page 28 GAO-07-680 Unemployment Insurance
more than a year after claimants were referred to services, and some state 

officials said they needed more timely data. Both the reemployment 

services and claimant outcomes data were aggregated to the state level, 

and some state officials said that local-level data would better meet their 

management needs. Four of our seven study states indicated that they did 

not utilize the reemployment services data or claimant outcomes data, and 

some only reported them because it was required by Labor; the remaining 

states said they used the reemployment services data for nonevaluative 

purposes, such as determining how many services were provided to 

claimants or the volume of claimants served under the worker-profiling 

program. 

In light of these data limitations, several state officials said they developed 

their own program performance measures and reports instead of using the 

reemployment services data and claimant outcomes data. For example, 

Washington developed its own data warehouse system that links data on 

UI benefits, reemployment services, and claimant wages. According to 

officials, on a monthly basis they review performance indicators, such as 

the number of UI claimants that find employment and the amount of time 

it takes before finding employment.32

Our findings suggest that although states continue to profile and refer 

claimants to reemployment services, the worker-profiling initiative is not a 

high priority at the federal level or in many states. In the past Labor has set 

out broad guidelines for states on the design and maintenance of profiling 

models. However, our analyses indicate that these have been inadequate. 

Labor’s 2006 survey of state profiling techniques revealed that many states 

had not updated their profiling models for many years. As a result, it is 

possible that many models have lost predictive accuracy, and are referring

claimants to services who are not in need of them, or failing to refer 

claimants that are in need of them. However, the worker-profiling program 

is required by law, and if there is to be a continued federal mandate, it may 

be that a more assertive federal role is necessary to ensure the integrity of 

those models. 

Conclusions 

A long time has passed since Labor articulated its vision of reemployment 

services, and our review of seven states indicates that what is being 

 32These performance indicators are for all UI claimants, not just the claimants that are

profiled and referred to services under the worker-profiling program.

Page 29 GAO-07-680 Unemployment Insurance
practiced is a diminished version of that vision. While the states we 

studied indicated they provided orientation sessions that seemed to 

convey important information, including job search skills, Labor’s 

guidance implies a more tailored and in-depth approach to services. It may 

be that the original vision is no longer realistic or perhaps, in the states’ 

experience, necessary. Absent clarification at the federal level, it will 

remain unclear what Labor expects from the states. 

The national data on the worker-profiling initiative is of very limited 

usefulness as a measure of program activity, outcomes, and effectiveness. 

Many of the data are not usable because of inconsistent or incorrect 

reporting, and neither Labor nor the states we contacted use the data for 

evaluating the worker-profiling initiative. Further, even if all the outcomes 

data were reported consistently and accurately, these data cannot, by 

themselves, be used to measure the impact of the program. In the end, by

requiring the submittal of data that are of such limited reliability and value, 

Labor is potentially wasting both its own and the states’ resources. Finally, 

absent information about the program’s current impact, Labor may find it 

more difficult to make decisions regarding the best means for returning 

the unemployed to work more quickly. 

To better ensure that claimants who need and could benefit from 

reemployment services are referred, and to ensure that resources are not 

unnecessarily expended on claimants not needing them, we recommend 

that the Secretary of Labor: 

Recommendations for 

Executive Action 

1. Reevaluate the agency’s worker-profiling data collection to 

determine whether it is sufficient for its intended purpose. The 

agency might assess gaps in data, evaluate data consistency, confer 

with states on what data would be beneficial to them, determine 

the purpose of the data collection and for whose benefit the data 

are collected, and modify what Labor requires states to collect. 

2. Ensure that the Employment and Training Administration takes a 

more active role to help ensure the accuracy of the state profiling 

models. The agency might track states’ management of their 

models and actively encourage review and updating of models in 

specific states where there have been no efforts to adjust the 

model for a number of years. The agency could also assess whether 

an expanded technical assistance effort is needed, and, if so, take 

the lead in developing one. 

Page 30 GAO-07-680 Unemployment Insurance
3. Encourage states to adhere to Labor’s vision for in-depth 

reemployment services, such as conducting individualized needs 

assessments and developing individual service plans, or issue 

updated guidance if this original vision would be too burdensome 

for the states. 

4. Evaluate the impact of the worker-profiling program on the 

reemployment of UI recipients to ensure the benefits are 

commensurate with the resources invested. 

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

general, Labor agreed with our findings and recommendations. Labor’s 

formal comments are reproduced in appendix V.

Labor also provided technical comments on the draft report, which we 

have incorporated where appropriate. 

We are sending copies of the report to interested congressional 

committees and members, and the Secretary of Labor. We will also make 

copies available to others upon request. In addition, our report will be 

available at no charge on GAO’s Web site at http://www.gao.gov. 

Agency Comments 

A list of related GAO products is included at the end of the report. If you 

or your staff has any questions about this report, please contact me at 

(202) 512-7215. You may also reach me by e-mail at nilsens@gao.gov. Key 

contributors to this report are listed in appendix VI. 

Sigurd R. Nilsen 

Director, Education, Workforce, 

and Income Security Issues 

Page 31 GAO-07-680 Unemployment Insurance
Appendix I: Objectives, Scope, and Appendix I: Objectives, Scope, and Methodology 

Methodology 

Our objectives were to answer the following questions: 

1. How do states identify unemployment claimants who are most 

likely to exhaust benefits? 

2. To what extent do states provide reemployment services as 

recommended by Labor? 

3. What is known about the effectiveness of the worker-profiling 

initiative in accelerating the reemployment of unemployment 

insurance claimants? 

To answer the first question, we reviewed Labor’s guidance about the 

worker-profiling initiative, and reviewed literature and interviewed 

experts with the Department of Labor and the Upjohn Institute for 

Employment Research regarding profiling techniques. We also obtained 

and analyzed the results of a 2006 Department of Labor-sponsored survey 

of the 53 states and territories.1

 This survey made numerous inquiries 

about the structural and operational aspects of the profiling tools—such 

as statistical models or characteristic screens—in use in the states. Finally,

we contacted officials in 7 states—California, Delaware, Illinois, Kentucky, 

Texas, Washington, and Wisconsin. We selected some states to ensure that 

we included certain aspects of worker profiling; for example, we selected 

Kentucky because it had a very complex statistical model with numerous 

variables, and we selected Delaware because it was one of the few states 

that profiled claimants using a characteristic screen instead of a statistical 

model. We also selected these states because they ensured geographic 

dispersion and a range of populations sizes. In each of these states, we 

reviewed documents describing the profiling model that the state uses, 

and interviewed knowledgeable officials about the variables used in the 

model, the degree to which the model has been assessed and updated, and 

other matters. 

To answer the second question, we reviewed Labor guidance regarding 

reemployment services provided to Unemployment Insurance (UI) 

claimants referred through the worker-profiling initiative, and obtained 

and analyzed national data collected by the Department of Labor from 

states on the Employment and Training Administration (ETA) 9048 

Worker Profiling and Reemployment Services Activity report. In this 

 1

The survey, which resulted in a 100 percent response rate, encompassed the 50 states, as 

well as the District of Columbia, Puerto Rico, and the Virgin Islands. 

Page 32 GAO-07-680 Unemployment Insurance
Appendix I: Objectives, Scope, and 

Methodology 

report, states submit to Labor, by quarter, information such as the number 

of UI claimants profiled, referred to services, and completing services.2

During our contacts with the 7 states mentioned above, we also obtained 

and reviewed state documents describing policies about referral and 

reemployment services for claimants profiled under the worker-profiling 

initiative. We also interviewed knowledgeable state officials about these 

policies, including referral and notification of claimants, enforcement of 

participation requirements, and the type of reemployment services that are 

offered to claimants. In 6 of these states, we also contacted officials at 

local one-stop offices or regional offices to discuss how reemployment 

services are managed and delivered. In 4 of these states, we also attended

the initial reemployment services session for claimants referred through 

the worker-profiling initiative and recorded our observations on a 

standard template. 

To answer the third question, we identified and reviewed six research 

studies that evaluated the impact of profiling and the referral to services 

on claimant outcomes. All the studies used regression techniques to 

estimate the impact of a referral to services on a claimant’s UI claims 

experience or the subsequent earnings and employment activities.3

 A GAO 

economist reviewed these studies and determined whether each study's 

findings were generally reliable by evaluating the methodological 

soundness of the studies and validity of the results and conclusions that 

were drawn. On the basis of this assessment, we determined that five of

the six studies were methodologically rigorous enough to use in this 

report. We confirmed with Labor and national experts on unemployment 

insurance that these remaining five studies constituted the definitive work 

done to date on the impact of the worker-profiling initiative. Additionally, 

we reviewed these studies to assess the reemployment services offered 

under the worker-profiling initiative. Finally, we reviewed several studies

on other work search programs that also evaluated impacts on claimant 

outcomes. We also obtained and analyzed national data collected by Labor 

from states via the ETA 9049 Worker Profiling and Reemployment Services 

Outcomes report.4

 In this report, states report to Labor on a quarterly basis 

information on the outcomes of referred claimants, such as the average 

 2

Data are reported for the quarter in which the activity occurred. 

3

One study used a Wald estimator, a simple nonparametric regression. 

4

All outcomes data were analyzed with respect to the cohort of claimants referred to 

services in a report quarter rather than at the individual claimant level. The date of the 

outcomes data is the quarter when the claimants were referred to services. 

Page 33 GAO-07-680 Unemployment Insurance
Appendix I: Objectives, Scope, and 

Methodology 

duration claimants received UI benefits and the number of claimants that 

found employment in the year following referral. Finally, in our contacts 

with the 7 states mentioned above, we interviewed knowledgeable

officials regarding the data collected by Labor and their general views 

about the worker-profiling initiative, and in particular whether they 

believed the initiative was having the intended outcomes. 

We conducted a data reliability assessment on the ETA 9048 and ETA 9049 

reports data, which included electronically checking the data and 

interviewing Labor and state officials on the reliability of the data. On the 

basis of our reliability assessment and interviews, we found that some of 

the ETA 9048 and ETA 9049 reports had missing or inaccurate data. As a 

result, we took the following actions to ensure the accuracy of the data. 

First, because Labor instituted data edit checks starting in 2002, we limited 

the time frame of our analysis to 2002 to the most recent available, 

September 2006 and March 2005 for the ETA 9048 and ETA 9049, 

respectively. Second, we disregarded data from states that had excessive 

amounts of missing data reports. Specifically, from the ETA 9048, we 

excluded Louisiana, New Mexico, Puerto Rico, and the Virgin Islands, and 

for the ETA 9049, we also excluded Idaho and New Jersey, in addition to 

those states dropped for the ETA 9048.5

 Third, we estimated data values, if 

possible, for states that had sporadically missing reports or data that were

anomalous or illogical, for example, when the number of claimants who 

found employment exceeded the number referred to services. Of the data 

we reported from the ETA 9048 and ETA 9049, we estimated 

approximately 1 percent of these data; because of this small proportion, 

we believe that any errors arising from our estimation process did not 

significantly affect the state and national averages we reported. Some 

possible issues resulting from our estimation process were the following: 

• We utilized logical relationships between data to estimate values, 

and at times, these values were based on other estimated data. Any 

errors resulting from the previous estimation would be carried over 

to the following estimated value. 

• Some states had volatile data, and as our estimation process was 

based on the existing state data, it is uncertain how accurate our 

estimates were. 

 5

Two of the three outcomes data we report for the ETA 9049 are calculated using data from 

the ETA 9048, and hence states dropped for the ETA 9048 also were dropped for the ETA 

9049. 

Page 34 GAO-07-680 Unemployment Insurance
Appendix I: Objectives, Scope, and 

Methodology 

• At times, our estimated values were the highest or the lowest in the 

data series, and it is possible that the estimation procedure resulted 

in an inaccurate value. 

Fourth, we excluded data from states that we confirmed were reported 

incorrectly. Specifically, for the ETA 9049, California and Georgia were 

excluded from calculations using the number of claimants who become 

employed, and Illinois was dropped from all analyses of both the ETA 9048 

and ETA 9049 data. Last, we did not use any of the detailed reemployment 

services data, such as the number of claimants that completed an 

orientation, assessment, and so forth, because both Labor and state 

officials said these data were not comparable within and between states. 

Page 35 GAO-07-680 Unemployment Insurance
Appendix II: Average Percentage of Claimants

Profiled, Referred to, and Completing 

Services for 2002-2006 and Average Claimant 

Outcomes for 2002-2005, by State 

State 

Claimants 

receiving first 

UI benefit 

payment who 

were profiled

(2002-2006) 

Profiled 

claimants 

referred to

services 

(2002-2006) 

Profiled 

claimants who 

completed

services 

(2002-2006)

Referred

claimants 

who exhaust

UI benefits

(2002-2005)

Referred

claimants 

who become

employed

(2002-2005) 

Length of 

time referred

claimants receive 

UI benefits

(weeks) (2002-

2005)

Ala. 102% 3% 3% 47% 56% 18.3

Alaska 89% 8% 5% 42% 60% 14.2

Ariz. 86% 16% 9% 37% 51% 14.6

Ark. 95% 2% 1% 46% 38% 21.0

Calif. 59% 14% 7% 32% Not available 21.3

Colo. 100% 2% 1% 45% 58% 16.3

Conn. 82% 13% 8% 47% 58% 17.7

Del. 162% 4% 3% 58% 87% 20.6

D.C. 93% 6% 4% 57% 52% 20.7

Fla. 90% 36% 21% 29% 29% 27.0

Ga. 74% 25% 24% 49% Not available 15.6

Hawaii 94% 11% 7% 40% 60% 18.2

Idaho 114% 2% 1% Not available Not available Not available

Ind. 97% 8% 5% 57% 61% 13.3

Iowa 37% 21% 13% 39% 58% 18.9

Kan. 71% 6% 6% 60% 52% 12.8

Ky. 136% 13% 10% 43% 50% 18.1

Maine 100% 18% 11% 40% 64% 15.1

Md. 100% 24% 12% 51% 43% 20.9

Mass. 100% 26% 20% 53% 48% 20.2

Mich. 95% 2% 1% 36% 55% 17.0

Minn. 114% 21% 19% 39% 59% 17.5

Miss. 115% 22% 13% 44% 59% 16.0

Mo. 73% 8% 6% 51% 56% 16.6

Mont. 171% 4% 3% 53% 64% 7.4

Neb. 22% 28% 24% 31% 85% 16.1

Nev. 96% 4% 3% 31% 46% 7.3

N.H. 112% 26% 26% 13% 74% 15.7

N.J. 86% 14% 14% Not available Not available Not available

N.Y. 93% 12% 11% 60% 52% 20.9

N.C. 37% 12% 7% 18% 22% 20.1

N.D. 123% 20% 15% 18% 70% 7.8

Appendix II: Average Percentage of Claimants 

Profiled, Referred to, and Completing Services 

for 2002-2006 and Average Claimant Outcomes 

for 2002-2005, by State

Page 36 GAO-07-680 Unemployment Insurance
Appendix II: Average Percentage of Claimants

Profiled, Referred to, and Completing 

Services for 2002-2006 and Average Claimant 

Outcomes for 2002-2005, by State 

State 

Claimants 

receiving first 

UI benefit 

payment who 

were profiled

(2002-2006) 

Profiled 

claimants 

referred to

services 

(2002-2006) 

Profiled 

claimants who 

completed

services 

(2002-2006)

Referred

claimants 

who exhaust

UI benefits

(2002-2005)

Referred

claimants 

who become

employed

(2002-2005) 

Length of 

time referred

claimants receive 

UI benefits

(weeks) (2002-

2005)

Ohio 94% 13% 7% 21% 62% 21.0

Okla. 115% 27% 23% 48% 51% 18.5

Ore. 74% 13% 9% 42% 45% 24.0

Pa. 96% 15% 10% 30% 28% 22.7

R.I. 74% 20% 18% 48% 43% 18.0

S.C. 73% 21% 14% 37% 52% 10.2

S.D. 86% 7% 6% 26% 55% 13.8

Tenn. 80% 10% 8% 35% 40% 21.2

Tex. 89% 49% 39% 39% 39% 17.8

Utah 94% 26% 24% 45% 38% 15.0

Vt. 99% 7% 5% 22% 48% 17.2

Va. 55% 12% 7% 31% 31% 24.2

Wash. 116% 52% 38% 26% 65% 14.8

W.Va. 122% 21% 18% 45% 54% 19.7

Wis. 104% 8% 7% 44% 55% 16.7

Wyo. 115% 1% 1% 43% 47% 15.4

National 

Average 

94% 15% 11% 40% 53% 17.3

Source: GAO analyses of Labor data, 2002-2006. 

a

GAO analysis based on 47 states and the District of Columbia. 

Notes: For the percentages profiled, referred to services, and completed services, Illinois, Louisiana, 

New Mexico, Puerto Rico, and the Virgin Islands were excluded because of reliability concerns or

missing data. For the percentage exhausted, percentage employed, and length of UI benefits 

received, Idaho and New Jersey were also excluded due to missing data. California and Georgia 

were excluded only from the percentage employed averages due to reliability concerns. See 

appendix I for further detail. 

Page 37 GAO-07-680 Unemployment Insurance
Appendix III: Bibliography of Research

Studies on the Worker-Profiling Initiative—

Exhaustive List Identified from the Literature 

Review

Appendix III: Bibliography of Research 

Studies on the Worker-Profiling Initiative—

Exhaustive List Identified from the Literature 

Review 

Black, Dan A., Jeffrey A. Smith, Mark C. Berger, and Brett J. Noel. “Is the 

Threat of Reemployment Services More Effective than the Services 

Themselves? Evidence from Random Assignment in the UI System.” The 

American Economic Review, Vol. 93, No. 4 (November 2003). 

Black, Dan A., Jose Galdo, and Jeffrey A. Smith. “Evaluating the Worker 

Profiling and Reemployment Services System Using a Regression 

Discontinuity Approach.” Paper presented at the American Economic 

Association conference in January 2007. Submitted to The American 

Economic Review for the May 2007 Papers and Proceedings Issue. 

Dickinson, Katherine P., Suzanne D. Kreutzer, and Paul T. Decker. 

“Evaluation of Worker Profiling and Reemployment Services Systems: 

Report to Congress.” U.S. Department of Labor, Employment and Training 

Administration (March 1997). 

Dickinson, Katherine P., Suzanne D. Kreutzer, Richard W. West, and Paul 

T. Decker. “Evaluation of Worker Profiling and Reemployment Services: 

Final Report.” U.S. Department of Labor, Employment and Training 

Administration Research and Evaluation Report Series 99-D (1999). 

Noel, Brett J. “Two Essays on Unemployment Insurance: Claimant 

Responses to Policy Changes.” Dissertation submitted for the degree of 

Doctor of Philosophy at the Graduate School of the University of 

Kentucky, UMI Number: 9922624 (1998). 

Page 38 GAO-07-680 Unemployment Insurance
Appendix IV: Summary of the Impact of 

Referral to Services on Claimant Outcomes Appendix IV from the Literature Review : Summary of the Impact of 

Referral to Services on Claimant Outcomes 

from the Literature Review 

Research

study Dataa

 

Duration of 

UI receipt

Amount of UI 

benefits 

Benefit 

exhaustion rate 

Earnings

following UI 

claimb

Employment rate

following UI claim

Kentucky studies 

Black and 

others 2003 

KY, 

1994-1996 

Reduced by 

2.2 weeks 

Reduced by $143cNot significant Increased by 

$1,054 in the year 

following UI claim 

Not available 

Black and 

others 2007 

KY, 

1994-1996 

Reduced by 

0.4 to 2.3 

weeks 

Inconsistent 

resultsd

Not available Increased by 

$648 to $1,054 in 

the year following 

UI claim 

Not available 

Noel 1998eKY, 

1994-1996 

Reduced by 

2.2 to 4 weeks

Reduced by 

$65 to $320 

Not available Increased by 

$218 to $1,054 in 

the year following 

UI claim 

Not available 

Multi-state studies 

Dickinson and 

others 1997 

DEf, KY, NJ, 

1994-1995 

KY, NJ: 

Reduced by 

0.6 to 0.7 

weeks 

KY, NJ: Reduced 

by $96 to $109

NJ: Reduced by

4 percentage 

points 

NJ: Increased by 

$190 and $226 in 

the first and 

second quarters, 

respectively 

NJ: Increased by 1 

percentage point

c

in first quarter 

Dickinson and 

others 1999 

CT, IL, KY, ME, 

NJ, SC, 

1995-1996 

CT, IL, KY,

ME, NJ: 

Reduced by 

0.2c

 to 1 week 

CT, IL, ME, NJ: 

Reduced by 

$55c

 to $139 

CT, ME, NJ:

Reduced by 

1.4 to 4.3 

percentage 

points SC, KY: 

Increased by 

1.1c

 to 4.1 

percentage 

points 

Inconsistent 

results 

Inconsistent results

Source: GAO analysis from literature review. See bibliography for full citations. 

Note: Only results significant at the 95 percent confidence level are included unless otherwise noted.

a

Dates indicate when claimants filed their UI claim or received their first UI benefit payment. 

b

The earnings may be underreported because not all employers are covered by the UI system, and 

claimant earnings are not tracked if the claimant moves to another state. 

c

Significant at the 90 percent confidence level. 

d

The results with the least likelihood of error show a reduction in the amount of UI benefits received of 

$175. 

e

Unpublished dissertation. 

f

Delaware was included in this study, but its sample size was too small to detect any significant

impacts. 

Page 39 GAO-07-680 Unemployment Insurance
Appendix V: Comments from the Department Appendix V of Labor : Comments from the Department 

of Labor 

Page 40 GAO-07-680 Unemployment Insurance
Appendix V: Comments from the Department 

of Labor 

Page 41 GAO-07-680 Unemployment Insurance
Appendix VI: 

A

GAO Contacts and 

cknowledgments 

Page 42 GAO-07-680

Appendix VI: GAO Contacts and 

Acknowledgments 

Sigurd Nilsen, Director, (202) 512-7215 or nilsens@gao.gov 

Patrick di Battista, Assistant Director, and Michael Hartnett, managed this

engagement.

Shannon Groff, Rosemary Torres Lerma, and Winchee Lin also made 

significant contributions throughout the engagement. Susan Bernstein 

helped develop the report’s message. Jay Smale, Stuart Kaufman, 

Rhiannon Patterson, Robert Dinkelmeyer, and Greg Dybalski contributed 

to the analysis of Labor data and reviews of external studies. Jessica 

Botsford provided legal support. 

GAO Contact 

Staff 

Acknowledgments 

Unemployment Insurance
Related GAO Products Related GAO Products 

Workforce Investment Act: Employers Found One-Stop Centers Useful in

Hiring Low-Skilled Workers; Performance Information Could Help 

Gauge Employer Involvement. GAO-07-167. Washington, D.C.: December 

22, 2006. 

Unemployment Insurance: States’ Tax Financing Systems Allow Costs to 

Be Shared among Industries. GAO-06-769. Washington, D.C.: July 26, 

2006. 

Unemployment Insurance: Enhancing Program Performance by 

Focusing on Improper Payments and Reemployment Services. 

GAO-06-696T. Washington, D.C.: May 4, 2006. 

Unemployment Insurance: Factors Associated with Benefit Receipt and

Linkages with Reemployment Services for Claimants. GAO-06-484T. 

Washington, D.C.: March, 15, 2006. 

Unemployment Insurance: Factors Associated with Benefit Receipt.

GAO-06-341. Washington, D.C.: March 7, 2006. 

Workforce Investment Act: Labor and States Have Taken Actions to 

Improve Data Quality, but Additional Steps Are Needed. GAO-06-82. 

Washington, D.C.: November 14, 2005. 

Unemployment Insurance: Better Data Needed to Assess Reemployment 

Services to Claimants. GAO-05-413. Washington, D.C.: June 24, 2005. 

Workforce Investment Act: Labor Should Consider Alternative 

Approaches to Implement New Performance and Reporting 

Requirements. GAO-05-539. Washington, D.C.: May 27, 2005. 

Unemployment Insurance: Information on Benefit Receipt. GAO-05-291. 

Washington, D.C. March 17, 2005. 

Workforce Investment Act: Employers Are Aware of, Using, and Satisfied

with One-Stop Services, but More Data Could Help Labor Better Address 

Employers’ Needs. GAO-05-259. Washington, D.C.: February 18, 2005. 

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. 

Page 43 GAO-07-680 Unemployment Insurance
Related GAO Products 

Workforce Investment Act: One-Stop Centers Implemented Strategies to 

Strengthen Services and Partnerships, but More Research and 

Information Sharing Is Needed. GAO-03-725. Washington, D.C.: June 

18, 2003. 

(130587) 

Page 44 GAO-07-680 Unemployment Insurance
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